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

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: 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: 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: 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: 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 2019 (COVID-19) in December 2019, the coronavirus has spread all over the world at an unprecedented rate. The transmissibility of coronavirus from asymptomatic patients to healthy individuals has received enormous attention. An important study using the COVID-19 data from the city 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-squared tests were unduly used for some contingency tables with small cell counts including zero, which may violate the assumptions for the chi-squared test. OBJECTIVE We reanalyze the data from the city 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 exclude the cases associated with the super-spreader and adopt more appropriate statistical methods, including the permutation test and Fisher's exact test, to reanalyze the COVID-19 data from the city Ningbo. RESULTS After excluding the cases related to the super-spreader, Fisher's exact test yields p-value=.84, which indicates stronger evidence of no difference in the transmission rates compared with the original analysis. The odds ratio of transmission rates of coronavirus 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 conclude that there is no difference in the transmission rates of coronavirus between the symptomatic and asymptomatic patients.

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: 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: 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: Spatial super-spreaders and super-susceptibles in human movement networks Content: As lockdowns and stay-at-home orders start to be lifted across the globe, governments are struggling to establish effective and practical guidelines to reopen their economies. In dense urban environments with people returning to work and public transportation resuming full capacity, enforcing strict social distancing measures will be extremely challenging, if not practically impossible. Governments are thus paying close attention to particular locations that may become the next cluster of disease spreading. Indeed, certain places, like some people, can be"super-spreaders."Is a bustling train station in a central business district more or less susceptible and vulnerable as compared to teeming bus interchanges in the suburbs? Here, we propose a quantitative and systematic framework to identify spatial super-spreaders and the novel concept of super-susceptibles, i.e. respectively, places most likely to contribute to disease spread or to people contracting it. Our proposed data-analytic framework is based on the daily-aggregated ridership data of public transport in Singapore. By constructing the directed and weighted human movement networks and integrating human flow intensity with two neighborhood diversity metrics, we are able to pinpoint super-spreader and super-susceptible locations. Our results reveal that most super-spreaders are also super-susceptibles and that counterintuitively, busy peripheral bus interchanges are riskier places than crowded central train stations. Our analysis is based on data from Singapore, but can be readily adapted and extended for any other major urban center. It therefore serves as a useful framework for devising targeted and cost-effective preventive measures for urban planning and epidemiological preparedness.

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: Using Modelling to Disentangle the Relative Contributions of Zoonotic and Anthroponotic Transmission: The Case of Lassa Fever Content: BACKGROUND: Zoonotic infections, which transmit from animals to humans, form the majority of new human pathogens. Following zoonotic transmission, the pathogen may already have, or may acquire, the ability to transmit from human to human. With infections such as Lassa fever (LF), an often fatal, rodent-borne, hemorrhagic fever common in areas of West Africa, rodent-to-rodent, rodent-to-human, human-to-human and even human-to-rodent transmission patterns are possible. Indeed, large hospital-related outbreaks have been reported. Estimating the proportion of transmission due to human-to-human routes and related patterns (e.g. existence of super-spreaders), in these scenarios is challenging, but essential for planned interventions. METHODOLOGY/PRINCIPAL FINDINGS: Here, we make use of an innovative modeling approach to analyze data from published outbreaks and the number of LF hospitalized patients to Kenema Government Hospital in Sierra Leone to estimate the likely contribution of human-to-human transmission. The analyses show that almost [Image: see text] of the cases at KGH are secondary cases arising from human-to-human transmission. However, we found much of this transmission is associated with a disproportionally large impact of a few individuals (‘super-spreaders’), as we found only [Image: see text] of human cases result in an effective reproduction number (i.e. the average number of secondary cases per infectious case) [Image: see text], with a maximum value up to [Image: see text]. CONCLUSIONS/SIGNIFICANCE: This work explains the discrepancy between the sizes of reported LF outbreaks and a clinical perception that human-to-human transmission is low. Future assessment of risks of LF and infection control guidelines should take into account the potentially large impact of super-spreaders in human-to-human transmission. Our work highlights several neglected topics in LF research, the occurrence and nature of super-spreading events and aspects of social behavior in transmission and detection.

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: Unlinking super-linkers: the topology of epidemic response (Covid-19) Content: A key characteristic of the spread of infectious diseases is their ability to use efficient transmission paths within contact graphs. This enables the pathogen to maximise infection rates and spread within a target population. In this work, we devise techniques to localise infections and decrease infection rates based on a principled analysis of disease transmission paths within human-contact networks (proximity graphs). Experimental results of disease spreading shows that that at low visibility rates contact tracing slows disease spreading. However to stop disease spreading, contact tracing requires both significant visibility (at least 60%) into the proximity graph and the ability to place half of the population under isolation. We find that pro-actively isolating super-links -- key proximity encounters -- has significant benefits: targeted isolation of a fourth of the population based on 35% visibility into the proximity graph prevents an epidemic outbreak. It turns out that isolating super-spreaders is more effective than contact tracing and testing but less effective than targeting super-links. We highlight the important role of topology in epidemic outbreaks. We argue that proactive innoculation of a population by disabling super-links and super-spreaders may have an important complimentary role alongside contact tracing and testing as part of a sophisticated public-health response to epidemic outbreaks.

Title: Clinical and Epidemiologic Characteristics of Spreaders of Middle East Respiratory Syndrome Coronavirus during the 2015 Outbreak in Korea Content: Nosocomial transmission is an important characteristic of Middle East Respiratory Syndrome Coronavirus (MERS-CoV) infection. Risk factors for transmission of MERS-CoV in healthcare settings are not well defined. During the Korean outbreak in 2015, 186 patients had laboratory-confirmed MERS-CoV infection. Those suspected as a source of viral transmission were categorized into the spreader groups (super-spreader [n = 5] and usual-spreader [n = 10]) and compared to the non-spreader group (n = 171). Body temperature of ≥ 38.5°C (adjusted odds ratio [aOR], 5.54; 95% confidence interval [CI], 1.38–22.30; P = 0.016), pulmonary infiltration of ≥ 3 lung zones (aOR, 7.33; 95% CI, 1.93–27.79; P = 0.003), and a more nonisolated in-hospital days (aOR, 1.32 per 1 day; 95% CI, 1.09–1.60; P = 0.004) were significant risk factors in the spreader group. There was no different clinical factor between super-spreaders and usual-spreaders. Nonisolated in-hospital days was the only factor which tended to be higher in super-spreaders than usual-spreaders (Mean, 6.6 vs. 2.9 days; P = 0.061). Early active quarantine might help reducing the size of an outbreak.

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: 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: 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: Importance of Interaction Structure and Stochasticity for Epidemic Spreading: A COVID-19 Case Study Content: In the recent COVID-19 pandemic, computer simulations are used to predict the evolution of the virus propagation and to evaluate the prospective effectiveness of non-pharmaceutical interventions. As such, the corresponding mathematical models and their simulations are central tools to guide political decision-making. Typically, ODE-based models are considered, in which fractions of infected and healthy individuals change deterministically and continuously over time. In this work, we translate an ODE-based COVID-19 spreading model from literature to a stochastic multi-agent system and use a contact network to mimic complex interaction structures. We observe a large dependency of the epidemic's dynamics on the structure of the underlying contact graph, which is not adequately captured by existing ODE-models. For instance, existence of super-spreaders leads to a higher infection peak but a lower death toll compared to interaction structures without super-spreaders. Overall, we observe that the interaction structure has a crucial impact on the spreading dynamics, which exceeds the effects of other parameters such as the basic reproduction number R0. We conclude that deterministic models fitted to COVID-19 outbreak data have limited predictive power or may even lead to wrong conclusions while stochastic models taking interaction structure into account offer different and probably more realistic epidemiological insights.

Title: Clustering model for transmission of the SARS virus: application to epidemic control and risk assessment Content: Abstract We propose a new four state model for disease transmission and illustrate the model with data from the 2003 SARS epidemic in Hong Kong. The critical feature of this model is that the community is modelled as a small-world network of interconnected nodes. Each node is linked to a fixed number of immediate neighbors and a random number of geographically remote nodes. Transmission can only propagate between linked nodes. This model exhibits two features typical of SARS transmission: geographically localized outbreaks and “super-spreaders”. Neither of these features are evident in standard susceptible-infected-removed models of disease transmission. Our analysis indicates that “super-spreaders” may occur even if the infectiousness of all infected individuals is constant. Moreover, we find that nosocomial transmission in Hong Kong directly contributed to the severity of the outbreak and that by limiting individual exposure time to 3–5 days the extent of the SARS epidemic would have been minimal.

Title: Risk Factors for Transmission of Middle East Respiratory Syndrome Coronavirus Infection During the 2015 Outbreak in South Korea Content: BACKGROUND. Transmission heterogeneity was observed during the 2015 Korean outbreak of Middle East respiratory syndrome coronavirus (MERS-CoV) infection. Only 22 of 186 cases transmitted the infection, and 5 super-spreading events caused 150 transmissions. We investigated the risk factors for MERS-CoV transmission. METHODS. Epidemiological reports were used to classify patients as nonspreaders, spreaders, or those associated with a super-spreading event (5 or more transmissions). Logistic regression analyses were used to evaluate the factors for MERS-CoV transmission. RESULTS. Compared to nonspreaders, spreaders exhibited a longer interval from symptom onset to isolation (7 days vs 3 days) and more frequent pre-isolation pneumonia diagnoses (68.2% vs 17.1%). Spreaders also exhibited higher values for pre-isolation contacts (149 vs 17.5), pre-isolation hospitalization (68.2% vs 16.5%), and emergency room (ER) visits (50% vs 7.3%). Spreaders exhibited lower cycle thresholds for the upE and ORF1a genes (22.7 vs 27.2 and 23.7 vs 27.9, respectively). In multivariate analysis, transmission was independently associated with the cycle threshold (odds ratio [OR], 0.84; 95% confidence interval [CI], 0.75–0.96) and pre-isolation hospitalization or ER visits (OR, 6.82; 95% CI, 2.06–22.84). The super-spreading events exhibited higher values for pre-isolation contacts (777 vs 78), pre-isolation ER visits (100% vs 35.3%), and doctor shopping (100% vs 47.1%) compared to non-super-spreading events. CONCLUSIONS. These findings indicate that transmission is determined by host infectivity and the number of contacts, whereas super-spreading events were determined by the number of contacts and hospital visits. These relationships highlight the importance of rapidly enforcing infection control measures to prevent outbreaks.

Title: The impact of super-spreaders in COVID-19: mapping genome variation worldwide Content: The human pathogen severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is responsible for the major pandemic of the 21st century. We analyzed >4,700 SARS-CoV-2 genomes and associated meta-data retrieved from public repositories. SARS-CoV-2 sequences have a high sequence identity (>99.9%), which drops to >96% when compared to bat coronavirus. We built a mutation-annotated reference SARS-CoV-2 phylogeny with two main macro-haplogroups, A and B, both of Asian origin, and >160 sub-branches representing virus strains of variable geographical origins worldwide, revealing a uniform mutation occurrence along branches that could complicate the design of future vaccines. The root of SARS-CoV-2 genomes locates at the Chinese haplogroup B1, with a TMRCA dating to 12 November 2019 - thus matching epidemiological records. Sub-haplogroup A2a originates in China and represents the major non-Asian outbreak. Multiple founder effect episodes, most likely associated with super-spreader hosts, explain COVID-19 pandemic to a large extent.

Title: Super spreader cohorts and covid-19 Content: A simple two-cohort SIR like model can explain the qualitative behaviour of the logarithmic derivative estimations of the covid-19 epidemic evolution as observed in several countries. The model consists of a general population in which the R_0 value is slightly below 1, but in which a super-spreading small subgroup with high R_0, coupled to the general population, is contaminating a significant fraction of the population. The epidemic starts to slow down when herd immunity is reached in this subgroup. The dynamics of this system is quite robust against non-pharmaceutical measures.

Title: Super-spreaders and the rate of transmission of the SARS virus Content: Abstract We describe a stochastic small-world network model of transmission of the SARS virus. Unlike the standard Susceptible-Infected-Removed models of disease transmission, our model exhibits both geographically localised outbreaks and “super-spreaders”. Moreover, the combination of localised and long range links allows for more accurate modelling of partial isolation and various public health policies. From this model, we derive an expression for the probability of a widespread outbreak and a condition to ensure that the epidemic is controlled. Moreover, multiple simulations are used to make predictions of the likelihood of various eventual scenarios for fixed initial conditions. The main conclusions of this study are: (i) “super-spreaders” may occur even if the infectiousness of all infected individuals is constant; (ii) consistent with previous reports, extended exposure time beyond 3–5 days (i.e. significant nosocomial transmission) was the key factor in the severity of the SARS outbreak in Hong Kong; and, (iii) the spread of SARS can be effectively controlled by either limiting long range links (imposing a partial quarantine) or enforcing rapid hospitalisation and isolation of symptomatic individuals.

Title: Characterizing super-spreading in microblog: An epidemic-based information propagation model Content: Abstract As the microblogging services are becoming more prosperous in everyday life for users on Online Social Networks (OSNs), it is more favorable for hot topics and breaking news to gain more attraction very soon than ever before, which are so-called “super-spreading events”. In the information diffusion process of these super-spreading events, messages are passed on from one user to another and numerous individuals are influenced by a relatively small portion of users, a.k.a. super-spreaders. Acquiring an awareness of super-spreading phenomena and an understanding of patterns of wide-ranged information propagations benefits several social media data mining tasks, such as hot topic detection, predictions of information propagation, harmful information monitoring and intervention. Taking into account that super-spreading in both information diffusion and spread of a contagious disease are analogous, in this study, we build a parameterized model, the SAIR model, based on well-known epidemic models to characterize super-spreading phenomenon in tweet information propagation accompanied with super-spreaders. For the purpose of modeling information diffusion, empirical observations on a real-world Weibo dataset are statistically carried out. Both the steady-state analysis on the equilibrium and the validation on real-world Weibo dataset of the proposed model are conducted. The case study that validates the proposed model shows that the SAIR model is much more promising than the conventional SIR model in characterizing a super-spreading event of information propagation. In addition, numerical simulations are carried out and discussed to discover how sensitively the parameters affect the information propagation process.

Title: Minimising lockdown periods for regional elimination of covid-19 Content: Some nations have the option of pursuing a policy of complete elimination of covid-19 instead of a policy of "flattening the curve" so that the load the dis- ease places on medical facilities is bearable. A policy of elimination requires a rather onerous "lockdown". As the goal of elimination is approached, it is therefore important that there be an informed trade-off between the risk of disease re-emergence and the duration of the "lockdown". Here it is shown that an important factor in assessing this trade-off, is the distribution of secondary cases, not just the expected value of this distribution, R0 . It is shown that a distribution in which "super-spreaders" are more prominent in the epidemiology, allows for an earlier release from "lockdown" with reasonable safety despite some probability of asymptomatic cases. There is some evidence to support such a distribution for covid-19. Analytical calculations and simulations show that once there is only one recognised case in some subregion, release from "lockdown" will be reasonably safe after just one or two further incubation periods.

Title: Agent-Based Modeling for Super-Spreading Events: A Case Study of MERS-CoV Transmission Dynamics in the Republic of Korea Content: Super-spreading events have been observed in the transmission dynamics of many infectious diseases. The 2015 MERS-CoV outbreak in the Republic of Korea has also shown super-spreading events with a significantly high level of heterogeneity in generating secondary cases. It becomes critical to understand the mechanism for this high level of heterogeneity to develop effective intervention strategies and preventive plans for future emerging infectious diseases. In this regard, agent-based modeling is a useful tool for incorporating individual heterogeneity into the epidemic model. In the present work, a stochastic agent-based framework is developed in order to understand the underlying mechanism of heterogeneity. Clinical (i.e., an infectivity level) and social or environmental (i.e., a contact level) heterogeneity are modeled. These factors are incorporated in the transmission rate functions under assumptions that super-spreaders have stronger transmission and/or higher links. Our agent-based model has employed real MERS-CoV epidemic features based on the 2015 MERS-CoV epidemiological data. Monte Carlo simulations are carried out under various epidemic scenarios. Our findings highlight the roles of super-spreaders in a high level of heterogeneity, underscoring that the number of contacts combined with a higher level of infectivity are the most critical factors for substantial heterogeneity in generating secondary cases of the 2015 MERS-CoV transmission.

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: Children are not COVID-19 super spreaders: time to go back to school. Content:

Title: Chest tube with air leaks is a potential “super spreader” of COVID-19 Content:

Title: Chest tube with air leaks is a potential "super spreader" of COVID-19 Content:

Title: Children are not COVID-19 super spreaders: time to go back to school Content:

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: Pausing super spreader events for COVID-19 mitigation: International Hajj pilgrimage cancellation Content:

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: Using models to identify routes of nosocomial infection: a large hospital outbreak of SARS in Hong Kong. Content: Two factors dominated the epidemiology of severe acute respiratory syndrome (SARS) during the 2002-2003 global outbreak, namely super-spreading events (SSE) and hospital infections. Although both factors were important during the first and the largest hospital outbreak in Hong Kong, the relative importance of different routes of infection has not yet been quantified. We estimated the parameters of a novel mathematical model of hospital infection using SARS episode data. These estimates described levels of transmission between the index super-spreader, staff and patients, and were used to compare three plausible hypotheses. The broadest of the supported hypotheses ascribes the initial surge in cases to a single super-spreading individual and suggests that the per capita risk of infection to patients increased approximately one month after the start of the outbreak. Our estimate for the number of cases caused by the SSE is substantially lower than the previously reported values, which were mostly based on self-reported exposure information. This discrepancy suggests that the early identification of the index case as a super-spreader might have led to biased contact tracing, resulting in too few cases being attributed to staff-to-staff transmission. We propose that in future outbreaks of SARS or other directly transmissible respiratory pathogens, simple mathematical models could be used to validate preliminary conclusions concerning the relative importance of different routes of transmission with important implications for infection control.

Title: Precision public health to inhibit the contagion of disease and move toward a future in which microbes spread health Content: Antimicrobial resistance continues to outpace the development of new chemotherapeutics. Novel pathogens continue to evolve and emerge. Public health innovation has the potential to open a new front in the war of “our wits against their genes” (Joshua Lederberg). Dense sampling coupled to next generation sequencing can increase the spatial and temporal resolution of microbial characterization while sensor technologies precisely map physical parameters relevant to microbial survival and spread. Microbial, physical, and epidemiological big data could be combined to improve prospective risk identification. However, applied in the wrong way, these approaches may not realize their maximum potential benefits and could even do harm. Minimizing microbial-human interactions would be a mistake. There is evidence that microbes previously thought of at best “benign” may actually enhance human health. Benign and health-promoting microbiomes may, or may not, spread via mechanisms similar to pathogens. Infectious vaccines are approaching readiness to make enhanced contributions to herd immunity. The rigorously defined nature of infectious vaccines contrasts with indigenous “benign or health-promoting microbiomes” but they may converge. A “microbial Neolithic revolution” is a possible future in which human microbial-associations are understood and managed analogously to the macro-agriculture of plants and animals. Tradeoffs need to be framed in order to understand health-promoting potentials of benign, and/or health-promoting microbiomes and infectious vaccines while also discouraging pathogens. Super-spreaders are currently defined as individuals who play an outsized role in the contagion of infectious disease. A key unanswered question is whether the super-spreader concept may apply similarly to health-promoting microbes. The complex interactions of individual rights, community health, pathogen contagion, the spread of benign, and of health-promoting microbiomes including infectious vaccines require study. Advancing the detailed understanding of heterogeneity in microbial spread is very likely to yield important insights relevant to public health.

Title: Mathematical Modeling of COVID-19 Transmission Dynamics with a Case Study of Wuhan Content: We propose a compartmental mathematical model for the spread of the COVID-19 disease with special focus on the transmissibility of super-spreaders individuals. We compute the basic reproduction number threshold, we study the local stability of the disease free equilibrium in terms of the basic reproduction number, and we investigate the sensitivity of the model with respect to the variation of each one of its parameters. Numerical simulations show the suitability of the proposed COVID-19 model for the outbreak that occurred in Wuhan, China.

Title: Mathematical Modeling of COVID-19 Transmission Dynamics with a Case Study of Wuhan Content: Abstract We propose a compartmental mathematical model for the spread of the COVID-19 disease with special focus on the transmissibility of super-spreaders individuals. We compute the basic reproduction number threshold, we study the local stability of the disease free equilibrium in terms of the basic reproduction number, and we investigate the sensitivity of the model with respect to the variation of each one of its parameters. Numerical simulations show the suitability of the proposed COVID-19 model for the outbreak that occurred in Wuhan, China.

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: Implications for forensic death investigations from first Swiss post-mortem CT in a case of non-hospital treatment with COVID-19 Content: Abstract Case details: A case of a 50-year old HIV-positive man is presented, with focus on visualization of post-mortem computed tomography (PMCT) of the lungs, in comparison to a forensic control case. He had been found dead at home, a day after his nasopharyngeal swab had returned positive for SARS-COV-2, three days after the sample had been taken as an outpatient, over five weeks after first exhibiting possible symptoms. 3D-visualization was performed by visually discriminating correlates for aerated, poorly aerated and non-aerated lung regions. The visual side-by-side comparison with a control case shows the deterioration beyond any ”normal” post-mortem finding, however. The PMCT findings in the lungs resemble those of patients with acute respiratory distress syndrome (ARDS), while histologically identified inflammation also shows, in part binuclear, lymphocytes. In addition, acute liver dystrophy and acute tubular necrosis in the kidneys were found. Except coronary artery atherosclerosis, there appeared to be no remarkable pathology of the heart. Comment: With the pandemic impact of SARS-COV-2, a range of issues unfolds, also for medicolegal investigations into deaths, as we report the first Swiss case with post-mortem CT where death had occurred due to a SARS-COV-2 infection, with features of a severe acute respiratory distress syndrome, as an outpatient. As this pandemic from the view of risk assessment does constitute a black swan, underestimated fat tails as technical reason should be addressed by also analyzing apparent extreme single observations. This case of an outpatient (without hospital or intensive-care treatment) shows a pulmonary progression beyond the typical findings of COVID-19, to a non-specific picture of ARDS, where histologically, in part binuclear lymphocytes were remarked. What appeared to be an initially slow progression with final rapid escalation raises the question whether nasopharyngeal swabs alone or added pulmonary CT might be better for screening high-risk patients. The reported symptoms and relatively late medical consultation in this case appeared to contrast with the extensive pathology, raising the question whether any search for super-spreaders should not just focus on asymptomatic but under-reported symptomatic patients, and whether their prolonged circulation in everyday life would justify measures such as for example more extensive face mask policies. As post-mortem testing for SARS-COV-2 may not be available for every case, PMCT may provide sensitive testing for lung changes related to COVID-19. In order to allow for more precise medicolegal investigations in the context of COVID-19, however, any more specific extra tests may have to be financed by stakeholders in epidemiology, infectious disease or policy.

Title: Accounting for super-spreading gives the basic reproduction number R0 of COVID-19 that is higher than initially estimated Content: Transmission of infectious diseases is characterized by the basic reproduction number R0, a metric used to assess the threat posed by an outbreak and inform proportionate preventive decision-making. Based on individual case reports from the initial stage of the coronavirus disease 2019 epidemic, R0 is often estimated to range between 2 and 4. In this report, we show that a SEIR model that properly accounts for the distribution of the incubation period suggests that R0 lie in the range 4.4 - 11.7. This estimate is based on the doubling time observed in the near-exponential phases of the epidemic spread in China, United States, and six European countries. To support our empirical estimation, we analyze stochastic trajectories of the SEIR model showing that in the presence of super-spreaders the calculations based on individual cases reported during the initial phase of the outbreak systematically overestimate the doubling time and thus underestimate the actual value of R0.

Title: ACE 2 Coding Variants: A Potential X-linked Risk Factor for COVID-19 Disease Content: Viral genetic variants are widely known to influence disease progression among infected humans. Given the recent and rapid emergence of pandemic SARS-CoV-2 infection, the cause of COVID-19 disease, viral protein variants have attracted research interest. However, little has yet been written about genetic risk factors among human hosts. Human genetic variation has proven to affect disease progression and outcome for important diseases such as HIV infection and malaria infestation. The fact that the human ACE2 protein is encoded on the X chromosome means that males who carry rare ACE2 coding variants will express those variants in all ACE2-expressing cells, whereas females will typically express those variants in a mosaic distribution determined by early X-inactivation events. This sex-based difference in ACE2 expression has unique implications for epidemiological studies designed to assess host genetic factors influencing progression from asymptomatic SARS-coV-2 infection to COVID-19. Here we present theoretical modelling of rare ACE2 coding variants documented to occur naturally in several human superpopulations and subpopulations, and show that rare variants predicted to affect the binding of ACE2 to the SARS-CoV-2 spike protein exist in people. Though the rs4646116 (p.Lys26Arg) allele is found in 1 in 70 Ashkenazi Jewish males, and in 1 in 172 non-Finnish European males, this allele is found at higher frequencies in females. Furthermore, the class of missense ACE2 alleles predicted to affect SARS-CoV-2 binding are found in aggregate among 1.43% and 2.16% of Ashkenazi males and females, respectively, as well as in 0.58% and 1.24% of European males and females outside of Finland. These alleles are rarer in other population groups, and almost absent from East Asians genotyped to date. Though we are aware that full genome-wide and exome-wide sequencing studies may ultimately be required to assess human genetic susceptibility to SARS-CoV-2 fully, we argue on the basis of strong prior probabilities that genotyping of this class of alleles is justified in cases of atypical SARS-CoV-2 diseases, such as asymptomatic super-spreaders (if any are identified), and in neonatal/paediatric-onset COVID-19 disease. Even relatively rare susceptibility factors (1% or fewer carriers) may become quantitatively important in the context of hundreds of thousands of infections. A small number of asymptomatic carriers, or a small number of super-spreaders, or a small segment of the population that is disproportionately likely to require intensive care, can magnify the medical, social and economic impacts of a pandemic of this size. The speed of the pandemic and the large number of affected cases worldwide justify efforts to identify all possible risk factors for adverse outcomes, including efforts to identify genetic susceptibility factors in human hosts.

Title: [Epidemiological characteristics of severe acute respiratory syndrome in Tianjin and the assessment of effectiveness on measures of control]. Content: OBJECTIVE To analyze the epidemiologic characteristics of severe acute respiratory syndrome (SARS) and to evaluate the effectiveness on its major control measures in Tianjn. METHODS Adopting two case reports 1 and 2, designed by the Tianjin Centers for Disease Control and Prevention to develop a unified case-tracing table including the map of the distribution of close contacts to SARS patients. With those methods, investigation on patients and their close contacts at hospital wards, families, communities and institutions of the patients were carried out. RESULTS From April 13 through May 8, 2003, there were 175 SARS cases including imported ones, were identified with an incidence rate of 1.9 cases per 100,000. Among them, 14 died with a fatality of 8.0%. The whole process of epidemic in Tianjin was less than one month with the following features: (1) 93.7% of the total SARS cases in Tianjin were directly or indirectly transmitted by a super-spreader. (2) 68.6% of the total SARS patients were concentrated in 3 hospitals A, B and C which was menifastated in 'clustering'. Through study on the rest of the SARS patients, results showed that 16.8% of them were transmitted through family close contact and 2.3% due to contact to colleagues. However, 12.6% of the patients were not able to show evidence that they had any contact to a diagnosed SARS patient. At the early stage of the epidemic, a number of medical practitioners were infected, taking up 38.2% of the total SARS cases. Among the total number of 1 975 medical workers who participated in the SARS medical cares and treatments, 3.4% of them got infected. During the outbreak, all index cases and chains of transmission seemed to be clear, with only 3 patients not able to be traced for the source of infection, taking up 2% of the total SARS patients in Tianjin. Among the 10 index cases, only the super spreader and another one index case transmitted the virus to their contacts but the rest of index cases did not cause any secondary infection. CONCLUSION Though SARS is clinically severe and can be spreaded quickly, the epidemic can be under control within a short period of time if chains of SARS transmission are broken down and effective measures as isolation and quarantine against patients as well as underscoring awareness among the publics in a scientific way, being carried out.

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: A note on community-detection (Kemeny) based testing for COVID-19 Content: The Kemeny constant of a graph can be used to identify and analyse bridges between communities in a graph. Testing, tracking and tracing abilities have been identified as pivotal in helping countries to safely reopen activities after the first wave of the COVID-19 virus. Tracing techniques aim at reconstructing past history of contacts, but can face practical limits in an exponential growth of either testing or overly conservative quarantining. We show how this application of graph theory can be conveniently used to efficiently intercept new virus outbreaks, when they are still in their early stage. Simulations provide promising results in early identification and blocking of possible"super-spreader links that transmit disease between different communities.

Title: Airflow as a Possible Transmission Route of Middle East Respiratory Syndrome at an Initial Outbreak Hospital in Korea Content: In this study, the results of an airflow investigation conducted on 7 June 2015 as part of a series of epidemiologic investigations at Pyeongtaek St. Mary’s Hospital, South Korea, were investigated. The study involved 38 individuals who were infected directly and indirectly with Middle East Respiratory Syndrome (MERS), by a super-spreader patient. Tracer gas experiments conducted on the eighth floor, where the initial patient was hospitalized, confirmed that the tracer gas spread to adjacent patient rooms and rooms across corridors. In particular, the experiment with an external wind direction and speed similar to those during the hospitalization of the initial patient revealed that the air change rate was 17–20 air changes per hour (ACH), with air introduced through the window in the room of the infected patient (room 8104). The tracer gas concentration of room 8110, which was the farthest room, was 7.56% of room 8104, indicating that a high concentration of gas has spread from room 8104 to rooms across the corridor. In contrast, the tracer gas was barely detected in a maternity ward to the south of room 8104, where there was no secondary infected patient. Moreover, MERS is known to spread mainly by droplets through close contact, but long-distance dispersion is probable in certain environments, such as that of a super-spreader patient hospitalized in a room without ventilation, hospitals with a central corridor type, and indoor airflow dispersion due to external wind.

Title: Transmission characteristics of the COVID-19 outbreak in China: a study driven by data Content: The COVID-19 outbreak has been a serious public health threat worldwide. We use individually documented case descriptions of COVID-19 from China (excluding Hubei Province) to estimate the distributions of the generation time, incubation period, and periods from symptom onset to isolation and to diagnosis. The recommended 14-day quarantine period may lead to a 6.7% failure for quarantine. We recommend a 22-day quarantine period. The mean generation time is 3.3 days and the mean incubation period is 7.2 days. It took 3.7 days to isolate and 6.6 days to diagnose a patient after his/her symptom onset. Patients may become infectious on average 3.9 days before showing major symptoms. This makes contact tracing and quarantine ineffective. The basic reproduction number is estimated to be 1.54 with contact tracing, quarantine and isolation, mostly driven by super spreaders.

Title: Spatially Adjusted Time-varying Reproductive Numbers: Understanding the Geographical Expansion of Urban Dengue Outbreaks Content: The basic reproductive number (R(0)) is a fundamental measure used to quantify the transmission potential of an epidemic in public health practice. However, R(0) cannot reflect the time-varying nature of an epidemic. A time-varying effective reproductive number R(t) can provide more information because it tracks the subsequent evolution of transmission. However, since it neglects individual-level geographical variations in exposure risk, R(t) may smooth out interpersonal heterogeneous transmission potential, obscure high-risk spreaders, and hence hamper the effectiveness of control measures in spatial dimension. Therefore, this study proposes a new method for quantifying spatially adjusted (time-varying) reproductive numbers that reflects spatial heterogeneity in transmission potential among individuals. This new method estimates individual-level effective reproductive numbers (R(j)) and a summarized indicator for population-level time-varying reproductive number (R(t)). Data from the five most severe dengue outbreaks in southern Taiwan from 1998–2015 were used to demonstrate the ability of the method to highlight early spreaders contributing to the geographic expansion of dengue transmission. Our results show spatial heterogeneity in the transmission potential of dengue among individuals and identify the spreaders with the highest R(j) during the epidemic period. The results also reveal that super-spreaders are usually early spreaders that locate at the edges of the epidemic foci, which means that these cases could be the drivers of the expansion of the outbreak. Therefore, our proposed method depicts a more detailed spatial-temporal dengue transmission process and identifies the significant role of the edges of the epidemic foci, which could be weak spots in disease control and prevention.

Title: Modelling suggests blood group incompatibility may substantially reduce SARS-CoV-2 transmission Content: Several independent datasets suggest blood type A is over-represented and type O under-represented among COVID-19 patients. Here, I model a scenario in which ABO transfusion incompatibility reduces the chance of a patient transmitting the virus to an incompatible recipient. Comparison of model outputs to published data on COVID-19 prevalence indicates that if this scenario holds true, ABO incompatibility may reduce virus transmissibility by 60% or more. Paradoxically, however, targeted vaccination of either high-susceptibility type A or "super-spreader" type O individuals is less effective than random vaccination at blocking community spread of the virus. Instead, the key is to maintain blood type diversity amongst the remaining susceptible individuals. I stress that these results illustrate a theoretical model of ABO blood group interaction with virus transmission and require confirmation by observation.

Title: The correspondence between the structure of the terrestrial mobility network and the emergence of COVID-19 in Brazil Content: The inter-cities mobility network is of great importance in understanding outbreaks, especially in Brazil, a continental-dimension country. Grounded on the complex networks approach, cities are here represented as nodes and the flows as weighted edges - these geographical graphs, (geo)graphs, are handled in a Geographical Information System. We adopt the IBGE database from 2016, which contains the weekly flow of people between cities in terrestrial vehicles. The present work aims to investigate the correspondences of the networks' measures, like strength, degree, and betweenness with the emergence of cities with confirmed cases of COVID-19 in Brazil, and special attention is given to the state of Sao Paulo. We show that the results are better when certain thresholds are applied to the networks' flows to neglect the lowest-frequency travels. The correspondences presented statistical significance for most measures up to a certain period. Until the end of April, the best matchings are with the strength measure (total flow related to a node/city) under a high flow threshold in the Sao Paulo state, when the most connected cities are reached. After this stage, the lower thresholds become more suitable, indicating a possible signature of the outbreak interiorization process. Surprisingly, some countryside cities such as Campina Grande (state of Paraiba), Feira de Santana (state of Bahia), and Caruaru (state of Pernambuco) have higher strengths than some states' capitals. Furthermore, some cities from the Sao Paulo state such as Presidente Prudente and Ribeirao Preto are captured in the top-rank positions of all the analyzed network measures under different flow thresholds. Their importance in mobility is crucial and they are potential super spreaders like the states' capitals. Our analysis offers additional tools for understanding and decision support to inter-cities mobility interventions regarding the SARS-CoV-2 and other epidemics.

Title: Testing for COVID-19: willful ignorance or selfless behavior? Content: Widespread testing is key to controlling the spread of COVID-19. But should we worry about self-selection bias in the testing? The recent literature on willful ignorance says we should – people often avoid health information. In the context of COVID-19, such willful ignorance can bias testing data. Furthermore, willful ignorance often arises when selfish wants conflict with social benefits, which might be particularly likely for potential ‘super-spreaders’ – people with many social interactions – given people who test positive are urged to self-isolate for two weeks. We design a survey in which participants (n = 897) choose whether to take a costless COVID-19 test. We find that 70% would take a test. Surprisingly, the people most likely to widely spread COVID-19 – the extraverts, others who meet more people in their daily lives and younger people – are the most willing to take a test. People's ability to financially or emotionally sustain self-isolation does not matter to their decision. We conclude that people are selfless in their decision to test for COVID-19. Our results are encouraging – they imply that COVOD-19 testing may succeed in targeting those who generate the largest social benefits from self-isolation if infected, which strengthens the case for widespread testing.

Title: Analysis of intrapatient heterogeneity uncovers the microevolution of Middle East respiratory syndrome coronavirus Content: Genome sequence analysis of Middle East respiratory syndrome coronavirus (MERS-CoV) variants from patient specimens has revealed the evolutionary dynamics and mechanisms of pathogenesis of the virus. However, most studies have analyzed the consensus sequences of MERS-CoVs, precluding an investigation of intrapatient heterogeneity. Here, we analyzed non–consensus sequences to characterize intrapatient heterogeneity in cases associated with the 2015 outbreak of MERS in South Korea. Deep-sequencing analysis of MERS-CoV genomes performed on specimens from eight patients revealed significant intrapatient variation; therefore, sequence heterogeneity was further analyzed using targeted deep sequencing. A total of 35 specimens from 24 patients (including a super-spreader) were sequenced to detect and analyze variants displaying intrapatient heterogeneity. Based on the analysis of non–consensus sequences, we demonstrated the intrapatient heterogeneity of MERS-CoVs, with the highest level in the super-spreader specimen. The heterogeneity could be transmitted in a close association with variation in the consensus sequences, suggesting the occurrence of multiple MERS-CoV infections. Analysis of intrapatient heterogeneity revealed a relationship between D510G and I529T mutations in the receptor-binding domain (RBD) of the viral spike glycoprotein. These two mutations have been reported to reduce the affinity of the RBD for human CD26. Notably, although the frequency of both D510G and I529T varied greatly among specimens, the combined frequency of the single mutants was consistently high (87.7% ± 1.9% on average). Concurrently, the frequency of occurrence of the wild type at the two positions was only 6.5% ± 1.7% on average, supporting the hypothesis that selection pressure exerted by the host immune response played a critical role in shaping genetic variants and their interaction in human MERS-CoVs during the outbreak.

Title: System Dynamics Modeling of Within-Host Viral Kinetics of Coronavirus (SARS CoV-2) Content: Mathematical models are being used extensively in the study of SARS-CoV-2 transmission dynamics, becoming an essential tool for decision making concerning disease control. It is now required to understand the mechanisms involved in the interaction between the virus and the immune response effector cells, both innate and adaptive, in order to support lines of research related to the use of drugs, production of protective antibodies and of course, vaccines against SARS-CoV-2. The present study, using a system dynamic approach, hypothesizes over the conditions that characterize the fraction of the population which get infected by SARS-CoV-2 as the asymptomatic patients, the mild symptomatic, acute symptomatic, and also super-spreaders, in terms of innate immune response, the initial virus load, the virus burden with shedding events, and the cytokine levels.

Title: Predicting Super Spreading Events during the 2003 Severe Acute Respiratory Syndrome Epidemics in Hong Kong and Singapore Content: One of the intriguing characteristics of the 2003 severe acute respiratory syndrome (SARS) epidemics was the occurrence of super spreading events (SSEs). Here, the authors report the results of identifying the occurrence of SSEs in the Hong Kong and Singapore epidemics using mathematical and statistical analysis. Their predicted occurrence of SSEs agreed well with the reported occurrence of all seven super spreaders in the two cities. Additional unidentified SSEs were also found to exist. It was found that 71.1% and 74.8% of the infections were attributable to SSEs in Hong Kong and Singapore, respectively. There also seemed to be “synchronized” occurrences of infection peaks in both the community and the hospitals in Hong Kong. The results strongly suggested that the infection did not depend on the total number of symptomatic cases, with only a very small proportion of symptomatic individuals being shown to be infectious (i.e., able to infect other individuals). The authors found that the daily infection rate did not correlate with the daily total number of symptomatic cases but with the daily number of symptomatic cases who were not admitted to a hospital within 4 days of the onset of symptoms.

Title: Multi-chain Fudan-CCDC model for COVID-19 -- a revisit to Singapore's case Content: Background: COVID-19 has been impacting on the whole world critically and constantly since late December 2019. Rapidly increasing infections has raised intense worldwide attention. How to model the evolution of COVID-19 effectively and efficiently is of great significance for prevention and control. Methods: We propose the multi-chain Fudan-CCDC model based on the original single-chain model in [8] to describe the evolution of COVID-19 in Singapore. Multi-chains can be considered as the superposition of several single chains with different characteristics. We identify parameters of models by minimizing the penalty function. Results: The numerical simulation results exhibit the multi-chain model performs well on data fitting. Though unsteady the increments are, they could still fall within the range of 25% fluctuation from simulation results. It is predicted by multi-chain models that Singapore are experiencing a nonnegligible risk of explosive outbreak, thus stronger measures are urgently needed to contain the epidemic. Conclusion: The multi-chain Fudan-CCDC model provides an effective way to early detect the appearance of imported infectors and super spreaders and forecast a second outbreak. It can also explain the data in those countries where the single-chain model shows deviation from the data.

Title: No evidence of viral polymorphisms associated with Paediatric Inflammatory Multisystem Syndrome Temporally Associated With SARS-CoV-2 (PIMS-TS). Content: Generally, children and teenagers do not become seriously ill with COVID-19. However, in countries with high rates of coronavirus disease, children with the syndrome COVID-19 associated inflammation syndrome referred to as PIMS-TS have been reported. Similarities noted between SARS-CoV-2 Spike protein sequences and those of other super antigens has prompted the suggestion that this might be the mechanism by SARS-CoV-ST triggers PIMS-TS. It has also been suggested that the D614G variant found more commonly in the US and across European countries may explain why PIMS-TS appears to be common in these countries. Here we analysed viral sequences from 13 paediatric COVID-19 patients of whom five were diagnosed with PIMS-TS. This is the first characterisation of viruses from PIMS-TS patients. In contrast to what has been hypothesised, we found no evidence of unique sequences associated with the viruses from PIMS-TS patients.

Title: Clinical and Transmission Characteristics of Covid-19 - A Retrospective Study of 25 Cases from a Single Thoracic Surgery Department Content: The outbreak of corona virus disease 2019 (Covid-19) imposes a major challenge in managing patients undergoing surgical operation. In this study, we analyzed clinical and transmission features of 25 cases of Covid-19 from a single thoracic department, including 13 patients and 12 health care staff. There were 13 males and 12 females. The median age of the patients was 61 (range: 51 to 69) years. The median age of the health care staff was 35 (range: 22 to 51) years. By the end of follow-up date (Mar. 3, 2020), there were 16 non-severe cases (64%) and 9 severe cases (36%), 5 cases were dead (20%). Nineteen (76%) of the infected cases were confirmed by SARS-CoV-2 nucleic acid test, the rest were clinically diagnosed as suspected Covid-19 cases, and 19 (76%) of the infected cases had positive exposure history. We found that COPD was significantly associated with severity and death (P=0.040, and P=0.038, respectively), and chest operation was significantly associated with death for Covid-19 patients (P=0.039). A potential "super spreader" may be the source of the transmission before the implementation of quarantine and comprehensive protection. It was concluded that Covid-19 is associated with poor prognosis for patients undergoing thoracic operation, especially for those with COPD. Implementation of comprehensive protective measures is important to control nosocomial infection.

Title: Clinical and Transmission Characteristics of Covid-19 — A Retrospective Study of 25 Cases from a Single Thoracic Surgery Department Content: The outbreak of corona virus disease 2019 (Covid-19) imposes a major challenge in managing patients undergoing surgical operation. In this study, we analyzed clinical and transmission features of 25 cases of Covid-19 from a single thoracic department, including 13 patients and 12 health care staff. There were 13 males and 12 females. The median age of the patients was 61 (range: 51 to 69) years. The median age of the health care staff was 35 (range: 22 to 51) years. By the end of follow-up date (Mar. 3, 2020), there were 16 non-severe cases (64%) and 9 severe cases (36%), 5 cases were dead (20%). Nineteen (76%) of the infected cases were confirmed by SARS-CoV-2 nucleic acid test, the rest were clinically diagnosed as suspected Covid-19 cases, and 19 (76%) of the infected cases had positive exposure history. We found that COPD was significantly associated with severity and death (P=0.040, and P=0.038, respectively), and chest operation was significantly associated with death for Covid-19 patients (P=0.039). A potential “super spreader” may be the source of the transmission before the implementation of quarantine and comprehensive protection. It was concluded that Covid-19 is associated with poor prognosis for patients undergoing thoracic operation, especially for those with COPD. Implementation of comprehensive protective measures is important to control nosocomial infection.

Title: Topological dynamics of the 2015 South Korea MERS-CoV spread-on-contact networks Content: Network analysis to examine infectious contact relations provides an important means to uncover the topologies of individual infectious contact networks. This study aims to investigate the spread of diseases among individuals over contact networks by exploring the 2015 Middle East Respiratory Syndrome (MERS) outbreak in Korea. We present several distinct features of MERS transmission by employing a comprehensive approach in network research to examine both the traced relationship matrix of infected individuals and their bipartite transmission routes among healthcare facilities visited for treatment. The results indicate that a few super-spreaders were more likely to hold certain structural advantages by linking to an exceptional number of other individuals, causing several ongoing transmission events in neighbourhoods without the aid of any intermediary. Thus, the infectious contact network exhibited small-world dynamics characterised by locally clustered contacts exposed to transmission paths via short path lengths. In addition, nosocomial infection analysis shows the pattern of a common-source outbreak followed by secondary person-to-person transmission of the disease. Based on the results, we suggest policy implications related to the redesign of prevention and control strategies against the spread of epidemics.

Title: Household transmissions of SARS-CoV-2 in the time of unprecedented travel lockdown in China Content: IMPORTANCE: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) emerged in the city of Wuhan, China, in December 2019 and then spread globally. Limited information is available for characterizing epidemiological features and transmission patterns in the regions outside of Hubei Province. Detailed data on transmission at the individual level could be an asset to understand the transmission mechanisms and respective patterns in different settings. OBJECTIVE: To reconstruct infection events and transmission clusters of SARS-CoV-2 for estimating epidemiological characteristics at household and non-household settings, including super-spreading events, serial intervals, age- and gender-stratified risks of infection in China outside of Hubei Province. DESIGN, SETTING, AND PARTICIPANTS: 9,120 confirmed cases reported online by 264 Chinese urban Health Commissions in 27 provinces from January 20 to February 19, 2020. A line-list database is established with detailed information on demographic, social and epidemiological characteristics. The infection events are categorized into the household and non-household settings. EXPOSURES: Confirmed cases of SARS-CoV-2 infections. MAIN OUTCOMES AND MEASURES: Information about demographic characteristics, social relationships, travel history, timelines of potential exposure, symptom onset, confirmation, and hospitalization were extracted from online public reports. 1,407 infection events formed 643 transmission clusters were reconstructed. RESULTS: In total 34 primary cases were identified as super spreaders, and 5 household super-spreading events were observed. The mean serial interval is estimated to be 4.95 days (standard deviation: 5.24 days) and 5.19 days (standard deviation: 5.28 days) for households and non-household transmissions, respectively. The risk of being infected outside of households is higher for age groups between 18 and 64 years, whereas the hazard of being infected within households is higher for age groups of young (<18) and elderly (>65) people. CONCLUSIONS AND RELEVANCE: The identification of super-spreading events, short serial intervals, and a higher risk of being infected outside of households for male people of age between 18 and 64 indicate a significant barrier to the case identification and management, which calls for intensive non-pharmaceutical interventions (e.g. cancellation of public gathering, limited access of public services) as the potential mitigation strategies.

Title: A study of the probable transmission routes of MERS‐CoV during the first hospital outbreak in the Republic of Korea Content: Infections caused by the Middle East respiratory syndrome coronavirus (MERS‐CoV) are a serious health issue due to their prevalence and associated mortality. However, the transmission routes of the virus remain unclear, and thus, the current recommended control strategies are not evidence based. In this study, we investigated the transmission routes of MERS‐CoV during the first nosocomial outbreak in the Republic of Korea in May 2015 using a multi‐agent modeling framework. We identified seven hypothesized transmission modes based on the three main transmission routes (long‐range airborne, close contact, and fomite). The infection risks for each hypothesis were estimated using the multi‐agent modeling framework. Least‐squares fitting was conducted to compare the distribution of the predicted infection risk in the various scenarios with that of the reported attack rates and to identify the hypotheses with the best fit. In the scenarios in which the index patient was a super‐spreader, our model simulations suggested that MERS‐CoV probably spread via the long‐range airborne route. However, it is possible that the index patient shed an average viral load comparable to the loads reported in the literature, and that transmission occurred via a combined long‐range airborne and close contact route.

Title: Ultrametric model for covid-19 dynamics: an attempt to explain slow approaching herd immunity in Sweden Content: We present a mathematical model of infection dynamics that might explain slower approaching the herd immunity during the covid-19 epidemy in Sweden than it was predicted by a variety of other models; see graphs Fig. 2. The new model takes into account the hierarchic structure of social clusters in the human society. We apply the well developed theory of random walk on the energy landscapes represented mathematically with ultrametric spaces. This theory was created for applications to spin glasses and protein dynamics. To move from one social cluster (valley) to another, the virus (its carrier) should cross a social barrier between them. The magnitude of a barrier depends on the number of social hierarchy's levels composing this barrier. As the most appropriate for the recent situation in Sweden, we consider linearly increasing (with respect to hierarchy's levels) barriers. This structure of barriers matches with a rather soft regulations imposed in Sweden in March 2020. In this model, the infection spreads rather easily inside a social cluster (say working collective), but jumps to other clusters are constrained by social barriers. This model's feature matches with the real situation during the covid-19 epidemy, with its cluster spreading structure. Clusters need not be determined solely geographically, they are based on a number of hierarchically ordered social coordinates. The model differs crucially from the standard mathematical models of spread of disease, such as the SIR-model. In particular, our model describes such a specialty of spread of covid-19 virus as the presence of "super-spreaders" who by performing a kind of random walk on a hierarchic landscape of social clusters spreads infection. In future, this model will be completed by adding the SIR-type counterpart. But, the latter is not a specialty of covid-19 spreading.

Title: Severe acute respiratory syndrome--Singapore, 2003. Content: The Singapore Ministry of Health (MOH), with assistance from the World Health Organization (WHO), has been investigating an outbreak of severe acute respiratory syndrome (SARS). This is a novel condition caused by the SARS-associated coronavirus (SARS-CoV) and is characterized by both an atypical pneumonia and efficient nosocomial transmission. This report summarizes epidemiologic features of this outbreak in Singapore, including the influence of super spreaders and the national prevention and control strategy.

Title: Epidemiology and Clinical Features of Coronavirus disease 2019 in Children Content: Coronavirus disease-2019 (COVID-19), which started in Wuhan, China, in December 2019 and has been declared a worldwide pandemic in March 11, 2020, is a novel infectious disease that causes respiratory illness and death. Pediatric COVID-19 accounts for a small percentage of patients with outbreaks and is often milder than adults, but can progress to severe disease in some cases. Even neonates can suffer from COVID-19, and children may play a role as a spreader in the community. In this review, we summarize what is known about COVID-19 in children and adolescents until now.

Title: Generality of endemic prevalence formulae Content: Abstract In simple infection models, the susceptible proportion s * in endemic equilibrium is related to the basic reproduction number R 0 by s * = 1 / R 0 . We investigate the extent to which this relationship remains valid under more realistic modelling assumptions. In particular, we relax the biologically implausible assumptions that individuals’ lifetimes and infectious periods follow exponential distributions; allow a general recruitment process; allow for multiple stages of infection; and consider extension to a multigroup model in which the groups may represent, for instance, spatial heterogeneity, or the existence of super-spreaders. For a homogeneous population, we find that: (i) the susceptible proportion is s * = 1 / R 0 e , where R 0 e is a modified reproduction number, equal to R 0 only in certain circumstances; (ii) the proportions of the population in each stage of infection are proportional to the expected time spent by an infected individual in that stage before recovery or death. We demonstrate robustness of the formula s * = 1 / R 0 for many human infections by noting conditions under which R 0 e is approximately equal to R 0, while pointing out other circumstances under which this approximation fails. For heterogeneous populations, the formula s * = 1 / R 0 does not hold in general, but we are able to exhibit symmetry conditions under which it is valid.

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: 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: Sensitivity of commercial Anti-SARS-CoV-2 serological assays in a high-prevalence setting Content: We analysed SARS-CoV-2 specific antibody responses in 42 social and working contacts of a super-spreader from the Heinsberg area in Germany. Consistent with a high-prevalence setting 26 individuals had SARS-CoV-2 antibodies determined by in-house neutralisation testing. These results were compared with four commercial assays, suggesting limited sensitivity of the assays in such a high-prevalence setting. Although SARS-CoV-2 nucleocapsid restricted tests showed a better sensitivity, spike based assays had a stronger correlation with neutralisation capacity.

Title: Geographical tracking and mapping of coronavirus disease COVID-19/severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) epidemic and associated events around the world: how 21st century GIS technologies are supporting the global fight against outbreaks and epidemics Content: In December 2019, a new virus (initially called 'Novel Coronavirus 2019-nCoV' and later renamed to SARS-CoV-2) causing severe acute respiratory syndrome (coronavirus disease COVID-19) emerged in Wuhan, Hubei Province, China, and rapidly spread to other parts of China and other countries around the world, despite China's massive efforts to contain the disease within Hubei. As with the original SARS-CoV epidemic of 2002/2003 and with seasonal influenza, geographic information systems and methods, including, among other application possibilities, online real-or near-real-time mapping of disease cases and of social media reactions to disease spread, predictive risk mapping using population travel data, and tracing and mapping super-spreader trajectories and contacts across space and time, are proving indispensable for timely and effective epidemic monitoring and response. This paper offers pointers to, and describes, a range of practical online/mobile GIS and mapping dashboards and applications for tracking the 2019/2020 coronavirus epidemic and associated events as they unfold around the world. Some of these dashboards and applications are receiving data updates in near-real-time (at the time of writing), and one of them is meant for individual users (in China) to check if the app user has had any close contact with a person confirmed or suspected to have been infected with SARS-CoV-2 in the recent past. We also discuss additional ways GIS can support the fight against infectious disease outbreaks and epidemics.

Title: Geographical tracking and mapping of coronavirus disease COVID-19/severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) epidemic and associated events around the world: how 21st century GIS technologies are supporting the global fight against outbreaks and epidemics Content: In December 2019, a new virus (initially called ‘Novel Coronavirus 2019-nCoV’ and later renamed to SARS-CoV-2) causing severe acute respiratory syndrome (coronavirus disease COVID-19) emerged in Wuhan, Hubei Province, China, and rapidly spread to other parts of China and other countries around the world, despite China’s massive efforts to contain the disease within Hubei. As with the original SARS-CoV epidemic of 2002/2003 and with seasonal influenza, geographic information systems and methods, including, among other application possibilities, online real-or near-real-time mapping of disease cases and of social media reactions to disease spread, predictive risk mapping using population travel data, and tracing and mapping super-spreader trajectories and contacts across space and time, are proving indispensable for timely and effective epidemic monitoring and response. This paper offers pointers to, and describes, a range of practical online/mobile GIS and mapping dashboards and applications for tracking the 2019/2020 coronavirus epidemic and associated events as they unfold around the world. Some of these dashboards and applications are receiving data updates in near-real-time (at the time of writing), and one of them is meant for individual users (in China) to check if the app user has had any close contact with a person confirmed or suspected to have been infected with SARS-CoV-2 in the recent past. We also discuss additional ways GIS can support the fight against infectious disease outbreaks and epidemics.

Title: Host susceptibility to MERS-CoV infection, a retrospective cohort study of the 2015 Korean MERS outbreak Content: Abstract To evaluate host susceptibility factors to Middle East respiratory syndrome coronavirus (MERS-CoV) infection, we conducted a retrospective cohort study from the single largest exposure event of the 2015 Korean MERS outbreak. A total of 175 patients were closely exposed to a super-spreader, 26 of which were infected (14.9%). In a multivariate analysis, history of autologous stem cell transplantation (HR, 31.151; 95% CI, 5.447–178.145; P < 0.001) and tachypnea at ED (HR, 4.392; 95% CI, 1.402–13.761; P = 0.011) were significantly associated with MERS-CoV infection.

Title: Plausible models for propagation of the SARS virus Content: Using daily infection data for Hong Kong we explore the validity of a variety of models of disease propagation when applied to the SARS epidemic. Surrogate data methods show that simple random models are insufficient and that the standard epidemic susceptible-infected-removed model does not fully account for the underlying variability in the observed data. As an alternative, we consider a more complex small world network model and show that such a structure can be applied to reliably produce simulations quantitative similar to the true data. The small world network model not only captures the apparently random fluctuation in the reported data, but can also reproduces mini-outbreaks such as those caused by so-called ``super-spreaders'' and in the Hong Kong housing estate Amoy Gardens.

Title: A systematic review of Anakinra, Tocilizumab, Sarilumab and Siltuximab for coronavirus-related infections Content: Background There is accumulating evidence for an overly activated immune response characterised by the release of pro-inflammatory cytokines in severe Covid-19. Suppression of the inflammatory response with immunomodulatory therapies may be a potential therapeutic strategy. We systematically review and assess the effectiveness of specific interleukin-1 and -6 inhibitors for the treatment of coronavirus-related infections. Methods Electronic databases, pre-print servers and clinical trial registries were searched to identify current and ongoing studies of immunomodulatory agents (anakinra, sarilumab, siltuximab and tocilizumab) for the treatment of Covid-19 and other coronavirus related super infections. The co-primary outcome was time to hospital discharge (days) and severity on an ordinal scale measured at day 15. Results Five retrospective studies (tocilizumab, two case series and two case reports; siltuximab, one case series) were shortlisted for inclusion, totalling 59 patients. All studies had a moderate or high risk of bias, with multiple limitations. Insufficient data and inter-study heterogeneity prevented meta-analysis. Primary outcomes were inconsistently reported but suggest many patients experienced an improvement in status seven days following therapy. The case fatality ratio (CFR) of patients with severe Covid-19 included in our review was 6.8%, a figure substantially lower than that estimated in non-interventional case series. Of the studies measuring IL-6, all reported elevated baseline levels. Twenty-five ongoing registered clinical trials exploring immunomodulatory agents in Covid-19 were identified, although inconsistency in participants and endpoints are noted. Conclusion Inhibition of IL-6 with tocilizumab and siltuximab requires further evaluation in managing the assumed hyperinflammatory response associated with severe Covid-19. These early data are considered hypothesis generating and justify the need for well-designed randomised clinical studies.

Title: Contact tracing and disease control. Content: Contact tracing, followed by treatment or isolation, is a key control measure in the battle against infectious diseases. It is an extreme form of locally targeted control, and as such has the potential to be highly efficient when dealing with low numbers of cases. For this reason it is frequently used to combat sexually transmitted diseases and new invading pathogens. Accurate modelling of contact tracing requires explicit information about the disease-transmission pathways from each individual, and hence the network of contacts. Here, pairwise-approximation methods and full stochastic simulations are used to investigate the utility of contact tracing. A simple relationship is found between the efficiency of contact tracing necessary for eradication and the basic reproductive ratio of the disease. This holds for a wide variety of realistic situations including heterogeneous networks containing core-groups or super-spreaders, and asymptomatic individuals. Clustering (transitivity) within the transmission network is found to destroy the relationship, requiring lower efficiency than predicted.

Title: Computational modeling of Human-nCoV protein-protein interaction network Content: COVID-19 has created a global pandemic with high morbidity and mortality in 2020. Novel coronavirus (nCoV), also known as Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV2), is responsible for this deadly disease. International Committee on Taxonomy of Viruses (ICTV) has declared that nCoV is highly genetically similar to SARS-CoV epidemic in 2003 (89% similarity). Limited number of clinically validated Human-nCoV protein interaction data is available in the literature. With this hypothesis, the present work focuses on developing a computational model for nCoV-Human protein interaction network, using the experimentally validated SARS-CoV-Human protein interactions. Initially, level-1 and level-2 human spreader proteins are identified in SARS-CoV-Human interaction network, using Susceptible-Infected-Susceptible (SIS) model. These proteins are considered as potential human targets for nCoV bait proteins. A gene-ontology based fuzzy affinity function has been used to construct the nCoV-Human protein interaction network at 99.98% specificity threshold. This also identifies the level-1 human spreaders for COVID-19 in human protein-interaction network. Level-2 human spreaders are subsequently identified using the SIS model. The derived host-pathogen interaction network is finally validated using 7 potential FDA listed drugs for COVID-19 with significant overlap between the known drug target proteins and the identified spreader proteins.

Title: Reply to Gautret et al: hydroxychloroquine sulfate and azithromycin for COVID-19: what is the evidence and what are the risks? Content: The severity of COVID-19 has resulted in a global rush to find the right antiviral treatment to conquer the pandemic and to treat patients. This requires reliable studies to support treatment. In a recently published study by Gautret et al. the authors concluded that hydroxychloroquine monotherapy and hydroxychloroquine in combination with azithromycin reduced viral load. However, this trial has several major methodological issues, including the design, outcome measure and the statistical analyses. In this paper we discuss the background, clinical evidence, pharmacology and methodological issues related to this clinical trial. We understand the rush to release results, however in case conclusions are far reaching the evidence needs to be robust.

Title: Fighting COVID-19 Misinformation on Social Media: Experimental Evidence for a Scalable Accuracy-Nudge Intervention Content: Across two studies with more than 1,700 U.S. adults recruited online, we present evidence that people share false claims about COVID-19 partly because they simply fail to think sufficiently about whether or not the content is accurate when deciding what to share. In Study 1, participants were far worse at discerning between true and false content when deciding what they would share on social media relative to when they were asked directly about accuracy. Furthermore, greater cognitive reflection and science knowledge were associated with stronger discernment. In Study 2, we found that a simple accuracy reminder at the beginning of the study (i.e., judging the accuracy of a non-COVID-19-related headline) nearly tripled the level of truth discernment in participants' subsequent sharing intentions. Our results, which mirror those found previously for political fake news, suggest that nudging people to think about accuracy is a simple way to improve choices about what to share on social media.

Title: Fighting COVID-19 Misinformation on Social Media: Experimental Evidence for a Scalable Accuracy-Nudge Intervention. Content: Across two studies with more than 1,700 U.S. adults recruited online, we present evidence that people share false claims about COVID-19 partly because they simply fail to think sufficiently about whether or not the content is accurate when deciding what to share. In Study 1, participants were far worse at discerning between true and false content when deciding what they would share on social media relative to when they were asked directly about accuracy. Furthermore, greater cognitive reflection and science knowledge were associated with stronger discernment. In Study 2, we found that a simple accuracy reminder at the beginning of the study (i.e., judging the accuracy of a non-COVID-19-related headline) nearly tripled the level of truth discernment in participants' subsequent sharing intentions. Our results, which mirror those found previously for political fake news, suggest that nudging people to think about accuracy is a simple way to improve choices about what to share on social media.

Title: Strategies adopted and lessons learnt during the severe acute respiratory syndrome crisis in Singapore. Content: In Singapore, the military was actively involved in the containment of the outbreak of severe acute respiratory syndrome (SARS) last year. The outbreak started in February 2003 with three Singapore travellers to Hong Kong. At that time, nothing was known about the aetiological agent of the atypical pneumonia that was termed SARS. Unfortunately one of the travellers was a super-spreader, defined as a person with high efficiency for virus transmission, and was responsible for the expansion of the national outbreak. Not only was the Singapore military involved in contact tracing of personnel and enforcement of home quarantine, military-affiliated research institutes were also involved in providing diagnostic support. This review reconstructs the events that took place during the SARS outbreak, focusing on the special support arising from complementing the military-affiliated laboratory with the public health laboratory. A description of the diagnostic findings is provided in chronological order. The review ends with lessons Singapore learnt from the SARS crisis, stressing the importance of national preparedness for future outbreaks.

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: Cytokine Storm in COVID-19 patients transforms to a Cytokine Super Cyclone in patients with risk factors Content: The seventh human coronavirus SARS-CoV2 belongs to the cluster of extremely pathogenic coronaviruses like SARS-CoV and MERS-CoV, which are established to cause lower respiratory tract infection. The viral infection can be fatal as the disease advances to pneumonia followed by acute respiratory distress syndrome (ARDS). Increasingly higher cytokine concentration on account of over-stimulated immune response against the virus, or the ‘cytokine storm’, is the reason behind the manifestation of lethal clinical symptoms. In this article, we discuss the immune pathogenesis of cytokine storm and its relation with SARS-CoV2/COVID-19 risk factors. People with underlying risk factors are more susceptible to fatal complications of COVID-19 infection leading to poor clinical outcome. The increased pro-inflammatory immune status in patients with risk factors (diabetes, hypertension, cardiovascular disease, COPD) exacerbates the Cytokine-storm of COVID-19 to a Cytokine Super Cyclone. We also overviewed antiviral immune response provided by BCG vaccine involving the IL-1β, IL-6 and TNF-α secretion via ‘trained monocytes’, which confers early protection against SARS-CoV2.

Title: The Role of Personality and Linguistic Patterns in Discriminating Between Fake News Spreaders and Fact Checkers Content: Users play a critical role in the creation and propagation of fake news online by consuming and sharing articles with inaccurate information either intentionally or unintentionally. Fake news are written in a way to confuse readers and therefore understanding which articles contain fabricated information is very challenging for non-experts. Given the difficulty of the task, several fact checking websites have been developed to raise awareness about which articles contain fabricated information. As a result of those platforms, several users are interested to share posts that cite evidence with the aim to refute fake news and warn other users. These users are known as fact checkers. However, there are users who tend to share false information, who can be characterised as potential fake news spreaders. In this paper, we propose the CheckerOrSpreader model that can classify a user as a potential fact checker or a potential fake news spreader. Our model is based on a Convolutional Neural Network (CNN) and combines word embeddings with features that represent users’ personality traits and linguistic patterns used in their tweets. Experimental results show that leveraging linguistic patterns and personality traits can improve the performance in differentiating between checkers and spreaders.

Title: Excess mortality during the Covid-19 pandemic: Early evidence from England and Wales. Content: The Covid-19 pandemic has claimed many lives in the UK and globally. The objective of this paper is to study whether the number of deaths not registered as Covid-19-related has increased compared to what would have been expected in the absence of the pandemic. Reasons behind this might include Covid-19 underreporting, avoiding visits to hospitals or GPs, and the effects of the lockdown. I used weekly ONS data on the number of deaths in England and Wales that did not officially involve Covid-19 over the period 2015-2020. Simply observing trends is not sufficient as spikes in deaths may occasionally occur. I thus followed a difference-in-differences econometric approach to study whether there was a relative increase in deaths not registered as Covid-19-related during the pandemic, compared to a control. Results suggest that there were an additional 968 weekly deaths that officially did not involve Covid-19, compared to what would have otherwise been expected. It is possible that some people are dying from Covid-19 without being diagnosed, and/or that there are excess deaths due to other causes as a result of the pandemic. Analysing the cause of death for any excess non-covid-19 deaths will shed light upon the reasons for the increase in such deaths and will help design appropriate policy responses to save lives.

Title: Excess mortality during the Covid-19 pandemic: Early evidence from England and Wales Content: The Covid-19 pandemic has claimed many lives in the UK and globally. The objective of this paper is to study whether the number of deaths not registered as Covid-19-related has increased compared to what would have been expected in the absence of the pandemic. Reasons behind this might include Covid-19 underreporting, avoiding visits to hospitals or GPs, and the effects of the lockdown. I used weekly ONS data on the number of deaths in England and Wales that did not officially involve Covid-19 over the period 2015-2020. Simply observing trends is not sufficient as spikes in deaths may occasionally occur. I thus followed a difference-in-differences econometric approach to study whether there was a relative increase in deaths not registered as Covid-19-related during the pandemic, compared to a control. Results suggest that there were an additional 968 weekly deaths that officially did not involve Covid-19, compared to what would have otherwise been expected. It is possible that some people are dying from Covid-19 without being diagnosed, and/or that there are excess deaths due to other causes as a result of the pandemic. Analysing the cause of death for any excess non-covid-19 deaths will shed light upon the reasons for the increase in such deaths and will help design appropriate policy responses to save lives.

Title: The SARS outbreak in a general hospital in Tianjin, China -- the case of super-spreader. Content: Severe acute respiratory syndrome (SARS) is a newly emerged infectious disease with a high case-fatality rate and devastating socio-economic impact. In this report we summarized the results from an epidemiological investigation of a SARS outbreak in a hospital in Tianjin, between April and May 2003. We collected epidemiological and clinical data on 111 suspect and probable cases of SARS associated with the outbreak. Transmission chain and outbreak clusters were investigated. The outbreak was single sourced and had eight clusters. All SARS cases in the hospital were traced to a single patient who directly infected 33 people. The patients ranged from 16 to 82 years of age (mean age 38.5 years); 38.7% were men. The overall case fatality in the SARS outbreak was 11.7% (13/111). The outbreak lasted around 4 weeks after the index case was identified. SARS is a highly contagious condition associated with substantial case fatality; an outbreak can result from one patient in a relatively short period. However, stringent public health measures seemed to be effective in breaking the disease transmission chain.

Title: Escherichia coli, cattle and the propagation of disease Content: Several early models describing host–pathogen interaction have assumed that each individual host has approximately the same likelihood of becoming infected or of infecting others. More recently, a concept that has been increasingly emphasized in many studies is that for many infectious diseases, transmission is not homogeneous but highly skewed at the level of populations. In what became known as the ‘20/80 rule’, about 20% of the hosts in a population were found to contribute to about 80% of the transmission potential. These heterogeneities have been described for the interaction between many microorganisms and their human or animal hosts. Several epidemiological studies have reported transmission heterogeneities for Escherichia coli by cattle, a phenomenon with far-reaching agricultural, medical and public health implications. Focusing on E. coli as a case study, this paper will describe super-spreading and super-shedding by cattle, review the main factors that shape these transmission heterogeneities and examine the interface with human health. Escherichia coli super-shedding and super-spreading by cattle are shaped by microorganism-specific, cattle-specific and environmental factors. Understanding the factors that shape heterogeneities in E. coli dispersion by cattle and the implications for human health represent key components that are critical for targeted infection control initiatives.

Title: Considerations for pharmacoepidemiological analyses in the SARS-CoV-2 pandemic Content: The coronavirus disease 2019 (COVID-19) pandemic has triggered several hypotheses regarding use of specific medicines and risk of infection as well as prognosis. Under these unique circumstances, rapid answers require quick engagement in data collection and analyses; however, appropriate design and conduct of pharmacoepidemiologic studies are needed to generate valid and reliable evidence. In this paper, endorsed by the International Society for Pharmacoepidemiology, we provide methodological considerations for the conduct of pharmacoepidemiological studies in relation to the pandemic across eight domains: (1) timeliness of evidence, including the need to prioritise some questions over others in the acute phase of the pandemic; (2) the need to align observational and interventional research on efficacy; (3) the specific challenges related to "real-time epidemiology" during an ongoing pandemic; (4) what design to use to answer a specific question; (5) considerations on the definition of exposures; (6) what covariates to collect; (7) considerations on the definition of outcomes; and (8) the need for transparent reporting.

Title: Comparison of clinical course of patients with severe acute respiratory syndrome among the multiple generations of nosocomial transmission. Content: BACKGROUND Severe acute respiratory syndrome (SARS) is characterized by both an atypical pneumonia and efficient nosocomial transmission. However, it remains unknown whether the infectivity and the virulence of the pathogen will change throughout the successive transmission. This study was conducted to compare the clinical features and management regimens of patients with SARS among the multiple generations from nosocomial transmission initiated by a super-spreader. METHODS The clinical data of 84 epidemiologically-linked SARS patients from a hospital outbreak were retrospectively studied. All patients, in whom a clear-cut transmission generation could be noted, had a direct or indirect exposure to the index patient and the epidemic successively propagated through the multiple generations of cases within a short period of time. RESULTS There were 66 women and 18 men with mean age of (29.2 +/- 10.3) years in this cluster; and 96.4% of whom were health care workers. Detailed contact tracing identified 35 (41.7%) first-generation cases, 34 (40.5%) second-generation cases, and 15 (17.8%) third-generation cases. No statistical differences among the multiple generations of transmission were found in terms of age, gender, incubation period and length of hospital stay. With the advanced transmission generations, the initial temperature lowered, the number of cases with dry cough decreased. There were no statistical differences in the peak temperature and duration of fever, other accompanying symptoms, leucopenia; however, the time from initial pulmonary infiltrates to radiographic recovery shortened (P < 0.05). No differences were found in maximum number of lung fields involved, duration from the onset of fever to the occurrence of pulmonary infiltrates and time from the initial pulmonary infiltrate to its peak among the multiple transmission generations (P > 0.05). No statistical differences were found in modes of oxygen therapy and sorts of antibiotics prescribed among the various transmission generations (P > 0.05); however, as with the advanced transmission generations, the number of cases prescribed with methylprednisolone, human gamma-globulin, interferon-alpha, antiviral drugs (oral ribavirin or oseltamivir) increased (P < 0.05) and time from admission to starting these medication shortened (P < 0.05). CONCLUSIONS There is no evidence that SARS infection will evolve or transmit within a fashion that permits it to become less powerful throughout the successive transmission within a short time.

Title: Laparoscopic Roux-en-Y gastric bypass in super obese Göttingen minipigs. Content: BACKGROUND The specific mechanisms behind weight loss and comorbidity improvements in obese patients after Roux-en-Y gastric bypass (RYGBP) are still poorly understood. The aim of this study was to establish and evaluate the feasibility of a long-term survival RYGBP model in super obese Göttingen minipigs in order to improve the translational potential relative to current animal models. METHODS Eleven Göttingen minipigs with diet-induced obesity underwent laparoscopic RYGBP and were followed up to 9 months after surgery. Intra- and post-operative complications, body weight (BW), food intake and necropsy data were recorded. RESULTS Five minipigs survived without complications to the end of the study. Four minipigs developed surgical related complications and were euthanized while two minipigs died due to central venous catheter related complications. BW and food intake is reported for the six minipigs surviving longer than 4.5 months post-surgery. Weight loss and reduced food intake was seen in all minipigs. After 2-3 months of weight loss, weight regain was evident in all but two minipigs which seemed to continue losing weight. Necropsy revealed some variation in the length of the alimentary, biliary and common limb between minipigs. CONCLUSION The use of obese Göttingen minipigs as a translational RYGBP model is feasible and has potential for the study of RYGBP-related changes in gut function, type-2 diabetes and appetite regulation. Still, the surgical procedure is technically highly demanding in obese Göttingen minipigs and the peri-operative animal care and follow up requires close monitoring.

Title: Genomic variations of SARS-CoV-2 suggest multiple outbreak sources of transmission Content: We examined 169 genomes of SARS-CoV-2 and found that they can be classified into two major genotypes, Type I and Type II. Type I can be further divided into Type IA and IB. Our phylogenetic analysis showed that the Type IA resembles the ancestral SARS-CoV-2 most. Type II was likely evolved from Type I and predominant in the infections. Our results suggest that Type II SARS-CoV-2 was the source of the outbreak in the Wuhan Huanan market and it was likely originated from a super-spreader. The outbreak caused by the Type I virus should have occurred somewhere else, because the patients had no direct link to the market. Furthermore, by analyzing three genomic sites that distinguish Type I and Type II strains, we found that synonymous changes at two of the three sites confer higher protein translational efficiencies in Type II strains than in Type I strains, which might explain why Type II strains are predominant, implying that Type II is more contagious (transmissible) than Type I. These findings could be valuable for the current epidemic prevention and control.

Title: Super-factors associated with transmission of occupational COVID-2019 infection among healthcare staff in Wuhan , China. Content: BACKGROUND Globally, there have been many cases of COVID-2019 cases among medical staff, however, the main factors associated with the infection are not well understood. AIM To identify the super-factors causing COVID-19 infection in medical staff in China. METHODS A cross-sectional study was conducted between Jan. 1st, and Feb. 30th, 2020, where front line members of medical staff that took part in the care and treatment of patients with COVID-19 were enrolled. Epidemiological and demographic data between infected and uninfected groups were collected and compared. Social network analysis (SNA) was used to establish socio-metric social links between influencing factors. FINDINGS A total of 92 medical staff were enrolled. In all participant groups, the super-factor identified by the network was wearing a medical protective mask or surgical mask correctly (degree = 572; closeness =25; betweenness centrality = 3·23). Touching the cheek, nose, and mouth while working was the super-factor in the infected group. This was the biggest node in the network and had the strongest influence (degree = 370; closeness = 29; betweenness centrality = 0·37). Self-protection score was the super-factor in the uninfected group but was the isolated factor in the infected group (degree = 201; closeness = 28; betweenness centrality = 5·64). For family members, the exposure history to Huanan Seafood Wholesale Market and the contact history to wild animals were two isolated nodes. CONCLUSION High self-protection score was the main factor that prevented medical staff from contracting COVID-19 infection. The main factor that contributed to COVID-19 infections among medical staff was touching the cheek, nose and mouth while working.

Title: Super-factors associated with transmission of occupational COVID-2019 infection among healthcare staff in Wuhan , China Content: BACKGROUND: Globally, there have been many cases of COVID-2019 cases among medical staff, however, the main factors associated with the infection are not well understood. AIM: To identify the super-factors causing COVID-19 infection in medical staff in China. METHODS: A cross-sectional study was conducted between Jan. 1st, and Feb. 30th, 2020, where front line members of medical staff that took part in the care and treatment of patients with COVID-19 were enrolled. Epidemiological and demographic data between infected and uninfected groups were collected and compared. Social network analysis (SNA) was used to establish socio-metric social links between influencing factors. FINDINGS: A total of 92 medical staff were enrolled. In all participant groups, the super-factor identified by the network was wearing a medical protective mask or surgical mask correctly (degree = 572; closeness =25; betweenness centrality = 3·23). Touching the cheek, nose, and mouth while working was the super-factor in the infected group. This was the biggest node in the network and had the strongest influence (degree = 370; closeness = 29; betweenness centrality = 0·37). Self-protection score was the super-factor in the uninfected group but was the isolated factor in the infected group (degree = 201; closeness = 28; betweenness centrality = 5·64). For family members, the exposure history to Huanan Seafood Wholesale Market and the contact history to wild animals were two isolated nodes. CONCLUSION: High self-protection score was the main factor that prevented medical staff from contracting COVID-19 infection. The main factor that contributed to COVID-19 infections among medical staff was touching the cheek, nose and mouth while working.

Title: The epidemiology of the outbreak of severe acute respiratory syndrome (SARS) in Hong Kong--what we do know and what we don't. Content: Severe acute respiratory syndrome (SARS) struck Hong Kong bitterly in the spring of 2003, infecting 1755 persons and claiming nearly 300 lives. The epidemic was introduced by travellers from southern China, where the disease had originated. It started in late February and lasted until early June. Two notable 'super-spreading' events were reported, one inside a teaching hospital and the other in a private housing estate. Other than in the super-spreading events, the infectivity in the community appeared to be low, and there were few, if any, asymptomatic or subclinical infections. Health-care workers were at particular risk and accounted for 22 % of all probable cases. The main modes of transmission were through droplet spread and close/direct contacts, but situations conducive to aerosol generation appeared to be associated with higher risk. Our review suggests that there are still many unknown factors concerning the mode of transmission and environmental risk that need to be clarified.

Title: Considerations for pharmacoepidemiological analyses in the SARS-CoV-2 pandemic. Content: The coronavirus disease 2019 (COVID-19) pandemic has triggered several hypotheses regarding use of specific medicines and risk of infection as well as prognosis. Under these unique circumstances, rapid answers require quick engagement in data collection and analyses, however, appropriate design and conduct of pharmacoepidemiologic studies is needed to generate valid and reliable evidence. In this paper, endorsed by the International Society for Pharmacoepidemiology, we provide methodological considerations for the conduct of pharmacoepidemiological studies in relation to the pandemic across eight domains: (1) timeliness of evidence, including the need to prioritize some questions over others in the acute phase of the pandemic; (2) the need to align observational and interventional research on efficacy; (3) the specific challenges related to 'real-time epidemiology' during an ongoing pandemic; (4) what design to use to answer a specific question; (5) considerations on the definition of exposures; (6) what covariates to collect; (7) considerations on the definition of outcomes; and (8) the need for transparent reporting. This article is protected by copyright. All rights reserved.

Title: EveSense: What Can You Sense from Twitter? Content: Social media has become a useful source for detecting real-life events. This paper presents an event detection application EveSense. It detects real-life events and related trending topics from the Twitter stream and allows users to find interesting events that have recently occurred. It uses a novel Dynamic Heartbeat Graph (DHG) approach, which efficiently extracts distinguishing features and performs better than the existing event detection methods. We tested and evaluated the application on three case studies, including a sports event (FA cup Final) and two political events (Super Tuesday and US Election).

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.