Question: what evidence is there related to COVID-19 super spreaders

Title: Significance of super spreader events in COVID-19 Content: The number of secondary cases from each primary case determines how fast an epidemic grows. It is known that all cases do not spread the infection equally; super spreaders play an important role as they contribute disproportionately to a much larger number of cases including in the ongoing COVID-19 pandemic. Super spreaders have been reported for more than a century, but limited information is available in scientific literature. An epidemic containment strategy needs to include early identification of super spreaders to limit an explosive growth. Super spreaders tend to get stigmatized, resulting in late reporting and hiding of cases. It is important for program managers to be sensitive to the manner in which related information is shared with media and general public.

Title: Significance of super spreader events in COVID-19. Content: The number of secondary cases from each primary case determines how fast an epidemic grows. It is known that all cases do not spread the infection equally; super spreaders play an important role as they contribute disproportionately to a much larger number of cases including in the ongoing COVID-19 pandemic. Super spreaders have been reported for more than a century, but limited information is available in scientific literature. An epidemic containment strategy needs to include early identification of super spreaders to limit an explosive growth. Super spreaders tend to get stigmatized, resulting in late reporting and hiding of cases. It is important for program managers to be sensitive to the manner in which related information is shared with media and general public.

Title: Do superspreaders generate new superspreaders? a hypothesis to explain the propagation pattern of COVID-19 Content: Abstract The current global propagation of COVID-19 is heterogeneous, with slow transmission continuing in many countries, and exponential propagation in others, in which the time that took to begin this explosive spread varies greatly. It is proposed that this could be explained by cascading superspreading events, in which new infections caused by a superspreader are more likely to be highly infectious. The mechanism suggested for this is related to viral loads. Exposure to high viral loads may result in infections of high intensity, which exposes new cases to high viral loads, and so on. This notion is supported by experimental veterinary research.

Title: Do superspreaders generate new superspreaders? A hypothesis to explain the propagation pattern of COVID-19 Content: The current global propagation of COVID-19 is heterogeneous, with slow transmission continuing in many countries and exponential propagation in others, where the time that it took for the explosive spread to begin varied greatly. It is proposed that this could be explained by cascading superspreading events, in which new infections caused by a superspreader are more likely to be highly infectious. The mechanism suggested for this is related to viral loads. Exposure to high viral loads may result in high-intensity infection, which exposes new cases to high viral loads. This notion is supported by experimental veterinary research.

Title: Identification of a super-spreading chain of transmission associated with COVID-19 Content: Background: Super-spreading events were associated with the outbreaks of SARS and MERS, but their association with the outbreak of COVID-19 remains unknown. Here, we report a super-spreading transmission chain of SARS-CoV-2 involving an index patient, seven cancer patients, 40 health care workers and four family members. Methods: We conducted a retrospective study to identify the index patient and the exposed individuals linked to a chain of transmission associated with COVID-19. We collected and analyzed the data on demographic features, exposure history, clinical presentation, laboratory investigation, radiological examination, and disease outcome of these patients. Results: We identified the index patient and another presumptive super-spreader, who initiated and amplified a super-spreading transmission chain associated with COVID-19, respectively. There were 31 female and 21 male patients in this cohort, and the median age was 37 years (range: 22-79 years). Each of them had an exposure history with the index patient or his close contacts. Approximately 87% (45/52) of the patients had fever or other symptoms, 96% (50/52) had abnormal chest CT-scan findings, 86% of the tested patients (39/45) were positive for SARS-CoV-2 in the nasopharyngeal or throat swab specimen, 85% of the tested patients (29/34) were positive for SARS-CoV-2-specific IgM and/or IgG, 15% of the RT-PCR positive patients were tested negative for the specific IgM and/or IgG at the convalescent phase, and 15% of the RT-PCR negative patients were tested positive for the specific IgM and/or IgG. The severe patients experienced a significant decrease in oximetry saturation, lymphocyte, and platelet counts, along with a significant increase in C-reactive protein, D-dimer, and lactate dehydrogenase. All six fatal cases had comorbidities and five of the seven cancer patients (71%) died within 2-20 days of the disease onset. Conclusions: The super-spreading events were associated with the outbreak of COVID-19 in Wuhan and its impact on disease transmission warrants further investigation. Cancer patients appeared highly vulnerable to COVID-19. The finding that a significant portion of SARS-CoV-2 infected patients were tested negative for the serum specific IgM and IgG at the convalescent phase should be addressed by additional studies.

Title: Inferring super-spreading from transmission clusters of COVID-19 in Hong Kong, Japan and Singapore Content: Super-spreading events in an outbreak can change the nature of an epidemic. Therefore, it is useful for public health teams to determine if an ongoing outbreak has any contribution from such events, which may be amenable to interventions. We estimated the basic reproductive number (R0) and the dispersion factor (k) from empirical data on clusters of epidemiologically-linked COVID-19 cases in Hong Kong, Japan and Singapore. This allowed us to infer the presence or absence of super-spreading events during the early phase of these outbreaks. The relatively large values of k implied that large cluster sizes, compatible with super-spreading, were unlikely.

Title: Inferring super-spreading from transmission clusters of COVID-19 in Hong Kong, Japan and Singapore Content: Super-spreading events in an outbreak can change the nature of an epidemic. Therefore, it is useful for public health teams to determine if an ongoing outbreak has any contribution from such events, which may be amenable to interventions. We estimated the basic reproductive number (R(0)) and the dispersion factor (k) from empirical data on clusters of epidemiologically-linked COVID-19 cases in Hong Kong, Japan and Singapore. This allowed us to infer the presence or absence of super-spreading events during the early phase of these outbreaks. The relatively large values of k implied that large cluster sizes, compatible with super-spreading, were unlikely.

Title: Evaluating Transmission Heterogeneity and Super-Spreading Event of COVID-19 in a Metropolis of China Content: COVID-19 caused rapid mass infection worldwide. Understanding its transmission characteristics, including heterogeneity and the emergence of super spreading events (SSEs) where certain individuals infect large numbers of secondary cases, is of vital importance for prediction and intervention of future epidemics. Here, we collected information of all infected cases (135 cases) between 21 January and 26 February 2020 from official public sources in Tianjin, a metropolis of China, and grouped them into 43 transmission chains with the largest chain of 45 cases and the longest chain of four generations. Utilizing a heterogeneous transmission model based on branching process along with a negative binomial offspring distribution, we estimated the reproductive number R and the dispersion parameter k (lower value indicating higher heterogeneity) to be 0.67 (95% CI: 0.54–0.84) and 0.25 (95% CI: 0.13–0.88), respectively. A super-spreader causing six infections was identified in Tianjin. In addition, our simulation allowing for heterogeneity showed that the outbreak in Tianjin would have caused 165 infections and sustained for 7.56 generations on average if no control measures had been taken by local government since 28 January. Our results highlighted more efforts are needed to verify the transmission heterogeneity of COVID-19 in other populations and its contributing factors.

Title: Evaluating Transmission Heterogeneity and Super-Spreading Event of COVID-19 in a Metropolis of China Content: COVID-19 caused rapid mass infection worldwide. Understanding its transmission characteristics, including heterogeneity and the emergence of super spreading events (SSEs) where certain individuals infect large numbers of secondary cases, is of vital importance for prediction and intervention of future epidemics. Here, we collected information of all infected cases (135 cases) between 21 January and 26 February 2020 from official public sources in Tianjin, a metropolis of China, and grouped them into 43 transmission chains with the largest chain of 45 cases and the longest chain of four generations. Utilizing a heterogeneous transmission model based on branching process along with a negative binomial offspring distribution, we estimated the reproductive number R and the dispersion parameter k (lower value indicating higher heterogeneity) to be 0.67 (95% CI: 0.54-0.84) and 0.25 (95% CI: 0.13-0.88), respectively. A super-spreader causing six infections was identified in Tianjin. In addition, our simulation allowing for heterogeneity showed that the outbreak in Tianjin would have caused 165 infections and sustained for 7.56 generations on average if no control measures had been taken by local government since 28 January. Our results highlighted more efforts are needed to verify the transmission heterogeneity of COVID-19 in other populations and its contributing factors.

Title: A super-spreader of COVID-19 in Ningbo city in China Content: An outbreak of Coronavirus Disease 2019 (COVID-19) has spread rapidly. It is imperative to control the epidemic by understanding the epidemiological feature, preventative quarantine, and effective hygiene measures. In the present study, we report a case of super-spreader who transmitted the disease to over twenty-eight persons in Ningbo, Zhejiang. Identifying and isolated super-spreaders, understanding the reasons behind the efficient transmission ability are important for the control and management of the ongoing COVID-19 pandemic.

Title: Evaluating transmission heterogeneity and super-spreading event of COVID-19 in a metropolis of China Content: Background: COVID-19 caused rapid mass infection worldwide. Understanding its transmission characteristics including heterogeneity is of vital importance for prediction and intervention of future epidemics. In addition, transmission heterogeneity usually envokes super spreading events (SSEs) where certain individuals infect large numbers of secondary cases. Till now, studies of transmission heterogeneity of COVID-19 and its underlying reason are far from reaching an agreement. MethodsWe collected information of all infected cases between January 21 and February 26, 2020 from official public sources in Tianjin, a metropolis of China. Utilizing a heterogeneous transmission model based on branching process along with a negative binomial offspring distribution, we estimated the reproductive number R and the dispersion parameter k which characterized the transmission potential and heterogeneity, respectively. Furthermore, we studied the SSE in Tianjin outbreak and evaluated the effect of control measures undertaken by local government based on the heterogeneous model. Results: A total of 135 confirmed cases (including 34 imported cases and 101 local infections) in Tianjin by February 26th 2020 entered the study. We grouped them into 43 transmission chains with the largest chain of 45 cases and the longest chain of 4 generations. The estimated reproduction number R was at 0.67 (95%CI: 0.54[~]0.84), and the dispersion parameter k was at 0.25 (95% CI: 0.13[~]0.88). A super spreader causing six infections in Tianjin, was identified. In addition, our simulation results showed that the outbreak in Tianjin would have caused 165 infections and sustained for 7.56 generations on average if no control measures had been taken by local government since January 28th. Conclusions: Our analysis suggested that the transmission of COVID-19 was subcritical but with significant heterogeneity and may incur SSE. More efforts are needed to verify the transmission heterogeneity of COVID-19 in other populations and its contributing factors, which is important for developing targeted measures to curb the pandemic.

Title: MERS, SARS, and Ebola: The Role of Super-Spreaders in Infectious Disease Content: Super-spreading occurs when a single patient infects a disproportionate number of contacts. The 2015 MERS-CoV, 2003 SARS-CoV, and to a lesser extent 2014–15 Ebola virus outbreaks were driven by super-spreaders. We summarize documented super-spreading in these outbreaks, explore contributing factors, and suggest studies to better understand super-spreading.

Title: Reconstruction of Transmission Pairs for novel Coronavirus Disease 2019 (COVID-19) in mainland China: Estimation of Super-spreading Events, Serial Interval, and Hazard of Infection Content: BACKGROUND: Knowledge on the epidemiological features and transmission patterns of COVID-19 is accumulating. Detailed line-list data with household settings can advance the understanding of COVID-19 transmission dynamics. METHODS: A unique database with detailed demographic characteristics, travel history, social relationships, and epidemiological timelines for 1,407 transmission pairs that formed 643 transmission clusters in mainland China was reconstructed from 9,120 COVID-19 confirmed cases reported during January 15 - February 29, 2020. Statistical model fittings were used to identify the super-spreaders and estimate serial interval distributions. Age and gender-stratified hazard of infection were estimated for household versus non-household transmissions. RESULTS: There were 34 primary cases identified as super-spreaders, with 5 super-spreading events occurred within households. Mean and standard deviation of serial intervals were estimated as 5.0 (95% CrI: 4.4, 5.5) and 5.2 (95% CrI: 4.9, 5.7) days for household transmissions and 5.2 (95% CrI: 4.6, 5.8) and 5.3 (95% CrI: 4.9, 5.7) days for non-household transmissions, respectively. Hazard of being infected outside of households is higher for age between 18 and 64 years, whereas hazard of being infected within households is higher for young and old people. CONCLUSIONS: Non-negligible frequency of super-spreading events, short serial intervals, and a higher risk of being infected outside of households for male people of working age indicate a significant barrier to the identification and management of COVID-19 cases, which requires enhanced non-pharmaceutical interventions to mitigate this pandemic.

Title: Genetic cluster analysis of SARS-CoV-2 and the identification of those responsible for the major outbreaks in various countries Content: A newly emerged coronavirus, SARS-CoV-2, caused severe pneumonia outbreaks in China in December 2019 and has since spread to various countries around the world. To trace the evolution route and probe the transmission dynamics of this virus, we performed phylodynamic analysis of 247 high quality genomic sequences available in the GISAID platform as of 5 March 2020. Among them, four genetic clusters, defined as super-spreaders (SSs), could be identified and were found to be responsible for the major outbreaks that subsequently occurred in various countries. SS1 was widely disseminated in Asia and the US, and mainly responsible for outbreaks in the states of Washington and California as well as South Korea, whereas SS4 contributed to the pandemic in Europe. Using the signature mutations of each SS as markers, we further analysed 1539 genome sequences reported after 29 February 2020 and found that 90% of these genomes belonged to SSs, with SS4 being the most dominant. The relative degree of contribution of each SS to the pandemic in different continents was also depicted. Identification of these super-spreaders greatly facilitates development of new strategies to control the transmission of SARS-CoV-2.

Title: Genetic cluster analysis of SARS-CoV-2 and the identification of those responsible for the major outbreaks in various countries. Content: A newly emerged coronavirus, SARS-CoV-2, caused severe pneumonia outbreaks in China in December 2019 and has since spread to various countries around the world. To trace the evolution route and probe the transmission dynamics of this virus, we performed phylodynamic analysis of 247 high quality genomic sequences available in the GISAID platform as of 5 March 2020. Among them, four genetic clusters, defined as super-spreaders (SSs), could be identified and were found to be responsible for the major outbreaks that subsequently occurred in various countries. SS1 was widely disseminated in Asia and the US, and mainly responsible for outbreaks in the states of Washington and California as well as South Korea, whereas SS4 contributed to the pandemic in Europe. Using the signature mutations of each SS as markers, we further analysed 1539 genome sequences reported after 29 February 2020 and found that 90% of these genomes belonged to SSs, with SS4 being the most dominant. The relative degree of contribution of each SS to the pandemic in different continents was also depicted. Identification of these super-spreaders greatly facilitates development of new strategies to control the transmission of SARS-CoV-2.

Title: COVID-19 Super-spreaders: Definitional Quandaries and Implications Content: Uncertainty around the role ‘super-spreaders’ play in the transmission and escalation of infectious disease is compounded by its broad and vague definition. It is a term that has been much used in relation to COVID-19, particularly in social media. On its widest definition, it refers to a propensity to infect a larger than average number of people. Given the biological, behavioural and environmental variables relevant to infectivity, this might be pertinent to almost any infected individual who is not physically isolated from others. Nor is the term confined to individuals with a propensity to spread infectious disease: it can potentially be used to describe events, policies or settings. This article explores the use of the term and considers circumstances in which the wide definition can be problematic. One problem is that it can lead to undeserved apportionment of moral blame to alleged super-spreaders. Another is that it can detract from scientific investigation of the heterogeneity of COVID-19 transmission. The author calls for a clearer epidemiological definition.

Title: Super-spreaders in infectious diseases Content: Summary Early studies that explored host–pathogen interactions assumed that infected individuals within a population have equal chances of transmitting the infection to others. Subsequently, in what became known as the 20/80 rule, a small percentage of individuals within any population was observed to control most transmission events. This empirical rule was shown to govern inter-individual transmission dynamics for many pathogens in several species, and individuals who infect disproportionately more secondary contacts, as compared to most others, became known as super-spreaders. Studies conducted in the wake of the severe acute respiratory syndrome (SARS) pandemic revealed that, in the absence of super-spreading events, most individuals infect few, if any, secondary contacts. The analysis of SARS transmission, and reports from other outbreaks, unveil a complex scenario in which super-spreading events are shaped by multiple factors, including co-infection with another pathogen, immune suppression, changes in airflow dynamics, delayed hospital admission, misdiagnosis, and inter-hospital transfers. Predicting and identifying super-spreaders open significant medical and public health challenges, and represent important facets of infectious disease management and pandemic preparedness plans.

Title: Closed environments facilitate secondary transmission of coronavirus disease 2019 (COVID-19) Content: Objective: To identify common features of cases with novel coronavirus disease (COVID-19) so as to better understand what factors promote secondary transmission including superspreading events. Methods: A total of 110 cases were examined among eleven clusters and sporadic cases, and investigated who acquired infection from whom. The clusters included four in Tokyo and one each in Aichi, Fukuoka, Hokkaido, Ishikawa, Kanagawa and Wakayama prefectures. The number of secondary cases generated by each primary case was calculated using contact tracing data. Results: Of the 110 cases examined, 27 (24.6%) were primary cases who generated secondary cases. The odds that a primary case transmitted COVID-19 in a closed environment was 18.7 times greater compared to an open-air environment (95% confidence interval [CI]: 6.0, 57.9). Conclusions: It is plausible that closed environments contribute to secondary transmission of COVID-19 and promote superspreading events. Our findings are also consistent with the declining incidence of COVID-19 cases in China, as gathering in closed environments was prohibited in the wake of the rapid spread of the disease.

Title: Superspreading in Early Transmissions of COVID-19 in Indonesia Content: We estimate the basic reproduction number R0 and the overdispersion parameter K at two COVID-19 clusters in Indonesia: Jakarta-Depok and Batam. Based on the first 397 confirmed cases in both clusters, we find a high degree of individual-level variation in the transmission. The basic reproduction number R0 is estimated at 6.79 and 2.47, while the overdispersion parameter K of a negative-binomial distribution is estimated at 0.08 and 0.2 for Jakarta-Depok and Batam, respectively. This suggests that superspreading events played a key role in the early stage of the outbreak, i.e., a small number of infected individuals are responsible for large amounts of COVID-19 transmission.

Title: COVID-19 Super-spreaders: Definitional Quandaries and Implications Content: Uncertainty around the role 'super-spreaders' play in the transmission and escalation of infectious disease is compounded by its broad and vague definition. It is a term that has been much used in relation to COVID-19, particularly in social media. On its widest definition, it refers to a propensity to infect a larger than average number of people. Given the biological, behavioural and environmental variables relevant to infectivity, this might be pertinent to almost any infected individual who is not physically isolated from others. Nor is the term confined to individuals with a propensity to spread infectious disease: it can potentially be used to describe events, policies or settings. This article explores the use of the term and considers circumstances in which the wide definition can be problematic. One problem is that it can lead to undeserved apportionment of moral blame to alleged super-spreaders. Another is that it can detract from scientific investigation of the heterogeneity of COVID-19 transmission. The author calls for a clearer epidemiological definition.

Title: Stochasticity and heterogeneity in the transmission dynamics of SARS-CoV-2 Content: SARS-CoV-2 causing COVID-19 disease has moved rapidly around the globe, infecting millions and killing hundreds of thousands. The basic reproduction number, which has been widely used and misused to characterize the transmissibility of the virus, hides the fact that transmission is stochastic, is dominated by a small number of individuals, and is driven by super-spreading events (SSEs). The distinct transmission features, such as high stochasticity under low prevalence, and the central role played by SSEs on transmission dynamics, should not be overlooked. Many explosive SSEs have occurred in indoor settings stoking the pandemic and shaping its spread, such as long-term care facilities, prisons, meat-packing plants, fish factories, cruise ships, family gatherings, parties and night clubs. These SSEs demonstrate the urgent need to understand routes of transmission, while posing an opportunity that outbreak can be effectively contained with targeted interventions to eliminate SSEs. Here, we describe the potential types of SSEs, how they influence transmission, and give recommendations for control of SARS-CoV-2.

Title: Post-donation COVID-19 identification in blood donors. Content: The coronavirus disease 19 (COVID-19) outbreak, which was characterized as a pandemic on 11 March 2020 by the WHO, started in December 2019 with the emergence of pneumonia cases of unknown cause in Wuhan, Hubei, China [1]. SARS-CoV-2, the causative agent of COVID-19, are enveloped, non-segmented, single stranded positive sense RNA viruses and are classified as a sister clade to the prototype human and bat severe acute respiratory syndrome coronaviruses (SARS-CoVs) of the species Severe acute respiratory syndrome-related coronavirus [2]. So far, no respiratory virus, including SARS-CoV and the Middle East Respiratory Syndrome (MERS)-CoV, has been confirmed as transfusion-transmissible [3,4].

Title: Characterizing super-spreading events and age-specific infectivity of COVID-19 transmission in Georgia, USA Content: As the current COVID-19 pandemic continues to impact countries around the globe, refining our understanding of its transmission dynamics and the effectiveness of interventions is imperative. In particular, it is essential to obtain a firmer grasp on the effect of social distancing, potential individual-level heterogeneities in transmission such as age-specific infectivity, and impact of super-spreading. To this end, it is important to exploit multiple data streams that are becoming abundantly available during the pandemic. In this paper, we formulate an individual-level spatio-temporal mechanistic framework to statistically integrate case data with geo-location data and aggregate mobility data, enabling a more granular understanding of the transmission dynamics of COVID-19. We analyze reported cases from surveillance data, between March and early May 2020, in five (urban and rural) counties in the State of Georgia USA. We estimate natural history parameters of COVID-19 and infer unobserved quantities including infection times and transmission paths using Bayesian data-augmentation techniques. First, our results show that the overall median reproductive number was 2.88 (with 95% C.I. [1.85, 4.9]) before the state-wide shelter-in-place order issued in early April, and the effective reproductive number was reduced to below 1 about two weeks by the order. Super-spreading appears to be widespread across space and time, and it may have a particularly important role in driving the outbreak in the rural area and increasing importance towards later stages of outbreaks in both urban and rural settings. Overall, about 2% of cases may have directly infected 20% of all infections. We estimate that the infected children and younger adults (<60 years old) may be 2.38 [1.30, 3.51] times more transmissible than infected elderly (>=60), and the former may be the main driver of super-spreading. Through the synthesis of multiple data streams using our transmission modelling framework, our results enforce and improve our understanding of the natural history and transmission dynamics of COVID-19. More importantly, we reveal the roles of age-specific infectivity and characterize systematic variations and associated risk factors of super-spreading. These have important implications for the planning of relaxing social distancing and, more generally, designing optimal control measures.

Title: Evaluating new evidence in the early dynamics of the novel coronavirus COVID-19 outbreak in Wuhan, China with real time domestic traffic and potential asymptomatic transmissions Content: The novel coronavirus (COVID-19), first detected in Wuhan, China in December 2019, has spread to 28 countries/regions with over 43,000 confirmed cases. Much about this outbreak is still unknown. At this early stage of the epidemic, it is important to investigate alternative sources of information to understand its dynamics and spread. With updated real time domestic traffic, this study aims to integrate recent evidence of international evacuees extracted from Wuhan between Jan. 29 and Feb. 2, 2020 to infer the dynamics of the COVD-19 outbreak in Wuhan. In addition, a modified SEIR model was used to evaluate the empirical support for the presence of asymptomatic transmissions. Based on the data examined, this study found little evidence for the presence of asymptomatic transmissions. However, it is still too early to rule out its presence conclusively due to sample size and other limitations. The updated basic reproductive number was found to be 2.12 on average with a 95% credible interval of [2.04, 2.18]. It is smaller than previous estimates probably because the new estimate factors in the social and non-pharmaceutical mitigation implemented in Wuhan through the evacuee dataset. Detailed predictions of infected individuals exported both domestically and internationally were produced. The estimated case confirmation rate has been low but has increased steadily to 23.37% on average. The findings of this study depend on the validity of the underlying assumptions, and continuing work is needed, especially in monitoring the current infection status of Wuhan residents.

Title: SUPERSPREADING AS A REGULAR FACTOR OF THE COVID-19 PANDEMIC Content: An impact of superspreading on the course of the COVID-19 epidemic is considered. A two-component model of the epidemic has been developed, in which all infected are divided in two groups. They are asymptomatic superspreaders spreading the infection and sensitive persons which can only get infection. Once infected the sensitive exhibit clear symptoms and become isolated. Taking into account both factors allows find the numbers of superspreaders and sensitive persons. It is shown, that the ratio of increment of the number of daily cases in the beginning of the epidemic and decrement at the end of the epidemic is equal to the ratio of numbers of the superspreaders and sensitive persons. In this way, on the base of data from 12 countries and territories, the share of asymptomatic among all infected persons is found to be (17 {+/-} 3)%. Specific measures to limit the epidemical incidence are proposed. The possibility of an allergic component in the disease is discussed.

Title: No evidence for distinct types in the evolution of SARS-CoV-2 Content: A recent study by Tang et al. (2020) claimed that two major types of SARS-CoV-2 had evolved in the ongoing COVID-19 pandemic and that one of these types was more “aggressive” than the other. Given the repercussions of these claims and the intense media coverage of these types of articles, we have examined in detail the data presented by Tang et al, and show that the major conclusions of that paper cannot be substantiated. Using examples from other viral outbreaks we discuss the difficulty in demonstrating the existence or nature of a functional effect of a viral mutation, and we advise against overinterpretation of genomic data during the pandemic.

Title: Scientometric Trends for Coronaviruses and Other Emerging Viral Infections Content: COVID-19 is the most rapidly expanding coronavirus outbreak in the past two decades. To provide a swift response to a novel outbreak, prior knowledge from similar outbreaks is essential. Here, we study the volume of research conducted on previous coronavirus outbreaks, specifically SARS and MERS, relative to other infectious diseases by analyzing over 35 million papers from the last 20 years. Our results demonstrate that previous coronavirus outbreaks have been understudied compared to other viruses. We also show that the research volume of emerging infectious diseases is very high after an outbreak and drops drastically upon the containment of the disease. This can yield inadequate research and limited investment in gaining a full understanding of novel coronavirus management and prevention. Independent of the outcome of the current COVID-19 outbreak, we believe that measures should be taken to encourage sustained research in the field.

Title: Severe acute respiratory syndrome-coronavirus 2 and novel coronavirus disease 2019: An extraordinary pandemic Content: COVID-19 has emerged as one of the most significant illnesses of the current century. It is caused by severe acute respiratory syndrome coronavirus 2. The world was initially viewing it as a localized outbreak in Wuhan city of China; however, it started spreading quickly to other parts of the world. Globally, half-hearted containment measures and a false sense of safety against this novel coronavirus led to the dissemination of disease. Currently, no effective therapy or vaccine is available to manage this illness. After learning a huge lesson, global efforts would hopefully lead to effective control of this pandemic.

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: Early detection of superspreaders by mass group pool testing can mitigate COVID-19 pandemic Content: Background Most of epidemiological models applied for COVID-19 do not consider heterogeneity in infectiousness and impact of superspreaders, despite the broad viral loading distributions amongst COVID-19 positive people (1-1 000 000 per mL). Also, mass group testing is not used regardless to existing shortage of tests. I propose new strategy for early detection of superspreaders with reasonable number of RT-PCR tests, which can dramatically mitigate development COVID-19 pandemic and even turn it endemic. Methods I used stochastic social-epidemiological SEIAR model, where S-suspected, E-exposed, I-infectious, A-admitted (confirmed COVID-19 positive, who are admitted to hospital or completely isolated), R-recovered. The model was applied to real COVID-19 dynamics in London, Moscow and New York City. Findings Viral loading data measured by RT-PCR were fitted by broad log-normal distribution, which governed high importance of superspreaders. The proposed full scale model of a metropolis shows that top 10% spreaders (100+ higher viral loading than median infector) transmit 45% of new cases. Rapid isolation of superspreaders leads to 4-8 fold mitigation of pandemic depending on applied quarantine strength and amount of currently infected people. High viral loading allows efficient group matrix pool testing of population focused on detection of the superspreaders requiring remarkably small amount of tests. Interpretation The model and new testing strategy may prevent thousand or millions COVID-19 deaths requiring just about 5000 daily RT-PCR test for big 12 million city such as Moscow. Though applied to COVID-19 pandemic the results are universal and can be used for other infectious heterogenous epidemics. Funding No funding

Title: Aktuální problematika COVID-19 z pohledu imunologa./ COVID-19 from the perspective of an immunologist Content: COVID-19 is an infectious disease caused by a coronavirus SARS-CoV-2. COVID-19 has a number of similarities to SARS and MERS diseases. Its highly contagious nature is particularly due to the rapid spread of the disease through asymptomatic individuals; however, the worlds most contagious infectious disease is still considered measles. Scientific data have revealed the interactions between COVID-19 and the immune system. These findings may contribute to the development of novel preventive and therapeutic approaches. Just as coronavirus itself the reports about the disease have massively spread through media and public contributing to overall public fear and stress. This promotion of non-scientific evidence and misinformation through social media might have also a devastating impact on the individuals immune system. Data regarding the mortality rates of COVID-19 have achieved unprecedented media and public engagements, however, the true facts about the disease prevention, immunomodulation and novel treatments are often left unsaid. We present the most recent facts about COVID-19 disease and its interactions with the immune system.

Title: COVID-19 from the perspective of an immunologist. Content: COVID-19 is an infectious disease caused by a coronavirus SARS-CoV-2. COVID-19 has a number of similarities to SARS and MERS diseases. Its highly contagious nature is particularly due to the rapid spread of the disease through asymptomatic individuals; however, the worlds most contagious infectious disease is still considered measles. Scientific data have revealed the interactions between COVID-19 and the immune system. These findings may contribute to the development of novel preventive and therapeutic approaches. Just as coronavirus itself the reports about the disease have massively spread through media and public contributing to overall public fear and stress. This promotion of non-scientific evidence and misinformation through social media might have also a devastating impact on the individuals immune system. Data regarding the mortality rates of COVID-19 have achieved unprecedented media and public engagements, however, the true facts about the disease prevention, immunomodulation and novel treatments are often left unsaid. We present the most recent facts about COVID-19 disease and its interactions with the immune system.

Title: Climate&BCG: Effects on COVID-19 Death Growth Rates Content: Multiple studies have suggested the spread of COVID-19 is affected by factors such as climate, BCG vaccinations, pollution and blood type. We perform a joint study of these factors using the death growth rates of 40 regions worldwide with both machine learning and Bayesian methods. We find weak, non-significant (<3$\sigma$) evidence for temperature and relative humidity as factors in the spread of COVID-19 but little or no evidence for BCG vaccination prevalence or $\text{PM}_{2.5}$ pollution. The only variable detected at a statistically significant level (>3$\sigma$) is the rate of positive COVID-19 tests, with higher positive rates correlating with higher daily growth of deaths.

Title: Transmission of SARS-CoV-2 by inhalation of respiratory aerosol in the Skagit Valley Chorale superspreading event Content: During the 2020 COVID-19 pandemic, an outbreak occurred following attendance of a symptomatic index case at a regular weekly rehearsal on 10 March of the Skagit Valley Chorale (SVC). After that rehearsal, 53 members of the SVC among 61 in attendance were confirmed or strongly suspected to have contracted COVID-19 and two died. Transmission by the airborne route is likely. It is vital to identify features of cases such as this so as to better understand the factors that promote superspreading events. Based on a conditional assumption that transmission during this outbreak was by inhalation of respiratory aerosol, we use the available evidence to infer the emission rate of airborne infectious quanta from the primary source. We also explore how the risk of infection would vary with several influential factors: the rates of removal of respiratory aerosol by ventilation; deposition onto surfaces; and viral decay. The results indicate an emission rate of the order of a thousand quanta per hour (mean [interquartile range] for this event = 970 [680-1190] quanta per hour) and demonstrate that the risk of infection is modulated by ventilation conditions, occupant density, and duration of shared presence with an infectious individual.

Title: Is it super-spreading? Content: If the covid-19 virus is transmitted largely by superspreaders, it might not go pandemic, reports Debora MacKenzie

Title: Climate & BCG: Effects on COVID-19 DeathGrowth Rates Content: Multiple studies have suggested the spread of COVID-19 is affected by factors such as climate, BCG vaccinations, pollution and blood type. We perform a joint study of these factors using the death growth rates of 40 regions worldwide with both machine learning and Bayesian methods. We find weak, non-significant (< 3 sigma) evidence for temperature and relative humidity as factors in the spread of COVID-19 but little or no evidence for BCG vaccination prevalence or PM2.5 pollution. The only variable detected at a statistically significant level (> 3 sigma) is the rate of positive COVID-19 tests, with higher positive rates correlating with higher daily growth of deaths.

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: Review of published systematic reviews and meta-analyses on COVID-19 Content: Purpose: The rapid spread of the COVID-19 pandemic has prompted researchers from all over the world to share their experience. The results were numerous reports with variable quality. The latter has provided an impetus to examine all published meta-analyses and systematic reviews on COVID-19 to date to examine available evidence. Methods: Using predefined selection criteria, a literature search identified 43 eligible meta-analyses and/or systematic reviews. Results: Most (N=17) studies addressed clinical manifestations and associated comorbidity, 6 studies addressed clinical manifestations in pregnant women and younger individuals, 8 studies addressed diagnostic data, 9 studies addressed various interventions, and 9 studies addressed prevention and control. The number of studies included in the various systemic reviews and meta-analyses ranged from 2 to 89. While there were some similarities and consistency for some findings, e.g. the relation between comorbidities and disease severity, we also noted occasionally conflicting data. Conclusion: As more data are collected from patients infected with COVID-19 all over the world, more studies will undoubtedly be published and attention to scientific accuracy in the performance of trials must be exercised to inform clinical decision-making and treatment guidelines.

Title: Genetic drift and environmental spreading dynamics of COVID-19 Content: Objective To delineate the genetic and environmental determinants of COVID-19 spreading. Design Retrospective case series. Setting Spain, Italy, Sweden, Finland, Norway. Participants All laboratory-confirmed infection cases (n=168,089) collected from February 21st to April 14th 2020. Main outcome measures Infection spreading velocity according to viral mutation load and to climate region. Results The mean doubling time of COVID-19 was 6.63 days in northern Italy, 5.87 days in central areas, and 5.38 days in southern Italy, with shorter COVID-19 doubling time in warmer regions. Spain extended this trend, with a mean COVID-19 doubling time of 4.2 days. At the other end of the spectrum, slower diffusion across progressively colder regions was observed in Scandinavia, with 9.4 days COVID-19 doubling time in Sweden, 10.8 days in Finland and 12.95 days in Norway. Mutations and mutation rates of SARS-CoV-2 versus COVID-19 spreading were analyzed worldwide. Models of increased aggressiveness of SARS-CoV-2 upon progressive acquisition of genetic changes were not supported by regional mutation data. Conclusion Current propagation models suggest dependence of COVID-19 pandemic spreading on wintertime conditions, with expected waning over the summer. Our findings indicate association of COVID-19 to a sharp North/South climate gradient, with faster spreading in southern regions. Thus, warmer climate conditions may not limit SARS-CoV-2 diffusion. Very cold regions may be better spared by recurrent courses of infection.

Title: Modelling spatial variations of coronavirus disease (COVID-19) in Africa Content: Clinical and epidemiological evidence has been advanced for human-to-human transmission of the novel coronavirus rampaging the world since late 2019. Outliers in the human-to-human transmission are yet to be explored. In this study, we examined the spatial density and leaned statistical credence to the global debate. We constructed spatial variations of clusters that examined the nexus between COVID-19 attributable deaths and confirmed cases. We rely on publicly available data on confirmed cases and death across Africa to unravel the unobserved factors, that could be responsible for the spread of COVID-19. We relied on the dynamic system generalised method of moment estimation procedure and found a ~0.045 Covid19 deaths as a result of confirmed cases in Africa. We accounted for cross-sectional dependence and found a basis for the strict orthogonal relationship. Policy measures were discussed.

Title: Super-Spreader Businesses and Risk of COVID-19 Transmission Content: Purpose: The United States has the highest number of confirmed COVID-19 cases in the world to date, with over 94,000 COVID-19-related deaths. The true risk of a COVID-19 resurgence as states prepare to reopen businesses is unknown. This paper aims to classify businesses by their risk of transmission and quantify the relationship between the density of super-spreader businesses and COVID-19 cases. Methods: We constructed a COVID-19 Business Transmission Risk Index based upon the frequency and duration of visits and square footage of businesses pre-pandemic in 2019 in 8 states (Massachusetts, Rhode Island, Connecticut, New Hampshire, Vermont, Maine, New York, and California). We used this index to classify businesses as super-spreaders. Then, we analyzed the association between the density of super-spreader businesses in a county and the rate of COVID-19 cases. We performed significance testing using a negative binomial regression. The main outcome of interest is the cumulative number of COVID-19 cases each week. Results: We found a positive association between the density of super-spreader businesses and COVID-19 cases. A 1 percentage point increase in the density of super-spreader businesses is associated with 5% higher COVID-19 cases, all else equal. Conclusion: Higher densities of super-spreader businesses are associated with higher rates of COVID-19 cases. This may have important implications for how states reopen super-spreader businesses.

Title: Identification of super-transmitters of SARS-CoV-2 Content: A newly emerged coronavirus, SARS-CoV-2, caused severe outbreaks of pneumonia in China in December 2019 and has since spread to various countries around the world. To probe the origin and transmission dynamics of this virus, we performed phylodynamic analysis of 247 high quality genomic sequences of viruses available in the GISAID platform as of March 05, 2020. A substantial number of earliest sequences reported in Wuhan in December 2019, including those of viruses recovered from the Huanan Seafood Market (HNSM), the site of the initial outbreak, were genetically diverse, suggesting that viruses of multiple sources were involved in the original outbreak. The viruses were subsequently disseminated to different parts of China and other countries, with diverse mutational profiles being recorded in strains recovered subsequently. Interestingly, four genetic clusters defined as Super-transmitters (STs) were found to become dominant and were responsible for the major outbreaks in various countries. Among the four clusters, ST1 is widely disseminated in Asia and the US and mainly responsible for outbreaks in the states of Washington and California in the US as well as those in South Korea at the end of February and early March, whereas ST4 contributed to the pandemic in Europe. Each ST cluster carried a signature mutation profile which allowed us to trace the origin and transmission patterns of specific viruses in different parts of the world. Using the signature mutations as markers of STs, we further analysed 1539 genome sequences reported after February 29, 2020. We found that around 90% of these genomes belonged to STs with ST4 being the dominant one and their contribution to pandemic in different continents were also depicted. The identification of these super-transmitters provides insight into the control of further transmission of SARS-CoV-2.

Title: Pandemic dynamics of COVID-19 using epidemic stage, instantaneous reproductive number and pathogen genome identity (GENI) score: modeling molecular epidemiology Content: Background: Global spread of COVID-19 created an unprecedented infectious disease crisis that progressed to a pandemic with >180,000 cases in >100 countries. Reproductive number (R) is an outbreak metric estimating the transmission of a pathogen. Initial R values were published based on the early outbreak in China with limited number of cases with whole genome sequencing. Initial comparisons failed to show a direct relationship viral genomic diversity and epidemic severity was not established for SARS-Cov-2. Methods: Each country's COVID-19 outbreak status was classified according to epicurve stage (index, takeoff, exponential, decline). Instantaneous R estimates (Wallinga and Teunis method) with a short and standard serial interval examined asymptomatic spread. Whole genome sequences were used to quantify the pathogen genome identity score that were used to estimate transmission time and epicurve stage. Transmission time was estimated based on evolutionary rate of 2 mutations/month. Findings: The country-specific R revealed variable infection dynamics between and within outbreak stages. Outside China, R estimates revealed propagating epidemics poised to move into the takeoff and exponential stages. Population density and local temperatures had variable relationship to the outbreaks. GENI scores differentiated countries in index stage with cryptic transmission. Integration of incidence data with genome variation directly increases in cases with increased genome variation. Interpretation: R was dynamic for each country and during the outbreak stage. Integrating the outbreak dynamic, dynamic R, and genome variation found a direct association between cases and genome variation. Synergistically, GENI provides an evidence-based transmission metric that can be determined by sequencing the virus from each case. We calculated an instantaneous country-specific R at different stages of outbreaks and formulated a novel metric for infection dynamics using viral genome sequences to capture gaps in untraceable transmission. Integrating epidemiology with genome sequencing allows evidence-based dynamic disease outbreak tracking with predictive evidence.

Title: Predictive Analysis of COVID-19 Time-series Data from Johns Hopkins University Content: We provide a predictive analysis of the spread of COVID-19, also known as SARS-CoV-2, using the dataset made publicly available online by the Johns Hopkins University. Our main objective is to provide predictions of the number of infected people for different countries in the next 14 days. The predictive analysis is done using time-series data transformed on a logarithmic scale. We use two well-known methods for prediction: polynomial regression and neural network. As the number of training data for each country is limited, we use a single-layer neural network called the extreme learning machine (ELM) to avoid over-fitting. Due to the non-stationary nature of the time-series, a sliding window approach is used to provide a more accurate prediction.

Title: Serial interval in determining the estimation of reproduction number of the novel coronavirus disease (COVID-19) during the early outbreak ;Journal of Travel Medicine ;Oxford Academic Content: Coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), emerged in Wuhan, China in the end of 2019, and soon spread oversea A comprehensive and timely review summarized the scientific research in estimating the basic reproduction number (R0) released from 1 January to 7 February 2020 [1] During the early outbreak, when the key epidemiological features of COVID-19 were uncovered, the R0 estimation largely relied on the growth rate of the epidemic curve and the estimation of the serial interval (SI) Here, we demonstrated that an overlarge SI would lead to overestimation of R0 We adopted the growing process proposed in [2] deterministically with a population of 11 million in Wuhan, 1 case initially onset on 5 December 2019 and a fixed step at 1 day We consider two values of the mean serial interval (SI) that are  SI at 4 6 days estimated based on 28 records of transmission chains [3], which was largely consistent with the SI estimate at 4 4 days based on 71 records [4];and  SI at 8 days, which was closer to the SI of the severe acute respiratory syndrome (SARS, 8 4 days), SI of the Middle East respiratory syndrome (MERS, 7 6 days) As for demonstration that a larger SI could lead to overestimation in R0, we conducted the simulation with two schemes that are  Scheme (I): R0 = 2, and SI = 4 6 days;and  Scheme (II): R0 = 2, 3, 4 and 3 3 as summarized in [1], and SI = 8 days We also compared the simulation results with the previous estimates of the cumulative number of COVID-19 infection in Wuhan In Fig 1, the simulation results of the scheme (I) had almost the same growing trends as those of scheme (II) with R0 = 3 3 Although a higher R0 could force the epidemic curve increasing rapidly, a shorter SI could increase iteration of transmission generation, i e , transmission may occur shortly post infection According to the simple approximated formula that R0 = exp(γ∙SI), where γ was the exponential growth rate calculated from the incidence data directly, a longer SI would lead to a higher R0 estimate theoretically With a shorter SI at 4 6 days, which was supported by richer datasets in [3, 4], the R0 of COVID-19 could be lower than previous estimates based on longer SI By using the growth rate (γ) at 0 15 per day, the R0 was found at 2 0 with SI at 4 6 days, whereas 3 3 with SI at 8 days Although the effects of public health control were ignored in this analysis, our model could be Downloaded from https://academic oup com/jtm/advance-article-abstract/doi/10 1093/jtm/taaa033/5803291 by guest on 13 March 2020 4 extended by introducing an effective reproduction number accounting for the effectiveness of the control measures, and we remarked this modification would not affect the main conclusion Furthermore, as pointed out in [3], provided that the SI of COVID-19 might be shorter than its incubation period, pre-symptomatic transmission may occur shortly after being infected [5] This implies that a fraction of transmissions cannot be prevented solely through isolating the symptomatic cases, since the time when contact tracing is conducted, they may have already been infectious and generated secondary cases Therefore, the effectively quarantine of suspected (and probable) cases, as well as close contacts, and timely contact tracing were crucial in successful outbreak mitigation

Title: Rich at risk: socio-economic drivers of COVID-19 pandemic spread Content: COVID-19, the novel coronavirus affecting the most part of worldwide countries since early 2020, is fast increasing its prevalence around the world, representing a significant emergency for the population and the health systems at large. While proper treatments are being developed, in-depth studies concerning its way of diffusion are necessary, in order to understand how the virus is actually spreading, through the investigation on some socio-economic indicators for the various countries in the world, retrieved through open-access data publicly available. The correlation analysis displayed significant relationships between COVID-19 incidence with several of such indicators, including the Gross Domestic Product per capita and the number of flights per capita, whereas mortality is mainly related to the main age of the population. All such data displayed an interesting mean to understand the way the virus has diffused worldwide, possibly representing the basis for future preventive measures to effectively challenge a new COVID-19 pandemic wave, but also other, similar pandemics.

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: 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: Differential diagnosis of illness in patients under investigation for the novel coronavirus (SARS-CoV-2), Italy, February 2020 Content: A novel coronavirus (SARS-CoV-2) has been identified as the causative pathogen of an ongoing outbreak of respiratory disease, now named COVID-19. Most cases and sustained transmission occurred in China, but travel-associated cases have been reported in other countries, including Europe and Italy. Since the symptoms are similar to other respiratory infections, differential diagnosis in travellers arriving from countries with wide-spread COVID-19 must include other more common infections such as influenza and other respiratory tract diseases.

Title: Modelling spatial variations of coronavirus disease (COVID-19) in Africa Content: Abstract Clinical and epidemiological evidence has been advanced for human-to-human transmission of the novel coronavirus rampaging the world since late 2019. Outliers in the human-to-human transmission are yet to be explored. In this study, we examined the spatial density and leaned statistical credence to the global debate. We constructed spatial variations of clusters that examined the nexus between COVID-19 attributable deaths and confirmed cases. We rely on publicly available data on confirmed cases and death across Africa to unravel the unobserved factors, that could be responsible for the spread of COVID-19. We relied on the dynamic system generalised method of moment estimation procedure and found a ~0.045 Covid19 deaths as a result of confirmed cases in Africa. We accounted for cross-sectional dependence and found a basis for the strict orthogonal relationship. Policy measures were discussed.

Title: COVID-19 and the 5G Conspiracy Theory: Social Network Analysis of Twitter Data Content: BACKGROUND: Since the beginning of December 2019, the coronavirus disease (COVID-19) has spread rapidly around the world, which has led to increased discussions across online platforms. These conversations have also included various conspiracies shared by social media users. Amongst them, a popular theory has linked 5G to the spread of COVID-19, leading to misinformation and the burning of 5G towers in the United Kingdom. The understanding of the drivers of fake news and quick policies oriented to isolate and rebate misinformation are keys to combating it. OBJECTIVE: The aim of this study is to develop an understanding of the drivers of the 5G COVID-19 conspiracy theory and strategies to deal with such misinformation. METHODS: This paper performs a social network analysis and content analysis of Twitter data from a 7-day period (Friday, March 27, 2020, to Saturday, April 4, 2020) in which the #5GCoronavirus hashtag was trending on Twitter in the United Kingdom. Influential users were analyzed through social network graph clusters. The size of the nodes were ranked by their betweenness centrality score, and the graph's vertices were grouped by cluster using the Clauset-Newman-Moore algorithm. The topics and web sources used were also examined. RESULTS: Social network analysis identified that the two largest network structures consisted of an isolates group and a broadcast group. The analysis also revealed that there was a lack of an authority figure who was actively combating such misinformation. Content analysis revealed that, of 233 sample tweets, 34.8% (n=81) contained views that 5G and COVID-19 were linked, 32.2% (n=75) denounced the conspiracy theory, and 33.0% (n=77) were general tweets not expressing any personal views or opinions. Thus, 65.2% (n=152) of tweets derived from nonconspiracy theory supporters, which suggests that, although the topic attracted high volume, only a handful of users genuinely believed the conspiracy. This paper also shows that fake news websites were the most popular web source shared by users; although, YouTube videos were also shared. The study also identified an account whose sole aim was to spread the conspiracy theory on Twitter. CONCLUSIONS: The combination of quick and targeted interventions oriented to delegitimize the sources of fake information is key to reducing their impact. Those users voicing their views against the conspiracy theory, link baiting, or sharing humorous tweets inadvertently raised the profile of the topic, suggesting that policymakers should insist in the efforts of isolating opinions that are based on fake news. Many social media platforms provide users with the ability to report inappropriate content, which should be used. This study is the first to analyze the 5G conspiracy theory in the context of COVID-19 on Twitter offering practical guidance to health authorities in how, in the context of a pandemic, rumors may be combated in the future.

Title: Coronavirus Disease 2019 and Transplantation: a view from the inside. Content: Since December 2019, world healthcare community faced with Coronavirus Disease 2019 (COVID-19) outbreak caused by SARS-CoV-2. Due to the high viral contagiousness and the possible transmission during the pre-symptomatic phase, COVID-19 progressively spread to several countries. Currently, Italy is the third Country for number of confirmed cases after mainland China and South Chorea, and the first western nation with a well-established deceased transplant program to tackle a COVID-19 outbreak1 .

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: Proteome Organization of COVID-19: Illustrating Targets for Vaccine Development Content: 'COVID-19' the recent virulent viral infection had influenced the lives of millions globally leading to both loss of life, economic and financial crisis Coronavirus belongs to family coronaviridae with four genus viz alpha/beta and gamma-coronavirus, infecting both aves and mammals The SARS-Cov-2 emerged in Wuhan, China in Dec, 2019 and since then had spread to 213 countries Its origin is debatable with both natural origin and conspiracy theory providing no conclusive evidences Coronavirus have '+'ive RNA and encodes for 29 proteins, which carries out its life cycle including infection and disease progression The study of its proteome organization could illustrate the proteins which act as the key molecular players in the infection cycle of the virus These proteins can also act as important drug targets in combating COVID-19 infection Majority of the drugs have been formulated in order to act as agonist to spike proteins inhibiting infection by binding to ACE2 receptors Proteome analysis has also revealed the critical mutated proteins that are responsible for COVID-19 pathogenesis and virulence mRNA based vaccines (mRNA-1273, BNT162) also targets these spike proteins Although DNA vaccine has also been attempted using RDT, but the high rate of mutation associated with COVID-19 have made such vaccines ineffective even before use Thus evolutionarily conserved proteins have been the best candidature for vaccine development Similarly phylogenetic analysis of its proteins could help us to understand the evolutionary pattern of COVID-19 It could be used to develop a predictable model for such pathogenic infections, preparing ourselves to take preventive action against its reoccurrence

Title: Study of Non-Pharmacological Interventions on COVID-19 Spread Content: COVID-19 disease has emerged as one of the life threatening threat to the society. It is caused by a novel beta coronavirus. It began as unidentified pneumonia of unknown aetiology in Wuhan City, Hubei province in China emerged in December 2019. No vaccine has been produced till now. Mathematical models are used to study impact of different measures used to decrease pandemic. Mathematical models have been designed to estimate the numbers of spreaders in different scenarios in the present manuscript. In the present manuscript, three different mathematical models have been proposed with different scenarios such as screening, quarantine and NPIs for estimating number of virus spreaders. the analysis shows that the numbers of COVID-19 patients will be more without screening the peoples coming from other countries. Since, every people suffering with COVID-19 disease are spreaders. The screening and quarantine with NPIs have been implemented to study their impact on the spreaders. It has been found that NPI measures are able to reduce number of spreaders. The NPI measures reduces the growth of the spread function and providing decision makers more time to prepare with in dealing of the disease.

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: Analytical Review of COVID-19 Outbreak in India During the Global Pandemic Content: COVID-19 is one of the very contagious diseases from the family Coronaviridae and spreading at a faster rate in the community In December 2019, the first case of COVID-19 was reported in Wuhan, China An epidemic outbreak of COVID-19 was seen in India from March 2020 Epidemiological data of COVID-19 cases of the world and India have been analyzed in our study We have utilized publicly available two databases from data repository by Johns Hopkins CSSE and covid19india org COVID-19 cases and case fatality rate (CFR) of the world have been summarized and compared with India from January 22, 2020 to April 15, 2020 Indian cases were analyzed among states of India and also compared with age and gender by performing statistical approaches such as central tendency, standard deviation and interquartile range By April 15, 2020, Indian has reported 12,322 confirmed cases, 1,498 recovered cases and 405 death cases of COVID-19 In spite of India being a diverse country with the second-highest population, the deadly side of COVID-19 was comparatively far less as compared to the other countries India has taken preemptive measures at an early stage to prevent transmission of COVID-19 outbreak and it is reviewed from our study by comparing India with other countries Our study also summarizes that age also plays a vital role in the intervention of COVID-19 cases

Title: COVID-19 and the 5G Conspiracy Theory: Social Network Analysis of Twitter Data Content: BACKGROUND: Since the beginning of December 2019, the coronavirus disease (COVID-19) has spread rapidly around the world, which has led to increased discussions across online platforms. These conversations have also included various conspiracies shared by social media users. Amongst them, a popular theory has linked 5G to the spread of COVID-19, leading to misinformation and the burning of 5G towers in the United Kingdom. The understanding of the drivers of fake news and quick policies oriented to isolate and rebate misinformation are keys to combating it. OBJECTIVE: The aim of this study is to develop an understanding of the drivers of the 5G COVID-19 conspiracy theory and strategies to deal with such misinformation. METHODS: This paper performs a social network analysis and content analysis of Twitter data from a 7-day period (Friday, March 27, 2020, to Saturday, April 4, 2020) in which the #5GCoronavirus hashtag was trending on Twitter in the United Kingdom. Influential users were analyzed through social network graph clusters. The size of the nodes were ranked by their betweenness centrality score, and the graph’s vertices were grouped by cluster using the Clauset-Newman-Moore algorithm. The topics and web sources used were also examined. RESULTS: Social network analysis identified that the two largest network structures consisted of an isolates group and a broadcast group. The analysis also revealed that there was a lack of an authority figure who was actively combating such misinformation. Content analysis revealed that, of 233 sample tweets, 34.8% (n=81) contained views that 5G and COVID-19 were linked, 32.2% (n=75) denounced the conspiracy theory, and 33.0% (n=77) were general tweets not expressing any personal views or opinions. Thus, 65.2% (n=152) of tweets derived from nonconspiracy theory supporters, which suggests that, although the topic attracted high volume, only a handful of users genuinely believed the conspiracy. This paper also shows that fake news websites were the most popular web source shared by users; although, YouTube videos were also shared. The study also identified an account whose sole aim was to spread the conspiracy theory on Twitter. CONCLUSIONS: The combination of quick and targeted interventions oriented to delegitimize the sources of fake information is key to reducing their impact. Those users voicing their views against the conspiracy theory, link baiting, or sharing humorous tweets inadvertently raised the profile of the topic, suggesting that policymakers should insist in the efforts of isolating opinions that are based on fake news. Many social media platforms provide users with the ability to report inappropriate content, which should be used. This study is the first to analyze the 5G conspiracy theory in the context of COVID-19 on Twitter offering practical guidance to health authorities in how, in the context of a pandemic, rumors may be combated in the future.

Title: A pilot study to investigate the fecal dissemination of SARS-CoV-2 virus genome in COVID-19 patients in Odisha, India Content: In infectious diseases, the routes of transmission play major roles in determining the rate and extent of disease spread. Though fomites and aerosol droplets are major sources of SARS-CoV-2 human to human transmission, studies have also reported possible involvement of other routes of transmission like fecal-oral. Multiple studies around the world have reported shedding of the SARS-CoV-2 viral genome in certain COVID-19 patient fecal samples. Hence, the major objective of this study was to get the experimental evidence whether in Indian COVID-19 patients fecal dissemination of the SARS-CoV-2 genome occurs or not. Information obtained from twelve number of patients from a COVID-19 hospital of Odisha has demonstrated that both symptomatic and asymptomatic Indian patients could be positive for the SARS-CoV-2 genome in their fecal component. The findings have also established a protocol to collect and extract viral RNA for SARS-CoV-2 detection in fecal samples. Together, the study supports the hypothesis of possible fecal-oral transmission of SARS-CoV-2 virus and provides a rationale to extend this study in a larger cohort of patient samples and correlate the significance of the SARS-CoV-2 virus genome detection in fecal samples with disease severity and transmission.

Title: New measures for COVID-19 response: a lesson from the Wenzhou experience Content: As the outbreak of COVID-19 has spread globally, determining how to prevent the spread is of paramount importance. We reported the effectiveness of different responses of four affected cities in preventing the COVID-19 spread. We expect Wenzhou anti-COVID-19 measures may provide experience for cities around the world that are experiencing this epidemic.

Title: First, second and potential third generation spreads of the COVID-19 epidemic in mainland China: an early exploratory study incorporating location-based service data of mobile devices Content: OBJECTIVES: The outbreak of atypical pneumonia caused by the novel coronavirus (COVID-19) has currently become a global concern. The generations of the epidemic spread are not well known, yet these are critical parameters to facilitate an understanding of the epidemic. A seafood wholesale market and Wuhan city, China, were recognized as the primary and secondary epidemic sources. Human movements nationwide from the two epidemic sources revealed the characteristics of the first-generation and second-generation spreads of the COVID-19 epidemic, as well as the potential third-generation spread. METHODS: We used spatiotemporal data of COVID-19 cases in mainland China and two categories of location-based service (LBS) data of mobile devices from the primary and secondary epidemic sources to calculate Pearson correlation coefficient,r, and spatial stratified heterogeneity, q, statistics. RESULTS: Two categories of device trajectories had generally significant correlations and determinant powers of the epidemic spread. Bothr and q statistics decreased with distance from the epidemic sources and their associations changed with time. At the beginning of the epidemic, the mixed first-generation and second-generation spreads appeared in most cities with confirmed cases. They strongly interacted to enhance the epidemic in Hubei province and the trend was also significant in the provinces adjacent to Hubei. The third-generation spread started in Wuhan from January 17-20, 2020, and in Hubei from January 23-24. No obvious third-generation spread was detected outside Hubei. CONCLUSIONS: The findings provide important foundations to quantify the effect of human movement on epidemic spread and inform ongoing control strategies. The spatiotemporal association between the epidemic spread and human movements from the primary and secondary epidemic sources indicates a transfer from second to third generations of the infection. Urgent control measures include preventing the potential third-generation spread in mainland China, eliminating it in Hubei, and reducing the interaction influence of first-generation and second-generation spreads.

Title: Coronavirus research before 2020 is more relevant than ever, especially when interpreted for COVID-19 Content: The speed with which biomedical researchers were able to identify and characterise COVID-19 was clearly due to prior research with other coronaviruses. Early epidemiological comparisons with two previous coronaviruses, Severe Acute Respiratory Syndrome (SARS) and Middle East Respiratory Syndrome (MERS), also made it easier to predict COVID-19's likely spread and lethality. This article assesses whether academic interest in prior coronavirus research has translated into interest in the primary source material, using Mendeley reader counts for early academic impact evidence. The results confirm that SARS and MERS research 2008-2017 experienced anomalously high increases in Mendeley readers in April-May 2020. Nevertheless, studies learning COVID-19 lessons from SARS and MERS or using them as a benchmark for COVID-19 have generated much more academic interest than primary studies of SARS or MERS. Thus, research that interprets prior relevant research for new diseases when they are discovered seems to be particularly important to help researchers to understand its implications in the new context.

Title: Modeling COVID-19 on a network: super-spreaders, testing and containment Content: We use a model of covid-19 spread, an SEIR agent-based model on a graph, which takes into account several important real-life attributes of covid-19: Super-spreaders, realistic epidemiological parameters of the disease, testing and quarantine policies. We provide simulation results and mathematical arguments to argue that certain results of our simulations hold in more general settings. We find that mass-testing is much less effective than testing the symptomatic and contact tracing, and some blend of these with social distancing is required to get suppression. We also find that the fat tail of the degree distribution matters a lot for epidemic growth, and many standard models do not account for this. Additionally, the average reproduction number for individuals is not an upper bound for the effective reproduction number, R. Even with an expectation of less than one new case per person, this model shows that exponential spread is possible. The parameter which closely predicts growth rate is the ratio between 2nd to 1st moments of the degree distribution.

Title: Relationship between perception and anxiety about COVID-19 infection and risk behaviors for spreading infection: A national survey in Japan Content: BACKGROUND: The novel corona virus infection (COVID-19) quickly became a pandemic state. Identifying characteristics of “possible super spreaders”, suggested as a dominant cause of rapid spreading transmission, will help us to design proper prevention strategies. METHODS: We conducted a nation-wide online survey to investigate the relationship of perception and anxiety levels about COVID-19 to the possible risk behaviors for spread of the virus in Japan. We recruited a total of 4,000 citizens, who responded to the questionnaire including several questions regarding the level of fear and anxiety about COVID-19, infection preventive behaviors and access to media with trust level about the virus as well as some demographic and socioeconomic data during March 27th and 28th, 2020. FINDINGS: Thirteen-point-three percent of the participants rated “1” on a nine-point Likert with respect to the knowledge about COVID-19. Ten-point-one percent and 11.7% presented no anxiety of being infected and transmission to others. Ten-point-eight percent showed no worry about symptomatic aggravation. Eight-point-one percent had no serious concern about expanding infection. The distribution of these items was highly correlated with each other. Participants with the low level of knowledge about COVID-19 were likely to less frequently access any information sources and neither trust them. They were less anxious about their health status, and less likely to put precautionary behaviors such as washing hands and avoiding crowded spaces, suggested by statistical analyses. INTERPRETATION: The present study suggests that it is greatly important to enlighten those have no concerns about this crisis of COVID-19 and modify their risk behavior via various ways, in order to prevent and control this viral pandemic. FUNDING: This study was funded by the management grand provided to Chiba University Graduate School of Medicine and the Japan Society for the Promotion of Science KAKENHI grants.

Title: Spatial Visualization of Cluster-Specific COVID-19 Transmission Network in South Korea During the Early Epidemic Phase Content: Background Coronavirus disease 2019 (COVID-19) has been rapidly spreading throughout China and other countries including South Korea. As of March 12, 2020, a total number of 7,869 cases and 66 deaths had been documented in South Korea. Although the first confirmed case in South Korea was identified on January 20, 2020, the number of confirmed cases showed a rapid growth on February 19, 2020 with a total number of 1,261 cases with 12 deaths based on the Korea Centers for Disease Control and Prevention (KCDC). Method Using the data of confirmed cases of COVID-19 in South Korea that are publicly available from the KCDC, this paper aims to create spatial visualizations of COVID-19 transmission between January 20, 2020 and February 19, 2020. Results Using spatial visualization, this paper identified two early transmission clusters in South Korea (Daegu cluster and capital area cluster). Using a degree-weighted centrality measure, this paper proposes potential super-spreaders of the virus in the visualized clusters. Conclusion Compared to various epidemiological measures such as the basic reproduction number, spatial visualizations of the cluster-specific transmission networks and the proposed centrality measure may be more useful to characterize super-spreaders and the spread of the virus especially in the early epidemic phase.

Title: Detection of spreader nodes and ranking of interacting edges in Human-SARS-CoV protein interaction network Content: The entire world has recently witnessed the commencement of coronavirus disease 19 (COVID-19) pandemic. It is caused by a novel coronavirus (n-CoV) generally distinguished as Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). It has exploited human vulnerabilities to coronavirus outbreak. SARS-CoV-2 promotes fatal chronic respiratory disease followed by multiple organ failure which ultimately puts an end to human life. No proven vaccine for n-CoV is available till date in spite of significant research efforts worldwide. International Committee on Taxonomy of Viruses (ICTV) has reached to a consensus that the virus SARS-CoV-2 is highly genetically similar to Severe Acute Respiratory Syndrome Coronavirus (SARS-CoV) outbreak of 2003. It has been reported that SARS-CoV has ∼89% genetic similarities with n-CoV. With this hypothesis, the current work focuses on the identification of spreader nodes in SARS-CoV protein interaction network. Various network characteristics like edge ratio, neighborhood density and node weight have been explored for defining a new feature spreadability index by virtue of which spreader nodes and edges are identified. The selected top spreader nodes having high spreadability index have been also validated by Susceptible-Infected-Susceptible (SIS) disease model. Initially, the proposed method is applied on a synthetic protein interaction network followed by SARS-CoV-human protein interaction network. Hence, key spreader nodes and edges (ranked edges) are unmasked in SARS-CoV proteins and its connected level 1 and level 2 human proteins. The new network attribute spreadability index along with generated SIS values of selected top spreader nodes when compared with the other network centrality based methodologies like Degree centrality (DC), Closeness centrality (CC), Local average centrality (LAC) and Betweeness centrality (BC) is found to perform relatively better than the existing-state-of-art.

Title: Pregnant women's knowledge and practice of preventive measures against COVID-19 in a low-resource African setting. Content: Since the emergence of coronavirus disease 2019 (COVID-19) in Wuhan, China in December 2019, the virus that causes it (SARS-Cov-2) has spread to over 110 countries, including Nigeria [1-3]. Although the impact of COVID-19 on pregnant women is not yet clear, there are concerns over its potential effect on maternal and perinatal outcomes due to unique immunological suppression during pregnancy [4,5].

Title: Virus strain of a mild COVID-19 patient in Hangzhou representing a new trend in SARS-CoV-2 evolution related to Furin cleavage site Content: We found, in our 788 confirmed COVID-19 patients, the decreased rate of severe/critical type, increased liver/kidney damage and prolonged period of nuclear acid positivity during virus dissemination, when compared with Wuhan. To investigate the underlining mechanism, we isolated one strain of SARS- CoV-2 (ZJ01) in mild COVID-19 patient and found the existence of 35 specific gene mutation by gene alignment. Further phylogenetic analysis and RSCU heat map results suggested that ZJ01 may be a potential evolutionary branch of SARS-CoV-2. We classified 54 strains of viruses worldwide (C/T type) based on the base (C or T) at positions 8824 and 28247. ZJ01 were both T at these two sites, becoming the only TT type currently identified in the world. The prediction of Furin cleavage site (FCS) and the sequence alignment of virus family indicated that FCS may be an important site of coronavirus evolution. ZJ01 had mutations near FCS (F1-2), which caused changes in the structure and the electrostatic distribution of the S protein surface, further affecting the binding capacity of Furin. Single cell sequencing and ACE2-Furin co-expression results confirmed that Furin level was higher in the whole body, especially in glands, liver, kidney and colon while FCS may help SARS-CoV-2 infect these organs. The evolutionary pattern of SARS-CoV-2 towards FCS formation may result in its clinical symptom becoming closer to HKU-1 and OC43 (the source of FCS sequence-PRRA) caused influenza, further showing potential in differentiating into mild COVID-19 subtypes.

Title: How Right-Leaning Media Coverage of COVID-19 Facilitated the Spread of Misinformation in the Early Stages of the Pandemic in the U.S. Content: We have yet to know the ultimate global impact of the novel coronavirus pandemic. However, we do know that delays, denials and misinformation about COVID-19 have exacerbated its spread and slowed pandemic response, particularly in the U.S. (e.g., Abutaleb et al., 2020).

Title: [Investigation of a cluster epidemic of COVID-19 in Ningbo] Content: Objective: To investigate a cluster epidemic of COVID-19 after a mass gathering activity in Ningbo of Zhejiang province and analyze the transmission chain and status of infection cases of different generations. Methods: The tracking of all the close contacts of the first COVID-19 case and epidemiological investigation were conducted on January 29, 2020 after a cluster epidemic of COVID-19 related with a Buddhism rally on January 19 (the 1.19 rally) in Ningbo occurred. The swabs of nose/throat of the cases and close contacts were collected and tested for nucleic acids by real-time fluorescence quantitative RT-PCR. Results: From January 26 to February 20, 2020, a total of 67 COVID-19 cases and 15 asymptomatic infection cases related with the 1.19 rally were reported in Ningbo. The initial case was the infection source who infected 29 second generation cases and 4 asymptomatic infection cases, in whom 23 second generation cases and 3 asymptomatic infection cases once took bus with the initial case, the attack rate was 33.82% (23/68) and the infection rate was 38.24% (26/68). The risks of suffering from COVID-19 and being infected were 28.91 times and 26.01 times higher in rally participants taking bus with initial case compared with those taking no bus with initial case. In this epidemic, 37 third+ generation cases and 11 related asymptomatic infection cases occurred, the attack rate was 2.88% (37/1 283) and the infection rate was 4.76% (48/1 008). The main transmission routes included vehicle sharing and family transmission. Conclusion: It was a cluster epidemic of COVID-19 caused by a super spreader in a massive rally. The epidemic has been under effective control.

Title: [Investigation of a cluster epidemic of COVID-19 in Ningbo]. Content: Objective: To investigate a cluster epidemic of COVID-19 after a mass gathering activity in Ningbo of Zhejiang province and analyze the transmission chain and status of infection cases of different generations. Methods: The tracking of all the close contacts of the first COVID-19 case and epidemiological investigation were conducted on January 29, 2020 after a cluster epidemic of COVID-19 related with a Buddhism rally on January 19 (the 1.19 rally) in Ningbo occurred. The swabs of nose/throat of the cases and close contacts were collected and tested for nucleic acids by real-time fluorescence quantitative RT-PCR. Results: From January 26 to February 20, 2020, a total of 67 COVID-19 cases and 15 asymptomatic infection cases related with the 1.19 rally were reported in Ningbo. The initial case was the infection source who infected 29 second generation cases and 4 asymptomatic infection cases, in whom 23 second generation cases and 3 asymptomatic infection cases once took bus with the initial case, the attack rate was 33.82% (23/68) and the infection rate was 38.24% (26/68). The risks of suffering from COVID-19 and being infected were 28.91 times and 26.01 times higher in rally participants taking bus with initial case compared with those taking no bus with initial case. In this epidemic, 37 third+ generation cases and 11 related asymptomatic infection cases occurred, the attack rate was 2.88% (37/1 283) and the infection rate was 4.76% (48/1 008). The main transmission routes included vehicle sharing and family transmission. Conclusion: It was a cluster epidemic of COVID-19 caused by a super spreader in a massive rally. The epidemic has been under effective control.

Title: The recent challenges of highly contagious COVID-19; causing respiratory infections: symptoms, diagnosis, transmission, possible vaccines, animal models and immunotherapy Content: COVID-19 is highly contagious pathogenic viral infection initiated from Wuhan seafood wholesale market of China on December 2019 and spread rapidly around the whole world due to onward transmission. This recent outbreak of novel coronavirus (CoV) was believed to be originated from bats and causing respiratory infections such as common cold, dry cough, fever, headache, dyspnea, pneumonia and finally Severe Acute Respiratory Syndrome (SARS) in humans. For this widespread zoonotic virus, human-to-human transmission has resulted in nearly 83 lakh cases in 213 countries and territories with 4,50,686 deaths as on 19th June 2020. This review presents a report on the origin, transmission, symptoms, diagnosis, possible vaccines, animal models and immunotherapy for this novel virus and will provide ample references for the researchers towards the ongoing development of therapeutic agents and vaccines and also preventing the spread of this disease.

Title: The recent challenges of highly contagious COVID-19; causing respiratory infections: symptoms, diagnosis, transmission, possible vaccines, animal models and immunotherapy. Content: COVID-19 is highly contagious pathogenic viral infection initiated from Wuhan seafood wholesale market of China on December 2019 and spread rapidly around the whole world due to onward transmission. This recent outbreak of novel coronavirus (CoV) was believed to be originated from bats and causing respiratory infections such as common cold, dry cough, fever, headache, dyspnea, pneumonia and finally Severe Acute Respiratory Syndrome (SARS) in humans. For this widespread zoonotic virus, human-to-human transmission has resulted in nearly 83 lakh cases in 213 countries and territories with 4,50,686 deaths as on 19th June 2020. This review presents a report on the origin, transmission, symptoms, diagnosis, possible vaccines, animal models and immunotherapy for this novel virus and will provide ample references for the researchers towards the ongoing development of therapeutic agents and vaccines and also preventing the spread of this disease.

Title: Genomic epidemiology put to the test against COVID-19 Content: In early April, a paper published in the journal Proceedings of the National Academy of Sciences of the United States of America (PNAS) raised the eyebrows of a number of genomic epidemiologists It suggested that there were three distinct variants of the novel coronavirus, SARS-CoV-2, spreading in different regions of the world—one predominantly in Australia and North America, one in China, and one in Europe It also suggested that the variant circulating in North America and Australia was older than the one that appeared in Wuhan, China, at the end of December (Proc Natl Acad Sci U S A 2020, DOI: 10 1073/pnas 2004999117) If this were true, the outbreak of COVID-19, the disease caused by the virus, would have started outside Wuhan, which contradicts scientific consensus Some genomic epidemiologists, who track the genomes of pathogens to understand how diseases spread, thought that although the data the PNAS paper used were sound, the paper’s analytical View: PDF ;Full Text HTML

Title: Research on COVID-19 virus spreading statistics based on the examples of the cases from different counties Content: The novel coronavirus COVID-19 originally identified in December 2019, based on the data issued by March 30, 2020 daily report, the epidemic of SARS-CoV-2 so far has caused 693224 cases and resulted in 33106 deaths in more than 200 countries. Referring to the data reported, World Health Organization declared the outbreak a pandemic. We considered the chain-binomial type of the model which involves short stages of high infectivity and approximately constant incubation periods. This research paper is to study and analyze the COVID-19 Virus spreading statistics on the examples of the cases from the different counties. High correlation coefficients (91.64%) and determinants (83.98%) between the total volumes of virus spread and recovery are considered to be high and indicate the correctness of the Bailey model. Thus, as of March 30, with the results of statistical and mathematical data processing, it is difficult to predict the future spread-reduction variables of the pandemic.

Title: Liver transplantation in an ICU dominated by COVID-19 Content: The Letter from D'Antiga L about concerns of transplanting patients in the context of COVID19 pandemic is very interesting [1]. COVID-19 designates the infection caused by the SARS-Cov2 virus. This illness originated in December, 2019, in Wuhan, China. Since then, it has been identified in more than 150 countries. The first case of COVID-19 in Portugal was notified in March 02, 2020.

Title: Liver transplantation in an ICU dominated by COVID-19. Content: The Letter from D'Antiga L about concerns of transplanting patients in the context of COVID19 pandemic is very interesting [1]. COVID-19 designates the infection caused by the SARS-Cov2 virus. This illness originated in December, 2019, in Wuhan, China. Since then, it has been identified in more than 150 countries. The first case of COVID-19 in Portugal was notified in March 02, 2020.

Title: Coinfection with COVID‐19 and Coronavirus HKU1 – the critical need for repeat testing if clinically indicated Content: COVID‐19 is the latest global pandemic caused by severe acute respiratory syndrome coronavirus ‐2 (SARS‐CoV‐2). There have been seven pathogenic Human Coronaviruses (HCoVs) which cause respiratory infections. Common cold coronaviruses HCoV‐229E, HCoV‐OC43, HCoV‐NL63, HCoV‐HKU1 are the four endemic HCoVs. SARS‐CoV‐1, MERS‐CoV, SARS‐CoV‐2 are zoonotic emerging epidemic pathogens with significant morbidity, mortality and economic impact. The endemic HCoVs have been known to cause co‐infections or can be co‐detected with each other or with other respiratory viruses. In general, respiratory viral co‐infections are recognized more commonly today with the use of respiratory multiplex molecular diagnostic panels. Clinicians need to be aware of co‐infections among HCoVs. A high degree of suspicion in this rapidly evolving outbreak is required in order to make the diagnosis. This is vital if we are to try and contain and control the spread of the COVID‐19. This article is protected by copyright. All rights reserved.

Title: The Rheumatologist's Role in Covid-19. Content: The novel coronavirus (SARS-CoV-2) pandemic has spread rapidly throughout the planet. It is believed to have originated in the Wuhan province of China, but this highly contagious respiratory virus has spread to over 140 countries on 6 continents as of mid-March 2020 according to the World Health Organization (WHO). Worldwide, there have been over 164,000 cases identified and over 6,500 deaths attributed to the viral infection. As of March 15, 2020, there are over 3,700 confirmed cases and 68 deaths ascribed to Covid-19 (the disease caused by SARS-CoV-2) in the United States [https://www.livescience.com/coronavirus-updates-unitedstates.html].

Title: COVID-19: A Risk Assessment Perspective Content: [Image: see text] COVID-19 is a newly emerging viral respiratory disease first identified in Wuhan, China, in December 2019. The disease is caused by the coronavirus SARS-CoV-2, which is related to the viruses that cause SARS and MERS. While the case fatality ratio for COVID-19 (5%) is far lower than that for SARS (11%) and MERS (34%), COVID-19 is spreading relatively uncontrolled at this time across the globe. In contrast, SARS appears to be contained, and MERS is controlled. This paper will explore why COVID-19 is able to progress to a global pandemic that affects our daily lives to an extent not known in recent history. The COVID-19 outbreak and spread will be examined based on the current literature, using a researcher’s perspective of risk assessment and risk mitigation; this approach will be related to public health.

Title: Characteristics of a family cluster of Severe Acute Respiratory Syndrome Coronavirus 2 in Henan, China Content: • The worldwide outbreak of SARS-CoV-2 called for more close investigations of the family transmission routes of infectious diseases. • We hypothesize that the likelihood to develop COVID-19 is probably associated with the duration of being exposed to SARS-CoV-2. • In a family cluster, asymptomatic infection carriers can be persons of all ages, from nine to sixty years old.

Title: Data-driven Analytical Models of COVID-2019 for Epidemic Prediction, Clinical Diagnosis, Policy Effectiveness and Contact Tracing: A Survey Content: The widely spread CoronaVirus Disease (COVID)-19 is one of the worst infectious disease outbreaks in history and has become an emergency of primary international concern. As the pandemic evolves, academic communities have been actively involved in various capacities, including accurate epidemic estimation, fast clinical diagnosis, policy effectiveness evaluation and development of contract tracing technologies. There are more than 23,000 academic papers on the COVID-19 outbreak, and this number is doubling every 20 days while the pandemic is still on-going [1]. The literature, however, at its early stage, lacks a comprehensive survey from a data analytics perspective. In this paper, we review the latest models for analyzing COVID19 related data, conduct post-publication model evaluations and cross-model comparisons, and collect data sources from different projects.

Title: Modeling COVID-19 Growing Trends to Reveal the Differences in the Effectiveness of Non-Pharmaceutical Interventions among Countries in the World Content: Objective: We hypothesize that COVID-19 case growth data reveals the efficacy of NPIs. In this study, we conduct a secondary analysis of COVID-19 case growth data to compare the differences in the effectiveness of NPIs among 16 representative countries in the world. Methods: This study leverages publicly available data to learn patterns of dynamic changes in the reproduction rate for sixteen countries covering Asia, Europe, North America, South America, Australia, and Africa. Furthermore, we model the relationships between the cumulative number of cases and the dynamic reproduction rate to characterize the effectiveness of the NPIs. We learn four levels of NPIs according to their effects in the control of COVID-19 growth and categorize the 16 countries into the corresponding groups. Results: The dynamic changes of the reproduction rate are learned via linear regression models for all of the studied countries, with the average adjusted R-squared at 0.96 and the 95% confidence interval as [0.94 0.98]. China, South Korea, Argentina, and Australia are at the first level of NPIs, which are the most effective. Japan and Egypt are at the second level of NPIs, and Italy, Germany, France, Netherlands, and Spain, are at the third level. The US and UK have the most inefficient NPIs, and they are at the fourth level of NPIs. Conclusions: COVID-19 case growth data provides evidence to demonstrate the effectiveness of the NPIs. Understanding the differences in the efficacy of the NPIs among countries in the world can give guidance for emergent public health events.

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: Psychological, Political, and Situational Factors Combine to Boost COVID-19 Conspiracy Theory Beliefs Content: Conspiracy theories (CTs) are not solely the domain of extremists and paranoids. They cut across demographic and political differences (Uscinski and Parent, 2014) and can have negative social/political consequences. For example, Imhoff and Lamberty (2020) find that belief that the seriousness of COVID-19 is being exaggerated is negatively correlated with self-reported preventative behaviours such as hand washing and social distancing, and belief that the virus was intentionally created by humans is positively correlated with self-reported hoarding of food, sanitary products, and gasoline/oil, as well as stocking up on weapons.

Title: [Epidemiological analysis on 1 052 cases of COVID-19 in epidemic clusters] Content: Objective: To understand the epidemiological characteristics of the cases of COVID-19 epidemic clusters, and explore the influence of family factors and social factors such as group activities on the spread of the disease. Methods: The data of cases of COVID-19 epidemic clusters from 19 January, 2020 to 25 February, 2020 were collected from the official platforms of 36 cities in 6 provinces in China. Descriptive statistical methods, χ(2) test and curve fitting were used to analyze the epidemiological characteristics of the clustered cases. Results: By 25 February, 2020, the data of 1 052 cases in 366 epidemic clusters were collected. In these clustered cases, 86.9%(914/1 050) occurred in families. Among the 1 046 cases with gender information, 513 were males (49.0%) and 533 were females (51.0%). The cases were mainly young adults between 18 and 59 years old, accounting for 68.5% (711/1 038). In the 366 epidemic clusters , the clusters in which the first confirmed cases with the history of sojourn in Wuhan or Hubei accounted for 47.0%(172/366). From 19 January to 3 February, 2020, the first confirmed cases with Wuhan or Hubei sojourn history accounted for 66.5%. From 4 to 25 February, the first confirmed cases who had Wuhan or Hubei sojourn history accounted for only 18.2%. The median of interval between the first generation case onset and the second generation case onset was 5 (2-8) days. The median of onset- diagnosis interval of the initial cases was 6 (3-9) days, and the median of onset-diagnosis interval of the secondary cases was 5 (3-8) days. Conclusions: Epidemic clusters of COVID-19 were common in many cities outside Wuhan and Hubei. Close contact in family was one of the main causes for the spread of household transmission of the virus. After 4 February, the epidemic clusters were mainly caused by the first generation or second generation cases in local areas, and the time for diagnosis became shorter.

Title: Active tuberculosis, sequelae and COVID-19 co-infection: first cohort of 49 cases Content: The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) disease (COVID-19) pandemic has attracted interest because of its global rapid spread, clinical severity, high mortality rate, and capacity to overwhelm healthcare systems [1, 2]. SARS-CoV-2 transmission occurs mainly through droplets, although surface contamination contributes and debate continues on aerosol transmission [3–5].

Title: Temporal data series of COVID-19 epidemics in the USA, Asia and Europe suggests a selective sweep of SARS-CoV-2 Spike D614G variant Content: The COVID-19 pandemic started in Wuhan, China, and caused the worldwide spread of the RNA virus SARS-CoV-2, the causative agent of COVID-19. Because of its mutational rate, wide geographical distribution, and host response variance this coronavirus is currently evolving into an array of strains with increasing genetic diversity. Most variants apparently have neutral effects for disease spread and symptoms severity. However, in the viral Spike protein, which is responsible for host cell attachment and invasion, an emergent variant, containing the amino acid substitution D to G in position 614 (D614G), was suggested to increase viral infection capability. To test whether this variant has epidemiological impact, the temporal distributions of the SARS-CoV-2 samples bearing D or G at position 614 were compared in the USA, Asia and Europe. The epidemiological curves were compared at early and late epidemic stages. At early stages, where containment measures were still not fully implemented, the viral variants are supposed to be unconstrained and its growth curves might approximate the free viral dynamics. Our analysis shows that the D614G prevalence and the growth rates of COVID-19 epidemic curves are correlated in the USA, Asia and Europe. Our results suggest a selective sweep that can be explained, at least in part, by a propagation advantage of this variant, in other words, that the molecular level effects of D614G have sufficient impact on population transmission dynamics as to be detected by differences in rate coefficients of epidemic growth curves.

Title: Is visiting Qom spread CoVID-19 epidemic in the Middle East? Content: The CoVID-19 epidemic started in Wuhan, China and spread to 217 other countries around the world through direct contact with patients, goods transfer, animal transport, and touching unclean surfaces. In the Middle East, the first confirmed case in both Iran and UAE originated from China. A series of infections since those confirmed cases started in the Middle East originated from Qom, Iran, and other Shi'ite holy places. Thereafter, CoVID-19 has been transmitted to other countries in the Middle East. This report aims to trace all of the confirmed cases in the Middle East until March 6, 2020 and their further spread. This report proves that further transmission of CoVID-19 to the Middle East was because of human mobility, besides engaging in different Jewish and Shi'ite religious rites. This report suggests avoiding several religious rites, closing the borders of infected countries, and supporting the infected countries to prevent further transmission.

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: Connecting the Dots of COVID-19 Transmissions in India Content: Witnessing its first case in late January 2020 India has seen a sharp rise in the number of positive cases of COVID-19. 34 States/UT (s) of the country have been found to be affected by the pandemic to date. We in this work, study the progress of COVID-19 pandemic in India. We aim to create transmission network visualization (s) of COVID-19 in India and perform analysis upon them. Using the transmission networks obtained we attempt to find the possible Super Spreader Individual (s) and Super Spreader Events (SSE) responsible for the outbreak in their respective regions. We discuss the potentials of network analysis in mitigating the further spread of the disease. This is one of the initial studies of the outbreak in India and the first attempt to study the pandemic in the country from a transmission network perspective.

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: Comparison of Transmissibility of Coronavirus Between Symptomatic and Asymptomatic Patients: Reanalysis of the Ningbo COVID-19 Data Content: BACKGROUND: Since the outbreak of the novel coronavirus disease (COVID-19) in December 2019, the coronavirus has spread all over the world at an unprecedented rate. The transmissibility of the coronavirus from asymptomatic patients to healthy individuals has received enormous attention. An important study using COVID-19 data from the city of Ningbo, China, was carried out to estimate and compare the transmission rates of the coronavirus by the symptomatic and asymptomatic patients. However, in the original analysis, the usual chi-square tests were unduly used for some contingency tables with small cell counts including zero, which may violate the assumptions for the chi-square test. OBJECTIVE: We reanalyze the data from the city of Ningbo with more appropriate statistical methods to draw more reliable and sound conclusions on the transmission rates of the coronavirus by the symptomatic and asymptomatic patients. METHODS: We excluded the cases associated with the super-spreader and adopted a more appropriate statistical method, including the permutation test and the Fisher exact test, to reanalyze the COVID-19 data from the city of Ningbo. RESULTS: After excluding the cases related to the super-spreader, the Fisher exact test yields a P value of .84, which indicates stronger evidence of no difference in the transmission rates compared with the original analysis. The odds ratio of the coronavirus transmission rates between the symptomatic and asymptomatic patients is 1.2 with a 95% confidence interval 0.5-2.8. CONCLUSIONS: Through a more in-depth and comprehensive statistical analysis of the Ningbo data, we concluded that there is no difference in the transmission rates of coronavirus between symptomatic and asymptomatic patients.

Title: Estimating the generation interval for coronavirus disease (COVID-19) based on symptom onset data, March 2020 Content: BACKGROUND: Estimating key infectious disease parameters from the coronavirus disease (COVID-19) outbreak is essential for modelling studies and guiding intervention strategies. AIM: We estimate the generation interval, serial interval, proportion of pre-symptomatic transmission and effective reproduction number of COVID-19. We illustrate that reproduction numbers calculated based on serial interval estimates can be biased. METHODS: We used outbreak data from clusters in Singapore and Tianjin, China to estimate the generation interval from symptom onset data while acknowledging uncertainty about the incubation period distribution and the underlying transmission network. From those estimates, we obtained the serial interval, proportions of pre-symptomatic transmission and reproduction numbers. RESULTS: The mean generation interval was 5.20 days (95% credible interval (CrI): 3.78–6.78) for Singapore and 3.95 days (95% CrI: 3.01–4.91) for Tianjin. The proportion of pre-symptomatic transmission was 48% (95% CrI: 32–67) for Singapore and 62% (95% CrI: 50–76) for Tianjin. Reproduction number estimates based on the generation interval distribution were slightly higher than those based on the serial interval distribution. Sensitivity analyses showed that estimating these quantities from outbreak data requires detailed contact tracing information. CONCLUSION: High estimates of the proportion of pre-symptomatic transmission imply that case finding and contact tracing need to be supplemented by physical distancing measures in order to control the COVID-19 outbreak. Notably, quarantine and other containment measures were already in place at the time of data collection, which may inflate the proportion of infections from pre-symptomatic individuals.

Title: COVID-19: A New Virus as a Potential Rapidly Spreading in the Worldwide Content: Covid-19 is a novel virus with high affinity to spread in the community In December 2019, it was first identified in Wuhan, China The symptoms are non-specific, so fever, cough, dyspnea, are prominent features Respiratory failure and mortality have also been reported The most common lung CT scan findings are bilateral ground glass opacities

Title: On the COVID-19 Pandemic in Indian State of Maharashtra: Forecasting & Effect of different parameters Content: This work details the outbreak and factors affecting the spread of novel coronavirus (COVID-19) in the Indian state of Maharashtra, which is considered as one of the most massive and deadly pandemic outbreaks. Observational data collected between 14 March 2020 and 4 May 2020 is statistically analyzed to determine the nonlinear behaviour of the epidemic. It is followed by validating predicted results with real-time data. Proposed model is further used to obtain statistical summaries in which Grubbs tests for outlier detection have justified high values of evaluation metrics. Outliers are found to be pilot elements in an outbreak under considered region. Statistically, a significant correlation has been observed between dependent and explanatory variables. Transmission pattern of this virus is very much different from the SARS-CoV-1 virus. Key findings of this work will be predominant in maintaining environment conditions at healthcare facilities to reduce transmission rates at these most vulnerable places. KEY WORDS-: SARS-CoV-1; COVID-19, Humidity, Polynomial, Temperature, Confirmed cases; Tests; Maharashtra.

Title: A Machine Learning Explanation of Incidence Inequalities of SARS-CoV-2 Across 88 Days in 157 Countries Content: Because the SARS-CoV-2 (COVID-19) pandemic viral outbreaks will likely continue until effective vaccines are widely administered, (1) new capabilities to accurately predict incidence rates by location and time to know in advance the disease burden and specific needs for any given population are valuable to minimize morbidity and mortality. In this study, a random forest of 9,250 regression trees was applied to 6,941 observations of 13 statistically significant predictor variables targeting SARS-CoV-2 incidence rates per 100,000 across 88 days in 157 countries. One key finding is an algorithm that can predict the incidence rate per day of a SARS-CoV-2 epidemic cycle with a pseudo-R2 accuracy of 98.5% and explain 97.4% of the variances. Another key finding is the relative importance of 13 demographic, economic, environmental, and public health modulators to the SARS-CoV-2 incidence rate. Four factors proposed in earlier research as potential modulators have no statistically significant relationship with incidence rates (2)(3). These findings give leaders new capabilities for improved capacity planning and targeting stay-at-home interventions and prioritizing programming by knowing the atypical social determinants that are the root causes of SARS-CoV-2 incidence variance. This work also proves that machine learning can accurately and quickly explain disease dynamics for zoonoses with pandemic potential.

Title: Covid-19 outbreak and perspective in morocco Content: Coronavirus disease 2019 (COVID-19) is a respiratory illness that can spread from person to person. The virus that causes COVID-19 is a novel coronavirus that was first identified during an investigation into an outbreak in Wuhan, China and rapidly spread across the world to become the first pandemic caused by a coronavirus. As of 26 March 2020, there are 275 cases affected by COVID-19 announced by the Moroccan government, and it possible to limit the spread of this serious disease, with the cooperation of all the citizens in respect of the measures of containment and individual protection. Also, with the announce yesterday by the Moroccan government of the authorization of use of chloroquine in treatment of COVID-19 pneumonia, COVID-19 will be soon eradicated from Morocco and hopefully from all over the world.