Question: what are the mortality rates overall and in specific populations

Title: Global, regional, and national under-5 mortality, adult mortality, age-specific mortality, and life expectancy, 1970-2016: a systematic analysis for the Global Burden of Disease Study 2016. Content: BACKGROUND Detailed assessments of mortality patterns, particularly age-specific mortality, represent a crucial input that enables health systems to target interventions to specific populations. Understanding how all-cause mortality has changed with respect to development status can identify exemplars for best practice. To accomplish this, the Global Burden of Diseases, Injuries, and Risk Factors Study 2016 (GBD 2016) estimated age-specific and sex-specific all-cause mortality between 1970 and 2016 for 195 countries and territories and at the subnational level for the five countries with a population greater than 200 million in 2016. METHODS We have evaluated how well civil registration systems captured deaths using a set of demographic methods called death distribution methods for adults and from consideration of survey and census data for children younger than 5 years. We generated an overall assessment of completeness of registration of deaths by dividing registered deaths in each location-year by our estimate of all-age deaths generated from our overall estimation process. For 163 locations, including subnational units in countries with a population greater than 200 million with complete vital registration (VR) systems, our estimates were largely driven by the observed data, with corrections for small fluctuations in numbers and estimation for recent years where there were lags in data reporting (lags were variable by location, generally between 1 year and 6 years). For other locations, we took advantage of different data sources available to measure under-5 mortality rates (U5MR) using complete birth histories, summary birth histories, and incomplete VR with adjustments; we measured adult mortality rate (the probability of death in individuals aged 15-60 years) using adjusted incomplete VR, sibling histories, and household death recall. We used the U5MR and adult mortality rate, together with crude death rate due to HIV in the GBD model life table system, to estimate age-specific and sex-specific death rates for each location-year. Using various international databases, we identified fatal discontinuities, which we defined as increases in the death rate of more than one death per million, resulting from conflict and terrorism, natural disasters, major transport or technological accidents, and a subset of epidemic infectious diseases; these were added to estimates in the relevant years. In 47 countries with an identified peak adult prevalence for HIV/AIDS of more than 0·5% and where VR systems were less than 65% complete, we informed our estimates of age-sex-specific mortality using the Estimation and Projection Package (EPP)-Spectrum model fitted to national HIV/AIDS prevalence surveys and antenatal clinic serosurveillance systems. We estimated stillbirths, early neonatal, late neonatal, and childhood mortality using both survey and VR data in spatiotemporal Gaussian process regression models. We estimated abridged life tables for all location-years using age-specific death rates. We grouped locations into development quintiles based on the Socio-demographic Index (SDI) and analysed mortality trends by quintile. Using spline regression, we estimated the expected mortality rate for each age-sex group as a function of SDI. We identified countries with higher life expectancy than expected by comparing observed life expectancy to anticipated life expectancy on the basis of development status alone. FINDINGS Completeness in the registration of deaths increased from 28% in 1970 to a peak of 45% in 2013; completeness was lower after 2013 because of lags in reporting. Total deaths in children younger than 5 years decreased from 1970 to 2016, and slower decreases occurred at ages 5-24 years. By contrast, numbers of adult deaths increased in each 5-year age bracket above the age of 25 years. The distribution of annualised rates of change in age-specific mortality rate differed over the period 2000 to 2016 compared with earlier decades: increasing annualised rates of change were less frequent, although rising annualised rates of change still occurred in some locations, particularly for adolescent and younger adult age groups. Rates of stillbirths and under-5 mortality both decreased globally from 1970. Evidence for global convergence of death rates was mixed; although the absolute difference between age-standardised death rates narrowed between countries at the lowest and highest levels of SDI, the ratio of these death rates-a measure of relative inequality-increased slightly. There was a strong shift between 1970 and 2016 toward higher life expectancy, most noticeably at higher levels of SDI. Among countries with populations greater than 1 million in 2016, life expectancy at birth was highest for women in Japan, at 86·9 years (95% UI 86·7-87·2), and for men in Singapore, at 81·3 years (78·8-83·7) in 2016. Male life expectancy was generally lower than female life expectancy between 1970 and 2016, and the gap between male and female life expectancy increased with progression to higher levels of SDI. Some countries with exceptional health performance in 1990 in terms of the difference in observed to expected life expectancy at birth had slower progress on the same measure in 2016. INTERPRETATION Globally, mortality rates have decreased across all age groups over the past five decades, with the largest improvements occurring among children younger than 5 years. However, at the national level, considerable heterogeneity remains in terms of both level and rate of changes in age-specific mortality; increases in mortality for certain age groups occurred in some locations. We found evidence that the absolute gap between countries in age-specific death rates has declined, although the relative gap for some age-sex groups increased. Countries that now lead in terms of having higher observed life expectancy than that expected on the basis of development alone, or locations that have either increased this advantage or rapidly decreased the deficit from expected levels, could provide insight into the means to accelerate progress in nations where progress has stalled. FUNDING Bill & Melinda Gates Foundation, and the National Institute on Aging and the National Institute of Mental Health of the National Institutes of Health.

Title: Why Do COVID-19 Fatality Rates Differ Across Countries? An Explorative Cross-country Study Based on Select Indicators Content: In this article, we analyse the factors that determine the fatality rates across 29 economies spread across both the developing and developed world. Recent emerging literature and expert opinions in popular media have indicated various factors that may explain cross-country difference in fatality rates. These factors range from access to public health infrastructure, BCG vaccination policies, demographic structure, restrictive policy interventions and the weather. In addition, articles are examining different kinds of fatality rates that can be explained. Progressing beyond fragmented databases and anecdotal evidence, we have developed a database for such factors, have explored various econometric models to test the explanatory power of these factors in explaining several kinds of fatality rates. Based on available data, our study reveals that factors such as public health system, population age structure, poverty level and BCG vaccination are powerful contributory factors in determining fatality rates. Interactions between factors such as poverty level and BCG vaccination provide interesting insights into the complex interplay of factors. Our analysis suggests that poor citizens’ access to the public healthcare system are worse in many countries irrespective of whether they are developed or developing countries.

Title: Non‐parametric estimation of the case fatality ratio with competing risks data: an application to Severe Acute Respiratory Syndrome (SARS) Content: For diseases with some level of associated mortality, the case fatality ratio measures the proportion of diseased individuals who die from the disease. In principle, it is straightforward to estimate this quantity from individual follow‐up data that provides times from onset to death or recovery. In particular, in a competing risks context, the case fatality ratio is defined by the limiting value of the sub‐distribution function, F (1)(t) = Pr(T ⩽t and J = 1), associated with death, as t → ∞, where T denotes the time from onset to death (J = 1) or recovery (J = 2). When censoring is present, however, estimation of F (1)(∞) is complicated by the possibility of little information regarding the right tail of F (1), requiring use of estimators of F (1)(t(*)) or F (1)(t (*))/(F (1)(t (*))+F (2)(t (*))) where t (*) is large, with F (2)(t) = Pr(T ⩽t and J = 2) being the analogous sub‐distribution function associated with recovery. With right censored data, the variability of such estimators increases as t (*) increases, suggesting the possibility of using estimators at lower values of t (*) where bias may be increased but overall mean squared error be smaller. These issues are investigated here for non‐parametric estimators of F (1) and F (2). The ideas are illustrated on case fatality data for individuals infected with Severe Acute Respiratory Syndrome (SARS) in Hong Kong in 2003. Copyright © 2006 John Wiley & Sons, Ltd.

Title: Simple Compartmental Models for Disease Transmission Content: Communicable diseases that are endemic (always present in a population ) cause many deaths). For example, in 2011 tuberculosis caused an estimated 1,400,000 deaths and HIV/AIDS caused an estimated 1,200,000 deaths worldwide. According to the World Health Organization there were 627,000 deaths caused by malaria, but other estimates put the number of malaria deaths at 1,2000,000. Measles, which is easily treated in the developed world, caused 160,000 deaths in 2011, but in 1980 there were 2,600,000 measles deaths. The striking reduction in measles deaths is due to the availability of a measles vaccine. Other diseases such as typhus, cholera, schistosomiasis, and sleeping sickness are endemic in many parts of the world. The effects of high disease mortality on mean life span and of disease debilitation and mortality on the economy in afflicted countries are considerable. Most of these disease deaths are in less developed countries, especially in Africa, where endemic diseases are a huge barrier to development.

Title: On case-fatality rate: review and hypothesis. Content: The relationship between log cumulative number of patients (X) and that of deaths (Y) in an epidemic follows the equation logY = klogX - klogN(0), where k is a constant determining the slope and N(0) is the value of X when Y = 1. Diseases with k = 1 are Ebola hemorrhagic fever, avian influenza H5N1, cholera, and hand, foot, and mouth disease; those with k > 1 are the influenza H1N1 2009 pandemic in countries other than Mexico and the SARS epidemic in some countries; and those with k < 1 include the influenza H1N1 2009 pandemic in Mexico. Epidemics with k > 1 can be simulated by postulating two subpopulations (normal population [NP] and vulnerable population [VP]), where the epidemic proceeds at higher speed and at higher mortality in VP than in NP. Epidemics with k < 1 can be simulated by postulating coexisting high virulence virus (HVV) and low virulence virus (LVV), with the former being propagated at slower speed and with a higher mortality rate than the latter. An epidemic with k > 1 was simulated using parameters that are fractions of subpopulations NP or VP from the total population (f) and NP- or VP-specific patient multiplication (M) and mortality (D) rates. An epidemic with k < 1 was simulated using parameters that are fractions of HVV- or LVV-infected human populations (f), and HVV- or LVV-specific M and D.

Title: Disparities in premature deaths from heart disease--50 States and the District of Columbia, 2001. Content: In 2001, heart disease accounted for approximately 29.0% of deaths among U.S. residents; 16.8% of those deaths occurred among persons aged <65 years. Although mortality rates from heart disease have decreased, the decline has not been uniform for all populations. One of the two overall national health objectives for 2010 is to eliminate health disparities among different segments of the U.S. population. To better understand these disparities, CDC analyzed death certificate data for premature deaths from heart disease occurring in 2001. This report summarizes the results of that analysis, which indicated that the proportion of premature heart disease deaths varied by state and was higher among blacks, American Indians/Alaska Natives (AI/ANs), Asians/Pacific Islanders (A/PIs), and Hispanics. Reducing premature death from heart disease and eliminating disparities will require preventing, detecting, treating, and controlling risk factors for heart disease in young and middle-aged adults.

Title: Estimating Absolute and Relative Case Fatality Ratios from Infectious Disease Surveillance Data Content: Knowing which populations are most at risk for severe outcomes from an emerging infectious disease is crucial in deciding the optimal allocation of resources during an outbreak response. The case fatality ratio (CFR) is the fraction of cases that die after contracting a disease. The relative CFR is the factor by which the case fatality in one group is greater or less than that in a second group. Incomplete reporting of the number of infected individuals, both recovered and dead, can lead to biased estimates of the CFR. We define conditions under which the CFR and the relative CFR are identifiable. Furthermore, we propose an estimator for the relative CFR that controls for time-varying reporting rates. We generalize our methods to account for elapsed time between infection and death. To demonstrate the new methodology, we use data from the 1918 influenza pandemic to estimate relative CFRs between counties in Maryland. A simulation study evaluates the performance of the methods in outbreak scenarios. An R software package makes the methods and data presented here freely available. Our work highlights the limitations and challenges associated with estimating absolute and relative CFRs in practice. However, in certain situations, the methods presented here can help identify vulnerable subpopulations early in an outbreak of an emerging pathogen such as pandemic influenza.

Title: A Comparison of Generalized Stochastic Milevsky-Promislov Mortality Models with Continuous Non-Gaussian Filters Content: The ability to precisely model mortality rates [Formula: see text] plays an important role from the economic point of view in healthcare. The aim of this article is to propose a comparison of the estimation of the mortality rates based on a class of stochastic Milevsky-Promislov mortality models. We assume that excitations are modeled by second, fourth and sixth order polynomials of outputs from a linear non-Gaussian filter. To estimate the model parameters we use the first and second moments of [Formula: see text]. The theoretical values obtained in both cases were compared with theoretical [Formula: see text] based on a classical Lee-Carter model. The obtained results confirm the usefulness of the switched model based on the continuous non-Gaussian processes used for modeling [Formula: see text].

Title: Motor vehicle-related death rates--United States, 1999-2005. Content: In 2005, the most recent year for which data are available, 45,520 deaths in the United States were related to motor vehicles. A Healthy People 2010 objective calls for reducing the rate of deaths related to motor vehicles to 9.2 per 100,000 population from a baseline of 15.6 in 1998. To assess progress toward the Healthy People objective and to examine characteristics of motor vehicle--related death rates, CDC analyzed data from the National Vital Statistics System (NVSS) for the period 1999--2005. This report summarizes the results of that analysis, which determined that, during 1999--2005, although annual age-adjusted motor vehicle--related death rates overall were nearly unchanged (range: 15.2--15.7 per 100,000 population), substantial differences were observed by state, U.S. Census region, sex, race, and age group. Among states, the average annual death rate ranged from 7.9 per 100,000 population in Massachusetts to 31.9 in Mississippi. Among regions, the rate ranged from 9.8 per 100,000 population in the Northeast to 19.5 in the South. The rate for men (21.7 per 100,000 population) was more than double the rate for women (9.4); the rate for American Indians/Alaska Natives (27.2) was nearly twice the rate for whites (15.7) and blacks (15.2), and the rate for persons aged 15--24 years (26.8) was 74% higher than the average annual rate overall (15.4). Additional analysis and research to determine the causes of geographic and demographic variations in motor vehicle--related deaths might result in more effective targeted interventions among the states, regions, and populations at greatest risk.

Title: Strict Lower Bound on the COVID-19 Fatality Rate in Overwhelmed Healthcare Systems Content: The Infection Fatality Rate (IFR) for COVID-19 is a poorly known, yet crucial, aspect of the disease. Counting only current deaths in a region and assuming everyone in that region is infected provides an absolute lower bound on the IFR. Using this estimator for New York City, Lombardy and Madrid yields strong bounds on the average IFR in overwhelmed health systems. Their combined 35,152 deaths implies IFR > 0.14% averaged over 25.1 million people. This is the best-case scenario and conclusively demonstrates that COVID-19 is more deadly than influenza. The actual value of the average COVID-19 IFR is likely to be higher than this bound.

Title: The true case fatality of COVID19: An analytical solution Content: The exact risk of dying from COVID-19 has remained elusive and a topic of debate. The observed case fatality rates of 46 different countries are hypothesized to be dependent on their testing rates. An analytical test to this hypothesis suggests that the case fatality rate of COVID-19 could be consistent to a certain degree across all countries and states. The current global fatality rate is estimated to be around 1% and expected to converge between 1-3% when the pandemic ends. This model can be helpful to estimate the true infection rate for individual countries.

Title: Trends in childhood cancer mortality--United States, 1990-2004. Content: Cancer is the fourth most common cause of death (after unintentional injury, homicide, and suicide) among persons aged 1-19 years in the United States. Because recent childhood cancer mortality has not been well characterized in terms of temporal, demographic, and geographic trends, CDC analyzed cancer death rates among children (defined as aged 0-14 years) and adolescents (defined as aged 15-19 years) for the period 1990-2004 by sex, age group, race, ethnicity, U.S. Census region, and primary cancer site/leading diagnosis, using the most recent data available from the National Vital Statistics System (NVSS). This report describes the results of that analysis, which indicated that, overall, age-adjusted childhood cancer death rates decreased significantly during 1990-2004 among both sexes, both age groups, all races (except American Indians/Alaska Natives [AI/ANs]), Hispanics, non-Hispanics, and all U.S. Census regions. However, decreases in death rates varied among U.S. Census regions and between Hispanics and non-Hispanics. Eliminating racial/ethnic health disparities is one of the overarching goals of Healthy People 2010. Further research is needed to understand geographic and ethnic disparities in childhood cancer death rates. Moreover, cancer prevention and intervention measures should be designed to reach populations that are underserved and at high risk.

Title: Trends in Infectious Disease Mortality, South Korea, 1983–2015 Content: We used national statistics from 1983–2015 to evaluate trends in mortality caused by infectious diseases in South Korea. Age-standardized mortality from infectious disease decreased from 43.5/100,000 population in 1983 to 16.5/100,000 in 1996, and then increased to 44.6/100,000 in 2015. Tuberculosis was the most common cause of death in 1983 and respiratory tract infections in 2015. We observed a significant decline in infant deaths caused by infectious diseases, but mortality in persons age >65 years increased from 135 deaths/100,000 population in 1996 to 307/100,000 in 2015. The relative inequality indices for respiratory tract infections, sepsis, and tuberculosis tended to increase over time. Although substantial progress has been achieved in terms of infant mortality, death rates from infectious disease has not decreased overall. Elderly populations with lower education levels and subgroups susceptible to respiratory infections and sepsis should be the focus of preventive policies.

Title: How Large Was the Mortality Increase Directly and Indirectly Caused by the COVID-19 Epidemic? An Analysis on All-Causes Mortality Data in Italy Content: Objective: Overall mortality is a relevant indicator of the population burden during an epidemic. It informs on both undiagnosed cases and on the effects of health system disruption. Methods: We aimed at evaluating the extent of the total death excess during the COVID-19 epidemic in Italy. Data from 4433 municipalities providing mortality reports until April 15th, 2020 were included for a total of 34.5 million residents from all Italian regions. Data were analyzed by region, sex and age, and compared to expected from 2015–2019. Results: In both genders, overall mortality was stable until February 2020 and abruptly increased from March 1st onwards. Within the municipalities studied, 77,339 deaths were observed in the period between March 1st to April 15th, 2020, in contrast to the 50,822.6 expected. The rate ratio was 1.11 before age 60 and 1.55 afterwards. Both sexes were affected. The excess was greater in the regions most affected by COVID-19 but always exceeded the deaths attributed to COVID-19. The extrapolation to the total Italian population suggests an excess of 45,033 deaths in the study period, while the number of COVID–19 deaths was 21,046. Conclusion: Our paper shows a large death excess during the COVID-19 epidemic in Italy; greater than the number attributed to it. Possible causes included both the undetected cases and the disruption of the Health Service organization. Timely monitoring of overall mortality based on unbiased nationwide data is an essential tool for epidemic control.

Title: Worldwide differences in COVID-19-related mortality Content: Mortality statistics due to COVID-19 worldwide are compared, by adjusting for the size of the population and the stage of the pandemic. Data from the European Centre for Disease Control and Prevention, and Our World in Data websites were used. Analyses are based on number of deaths per one million inhabitants. In order to account for the stage of the pandemic, the baseline date was defined as the day in which the 10th death was reported. The analyses included 78 countries and territories which reported 10 or more deaths by April 9. On day 10, India had 0.06 deaths per million, Belgium had 30.46 and San Marino 618.78. On day 20, India had 0.27 deaths per million, China had 0.71 and Spain 139.62. On day 30, four Asian countries had the lowest mortality figures, whereas eight European countries had the highest ones. In Italy and Spain, mortality on day 40 was greater than 250 per million, whereas in China and South Korea, mortality was below 4 per million. Mortality on day 10 was moderately correlated with life expectancy, but not with population density. Asian countries presented much lower mortality figures as compared to European ones. Life expectancy was found to be correlated with mortality.

Title: Worldwide differences in COVID-19-related mortality. Content: Mortality statistics due to COVID-19 worldwide are compared, by adjusting for the size of the population and the stage of the pandemic. Data from the European Centre for Disease Control and Prevention, and Our World in Data websites were used. Analyses are based on number of deaths per one million inhabitants. In order to account for the stage of the pandemic, the baseline date was defined as the day in which the 10th death was reported. The analyses included 78 countries and territories which reported 10 or more deaths by April 9. On day 10, India had 0.06 deaths per million, Belgium had 30.46 and San Marino 618.78. On day 20, India had 0.27 deaths per million, China had 0.71 and Spain 139.62. On day 30, four Asian countries had the lowest mortality figures, whereas eight European countries had the highest ones. In Italy and Spain, mortality on day 40 was greater than 250 per million, whereas in China and South Korea, mortality was below 4 per million. Mortality on day 10 was moderately correlated with life expectancy, but not with population density. Asian countries presented much lower mortality figures as compared to European ones. Life expectancy was found to be correlated with mortality.

Title: How Large Was the Mortality Increase Directly and Indirectly Caused by the COVID-19 Epidemic? An Analysis on All-Causes Mortality Data in Italy Content: Objective: Overall mortality is a relevant indicator of the population burden during an epidemic. It informs on both undiagnosed cases and on the effects of health system disruption. Methods: We aimed at evaluating the extent of the total death excess during the COVID-19 epidemic in Italy. Data from 4433 municipalities providing mortality reports until April 15th, 2020 were included for a total of 34.5 million residents from all Italian regions. Data were analyzed by region, sex and age, and compared to expected from 2015-2019. Results: In both genders, overall mortality was stable until February 2020 and abruptly increased from March 1st onwards. Within the municipalities studied, 77,339 deaths were observed in the period between March 1st to April 15th, 2020, in contrast to the 50,822.6 expected. The rate ratio was 1.11 before age 60 and 1.55 afterwards. Both sexes were affected. The excess was greater in the regions most affected by COVID-19 but always exceeded the deaths attributed to COVID-19. The extrapolation to the total Italian population suggests an excess of 45,033 deaths in the study period, while the number of COVID-19 deaths was 21,046. Conclusion: Our paper shows a large death excess during the COVID-19 epidemic in Italy; greater than the number attributed to it. Possible causes included both the undetected cases and the disruption of the Health Service organization. Timely monitoring of overall mortality based on unbiased nationwide data is an essential tool for epidemic control.

Title: Serology-informed estimates of SARS-COV-2 infection fatality risk in Geneva, Switzerland Content: The infection fatality risk (IFR) is the average number of deaths per infection by a pathogen and is key to characterizing the severity of infection across the population and for specific demographic groups. To date, there are few empirical estimates of IFR published due to challenges in measuring infection rates. Outside of closed, closely surveilled populations where infection rates can be monitored through viral surveillance, we must rely on indirect measures of infection, like specific antibodies. Representative seroprevalence studies provide an important avenue for estimating the number of infections in a community, and when combined with death counts can lead to robust estimates of the IFR. We estimated overall and age-specific IFR for the canton of Geneva, Switzerland using age-stratified daily case and death incidence reports combined with five weekly population-based seroprevalence estimates. From February 24th to June 2nd there were 5'039 confirmed cases and 286 reported deaths within Geneva (population of 506'765). We inferred age-stratified (5-9, 10-19, 20-49, 50-65 and 65+) IFRs by linking the observed number of deaths to the estimated number of infected individuals from each serosurvey. We account for the delays between infection and seroconversion as well as between infection and death. Inference is drawn in a Bayesian framework that incorporates uncertainty in seroprevalence estimates (supplement). Of the 286 reported deaths caused by SARS-CoV-2, the youngest person to die was 31 years old. Infected individuals younger than 50 years experienced statistically similar IFRs (range 0.00032-0.0016%), which increases to 0.14% (95% CrI 0.096-0.19) for those 50-64 years old to 5.6% (95% CrI 4.3-7.4) for those 65 years and older (supplement). After accounting for demography and age-specific seroprevalence, we estimate a population-wide IFR of 0.64% (95% CrI 0.38-0.98). Our results are subject to two notable limitations. Among the 65+ age group that died of COVID-19 within Geneva, 50% were reported among residents of assisted care facilities, where around 0.8% of the Geneva population resides. While the serosurvey protocol did not explicitly exclude these individuals, they are likely to have been under-represented. This would lead to an overestimation of the IFR in the 65+ age group if seroprevalence in this institutionalized population was higher than in the general population (supplement). Further, our IFR estimates are based on current evidence regarding post-infection antibody kinetics, which may differ between severe and mild infections. If mild infections have significantly lower and short-lived antibody responses, our estimates of IFR may be biased upwards. Estimates of IFR are key for understanding the true pandemic burden and for weighing different risk reduction strategies. The IFR is not solely determined by host and pathogen biology, but also by the capacity of health systems to treat severe cases. Despite having among the highest per capita incidence in Switzerland, Geneva's health system accommodated the influx of cases needing intensive care (peak of 80/110 ICU-beds including surge capacity) while maintaining care quality standards. As such, our IFR estimates can be seen as a best-case scenario with respect to health system capacity. Our results reveal that population-wide estimates of IFR mask great heterogeneity by age and point towards the importance of age-targeted interventions to reduce exposures among those at highest risk of death.

Title: Incidence and Mortality Rates of Disasters and Mass Casualty Incidents in Korea: A Population-Based Cross-Sectional Study, 2000-2009 Content: The objective of study was to evaluate the incidence and mortality rates of disasters and mass casualty incidents (MCIs) over the past 10 yr in the administrative system of Korea administrative system and to examine their relationship with population characteristics. This was a population-based cross-sectional study. We calculated the nationwide incidence, as well as the crude mortality and injury incidence rates, of disasters and MCIs. The data were collected from the administrative database of the National Emergency Management Agency (NEMA) and from provincial fire departments from January 2000 to December 2009. A total of 47,169 events were collected from the NEMA administrative database. Of these events, 115 and 3,079 cases were defined as disasters and MCIs that occurred in Korea, respectively. The incidence of technical disasters/MCIs was approximately 12.7 times greater than that of natural disasters/MCIs. Over the past 10 yr, the crude mortality rates for disasters and MCIs were 2.36 deaths per 100,000 persons and 6.78 deaths per 100,000 persons, respectively. The crude injury incidence rates for disasters and MCIs were 25.47 injuries per 100,000 persons and 152 injuries per 100,000 persons, respectively. The incidence and mortality of disasters/MCIs in Korea seem to be low compared to that of trend around the world.

Title: COVID-19, Australia: Epidemiology Report 12 (Reporting week to 23:59 AEST 19 April 2020) Content: Confirmed cases in Australia notified up to 19 April 2020: notifications = 6,606; deaths = 69. The reduction in international travel and domestic movement, social distancing measures and public health action have likely slowed the spread of the disease. Notifications in Australia remain predominantly among people with recent overseas travel, with some locally-acquired cases being detected. Most locally-acquired cases can be linked back to a confirmed case, with a small portion unable to be epidemiologically linked. The distribution of overseas-acquired cases to locally-acquired cases varies by jurisdiction. The crude case fatality rate (CFR) in Australia remains low (1.0%) compared to the World Health Organization's globally-reported rate (6.8%) and to other comparable high-income countries such as the United States of America (4.7%) and the United Kingdom (13.5%). The low CFR is likely reflective of high case ascertainment including detection of mild cases. High case ascertainment enables public health response and reduction of disease transmission. Internationally, cases continue to increase. The rates of increase have started to slow in several regions, although it is too soon to tell whether this trend will be sustained. Interpretation of international epidemiology should be conducted with caution as it differs from country to country depending not only on the disease dynamics, but also on differences in case detection, testing and implemented public health measures.

Title: COVID-19, Australia: Epidemiology Report 12 (Reporting week to 23:59 AEST 19 April 2020). Content: Confirmed cases in Australia notified up to 19 April 2020: notifications = 6,606; deaths = 69. The reduction in international travel and domestic movement, social distancing measures and public health action have likely slowed the spread of the disease. Notifications in Australia remain predominantly among people with recent overseas travel, with some locally-acquired cases being detected. Most locally-acquired cases can be linked back to a confirmed case, with a small portion unable to be epidemiologically linked. The distribution of overseas-acquired cases to locally-acquired cases varies by jurisdiction. The crude case fatality rate (CFR) in Australia remains low (1.0%) compared to the World Health Organization's globally-reported rate (6.8%) and to other comparable high-income countries such as the United States of America (4.7%) and the United Kingdom (13.5%). The low CFR is likely reflective of high case ascertainment including detection of mild cases. High case ascertainment enables public health response and reduction of disease transmission. Internationally, cases continue to increase. The rates of increase have started to slow in several regions, although it is too soon to tell whether this trend will be sustained. Interpretation of international epidemiology should be conducted with caution as it differs from country to country depending not only on the disease dynamics, but also on differences in case detection, testing and implemented public health measures.

Title: Global Burden of Infectious Diseases Content: Systematic efforts to quantify and monitor the burden of specific health conditions in populations, at the national level, started in the mid-1950s for malaria, poliomyelitis, and influenza in the United States. Comprehensive surveillance of morbidity and mortality for dozens of conditions has since been well established in the United States and in other industrialized countries. However, despite the clear need for epidemiological data to inform health policies, reliable and comprehensive health statistics are not available in many developing countries. International efforts to assess and monitor the burden of certain diseases have been limited in the past to a small number of infectious diseases in the context of global eradication programs – smallpox, poliomyelitis, guinea worm, and, more recently, HIV/AIDS, severe acute respiratory syndrome (SARS), and avian flu influenza A (H5N1). The Global Burden of Disease Study (GBD), published in 1996, filled an important gap in our knowledge of population health status. It created a common metric, the disability-adjusted life year (DALY), to estimate morbidity and mortality for eight regions that collectively span the world’s population, generating comparable information on incidence and prevalence in global health. However, patterns of disease, disability, and risk factors have since changed significantly and new data on their distribution are available. Furthermore, the unprecedented money and attention now pouring into international health has made an accurate assessment of global health patterns a matter of utmost urgency. The new Global Burden of Diseases, Injuries, and Risk Factors (GBD 2005) project, which began in 2007, represents the first major effort at a systematic revision of estimates in health for every region in the world comprehensively, and will ensure that that the global health community bases its research and policies on complete, valid, and reliable information. Burden of disease estimates provided in this article are for 2001 – the year for which the most recent estimates of the global burden of disease and risk factors are currently available. Causes of deaths were categorized into three main groups: group I (infectious diseases and maternal, perinatal, and nutritional conditions), group II (noncommunicable diseases), and group III (injuries). Accordingly, estimates of the global burden of infectious diseases are provided in the context of the overall burden from other conditions, diseases, and injuries. The relative importance of the burden of infectious diseases was forecasted to change by 2020. As the epidemiological transition progresses worldwide, a decline in the burden of infectious diseases is expected as the burden of noncommunicable diseases and injuries gradually increases. The pace of the epidemiological transition, however, varies greatly among regions so that the projected decreases in the burden of infectious diseases are expected to vary between regions. Trends in the global burden due to specific infectious diseases projected to 2020 also vary among specific conditions. The global burden of HIV/AIDS, for instance, is expected to greatly increase, whereas the global burden due to respiratory infections and diarrheal diseases is expected to decrease. Contrary to expectations, the global burden of malaria has increased in recent years.

Title: Methods for Estimating the Case Fatality Ratio for a Novel, Emerging Infectious Disease Content: During the course of an epidemic of a potentially fatal disease, it is important that the case fatality ratio be well estimated. The authors propose a novel method for doing so based on the Kaplan-Meier survival procedure, jointly considering two outcomes (death and recovery), and evaluate its performance by using data from the 2003 epidemic of severe acute respiratory syndrome in Hong Kong, People's Republic of China. They compare this estimate obtained at various points in the epidemic with the case fatality ratio eventually observed; with two commonly quoted, naïve estimates derived from cumulative incidence and mortality statistics at single time points; and with estimates in which a parametric mixture model is used. They demonstrate the importance of patient characteristics regarding outcome by analyzing subgroups defined by age at admission to the hospital.

Title: A comparison study of realtime fatality rates: severe acute respiratory syndrome in Hong Kong, Singapore, Taiwan, Toronto and Beijing, China Content: Summary. In an outbreak of a completely new infectious disease like severe acute respiratory syndrome (SARS), estimation of the fatality rate over the course of the epidemic is of clinical and epidemiological importance. In contrast with the constant case fatality rate, a new measure, termed the ‘realtime’ fatality rate, is proposed for monitoring the new emerging epidemic at a population level. A competing risk model implemented via a counting process is used to estimate the realtime fatality rate in an epidemic of SARS. It can capture and reflect the time‐varying nature of the fatality rate over the course of the outbreak in a timely and accurate manner. More importantly, it can provide information on the efficacy of a certain treatment and management policy for the disease. The method has been applied to the SARS data from the regions affected, namely Hong Kong, Singapore, Toronto, Taiwan and Beijing. The magnitudes and patterns of the estimated fatalities are virtually the same except in Beijing, which has a lower rate. It is speculated that the effect is linked to the different treatment protocols that were used. The standard estimate of the case fatality rate that was used by the World Health Organization has been shown to be unable to provide useful information to monitor the time‐varying fatalities that are caused by the epidemic.

Title: Occupational Deaths among Healthcare Workers Content: Recent experiences with severe acute respiratory syndrome and the US smallpox vaccination program have demonstrated the vulnerability of healthcare workers to occupationally acquired infectious diseases. However, despite acknowledgment of risk, the occupational death rate for healthcare workers is unknown. In contrast, the death rate for other professions with occupational risk, such as police officer or firefighter, has been well defined. With available information from federal sources and calculating the additional number of deaths from infection by using data on prevalence and natural history, we estimate the annual death rate for healthcare workers from occupational events, including infection, is 17–57 per 1 million workers. However, a much more accurate estimate of risk is needed. Such information could inform future interventions, as was seen with the introduction of safer needle products. This information would also heighten public awareness of this often minimized but essential aspect of patient care.

Title: EXCESS MORTALITY FROM COVID-19. WEEKLY EXCESS DEATH RATES BY AGE AND SEX FOR SWEDEN. Content: Objectives: Mortality from Covid-19 is monitored in detail both within as well as between countries with different strategies against the virus. However, death counts and relative risks based on crude numbers can be misleading. Instead, age specific death rates should be used for comparability. Given the difficulty of ascertainment of Covid-19 specific deaths, excess all-cause mortality is currently more appropriate for comparisons. By estimating age- and sex-specific death rates we aim to get more accurate estimates of the excess mortality attributed to Covid-19, as well as the difference between men and women in Sweden. Design: We make use of Swedish register data about total weekly deaths, total population at risk, and estimate age- and sex-specific weekly death rates for 2020 and the 5 previous years. The data is provided by Statistics Sweden. Results: From the first week of April and onwards, the death rates at all ages above 60 are higher than those in previous years in Sweden. Persons above age 80 are dis-proportionally more affected, and men suffer higher levels of excess mortality than women at all ages with 75% higher death rates for males and 50% higher for females. Current excess mortality corresponds to a decline in remaining life expectancy of 3 years for men and 2 years for women. Conclusion: The Covid-19 pandemic has so far had a clear and consistent effect on total mortality in Sweden, with male death rates being comparably more affected. What consequences the pandemic will eventually have on mortality and life expectancy will depend on the progression of the pandemic, the extent that some of the deaths would have occurred in the absence of the pandemic, only somewhat later, the consequences for other health conditions, as well as the health care sector at large.

Title: Estimating Lower Bounds for COVID-19 Mortality from Northern Italian Towns Content: For COVID-19 the Infection Fatality Rate or IFR - a crucial variable in epidemiological modeling - is difficult to estimate because many cases are asymptomatic and the overall infection rate is generally not known. Circumstances in the Italian provinces of Milano, Bergamo, Brescia, and Lodi allow estimation of lower bounds for age- and sex-specific all-cause excess mortality (a proxy for IFR) since anecdotal reports indicate some towns were close to fully infected. Using data from ISTAT on mortality from January 1 through April 15 for 2020 and the three preceding years, I estimate excess mortality by sex and age categories (0-14, 15-54, 55-64, 65-74, and 75+ years) while controlling for town-specific mortality that proxies for town-specific infection rate. The 99th percentile from the tail of the town distribution gives a lower-bound estimate for COVID-19 mortality. The overall population-weighted mortality at the 99th percentile is 1.09 percent (95% CI 1.06-1.14). The age- and sex-specific rates vary considerably: for men age 65-74 the estimate is 2.10 percent (95% CI 1.94-2.28) which is 3.5-times higher than men 55-64 and 2.7-times higher than women 65-74.

Title: [Covid-19 - deaths and analysis]. Content: Mortality from Covid-19 is monitored in detail and compared between countries with different strategies against the virus. There is, however, often a lack of understanding of what is required in terms of measures and interpretation to enable correct comparisons. The number of deaths from Covid-19 is affected by the testing strategy and many other things that differ between countries. Therefore, today, the most reliable source for monitoring and comparing mortality from Covid-19 is total mortality. In Sweden, there is good correspondence of Covid-19 deaths and total mortality, with a tendency to a higher total mortality indicating some under-reporting of Covid-19 mortality.

Title: Total mortalitet bättre vid jämförelser än död i covid-19./ [Covid-19 - deaths and analysis] Content: Mortality from Covid-19 is monitored in detail and compared between countries with different strategies against the virus. There is, however, often a lack of understanding of what is required in terms of measures and interpretation to enable correct comparisons. The number of deaths from Covid-19 is affected by the testing strategy and many other things that differ between countries. Therefore, today, the most reliable source for monitoring and comparing mortality from Covid-19 is total mortality. In Sweden, there is good correspondence of Covid-19 deaths and total mortality, with a tendency to a higher total mortality indicating some under-reporting of Covid-19 mortality.

Title: Beyond Deaths per Capita: Three CoViD-19 Mortality Indicators for Temporal and International Comparisons Content: CoViD-19 deaths to population size ratios fail to account for well-documented age and sex differences in CoViD-19 mortality. To assess trends across populations for which CoViD-19 deaths might not be available by age and sex, an indirect age-and-sex adjustment can still be performed. The corresponding Comparative CoViD-19 Mortality Ratio (CCMR) only requires population age and sex compositions. To compare CoViD-19 and overall mortality levels, the Crude Death Rate (CDR) and life expectancy at birth for recent calendar years are the most widely available overall mortality indicators. Readily comparable to an annual CDR, a Crude CoViD-19 Death Rate (CCDR) can be calculated for periods of any duration. CoViD-19-induced declines in projected life expectancy at birth for 2020 can also be calculated from existing life tables. We calculate the CCMR and CCDR for the period from their first CoViD-19 death to the present using US age and sex data and current estimates of CoViD-19 deaths in 166 Countries whose population composition is available from the UN, 28 Provinces in China, the 50 United States and DC. Across these 245 populations, 14 States and 11 Countries have CCMR values above 1—the US value by construction. Most affected to date, the period CCDR in New York exceeds its CDR for the most recent year available (7.83 per thousand in 2017). We also calculate CCMR and CCDR values corresponding to projections for the 50 States and DC, and for 49 countries, for which we can additionally calculate reductions in 2020 life expectancy at birth using UN life tables. This suggests life-expectancy reductions between .5 and 1 year for 7 European Countries, 3 South-American Countries and the US. The .55 reduction in the U.S. amounts to nearly twice the largest single-year decline induced by HIV/AIDS (−.3 between 1992 and 1993) or the total decline induced by opioid overdoses (also −.3 between 2014 and 2017), and would bring US life expectancy at birth down to its lowest level since 2008. As current CoViD-19 death counts likely underestimate the total increase in deaths and current projections do not account for possible new infection waves later this year, the impact on 2020 life expectancies at birth should be expected to exceed these figures.

Title: Pathogen Genomics and the Potential for Understanding Diseases in the Developing World Content: Approximately 46% and 32% of deaths among children under five globally occur in sub-Saharan Africa and South Asia, respectively. Over 80% of the 4.2 million child deaths in Africa are caused by infectious diseases, sharply contrasted to Europe where 39% of the 0.15 million child deaths are attributable to infectious diseases (Fig. 5.1) (Black et al. 2010). Hence, despite the remarkable public health advancements in hygiene, sanitation, antimicrobial drugs and vaccine strategies of the twenty-first century, the burden of infectious diseases remains unacceptably high in the developing world.

Title: Epidemiology of Viral Infections Content: Viruses survive in nature only if they are able to pass from one host to another, whether of the same or another species. Viral epidemiology is the study of the factors that determine the frequency and distribution of viral diseases in an animal population. In the broadest sense, epidemiology may be viewed as a part of population biology, involving not only environmental factors but also genetic factors in both the virus and the host. The terms incidence and prevalence are used to describe quantitative aspects of the occurrence of infections in populations. The incidence of infection is defined as the proportion of a population contracting that infection during a specified period, whereas prevalence refers to the proportion infected at a particular point in time. The comparisons of incidence and prevalence at different times and places are made by relating the appropriate numerator to a denominator that may be as general as the total population of the animal species concerned or may be specified as the susceptible population at risk. A disease is said to be enzootic when there are continuous chains of transmission in the region involved; epizootics are peaks in disease incidence. The size of the peak required to constitute an epizootic is arbitrary and is related to the background enzootic rate, the morbidity, and the anxiety that the disease arouses.

Title: The Contribution of Age Structure to the Number of Deaths from Covid-19 in the UK by Geographical Units Content: This study investigates the contribution of population age structure to mortality from Covid-19 in the UK by geographical units. We project death rates at various spatial scales by applying data on age-specific fatality rates to the area's population by age and sex. Our analysis shows a significant variation in the projected death rates between the constituent countries of the UK, between its regions and within regions. First, Scotland and Wales have higher projected fatality levels from Covid-19 than England, whereas Northern Ireland has lower rate. Second, the infection fatality rates are projected to be substantially higher in small towns and rural areas than those in large urban areas. Third, our analysis shows that within urban regions there are also 'pockets' of high projected death rates. Overall, the areas with high and low fatality rates tend to cluster because of the high residential separation of different population age-groups in the UK. Our analysis also reveals that the Welsh-, Gaelic- and Cornish-speaking communities with relatively old populations are likely to experience heavy population losses if the virus spreads widely across the UK.

Title: Explaining national differences in the mortality of Covid-19: individual patient simulation model to investigate the effects of testing policy and other factors on apparent mortality. Content: There has been extensive speculation on the apparent differences in mortality between countries reporting on the confirmed cases and deaths due to Covid-19. A number of explanations have been suggested, but there is no clear evidence about how apparent fatality rates may be expected to vary with the different testing regimes, admission policies and other variables. An individual patient simulation model was developed to address this question. Parameters and sensitivity analysis based upon recent international data sources for Covid-19 and results were averaged over 100 iterations for a simulated cohort of over 500,000 patients. Different testing regimes for Covid-19 were considered; testing admitted patients only, various rates of community testing of symptomatic cases and active contact-tracing and screening. In the base case analysis, apparent mortality ranged from 10.5% under a policy of testing only admitted patients to 0.4% with intensive contact tracing and community testing. These findings were sensitive to assumptions regarding admission rates and the rate of spread, with more selective admission policies and suppression of spread increasing the apparent mortality and the potential for apparent mortality rates to exceed 18% under some circumstances. Under all scenarios the proportion of patients tested in the community had the greatest impact on apparent mortality. Whilst differences in mortality due to health service and demographic factors cannot be excluded, the current international differences in reported mortality are all consistent with differences in practice regarding screening, community testing and admission policies.

Title: What does and does not correlate with COVID-19 death rates Content: We correlate county-level COVID-19 death rates with key variables using both linear regression and negative binomial mixed models, although we focus on linear regression models. We include four sets of variables: socio-economic variables, county-level health variables, modes of commuting, and climate and pollution patterns. Our analysis studies daily death rates from April 4, 2020 to May 27, 2020. We estimate correlation patterns both across states, as well as within states. For both models, we find higher shares of African American residents in the county are correlated with higher death rates. However, when we restrict ourselves to correlation patterns within a given state, the statistical significance of the correlation of death rates with the share of African Americans, while remaining positive, wanes. We find similar results for the share of elderly in the county. We find that higher amounts of commuting via public transportation, relative to telecommuting, is correlated with higher death rates. The correlation between driving into work, relative to telecommuting, and death rates is also positive across both models, but statistically significant only when we look across states and counties. We also find that a higher share of people not working, and thus not commuting either because they are elderly, children or unemployed, is correlated with higher death rates. Counties with higher home values, higher summer temperatures, and lower winter temperatures have higher death rates. Contrary to past work, we do not find a correlation between pollution and death rates. Also importantly, we do not find that death rates are correlated with obesity rates, ICU beds per capita, or poverty rates. Finally, our model that looks within states yields estimates of how a given state's death rate compares to other states after controlling for the variables included in our model; this may be interpreted as a measure of how states are doing relative to others. We find that death rates in the Northeast are substantially higher compared to other states, even when we control for the four sets of variables above. Death rates are also statistically significantly higher in Michigan, Louisiana, Iowa, Indiana, and Colorado. California's death rate is the lowest across all states.

Title: Basic Reproduction Rate and Case Fatality Rate of COVID-19: Application of Meta-analysis Content: Abstract Background: The outbreak of novel coronavirus disease of 2019 (COVID-19) has a wider geographical spread than other previous viruses such as Ebola and H1N1. The onset of disease and its transmission and severity has become a global concern. The policymakers have a serious concern for containing the spread and minimising the risk of death. Aim: This study aims to provide the estimates of basic reproduction rate (R0) and case fatality rate (CFR) which applies to a generalised population. Methods: A systematic review was carried out to retrieve the published estimates of reproduction rate and case fatality rate in peer-reviewed articles from PubMed MEDLINE database with defined inclusion and exclusion criteria in the period 15 December 2019 to 3 May 2020. The systematic review led to the selection of 24 articles for R0 and 17 articles for CFR. These studies used data from China and its provinces, other Asian countries such as Japan, Korea, the Philippines, and countries from other parts of the world such as Nigeria, Iran, Italy, Europe as a whole, France, Latin America, Turkey, the United Kingdom (UK), and the United States of America (USA). These selected articles gave an output of 30 counts of R0 and 29 counts of CFR which were used in a meta-analysis. A meta-analysis, with the inverse variance method, fixed- and random-effects model and the Forest plot, was performed to estimate the mean effect size or mean value of basic reproduction rate and case fatality rate. The Funnel plot is used to comprehend the publication bias. Results: We estimated the robust estimate of R0 at 3.11 (2.49-3.71) persons and the robust estimate of CFR at 2.56 (2.06-3.05) per cent after accounting for heterogeneity among studies, using the random-effects model. The regional subgroup analysis in a meta-analysis was significant for R0 but was not significant for CFR. The R0 values varied from 1.90 (1.06-2.74) persons to 3.83 (2.44-5.22) persons across the regions. The Funnel plot confirms that the selected studies are significant at one per cent level of significance. Conclusion: We found that one person is likely to infect two to three persons in the absence of any control measures, and around three per cent of the population are at the risk of death within one-and-a-half months from the onset of disease COVID-19 in a generalised population. The emergence of SARS-CoV-2 varies across regions, but the risk of death remains the same. Contribution: The estimates of R0 and CFR are independent of data from a particular region or time or a homogeneous population. These estimates are applicable to a generalised population. Therefore, the estimates of R0 and CFR are unequivocally applicable to developing country like India and its states or districts, in ambivalence. The assessments of R0 and CFR values across the developed nations make all of us aware of consequences of COVID-19, and hence these estimates are of crucial importance for government authorities for the practical implementation of strategies and control measures to contain the disease. Keywords: Covid-19, SARS-CoV-2, Reproduction Rate, Case Fatality Rate, Systematic Review, Meta-analysis

Title: Mortality, morbidity and health in developed societies: a review of data sources Content: The purpose of this paper is to review the major sources of data on mortality, morbidity and health in Europe and in other developed regions in order to examine their potential for analysing mortality and morbidity levels and trends. The review is primarily focused on routinely collected information covering a whole country. No attempt is made to draw up an inventory of sources by country; the paper deals instead with the pros and cons of each source for mortality and morbidity studies in demography. While each source considered separately can already yield useful, though partial, results, record linkage among data sources can significantly improve the analysis. Record linkage can also lead to the detection of possible causal associations that could eventually be confirmed. More generally, Big Data can reveal changing mortality and morbidity trends and patterns that could lead to preventive measures being taken rather than more costly curative ones.

Title: Age-Specific Excess Mortality Patterns During the 1918–1920 Influenza Pandemic in Madrid, Spain Content: Although much progress has been made to uncover age-specific mortality patterns of the 1918 influenza pandemic in populations around the world, more studies in different populations are needed to make sense of the heterogeneous death impact of this pandemic. We assessed the absolute and relative magnitudes of 3 pandemic waves in the city of Madrid, Spain, between 1918 and 1920, on the basis of age-specific all-cause and respiratory excess death rates. Excess death rates were estimated using a Serfling model with a parametric bootstrapping approach to calibrate baseline death levels with quantified uncertainty. Excess all-cause and pneumonia and influenza mortality rates were estimated for different pandemic waves and age groups. The youngest and oldest persons experienced the highest excess mortality rates, and young adults faced the highest standardized mortality risk. Waves differed in strength; the peak standardized mortality risk occurred during the herald wave in spring 1918, but the highest excess rates occurred during the fall and winter of 1918/1919. Little evidence was found to support a “W”-shaped, age-specific excess mortality curve. Acquired immunity may have tempered a protracted fall wave, but recrudescent waves following the initial 2 outbreaks heightened the total pandemic mortality impact.

Title: A Method to Identify the Missing COVID-19 Cases in the U.S. and Results for mid-April 2020 Content: I use the COVID-19 death rate in South Korea and a method relating the ratio of death rates in a U.S. state to its share of cumulative positive tests to estimate the total cases of COVID-19 in the U.S. and to estimate the extent of infection and the unidentified share of the infected population in each of the lower-48 states and in New York City in mid-April, 2020. I identify a logarithmic relationship between the cumulative death rate in a state and its cumulative positive share of tests. Using this relationship, I find that 4.3-5.4 million people, 1.4-1.7% of the U.S. population, were infected, with rates of infection that ranged from 0.1% in more rural states to 8-10% in New York state and 11-13% in New York City. Only 16-20% of these infected individuals were identified later through testing.

Title: The sociospatial factors of death: Analyzing effects of geospatially-distributed variables in a Bayesian mortality model for Hong Kong Content: Human mortality is in part a function of multiple socioeconomic factors that differ both spatially and temporally. Adjusting for other covariates, the human lifespan is positively associated with household wealth. However, the extent to which mortality in a geographical region is a function of socioeconomic factors in both that region and its neighbors is unclear. There is also little information on the temporal components of this relationship. Using the districts of Hong Kong over multiple census years as a case study, we demonstrate that there are differences in how wealth indicator variables are associated with longevity in (a) areas that are affluent but neighbored by socially deprived districts versus (b) wealthy areas surrounded by similarly wealthy districts. We also show that the inclusion of spatially-distributed variables reduces uncertainty in mortality rate predictions in each census year when compared with a baseline model. Our results suggest that geographic mortality models should incorporate nonlocal information (e.g., spatial neighbors) to lower the variance of their mortality estimates, and point to a more in-depth analysis of sociospatial spillover effects on mortality rates.

Title: Correspondence regarding recently published editorial: ‘Will children reveal their secret? The coronavirus dilemma’ Content: When individuals without prior immunity are considered, case fatality ratios are typically higher in adults than in children for most infectious diseases, with few exceptions.

Title: TRACKing Excess Deaths (TRACKED): an interactive online tool to monitor excess deaths associated with COVID-19 pandemic in the United Kingdom Content: Aim: We aimed to describe trends of excess mortality in the United Kingdom (UK) stratified by nation and cause of death, and to develop an online tool for reporting the most up to date data on excess mortality. Methods: Population statistics agencies in the UK including the Office for National Statistics (ONS), National Records of Scotland (NRS), and Northern Ireland Statistics and Research Agency (NISRA) publish weekly data on deaths. We used mortality data up to 22nd May in the ONS and the NISRA and 24th May in the NRS. Crude mortality for non-COVID deaths (where there is no mention of COVID-19 on the death certificate) calculated. Excess mortality defined as difference between observed mortality and expected average of mortality from previous 5 years. Results: There were 56,961 excess deaths and 8,986 were non-COVID excess deaths. England had the highest number of excess deaths per 100,000 population (85) and Northern Ireland the lowest (34). Non-COVID mortality increased from 23rd March and returned to the 5-year average on 10th May. In Scotland, where underlying cause mortality data besides COVID-related deaths was available, the percentage excess over the 8-week period when COVID-related mortality peaked was: dementia 49%, other causes 21%, circulatory diseases 10%, and cancer 5%. We developed an online tool (TRACKing Excess Deaths - TRACKED) to allow dynamic exploration and visualisation of the latest mortality trends. Conclusions: Continuous monitoring of excess mortality trends and further integration of age- and gender-stratified and underlying cause of death data beyond COVID-19 will allow dynamic assessment of the impacts of indirect and direct mortality of the COVID-19 pandemic.

Title: Global patterns of mortality in international migrants: a systematic review and meta-analysis. Content: BACKGROUND 258 million people reside outside their country of birth; however, to date no global systematic reviews or meta-analyses of mortality data for these international migrants have been done. We aimed to review and synthesise available mortality data on international migrants. METHODS In this systematic review and meta-analysis, we searched MEDLINE, Embase, the Cochrane Library, and Google Scholar databases for observational studies, systematic reviews, and randomised controlled trials published between Jan 1, 2001, and March 31, 2017, without language restrictions. We included studies reporting mortality outcomes for international migrants of any age residing outside their country of birth. Studies that recruited participants exclusively from intensive care or high dependency hospital units, with an existing health condition or status, or a particular health exposure were excluded. We also excluded studies limited to maternal or perinatal outcomes. We screened studies using systematic review software and extracted data from published reports. The main outcomes were all-cause and International Classification of Diseases, tenth revision (ICD-10) cause-specific standardised mortality ratios (SMRs) and absolute mortality rates. We calculated summary estimates using random-effects models. This study is registered with PROSPERO, number CRD42017073608. FINDINGS Of the 12 480 articles identified by our search, 96 studies were eligible for inclusion. The studies were geographically diverse and included data from all global regions and for 92 countries. 5464 mortality estimates for more than 15·2 million migrants were included, of which 5327 (97%) were from high-income countries, 115 (2%) were from middle-income countries, and 22 (<1%) were from low-income countries. Few studies included mortality estimates for refugees (110 estimates), asylum seekers (144 estimates), or labour migrants (six estimates). The summary estimate of all-cause SMR for international migrants was lower than one when compared with the general population in destination countries (0·70 [95% CI 0·65-0·76]; I2=99·8%). All-cause SMR was lower in both male migrants (0·72 [0·63-0·81]; I2=99·8%) and female migrants (0·75 [0·67-0·84]; I2=99·8%) compared with the general population. A mortality advantage was evident for refugees (SMR 0·50 [0·46-0·54]; I2=89·8%), but not for asylum seekers (1·05 [0·89-1·24]; I2=54·4%), although limited data was available on these groups. SMRs for all causes of death were lower in migrants compared with the general populations in the destination country across all 13 ICD-10 categories analysed, with the exception of infectious diseases and external causes. Heterogeneity was high across the majority of analyses. Point estimates of all-cause age-standardised mortality in migrants ranged from 420 to 874 per 100 000 population. INTERPRETATION Our study showed that international migrants have a mortality advantage compared with general populations, and that this advantage persisted across the majority of ICD-10 disease categories. The mortality advantage identified will be representative of international migrants in high-income countries who are studying, working, or have joined family members in these countries. However, our results might not reflect the health outcomes of more marginalised groups in low-income and middle-income countries because little data were available for these groups, highlighting an important gap in existing research. Our results present an opportunity to reframe the public discourse on international migration and health in high-income countries. FUNDING Wellcome Trust, National Institute for Health Research, Medical Research Council, Alliance for Health Policy and Systems Research, Department for International Development, Fogarty International Center, Grand Challenges Canada, International Development Research Centre Canada, Inter-American Institute for Global Change Research, National Cancer Institute, National Heart, Lung and Blood Institute, National Institute of Mental Health, Swiss National Science Foundation, World Diabetes Foundation, UK National Institute for Health Research Imperial Biomedical Research Centre, Imperial College Healthcare Charity, and European Society for Clinical Microbiology and Infectious Diseases (ESCMID) Study Group Research Funding for the ESCMID Study Group for Infections in Travellers and Migrants.

Title: Global, regional, and national disability-adjusted life-years (DALYs) for 333 diseases and injuries and healthy life expectancy (HALE) for 195 countries and territories, 1990-2016: a systematic analysis for the Global Burden of Disease Study 2016. Content: BACKGROUND Measurement of changes in health across locations is useful to compare and contrast changing epidemiological patterns against health system performance and identify specific needs for resource allocation in research, policy development, and programme decision making. Using the Global Burden of Diseases, Injuries, and Risk Factors Study 2016, we drew from two widely used summary measures to monitor such changes in population health: disability-adjusted life-years (DALYs) and healthy life expectancy (HALE). We used these measures to track trends and benchmark progress compared with expected trends on the basis of the Socio-demographic Index (SDI). METHODS We used results from the Global Burden of Diseases, Injuries, and Risk Factors Study 2016 for all-cause mortality, cause-specific mortality, and non-fatal disease burden to derive HALE and DALYs by sex for 195 countries and territories from 1990 to 2016. We calculated DALYs by summing years of life lost and years of life lived with disability for each location, age group, sex, and year. We estimated HALE using age-specific death rates and years of life lived with disability per capita. We explored how DALYs and HALE differed from expected trends when compared with the SDI: the geometric mean of income per person, educational attainment in the population older than age 15 years, and total fertility rate. FINDINGS The highest globally observed HALE at birth for both women and men was in Singapore, at 75·2 years (95% uncertainty interval 71·9-78·6) for females and 72·0 years (68·8-75·1) for males. The lowest for females was in the Central African Republic (45·6 years [42·0-49·5]) and for males was in Lesotho (41·5 years [39·0-44·0]). From 1990 to 2016, global HALE increased by an average of 6·24 years (5·97-6·48) for both sexes combined. Global HALE increased by 6·04 years (5·74-6·27) for males and 6·49 years (6·08-6·77) for females, whereas HALE at age 65 years increased by 1·78 years (1·61-1·93) for males and 1·96 years (1·69-2·13) for females. Total global DALYs remained largely unchanged from 1990 to 2016 (-2·3% [-5·9 to 0·9]), with decreases in communicable, maternal, neonatal, and nutritional (CMNN) disease DALYs offset by increased DALYs due to non-communicable diseases (NCDs). The exemplars, calculated as the five lowest ratios of observed to expected age-standardised DALY rates in 2016, were Nicaragua, Costa Rica, the Maldives, Peru, and Israel. The leading three causes of DALYs globally were ischaemic heart disease, cerebrovascular disease, and lower respiratory infections, comprising 16·1% of all DALYs. Total DALYs and age-standardised DALY rates due to most CMNN causes decreased from 1990 to 2016. Conversely, the total DALY burden rose for most NCDs; however, age-standardised DALY rates due to NCDs declined globally. INTERPRETATION At a global level, DALYs and HALE continue to show improvements. At the same time, we observe that many populations are facing growing functional health loss. Rising SDI was associated with increases in cumulative years of life lived with disability and decreases in CMNN DALYs offset by increased NCD DALYs. Relative compression of morbidity highlights the importance of continued health interventions, which has changed in most locations in pace with the gross domestic product per person, education, and family planning. The analysis of DALYs and HALE and their relationship to SDI represents a robust framework with which to benchmark location-specific health performance. Country-specific drivers of disease burden, particularly for causes with higher-than-expected DALYs, should inform health policies, health system improvement initiatives, targeted prevention efforts, and development assistance for health, including financial and research investments for all countries, regardless of their level of sociodemographic development. The presence of countries that substantially outperform others suggests the need for increased scrutiny for proven examples of best practices, which can help to extend gains, whereas the presence of underperforming countries suggests the need for devotion of extra attention to health systems that need more robust support. FUNDING Bill & Melinda Gates Foundation.

Title: Potential Biases in Estimating Absolute and Relative Case-Fatality Risks during Outbreaks Content: Estimating the case-fatality risk (CFR)—the probability that a person dies from an infection given that they are a case—is a high priority in epidemiologic investigation of newly emerging infectious diseases and sometimes in new outbreaks of known infectious diseases. The data available to estimate the overall CFR are often gathered for other purposes (e.g., surveillance) in challenging circumstances. We describe two forms of bias that may affect the estimation of the overall CFR—preferential ascertainment of severe cases and bias from reporting delays—and review solutions that have been proposed and implemented in past epidemics. Also of interest is the estimation of the causal impact of specific interventions (e.g., hospitalization, or hospitalization at a particular hospital) on survival, which can be estimated as a relative CFR for two or more groups. When observational data are used for this purpose, three more sources of bias may arise: confounding, survivorship bias, and selection due to preferential inclusion in surveillance datasets of those who are hospitalized and/or die. We illustrate these biases and caution against causal interpretation of differential CFR among those receiving different interventions in observational datasets. Again, we discuss ways to reduce these biases, particularly by estimating outcomes in smaller but more systematically defined cohorts ascertained before the onset of symptoms, such as those identified by forward contact tracing. Finally, we discuss the circumstances in which these biases may affect non-causal interpretation of risk factors for death among cases.

Title: Why case fatality ratios can be misleading: individual- and population-based mortality estimates and factors influencing them Content: Different ways of calculating mortality during epidemics have yielded very different results, particularly during the current COVID-19 pandemic. For example, the "CFR" has been interchangeably called the case fatality ratio, case fatality rate, and case fatality risk, often without standard mathematical definitions. The most commonly used CFR is thecase fatality ratio, typically constructed using the estimated number of deaths to date divided by the estimated total number of confirmed infected cases to date. How does this CFR relate to an infected individual's probability of death? To explore such issues, we formulate both a survival probability model and an associated infection duration-dependent SIR model to define individual- and population-based estimates of dynamic mortality measures to show that neither of these are directly represented by the case fatality ratio. The key parameters that affect the dynamics of different mortality estimates are the incubation period and the time individuals were infected before confirmation of infection. Using data on the recent SARS-CoV-2 outbreaks, we estimate and compare the different dynamic mortality estimates and highlight their differences. Informed by our modeling, we propose more systematic methods to determine mortality during epidemic outbreaks and discuss sensitivity to confounding effects and uncertainties in the data such as undertesting and heterogeneous populations.

Title: Audit of intensive care: a 30 month experience using the Apache II severity of disease classification system Content: 608 patients admitted to a general Intensive Care Unit (ICU) over a 30 month period were analyzed according to the Apache II Severity of Disease Classification System on day one of admission. Hospital outcome details were available on 583 patients in the series. The mean Apache II scores for survivors (396) and non-survivors (187) were 13 (SD 7) and 24 (SD 9), and their Risk of Death were 16 (SD 16) and 47 (SD 27) respectively (p(0.001 for both). The majority of deaths (75%: 141/187) in our series came from those with chronic ill health (55%: 103/187), of whom 37% (38/103) were in endstage disease, and those with “old” trauma (18%: 34/187) often with incipient sepsis transferred from other hospitals after a mean delay of 9 days. Our higher than predicted mortality (mortality ratio 1.2) in comparison with centres in the United States of America (US) may be partly explained by the high proportion of our population from these unfavourable groups, by our use of the best Glasgow Coma Scale in the first 24 h following admission, and the major differences between our patient population and that of the US upon which the Apache II was based. The presence of these large unfavourable groups indicates a change in our admission policy is warranted.

Title: Chapter 6 Real-Time Estimation of the Case Fatality Ratio and Risk Factors of Death Content: Abstract During the course of an epidemic, estimating the risk of death and identifying risk factors of death are of utmost importance for public health assessment of the severity of infection. The real-time estimation involves a number of important statistical problems to consider, and this chapter comprehensively describes commonly used estimation methods and their pitfalls. When estimating the case fatality risk (CFR) during the course of an epidemic, the data are right-censored because of the time delay from illness onset to death. A conventional survival analysis technique is employed for addressing right censoring. Identification of risk factors of death also requires the care for censored nature of the data, and we have devised a method that combines the survival analysis and logistic regression. Ascertainment bias is always a practical issue in interpreting the absolute value of the CFR or comparing CFR between different groups, and recent studies have shown that observational effort including seroepidemiological survey has to be made to overcome this bias.

Title: A Novel Approach for Estimating the Final Outcome of Global Diseases Like COVID-19 Content: The existence of a universal law which maps the bell curve of daily cases to a sigmoid curve for cumulative ones is used for making robust estimations about the final outcome of a disease. Computations of real time effective reproduction rate are presented and its limited usefulness is derived. After using methods ESE and EDE we are able to find the inflection point of the cumulative curve under consideration and study its time evolution. Since mortality processes tend to follow a Gompertz distribution, we apply the properties of it and introduce novel estimations for both the time remaining after inflection time and the capacity of the curve. Special properties of sigmoid curves are used for assessing the quality of estimation and as indices for the cycle completion. Application is presented for COVID-19 evolution for most affected countries and the World.

Title: Population-level COVID-19 mortality risk for non-elderly individuals overall and for non-elderly individuals without underlying diseases in pandemic epicenters Content: OBJECTIVE: To provide estimates of the relative rate of COVID-19 death in people <65 years old versus older individuals in the general population, the absolute risk of COVID-19 death at the population level during the first epidemic wave, and the proportion of COVID-19 deaths in non-elderly people without underlying diseases in epicenters of the pandemic. ELIGIBLE DATA: Cross-sectional survey of countries and US states with at least 800 COVID-19 deaths as of April 24, 2020 and with information on the number of deaths in people with age <65. Data were available for 14 countries (Belgium, Canada, France, Germany, India, Ireland, Italy, Mexico, Netherlands, Portugal, Spain, Sweden, Switzerland, UK) and 13 US states (California, Connecticut, Florida, Georgia, Illinois, Indiana, Louisiana, Maryland, Massachusetts, Michigan, New Jersey, New York, Pennsylvania). We also examined available data on COVID-19 deaths in people with age <65 and no underlying diseases. MAIN OUTCOME MEASURES: Proportion of COVID-19 deaths in people <65 years old; relative mortality rate of COVID-19 death in people <65 versus ≥65 years old; absolute risk of COVID-19 death in people <65 and in those ≥80 years old in the general population as of June 17, 2020; absolute COVID-19 mortality rate expressed as equivalent of mortality rate from driving a motor vehicle. RESULTS: Individuals with age <65 account for 4.5–11.2% of all COVID-19 deaths in European countries and Canada, 8.3–22.7% in the US locations, and were the majority in India and Mexico. People <65 years old had 30- to 100-fold lower risk of COVID-19 death than those ≥65 years old in 11 European countries and Canada, 16- to 52-fold lower risk in US locations, and less than 10-fold in India and Mexico. The absolute risk of COVID-19 death as of June 17, 2020 for people <65 years old in high-income countries ranged from 10 (Germany) to 349 per million (New Jersey) and it was 5 per million in India and 96 per million in Mexico. The absolute risk of COVID-19 death for people ≥80 years old ranged from 0.6 (Florida) to 17.5 per thousand (Connecticut). The COVID-19 mortality rate in people <65 years old during the period of fatalities from the epidemic was equivalent to the mortality rate from driving between 4 and 82 miles per day for 13 countries and 5 states, and was higher (equivalent to the mortality rate from driving 106–483 miles per day) for 8 other states and the UK. People <65 years old without underlying predisposing conditions accounted for only 0.7–3.6% of all COVID-19 deaths in France, Italy, Netherlands, Sweden, Georgia, and New York City and 17.7% in Mexico. CONCLUSIONS: People <65 years old have very small risks of COVID-19 death even in pandemic epicenters and deaths for people <65 years without underlying predisposing conditions are remarkably uncommon. Strategies focusing specifically on protecting high-risk elderly individuals should be considered in managing the pandemic.

Title: Global between-countries variance in SARS-CoV-2 mortality is driven by reported prevalence, age distribution, and case detection rate Content: Objective: To explain the global between-countries variance in number of deaths per million citizens (nDpm) and case fatality rate (CFR) due to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. Design: Systematic analysis. Data sources: Worldometer, European Centre for Disease Prevention and Control, United Nations Main outcome measures: The explanators of nDpm and CFR were mathematically hypothesised and tested on publicly-available data from 88 countries with linear regression models on May 1st 2020. The derived explanators - age-adjusted infection fatality rate (IFRadj) and case detection rate (CDR) - were estimated for each country based on a SARS-CoV-2 model of China. The accuracy and agreement of the models with observed data was assessed with R2 and Bland-Altman plots, respectively. Sensitivity analyses involved removal of outliers and testing the models at five retrospective and two prospective time points. Results: Globally, IFRadj estimates varied between countries, ranging from below 0.2% in the youngest nations, to above 1.3% in Portugal, Greece, Italy, and Japan. The median estimated global CDR of SARS-CoV-2 infections on April 16th 2020 was 12.9%, suggesting that most of the countries have a much higher number of cases than reported. At least 93% and up to 99% of the variance in nDpm was explained by reported prevalence expressed as cases per million citizens (nCpm), IFRadj, and CDR. IFRadj and CDR accounted for up to 97% of the variance in CFR, but this model was less reliable than the nDpm model, being sensitive to outliers (R2 as low as 67.5%). Conclusions: The current differences in SARS-CoV-2 mortality between countries are driven mainly by reported prevalence of infections, age distribution, and CDR. The nDpm might be a more stable estimate than CFR in comparing mortality burden between countries.

Title: Excess mortality in mental health service users during the COVID-19 pandemic described by ethnic group: South London and Maudsley data Content: The COVID-19 pandemic in the UK was accompanied by excess all-cause mortality at a national level, only part of which was accounted for by known infections. Excess mortality has previously been described in people who had received care from the South London and Maudsley NHS Foundation Trust (SLaM), a large mental health service provider for 1.2m residents in south London. The SLaM Clinical Record Interactive Search (CRIS) data resource receives 24-hourly updates from its full electronic health record, including regularly sourced national mortality on all past and present SLaM service users. The SLaM urban catchment has high levels of deprivation and is ethnically diverse, so the objective of the descriptive analyses reported in this manuscript was to compare mortality in SLaM service users from 16th March to 15th May 2020 to that for the same period in 2019 within specific ethnic groups: i) White British, ii) Other White, iii) Black African/Caribbean, iv) South Asian, v) Other, and vi) missing/not stated. For Black African/Caribbean patients (the largest minority ethnic group) this ratio was 3.33, compared to 2.47 for White British patients. Considering premature mortality (restricting to deaths below age 70), these ratios were 2.74 and 1.96 respectively. Ratios were also high for those from Other ethnic groups (2.63 for all mortality, 3.07 for premature mortality).

Title: Morbidity and mortality in homeless individuals, prisoners, sex workers, and individuals with substance use disorders in high-income countries: a systematic review and meta-analysis. Content: BACKGROUND Inclusion health focuses on people in extremely poor health due to poverty, marginalisation, and multimorbidity. We aimed to review morbidity and mortality data on four overlapping populations who experience considerable social exclusion: homeless populations, individuals with substance use disorders, sex workers, and imprisoned individuals. METHODS For this systematic review and meta-analysis, we searched MEDLINE, Embase, and the Cochrane Library for studies published between Jan 1, 2005, and Oct 1, 2015. We included only systematic reviews, meta-analyses, interventional studies, and observational studies that had morbidity and mortality outcomes, were published in English, from high-income countries, and were done in populations with a history of homelessness, imprisonment, sex work, or substance use disorder (excluding cannabis and alcohol use). Studies with only perinatal outcomes and studies of individuals with a specific health condition or those recruited from intensive care or high dependency hospital units were excluded. We screened studies using systematic review software and extracted data from published reports. Primary outcomes were measures of morbidity (prevalence or incidence) and mortality (standardised mortality ratios [SMRs] and mortality rates). Summary estimates were calculated using a random effects model. FINDINGS Our search identified 7946 articles, of which 337 studies were included for analysis. All-cause standardised mortality ratios were significantly increased in 91 (99%) of 92 extracted datapoints and were 11·86 (95% CI 10·42-13·30; I2=94·1%) in female individuals and 7·88 (7·03-8·74; I2=99·1%) in men. Summary SMR estimates for the International Classification of Diseases disease categories with two or more included datapoints were highest for deaths due to injury, poisoning, and other external causes, in both men (7·89; 95% CI 6·40-9·37; I2=98·1%) and women (18·72; 13·73-23·71; I2=91·5%). Disease prevalence was consistently raised across the following categories: infections (eg, highest reported was 90% for hepatitis C, 67 [65%] of 103 individuals for hepatitis B, and 133 [51%] of 263 individuals for latent tuberculosis infection), mental health (eg, highest reported was 9 [4%] of 227 individuals for schizophrenia), cardiovascular conditions (eg, highest reported was 32 [13%] of 247 individuals for coronary heart disease), and respiratory conditions (eg, highest reported was 9 [26%] of 35 individuals for asthma). INTERPRETATION Our study shows that homeless populations, individuals with substance use disorders, sex workers, and imprisoned individuals experience extreme health inequities across a wide range of health conditions, with the relative effect of exclusion being greater in female individuals than male individuals. The high heterogeneity between studies should be explored further using improved data collection in population subgroups. The extreme health inequity identified demands intensive cross-sectoral policy and service action to prevent exclusion and improve health outcomes in individuals who are already marginalised. FUNDING Wellcome Trust, National Institute for Health Research, NHS England, NHS Research Scotland Scottish Senior Clinical Fellowship, Medical Research Council, Chief Scientist Office, and the Central and North West London NHS Trust.

Title: Mortality of Life‐Insured Swedish Cats during 1999–2006: Age, Breed, Sex, and Diagnosis Content: Background: A cat life insurance database can potentially be used to study feline mortality. Hypothesis: The aim was to describe patterns of mortality in life‐insured Swedish cats. Cats: All cats (<13 years of age) with life insurance during the period 1999–2006 were included. Methods: Age‐standardized mortality rates (MR) were calculated with respect to sex (males and females), age, breed, and diagnosis. Survival to various ages is presented by time period and breed. Results: The total number of cats insured was 49,450 and the number of cat‐years at risk (CYAR) was 142,049. During the period, 6,491 cats died and of these 4,591 cats (71%) had a diagnosis, ie, were claimed for life insurance. The average annual MR was 462 deaths per 10,000 CYAR (95% confidence interval, 431–493). Sex‐specific rates did not differ significantly. The overall mortality of the Persian and the Siamese groups was higher than that of several other breeds. Overall and breed‐specific (for most breeds) survival increased with time when analyzed by 2‐year periods. The 6 most common diagnostic categories (ignoring cats recorded as dead with no diagnosis) were urinary, traumatic, neoplastic, infectious, cardiovascular, and gastrointestinal. The MR within diagnostic categories varied by age and breed. Conclusions and Clinical Importance: In this mainly purebred, insured cat population, the overall mortality varied with age and breed but not with sex. The increase in survival over time is likely a reflection of willingness to keep pet cats longer and increased access to and sophistication of veterinary care.

Title: Online estimation of the case fatality rate using a run-off triangle data approach: An application to the Korean MERS outbreak in 2015. Content: This work is motivated by the recent Korean Middle East respiratory syndrome outbreak. We propose an easy online estimation procedure for the case fatality rate, ie, the proportion of deaths among the total cases during the course of an epidemic disease, which is an important indicator of the severity of a disease. The key step in our procedure is representing the data with the run-off triangle, which simultaneously takes into account two time axes, namely, the calendar and disease-duration times. We restructure the original data into run-off triangle data, where the cells contain the numbers of cured patients, deceased patients, and patients still having the disease at a given combination of calendar and disease-duration times. Based on the restructured run-off triangle data, we propose an online estimator of the case fatality rate. We numerically show the advantages of the proposed estimator compared to the existing estimators in the literature. Finally, we apply our procedure to the 2015 Korean Middle East respiratory syndrome outbreak data.

Title: Estimates of COVID-19 case-fatality risk from individual-level data Content: When calculated from aggregate data on confirmed cases and deaths, the case-fatality risk (CFR) is a simple ratio between the former and the latter, which is prone to numerous biases. With individual-level data, the CFR can be estimated as a true measure of risk as the proportion of incidence for the disease. We present the first estimates of the CFR for COVID-19 by age and sex based on event history modelling of the risk of dying among confirmed positive individuals in the Canadian province of Ontario, which maintains one of the few individual-level datasets on COVID-19 in the world.

Title: Age effects in monetary valuation of reduced mortality risks: the relevance of age-specific hazard rates Content: This paper highlights the relevance of age-specific hazard rates in explaining the age variation in “value of statistical life” (VSL) figures. The analysis—which refers to a stated preference framework—contributes to the ongoing discussion of whether benefits resulting from reduced mortality risk should be valued differently depending on the age of the beneficiaries. By focussing on a life-threatening environmental phenomenon I show that the consideration of the individual’s age-specific hazard rate is important. If a particular risk affects all individuals regardless of their age so that their hazard rate is age-independent, VSL is rather constant for people at different age; if hazard rate varies with age, VSL estimates are sensitive to age. The results provide an explanation for the mixed outcomes in empirical studies and illustrate in which cases an adjustment to age may or may not be justified. Efficient provision of live-saving measures requires that such differences to be taken into account.

Title: Global, regional, and national estimates of levels of preterm birth in 2014: a systematic review and modelling analysis. Content: BACKGROUND Preterm birth is the leading cause of death in children younger than 5 years worldwide. Although preterm survival rates have increased in high-income countries, preterm newborns still die because of a lack of adequate newborn care in many low-income and middle-income countries. We estimated global, regional, and national rates of preterm birth in 2014, with trends over time for some selected countries. METHODS We systematically searched for data on preterm birth for 194 WHO Member States from 1990 to 2014 in databases of national civil registration and vital statistics (CRVS). We also searched for population-representative surveys and research studies for countries with no or limited CRVS data. For 38 countries with high-quality data for preterm births in 2014, data are reported directly. For countries with at least three data points between 1990 and 2014, we used a linear mixed regression model to estimate preterm birth rates. We also calculated regional and global estimates of preterm birth for 2014. FINDINGS We identified 1241 data points across 107 countries. The estimated global preterm birth rate for 2014 was 10·6% (uncertainty interval 9·0-12·0), equating to an estimated 14·84 million (12·65 million-16·73 million) live preterm births in 2014. 12· 0 million (81·1%) of these preterm births occurred in Asia and sub-Saharan Africa. Regional preterm birth rates for 2014 ranged from 13·4% (6·3-30·9) in North Africa to 8·7% (6·3-13·3) in Europe. India, China, Nigeria, Bangladesh, and Indonesia accounted for 57·9 million (41×4%) of 139·9 million livebirths and 6·6 million (44×6%) of preterm births globally in 2014. Of the 38 countries with high-quality data, preterm birth rates have increased since 2000 in 26 countries and decreased in 12 countries. Globally, we estimated that the preterm birth rate was 9×8% (8×3-10×9) in 2000, and 10×6% (9×0-12×0) in 2014. INTERPRETATION Preterm birth remains a crucial issue in child mortality and improving quality of maternal and newborn care. To better understand the epidemiology of preterm birth, the quality and volume of data needs to be improved, including standardisation of definitions, measurement, and reporting. FUNDING WHO and the March of Dimes.

Title: Global, regional, and national incidence, prevalence, and years lived with disability for 328 diseases and injuries for 195 countries, 1990-2016: a systematic analysis for the Global Burden of Disease Study 2016. Content: BACKGROUND As mortality rates decline, life expectancy increases, and populations age, non-fatal outcomes of diseases and injuries are becoming a larger component of the global burden of disease. The Global Burden of Diseases, Injuries, and Risk Factors Study 2016 (GBD 2016) provides a comprehensive assessment of prevalence, incidence, and years lived with disability (YLDs) for 328 causes in 195 countries and territories from 1990 to 2016. METHODS We estimated prevalence and incidence for 328 diseases and injuries and 2982 sequelae, their non-fatal consequences. We used DisMod-MR 2.1, a Bayesian meta-regression tool, as the main method of estimation, ensuring consistency between incidence, prevalence, remission, and cause of death rates for each condition. For some causes, we used alternative modelling strategies if incidence or prevalence needed to be derived from other data. YLDs were estimated as the product of prevalence and a disability weight for all mutually exclusive sequelae, corrected for comorbidity and aggregated to cause level. We updated the Socio-demographic Index (SDI), a summary indicator of income per capita, years of schooling, and total fertility rate. GBD 2016 complies with the Guidelines for Accurate and Transparent Health Estimates Reporting (GATHER). FINDINGS Globally, low back pain, migraine, age-related and other hearing loss, iron-deficiency anaemia, and major depressive disorder were the five leading causes of YLDs in 2016, contributing 57·6 million (95% uncertainty interval [UI] 40·8-75·9 million [7·2%, 6·0-8·3]), 45·1 million (29·0-62·8 million [5·6%, 4·0-7·2]), 36·3 million (25·3-50·9 million [4·5%, 3·8-5·3]), 34·7 million (23·0-49·6 million [4·3%, 3·5-5·2]), and 34·1 million (23·5-46·0 million [4·2%, 3·2-5·3]) of total YLDs, respectively. Age-standardised rates of YLDs for all causes combined decreased between 1990 and 2016 by 2·7% (95% UI 2·3-3·1). Despite mostly stagnant age-standardised rates, the absolute number of YLDs from non-communicable diseases has been growing rapidly across all SDI quintiles, partly because of population growth, but also the ageing of populations. The largest absolute increases in total numbers of YLDs globally were between the ages of 40 and 69 years. Age-standardised YLD rates for all conditions combined were 10·4% (95% UI 9·0-11·8) higher in women than in men. Iron-deficiency anaemia, migraine, Alzheimer's disease and other dementias, major depressive disorder, anxiety, and all musculoskeletal disorders apart from gout were the main conditions contributing to higher YLD rates in women. Men had higher age-standardised rates of substance use disorders, diabetes, cardiovascular diseases, cancers, and all injuries apart from sexual violence. Globally, we noted much less geographical variation in disability than has been documented for premature mortality. In 2016, there was a less than two times difference in age-standardised YLD rates for all causes between the location with the lowest rate (China, 9201 YLDs per 100 000, 95% UI 6862-11943) and highest rate (Yemen, 14 774 YLDs per 100 000, 11 018-19 228). INTERPRETATION The decrease in death rates since 1990 for most causes has not been matched by a similar decline in age-standardised YLD rates. For many large causes, YLD rates have either been stagnant or have increased for some causes, such as diabetes. As populations are ageing, and the prevalence of disabling disease generally increases steeply with age, health systems will face increasing demand for services that are generally costlier than the interventions that have led to declines in mortality in childhood or for the major causes of mortality in adults. Up-to-date information about the trends of disease and how this varies between countries is essential to plan for an adequate health-system response. FUNDING Bill & Melinda Gates Foundation, and the National Institute on Aging and the National Institute of Mental Health of the National Institutes of Health.

Title: Perspectives on the basic reproductive ratio. Content: The basic reproductive ratio, R0, is defined as the expected number of secondary infections arising from a single individual during his or her entire infectious period, in a population of susceptibles. This concept is fundamental to the study of epidemiology and within-host pathogen dynamics. Most importantly, R0 often serves as a threshold parameter that predicts whether an infection will spread. Related parameters which share this threshold behaviour, however, may or may not give the true value of R0. In this paper we give a brief overview of common methods of formulating R0 and surrogate threshold parameters from deterministic, non-structured models. We also review common means of estimating R0 from epidemiological data. Finally, we survey the recent use of R0 in assessing emerging diseases, such as severe acute respiratory syndrome and avian influenza, a number of recent livestock diseases, and vector-borne diseases malaria, dengue and West Nile virus.

Title: Introduction: A Prelude to Mathematical Epidemiology Content: Recorded history continuously documents the invasion of populations by infectious agents, some causing many deaths before disappearing, others reappearing in invasions some years later in populations that have acquired some degree of immunity, due to prior exposure to related infectious pathogens. The “Spanish” flu epidemic of 1918–1919 exemplifies the devastating impact of relatively rare pandemics; this one was responsible for about 50,000,000 deaths worldwide, while on the mild side of the spectrum we experience annual influenza seasonal epidemics that cause roughly 35,000 deaths in the USA each year.

Title: The Longevity-Frailty Hypothesis: Evidence from COVID-19 Death Rates in Europe Content: COVID-19 death rates vary strikingly across Europe. The death rate in Spain, for example, is greater than the death rate in Germany by more than a factor of ten. Few if any epidemiological indicators distinguish the countries of Europe by such a vast margin. Evidence on age-specific case-fatality rates (deaths over observed infections) and age-specific death rates (deaths over population) indicate that COVID-19 disproportionately afflicts the elderly and frail, suggesting that the share of elderly population (≥ 65 years of age) in a country ought to be a strong predictor of the COVID-19 death rate. However, the COVID-19 death rate and the share of elderly population are statistically uncorrelated (r = 0.163, p = 0.399). Share of population ≥ 65 years of age is confounded by mortality selection, as well as other demographic dynamics. By contrast, elderly longevity or life expectancy at 65 more effectively captures population survival and the accumulation of age-related frailty in society. We find a strong statistical relationship between the COVID-19 death rate (r = 0.839, p < .001) and elderly longevity, and a moderately strong relationship between the date of epidemic timing and elderly longevity (r = −0.634, p < .001). These relationships are robust to the inclusion of statistical controls for international tourism inflow and hospital bed capacity. While the countries of Europe vary meaningfully in healthcare system capacity and in the timing and intensity of non-pharmaceutical interventions, the striking variation in COVID-19 death rates across these countries is statistically and intuitively associated with elderly survival and consequent frailty.

Title: Monitoring trends and differences in COVID-19 case fatality rates using decomposition methods: Contributions of age structure and age-specific fatality Content: The population-level case fatality rate (CFR) associated with COVID-19 varies substantially, both across countries and within countries over time. We analyze the contribution of two key determinants of the variation in the observed CFR: the age-structure of diagnosed infection cases and age-specific case-fatality rates. We use data on diagnosed COVID-19 cases and death counts attributable to COVID-19 by age for China, France, Germany, Italy, South Korea, Spain, and the United States. We calculate the CFR for each country at the latest data point and for Italy also over time. We use demographic decomposition to break the difference between CFRs into unique contributions arising from the age-structure of confirmed cases and the age-specific case-fatality. CFRs vary from 0.7% in Germany and 1.6% in South Korea to 8.6% in Spain and 10.6% in Italy. The age-structure of detected cases can explain a substantial proportion of cross-country variation in the CFR. For example, 57% of Spain's difference with respect to South Korea is explained by the observed cases being older. In Italy, the CFR increased from 4.2% to 10.6% between March 9 and March 29, 2020, and more than 95% of the change was due to increasing age-specific case fatality rates. The importance of the age-structure of infected cases likely reflects several factors, including different testing regimes and differences in transmission trajectories; while increasing age-specific case fatality rates indicate the worsening health outcomes of those infected with COVID-19. Our findings lend support to recommendations for data to be disaggregated by age, and potentially other variables, to facilitate a better understanding of population-level differences in CFRs. They also show the need for well designed seroprevalence studies to ascertain the extent to which differences in testing regimes drive differences in the age-structure of detected cases.

Title: Understanding the asymmetric spread and case fatality rate (CFR) for COVID-19 among countries Content: The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections are rising rapidly every day in the world, causing the disease COVID-19 with around 2 million people infected and more than 100,000 people died so far, in more than 200 countries. One of the baffling aspects of this pandemic is the asymmetric increase in cases and case fatality rate (CFR) among countries. We analyze the time series of the infection and fatality numbers and found two interesting aspects. Firstly, the rate of spread in a region is directly connected to the population density of the region where the virus is spreading. For example, the high rate of increase in cases in the United States of America (USA) is related to the high population density of New York City. This is shown by scaling the cumulative number of cases with a measure of the population density of the affected region in countries such as Italy, Spain, Germany, and the USA and we see that the curves are coinciding. Secondly, we analyzed the CFR number as a function of the number of days, since the first death, and we found that there are two clear categories among countries: one category with high CFR numbers (around 10%) and the other category with low CFR numbers (2% to 4%). When we analyzed the results, we see that countries with lower CFR numbers more or less tend to have implemented active control measures such as aggressive testing, tracking down possible infections, effective quarantine measures, etc. Moreover, we did not see any convincing correlation between mortality rates and the median age of the population.

Title: The Impact of Population Growth on the Epidemiology and Evolution of Infectious Diseases Content: It is generally expected that in developing countries the epidemiological transition, with improved health and lower mortality rates, will eventually lead to a demographic transition with lower fertility rates. The reductions in mortality characterising the epidemiological transition are often associated with controlling the infectious diseases within populations, which leaves the chronic diseases associated with old age, cancer and heart disease dominating the causes of death. However, if the demographic transition does not occur quickly, populations can grow rapidly, creating an increased potential for spread of infectious disease. These infectious diseases could, in turn, increase death rates amongst young people and reverse the epidemiological transition. The relationship between population growth, size and infection depends upon the changes in contact pattern associated with there being more people. If facilities can keep pace with growth, then the increase in contact rates can be kept to a minimum, and the potential reversal in the epidemic transition prevented. This makes development a crucial adjunct to population growth if the global community is not to be increasingly exposed to pandemics of infectious disease. Here we review the epidemiological and demographic theory which relates population growth and infectious disease.

Title: Staphylococcus aureus Colonization and Long-Term Risk for Death, United States. Content: To examine the association of colonization by Staphylococcus aureus and general population mortality, we followed 10,598 adults for 8.5 years on average. Methicillin-susceptible S. aureus colonization was not associated with death. Methicillin-resistant S. aureus carriage predicted death in a crude analysis but not after adjustment for socioeconomic status and co-morbidities.

Title: Risk for Death among Children with Pneumonia, Afghanistan. Content: In Afghanistan, childhood deaths from pneumonia are high. Among 639 children at 1 hospital, the case-fatality rate was 12.1%, and 46.8% of pneumococcal serotypes detected were covered by the 13-valent vaccine. Most deaths occurred within 2 days of hospitalization; newborns and malnourished children were at risk. Vaccination could reduce pneumonia and deaths.

Title: Ecology of Increasing Diseases: Population Growth and Environmental Degradation Content: The World Health Organization (WHO) and other organizations report that the prevalence of human diseases during the past decade is rapidly increasing. Population growth and the pollution of water, air, and soil are contributing to the increasing number of human diseases worldwide. Currently an estimated 40% of world deaths are due to environmental degradation. The ecology of increasing diseases has complex factors of environmental degradation, population growth, and the current malnutrition of about 3.7 billion people in the world.

Title: Predicting the mortality due to Covid-19 by the next month for Italy, Iran and South Korea; a simulation study Content: AIM: To estimate the number of confirmed cases and the rate of death and also to investigate the cause of death in Italy, Iran and South Korea in the next month. BACKGROUND: Growing number of confirmed and deaths cases from the coronavirus worldwide, particularly in Italy, Iran and South Korea, has resulted concerns about the future of these countries and their deterioration. Also the European region is likely to face more casualties due to the delay in the virus reaching most of its regions and, of course, as the trend continues. METHODS: We conducted a simulation in both current and ideal situation for the next month to predict the death rate and examine the reason for the difference in Italy, Iran and South Korea individually. If we assume the cultural and political factors and age pyramids distribution are similar across regions, the differences are mainly due either to the heavier health-care burden owing to the larger population or to the medical facilities diversities. RESULTS: Our results for Italy showed higher death number, but the rate would be more for Iran. South Korea is also expected to have a smaller increase in the number of confirmed cases and deaths compared to Iran and Italy by the next month. CONCLUSION: Given the prevailing conditions around the world and the increasing number of casualties, it is essential that all countries, especially those with fewer days of involvement, shall do their best to avoid major losses and damages.

Title: Predicting the mortality due to Covid-19 by the next month for Italy, Iran and South Korea; A simulation study Content: Aim: To estimate the number of confirmed cases and the rate of death and also to investigate the cause of death in Italy, Iran and South Korea in the next month. Background: Growing number of confirmed and deaths cases from the coronavirus worldwide, particularly in Italy, Iran and South Korea, has resulted concerns about the future of these countries and their deterioration. Also the European region is likely to face more casualties due to the delay in the virus reaching most of its regions and, of course, as the trend continues. Methods: We conducted a simulation in both current and ideal situation for the next month to predict the death rate and examine the reason for the difference in Italy, Iran and South Korea individually. If we assume the cultural and political factors and age pyramids distribution are similar across regions, the differences are mainly due either to the heavier health-care burden owing to the larger population or to the medical facilities diversities. Results: Our results for Italy showed higher death number, but the rate would be more for Iran. South Korea is also expected to have a smaller increase in the number of confirmed cases and deaths compared to Iran and Italy by the next month. Conclusion: Given the prevailing conditions around the world and the increasing number of casualties, it is essential that all countries, especially those with fewer days of involvement, shall do their best to avoid major losses and damages.

Title: Aetiology-Specific Estimates of the Global and Regional Incidence and Mortality of Diarrhoeal Diseases Commonly Transmitted through Food Content: BACKGROUND: Diarrhoeal diseases are major contributors to the global burden of disease, particularly in children. However, comprehensive estimates of the incidence and mortality due to specific aetiologies of diarrhoeal diseases are not available. The objective of this study is to provide estimates of the global and regional incidence and mortality of diarrhoeal diseases caused by nine pathogens that are commonly transmitted through foods. METHODS AND FINDINGS: We abstracted data from systematic reviews and, depending on the overall mortality rates of the country, applied either a national incidence estimate approach or a modified Child Health Epidemiology Reference Group (CHERG) approach to estimate the aetiology-specific incidence and mortality of diarrhoeal diseases, by age and region. The nine diarrhoeal diseases assessed caused an estimated 1.8 billion (95% uncertainty interval [UI] 1.1–3.3 billion) cases and 599,000 (95% UI 472,000–802,000) deaths worldwide in 2010. The largest number of cases were caused by norovirus (677 million; 95% UI 468–1,153 million), enterotoxigenic Escherichia coli (ETEC) (233 million; 95% UI 154–380 million), Shigella spp. (188 million; 95% UI 94–379 million) and Giardia lamblia (179 million; 95% UI 125–263); the largest number of deaths were caused by norovirus (213,515; 95% UI 171,783–266,561), enteropathogenic E. coli (121,455; 95% UI 103,657–143,348), ETEC (73,041; 95% UI 55,474–96,984) and Shigella (64,993; 95% UI 48,966–92,357). There were marked regional differences in incidence and mortality for these nine diseases. Nearly 40% of cases and 43% of deaths caused by these nine diarrhoeal diseases occurred in children under five years of age. CONCLUSIONS: Diarrhoeal diseases caused by these nine pathogens are responsible for a large disease burden, particularly in children. These aetiology-specific burden estimates can inform efforts to reduce diarrhoeal diseases caused by these nine pathogens commonly transmitted through foods.

Title: How Many Lives Has Lockdown Saved in the UK? Content: We compare the trajectory of deaths (both in hospitals and care homes) on a daily basis in Sweden and England and Wales (which constitute 90 per cent of the UK population) from 11 March to 12 June 2020, the latest date at which the relevant data is available for England and Wales. Deaths in both Sweden and England and Wales peaked on 8 April. The build up to the peak was very similar in both. Given the time lag between infection and death, the lockdown would have had little effect on the peak number of deaths. By 12 June, the deaths are virtually the same in both. However, from early May the decline in England and Wales has been much sharper. We estimate that to 12 June, lockdown saved just under 6,000 lives in England and Wales, or around 6,500 extrapolating to a UK level.

Title: Inferring the effective fraction of the population infected with Covid-19 from the behaviour of Lombardy, Madrid and London relative to the remainder of Italy, Spain and England Content: I use a very simple deterministic model for the spread of Covid-19 in a large population. Using this to compare the relative decay of the number of deaths per day between different regions in Italy, Spain and England, each applying in principle the same social distancing procedures across the whole country, I obtain an estimate of the total fraction of the population which had already become infected by April 10th. In the most heavily affected regions, Lombardy, Madrid and London, this fraction is higher than expected, i.e. $\approx 0.3$. This result can then be converted to a determination of the infection fatality rate $ifr$, which appears to be $ifr \approx 0.0025-0.005$, and even smaller in London, somewhat lower than usually assumed. Alternatively, the result can also be interpreted as an effectively larger fraction of the population than simple counting would suggest if there is a variation in susceptibility to infection with a variance of up to a value of about 2. The implications are very similar for either interpretation or for a combination of effects.

Title: Methods for estimating disease transmission rates: Evaluating the precision of Poisson regression and two novel methods Content: Precise estimates of disease transmission rates are critical for epidemiological simulation models. Most often these rates must be estimated from longitudinal field data, which are costly and time-consuming to conduct. Consequently, measures to reduce cost like increased sampling intervals or subsampling of the population are implemented. To assess the impact of such measures we implement two different SIS models to simulate disease transmission: A simple closed population model and a realistic dairy herd including population dynamics. We analyze the accuracy of different methods for estimating the transmission rate. We use data from the two simulation models and vary the sampling intervals and the size of the population sampled. We devise two new methods to determine transmission rate, and compare these to the frequently used Poisson regression method in both epidemic and endemic situations. For most tested scenarios these new methods perform similar or better than Poisson regression, especially in the case of long sampling intervals. We conclude that transmission rate estimates are easily biased, which is important to take into account when using these rates in simulation models.

Title: Childhood Infectious Diseases: Overview Content: Of the annual burden of 10 million deaths among children under 5 years, a large proportion is associated with infectious diseases. These include 36% of the 4 million newborn deaths due to sepsis, pneumonia, diarrhea, and tetanus. Among the postneonatal deaths due to infections, estimates and uncertainty bounds include: 22% of deaths attributed to diarrhea (14–30%), 21% to pneumonia (14–24%), 9% to malaria (6–13%), and 1% to measles (1–9%). Some 42 countries alone account for almost 90% of the global burden of child mortality. There is now sufficient evidence available on evidence-based interventions that can make a difference. It is estimated that almost two-thirds of these deaths are potentially preventable if interventions can be delivered at scale. Newborn infections and related mortality can be reduced by maternal tetanus toxoid vaccination, clean delivery, cord hygiene, exclusive and early breast-feeding, and prompt diagnosis and therapy. Diarrheal deaths can be prevented by adequate attention to breast-feeding, hand-washing and sanitation strategies, rota virus vaccine, adequate treatment including oral rehydration, appropriate dietary therapy, and oral zinc administration. Similarly, the global burden of pneumonia deaths can be reduced by vaccination strategies for measles, Hib, and pneumococcal disease, timely case detection, and treatment with appropriate antibiotics.

Title: Predicting the mortality due to Covid-19 by the next month for Italy, Iran and South Korea; a simulation study. Content: Aim To estimate the number of confirmed cases and the rate of death and also to investigate the cause of death in Italy, Iran and South Korea in the next month. Background Growing number of confirmed and deaths cases from the coronavirus worldwide, particularly in Italy, Iran and South Korea, has resulted concerns about the future of these countries and their deterioration. Also the European region is likely to face more casualties due to the delay in the virus reaching most of its regions and, of course, as the trend continues. Methods We conducted a simulation in both current and ideal situation for the next month to predict the death rate and examine the reason for the difference in Italy, Iran and South Korea individually. If we assume the cultural and political factors and age pyramids distribution are similar across regions, the differences are mainly due either to the heavier health-care burden owing to the larger population or to the medical facilities diversities. Results Our results for Italy showed higher death number, but the rate would be more for Iran. South Korea is also expected to have a smaller increase in the number of confirmed cases and deaths compared to Iran and Italy by the next month. Conclusion Given the prevailing conditions around the world and the increasing number of casualties, it is essential that all countries, especially those with fewer days of involvement, shall do their best to avoid major losses and damages.

Title: A comparative epidemiologic analysis of SARS in Hong Kong, Beijing and Taiwan Content: BACKGROUND: The 2002-2003 Severe Acute Respiratory Syndrome (SARS) outbreak infected 8,422 individuals leading to 916 deaths around the world. However, there have been few epidemiological studies of SARS comparing epidemiologic features across regions. The aim of this study is to identify similarities and differences in SARS epidemiology in three populations with similar host and viral genotype. METHODS: We present a comparative epidemiologic analysis of SARS, based on an integrated dataset with 3,336 SARS patients from Hong Kong, Beijing and Taiwan, epidemiological and clinical characteristics such as incubation, onset-to-admission, onset-to-discharge and onset-to-death periods, case fatality ratios (CFRs) and presenting symptoms are described and compared between regions. We further explored the influence of demographic and clinical variables on the apparently large differences in CFRs between the three regions. RESULTS: All three regions showed similar incubation periods and progressive shortening of the onset-to-admission interval through the epidemic. Adjusted for sex, health care worker status and nosocomial setting, older age was associated with a higher fatality, with adjusted odds ratio (AOR): 2.10 (95% confidence interval: 1.45, 3.04) for those aged 51-60; AOR: 4.57 (95% confidence interval: 3.32, 7.30) for those aged above 60 compared to those aged 41-50 years. Presence of pre-existing comorbid conditions was also associated with greater mortality (AOR: 1.74; 95% confidence interval: 1.36, 2.21). CONCLUSION: The large discrepancy in crude fatality ratios across the three regions can only be partly explained by epidemiological and clinical heterogeneities. Our findings underline the importance of a common data collection platform, especially in an emerging epidemic, in order to identify and explain consistencies and differences in the eventual clinical and public health outcomes of infectious disease outbreaks, which is becoming increasingly important in our highly interconnected world.

Title: The Effective Reproduction Number as a Prelude to Statistical Estimation of Time-Dependent Epidemic Trends Content: Although the basic reproduction number, R (0), is useful for understanding the transmissibility of a disease and designing various intervention strategies, the classic threshold quantity theoretically assumes that the epidemic first occurs in a fully susceptible population, and hence, R (0) is essentially a mathematically defined quantity. In many instances, it is of practical importance to evaluate time-dependent variations in the transmission potential of infectious diseases. Explanation of the time course of an epidemic can be partly achieved by estimating the effective reproduction number, R(t), defined as the actual average number of secondary cases per primary case at calendar time t (for t >0). R(t) shows time-dependent variation due to the decline in susceptible individuals (intrinsic factors) and the implementation of control measures (extrinsic factors). If R(t)<1, it suggests that the epidemic is in decline and may be regarded as being under control at time t (vice versa, if R(t)>1). This chapter describes the primer of mathematics and statistics of R(t) and discusses other similar markers of transmissibility as a function of time.

Title: Early and massive testing saves lives: COVID-19 related infections and deaths in the United States during March of 2020 Content: To optimize epidemiologic interventions, predictors of mortality should be identified. The US COVID-19 epidemic data, reported up to 31 March 2020, were analyzed using kernel regularized least squares regression. Six potential predictors of mortality were investigated: (i) the number of diagnostic tests performed in testing week I; (ii) the proportion of all tests conducted during week I of testing; (iii) the cumulative number of (test-positive) cases through 3-31-2020, (iv) the number of tests performed/million citizens; (v) the cumulative number of citizens tested; and (vi) the apparent prevalence rate, defined as the number of cases/million citizens. Two metrics estimated mortality: the number of deaths and the number of deaths/million citizens. While both expressions of mortality were predicted by the case count and the apparent prevalence rate, the number of deaths/million citizens was {approx}3.5 times better predicted by the apparent prevalence rate than the number of cases. In eighteen states, early testing/million citizens/population density was inversely associated with the cumulative mortality reported by 31 March, 2020. Findings support the hypothesis that early and massive testing saves lives. Other factors --e.g., population density-- may also influence outcomes. To optimize national and local policies, the creation and dissemination of high resolution geo-referenced, epidemic data is recommended.

Title: On Determining the Age Distribution of COVID-19 Pandemic Content: Pandemics tend to have higher occurrence (morbidity) in younger individuals but higher mortality for the elderly. The higher rate of mortality of COVID-19 in elderly individuals has been discussed in many reports. However, this pandemic is a double-edged sword as this comment shows higher morbidity rates in elderly as well. This is shown by comparing the age distribution of cases in China and South Korea to the relative populations. In every case, the relative number of elderly contracting the virus is far higher than the proportion of elderly in the population. This is unlike past pandemics and shows that aging populations are at an even higher risk than the perceived age dependent rates may imply.

Title: Scientific comment on"Tail risk of contagious diseases" Content: Cirillo and Taleb [Nature Phys. 16, 606-613 (2020)] study the size of major epidemics in human history in terms of the number of fatalities. Using the figures from 72 epidemics, from the plague of Athens (429 BC) to the COVID-19 (2019-2020), they claim that the resulting fatality distribution is ``extremely fat-tailed'', i.e., asymptotically a power law. This has important consequences for risk, as the mean value of the fatality distribution becomes infinite. Reanalyzing the same data, we find that, although the data may be compatible with a power-law tail, these results are not conclusive, and other distributions, not fat-tailed, could explain the data equally well. Simulation of a log-normally distributed random variable provides synthetic data whose statistics are undistinguishable from the statistics of the empirical data.

Title: Estimation of the true infection rate and infection fatality rate of COVID-19 in the whole population of each country Content: The true infection rate of COVID-19 and the infection fatality rate in the whole population have been estimated for each country. The estimate well coincided with local surveys. The fact that several tens of times, or more, of identified cases are already infected might require reconsideration of the strategy.

Title: Estimating finite-population reproductive numbers in heterogeneous populations Content: Abstract The basic reproductive number, R 0 , is one of the most important epidemiological quantities. R 0 provides a threshold for elimination and determines when a disease can spread or when a disease will die out. Classically, R 0 is calculated assuming an infinite population of identical hosts. Previous work has shown that heterogeneity in the host mixing rate increases R 0 in an infinite population. However, it has been suggested that in a finite population, heterogeneity in the mixing rate may actually decrease the finite-population reproductive numbers. Here, we outline a framework for discussing different types of heterogeneity in disease parameters, and how these affect disease spread and control. We calculate “finite-population reproductive numbers” with different types of heterogeneity, and show that in a finite population, heterogeneity has complicated effects on the reproductive number. We find that simple heterogeneity decreases the finite-population reproductive number, whereas heterogeneity in the intrinsic mixing rate (which affects both infectiousness and susceptibility) increases the finite-population reproductive number when R 0 is small relative to the size of the population and decreases the finite-population reproductive number when R 0 is large relative to the size of the population. Although heterogeneity has complicated effects on the finite-population reproductive numbers, its implications for control are straightforward: when R 0 is large relative to the size of the population, heterogeneity decreases the finite-population reproductive numbers, making disease control or elimination easier than predicted by R 0 .

Title: Injecting epidemiology into population viability analysis: avian cholera transmission dynamics at an arctic seabird colony. Content: Infectious diseases have the potential to spread rapidly and cause high mortality within populations of immunologically naïve hosts. The recent appearance of avian cholera, a highly virulent disease of birds caused by the bacterium Pasteurella multocida, at remote Arctic seabird colonies is an emerging conservation concern. Determining disease risk to population viability requires a quantitative understanding of transmission potential and the factors that regulate epidemic persistence. Estimates of the basic (R0 ) and real-time (Rt ) reproductive number are critical in this regard - enumerating the number of secondary infections caused by each primary infection in a newly invaded host population and the decline in transmission rate as susceptible individuals are removed via mortality or immunized recovery. Here, we use data collected at a closely monitored common eider (Somateria mollissima) breeding colony located in the Canadian Arctic to examine transmission and host population dynamics. Specifically, we infer epidemic curves from daily mortality observations and use a likelihood-based procedure to estimate changes in the reproductive number over a series of annual outbreaks. These data are interpreted in relation to concurrent changes in host numbers to assess local extinction risk. Consistent with expectations for a novel pathogen invasion, case incidence increased exponentially during the initial wave of exposure (R0 = 2·5; generation time = 6·5 days ± 1·1 SD). Disease conditions gradually abated, but only after several years of smouldering infection (Rt ≈ 1). In total, 6194 eider deaths were recorded during outbreaks spanning eight consecutive breeding seasons. Breeding pair abundance declined by 56% from the pre-outbreak peak; however, a robust population of >4000 pairs remained intact upon epidemic fade-out. Overall, outbreak patterns were consistent with herd immunity acting as a mitigating factor governing in the extent and duration of mortality. Disease mortality is frequently modelled as a form of stochastic catastrophe in wildlife population assessments, whereas our approach gives shape to the functional response between transmission and host population dynamics. We conclude that increased emphasis on integrating epidemiological and population processes is essential to predicting the conservation impact of emerging infectious diseases in wildlife.

Title: Estimating the case fatality rate using a constant cure-death hazard ratio. Content: The case fatality rate is an important indicator of the severity of a disease, and unbiased and accurate estimates of it during an outbreak are important in the study of epidemic diseases, including severe acute respiratory syndrome (SARS). In this paper, estimation methods are developed using a constant cure-death hazard ratio. A semiparametric model is presented, in which the cure-death hazard ratio is a parameter of interest, and a profile likelihood-based technique is proposed for estimating the case fatality rate. An extensive simulation was carried out to investigate the performance of this technique for small and medium sample sizes, using both summary and individual data. The results show that the performance depends on the model validity but is not heavily dependent on the sample size. The method was applied to summary SARS data obtained from Hong Kong and Singapore.

Title: Mortality from COVID-19 in 12 countries and 6 states of the United States Content: Importance: Reliable estimates of COVID-19 mortality are crucial to aid control strategies and to assess the effectiveness of interventions. Objective: Project COVID-19 mortality trends to October 1, 2020, in 12 countries or regions that constitute >90% of the global COVID-19 deaths reported as of April 12, 2020. Design, Setting, and Participants: The Global COVID-19 Assessment of Mortality (GCAM) is an open, transparent, and continuously updated (www.cghr.org/covid) statistical model that combines actual COVID-19 mortality counts with Bayesian inference to forecast COVID-19 deaths, the date of peak deaths, and the duration of excess mortality. The analyses covered a total of 700 million population above age 20 in 12 countries or regions: USA; Italy; Spain; France; UK; Iran; Belgium; a province of China (Hubei, which accounted for 90% of reported Chinese deaths); Germany; the Netherlands; Switzerland; and Canada; and six US states: New York, New Jersey, Michigan, Louisiana, California, and Washington. Results: Forecasted deaths across the 12 current high-burden countries sum 167,000 to 593,000 (median 253,000). The trajectory of US deaths (49,000-249,000 deaths; median 86,000)- over half of which are expected in states beyond the initial six states analysed in this study- will have the greatest impact on the eventual total. Mortality ranges are 25,000-109,000 (median 46,000) in the UK; 23,000-31,000 (median 26,000) in Italy; 21,000-37,000 (median 26,000) in France and 21,000-32,000 (median 25,000) in Spain. Estimates are most precise for Hubei, China, where the epidemic curve is complete, and least precise in California, where it is ongoing. New York has the highest cumulative median mortality rate per million (1135), about 12-fold that of Germany. Mortality trajectories are notably flatter in Germany, California, and Washington State, each of which took physical distancing and testing strategies seriously. Using past country-specific mortality as a guide, GCAM predicts surge capacity needs, reaching more than twice existing capacity in a number of places., In every setting, the results might be sensitive to undercounts of COVID-19 deaths, which are already apparent. Conclusion and Relevance: Mortality from COVID-19 will be substantial across many settings, even in the best case scenario. GCAM will provide continually updated and increasingly precise estimates as the pandemic progresses.

Title: Will COVID‐19 be a litmus test for post‐Ebola sub‐Saharan Africa? Content: In 2014, the worst outbreak of Ebola virus disease (EVD) emerged in sub-Saharan Africa (SSA) causing fear and panic. The outbreak which started in Guinea quickly moved across to Sierra Leone and Liberia. With an average EVD case fatality rate of around 50% (range 25-90%), there were many casualties, and the number of recorded deaths exceeded 11,300 by June 2016.1 This article is protected by copyright. All rights reserved.

Title: Differences by country-level income in COVID-19 cases, deaths, case-fatality rates, and rates per million population in the first five months of the pandemic Content: Abstract Objective: To describe differences by country-level income in COVID-19 cases, deaths, case-fatality rates, incidence rates, and death rates per million population. Methods: Publicly available data on COVID-19 cases and deaths from December 31, 2019 to June 3, 2020 were analyzed. Kruskal-Wallis tests were used to examine associations of country-level income with COVID-19 cases, deaths, case-fatality rates, incidence rates, and death rates. Results: A total of 380,803 deaths out of 6,348,204 COVID-19 cases were reported from 210 countries and territories globally in the period under study, and the global case-fatality rate was 6.0%. Of the total globally reported cases and deaths, the percentages of cases and deaths were 59.9% and 75.0% for high-income countries, and 30.9% and 20.7% for upper-middle-income countries. Countries in higher-income categories had higher incidence rates and death rates. Between April and May, the incidence rates in higher-income groups of countries decreased, but in other groups, it increased. Conclusions In the first five months of the COVID-19 pandemic, most cases and deaths were reported from high-income and upper-middle-income countries, and those countries had higher incidence rates and death rates per million population than did lower-middle and low-income countries. Keywords: COVID-19, incidence rate, death rate, case fatality rate, income, and country

Title: How do environmental, economic and health factors influence regional vulnerability to COVID-19? Content: We have studied the correlations between twelve environmental, economic and health variables, by carrying out a statistical analysis of the fatality rate of COVID-19 in 14 countries. Our statistical analysis indicates that, among the 12 variables, the diabetes percentage of the total population and the extent of the population ages 65 and older in each country are correlated most strongly with the total number of deaths in them. Although the strength of the correlations between the variables and the total ND may change as the ongoing pandemic evolves, the study highlights the importance of integrating regional-specific variables in the modelling efforts aimed at projecting how the spread of the virus may influence different parts of the world.

Title: Communicating the Risk of Death from Novel Coronavirus Disease (COVID-19) Content: To understand the severity of infection for a given disease, it is common epidemiological practice to estimate the case fatality risk, defined as the risk of death among cases. However, there are three technical obstacles that should be addressed to appropriately measure this risk. First, division of the cumulative number of deaths by that of cases tends to underestimate the actual risk because deaths that will occur have not yet observed, and so the delay in time from illness onset to death must be addressed. Second, the observed dataset of reported cases represents only a proportion of all infected individuals and there can be a substantial number of asymptomatic and mildly infected individuals who are never diagnosed. Third, ascertainment bias and risk of death among all those infected would be smaller when estimated using shorter virus detection windows and less sensitive diagnostic laboratory tests. In the ongoing COVID-19 epidemic, health authorities must cope with the uncertainty in the risk of death from COVID-19, and high-risk individuals should be identified using approaches that can address the abovementioned three problems. Although COVID-19 involves mostly mild infections among the majority of the general population, the risk of death among young adults is higher than that of seasonal influenza, and elderly with underlying comorbidities require additional care.

Title: Homicide rates among persons aged 10-24 years - United States, 1981-2010. Content: Homicide disproportionately affects persons aged 10-24 years in the United States and consistently ranks in the top three leading causes of death in this age group, resulting in approximately 4,800 deaths and an estimated $9 billion in lost productivity and medical costs in 2010. To investigate trends in homicide among persons aged 10-24 years for the period 1981-2010, CDC analyzed National Vital Statistics System data on deaths caused by homicide of persons in this age group and examined trends by sex, age, race/ethnicity, and mechanism of injury. This report describes the results of that analysis, which indicated that homicide rates varied substantially during the study period, with a sharp rise from 1985 to 1993 followed by a decline that has slowed since 1999. During the period 2000-2010, rates declined for all groups, although the decline was significantly slower for males compared with females and for blacks compared with Hispanics and persons of other racial/ethnic groups. By mechanism of injury, the decline for firearm homicides from 2000 to 2010 was significantly slower than for nonfirearm homicides. The homicide rate among persons aged 10-24 years in 2010 was 7.5 per 100,000, the lowest in the 30-year study period. Primary prevention strategies remain critical, particularly among groups at increased risk for homicide.

Title: SARS hits hard Content: Death rates higher than expected, but control measures seem to be working.

Title: Epidemiologie Content: Früher wurde der Begriff Epidemiologie für die Lehre von den großen, menschheitsbedrohenden Seuchen benutzt. Heute versteht man darunter die Wissenschaft von allen übertragbaren und nichtübertragbaren Krankheiten in einer Population, unabhängig davon, ob sie zeitlich oder räumlich gehäuft auftreten. Im Bereich der Mikrobiologie befasst sich die Epidemiologie mit Erkrankungen, die durch übertragbare Agenzien wie Bakterien, Viren oder auch Prionen verursacht werden, und zwar insbesondere mit deren Verbreitung und den Infektionsfolgen. Epidemiologische Untersuchungen besitzen somit eine große Bedeutung für die Gesundheit der Weltbevölkerung und sind die Grundlage für allgemein- und seuchenhygienische Maßnahmen wie Quarantäne oder Impfungen zur Verhinderung oder Eindämmung von Pandemien und Epidemien. Sie ermöglichen außerdem die Entwicklung von Richtlinien und Vorschriften für Impfungen und andere Maßnahmen zur Verhütung von Infektionen.

Title: COVID-19, Australia: Epidemiology Report 10 (Reporting week to 23:59 AEST 5 April 2020) Content: Confirmed cases in Australia notified up to 5 April 2020: Notifications = 5,805; Deaths = 33. Notifications in Australia remain predominantly among people with recent overseas travel, with some locally-acquired cases being detected. Most locally-acquired cases are able to be linked back to a confirmed case, with a small portion unable to be epidemiologically link. The distribution of overseas-acquired cases to locally acquired cases varies by jurisdiction. Early indications are that reduction in international travel, domestic movement, social distancing measures and public health action are slowing the spread of the disease. Internationally, cases continue to increase, with high rates of increase observed in the European region and the United States of America. The epidemiology differs from country to country depending not only on the disease, but also on differences in case detection, testing and implemented public health measures.

Title: COVID-19, Australia: Epidemiology Report 10 (Reporting week to 23:59 AEST 5 April 2020). Content: Confirmed cases in Australia notified up to 5 April 2020: Notifications = 5,805; Deaths = 33. Notifications in Australia remain predominantly among people with recent overseas travel, with some locally-acquired cases being detected. Most locally-acquired cases are able to be linked back to a confirmed case, with a small portion unable to be epidemiologically link. The distribution of overseas-acquired cases to locally acquired cases varies by jurisdiction. Early indications are that reduction in international travel, domestic movement, social distancing measures and public health action are slowing the spread of the disease. Internationally, cases continue to increase, with high rates of increase observed in the European region and the United States of America. The epidemiology differs from country to country depending not only on the disease, but also on differences in case detection, testing and implemented public health measures.

Title: The association between Ostertagia ostertagi antibodies in bulk tank milk samples and parameters linked to cattle reproduction and mortality Content: Abstract In Western Europe, gastrointestinal nematodes are widespread in dairy cattle. This study was carried out to evaluate the relationship between optical density ratio (ODR) measured on bulk tank milk with an indirect Ostertagia ostertagi ELISA and reproduction/mortality parameters. Data were collected between 2008 and 2010 from monitoring carried out on 1643 dairy herds (Normandy, Western France). ODR values of 3 samples from each farm taken from November 2008 to 2010 were averaged and then transformed into a categorical variable. Reproductive and mortality data were obtained from 1444 herds using cow records from government databases. Statistical analysis was carried out using ordinary logistic regression (OLR). The outcome variables were the case–control status of a herd for reproductive factors, age at first calving and inter-calving intervals, and mortality ratios of various age classes. The effect of the categorical ODR variable was studied and several potential confounder herd factors were used to improve the model fit. A significant relationship was found between high Ostertagia ODR levels and a late age at the first calving (>34.5 months) (odds ratio (OR)=1.94, p <0.001). No significant relationship was observed with OLR for inter-calving intervals although bivariate analysis showed that herds with high ODR levels had longer inter-calving intervals than herds with low ODR level (first inter-calving interval in herds with low vs. high ODR levels=412 days vs. 422 days, p <0.001; other inter-calving intervals=408 days vs. 413 days, p <0.01). A high ODR level was also associated with high mortality of calves between 0 and 30 days of life (mortality ratio>6%) (OR=1.43, p <0.05) and between 91 and 365 days (ratio>3%) (OR=1.72, p <0.01). No significant relationship was observed with multivariate approach for mortalities in other classes by age, but bivariate analysis showed that herds with high ODR level had higher mortalities than herds with low ODR levels (mortality between 31 and 90 days in herds with low vs. high ODR levels=1.89% vs. 2.91%, p <0.001; mortality after 365 days=1.67% vs. 2.93%, p <0.001). In conclusion, our results confirm the usefulness of ELISA as an indicator for production losses in dairy herds. This inexpensive tool could be advantageous, used to aid farmers and veterinarians to carry out appropriate control measures.

Title: Apoptosis and Cell Death: Relevance to Lung Content: In multicellular organisms, cell death plays an important role in development, morphogenesis, control of cell numbers, and removal of infected, mutated, or damaged cells. The term apoptosis was first coined in 1972 by Kerr et al.1 to describe the morphologic features of a type of cell death that is distinct from necrosis and is today considered to represent programmed cell death. In fact, the evidence that a genetic program existed for physiologic cell death came from the developmental studies of the nematode Caenorhabditis elegans.2 As time has progressed, however, apoptotic cell death has been shown to occur in many cell types under a variety of physiologic and pathologic conditions. Cells dying by apoptosis exhibit several characteristic morphologic features that include cell shrinkage, nuclear condensation, membrane blebbing, nuclear and cellular fragmentation into membrane-bound apoptotic bodies, and eventual phagocytosis of the fragmented cell (Figure 4.1).

Title: Changing pattern of premature mortality burden over 6 years of rapid growth of the economy in suburban south-west China: 1998–2003 Content: Summary Background This study was conducted in Kunming, the capital of Yunnan, a poor province in south-west China experiencing rapid economic growth. The study examined the short-term trend in premature mortality burden from common causes of death in a suburban region between 1998 and 2003. Methods Years of life lost (YLL) per 1000 population and mortality rate per 100,000 population were calculated from medical death certificates, and broken down by cause of death, sex and year without age weighting but with a discounting rate of 3%. Results Non-communicable diseases contributed over 80% of all causes of YLL, with a slightly increasing trend. The combined rate for communicable, maternal, prenatal and nutritional deficiencies declined from 4.7 to 2.4 per 1000 population. Remarkably, declining trends in YLL were also seen for chronic obstructive pulmonary disease, drug use and road traffic accidents, whereas increasing trends were seen for ischaemic heart disease (IHD) and liver cancer (males). The YLL rate for stroke, self-inflicted injuries, lung cancer and stomach cancer fluctuated over time. Conclusions The region should focus on further control of IHD and liver cancer.

Title: Determinants for autopsy after unexplained deaths possibly resulting from infectious causes, United States. Content: We analyzed US multiple cause-of-death data for 2003-2006 for demographic and clinical determinants for autopsy in unexplained deaths possibly resulting from infectious causes. For 96,242 deaths, the definition for unexplained death was met and autopsy status was recorded. Most decedents were male, 40-49 years of age, and white. To identify factors associated with unexplained death, we used data from Arizona records. Multivariate analysis of Arizona records suggested that decedents of races other than white and black and decedents who had clinicopathologic syndromes in the cardiovascular, sepsis/shock, and multisyndrome categories recorded on the death certificate were least likely to have undergone autopsy; children with unexplained death were the most likely to have undergone autopsy. Improved understanding of unexplained deaths can provide opportunities for further studies, strengthen collaboration between investigators of unexplained deaths, and improve knowledge and awareness of infectious diseases of public health concern.

Title: Health Inequalities, General Trends in Mortality and Morbidity, and Associated Factors Content: All measures of health status are ultimately derived from observations of individuals. At the field level we have such measures as self-assessed health status, report of a specific disease, record of a particular death, or an individual’s test on a biomarker, such as blood pressure or serum cholesterol. The observations for individuals are combined and summarized to represent subnational geographic areas, demographic or socioeconomic groups within countries, or national populations. The summary measures, whether they are percentages, averages, or rates, apply to groups. A problem arises when the measures that are based on groups are assumed to represent individuals. The analysis becomes especially problematic when the units analyzed are geographic areas and inferences are being made about individuals from the analysis for these geographic areas.