Early epidemiological analysis of the 2019-nCoV outbreak based on a crowdsourced data

As the outbreak of novel 2019 coronavirus (2019-nCoV) progresses within China and beyond, there is a need for rapidly available epidemiological data to guide situational awareness and intervention strategies. Here we present an effort to compile epidemiological information on 2019-nCoV from media news reports and a physician community website (dxy.cn) between Jan 20, 2020 and Jan 30, 2020, as the outbreak entered its 7th week. We compiled a line list of patients reported in China and internationally and daily case counts by Chinese province. We describe the demographics, hospitalization and reporting delays for 288 patients, over time and geographically. We find a decrease in case detection lags in provinces outside of Wuhan and internationally, compared to Wuhan, and after Jan 18, 2020, as outbreak awareness increased. The rapid progression of reported cases in different provinces of China is consistent with local transmission beyond Wuhan. The age profile of cases points at a deficit among children under 15 years of age, possibly related to prior immunity with related coronavirus or behavioral differences. Overall, our datasets, which have been publicly available since Jan 21, 2020, align with official reports from Chinese authorities published more than a week later. Availability of publicly available datasets in the early stages of an outbreak is important to encourage disease modeling efforts by independent academic modeling teams and provide robust evidence to guide interventions.

Estimating the time-varying reproduction number for COVID-19 in South Africa during the first four waves using multiple measures of incidence for public and private sectors across four waves

ObjectivesWe aimed to quantify transmission trends in South Africa during the first four waves of the COVID-19 pandemic using estimates of the time-varying reproduction number (R) and to compare the robustness of R estimates based on three different data sources and using data from public and private sector service providers. MethodsWe estimated R from March 2020 through April 2022, nationally and by province, based on time series of rt-PCR-confirmed cases, hospitalizations, and hospital-associated deaths, using a method which models daily incidence as a weighted sum of past incidence. We also estimated R separately using public and private sector data. ResultsNationally, the maximum case-based R following the introduction of lockdown measures was 1.55 (CI: 1.43-1.66), 1.56 (CI: 1.47-1.64), 1.46 (CI: 1.38-1.53) and 3.33 (CI: 2.84-3.97) during the first (Wuhan-Hu), second (Beta), third (Delta), and fourth (Omicron) waves respectively. Estimates based on the three data sources (cases, hospitalisations, deaths) were generally similar during the first three waves but case-based estimates were higher during the fourth wave. Public and private sector R estimates were generally similar except during the initial lockdowns and in case-based estimates during the fourth wave. DiscussionAgreement between R estimates using different data sources during the first three waves suggests that data from any of these sources could be used in the early stages of a future pandemic. High R estimates for Omicron relative to earlier waves is interesting given a high level of exposure pre-Omicron. The agreement between public and private sector R estimates highlights the fact that clients of the public and private sectors did not experience two separate epidemics, except perhaps to a limited extent during the strictest lockdowns in the first wave.

Leveraging Serosurveillance and Postmortem Surveillance to Quantify the Impact of COVID-19 in Africa

BackgroundThe COVID-19 pandemic has had a devastating impact on global health, the magnitude of which appears to differ intercontinentally: for example, reports suggest 271,900 per million people have been infected in Europe versus 8,800 per million people in Africa. While Africa is the second largest continent by population, its reported COVID-19 cases comprise <3% of global cases. Although social, environmental, and environmental explanations have been proposed to clarify this discrepancy, systematic infection underascertainment may be equally responsible. MethodsWe seek to quantify magnitude of underascertainment in COVID-19s cumulative incidence in Africa. Using serosurveillance and postmortem surveillance, we constructed multiplicative factors estimating ratios of true infections to reported cases in African nations since March 2020. ResultsMultiplicative factors derived from serology data - in a subset of 12 nations - suggested a range of COVID-19 reporting rates, from 1 in 630 infections reported in Kenya (May 2020) to 1 in 15 infections reported in South Africa (November 2021). The largest multiplicative factor, 3,795, corresponded to Malawi (June 2020), suggesting <0.05% of infections captured. A similar set of multiplicative factors for all nations derived from postmortem data points toward the same conclusion: reported COVID-19 cases are unrepresentative of true infections, suggesting a key reason for low case burden in many African nations is significant underdetection and underreporting. ConclusionsWhile estimating COVID-19s exact burden is challenging, the multiplicative factors we present provide incidence curves reflecting likely-to-worst-case ranges of infection. Our results stress the need for expansive surveillance to allocate resources in areas experiencing severe discrepancies between reported cases, projected infections, and deaths. SummaryHere we present a range of estimates quantifying the extent of underascertainment of COVID-19 cumulative incidence in Africa. These estimates, constructed from serology and mortality data, suggest that systematic underdetection and underreporting may be contributing to the seemingly low burden of COVID-19 reported in Africa.

Potential roles of social distancing in mitigating the spread of coronavirus disease 2019 (COVID-19) in South Korea

On January 20, 2020, the first COVID-19 case was confirmed in South Korea. After a rapid outbreak, the number of incident cases has been consistently decreasing since early March; this decrease has been widely attributed to its intensive testing. We report here on the likely role of social distancing in reducing transmission in South Korea. Our analysis suggests that transmission may still be persisting in some regions.

The impact of relaxing interventions on human contact patterns and SARS-CoV-2 transmission in China

Non-pharmaceutical interventions to control COVID-19 spread have been implemented in several countries with different intensity, timing, and impact on transmission. As a result, post-lockdown COVID-19 dynamics are heterogenous and difficult to interpret. Here we describe a set of contact surveys performed in four Chinese cities (Wuhan, Shanghai, Shenzhen, and Changsha) during the pre-pandemic, lockdown, and post-lockdown period to quantify the transmission impact of relaxing interventions via changes in age-specific contact patterns. We estimate that the mean number of contacts increased 5%-17% since the end of the lockdown but are still 3-7 times lower than their pre-pandemic levels. We find that post-lockdown contact patterns in China are still sufficiently low to keep SARS-CoV-2 transmission under control. We also find that the impact of school interventions depends non-linearly on the share of other activities being resumed. When most community activities are halted, school closure leads to a 77% decrease in the reproductive number; in contrast, when social mixing outside of schools is at pre-pandemic level, school closure leads to a 5% reduction in transmission. Moving forward, to control COVID-19 spread without resorting to a lockdown, it will be key to dose relaxation in social mixing in the community and strengthen targeted interventions. One Sentence SummarySocial contacts estimated in the post-lockdown period in four large Chinese cities are not sufficient to sustain local SARS-CoV-2 transmission.

Health seeking behaviors of patients with acute respiratory infections during the outbreak of novel coronavirus disease 2019 in Wuhan, China

We conducted two surveys to evaluate the health-seeking behaviors of individuals with acute respiratory infections (ARI) during the COVID-19 outbreak in Wuhan, China. Among 351 participants reporting ARI (10.3%, 351/3,411), 36.5% sought medical assistance. Children were more likely to seek medical assistance than other age groups (66.1% vs. 28.0%-35.1%).

Assessing the feasibility of sustaining a 'Zero-COVID' policy in China in the era of highly transmissible variants

We developed a spatially structured, fully stochastic, individual-based SARS-CoV-2 transmission model to evaluate the feasibility of sustaining SARS-CoV-2 local containment in mainland China considering currently dominant Omicron variants, Chinas current immunization level, and non-pharmaceutical interventions (NPIs). We also built a statistical model to estimate the overall disease burden under various hypothetical mitigation scenarios. We found that due to high transmissibility, neither Omicron BA.1 or BA.2 could be contained by Chinas pre-Omicron NPI strategies which were successful prior to the emergence of the Omicron variants. However, increased intervention intensity, such as enhanced population mobility restrictions and multi-round mass testing, could lead to containment success. We estimated that an acute Omicron epidemic wave in mainland China would result in significant number of deaths if China were to reopen under current vaccine coverage with no antiviral uptake, while increasing vaccination coverage and antiviral uptake could substantially reduce the disease burden. As Chinas current vaccination has yet to reach high coverage in older populations, NPIs remain essential tools to maintain low levels of infection while building up protective population immunity, ensuring a smooth transition out of the pandemic phase while minimizing the overall disease burden.

Direct and indirect mortality impacts of the COVID-19 pandemic in the US, March 2020-April 2021

Excess mortality studies provide crucial information regarding the health burden of pandemics and other large-scale events. Here, we used time series approaches to separate the direct contribution of SARS-CoV-2 infections on mortality from the indirect consequences of pandemic interventions and behavior changes in the United States. We estimated deaths occurring in excess of seasonal baselines stratified by state, age, week and cause (all causes, COVID-19 and respiratory diseases, Alzheimers disease, cancer, cerebrovascular disease, diabetes, heart disease, and external causes, including suicides, opioids, accidents) from March 1, 2020 to April 30, 2021. Our estimates of COVID-19 excess deaths were highly correlated with SARS-CoV-2 serology, lending support to our approach. Over the study period, we estimate an excess of 666,000 (95% Confidence Interval (CI) 556000, 774000) all-cause deaths, of which 90% could be attributed to the direct impact of SARS-CoV-2 infection, and 78% were reflected in official COVID-19 statistics. Mortality from all disease conditions rose during the pandemic, except for cancer. The largest direct impacts of the pandemic were seen in mortality from diabetes, Alzheimers, and heart diseases, and in age groups over 65 years. In contrast, the largest indirect consequences of the pandemic were seen in deaths from external causes, which increased by 45,300 (95% CI 30,800, 59,500) and were statistically linked to the intensity of non-pharmaceutical interventions. Within this category, increases were most pronounced in mortality from accidents and injuries, drug overdoses, and assaults and homicides, while the rate of death from suicides remained stable. Younger age groups suffered the brunt of these indirect effects. Overall, on a national scale, the largest consequences of the COVID-19 pandemic are attributable to the direct impact of SARS-CoV-2 infections; yet, the secondary impacts dominate among younger age groups, in periods of stricter interventions, and in mortality from external causes. Further research on the drivers of indirect mortality is warranted to optimize interventions in future pandemics.

Immune Heterogeneity and Epistasis Explain Punctuated Evolution of SARS-CoV-2

Identifying drivers of viral diversity is key to understanding the evolutionary as well as epidemiological dynamics of the COVID-19 pandemic. Using rich viral genomic data sets, we show that periods of steadily rising diversity have been punctuated by sudden, enormous increases followed by similarly abrupt collapses of diversity. We introduce a mechanistic model of saltational evolution with epistasis and demonstrate that these features parsimoniously account for the observed temporal dynamics of inter-genomic diversity. Our results provide support for recent proposals that saltational evolution may be a signature feature of SARS-CoV-2, allowing the pathogen to more readily evolve highly transmissible variants. These findings lend theoretical support to a heightened awareness of biological contexts where increased diversification may occur. They also underline the power of pathogen genomics and other surveillance streams in clarifying the phylodynamics of emerging and endemic infections. In public health terms, our results further underline the importance of equitable distribution of up-to-date vaccines.

Herd immunity induced by COVID-19 vaccination programs to suppress epidemics caused by SARS-CoV-2 wild type and variants in China

BackgroundTo allow a return to a pre-COVID-19 lifestyle, virtually every country has initiated a vaccination program to mitigate severe disease burden and control transmission. However, it remains to be seen whether herd immunity will be within reach of these programs. MethodsWe developed a data-driven model of SARS-CoV-2 transmission for China, a population with low prior immunity from natural infection. The model is calibrated considering COVID-19 natural history and the estimated transmissibility of the Delta variant. Three vaccination programs are tested, including the one currently enacted in China and model-based estimates of the herd immunity level are provided. ResultsWe found that it is unlike to reach herd immunity for the Delta variant given the relatively low efficacy of the vaccines used in China throughout 2021, the exclusion of underage individuals from the targeted population, and the lack of prior natural immunity. We estimate that, assuming a vaccine efficacy of 90% against the infection, vaccine-induced herd immunity would require a coverage of 93% or higher of the Chinese population. However, even when vaccine-induced herd immunity is not reached, we estimated that vaccination programs can reduce SARS-CoV-2 infections by 53-58% in case of an epidemic starts to unfold in the fall of 2021. ConclusionsEfforts should be taken to increase populations confidence and willingness to be vaccinated and to guarantee highly efficacious vaccines for a wider age range.

Global, regional, and national estimates of target population sizes for COVID-19 vaccination

BackgroundCOVID-19 vaccine prioritization and allocation strategies that maximize health benefit through efficient use of limited resources are urgently needed. We aimed to provide global, regional, and national estimates of target population sizes for COVID-19 vaccination to inform country-specific immunization strategies on a global scale. MethodsBased on a previous study of international allocation for pandemic COVID-19 vaccines, we classified the entire world population into eleven priority groups. Information on priority groups was derived from a multi-pronged search of official websites, media sources and academic journal articles. The sizes of different priority groups were projected for 194 countries globally. ResultsOverall, the size of COVID-19 vaccine recipient population varied markedly by goals of the vaccination program and geography. The general population aged <60 years without any underlying condition accounts for the majority of the total population (5.2 billion people, 68%), followed by 2.3 billion individuals at risk of severe disease, and 246.9 million essential workers which are critical to maintaining a functional society. Differences in the demographic structure, presence of underlying conditions, and number of essential workers led to highly variable estimates of target populations both at the WHO region and country level. In particular, Europe has the highest share of essential workers (6.8%) and the highest share of individuals with underlying conditions (37.8%), two priority categories to maintain societal functions and reduce severe burden. In contrast, Africa has the highest share of healthy adults, school-age individuals, and infants (77.6%), which are the key groups to target to reduce community transmission. InterpretationThe sizeable distribution of target groups on a country and regional bases underlines the importance of equitable and efficient vaccine prioritization and allocation globally. The direct and indirect benefits of COVID-19 vaccination should be balanced by considering local differences in demography and health.

Serological evidence of human infection with SARS-CoV-2: a systematic review and meta-analysis

BackgroundA rapidly increasing number of serological surveys for anti-SARS-CoV-2 antibodies have been reported worldwide. A synthesis of this large corpus of data is needed. PurposeTo evaluate the quality of serological studies and provide a global picture of seroprevalence across demographic and occupational groups, and to provide guidance for conducting better serosurveys. Data sourcesWe searched PubMed, Embase, Web of Science, and 4 pre-print servers for English-language papers published from December 1, 2019 to September 25, 2020. Study selectionSerological studies evaluating SARS-CoV-2 seroprevalence in humans. Data extractionTwo investigators independently extracted data from studies. Data SynthesisMost of 230 serological studies, representing tests in >1,400,000 individuals, identified were of low quality based on a standardized study quality scale. In the 51 studies of higher quality, high-risk healthcare workers had higher seroprevalence of 17.1% (95% CI: 9.9-24.4%), compared to low-risk healthcare workers and general population of 5.4% (0.7-10.1%) and 5.3% (4.2-6.4%). Seroprevalence varied hugely across WHO regions, with lowest seroprevalence of general population in Western Pacific region (1.7%, 0.0-5.0%). Generally, the young (<20 years) and the old ([≥]65 years) were less likely to be seropositive compared to middle-aged (20-64 years) populations. Seroprevalence correlated with clinical COVID-19 reports, with pooled average of 7.7 (range: 2.0 to 23.1) serologically-detected-infections per confirmed COVID-19 case. LimitationsSome heterogeneity cannot be well explained quantitatively. ConclusionsThe overall quality of seroprevalence studies examined was low. The relatively low seroprevalence among general populations suggest that in most settings, antibody-mediated herd immunity is far from being reached. Given the relatively narrow range of estimates of the ratio of serologically-detected infections to confirmed cases across different locales, reported case counts may help provide insights into the true proportion of the population infected. Primary Funding sourceNational Science Fund for Distinguished Young Scholars (PROSPERO: CRD42020198253).

Disease burden and clinical severity of the first pandemic wave of COVID-19 in Wuhan, China

The pandemic of novel coronavirus disease 2019 (COVID-19) began in Wuhan, China, where a first wave of intense community transmission was cut short by interventions. Using multiple data source, we estimated the disease burden and clinical severity of COVID-19 by age in Wuhan from December 1, 2019 to March 31, 2020. We adjusted estimates for sensitivity of laboratory assays and accounted for prospective community screenings and healthcare seeking behaviors. Rates of symptomatic cases, medical consultations, hospitalizations and deaths were estimated at 796 (95%CI: 703-977), 489 (472-509), 370 (358-384), and 36.2 (35.0-37.3) per 100,000 persons, respectively. The COVID-19 outbreak in Wuhan had higher burden than the 2009 influenza pandemic or seasonal influenza, and that clinical severity was similar to that of the 1918 influenza pandemic. Our comparison puts the COVID-19 pandemic into context and could be helpful to guide intervention strategies and preparedness for the potential resurgence of COVID-19.

Estimating the early death toll of COVID-19 in the United States

BackgroundEfforts to track the severity and public health impact of the novel coronavirus, COVID-19, in the US have been hampered by testing issues, reporting lags, and inconsistency between states. Evaluating unexplained increases in deaths attributed to broad outcomes, such as pneumonia and influenza (P&I) or all causes, can provide a more complete and consistent picture of the burden caused by COVID-19. MethodsWe evaluated increases in the occurrence of deaths due to P&I above a seasonal baseline (adjusted for influenza activity) or due to any cause across the United States in February and March 2020. These estimates are compared with reported deaths due to COVID-19 and with testing data. ResultsThere were notable increases in the rate of death due to P&I in February and March 2020. In a number of states, these deaths pre-dated increases in COVID-19 testing rates and were not counted in official records as related to COVID-19. There was substantial variability between states in the discrepancy between reported rates of death due to COVID-19 and the estimated burden of excess deaths due to P&I. The increase in all-cause deaths in New York and New Jersey is 1.5-3 times higher than the official tally of COVID-19 confirmed deaths or the estimated excess death due to P&I. ConclusionsExcess P&I deaths provide a conservative estimate of COVID-19 burden and indicate that COVID-19-related deaths are missed in locations with inadequate testing or intense pandemic activity. RESEARCH IN CONTEXTO_ST_ABSEvidence before this studyC_ST_ABSDeaths due to the novel coronavirus, COVID-19, have been increasing sharply in the United States since mid-March. However, efforts to track the severity and public health impact of COIVD-19 in the US have been hampered by testing issues, reporting lags, and inconsistency between states. As a result, the reported number of deaths likely represents an underestimate of the true burden. Added Value of this studyWe evaluate increases in deaths due to pneumonia across the United States and relate these increases to the number of reported deaths due to COVID-19 in different states and evaluate the trajectories of these increases in relation to the volume of testing and to indicators of COVID-19 morbidity. This provides a more complete picture of mortality due to COVID-19 in the US and demonstrates how delays in testing led to many coronavirus deaths not being counted in certain states. Implications of all the available evidenceThe number of deaths reported to be due to COVID-19 represents just a fraction of the deaths linked to the pandemic. Monitoring trends in deaths due to pneumonia and all-causes provides a more complete picture of the tool of the disease.

Age profile of susceptibility, mixing, and social distancing shape the dynamics of the novel coronavirus disease 2019 outbreak in China

Strict interventions were successful to control the novel coronavirus (COVID-19) outbreak in China. As transmission intensifies in other countries, the interplay between age, contact patterns, social distancing, susceptibility to infection and disease, and COVID-19 dynamics remains unclear. To answer these questions, we analyze contact surveys data for Wuhan and Shanghai before and during the outbreak and contact tracing information from Hunan Province. Daily contacts were reduced 7-9 fold during the COVID-19 social distancing period, with most interactions restricted to the household. Children 0-14 years were 59% (95% CI 7-82%) less susceptible than individuals 65 years and over. A transmission model calibrated against these data indicates that social distancing alone, as implemented in China during the outbreak, is sufficient to control COVID-19. While proactive school closures cannot interrupt transmission on their own, they reduce peak incidence by half and delay the epidemic. These findings can help guide global intervention policies.

The impact of COVID-19 non-pharmaceutical interventions on future respiratory syncytial virus transmission in South Africa

In response to the COVID-19 pandemic, the South African government employed various nonpharmaceutical interventions (NPIs) in order to reduce the spread of SARS-CoV-2. In addition to mitigating transmission of SARS-CoV-2, these public health measures have also functioned in slowing the spread of other endemic respiratory pathogens. Surveillance data from South Africa indicates low circulation of respiratory syncytial virus (RSV) throughout the 2020-2021 Southern Hemisphere winter seasons. Here we fit age-structured epidemiological models to national surveillance data to predict the 2022 RSV outbreak following two suppressed seasons. We project a 32% increase in the peak number of monthly hospitalizations among infants [≤] 2 years, with older infants (6-23 month olds) experiencing a larger portion of severe disease burden than typical. Our results suggest that hospital system readiness should be prepared for an intense RSV season in early 2022.

Inferring the differences in incubation-period and generation-interval distributions of the Delta and Omicron variants of SARS-CoV-2

Estimating the differences in the incubation-period, serial-interval, and generation-interval distributions of SARS-CoV-2 variants is critical to understanding their transmission and control. However, the impact of epidemic dynamics is often neglected in estimating the timing of infection and transmission--for example, when an epidemic is growing exponentially, a cohort of infected individuals who developed symptoms at the same time are more likely to have been infected recently. Here, we re-analyze incubation-period and serial-interval data describing transmissions of the Delta and Omicron variants from the Netherlands at the end of December 2021. Previous analysis of the same data set reported shorter mean observed incubation period (3.2 days vs 4.4 days) and serial interval (3.5 days vs 4.1 days) for the Omicron variant, but the number of infections caused by the Delta variant decreased during this period as the number of Omicron infections increased. When we account for growth-rate differences of two variants during the study period, we estimate similar mean incubation periods (3.8-4.5 days) for both variants but a shorter mean generation interval for the Omicron variant (3.0 days; 95% CI: 2.7-3.2 days) than for the Delta variant (3.8 days; 95% CI: 3.7-4.0 days). We further note that the differences in estimated generation intervals may be driven by the "network effect"--higher effective transmissibility of the Omicron variant can cause faster susceptible depletion among contact networks, which in turn prevents late transmission (therefore shortening realized generation intervals). Using up-to-date generation-interval distributions is critical to accurately estimating the reproduction advantage of the Omicron variant. SignificanceRecent studies suggest that individuals infected with the Omicron variant develop symptoms earlier (shorter incubation period) and transmit faster (shorter generation interval) than those infected with the Delta variant. However, these studies typically neglect population-level effects: when an epidemic is growing, a greater proportion of current cases were infected recently, biasing us toward observing faster transmission events. Accounting for this dynamical bias, we find that Omicron infections from the Netherlands at the end of December 2021 had similar incubation periods, but shorter generation intervals, compared to Delta infections from the same period. Shorter generation intervals of the Omicron variant might be due to its higher effective reproduction number, which can cause faster local susceptible depletion around the contact network.

Transmission heterogeneities, kinetics, and controllability of SARS-CoV-2

A long-standing question in infectious disease dynamics is the role of transmission heterogeneities, particularly those driven by demography, behavior and interventions. Here we characterize transmission risk between 1,178 SARS-CoV-2 infected individuals and their 15,648 close contacts based on detailed contact tracing data from Hunan, China. We find that 80% of secondary transmissions can be traced back to 14% of SARS-CoV-2 infections, indicating substantial transmission heterogeneities. Regression analysis suggests a marked gradient of transmission risk scales positively with the duration of exposure and the closeness of social interactions, after adjusted for demographic and clinical factors. Population-level physical distancing measures confine transmission to families and households; while case isolation and contact quarantine reduce transmission in all settings. Adjusted for interventions, the reconstructed infectiousness profile of a typical SARS-CoV-2 infection peaks just before symptom presentation, with ~50% of transmission occurring in the pre-symptomatic phase. Modelling results indicate that achieving SARS-CoV-2 control would require the synergistic efforts of case isolation, contact quarantine, and population-level physical distancing measures, owing to the particular transmission kinetics of this virus.

The effect of travel restrictions on the spread of the 2019 novel coronavirus (2019-nCoV) outbreak

Motivated by the rapid spread of a novel coronavirus (2019-nCoV) in Mainland China, we use a global metapopulation disease transmission model to project the impact of both domestic and international travel limitations on the national and international spread of the epidemic. The model is calibrated on the evidence of internationally imported cases before the implementation of the travel quarantine of Wuhan. By assuming a generation time of 7.5 days, the reproduction number is estimated to be 2.4 [90% CI 2.2-2.6]. The median estimate for number of cases before the travel ban implementation on January 23, 2020 is 58,956 [90% CI 40,759 - 87,471] in Wuhan and 3,491 [90% CI 1,924 - 7,360] in other locations in Mainland China. The model shows that as of January 23, most Chinese cities had already received a considerable number of infected cases, and the travel quarantine delays the overall epidemic progression by only 3 to 5 days. The travel quarantine has a more marked effect at the international scale, where we estimate the number of case importations to be reduced by 80% until the end of February. Modeling results also indicate that sustained 90% travel restrictions to and from Mainland China only modestly affect the epidemic trajectory unless combined with a 50% or higher reduction of transmission in the community.

Model-based evaluation of alternative reactive class closure strategies against COVID-19

There are contrasting results concerning the effect of reactive school closure on SARS-CoV-2 transmission. To shed light on this controversy, here we develop a data-driven computational model of SARS-CoV-2 transmission to investigate mechanistically the effect on COVID-19 outbreaks of school closure strategies based on syndromic surveillance and antigen screening of students. We found that by reactively closing classes based on syndromic surveillance, SARS-CoV-2 infections are reduced by no more than 13.1% (95%CI: 8.6%-20.2 %), due to the low probability of timely symptomatic case identification among the young population. We thus investigated an alternative triggering mechanism based on repeated screening of students using antigen tests. Should population-level social distancing measures unrelated to schools enable maintaining the reproduction number (R) at 1.3 or lower, an antigen-based screening strategy is estimated to fully prevent COVID-19 outbreaks in the general population. Depending on the contribution of schools to transmission, this strategy can either prevent COVID-19 outbreaks for R up to 1.9 or to at least greatly reduce outbreak size in very conservative scenarios about school contribution to transmission. Moving forward, the adoption of antigen-based screenings in schools could be instrumental to limit COVID-19 burden while vaccines continue to roll out through 2021, especially in light of possible continued emergence of SARS-CoV-2 variants.