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BACKGROUND Most countries have enacted some restrictions to reduce social contacts to slow down disease transmission during the COVID-19 pandemic. For nearly two years, individuals likely also adopted new behaviours to avoid pathogen exposure based on personal circumstances. We aimed to understand the way in which different factors affect social contacts - a critical step to improving future pandemic responses. METHODS The analysis was based on repeated cross-sectional contact survey data collected in a standardized international study from 21 European countries between March 2020 and March 2022. We calculated the mean daily contacts reported using a clustered bootstrap by country and by settings (at home, at work, or in other settings). Where data were available, contact rates during the study period were compared with rates recorded prior to the pandemic. We fitted censored individual-level generalized additive mixed models to examine the effects of various factors on the number of social contacts. RESULTS The survey recorded 463,336 observations from 96,456 participants. In all countries where comparison data were available, contact rates over the previous two years were substantially lower than those seen prior to the pandemic (approximately from over 10 to

Additional file 3. Supplementary figures and additional results.

Additional file 1. Mixing data collection tool.

Additional file 2. Measurement of socioeconomic status, and food and economic security.

Background: The COVID-19 pandemic has significantly affected social contact patterns worldwide. Particularly during the first epidemic wave, because of the lack of specific treatment or vaccine, most countries around the world enforced non-pharmaceutical interventions. Italy was one of the first countries to be strongly affected by the pandemic, imposing in the first epidemic wave a hard lockdown. During the second wave, the country implemented color-coded, progressively restrictive tiers at the regional level according to weekly epidemiological risk assessments. Methods: We analyze longitudinal surveys of a representative sample of the Italian population by age, gender, and region of residence, collected during the second epidemic wave. After presenting a statistical description of the sample, we compare variations in contact patterns according to a color-coded tier of interventions experienced by the participants. In particular, we use contact matrices to quantify the reduction in the number of contacts by age group and contact settings, focusing on the adult population. We also compare the results with the pre-pandemic baseline assessing the impact of tiered restrictions on contacts. Finally, we compute the reproduction number to evaluate the impact of the restrictions on the spreading of the disease.Results: The comparison with the pre-pandemic baseline, shows a significant decrease in the number of contacts, independently from the age group or contact settings. Moreover, we show that the decrease in the number of contacts significantly depends on the strictness of the non-pharmaceutical interventions. For all levels of strictness considered, the reduction in social mixing results in a reproduction number smaller than one. In particular, the impact of the restriction on the number of contacts decreases with the severity of the interventions. Conclusions: We showed that the progressive restriction tiers implemented in Italy reduced overall the reproduction number, with stricter interventions associated with higher reductions. Readily collected contact data can promptly inform the implementation of mitigation measures at the national level in epidemic emergencies to come.

Background High incidence of cases and deaths due to coronavirus disease 2019 (COVID-19) have been reported in prisons worldwide. This study aimed to evaluate the impact of different COVID-19 vaccination strategies in epidemiologically semi-enclosed settings such as prisons, where staff interact regularly with those incarcerated and the wider community. Methods We used a metapopulation transmission-dynamic model of a local prison in England and Wales. Two-dose vaccination strategies included no vaccination, vaccination of all individuals who are incarcerated and/or staff, and an age-based approach. Outcomes were quantified in terms of COVID-19-related symptomatic cases, losses in quality-adjusted life-years (QALYs), and deaths. Results Compared to no vaccination, vaccinating all people living and working in prison reduced cases, QALY loss and deaths over a one-year period by 41%, 32% and 36% respectively. However, if vaccine introduction was delayed until the start of an outbreak, the impact was negligible. Vaccinating individuals who are incarcerated and staff over 50 years old averted one death for every 104 vaccination courses administered. All-staff-only strategies reduced cases by up to 5%. Increasing coverage from 30 to 90% among those who are incarcerated reduced cases by around 30 percentage points. Conclusions The impact of vaccination in prison settings was highly dependent on early and rapid vaccine delivery. If administered to both those living and working in prison prior to an outbreak occurring, vaccines could substantially reduce COVID-19-related morbidity and mortality in prison settings.

Additional file 2: Table S1. Survey 2 Respondent Descriptives. Table S2. Population age structure. Table S3. Percentage female and rural population. Table S4. Mean, median, standard deviation, interquartile range (IQR) contacts in both surveys. Table S5. Permutation test results by main respondent characteristic and survey wave. Table S6. Oxford Stringency Index for surveys 1 and 2. Table S7. Percentage of people who agreed to participate out of total people called.

Additional file 1: Additional details on specific analysis steps.

Additional file 1: Supplementary Figure S1. Oxford COVID-19 Government Response Tracker Stringency Index in 21 study countries. Supplementary Figure S2. Covid-19 vaccine policies on pregnancy in 18 CoMix countries between March and September 2021. Supplementary Table S1. Number of participants and number of completed surveys by country.

dentifying the potential for SARS-CoV-2 reinfection is crucial for understanding possible long-term epidemic dynamics. We analysed longitudinal PCR and serological testing data from a prospective cohort of 4,411 United States employees in 4 states between April 2020 and February 2021. We conducted a multivariable logistic regression investigating the association between baseline serological status and subsequent PCR test result in order to calculate an odds ratio for reinfection. We estimated an odds ratio for reinfection ranging from 0.14 (95% CI: 0.019 to 0.63) to 0.28 (95% CI: 0.05 to 1.1), implying that the presence of SARS-CoV-2 antibodies at baseline is associated with around 72% to 86% reduced odds of a subsequent PCR positive test based on our point estimates. This suggests that primary infection with SARS-CoV-2 provides protection against reinfection in the majority of individuals, at least over a 6-month time period. We also highlight 2 major sources of bias and uncertainty to be considered when estimating the relative risk of reinfection, confounders and the choice of baseline time point, and show how to account for both in reinfection analysis. The authors received funding from the following sources: EF was funded by the Medical Research Council (MR/N013638/1); AJK was supported by Wellcome Trust (206250/Z/17/Z) and National Institute for Health Research (NIHR200908); RL was funded by a Royal Society Dorothy Hodgkin Fellowship (https://royalsociety.org). EN was supported by the US Centers for Disease Control and Prevention (U01 U01GH002238). AM was supported by the Translational Research Institute for Space Health through NASA Cooperative Agreement (https://www.nasa.gov/hrp/tri; NNX16AO69A). GA was supported by the Massachusetts Consortium on Pathogen Readiness (https://masscpr.hms.harvard.edu/; MassCPR), the National Institutes of Health (3R37AI080289-11S1, R01AI146785, U19AI42790-01, U19AI135995-02, 1U01CA260476-01) and the Musk Foundation (http://www.muskfoundation.org/). The funders had no role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript. "Article signat per 18 autors/es: Emilie Finch ,Rachel Lowe,Stephanie Fischinger,Michael de St Aubin,Sameed M. Siddiqui,Diana Dayal,Michael A. Loesche,Justin Rhee,Samuel Beger,Yiyuan Hu,Matthew J. Gluck,Benjamin Mormann,Mohammad A. Hasdianda,Elon R. Musk,Galit Alter,Anil S. Menon ,Eric J. Nilles ,Adam J. Kucharski ,on behalf of the CMMID COVID-19 working group and the SpaceX COVID-19 Cohort Collaborative"

Background To contain the spread of COVID-19, a cordon sanitaire was put in place in Wuhan prior to the Lunar New Year, on 23 January 2020. We assess the efficacy of the cordon sanitaire to delay the introduction and onset of local transmission of COVID-19 in other major cities in mainland China. Methods We estimated the number of infected travellers from Wuhan to other major cities in mainland China from November 2019 to February 2020 using previously estimated COVID-19 prevalence in Wuhan and publicly available mobility data. We focused on Beijing, Chongqing, Hangzhou, and Shenzhen as four representative major cities to identify the potential independent contribution of the cordon sanitaire and holiday travel. To do this, we simulated outbreaks generated by infected arrivals in these destination cities using stochastic branching processes. We also modelled the effect of the cordon sanitaire in combination with reduced transmissibility scenarios to simulate the effect of local non-pharmaceutical interventions. Results We find that in the four cities, given the potentially high prevalence of COVID-19 in Wuhan between December 2019 and early January 2020, local transmission may have been seeded as early as 1–8 January 2020. By the time the cordon sanitaire was imposed, infections were likely in the thousands. The cordon sanitaire alone did not substantially affect the epidemic progression in these cities, although it may have had some effect in smaller cities. Reduced transmissibility resulted in a notable decrease in the incidence of infection in the four studied cities. Conclusions Our results indicate that sustained transmission was likely occurring several weeks prior to the implementation of the cordon sanitaire in four major cities of mainland China and that the observed decrease in incidence was likely attributable to other non-pharmaceutical, transmission-reducing interventions.

Emerging evidence suggests that contact tracing has had limited success in the UK in reducing the R number across the COVID-19 pandemic. We investigate potential pitfalls and areas for improvement by extending an existing branching process contact tracing model, adding diagnostic testing and refining parameter estimates. Our results demonstrate that reporting and adherence are the most important predictors of programme impact but tracing coverage and speed plus diagnostic sensitivity also play an important role. We conclude that well-implemented contact tracing could bring small but potentially important benefits to controlling and preventing outbreaks, providing up to a 15% reduction in R. We reaffirm that contact tracing is not currently appropriate as the sole control measure.

BACKGROUND: Schools were closed in England on 4 January 2021 as part of increased national restrictions to curb transmission of SARS-CoV-2. The UK government reopened schools on 8 March. Although there was evidence of lower individual-level transmission risk amongst children compared to adults, the combined effects of this with increased contact rates in school settings and the resulting impact on the overall transmission rate in the population were not clear. METHODS: We measured social contacts of > 5000 participants weekly from March 2020, including periods when schools were both open and closed, amongst other restrictions. We combined these data with estimates of the susceptibility and infectiousness of children compared with adults to estimate the impact of reopening schools on the reproduction number. RESULTS: Our analysis indicates that reopening all schools under the same measures as previous periods that combined lockdown with face-to-face schooling would be likely to increase the reproduction number substantially. Assuming a baseline of 0.8, we estimated a likely increase to between 1.0 and 1.5 with the reopening of all schools or to between 0.9 and 1.2 reopening primary or secondary schools alone. CONCLUSION: Our results suggest that reopening schools would likely halt the fall in cases observed between January and March 2021 and would risk a return to rising infections, but these estimates relied heavily on the latest estimates or reproduction number and the validity of the susceptibility and infectiousness profiles we used at the time of reopening.

The global spread of coronavirus disease 2019 (COVID-19) has emphasized the need for evidence-based strategies for the safe operation of schools during pandemics that balance infection risk with the society's responsibility of allowing children to attend school. Due to limited empirical data, existing analyses assessing school-based interventions in pandemic situations often impose strong assumptions, for example, on the relationship between class size and transmission risk, which could bias the estimated effect of interventions, such as split classes and staggered attendance. To fill this gap in school outbreak studies, we parameterized an individual-based model that accounts for heterogeneous contact rates within and between classes and grades to a multischool outbreak data of influenza. We then simulated school outbreaks of respiratory infectious diseases of ongoing threat (i.e., COVID-19) and potential threat (i.e., pandemic influenza) under a variety of interventions (changing class structures, symptom screening, regular testing, cohorting, and responsive class closures). Our results suggest that interventions changing class structures (e.g., reduced class sizes) may not be effective in reducing the risk of major school outbreaks upon introduction of a case and that other precautionary measures (e.g., screening and isolation) need to be employed. Class-level closures in response to detection of a case were also suggested to be effective in reducing the size of an outbreak., Proceedings of the National Academy of Sciences, 119(37), art. no. e2203019119; 2022

We assess the feasibility of reaching the herd immunity threshold against SARS-CoV-2 through vaccination, considering vaccine effectiveness (VE), transmissibility of the virus and the level of pre-existing immunity in populations, as well as their age structure. If highly transmissible variants of concern become dominant in areas with low levels of naturally-acquired immunity and/or in populations with large proportions of < 15 year-olds, control of infection without non-pharmaceutical interventions may only be possible with a VE ≥ 80%, and coverage extended to children. Initial reports of vaccine effectiveness against severe acute respiratory syndrome coronavirus 2 (SARSCoV-2), the virus responsible for coronavirus disease (COVID-19), have suggested a substantial reduction of the risk of infection [1]. Nevertheless, with the emergence of more transmissible variants such as B.1.1.7 [2], how large-scale immunisation programmes against SARS-CoV-2 will perform is currently unclear. This study assesses the potential of COVID-19 vaccination to generate herd immunity and takes into account vaccine effectiveness, naturally-acquired immunity and achievable vaccination coverage (depending on the population age structure), as well as two transmissibility scenarios ((i) with pre-B.1.1.7, and (ii) with exclusively B.1.1.7 variants).