Question: how has lack of testing availability led to underreporting of true incidence of Covid-19?

Title: ¿Conocemos las propiedades diagnósticas de las pruebas usadas en COVID-19? Una revisión rápida de la literatura recientemente publicada./ ¿Conocemos las propiedades diagnósticas de las pruebas usadas en COVID-19? Una revisión rápida de la literatura recientemente publicada./ Do we know the diagnostic properties of the tests used in COVID-19? A rapid review of recently published literature Content: COVID-19 has brought death and disease to large parts of the world. Governments must deploy strategies to screen the population and subsequently isolate the suspect cases. Diagnostic testing is critical for epidemiological surveillance, but the accuracy (sensitivity and specificity) and clinical utility (impact on health outcomes) of the current diagnostic methods used for SARS-CoV-2 detection are not known. I ran a quick search in PubMed/MEDLINE to find studies on laboratory diagnostic tests and rapid viral diagnosis. After running the search strategies, I found 47 eligible articles that I discuss in this review, commenting on test characteristics and limitations. I did not find any papers that report on the clinical utility of the tests currently used for COVID-19 detection, meaning that we are fighting a battle without proper knowledge of the proportion of false negatives that current testing is resulting in. This shortcoming should not be overlooked as it might hamper national efforts to contain the pandemic through testing community-based suspect cases.

Title: Do we know the diagnostic properties of the tests used in COVID-19? A rapid review of recently published literature. Content: COVID-19 has brought death and disease to large parts of the world. Governments must deploy strategies to screen the population and subsequently isolate the suspect cases. Diagnostic testing is critical for epidemiological surveillance, but the accuracy (sensitivity and specificity) and clinical utility (impact on health outcomes) of the current diagnostic methods used for SARS-CoV-2 detection are not known. I ran a quick search in PubMed/MEDLINE to find studies on laboratory diagnostic tests and rapid viral diagnosis. After running the search strategies, I found 47 eligible articles that I discuss in this review, commenting on test characteristics and limitations. I did not find any papers that report on the clinical utility of the tests currently used for COVID-19 detection, meaning that we are fighting a battle without proper knowledge of the proportion of false negatives that current testing is resulting in. This shortcoming should not be overlooked as it might hamper national efforts to contain the pandemic through testing community-based suspect cases.

Title: The challenges of covid-19 testing: Time for pathologists to rise to the occasion Content: An outbreak of novel coronavirus (Covid-19) was first reported in Wuhan, China in the late December 1 Since then, the positive cases have increased exponentially to 1 4 million (as of 8 April 2020) 2 The ability of a country to cope with increasing number of Covid-19 testing is the ultimate test Teaching/university hospitals should pull their resources and man-power to provide the muchneeded assistance to the demand of Covid-19 testing Inadequate testing could result in unrecognised Covid-19 infected individuals, roaming freely in the population The other issue is the sensitivity of test if samples were obtained from different sites Classically, the confirmation of diagnosis of Covid-19 depends on real time polymerase chain reaction (RT-PCR) analysis to detect viral genetic material in either a nasal swab or bronchioalveolar lavage sample Wang et al (2020) reported that bronchioalveolar lavage sample has the highest sensitivity in identifying Covid-19, followed by sputum and nasal swab with positive rates of 93%, 72% and 63%, respectively 3 Furthermore, they found that nasal swab contained the highest concentration of viral load as it required less number of cycles to achieve higher copy numbers In some patients, viral genetic material was also identified in faeces and blood 3 While the reliability of testing is a concern, the safety of the laboratory staff also has to be kept in mind In this issue, there are three review articles on Covid-19, first article described the general properties of coronavirus, second article described the diagnostic performance of Covid-19 serology assay and third article described the importance of the site of sampling for Covid-19 4-6

Title: Testing for SARS-CoV-2: Can We Stop at Two? Content: The COVID-19 epidemic requires accurate identification and isolation of confirmed cases for effective control. This report describes the effectiveness of our testing strategy and highlights the importance of repeat testing in suspect cases in our cohort.

Title: Statistically-based methodology for revealing real contagion trends and correcting delay-induced errors in the assessment of COVID-19 pandemic Content: COVID-19 pandemic has reshaped our world in a timescale much shorter than what we can understand. Particularities of SARS-CoV-2, such as its persistence in surfaces and the lack of a curative treatment or vaccine against COVID-19, have pushed authorities to apply restrictive policies to control its spreading. As data drove most of the decisions made in this global contingency, their quality is a critical variable for decision-making actors, and therefore should be carefully curated. In this work, we analyze the sources of error in typically reported epidemiological variables and usual tests used for diagnosis, and their impact on our understanding of COVID-19 spreading dynamics. We address the existence of different delays in the report of new cases, induced by the incubation time of the virus and testing-diagnosis time gaps, and other error sources related to the sensitivity/specificity of the tests used to diagnose COVID-19. Using a statistically-based algorithm, we perform a temporal reclassification of cases to avoid delay-induced errors, building up new epidemiologic curves centered in the day where the contagion effectively occurred. We also statistically enhance the robustness behind the discharge/recovery clinical criteria in the absence of a direct test, which is typically the case of non-first world countries, where the limited testing capabilities are fully dedicated to the evaluation of new cases. Finally, we applied our methodology to assess the evolution of the pandemic in Chile through the Effective Reproduction Number R(t), identifying different moments in which data was misleading governmental actions. In doing so, we aim to raise public awareness of the need for proper data reporting and processing protocols for epidemiological modelling and predictions.

Title: Substantial underestimation of SARS-CoV-2 infection in the United States due to incomplete testing and imperfect test accuracy Content: Accurate estimates of the burden of SARS-CoV-2 infection are critical to informing pandemic response. Current confirmed COVID-19 case counts in the U.S. do not capture the total burden of the pandemic because testing has been primarily restricted to individuals with moderate to severe symptoms due to limited test availability. Using a semi-Bayesian probabilistic bias analysis to account for incomplete testing and imperfect diagnostic accuracy, we estimated 6,275,072 cumulative infections compared to 721,245 confirmed cases (1.9% vs. 0.2% of the population) as of April 18, 2020. Accounting for uncertainty, the number of infections was 3 to 20 times higher than the number of confirmed cases. 86% (simulation interval: 64-99%) of this difference was due to incomplete testing, while 14% (0.3-36%) was due to imperfect test accuracy. Estimates of SARS-CoV-2 infections that transparently account for testing practices and diagnostic accuracy reveal that the pandemic is larger than confirmed case counts suggest.

Title: Global analysis of daily new COVID-19 cases reveals many static-phase countries including US and UK potentially with unstoppable epidemics Content: The COVID-19 epidemics are differentially progressing in different countries. Here, comparative analyses of daily new cases reveal that 61 most affected countries can be classified into four types: downward (22), upward (20), static-phase (12) and uncertain ones (7). In particular, the 12 static-phase countries including US and UK are characterized by largely constant numbers of daily new cases in the past over 14 days. Furthermore, these static-phase countries are overall significantly lower in testing density but higher in the level of positive COVID-19 tests than downward countries. These findings suggest that the testing capacity in static-phase countries is lagging behind the spread of the outbreak, i.e., daily new cases (confirmed) are likely less than daily new infections and the remaining undocumented infections are thus still expanding, resulting in unstoppable epidemics. As such, increasing the testing capacity and/or reducing the COVID-19 transmission are urgently needed to stop the severing crisis in static-phase countries.

Title: Severe underestimation of COVID-19 case numbers: effect of epidemic growth rate and test restrictions Content: To understand the scope and development of the COVID-19 pandemic, knowledge of the number of infected persons is essential. Often, the number of "confirmed cases", which is based on positive RT-PCR test results, is regarded as a reasonable indicator. However, limited COVID-19 test capacities in many countries are restricting the amount of testing that can be done. This can lead to the implementation of testing policies that restrict access to COVID-19 tests, and to testing backlogs and delays. As a result, confirmed case numbers can be significantly lower than the actual number of infections, especially during rapid growth phases of the epidemic. This study examines the quantitative relation between infections and reported confirmed case numbers for two different testing strategies, "limited" and "inclusive" testing, in relation to the growth rate of the epidemic. The results indicate that confirmed case numbers understate the actual number of infections substantially; during rapid growth phases where the daily growth rate can reach or exceed 30%, as has been seen in many countries, the confirmed case numbers under-report actual infections by up to 50 to 100-fold.

Title: The Challenge of Using Epidemiological Case Count Data: The Example of Confirmed COVID-19 Cases and the Weather Content: The publicly available data on COVID-19 cases provides an opportunity to better understand this new disease. However, strong attention needs to be paid to the limitations of the data to avoid making inaccurate conclusions. This article, which focuses on the relationship between the weather and COVID-19, raises the concern that the same factors influencing the spread of the disease might also affect the number of tests performed and who gets tested. For example, weather conditions impact the prevalence of respiratory diseases with symptoms similar to COVID-19, and this will likely influence the number of tests performed. This general limitation could severely undermine any similar analysis using existing COVID-19 data or similar epidemiological data, which could, therefore, mislead decision-makers on questions of great policy relevance.

Title: COVID-19: Are Africa’s diagnostic challenges blunting response effectiveness? Content: Since its emergence in Wuhan, China in December 2019, novel Coronavirus disease - 2019 (COVID-19) has rapidly spread worldwide, achieving pandemic status on 11 (th) March, 2020. As of 1 (st) April 2020, COVID-19, which is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), had infected over 800,000 people and caused over 40,000 deaths in 205 countries and territories. COVID-19 has had its heaviest toll on Europe, United States and China. As of 1 (st) of April 2020, the number of confirmed COVID-19 cases in Africa was relatively low, with the highest number registered by South Africa, which had reported 1,380 confirmed cases. On the same date (also the date of this review), Africa had reported 5,999 confirmed cases, of which 3,838 (almost 65%) occurred in South Africa, Algeria, Egypt, Morocco and Tunisia, with the remaining 2,071 cases distributed unevenly across the other African countries. We speculate that while African nations are currently experiencing much lower rates of COVID-19 relative to other continents, their significantly lower testing rates may grossly underestimate incidence rates. Failure to grasp the true picture may mean crucial windows of opportunity shut unutilized, while limited resources are not deployed to maximum effect. In the absence of extensive testing data, an overestimation of spread may lead to disproportionate measures being taken, causing avoidable strain on livelihoods and economies. Here, based on the African situation, we discuss COVID-19 diagnostic challenges and how they may blunt responses.

Title: COVID-19: Should We Test Everyone? Content: Since the beginning of 2020, the coronavirus disease 2019 (COVID-19) has spread rapidly in the city of Wuhan, P.R. China, and subsequently, across the world. The swift spread of the virus is largely attributed to its stealth transmissions in which infected patients may be asymptomatic. Undetected transmissions present a remarkable challenge for the containment of the virus and pose an appalling threat to the public. An urgent question that has been asked by the public is"Should I be tested for COVID-19 if I am sick?". While different regions established their own criteria for screening infected cases, the screening criteria have been modified based on new evidence and understanding of the virus as well as the availability of resources. The shortage of test kits and medical personnel has considerably limited our ability to do as many tests as possible. Public health officials and clinicians are facing a dilemma of balancing the limited resources and unlimited demands. On one hand, they are striving to achieve the best outcome by optimizing the usage of the scant resources. On the other hand, they are challenged by the patients' frustrations and anxieties, stemming from the concerns of not being tested for COVID-19 for not meeting the definition of PUI (person under investigation). In this paper, we evaluate the situation from the statistical viewpoint by factoring into the considerations of the uncertainty and inaccuracy of the test, an issue that is often overlooked by the general public. We aim to shed light on the tough situation by providing evidence-based reasoning from the statistical angle, and we expect this examination will help the general public understand and assess the situation rationally. Most importantly, the development offers recommendations for physicians to make sensible evaluations to optimally use the limited resources for the best medical outcome.

Title: False positives in reverse transcription PCR testing for SARS-CoV-2 Content: Background: Large-scale testing for SARS-CoV-2 by RT-PCR is a key element of the response to COVID-19, but little attention has been paid to the potential frequency and impacts of false positives. Method: From a meta-analysis of external quality assessments of RT-PCR assays of RNA viruses, we derived a conservative estimate of the range of false positive rates that can reasonably be expected in SARS-CoV-2 testing, and analyzed the effect of such rates on analyses of regional test data and estimates of population prevalence and asymptomatic ratio. Findings: Review of external quality assessments revealed false positive rates of 0-16.7%, with an interquartile range of 0.8-4.0%. Such rates would have large impacts on test data when prevalence is low. Inclusion of such rates significantly alters four published analyses of population prevalence and asymptomatic ratio. Interpretation: The high false discovery rate that results, when prevalence is low, from false positive rates typical of RT-PCR assays of RNA viruses raises questions about the usefulness of mass testing; and indicates that across a broad range of likely prevalences, positive test results are more likely to be wrong than are negative results, contrary to public health advice about SARS-CoV-2 testing. There are myriad clinical and case management implications. Failure to appreciate the potential frequency of false positives and the consequent unreliability of positive test results across a range of scenarios could unnecessarily remove critical workers from service, expose uninfected individuals to greater risk of infection, delay or impede appropriate medical treatment, lead to inappropriate treatment, degrade patient care, waste personal protective equipment, waste human resources in unnecessary contact tracing, hinder the development of clinical improvements, and weaken clinical trials. Measures to raise awareness of false positives, reduce their frequency, and mitigate their effects should be considered.

Title: SARS-CoV2 Testing: The Limit of Detection Matters Content: Resolving the COVID-19 pandemic requires diagnostic testing to determine which individuals are infected and which are not. The current gold standard is to perform RT-PCR on nasopharyngeal samples. Best-in-class assays demonstrate a limit of detection (LoD) of ~100 copies of viral RNA per milliliter of transport media. However, LoDs of currently approved assays vary over 10,000-fold. Assays with higher LoDs will miss more infected patients, resulting in more false negatives. However, the false-negative rate for a given LoD remains unknown. Here we address this question using over 27,500 test results for patients from across our healthcare network tested using the Abbott RealTime SARS-CoV-2 EUA. These results suggest that each 10-fold increase in LoD is expected to increase the false negative rate by 13%, missing an additional one in eight infected patients. The highest LoDs on the market will miss a majority of infected patients, with false negative rates as high as 70%. These results suggest that choice of assay has meaningful clinical and epidemiological consequences. The limit of detection matters.

Title: Estimating the COVID-19 infection rate: Anatomy of an inference problem Content: As a consequence of missing data on tests for infection and imperfect accuracy of tests, reported rates of cumulative population infection by the SARS CoV-2 virus are lower than actual rates of infection. Hence, reported rates of severe illness conditional on infection are higher than actual rates. Understanding the time path of the COVID-19 pandemic has been hampered by the absence of bounds on infection rates that are credible and informative. This paper explains the logical problem of bounding these rates and reports illustrative findings, using data from Illinois, New York, and Italy. We combine the data with assumptions on the infection rate in the untested population and on the accuracy of the tests that appear credible in the current context. We find that the infection rate might be substantially higher than reported. We also find that the infection fatality rate in Illinois, New York, and Italy is substantially lower than reported.

Title: Towards reduction in bias in epidemic curves due to outcome misclassification through Bayesian analysis of time-series of laboratory test results: case study of COVID-19 in Alberta, Canada and Philadelphia, USA Content: BACKGROUND: Despite widespread use, the accuracy of the diagnostic test for SARS-CoV-2 infection is poorly understood. The aim of our work was to better quantify misclassification errors in identification of true cases of COVID-19 and to study the impact of these errors in epidemic curves using publicly available surveillance data from Alberta, Canada and Philadelphia, USA. METHODS: We examined time-series data of laboratory tests for SARS-CoV-2 viral infection, the causal agent for COVID-19, to try to explore, using a Bayesian approach, the sensitivity and specificity of the diagnostic test. RESULTS: Our analysis revealed that the data were compatible with near-perfect specificity, but it was challenging to gain information about sensitivity. We applied these insights to uncertainty/bias analysis of epidemic curves under the assumptions of both improving and degrading sensitivity. If the sensitivity improved from 60 to 95%, the adjusted epidemic curves likely falls within the 95% confidence intervals of the observed counts. However, bias in the shape and peak of the epidemic curves can be pronounced, if sensitivity either degrades or remains poor in the 60–70% range. In the extreme scenario, hundreds of undiagnosed cases, even among the tested, are possible, potentially leading to further unchecked contagion should these cases not self-isolate. CONCLUSION: The best way to better understand bias in the epidemic curves of COVID-19 due to errors in testing is to empirically evaluate misclassification of diagnosis in clinical settings and apply this knowledge to adjustment of epidemic curves.

Title: Towards reduction in bias in epidemic curves due to outcome misclassification through Bayesian analysis of time-series of laboratory test results: case study of COVID-19 in Alberta, Canada and Philadelphia, USA Content: BACKGROUND: Despite widespread use, the accuracy of the diagnostic test for SARS-CoV-2 infection is poorly understood. The aim of our work was to better quantify misclassification errors in identification of true cases of COVID-19 and to study the impact of these errors in epidemic curves using publicly available surveillance data from Alberta, Canada and Philadelphia, USA. METHODS: We examined time-series data of laboratory tests for SARS-CoV-2 viral infection, the causal agent for COVID-19, to try to explore, using a Bayesian approach, the sensitivity and specificity of the diagnostic test. RESULTS: Our analysis revealed that the data were compatible with near-perfect specificity, but it was challenging to gain information about sensitivity. We applied these insights to uncertainty/bias analysis of epidemic curves under the assumptions of both improving and degrading sensitivity. If the sensitivity improved from 60 to 95%, the adjusted epidemic curves likely falls within the 95% confidence intervals of the observed counts. However, bias in the shape and peak of the epidemic curves can be pronounced, if sensitivity either degrades or remains poor in the 60-70% range. In the extreme scenario, hundreds of undiagnosed cases, even among the tested, are possible, potentially leading to further unchecked contagion should these cases not self-isolate. CONCLUSION: The best way to better understand bias in the epidemic curves of COVID-19 due to errors in testing is to empirically evaluate misclassification of diagnosis in clinical settings and apply this knowledge to adjustment of epidemic curves.

Title: The Appropriate Use of Testing for COVID-19 Content: Many public officials are calling for increased testing for the 2019 novel coronavirus disease (COVID-19), and some governments have taken extraordinary measures to increase the availability of testing. However, little has been published about the sensitivity and specificity of the reverse transcriptase-polymerase chain reaction (RT-PCR) nasopharyngeal swabs that are commonly used for testing. This narrative review evaluates the literature regarding the accuracy of these tests, and makes recommendations based on this literature. In brief, a negative RT-PCR nasopharyngeal swab test is insufficient to rule out COVID-19. Thus, over-reliance on the results of the test may be dangerous, and the push for widespread testing may be overstated.

Title: Estimating the true (population) infection rate for COVID-19: A Backcasting Approach with Monte Carlo Methods Content: Differences in COVID-19 testing and tracing across countries, as well as changes in testing within each country over time, make it difficult to estimate the true (population) infection rate based on the confirmed number of cases obtained through RNA viral testing. We applied a backcasting approach, coupled with Monte Carlo methods, to estimate a distribution for the true (population) cumulative number of infections (infected and recovered) for 15 countries where reliable data are available. We find a positive relationship between the testing rate per 1,000 people and the implied true detection rate of COVID-19, and a negative relationship between the proportion who test positive and the implied true detection rate. Our estimates suggest that the true number of people infected across our sample of 15 developed countries is 18.2 (5-95% CI: 11.9-39.0) times greater than the reported number of cases. In individual countries, the true number of cases exceeds the reported figure by factors that range from 1.7 (5-95% CI: 1.1-3.6) for Australia to 35.6 (5-95% CI: 23.2-76.3) for Belgium.

Title: SARS-CoV-2 Laboratory Testing in India's Pandemic Response: A Public Health Perspective. Content: Coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has resulted (at the time of writing) in over 3.3 million cases and 233,000 deaths globally and ~33,000 cases and ~1,100 deaths in India. The mainstay of the diagnosis is a reverse-transcription polymerase chain reaction assay to detect SARS-CoV-2 RNA. The accurate diagnosis is contingent on appropriate specimen choice, time of collection, and assay employed. In this commentary, we highlight the role of laboratory diagnostic tests used in the different stages of India's COVID-19 pandemic response.

Title: SARS-CoV-2 Laboratory Testing in India's Pandemic Response: A Public Health Perspective Content: Coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has resulted (at the time of writing) in over 3.3 million cases and 233,000 deaths globally and ~33,000 cases and ~1,100 deaths in India. The mainstay of the diagnosis is a reverse-transcription polymerase chain reaction assay to detect SARS-CoV-2 RNA. The accurate diagnosis is contingent on appropriate specimen choice, time of collection, and assay employed. In this commentary, we highlight the role of laboratory diagnostic tests used in the different stages of India's COVID-19 pandemic response.

Title: Disentangling Increased Testing From Covid-19 Epidemic Spread Content: To design effective disease control strategies, it is critical to understand the incidence of diseases. In the Covid-19 epidemic in the United States (caused by outbreak of the SARS-CoV-2 virus), testing capacity was initially very limited and has been increasing at the same time as the virus has been spreading. When estimating the incidence, it can be difficult to distinguish whether increased numbers of positive tests stem from increases in the spread of the virus or increases in testing. This has made it very difficult to identify locations in which the epidemic poses the largest public health risks. Here, we use a probabilistic model to quantify beliefs about testing strategies and understand implications regarding incidence. We apply this model to estimate the incidence in each state of the United States, and find that: (1) the Covid-19 epidemic is likely to be more widespread than reported by limited testing, (2) the Covid-19 epidemic growth in the summer months is likely smaller than it was during the spring months, and (3) the regions which are at highest risk of Covid-19 epidemic outbreaks are not always those with the largest number of positive test results.

Title: Estimating the COVID-19 Infection Rate: Anatomy of an Inference Problem Content: As a consequence of missing data on tests for infection and imperfect accuracy of tests, reported rates of population infection by the SARS CoV-2 virus are lower than actual rates of infection. Hence, reported rates of severe illness conditional on infection are higher than actual rates. Understanding the time path of the COVID-19 pandemic has been hampered by the absence of bounds on infection rates that are credible and informative. This paper explains the logical problem of bounding these rates and reports illustrative findings, using data from Illinois, New York, and Italy. We combine the data with assumptions on the infection rate in the untested population and on the accuracy of the tests that appear credible in the current context. We find that the infection rate might be substantially higher than reported. We also find that the infection fatality rate in Italy is substantially lower than reported.

Title: Urgent need for individual mobile phone and institutional reporting of at home, hospitalized, and intensive care unit cases of SARS-CoV-2 (COVID-19) infection Content: Approximately 90 days of the SARS-CoV-2 (COVID-19) spreading originally from Wuhan, China, and across the globe has led to a widespread chain of events with imminent threats to the fragile relationship between community health and economic health. Despite near hourly reporting on this crisis, there has been no regular, updated, or accurate reporting of hospitalizations for COVID-19. It is known that many test-positive individuals may not develop symptoms or have a mild self-limited viral syndrome consisting of fever, malaise, dry cough, and constitutional symptoms. However some individuals develop a more fulminant syndrome including viral pneumonia, respiratory failure requiring oxygen, acute respiratory distress syndrome requiring mechanical ventilation, and in substantial fractions leading to death attributable to COVID-19. The pandemic is evolving in a clustered, non-inform fashion resulting in many hospitals with preparedness but few or no cases, and others that are completely overwhelmed. Thus, a considerable risk of spread when personal protection equipment becomes exhausted and a large fraction of mortality in those not offered mechanical ventilation are both attributable to a crisis due to maldistribution of resources. The pandemic is amenable to self-reporting through a mobile phone application that could obtain critical information on suspected cases and report on the results of self testing and actions taken. The only method to understand the clustering and the immediate hospital resource needs is mandatory, uniform, daily reporting of hospital censuses of COVID-19 cases admitted to hospital wards and intensive care units. Current reports of hospitalizations are delayed, uncertain, and wholly inadequate. This paper urges all the relevant stakeholders to take up self-reporting and reporting of hospitalizations of COVID-19 as an urgent task in combating this devastating pandemic.

Title: Urgent need for individual mobile phone and institutional reporting of at home, hospitalized, and intensive care unit cases of SARS-CoV-2 (COVID-19) infection. Content: Approximately 90 days of the SARS-CoV-2 (COVID-19) spreading originally from Wuhan, China, and across the globe has led to a widespread chain of events with imminent threats to the fragile relationship between community health and economic health. Despite near hourly reporting on this crisis, there has been no regular, updated, or accurate reporting of hospitalizations for COVID-19. It is known that many test-positive individuals may not develop symptoms or have a mild self-limited viral syndrome consisting of fever, malaise, dry cough, and constitutional symptoms. However some individuals develop a more fulminant syndrome including viral pneumonia, respiratory failure requiring oxygen, acute respiratory distress syndrome requiring mechanical ventilation, and in substantial fractions leading to death attributable to COVID-19. The pandemic is evolving in a clustered, non-inform fashion resulting in many hospitals with preparedness but few or no cases, and others that are completely overwhelmed. Thus, a considerable risk of spread when personal protection equipment becomes exhausted and a large fraction of mortality in those not offered mechanical ventilation are both attributable to a crisis due to maldistribution of resources. The pandemic is amenable to self-reporting through a mobile phone application that could obtain critical information on suspected cases and report on the results of self testing and actions taken. The only method to understand the clustering and the immediate hospital resource needs is mandatory, uniform, daily reporting of hospital censuses of COVID-19 cases admitted to hospital wards and intensive care units. Current reports of hospitalizations are delayed, uncertain, and wholly inadequate. This paper urges all the relevant stakeholders to take up self-reporting and reporting of hospitalizations of COVID-19 as an urgent task in combating this devastating pandemic.

Title: Evaluating the massive underreporting and undertesting of COVID-19 cases in multiple global epicenters Content: BACKGROUND: With continuous global COVID-19 outbreak, differing case numbers and mortality rates are observed. While actual case numbers appear vague, mortality numbers related to COVID-19 seem more precise. In this study, we used the mortality rate as the main indicator to evaluate the extent of underreporting and underdetection of COVID-19 cases. METHODS: We have analyzed all available data provided by the World Health Organization on the development of international COVID-19 cases and mortality numbers on March 17th, 2020. A crude case-fatality risk (cCFR) and adjusted case-fatality risk (aCFR) was calculated for China, South Korea, Japan, Italy, France, Spain, Germany, Iran and the United States. Additionally, a fold-change (FC) was derived for each country. RESULTS: The highest aCFR and FC were detected for Spain. Based on their FC values, an extremely high number of undetected COVID-19 cases was displayed in France, the United States, Italy and Spain. For these countries, our findings indicate a detection rate of only 1-2% of total actual COVID-19 cases. CONCLUSIONS: Due to limited testing capacities, mortality numbers may serve as a better indicator for COVID-19 case spread in many countries. Our data indicate that countries like France, Italy, the United States, Iran and Spain have extremely high numbers of undetected and underreported cases. Differences in testing availability and capacity, containment as well as overall health care and medical infrastructure result in significantly different mortality rates and COVID-19 case numbers for each respective country.

Title: Discharged COVID-19 Patients Testing Positive Again for SARS-CoV-2 RNA: A Minireview of Published Studies from China Content: In the ongoing COVID-19 pandemic, one potential cause of concern is that some discharged COVID-19 patients are testing positive again for SARS-CoV-2 RNA. To better understand what is happening and to provide public health policy planners and clinicians timely information, we have searched and reviewed published studies about discharged patients testing positive again for the SARS-CoV-2 RNA. Our search found 12 reports, all of which described patients in China. Our review of these reports indicates the presence of discharged patients who remain asymptomatic but test positive. However, it is unclear whether they are contagious because a positive RT-PCR test does not necessarily indicate the presence of replicating and transmissible virus. Our review suggests the need for timely, parallel testing of different samples, including for example, fecal specimens, from COVID-19 patients before and after they are discharged from hospitals. This article is protected by copyright. All rights reserved.

Title: Active Monitoring of Persons Exposed to Patients with Confirmed COVID-19 - United States, January-February 2020 Content: In December 2019, an outbreak of coronavirus disease 2019 (COVID-19), caused by the virus SARS-CoV-2, began in Wuhan, China (1). The disease spread widely in China, and, as of February 26, 2020, COVID-19 cases had been identified in 36 other countries and territories, including the United States. Person-to-person transmission has been widely documented, and a limited number of countries have reported sustained person-to-person spread.* On January 20, state and local health departments in the United States, in collaboration with teams deployed from CDC, began identifying and monitoring all persons considered to have had close contact with patients with confirmed COVID-19 (2). The aims of these efforts were to ensure rapid evaluation and care of patients, limit further transmission, and better understand risk factors for transmission.

Title: Active Monitoring of Persons Exposed to Patients with Confirmed COVID-19 - United States, January-February 2020. Content: In December 2019, an outbreak of coronavirus disease 2019 (COVID-19), caused by the virus SARS-CoV-2, began in Wuhan, China (1). The disease spread widely in China, and, as of February 26, 2020, COVID-19 cases had been identified in 36 other countries and territories, including the United States. Person-to-person transmission has been widely documented, and a limited number of countries have reported sustained person-to-person spread.* On January 20, state and local health departments in the United States, in collaboration with teams deployed from CDC, began identifying and monitoring all persons considered to have had close contact† with patients with confirmed COVID-19 (2). The aims of these efforts were to ensure rapid evaluation and care of patients, limit further transmission, and better understand risk factors for transmission.

Title: Catastrophic failure of outbreak containment: Limited testing causes discontinuity in epidemic transition Content: Standard measures such as quarantining suspects and contact tracing could not contain the ongoing COVID-19 pandemic. Unlike for other recent epidemics where such instruments were successful, in the present case a large fraction of the infected have only mild unspecific symptoms. By employing network models we here show that even for near perfect contact tracing and unlimited suspect testing, containment starts to fail when more than approximately half of the carriers fall into the weak-symptom category. The situation becomes considerably more severe if the number of daily available tests is limited. In this case the epidemic transition becomes discontinuous and a much larger percentage of the population becomes infected. While moderate levels of social distancing can bring the situation back under control, the limited number of daily tests introduces a finite time horizon: If social distancing is implemented after the cut off date, containment catastrophically breaks down resulting in an exponential disease spread.

Title: "No test is better than a bad test": Impact of diagnostic uncertainty in mass testing on the spread of Covid-19 Content: Background: The cessation of lock-down measures will require an effective testing strategy. Much focus at the beginning of the UK's Covid-19 epidemic was directed to deficiencies in the national testing capacity. The quantity of tests may seem an important focus, but other characteristics are likely more germane. False positive tests are more probable than positive tests when the overall population has a low prevalence of the disease, even with highly accurate tests. Methods: We modify an SIR model to include quarantines states and test performance using publicly accessible estimates for the current situation. Three scenarios for cessation of lock-down measures are explored: (1) immediate end of lock-down measures, (2) continued lock-down with antibody testing based immunity passports, and (3) incremental relaxation of lock-down measures with active viral testing. Sensitivity, specifcity, prevalence and test capacity are modified for both active viral and antibody testing to determine their population level effect on the continuing epidemic. Findings: Diagnostic uncertainty can have a large effect on the epidemic dynamics of Covid-19 within the UK. The dynamics of the epidemic are more sensitive to test performance and targeting than test capacity. The quantity of tests is not a substitute for an effective strategy. Poorly targeted testing has the propensity to exacerbate the peak in infections. Interpretation: The assessment that 'no test is better than a bad test' is broadly supported by the present analysis. Antibody testing is unlikely to be a solution to the lock-down, regardless of test quality or capacity. A well designed active viral testing strategy combined with incremental relaxation of the lock-down measures is shown to be a potential strategy to restore some social activity whilst continuing to keep infections low.

Title: The usefulness of SARS-CoV-2 test positive proportion as a surveillance tool Content: Comparison of COVID-19 case numbers over time and between locations is complicated by limits to virologic testing confirm SARS-CoV-2 infection, leading to under-reporting of incidence, and by variations in testing capacity between locations and over time. The proportion of tested individuals who have tested positive (test positive proportion, TPP) can potentially be used to qualitatively assess the testing capacity of a location; a high TPP could provide evidence that too few people are tested, leading to more under-reporting. In this study we propose a simple model for testing in a population experiencing an epidemic of COVID-19, and derive an expression for TPP in terms of well-defined parameters in the model, related to testing and presence of other pathogens causing COVID-19 like symptoms. We use simulations to show situations in which the TPP is higher or lower than we expect based on these parameters, and the effect of testing strategies on the TPP. In our simulations, we find in the absence of dramatic shifts of testing practices in time or between spatial locations, the TPP is positively correlated with the incidence of infection. As a corollary, the TPP can be used to distinguish between a decline in confirmed cases due to decline in incidence (in which case TPP should decline) and a decline in confirmed cases due to testing constraints (in which case TPP should remain constant). We show that the proportion of tested individuals who present COVID-19 like symptoms (test symptomatic proportion, TSP) encodes similar information to the TPP but has different relationships with the testing parameters, and can thus provide additional information regarding dynamic changes in TPP and incidence. Finally, we compare data on confirmed cases and TPP from US states. We conjecture why states may have higher or lower TPP than average. We suggest that collection of symptom status and age/risk category of tested individuals can aid interpretation of changes in TPP and increase the utility of TPP in assessing the state of the pandemic in different locations and times.

Title: Application of pooled testing in screening and estimating the prevalence of Covid-19 Content: The recent emergence of the COVID-19 pandemic has posed an unprecedented healthcare challenge and catastrophic economic and social consequences to the countries across the world. The situation is even worse for emerging economies like India. WHO recommends mass scale testing as one of the most effective ways to contain its spread and fight the pandemic. But, due to the high cost and shortage of test kits, specifically in India, the testing is restricted to only those who are symptomatic. In this context, pooled testing is recommended by some experts as a partial solution to overcome this problem. In this article, we explain the basic statistical theory behind the pooled testing procedure for screening as well as prevalence estimation. In real world situations, the tests are imperfect, and lead to false positive and false negative results. We provide theoretical explanation of the impact of these diagnostic errors on the performances of individual testing and pooled testing procedures. Finally, we study the effect of misspecification of sensitivity and specificity of tests on the estimate of prevalence, an issue, which is debated a lot among the scientists in the context of COVID-19. Our theoretical investigations lead to some interesting and precise understanding of some of these issues.

Title: Reconstructing the global dynamics of under-ascertained COVID-19 cases and infections Content: Background: Asymptomatic or subclinical SARS-CoV-2 infections are often unreported, which means that confirmed case counts may not accurately reflect underlying epidemic dynamics. Understanding the level of ascertainment (the ratio of confirmed symptomatic cases to the true number of symptomatic individuals) and undetected epidemic progression is crucial to informing COVID-19 response planning, including the introduction and relaxation of control measures. Estimating case ascertainment over time allows for accurate estimates of specific outcomes such as seroprevalence, which is essential for planning control measures. Methods: Using reported data on COVID-19 cases and fatalities globally, we estimated the proportion of symptomatic cases (i.e. any person with any of fever >= to 37.5C, cough, shortness of breath, sudden onset of anosmia, ageusia or dysgeusia illness) that were reported in 210 countries and territories, given those countries had experienced more than ten deaths. We used published estimates of the case fatality ratio (CFR) as an assumed baseline. We then calculated the ratio of this baseline CFR to an estimated local delay-adjusted CFR to estimate the level of under-ascertainment in a particular location. We then fit a Bayesian Gaussian process model to estimate the temporal pattern of under-ascertainment. Results: We estimate that, during March 2020, the median percentage of symptomatic cases detected across the 84 countries which experienced more than ten deaths ranged from 2.38% (Bangladesh) to 99.6% (Chile). Across the ten countries with the highest number of total confirmed cases as of 6th July 2020, we estimated that the peak number of symptomatic cases ranged from 1.4 times (Chile) to 17.8 times (France) larger than reported. Comparing our model with national and regional seroprevalence data where available, we find that our estimates are consistent with observed values. Finally, we estimated seroprevalence for each country. Despite low case detection in some countries, our results that adjust for this still suggest that all countries have had only a small fraction of their populations infected as of July 2020. Conclusions: We found substantial under-ascertainment of symptomatic cases, particularly at the peak of the first wave of the SARS-CoV-2 pandemic, in many countries. Reported case counts will therefore likely underestimate the rate of outbreak growth initially and underestimate the decline in the later stages of an epidemic. Although there was considerable under-reporting in many locations, our estimates were consistent with emerging serological data, suggesting that the proportion of each country's population infected with SARS-CoV-2 worldwide is generally low.

Title: Effectiveness of a COVID-19 screening questionnaire for pregnant women at admission to an obstetric unit in Milan. Content: Sutton et al. [1] recently reported on universal testing with nasopharyngeal swabs to detect severe acute respiratory syndrome coronavirus 2 (SARS-Cov-2) infection in 215 women admitted for delivery at the Presbyterian Allen Hospital in New York, USA. They identified 33 (15.3%) infected women, of whom only four had fever or symptoms suggesting coronavirus disease 2019 (COVID-19). These findings suggest that only universal testing can reliably recognize infected cases. However, this approach is only feasible in major hospitals in high-resource countries with efficient lab facilities in-house. Alternative approaches deserve consideration.

Title: RT-qPCR Testing of SARS-CoV-2: A Primer Content: Testing for the presence of coronavirus is an essential diagnostic tool for monitoring and managing the current COVID-19 pandemic. The only reliable test in current use for testing acute infection targets the genome of SARS-CoV-2, and the most widely used method is quantitative fluorescence-based reverse transcription polymerase chain reaction (RT-qPCR). Despite its ubiquity, there is a significant amount of uncertainty about how this test works, potential throughput and reliability. This has resulted in widespread misrepresentation of the problems faced using this test during the current COVID-19 epidemic. This primer provides simple, straightforward and impartial information about RT-qPCR.

Title: Infections and Identified Cases of COVID-19 from Random Testing Data Content: There are many hard-to-reconcile numbers circulating concerning Covid-19. Using reports from random testing, the fatality ratio per infection is evaluated and used to extract further information on the actual fraction of infections and the success of their identification for different countries.

Title: Comparing and Integrating US COVID-19 Daily Data from Multiple Sources: A County-Level Dataset with Local Characteristics Content: Over the past several months, the outbreak of COVID-19 has been expanding over the world. A reliable and accurate dataset of the cases is vital for scientists to conduct related research and for policy-makers to make better decisions. We collect the COVID-19 daily reported data from four open sources: the New York Times, the COVID-19 Data Repository by Johns Hopkins University, the COVID Tracking Project at the Atlantic, and the USAFacts, and compare the similarities and differences among them. In addition, we examine the following problems which occur frequently: (1) the order dependencies violation, (2) the delay-reported issue on weekends and/or holidays, and (3) abnormal data point or data period. We also integrate the COVID-19 reported cases with the county-level auxiliary information of the local features from official sources, such as health infrastructure, demographic, socioeconomic, and environment information, which are important for understanding the spread of the virus.

Title: [Advances on presymptomatic or asymptomatic carrier transmission of COVID-19] Content: COVID-19 is rapidly spreading. Patients in incubation period and healthy carriers are possible sources for transmission. However, such sources of infection cannot be effectively identified due to the symptoms absent. The research evidence is very lacking so far, although there are a few studies suggesting that presymptomatic or asymptomatic carrier may cause COVID-19 transmission. Nearly half of the literature is in the state of preprint without peer review. The question of "the degree to which presymptomatic or asymptomatic infections can transmit" is not fully understood. There is an urgent need to screen infected carriers in larger close contacts or in the general population, and assess their risk for transmission.

Title: [Advances on presymptomatic or asymptomatic carrier transmission of COVID-19]. Content: COVID-19 is rapidly spreading. Patients in incubation period and healthy carriers are possible sources for transmission. However, such sources of infection cannot be effectively identified due to the symptoms absent. The research evidence is very lacking so far, although there are a few studies suggesting that presymptomatic or asymptomatic carrier may cause COVID-19 transmission. Nearly half of the literature is in the state of preprint without peer review. The question of "the degree to which presymptomatic or asymptomatic infections can transmit" is not fully understood. There is an urgent need to screen infected carriers in larger close contacts or in the general population, and assess their risk for transmission.

Title: COVID-19 Serological Tests: How Well Do They Actually Perform? Content: In only a few months after initial discovery in Wuhan, China, SARS-CoV-2 and the associated coronavirus disease 2019 (COVID-19) have become a global pandemic causing significant mortality and morbidity and implementation of strict isolation measures In the absence of vaccines and effective therapeutics, reliable serological testing must be a key element of public health policy to control further spread of the disease and gradually remove quarantine measures Serological diagnostic tests are being increasingly used to provide a broader understanding of COVID-19 incidence and to assess immunity status in the population However, there are discrepancies between claimed and actual performance data for serological diagnostic tests on the market In this study, we conducted a review of independent studies evaluating the performance of SARS-CoV-2 serological tests We found significant variability in the accuracy of marketed tests and highlight several lab-based and point-of-care rapid serological tests with high levels of performance The findings of this review highlight the need for ongoing independent evaluations of commercialized COVID-19 diagnostic tests

Title: Covid-19 Pandemic- Pits and falls of major states of India. Content: Covid-19, just like SARS and MERS before it, is a disease caused by corona virus and can lead to severe respiratory diseases in humans. With the outbreak of novel corona virus, WHO on 30th January 2020 declared it a Public Health Emergency and further on 11th March 2020, Covid-19 disease was declared a pandemic. India in the initial stages of the pandemic dealt with it in a very effective manner. With timely implementation of lockdown, India was able to contain the spread of Covid-19 to some extent. However with the recently announced Unlock 1.0, the SARS CoV-2 is expected to spread. This study aims to track and analyze the Covid-19 situation in major states that constitute of 70 percent of the total cases. Thus the states selected for the study are: Maharashtra, Delhi, Tamil Nadu, Gujarat, Uttar Pradesh and Rajasthan. These are the states which had more than ten thousand Covid-19 patients as/on June 10th 2020. The analysis period is from March 25th to June 10th and the data source is India Covid-19 tracker. To assess the previous and current Covid-19 situations in these states indicators such as Active rates, Recovery rate, Case fatality rate, Test positivity rate, tests per million, cases per million, test per confirmed case has been used. The study finds that although the absolute number of active cases may be rising, however it is showing a decreasing trend with an increase in recovery rates. With increasing number of Covid-19 cases, testing also has increased however not in the similar proportion and thus by developed nation standard we are lagging. With increasing TPR and cases per million, Delhi is well on its way to surpass even Mumbai which till now has proven to be worst hit in this pandemic. An interesting finding is that of test per confirmed case which shows that every 6th person in Maharashtra and every 8th in Delhi is showing positive result of Covid-19 test. Given such an increase and unlocked India, Delhi might soon enter into the third stage of community transmission where source of 50 percent or more cases would be unknown. There has been an increase in the Covid-19 related health infrastructure with the public-private partnership which involved both private hospitals and lab joining hands to battle Covid-19, however, affordability still remains an issue. If experts are to be believed, pandemic is not over because we have unlocked. The worst is yet to come as Covid-19 is predicted to peak in mid-July to August in India. Thus, it would be advisable to not venture out unnecessarily just because restrictions have been lifted. Also, following the guidelines- hand-washing, avoiding public gathering, social distancing and covering nose and mouth has now become imperative.

Title: Network structure of COVID-19 spread and the lacuna in India's testing strategy Content: We characterize the network of COVID-19 spread in India and find that the transmission rate is 0.43, with daily case growth driven by individuals who contracted the virus abroad. We explore the question of whether this represents exponentially decaying dynamics or is simply an artefact of India's testing strategy. Testing has largely been limited to individuals travelling from high-risk countries and their immediate contacts, meaning that the network reflects positive identifications from a biased testing sample. Given generally low levels of testing and an almost complete absence of testing for community spread, there is significant risk that we may be missing out on the actual nature of outbreak. India still has an apparently low current caseload, with possibly a small window of time to act, and should therefore aggressively and systematically expand random testing for community spread, including for asymptomatic cases. This will help understand true transmission characteristics and plan appropriately for the immediate future.

Title: Testing COVID-19 tests faces methodological challenges Content: In battling the COVID-19 pandemic, testing is essential. The detection of viral RNA allows the identification of infected persons, while the detection of antibodies may reveal a response to a previous infection. Tests for coronavirus should be rigorously evaluated in terms of their analytical and clinical performance. This poses not only logistic challenges, but also methodological ones. Some of these are generic for the diagnostic accuracy paradigm, while others are more specific for tests for viruses. Problematic for evaluations of the clinical performance of tests for viral RNA is the absence of an independent reference standard. Many studies lack rigor in terms of the recruitment of study participants. Study reports are often insufficiently informative, which makes it difficult to assess the applicability of study findings. Attempts to summarize the performance of these tests in terms of a single estimate of the clinical sensitivity fails to do justice to the identifiable sources of the large heterogeneity in mechanisms for generating false negative results.

Title: Low Utility of Repeat Real-Time PCR Testing for SARS-CoV-2 in Clinical Specimens Content: Abstract: In a multicenter cohort of 22,315 patients tested for COVID-19, 1676 (7.5%) had repeat testing via real-time PCR following an initial negative test. Of those retested within seven days of their first negative test, only 2.0% had a positive result. This suggests that repeat testing from the same source is unlikely to provide additional information.

Title: Serial Laboratory Testing for SARS-CoV-2 Infection Among Incarcerated and Detained Persons in a Correctional and Detention Facility — Louisiana, April–May 2020 Content: Transmission of SARS-CoV-2, the virus that causes coronavirus disease 2019 (COVID-19), by asymptomatic and presymptomatic persons poses important challenges to controlling spread of the disease, particularly in congregate settings such as correctional and detention facilities (1). On March 29, 2020, a staff member in a correctional and detention facility in Louisiana developed symptoms† and later had a positive test result for SARS-CoV-2. During April 2-May 7, two additional cases were detected among staff members, and 36 cases were detected among incarcerated and detained persons at the facility; these persons were removed from dormitories and isolated, and the five dormitories that they had resided in before diagnosis were quarantined. On May 7, CDC and the Louisiana Department of Health initiated an investigation to assess the prevalence of SARS-CoV-2 infection among incarcerated and detained persons residing in quarantined dormitories. Goals of this investigation included evaluating COVID-19 symptoms in this setting and assessing the effectiveness of serial testing to identify additional persons with SARS-CoV-2 infection as part of efforts to mitigate transmission. During May 7-21, testing of 98 incarcerated and detained persons residing in the five quarantined dormitories (A-E) identified an additional 71 cases of SARS-CoV-2 infection; 32 (45%) were among persons who reported no symptoms at the time of testing, including three who were presymptomatic. Eighteen cases (25%) were identified in persons who had received negative test results during previous testing rounds. Serial testing of contacts from shared living quarters identified persons with SARS-CoV-2 infection who would not have been detected by symptom screening alone or by testing at a single time point. Prompt identification and isolation of infected persons is important to reduce further transmission in congregate settings such as correctional and detention facilities and the communities to which persons return when released.

Title: A novel comprehensive metric to assess COVID-19 testing outcomes: Effects of geography, government, and policy response Content: Testing and case identification are key strategies in controlling the COVID-19 pandemic. Contact tracing and isolation are only possible if cases have been identified. The effectiveness of testing must be tracked, but a single comprehensive metric is not available to assess testing effectiveness, and no timely estimates of case detection rate are available globally, making inter-country comparisons difficult. The purpose of this paper was to propose a single, comprehensive metric, called the COVID-19 Testing Index (CovTI) scaled from 0 to 100, that incorporated several testing metrics. The index was based on case-fatality rate, test positivity rate, active cases, and an estimate of the detection rate. It used parsimonious modeling to estimate the true total number of COVID-19 cases based on deaths, testing, health system capacity, and government transparency. Publicly reported data from 188 countries and territories were included in the index. Estimates of detection rates aligned with previous estimates in literature (R2=0.97). As of June 3, 2020, the states with the highest CovTI included Iceland, Australia, New Zealand, Hong Kong, and Thailand, and some island nations. Globally, CovTI increased from April 20 ([x]=43.2) to June 3 ([x]=52.2) but declined in ca. 10% of countries. Bivariate analyses showed the average in countries with open public testing policies (59.7, 95% CI 55.6-63.8) were significantly higher than countries with no testing policy (30.2, 95% CI 18.1-42.3) (p<0.0001). A multiple linear regression model assessed the association of independent grouping variables with CovTI. Open public testing and extensive contact tracing were shown to significantly increase CovTI, after adjusting for extrinsic factors, including geographic isolation and centralized forms of government. This tool may be useful for policymakers to assess testing effectiveness, inform decisions, and identify model countries. It may also serve as a tool for researchers in analyses by combining it with other databases.

Title: How much of SARS-CoV-2 Infections is India detecting? A model-based estimation Content: Background and Rationale: Amid SARS-CoV-2 outbreak, the low number of infections for a population size of 1.38 billion is widely discussed, but with no definite answers. Methods: We used the model proposed by Bommer and Vollmer to assess the quality of official case records. The infection fatality rates were taken from Verity et al (2020). Age distribution of the population for India and states are taken from the Census of India (2011). Reported number of deaths and SARS-CoV-2 confirmed cases from https://www.covid19india.org. The reported numbers of samples tests were collected from the reports of the Indian Council for Medical Research (ICMR). Results: The findings suggest that India is detecting just 3.6% of the total number of infections with a huge variation across its states. Among 13 states which have more than 100 COVID-19 cases, the detection rate varies from 81.9% (of 410 estimated infections) in Kerala to 0.8% (of 35487 estimated infections) in Madhya Pradesh and 2.4% (of 7431 estimated infections) in Gujarat. Conclusion: As the study reports a lower number of deaths and higher recovery rates in the states with a high detection rate, thus suggest that India must enhance its testing capacity and go for widespread testing. Late detection puts patients in greater need of mechanical ventilation and ICU care, which imposes greater costs on the health system. The country should also adopt population-level random testing to assess the prevalence of the infection.

Title: Diagnostic Performance of a Rapid Point of Care Test for SARS-CoV-2 in an Urban ED Setting Content: The ability to rapidly and accurately identify a patient's COVID-19 status has had significant impact on emergency departments (ED) and health systems globally. Since the identification of SARS-CoV-2 illness in the United States, there has been rapid development in patient testing capacity following initial challenges including sparse availability. This was made possible by increasing availability of diagnostic molecular tests in several formats, from laboratory based traditional, RT-PCR methods to near patient testing rapid point of care PCR tests.

Title: Serial Laboratory Testing for SARS-CoV-2 Infection Among Incarcerated and Detained Persons in a Correctional and Detention Facility - Louisiana, April-May 2020 Content: Transmission of SARS-CoV-2, the virus that causes coronavirus disease 2019 (COVID-19), by asymptomatic and presymptomatic persons poses important challenges to controlling spread of the disease, particularly in congregate settings such as correctional and detention facilities (1). On March 29, 2020, a staff member in a correctional and detention facility in Louisiana developed symptoms and later had a positive test result for SARS-CoV-2. During April 2-May 7, two additional cases were detected among staff members, and 36 cases were detected among incarcerated and detained persons at the facility; these persons were removed from dormitories and isolated, and the five dormitories that they had resided in before diagnosis were quarantined. On May 7, CDC and the Louisiana Department of Health initiated an investigation to assess the prevalence of SARS-CoV-2 infection among incarcerated and detained persons residing in quarantined dormitories. Goals of this investigation included evaluating COVID-19 symptoms in this setting and assessing the effectiveness of serial testing to identify additional persons with SARS-CoV-2 infection as part of efforts to mitigate transmission. During May 7-21, testing of 98 incarcerated and detained persons residing in the five quarantined dormitories (A-E) identified an additional 71 cases of SARS-CoV-2 infection; 32 (45%) were among persons who reported no symptoms at the time of testing, including three who were presymptomatic. Eighteen cases (25%) were identified in persons who had received negative test results during previous testing rounds. Serial testing of contacts from shared living quarters identified persons with SARS-CoV-2 infection who would not have been detected by symptom screening alone or by testing at a single time point. Prompt identification and isolation of infected persons is important to reduce further transmission in congregate settings such as correctional and detention facilities and the communities to which persons return when released.

Title: Major testing issues in US Content: Delays and restrictions on who can be tested for the covid-19 virus in the US have raised the risk that it is spreading undetected, reports Colin Barras

Title: Evolução da prevalência de infecção por COVID-19 no Rio Grande do Sul, Brasil: inquéritos sorológicos seriados./ Evolução da prevalência de infecção por COVID-19 no Rio Grande do Sul, Brasil: inquéritos sorológicos seriados./ Trends in the prevalence of COVID-19 infection in Rio Grande do Sul, Brazil: repeated serological surveys Content: COVID-19, the disease produced by the virus SARS-CoV-2, has spread quickly throughout the world, leading the World Health Organization to first classify it as an international health emergency and, subsequently, declaring it pandemic. The number of confirmed cases, as April 11, surpassed 1,700,000, but this figure does not reflect the prevalence of COVID-19 in the population as, in many countries, tests are almost exclusively performed in people with symptoms, particularly severe cases. To properly assess the magnitude of the problem and to contribute to the design of evidence-based policies for fighting COVID-19, one must accurately estimate the population prevalence of infection. Our study is aimed at estimating the prevalence of infected individuals in the state of Rio Grande do Sul, Brazil, to document how fast the infection spreads, and to estimate the proportion of infected persons who present or presented symptoms, as well as the proportion of asymptomatic infections. Four repeated serological surveys will be conducted in probability samples of nine sentinel cities every two weeks. Tests will be performed in 4,500 participants in each survey, totaling18,000 interviews. Interviews and tests will be conducted at the participants' household. A rapid test for the detection of antibodies will be used; the test was validated prior to the beginning of the fieldwork.

Title: Trends in the prevalence of COVID-19 infection in Rio Grande do Sul, Brazil: repeated serological surveys. Content: COVID-19, the disease produced by the virus SARS-CoV-2, has spread quickly throughout the world, leading the World Health Organization to first classify it as an international health emergency and, subsequently, declaring it pandemic. The number of confirmed cases, as April 11, surpassed 1,700,000, but this figure does not reflect the prevalence of COVID-19 in the population as, in many countries, tests are almost exclusively performed in people with symptoms, particularly severe cases. To properly assess the magnitude of the problem and to contribute to the design of evidence-based policies for fighting COVID-19, one must accurately estimate the population prevalence of infection. Our study is aimed at estimating the prevalence of infected individuals in the state of Rio Grande do Sul, Brazil, to document how fast the infection spreads, and to estimate the proportion of infected persons who present or presented symptoms, as well as the proportion of asymptomatic infections. Four repeated serological surveys will be conducted in probability samples of nine sentinel cities every two weeks. Tests will be performed in 4,500 participants in each survey, totaling18,000 interviews. Interviews and tests will be conducted at the participants' household. A rapid test for the detection of antibodies will be used; the test was validated prior to the beginning of the fieldwork.

Title: Evaluating the massive underreporting and undertesting of COVID-19 cases in multiple global epicenters Content: Abstract Background With continuous global COVID-19 outbreak, differing case numbers and mortality rates are observed. While actual case numbers appear vague, mortality numbers related to COVID-19 seem more precise. In this study, we used the mortality rate as the main indicator to evaluate the extent of underreporting and underdetection of COVID-19 cases. Methods We have analyzed all available data provided by the World Health Organization on the development of international COVID-19 cases and mortality numbers on March 17th, 2020. A crude case-fatality risk (cCFR) and adjusted case-fatality risk (aCFR) was calculated for China, South Korea, Japan, Italy, France, Spain, Germany, Iran and the United States. Additionally, a fold-change (FC) was derived for each country. Results The highest aCFR and FC were detected for Spain. Based on their FC values, an extremely high number of undetected COVID-19 cases was displayed in France, the United States, Italy and Spain. For these countries, our findings indicate a detection rate of only 1-2% of total actual COVID-19 cases. Conclusions Due to limited testing capacities, mortality numbers may serve as a better indicator for COVID-19 case spread in many countries. Our data indicate that countries like France, Italy, the United States, Iran and Spain have extremely high numbers of undetected and underreported cases. Differences in testing availability and capacity, containment as well as overall health care and medical infrastructure result in significantly different mortality rates and COVID-19 case numbers for each respective country.

Title: [Covid-19 diagnosis : clinical recommendations and performance of nasopharyngeal swab-PCR]. Content: The Covid-19 pandemic imposes new diagnostic strategies in order to optimize the medical care of our patients. The current biblio-graphy, although of low quality, shows a sensitivity of 56 to 83 % for the Covid-19 PCR. Even though one negative test can exclude a Covid-19 in the majority of cases, the NPV (Negative Predictive Value) decreases with increasing prevalence (pre-test probability). This finding suggests the need for strict auto-isolation of patients until the resolution of their symptoms. For patients that present with typical symptoms, who have a presumed Covid-19 prevalence of -40-50 %, a negative test should be interpreted with caution and a repeat test may be needed.

Title: SARS-CoV-2 and the COVID-19 disease: a mini review on diagnostic methods Content: Coronavirus disease 2019 (COVID-19) is an infectious disease initially reported in China and currently worldwide dispersed caused by a new coronavirus (SARS-CoV-2 or 2019-nCoV) affecting more than seven million people around the world causing more than 400 thousand deaths (on June 8th, 2020). The diagnosis of COVID-19 is based on the clinical and epidemiological history of the patient. However, the gold standard for COVID-19 diagnosis is the viral detection through the amplification of nucleic acids. Although the quantitative Reverse-Transcription Polymerase Chain Reaction (RT-PCR) has been described as the gold standard for diagnosing COVID-19, there are several difficulties involving its use. Here we comment on RT-PCR and describe alternative tests developed for the diagnosis of COVID-19.

Title: Time Course of COVID-19 Cases in Austria Content: COVID-19 is an infectious disease caused by a novel coronavirus, which first appeared in China in late 2019, and reached pandemic distribution in early 2020. The first major outbreak in Europe occurred in Northern Italy where it spread to neighboring countries, notably to Austria, where skiing resorts served as a main transmission hub. Soon, the Austrian government introduced strict measures to curb the spread of the virus. Using publicly available data, we assessed the efficiency of the governmental measures. We assumed an average incubation period of one week and an average duration of infectivity of 10 days. One week after the introduction of strict measures, the increase in daily new cases was reversed, and the reproduction number dropped. The crude estimates tended to overestimate the reproduction rate in the early phase. Publicly available data provide a first estimate about the effectiveness of public health measures. However, more data are needed for an unbiased assessment.

Title: Dynamics of RT-qPCR SARS-CoV-2 Detection Rates Prior to and After Symptom Onset Content: Effective RT-qPCR testing for SARS-CoV-2 is essential for treatment, surveillance and control of the COVID-19 pandemic. A recent meta-analysis suggested that testing prior to the onset of symptoms is likely to miss the majority of infected individuals. These findings cast severe doubts on the effectiveness of mass screening efforts intended to detect SARS-CoV-2 prior to the onset of symptoms and decrease community transmissions from pre-/asymptomatic individuals. However, alternative analyses and additional data described herein refine these estimates and suggest that many SARS-CoV-2 infections could potentially be detected prior to symptom onset.

Title: Estimating the global spread of COVID-19 Content: Limited and inconsistent testing and differences in age distribution, health care resources, social distancing, and policies have caused large variations in the extent and dynamics of the COVID-19 pandemic across nations, complicating the estimation of prevalence, the infection fatality rate (IFR), and other factors important to care providers and policymakers. Using data for all 84 countries with reliable testing data (spanning 4.75 billion people) we develop a dynamic epidemiological model integrating data on cases, deaths, excess mortality and other factors to estimate how asymptomatic transmission, disease acuity, hospitalization, and behavioral and policy responses to risk condition prevalence and IFR across nations and over time. For these nations we estimate IFR averages 0.68% (0.64%-0.7%). Cases and deaths through June 18, 2020 are estimated to be 11.8 and 1.48 times official reports, respectively, at 88.5 (85-95.3) million and 600 (586-622) thousand. Prevalence and IFR vary substantially, e.g., Ecuador (18%; 0.61%), Chile (15.5%; 0.57%), Mexico (8.8%; 0.69%), Iran (7.9%; 0.44%), USA (5.3%; 0.99%), UK (5.2%; 1.59%), Iceland (1.65%, 0.56%), New Zealand (0.1%, 0.64%), but all nations remain well below the level needed for herd immunity. By alerting the public earlier and reducing contacts, extensive testing when the pandemic was declared could have averted 35.3 (32.7-42.7) million cases and 197 (171-232) thousand deaths. However, future outcomes are less dependent on testing and more contingent on the willingness of communities and governments to reduce transmission. Absent breakthroughs in treatment or vaccination and with mildly improved responses we project 249 (186-586) million cases and 1.75 (1.40-3.67) million deaths in the 84 countries by Spring 2021.

Title: Estimating the extent of true asymptomatic COVID-19 and its potential for community transmission: systematic review and meta-analysis Content: Background: The prevalence of true asymptomatic COVID-19 cases is critical to policy makers considering the effectiveness of mitigation measures against the SARS-CoV-2 pandemic. We aimed to synthesize all available research on the asymptomatic rates and transmission rates where possible. Methods: We searched PubMed, Embase, Cochrane COVID-19 trials, and European PMC for pre-print platforms such as MedRxiv. We included primary studies reporting on asymptomatic prevalence where: (a) the sample frame includes at-risk population, and (b) there was sufficiently long follow up to identify pre-symptomatic cases. Meta-analysis used fixed effect and random effects models. Results: We screened 571 articles and included five low risk-of-bias studies from three countries (China (2), USA (2), Italy (1)) that tested 9,242 at-risk people, of which 413 were positive and 65 were asymptomatic. Diagnosis in all studies was confirmed using a RT-qPCR test. The proportion of asymptomatic cases ranged from 6% to 41%. Meta-analysis (fixed effect) found that the proportion of asymptomatic cases was 16% (95% CI: 12% - 20%) overall; higher in non-aged care 19% (15% - 24%), and lower in long-term aged care 8% (4% - 14%). Two studies provided direct evidence of forward transmission of the infection by asymptomatic cases but suggested lower rates than symptomatic cases. Conclusion: Our estimates of the prevalence of asymptomatic COVID-19 cases are lower than many highly publicized studies, but still substantial. Further robust epidemiological evidence is urgently needed, including in sub-populations such as children, to better understand the importance of asymptomatic cases for driving spread of the pandemic.

Title: SARS-CoV-2 and the COVID-19 disease: a mini review on diagnostic methods Content: Coronavirus disease 2019 (COVID-19) is an infectious disease initially reported in China and currently worldwide dispersed caused by a new coronavirus (SARS-CoV-2 or 2019-nCoV) affecting more than seven million people around the world causing more than 400 thousand deaths (on June 8(th), 2020). The diagnosis of COVID-19 is based on the clinical and epidemiological history of the patient. However, the gold standard for COVID-19 diagnosis is the viral detection through the amplification of nucleic acids. Although the quantitative Reverse-Transcription Polymerase Chain Reaction (RT-PCR) has been described as the gold standard for diagnosing COVID-19, there are several difficulties involving its use. Here we comment on RT-PCR and describe alternative tests developed for the diagnosis of COVID-19.

Title: Sniffing out the evidence; It's now time for public health bodies recognize the link between COVID-19 and smell and taste disturbance Content: Since the outbreak of the pandemic, anecdotal observations have been accumulating rapidly that sudden anosmia and dysgeusia are peculiar symptoms associated with the COVID-19 infection. Prof C. Hopkins, as President of British Rhinological Society, published a letter describing "the loss of sense of smell as a marker of COVID-19 infection" and proposed that adults presenting with anosmia but no other symptoms should self-isolate for seven days. The Hopkins team published the first case report and case series as well as other evidence that isolated sudden onset anosmia (ISOA), should be considered highly suspicious for SARS-CoV-2(1). Subsequently, a larger series of 2428 patients presenting with new onset anosmia during the COVID-19 pandemic has been reported, of whom 16% report loss of sense of smell as an isolated symptom. Only 51% reported the recognized symptoms of cough or fever. A major limitation of this series however, was a lack of access to testing to confirm the COVID-19 status of the patients(2); in the 80 who had been tested 74% were positive. In the same way, the American Academy of Otolaryngology-head and neck surgery (AA0-HNS) proposed "that anosmia could be added to the list of screening tools for possible COVID-19 infection. More, they warrant serious consideration for self-isolation and testing those patients".

Title: Management of COVID‐19‐related paediatric blood samples in a clinical haematology laboratory Content: There is currently limited knowledge about the transmission risks of the SARS-CoV-2 virus and its associated disease COVID-19 from routine clinical specimens. The first study to be published on the initial 41 cases of COVID-19 infections admitted in Wuhan detected SARS-CoV-2 RNA in the blood of 6/41 (15%) of patients (Huang et. al., 2020) . However, another study conducted on 1070 clinical specimens collected from confirmed COVID-19 patients in China showed the highest positive rates of SARS-CoV-2 from rRT-PCR testing of respiratory specimens such as bronchoalveolar lavage, sputum and nasopharyngeal swabs (32% - 93%). In contrast, only 1% of blood specimens and none of the urine specimens tested positive (Wang et. al., 2020).

Title: Redundancy in reporting on COVID‐19 Content: Additional to the problems described very well by Dr. Ioannidis1 , there is another issue that became highlighted during this pandemic: redundancy in research and reporting. Redundant articles repeat already known information and are mostly published just for the sake of publishing. By searching through Pubmed, one can easily see that the number of publications related to COVID-19 is growing exponentially (Figure).

Title: A Statistical Analysis Of CoV-19 Positive Test Frequency Data Indicates A Need For Greater Attention To CoV-19 Test Quality And Pre-Wuhan Cov-19 Prevalence Content: Increased attention to analysis of SARS-CoV-2 (CoV-19) positive test frequency data is essential for achievement of better knowledge of the natural history of the virus in human populations, improved accuracy of CoV-19 epidemiological data, and development of public response policies that are better crafted to address the current CoV-19-induced global crisis. A statistical analysis of currently available positive test frequency data reveals a surprisingly uniform relationship between the number of CoV-19 test performed and the number of positive tests obtained. The uniformity is particularly striking for United States CoV-19 test data. Such observations warrant closer evaluation of other factors, besides virus spread, that may also contribute to the nature of the coronavirus pandemic. These include indigenous CoV-19 and the quality of CoV-19 testing.

Title: Changes in testing rates could mask the novel coronavirus disease (COVID-19) growth rate Content: Since the novel coronavirus disease (COVID-19) emerged in December 2019 in China, it has rapidly spread around the world, leading to one of the most significant pandemic events of recent history. Deriving reliable estimates of the COVID-19 epidemic growth rate is quite important to guide the timing and intensity of intervention strategies. Indeed, many studies have quantified the epidemic growth rate using time-series of reported cases during the early phase of the outbreak to estimate the basic reproduction number, R0. Using daily time series of COVID-19 incidence, we illustrate how epidemic curves of reported cases may not always reflect the true epidemic growth rate due to changes in testing rates, which could be influenced by limited diagnostic testing capacity during the early epidemic phase.

Title: Towards reduction in bias in epidemic curves due to outcome misclassification through Bayesian analysis of time-series of laboratory test results: Case study of COVID-19 in Alberta, Canada and Philadelphia, USA Content: The aim of our work was to better understand misclassification errors in identification of true cases of COVID-19 and to study the impact of these errors in epidemic curves. We examined publically available time-series data of laboratory tests for SARS-CoV-2 viral infection, the causal agent for COVID-19, to try to explore, using a Bayesian approach, about the sensitivity and specificity of the PCR-based diagnostic test. Data originated from Alberta, Canada (available on 3/28/2020) and city of Philadelphia, USA (available on 3/31/2020). Our analysis revealed that the data were compatible with near-perfect specificity but it was challenging to gain information about sensitivity (prior and posterior largely overlapped). We applied these insights to uncertainty/bias analysis of epidemic curves into jurisdictions under the assumptions of both improving and degrading sensitivity. If the sensitivity improved from 60 to 95%, the observed and adjusted epidemic curves likely fall within the 95% confidence intervals of the observed counts. However, bias in the shape and peak of the epidemic curves can be pronounced, if sensitivity either degrades or remains poor in the 60–70% range. In the extreme scenario, hundreds of undiagnosed cases, even among tested, are possible, potentially leading to further unchecked contagion should these cases not self-isolate. The best way to better understand bias in the epidemic curves of COVID-19 due to errors in testing is to empirically evaluate misclassification of diagnosis in clinical settings and apply this knowledge to adjustment of epidemic curves, a task for which the Bayesian method we presented is well-suited.

Title: Sniffing out the evidence; It's now time for public health bodies recognize the link between COVID-19 and smell and taste disturbance. Content: Since the outbreak of the pandemic, anecdotal observations have been accumulating rapidly that sudden anosmia and dysgeusia are peculiar symptoms associated with the COVID-19 infection. Prof C. Hopkins, as President of British Rhinological Society, published a letter describing "the loss of sense of smell as a marker of COVID-19 infection" and proposed that adults presenting with anosmia but no other symptoms should self-isolate for seven days. The Hopkins team published the first case report and case series as well as other evidence that isolated sudden onset anosmia (ISOA), should be considered highly suspicious for SARS-CoV-2(1). Subsequently, a larger series of 2428 patients presenting with new onset anosmia during the COVID-19 pandemic has been reported, of whom 16% report loss of sense of smell as an isolated symptom. Only 51% reported the recognized symptoms of cough or fever. A major limitation of this series however, was a lack of access to testing to confirm the COVID-19 status of the patients(2); in the 80 who had been tested 74% were positive. In the same way, the American Academy of Otolaryngology-head and neck surgery (AA0-HNS) proposed "that anosmia could be added to the list of screening tools for possible COVID-19 infection. More, they warrant serious consideration for self-isolation and testing those patients".

Title: [Covid-19 diagnosis : clinical recommendations and performance of nasopharyngeal swab-PCR] Content: The Covid-19 pandemic imposes new diagnostic strategies in order to optimize the medical care of our patients The current biblio-graphy, although of low quality, shows a sensitivity of 56 to 83 % for the Covid-19 PCR Even though one negative test can exclude a Covid-19 in the majority of cases, the NPV (Negative Predictive Value) decreases with increasing prevalence (pre-test probability) This finding suggests the need for strict auto-isolation of patients until the resolution of their symptoms For patients that present with typical symptoms, who have a presumed Covid-19 prevalence of -40-50 %, a negative test should be interpreted with caution and a repeat test may be needed

Title: The Infection Rate of the Coronavirus Disease 2019 (COVID-19) in Wuhan, China Content: For the pandemic of COVID-19, the initial number of infections in Wuhan China has never been known or estimated properly. This data is critical to understand the current pandemic across the world, as well as to eliminate panic from overestimated fatality rate that has biased the public health policies of many countries. By our unique estimation with the data of a number of foreign government evacuations with thorough follow-up and etiological tests, it is safe to say that a large number of infections in Wuhan, China have not been diagnosed (the number of undiagnosed is much more than the final diagnosed number 50,333 to date).

Title: Epidemiology, diagnosis, treatment, and future perspectives concerning SARS-COV-2: a review article Content: The present study aimed to review the epidemiology, clinical manifestation, laboratory diagnosis, treatment, and future perspectives related to COVID-19 infections. The following electronic databases were used searched: MEDLINE, SCIELO, and LILACS. It became clear that COVID-19 infections occur through exposure to the virus, and both the immunosuppressed and healthy population appear susceptible. The clinical course of COVID-19 is still not clear, although the SARS-CoV-2 infection seems to develop with mild, influenza-like symptoms in the vast majority of subjects, i.e., 10%-15% of COVID-19 patients. Since rRT-PCR tests serve as the gold standard method to confirm a SARS-CoV-2 infection, false-negative results could hinder the prevention and control of the epidemic, particularly considering the test plays a key role in the decision for continued isolated medical observation or discharge. Our findings also indicate that a radical increase in the identification and isolation of currently undocumented infections would be needed to fully control SARS-CoV2.

Title: Epidemiology, diagnosis, treatment, and future perspectives concerning SARS-COV-2: a review article. Content: The present study aimed to review the epidemiology, clinical manifestation, laboratory diagnosis, treatment, and future perspectives related to COVID-19 infections. The following electronic databases were used searched: MEDLINE, SCIELO, and LILACS. It became clear that COVID-19 infections occur through exposure to the virus, and both the immunosuppressed and healthy population appear susceptible. The clinical course of COVID-19 is still not clear, although the SARS-CoV-2 infection seems to develop with mild, influenza-like symptoms in the vast majority of subjects, i.e., 10%-15% of COVID-19 patients. Since rRT-PCR tests serve as the gold standard method to confirm a SARS-CoV-2 infection, false-negative results could hinder the prevention and control of the epidemic, particularly considering the test plays a key role in the decision for continued isolated medical observation or discharge. Our findings also indicate that a radical increase in the identification and isolation of currently undocumented infections would be needed to fully control SARS-CoV2.

Title: How to Best Predict the Daily Number of New Infections of Covid-19 Content: Knowledge about the daily number of new infections of Covid-19 is important because it is the basis for political decisions resulting in lockdowns and urgent health care measures. We use Germany as an example to illustrate shortcomings of official numbers, which are, at least in Germany, disclosed only with several days of delay and severely underreported on weekends (more than 40%). These shortcomings outline an urgent need for alternative data sources. The other widely cited source provided by the Center for Systems Science and Engineering at Johns Hopkins University (JHU) also deviates for Germany on average by 79% from the official numbers. We argue that Google Search and Twitter data should complement official numbers. They predict even better than the original values from Johns Hopkins University and do so several days ahead. These two data sources could also be used in parts of the world where official numbers do not exist or are perceived to be unreliable.

Title: Transmission risk of patients with COVID-19 meeting discharge criteria should be interpreted with caution Content: As of Apr. 22, 2020, the World Health Organization (2020) has reported over 2.4 million confirmed coronavirus disease 2019 (COVID-19) patients and 169 151 deaths. Recent articles have uncovered genomic characteristics and clinical features of COVID-19 (Chan et al., 2020; Chang et al., 2020; Guan et al., 2020; Zhu et al., 2020), while our understanding of COVID-19 is still limited. As suggested by guidelines promoted by the General Office of National Health Commission of the People's Republic of China (2020) (from Versions 1 to 6), discharged standards for COVID-19 were still dependent on viral real-time polymerase chain reaction (RT-PCR) tests of respiratory specimens, showing that recovered COVID-19 patients with twice negative RT-PCR could meet discharge criteria. Here, we examined two cases in which nucleic acid test results were inconsistent with clinical and radiological findings, leading to suboptimal care.

Title: Test sensitivity is secondary to frequency and turnaround time for COVID-19 surveillance Content: The COVID-19 pandemic has created a public health crisis. Because SARS-CoV-2 can spread from individuals with pre-symptomatic, symptomatic, and asymptomatic infections, the re-opening of societies and the control of virus spread will be facilitated by robust surveillance, for which virus testing will often be central. After infection, individuals undergo a period of incubation during which viral titers are usually too low to detect, followed by an exponential growth of virus, leading to a peak viral load and infectiousness, and ending with declining viral levels and clearance. Given the pattern of viral load kinetics, we model surveillance effectiveness considering test sensitivities, frequency, and sample-to-answer reporting time. These results demonstrate that effective surveillance, including time to first detection and outbreak control, depends largely on frequency of testing and the speed of reporting, and is only marginally improved by high test sensitivity. We therefore conclude that surveillance should prioritize accessibility, frequency, and sample-to-answer time; analytical limits of detection should be secondary.

Title: Testing COVID-19 tests faces methodological challenges Content: Abstract In battling the COVID-19 pandemic, testing is essential. The detection of viral RNA allows the identification of infected persons, while the detection of antibodies may reveal a response to a previous infection. Tests for coronavirus should be rigorously evaluated in terms of their analytical and clinical performance. This poses not only logistic challenges, but also methodological ones. Some of these are generic for the diagnostic accuracy paradigm, while others are more specific for tests for viruses. Problematic for evaluations of the clinical performance of tests for viral RNA is the absence of an independent reference standard. Many studies lack rigor in terms of the recruitment of study participants. Study reports are often insufficiently informative, which makes it difficult to assess the applicability of study findings. Attempts to summarize the performance of these tests in terms of a single estimate of the clinical sensitivity fails to do justice to the identifiable sources of the large heterogeneity in mechanisms for generating false negative results.

Title: COVID-19 Waves: Importance of Accumulative Mortality per Million Inhabitants Content: The reported number of new cases underestimates the real spread of COVID-19 pandemic because of non-tested asymptomatic people and limited global access to reliable diagnostic tests. In this context, COVID-19 mortality with confirmed diagnosis becomes an attractive source of information to be included in the analysis of perspectives and proposals. Objective data are required to calculate the capacity of resources provided by health systems. New strategies are needed to stabilize or minimize the mortality surge. However, we will not afford this goal until more alternatives were available. We still need an effective treatment, an affordable vaccine, or a collective achievement of sufficient immunity (reaching up to 70% of the whole population). At any time, the arriving waves of the pandemic are testing the capacity of governments. The health services struggle to keep the plateau in a steady-state below 100 deaths per million inhabitants. Therefore, it is necessary to increase the alternatives and supplies based on the current and near-future expected demands imposed by the number of deaths by COVID-19. Estimating COVID-19 mortality in various scenarios with the gradual release of social constraints will help predict the magnitude of those arriving waves.

Title: COVID-19 Waves: Importance of Accumulative Mortality per Million Inhabitants. Content: The reported number of new cases underestimates the real spread of COVID-19 pandemic because of non-tested asymptomatic people and limited global access to reliable diagnostic tests. In this context, COVID-19 mortality with confirmed diagnosis becomes an attractive source of information to be included in the analysis of perspectives and proposals. Objective data are required to calculate the capacity of resources provided by health systems. New strategies are needed to stabilize or minimize the mortality surge. However, we will not afford this goal until more alternatives were available. We still need an effective treatment, an affordable vaccine, or a collective achievement of sufficient immunity (reaching up to 70% of the whole population). At any time, the arriving waves of the pandemic are testing the capacity of governments. The health services struggle to keep the plateau in a steady-state below 100 deaths per million inhabitants. Therefore, it is necessary to increase the alternatives and supplies based on the current and near-future expected demands imposed by the number of deaths by COVID-19. Estimating COVID-19 mortality in various scenarios with the gradual release of social constraints will help predict the magnitude of those arriving waves.

Title: Detecting the Emergent or Re-Emergent COVID-19 Pandemic in a Country: Modelling Study of Combined Primary Care and Hospital Surveillance Content: Aims: We aimed to determine the effectiveness of surveillance using testing for SARS-CoV-2 to identify an outbreak arising from a single case of border control failure at a country level. Methods: A stochastic version of the SEIR model CovidSIM v1.1 designed specifically for COVID-19 was utilised. It was seeded with New Zealand (NZ) population data and relevant parameters sourced from the NZ and international literature. Results: For what we regard as the most plausible scenario with an effective reproduction number of 2.0, the results suggest that 95% of outbreaks from a single imported case would be detected in the period up to day 33 after introduction. At the time point of detection, there would be a median number of 6 infected cases in the community (95%UI: 1-68). To achieve this level of detection, an on-going programme of 7,800 tests per million people per week for the NZ population would be required. The vast majority of this testing (96%) would be of symptomatic cases in primary care settings and the rest in hospitals. Despite the large number of tests required, there are plausible strategies to enhance testing yield and cost-effectiveness eg, (i) adjusting the eligibility criteria via symptom profiles; (ii) and pooling of test samples. Conclusions: This model-based analysis suggests that a surveillance system with a very high level of routine testing is probably required to detect an emerging or re-emerging SARS-CoV-2 outbreak within one month of a border control failure in a nation.

Title: Laboratory preparedness for SARS-CoV-2 testing in India: Harnessing a network of Virus Research & Diagnostic Laboratories Content: BACKGROUND & OBJECTIVES: An outbreak of respiratory illness of unknown aetiology was reported from Hubei province of Wuhan, People's Republic of China, in December 2019. The outbreak was attributed to a novel coronavirus (CoV), named as severe acute respiratory syndrome (SARS)-CoV-2 and the disease as COVID-19. Within one month, cases were reported from 25 countries. In view of the novel viral strain with reported high morbidity, establishing early countrywide diagnosis to detect imported cases became critical. Here we describe the role of a countrywide network of VRDLs in early diagnosis of COVID-19. METHODS: The Indian Council of Medical Research (ICMR)-National Institute of Virology (NIV), Pune, established screening as well as confirmatory assays for SARS-CoV-2. A total of 13 VRDLs were provided with the E gene screening real-time reverse transcription-polymerase chain reaction (rRT-PCR) assay. VRDLs were selected on the basis of their presence near an international airport/seaport and their past performance. The case definition for testing included all individuals with travel history to Wuhan and symptomatic individuals with travel history to other parts of China. This was later expanded to include symptomatic individuals returning from Singapore, Japan, Hong Kong, Thailand and South Korea. RESULTS: Within a week of standardization of the test at NIV, all VRDLs could initiate testing for SARS-CoV-2. Till February 29, 2020, a total of 2,913 samples were tested. This included both 654 individuals quarantined in the two camps and others fitting within the case definition. The quarantined individuals were tested twice - at days 0 and 14. All tested negative on both occasions. Only three individuals belonging to different districts in Kerala were found to be positive. INTERPRETATION & CONCLUSIONS: Sudden emergence of SARS-CoV-2 and its potential to cause a pandemic posed an unsurmountable challenge to the public health system of India. However, concerted efforts of various arms of the Government of India resulted in a well-coordinated action at each level. India has successfully demonstrated its ability to establish quick diagnosis of SARS-CoV-2 at NIV, Pune, and the testing VRDLs.

Title: Laboratory preparedness for SARS-CoV-2 testing in India: Harnessing a network of Virus Research & Diagnostic Laboratories Content: Background & objectives: An outbreak of respiratory illness of unknown aetiology was reported from Hubei province of Wuhan, People's Republic of China, in December 2019. The outbreak was attributed to a novel coronavirus (CoV), named as severe acute respiratory syndrome (SARS)-CoV-2 and the disease as COVID-19. Within one month, cases were reported from 25 countries. In view of the novel viral strain with reported high morbidity, establishing early countrywide diagnosis to detect imported cases became critical. Here we describe the role of a countrywide network of VRDLs in early diagnosis of COVID-19. Methods: The Indian Council of Medical Research (ICMR)-National Institute of Virology (NIV), Pune, established screening as well as confirmatory assays for SARS-CoV-2. A total of 13 VRDLs were provided with the E gene screening real-time reverse transcription-polymerase chain reaction (rRT-PCR) assay. VRDLs were selected on the basis of their presence near an international airport/seaport and their past performance. The case definition for testing included all individuals with travel history to Wuhan and symptomatic individuals with travel history to other parts of China. This was later expanded to include symptomatic individuals returning from Singapore, Japan, Hong Kong, Thailand and South Korea. Results: Within a week of standardization of the test at NIV, all VRDLs could initiate testing for SARS-CoV-2. Till February 29, 2020, a total of 2,913 samples were tested. This included both 654 individuals quarantined in the two camps and others fitting within the case definition. The quarantined individuals were tested twice - at days 0 and 14. All tested negative on both occasions. Only three individuals belonging to different districts in Kerala were found to be positive. Interpretation & conclusions: Sudden emergence of SARS-CoV-2 and its potential to cause a pandemic posed an unsurmountable challenge to the public health system of India. However, concerted efforts of various arms of the Government of India resulted in a well-coordinated action at each level. India has successfully demonstrated its ability to establish quick diagnosis of SARS-CoV-2 at NIV, Pune, and the testing VRDLs.

Title: Data-driven Identification of Number of Unreported Cases for COVID-19: Bounds and Limitations Content: Accurate forecasts for COVID-19 are necessary for better preparedness and resource management. Specifically, deciding the response over months or several months requires accurate long-term forecasts which is particularly challenging as the model errors accumulate with time. A critical factor that can hinder accurate long-term forecasts, is the number of unreported/asymptomatic cases. While there have been early serology tests to estimate this number, more tests need to be conducted for more reliable results. To identify the number of unreported/asymptomatic cases, we take an epidemiology data-driven approach. We show that we can identify lower bounds on this ratio or upper bound on actual cases as a factor of reported cases. To do so, we propose an extension of our prior heterogeneous infection rate model, incorporating unreported/asymptomatic cases. We prove that the number of unreported cases can be reliably estimated only from a certain time period of the epidemic data. In doing so, we construct an algorithm called Fixed Infection Rate method, which identifies a reliable bound on the learned ratio. We also propose two heuristics to learn this ratio and show their effectiveness on simulated data. We use our approaches to identify the upper bounds on the ratio of actual to reported cases for New York City and several US states. Our results demonstrate with high confidence that the actual number of cases cannot be more than 35 times in New York, 40 times in Illinois, 38 times in Massachusetts and 29 times in New Jersey, than the reported cases.

Title: Public health measures to slow community spread of COVID-19 ;The Journal of Infectious Diseases ;Oxford Academic Content: COVID-19 was initially identified in an outbreak of viral pneumonia in Wuhan in December 2019, and has now been recognized in 77 countries with over 90,000 laboratory-confirmed cases and over 3,000 deaths as of 3 March 2020 [1] The epidemiology of COVID-19 has recently become clearer as incident cases continue to rise and researchers refine estimates of the severity, transmissibility, and populations affected Based on available data, COVID-19 is efficiently transmitted in the community, and the proportion of infections leading to severe illness is particularly high among adults ≥50 years of age and among individuals with comorbid health conditions Although rare, severe cases have also been reported among younger individuals Thus far, the estimated basic reproductive number (R0) of COVID-19 is higher than that of influenza [2], as is the case fatality risk for adults and older individuals An estimated 80% of COVID-19 cases are mild [1] This is not a glass half full statistic, as 20% of infections result in clinically severe cases that have the potential to overwhelm already overburdened health facilities Given the lack of vaccines and effective antivirals, nonpharmaceutical interventions (NPIs) are the most effective available interventions for local and global control and mitigation of COVID-19 To date, measures aimed at slowing introduction of infection globally have included travel restrictions, isolation of confirmed cases, and quarantine of exposed persons In the United States, NPIs have reduced the number of infected persons entering the country, but recent outbreaks in multiple US states make it clear that these measures have delayed but not prevented community transmission In 2009, NPIs were able to delay large epidemic waves of pandemic influenza A(H1N1)pdm09 in some locations until after the summer, since influenza transmission tends to be reduced by higher temperatures and humidity It is unclear whether COVID-19 transmission will be heavily affected by seasonal weather variation, given that transmission is now occurring in multiple tropical and sub-tropical locations

Title: Early trends for SARS-CoV-2 infection in central and north Texas and impact on other circulating respiratory viruses Content: Introduction: Rapid diagnosis and isolation are key to containing the rapid spread of a pandemic agent like SARS-CoV-2, which has spread globally since its initial outbreak in Wuhan province in China. SARS-CoV-2 is novel to most parts of the world including USA and the effect on normally prevalent viruses is just becoming apparent. We present our initial data on the prevalence of respiratory viruses in the month of March, 2020. Methods: This is a retrospective cohort study post launching of SARS-CoV-2 testing at BSWH, Temple TX. Testing for SARS-CoV-2 was performed by real-time RT-PCR assay and results were shared with State public health officials for immediate interventions. Results: More than 3500 tests were performed during the first two weeks of testing for SARS-CoV-2 and identified 168 (4.7%) positive patients. Sixty-two (3.2%) of the 1,912 ambulatory patients and 106 (6.3%) of the 1,659 ED/inpatients were tested positive. Higher rate of infection (6.9%) were noted in the patients belonging to age group 25-34 years and least number of positive cases were noted in <25 years old (2%) group. The TX State county specific patient demographic information was shared with respective public health departments for epidemiological interventions. Incidentally, this study showed that there was a sudden decrease in the occurrence of other infections due to seasonal viruses, perhaps due to increased epidemiological awareness, about SARS-CoV-2, among general public. Authors would also like to share a small study on SARS-CoV-2 serological assay for the detection of IgG antibodies. Conclusions: This study was intended to provide an initial experience of dealing with a pandemic and the role of laboratories in crisis management. Epidemiological interventions depend on timely availability of accurate diagnostic tests and throughput capacity of such systems during large outbreaks like SARS-CoV-2.

Title: Asymptomatic patients and asymptomatic phases of Coronavirus Disease 2019 (COVID-19): a population-based surveillance study Content: In this population-based study, we identified 307 confirmed COVID-19 cases from massive surveillance, including 129,551 individuals screened at fever clinics or returning from Hubei and 3710 close contacts of confirmed COVID-19 patients. Among them, 17 patients were asymptomatic at initial clinical assessment. These asymptomatic patients on admission accounted for a small proportion of all patients (5.54%) with relatively weak transmissibility, and the detection rate was 0.35 per 100 close contacts. Moreover, the dynamics of symptoms of the 307 patients showed that the interval from symptom remission to the final negativity of viral nucleic acid was 5.0 days (IQR 2.0 to 11.0 days), with 14 patients (4.56%) having re-detectable viral RNA after discharge. Together, our findings suggested asymptomatic carriers and presymptomatic patients only accounted for a small proportion of COVID-19. Also, the asymptomatic phase in during recovery of COVID-19 urged that negativity in viral RNA is necessary as de-isolation criteria and follow-up is recommended.

Title: Estimating the Early Outbreak Cumulative Incidence of COVID-19 in the United States: Three Complementary Approaches Content: Effectively designing and evaluating public health responses to the ongoing COVID-19 pandemic requires accurate estimation of the weekly incidence of COVID-19. Unfortunately, a lack of systematic testing across the United States (US) due to equipment shortages and varying testing strategies has hindered the usefulness of the reported positive COVID-19 case counts. We introduce three complementary approaches to estimate the cumulative incidence of symptomatic COVID-19 during the early outbreak in each state in the US as well as in New York City, using a combination of excess influenza-like illness reports, COVID-19 test statistics, and COVID-19 mortality reports. Instead of relying on an estimate from a single data source or method that may be biased, we provide multiple estimates, each relying on different assumptions and data sources. Across our three approaches, there is a consistent conclusion that estimated state-level COVID-19 symptomatic case counts from March 1 to April 4, 2020 varied from 5 to 50 times greater than the official positive test counts. Nationally, our estimates of COVID-19 symptomatic cases in the US as of April 4 have a likely range of 2.2 to 5.1 million cases, with possibly as high as 8.1 million cases, up to 26 times greater than the cumulative confirmed cases of about 311,000. Extending our method to May 16, 2020, we estimate that cumulative symptomatic incidence ranges from 6.0 to 12.2 million, which compares with 1.5 million positive test counts. Our approaches demonstrate the value of leveraging existing influenza-like-illness surveillance systems during the flu season for measuring the burden of new diseases that share symptoms with influenza-like-illnesses. Our methods may prove useful in assessing the burden of COVID-19 during upcoming flu seasons in the US and other countries with comparable influenza surveillance systems.

Title: Estimating cases of COVID-19 from Daily Death Data in Italy Content: COVID-19 is an emerging infectious disease which has been declared a pan- demic by the World Health Organisation. Due to limited testing capacity for this new virus, variable symptomatology the majority of infected showing non-specific mild or no symptoms it is likely current prevalence data is an underestimate. Methods: We present an estimate of the number of cases of COVID-19 com- pared to the number of confirmed case in Italy based on the daily reported deaths and information about the incubation period, time from symptom on- set to death and reported case fatality rate. Results: Our model predicts that on the 31st of January 2020 when the first 3 infected cases had been identified by Italian authorise there were already nearly 30 cases in Italy, and by the 24th of February 2020 only 0.5% cases had been detected and confirmed by Italian authorities. While official statistics had 132 confirmed case we believe a more accurate estimate would be closer to 26000. With a case-doubling period of about 2.5 days.

Title: Global prediction of unreported SARS-CoV2 infection from observed COVID-19 cases Content: Summary: Estimation of infectiousness and fatality of the SARS-CoV-2 virus in the COVID-19 global pandemic is complicated by ascertainment bias resulting from incomplete and non-representative samples of infected individuals. We developed a strategy for overcoming this bias to obtain more plausible estimates of the true values of key epidemiological variables. We fit mechanistic Bayesian latent-variable SIR models to confirmed COVID-19 cases, deaths, and recoveries, for all regions (countries and US states) independently. Bayesian averaging over models, we find that the raw infection incidence rate underestimates the true rate by a factor, the case ascertainment ratio CARt that depends upon region, and show how CARt changes over time. At the regional onset of COVID-19, the predicted global median for each case confirmed was 13 infections unreported (CARt = 0.07 C.I. (0.02, 0.4)). As the infection spread, the median CARt rose to 9 unreported cases for every one diagnosed as of April 15, 2020 (CARt = 0.1 C.I. (0.02, 0.5)). We also estimate that the median global initial reproduction number R0 is 3.3 (C.I (1.5, 8.3)) and the total infection fatality rate near the onset is 0.17% (C.I. (0.05%, 0.9%)). However the time-dependent reproduction number Rt and infection fatality rate as of April 15 were 1.2 (C.I. (0.6, 2.5)) and 0.8% (C.I. (0.2%,4%)), respectively. We find that there is great variability between country- and state-level values. Our estimates are consistent with recent serological estimates of cumulative infections for the state of New York, but inconsistent with claims that very large fractions of the population have already been infected in most other regions. For most regions, our estimates imply a great deal of uncertainty about the current state and trajectory of the epidemic.

Title: Projection of COVID-19 Pandemic in Uganda Content: COVID-19 (Corona Virus) is caused by Severe Acute Respiratory Syndrome Corona Virus 2 (SARS-COV-2). The virus that was first discovered in China Wuhan Province about 3 months ago (first cases were reported in Wuhan on December 31st, 2019) has spread world wide. The six (6) top countries (excluding China) most affected so far include; USA, Italy, Spain, Germany, France, and Iran. With Italy showing the highest death toll. In Uganda where it was discovered on 19/3/2020 with one (01) case has just in nine (9) days, increased to thirty (30) infected individuals. This model is a wake-up call over the rate at which COVID-19 is likely to spread throughout the country. Thus it is a guide for policymakers and planners to benchmark on for solutions to this deadly virus.

Title: Test, test, test for COVID-19 antibodies: the importance of sensitivity, specificity and predictive powers Content: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) antibody tests of varying specificity and sensitivity are now available. For informing individuals whether they have had coronavirus disease 2019 (COVID-19), they need to be very accurate. For measuring population prevalence of past infection, the numbers of false positives and negatives need to be roughly equal. With a series of worked examples for a notional population of 100,000 people, we show that even test systems with a high specificity can yield a large number of false positive results, especially where the population prevalence is low. For example, at a true population prevalence of 5%, using a test with 99% sensitivity and specificity, 16% of positive results will be false and thus 950 people will be incorrectly informed they have had the infection. Further confirmatory testing may be needed. Giving false reassurance on which personal or societal decisions might be based could be harmful for individuals, undermine public confidence and foster further outbreaks.

Title: Burden of COVID-19 pandemic in India: Perspectives from Health Infrastructure Content: The coronavirus (COVID-19) is spreading rapidly across the country but testing regime of India is far from the global standards. It is important to identify the states where testing needs expansion and the magnitudes of active COVID cases are higher focusing on current health infrastructure to meet the pandemic. The data on COVID-19 was extracted from the Application Programming Interface. Test positive rate, test per confirmed case, recovery rate, case fatality rate, and percent distribution of active cases were computed. Availability of hospitals, hospital beds, intensive care unit and ventilators per lakh population was also computed by public and private sector. The result revealed that, Maharashtra constitutes more than one-third positive cases in the country. More than a quarter of the active cases in India belonged to the Mumbai district of Maharashtra, followed by the Chennai district (9.4%) and Ahmedabad district (9.1%). Further, about 40 percent of the active cases in India belonged to the 11 districts of Maharashtra. The increased test positive rate in Maharashtra and Gujarat to almost double in last one month is a concern. In order to bring the states and the country in right track, the test positive rate need to be brought down to below 2 percent. The procurement of higher number of high throughput machine, the Cobas 6800 testing machine, is need of the hour. Only few states have adequate health infrastructure. The priority should be the laid on expansion of more laboratories and hospitals, storage of PPE kit, testing kit, and indigenously developed vaccines.

Title: The misleading illusion of COVID-19 confirmed case data: alternative estimates and a monitoring tool Content: Confirmed Case Data have been widely cited during the current COVID-19 pandemic as an estimate of the spread of the SARS-CoV-2 virus. However, their central role in media, official reports and decision-making may be undeserved and misleading. Previously published Infection Fatality Rates were weighted by age structure in the 50 countries with more reported deaths to obtain country-specific rates. For each country, the number of infections up to the Infection Date (23 days ago = Incubation Period + Onset to Death period) and the present percentage of immune population were estimated using Infection Fatality Rate, the number of reported deaths (which is less prone to undersampling), and projecting back to Infection Date. We then estimated a Detection Index for each country as the percentage of estimated infections that confirmed cases represent. Assuming that detection remains constant after Infection Date, we estimated the number of deaths and the estimated percentage of the population of each country expected to be immune up to 23 days into the future. Estimated Infection Fatality Rates are higher in Europe. In most countries, confirmed cases currently represent less than 30% of estimated infections on Infection Date, and this value decreases with time. Countries with flat curves throughout the pandemic show the lowest immunity percentages and these values seem unlikely to change in the near future, suggesting that they remain vulnerable to new outbreaks. Estimates for some countries with low Infection Fatality Rates suggest a still steep increase in the number of casualties in the next three weeks. Countries that did not control initial outbreaks seem to have reached higher immunity percentages, although mostly still under 5%. We provide the code to monitor the trajectories of these estimates in 178 countries throughout the COVID-19 pandemic.

Title: COVID-19: The unreasonable effectiveness of simple models Content: When the novel coronavirus disease SARS-CoV2 (COVID-19) was officially declared a pandemic by the WHO in March 2020, the scientific community had already braced up in the effort of making sense of the fast-growing wealth of data gathered by national authorities all over the world. However, despite the diversity of novel theoretical approaches and the comprehensiveness of many widely established models, the official figures that recount the course of the outbreak still sketch a largely elusive and intimidating picture. Here we show unambiguously that the dynamics of the COVID-19 outbreak belongs to the simple universality class of the SIR model and extensions thereof. Our analysis naturally leads us to establish that there exists a fundamental limitation to any theoretical approach, namely the unpredictable non-stationarity of the testing frames behind the reported figures. However, we show how such bias can be quantified self-consistently and employed to mine useful and accurate information from the data. In particular, we describe how the time evolution of the reporting rates controls the occurrence of the apparent epidemic peak, which typically follows the true one in countries that were not vigorous enough in their testing at the onset of the outbreak. The importance of testing early and resolutely appears as a natural corollary of our analysis, as countries that tested massively at the start clearly had their true peak earlier and less deaths overall.

Title: Scrutinising the COVID-19 data on 590.000 cases. A retrospective, population-based descriptive study for data quality surveillance and a review at 4.540.000 cases. Content: Reports on the detected positive patients with COVID-19 are as per today the best estimation of a country spread of the pandemic. In order to evaluate the early indicators for true lethality and recovery time, the data where the model is built must be quality checked. Each country sets different procedures and criteria for fatality count due to COVID-19 and the health system is stressed by having insufficient testing, untracked patients and premature discharge. In this paper the dynamics behind such data quality issues are discussed throughout the disease course to support better modeling and decision-making processes in a stressed healthcare system. From 593.291 cases in the sample, and its 7 representative groups, the recovery time and the local CFR are negatively correlated, having the highest fatality rates (21%, Spain) the countries with shorter recovery time (11 days, Spain). Also, CFR can be an indicator of Infection inconsistencies (i.e. South Korea, CFR 1%, Time to recovery 25 days). At the review part, focus is made on the inconsistencies detected in Germany and South Korea datasets as well as the potential misfits on China and Spain. Overall, the Time to Fatality ranges between 4 and 8 days, and the mean is of 6 days (South Korea, 7 days; Japan, 6days). Only Germany and France are detecting earlier than other countries and admit 10 days before fatality occurs. One simple explanation for the local CFR and Recovery time correlation is to define such rate as a measure of the healthcare system overload. Anomalous CFR indexes point to a stressed healthcare system. The higher the overload, the more focus on critical cases and hence the higher local CFR. The COVID-19 intrinsic CFR is unlikely to change by a factor of 10x from countries with similar lifestyle, GDP per capita and health services (i.e. the Mediterranean Basin, Northern Europe, etc.). Because of this fact, early CFR measured before Healthcare system overwhelming (COVID-19 free flow) are considered to be more accurate than the measured CFR while the outbreak is still ongoing, Finally, the synthetic Infection indexes may be a helpful indirect measure of the real population infection rate and also used for data quality audit. Any model built upon inconsistent data will be complex to explain and justify.

Title: Dynamic of SARS-CoV-2 RT-PCR positivity and seroprevalence among high-risk health care workers and hospital staff Content: Staff members from Covid-19 highly exposed units were invited to participate in a six month study of SARS-CoV-2 carriage and seroprevalence. The results of Day 1 and Day 15 visits show that 41 SARS-CoV-2 infections were confirmed by RT-PCR and/or serology in 326 participants (overall infection rate=12.6%). Having co-morbidity or symptoms at the time of collection was a risk factor for infection but not working as a physician/nurse. This universal screening in high-risk units irrespective of symptoms allowed asymptomatic and potentially contagious infected workers to be self-isolated during 7 days.

Title: Guidelines for Laboratory Diagnosis of Coronavirus Disease 2019 (COVID-19) in Korea Content: The outbreak of coronavirus disease 2019 (COVID-19), which began in December 2019, is still ongoing in Korea, with >9,000 confirmed cases as of March 25, 2020 COVID-19 is a severe acute respiratory syndrome Coronavirus 2 (SARS-CoV-2) infection, and real-time reverse transcription-PCR is currently the most reliable diagnostic method for COVID-19 around the world Korean Society for Laboratory Medicine and the Korea Centers for Disease Prevention and Control propose guidelines for diagnosing COVID-19 in clinical laboratories in Korea These guidelines are based on other related domestic and international guidelines, as well as expert opinions and include the selection of test subjects, selection of specimens, diagnostic methods, interpretation of test results, and biosafety

Title: Predicting Whom to Test is More Important Than More Tests - Modeling the Impact of Testing on the Spread of COVID-19 Virus By True Positive Rate Estimation Content: I estimate plausible true positive (TP) rates for the number of COVID-19 tests per day, most relevant when the number of test is on the same order of magnitude as number of infected persons. I then modify a standard SEIR model to model current growth patterns and detection rates in South Korea and New York state. Although reducing transmission rates have the largest impact, increasing TP rates by ~10% in New York can have an impact equal to adding tens of thousands of new tests per day. Increasing both TP rates and tests per day together can have significant impacts and likely be more easily sustained than social distancing restrictions. Systematic and standardized data collection, even beyond contact tracking, should be ongoing and quickly made available for research teams to maximize the efficacy of testing.

Title: Prevalence of SARS-CoV-2 among workers returning to Bihar gives snapshot of COVID across India Content: India has reported the fourth highest number of confirmed SARS-CoV-2 cases worldwide. Because there is little community testing for COVID, this case count is likely an underestimate. When India partially exited from lockdown on May 4, 2020, millions of daily laborers left cities for their rural family homes. RNA testing on a near-random sample of laborers returning to the state of Bihar is used to estimate positive testing rate for COVID across India for a 6-week period immediately following the initial lifting of India's lockdown. Positive testing rates among returning laborers are only moderately correlated with, and 21% higher than, Indian states' official reports, which are not based on random sampling. Higher prevalence among returning laborers may also reflect greater COVID spread in crowded poor communities such as slums.

Title: Co-detection of respiratory pathogens in patients hospitalized with Coronavirus viral disease-2019 pneumonia. Content: Clinical, laboratory and imaging characteristics of Coronavirus disease 2019 (Covid-19) and risk factors associated with poor outcomes have been reported in various studies.1-2 Nevertheless, information on whether other respiratory pathogens (RP) were co-detected in patients in these series was not provided, despite the fact that coinfections with RP have been reported to occur in this clinical setting.3-6 This article is protected by copyright. All rights reserved.

Title: Contact tracing: Unearthing key epidemiological features of COVID-19 Content: COVID-19 is an emerging global pandemic with a steady rise in both morbidity and mortality over the past few months. Contact tracing of COVID-19 patients is an essential task to mitigate the spread. The following case was one of the initial patients reported from India and details the importance of contact tracing, timely testing and adequate quarantine/isolation in disease control.

Title: Point-of-Care Diagnostic Tests for Detecting SARS-CoV-2 Antibodies: A Systematic Review and Meta-Analysis of Real-World Data Content: SARS-CoV-2 is responsible for a highly contagious infection, known as COVID-19. SARS-CoV-2 was discovered in late December 2019 and, since then, has become a global pandemic. Timely and accurate COVID-19 laboratory testing is an essential step in the management of the COVID-19 outbreak. To date, assays based on the reverse-transcription polymerase chain reaction (RT-PCR) in respiratory samples are the gold standard for COVID-19 diagnosis. Unfortunately, RT-PCR has several practical limitations. Consequently, alternative diagnostic methods are urgently required, both for alleviating the pressure on laboratories and healthcare facilities and for expanding testing capacity to enable large-scale screening and ensure a timely therapeutic intervention. To date, few studies have been conducted concerning the potential utilization of rapid testing for COVID-19, with some conflicting results. Therefore, the present systematic review and meta-analysis was undertaken to explore the feasibility of rapid diagnostic tests in the management of the COVID-19 outbreak. Based on ten studies, we computed a pooled sensitivity of 64.8% (95%CI 54.5–74.0), and specificity of 98.0% (95%CI 95.8–99.0), with high heterogeneity and risk of reporting bias. We can conclude that: (1) rapid diagnostic tests for COVID-19 are necessary, but should be adequately sensitive and specific; (2) few studies have been carried out to date; (3) the studies included are characterized by low numbers and low sample power, and (4) in light of these results, the use of available tests is currently questionable for clinical purposes and cannot substitute other more reliable molecular tests, such as assays based on RT-PCR.