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1.
Euro Surveill ; 27(6)2022 02.
Article in English | MEDLINE | ID: covidwho-1883862

ABSTRACT

IntroductionSARS-CoV-2, the virus that causes COVID-19, has spread rapidly worldwide. In January 2020, a surveillance system was implemented in France for early detection of cases and their contacts to help limit secondary transmissions.AimTo use contact-tracing data collected during the initial phase of the COVID-19 pandemic to better characterise SARS-CoV-2 transmission.MethodsWe analysed data collected during contact tracing and retrospective epidemiological investigations in France from 24 January to 30 March 2020. We assessed the secondary clinical attack rate and characterised the risk of a contact becoming a case. We described chains of transmission and estimated key parameters of spread.ResultsDuring the study period, 6,082 contacts of 735 confirmed cases were traced. The overall secondary clinical attack rate was 4.1% (95% confidence interval (CI): 3.6-4.6), increasing with age of index case and contact. Compared with co-workers/friends, family contacts were at higher risk of becoming cases (adjusted odds ratio (AOR): 2.1, 95% CI: 1.4-3.0) and nosocomial contacts were at lower risk (AOR: 0.3, 95% CI: 0.1-0.7). Of 328 infector/infectee pairs, 49% were family members. The distribution of secondary cases was highly over-dispersed: 80% of secondary cases were caused by 10% of cases. The mean serial interval was 5.1 days (interquartile range (IQR): 2-8 days) in contact tracing pairs, where late transmission events may be censored, and 6.8 (3-8) days in pairs investigated retrospectively.ConclusionThis study increases knowledge of SARS-CoV-2 transmission, including the importance of superspreading events during the onset of the pandemic.


Subject(s)
COVID-19 , Contact Tracing , Humans , Pandemics , Retrospective Studies , SARS-CoV-2
2.
EuropePMC; 2022.
Preprint in English | EuropePMC | ID: ppcovidwho-337634

ABSTRACT

Population-level immunity to SARS-CoV-2 is growing through vaccination as well as ongoing circulation. Given waning immunity and emergence of new variants, it is important to dynamically determine the risk of re-infection in the population. For estimating immune protection, neutralization titers are most informative, but these assays are difficult to conduct at a population level. Measurement of antibody levels can be implemented at high throughput, but has not been robustly validated as a correlate of protection. Here, we have developed a method that predicts neutralization and protection based on variant-specific antibody measurements to SARS-CoV-2 antigens. This approach allowed us to estimate population-immunity in a longitudinal cohort from France followed for up to 2 years. Participants with a single vaccination or immunity caused by infection only are especially vulnerable to COVID-19 or hospitalization due to SARS-CoV-2. While the median reduced risk to COVID-19 in participants with 3 vaccinations was 96%, the median reduced risk among participants with infection-acquired immunity only was 42%. The results presented here are consistent with data from vaccine-effectiveness studies indicating robustness of our approach. Our multiplex serological assay can be readily optimized and employed to study any new variant and provides a framework for development of an assay that would include protection estimates.

3.
Commun Med (Lond) ; 1: 57, 2021.
Article in English | MEDLINE | ID: covidwho-1860423

ABSTRACT

Background: After one year of stop-and-go COVID-19 mitigation, in the spring of 2021 European countries still experienced sustained viral circulation due to the Alpha variant. As the prospect of entering a new pandemic phase through vaccination was drawing closer, a key challenge remained on how to balance the efficacy of long-lasting interventions and their impact on the quality of life. Methods: Focusing on the third wave in France during spring 2021, we simulate intervention scenarios of varying intensity and duration, with potential waning of adherence over time, based on past mobility data and modeling estimates. We identify optimal strategies by balancing efficacy of interventions with a data-driven "distress" index, integrating intensity and duration of social distancing. Results: We show that moderate interventions would require a much longer time to achieve the same result as high intensity lockdowns, with the additional risk of deteriorating control as adherence wanes. Shorter strict lockdowns are largely more effective than longer moderate lockdowns, for similar intermediate distress and infringement on individual freedom. Conclusions: Our study shows that favoring milder interventions over more stringent short approaches on the basis of perceived acceptability could be detrimental in the long term, especially with waning adherence.

4.
Elife ; 112022 05 19.
Article in English | MEDLINE | ID: covidwho-1856226

ABSTRACT

Evaluating the characteristics of emerging SARS-CoV-2 variants of concern is essential to inform pandemic risk assessment. A variant may grow faster if it produces a larger number of secondary infections ("R advantage") or if the timing of secondary infections (generation time) is better. So far, assessments have largely focused on deriving the R advantage assuming the generation time was unchanged. Yet, knowledge of both is needed to anticipate the impact. Here, we develop an analytical framework to investigate the contribution of both the R advantage and generation time to the growth advantage of a variant. It is known that selection on a variant with larger R increases with levels of transmission in the community. We additionally show that variants conferring earlier transmission are more strongly favored when the historical strains have fast epidemic growth, while variants conferring later transmission are more strongly favored when historical strains have slow or negative growth. We develop these conceptual insights into a new statistical framework to infer both the R advantage and generation time of a variant. On simulated data, our framework correctly estimates both parameters when it covers time periods characterized by different epidemiological contexts. Applied to data for the Alpha and Delta variants in England and in Europe, we find that Alpha confers a+54% [95% CI, 45-63%] R advantage compared to previous strains, and Delta +140% [98-182%] compared to Alpha, and mean generation times are similar to historical strains for both variants. This work helps interpret variant frequency dynamics and will strengthen risk assessment for future variants of concern.


Mutations in genes of the SARS-CoV-2 virus have generated new variants of concern, like Alpha, Delta, and more recently Omicron. These strains contain genetic modifications that help the virus spread more easily as well as altering the severity of the illness it causes. This has led to rising numbers of infections, known as epidemic waves, in many parts of the world. Tracking new variants of concern is crucial to protecting the public. To do this, scientists monitor how many people one person with the virus can infect, also known as the number of secondary infections. They may also measure when in the course of the illness an individual may pass along the virus to others. Together, these metrics help determine how fast and large an outbreak caused by a new variant will grow. The more people the new variant infects and the quicker it spreads, the more likely it is to replace existing strains of the virus. So far, most studies have assumed that the growth rate of a new variant solely depends on the number of secondary infections, and the timing of secondary infections is often not considered. To address this, Blanquart et al. built a mathematical model that combines both these parameters to determine the growth rate of new viral strains. The model showed that variants which rapidly cause secondary infections have a larger growth advantage over existing strains when the virus is more easily transmitted between individuals and the epidemic spreads rapidly. But when there is less transmission and the epidemic is declining, variants that generate secondary infections after a longer time have an advantage. For example, when control measures like mask wearing or social distancing are in place, delayed secondary infections may be more advantageous. Blanquart et al. then applied their model to data from the Alpha and Delta variant outbreaks in the United Kingdom. They found that Alpha and Delta did not change the timing of secondary infections compared to previously circulating strains. But the Alpha variant had a 54% transmission advantage over previous strains and the Delta variant had a 140% transmission advantage over Alpha. Taken together, these findings suggest that the timing of secondary infections and transmission rates both play an important role in how quickly a virus spreads. The new mathematical model created by Blanquart et al. may help epidemiologists better predict the trajectory of new SARS-CoV-2 variants and determine how to best control their spread.


Subject(s)
COVID-19 , Coinfection , COVID-19/epidemiology , Humans , Pandemics , SARS-CoV-2/genetics
5.
Emerg Infect Dis ; 28(7): 1345-1354, 2022 07.
Article in English | MEDLINE | ID: covidwho-1847125

ABSTRACT

Outbreaks of SARS-CoV-2 infection frequently occur in hospitals. Preventing nosocomial infection requires insight into hospital transmission. However, estimates of the basic reproduction number (R0) in care facilities are lacking. Analyzing a closely monitored SARS-CoV-2 outbreak in a hospital in early 2020, we estimated the patient-to-patient transmission rate and R0. We developed a model for SARS-CoV-2 nosocomial transmission that accounts for stochastic effects and undetected infections and fit it to patient test results. The model formalizes changes in testing capacity over time, and accounts for evolving PCR sensitivity at different stages of infection. R0 estimates varied considerably across wards, ranging from 3 to 15 in different wards. During the outbreak, the hospital introduced a contact precautions policy. Our results strongly support a reduction in the hospital-level R0 after this policy was implemented, from 8.7 to 1.3, corresponding to a policy efficacy of 85% and demonstrating the effectiveness of nonpharmaceutical interventions.


Subject(s)
COVID-19 , Cross Infection , Basic Reproduction Number , COVID-19/epidemiology , COVID-19/prevention & control , Cross Infection/epidemiology , Cross Infection/prevention & control , Humans , Infection Control/methods , SARS-CoV-2
6.
Proc Natl Acad Sci U S A ; 119(18): e2103302119, 2022 05 03.
Article in English | MEDLINE | ID: covidwho-1815692

ABSTRACT

Short-term forecasting of the COVID-19 pandemic is required to facilitate the planning of COVID-19 health care demand in hospitals. Here, we evaluate the performance of 12 individual models and 19 predictors to anticipate French COVID-19-related health care needs from September 7, 2020, to March 6, 2021. We then build an ensemble model by combining the individual forecasts and retrospectively test this model from March 7, 2021, to July 6, 2021. We find that the inclusion of early predictors (epidemiological, mobility, and meteorological predictors) can halve the rms error for 14-d­ahead forecasts, with epidemiological and mobility predictors contributing the most to the improvement. On average, the ensemble model is the best or second-best model, depending on the evaluation metric. Our approach facilitates the comparison and benchmarking of competing models through their integration in a coherent analytical framework, ensuring that avenues for future improvements can be identified.


Subject(s)
COVID-19 , COVID-19/epidemiology , Delivery of Health Care , France/epidemiology , Health Services Needs and Demand , Humans , Pandemics/prevention & control , Retrospective Studies
7.
Anaesth Crit Care Pain Med ; 41(2): 101048, 2022 04.
Article in English | MEDLINE | ID: covidwho-1782349
8.
EuropePMC; 2022.
Preprint in English | EuropePMC | ID: ppcovidwho-332946

ABSTRACT

Several vaccines candidates are in development against Middle East respiratory syndrome–related coronavirus (MERS-CoV), which remains a major public health concern. Using individual-level data on the 2013-2014 Kingdom of Saudi Arabia epidemic, we employ counterfactual analysis on inferred transmission trees (“who-infected-whom”) to assess potential vaccine impact. We investigate the conditions under which prophylactic “proactive” campaigns would outperform “reactive” campaigns (i.e. vaccinating either before or in response to the next outbreak), focussing on healthcare workers. Spatial scale is crucial: if vaccinating healthcare workers in response to outbreaks at their hospital only, proactive campaigns perform better, unless efficacy has waned significantly. However, campaigns that react at regional or national level consistently outperform proactive campaigns. Measures targeting the animal reservoir reduce transmission linearly, albeit with wide uncertainty. Substantial reduction of MERS-CoV morbidity and mortality is possible when vaccinating healthcare workers, underlining the need for at-risk countries to stockpile vaccines when available.

9.
Lancet Infect Dis ; 22(7): 977-989, 2022 Jul.
Article in English | MEDLINE | ID: covidwho-1768664

ABSTRACT

BACKGROUND: Schools were closed extensively in 2020-21 to counter SARS-CoV-2 spread, impacting students' education and wellbeing. With highly contagious variants expanding in Europe, safe options to maintain schools open are urgently needed. By estimating school-specific transmissibility, our study evaluates costs and benefits of different protocols for SARS-CoV-2 control at school. METHODS: We developed an agent-based model of SARS-CoV-2 transmission in schools. We used empirical contact data in a primary and a secondary school and data from pilot screenings in 683 schools during the alpha variant (B.1.1.7) wave in March-June, 2021, in France. We fitted the model to observed school prevalence to estimate the school-specific effective reproductive number for the alpha (Ralpha) and delta (B.1.617.2; Rdelta) variants and performed a cost-benefit analysis examining different intervention protocols. FINDINGS: We estimated Ralpha to be 1·40 (95% CI 1·35-1·45) in the primary school and 1·46 (1·41-1·51) in the secondary school during the spring wave, higher than the time-varying reproductive number estimated from community surveillance. Considering the delta variant and vaccination coverage in Europe as of mid-September, 2021, we estimated Rdelta to be 1·66 (1·60-1·71) in primary schools and 1·10 (1·06-1·14) in secondary schools. Under these conditions, weekly testing of 75% of unvaccinated students (PCR tests on saliva samples in primary schools and lateral flow tests in secondary schools), in addition to symptom-based testing, would reduce cases by 34% (95% CI 32-36) in primary schools and 36% (35-39) in secondary schools compared with symptom-based testing alone. Insufficient adherence was recorded in pilot screening (median ≤53%). Regular testing would also reduce student-days lost up to 80% compared with reactive class closures. Moderate vaccination coverage in students would still benefit from regular testing for additional control-ie, weekly testing 75% of unvaccinated students would reduce cases compared with symptom-based testing only, by 23% in primary schools when 50% of children are vaccinated. INTERPRETATION: The COVID-19 pandemic will probably continue to pose a risk to the safe and normal functioning of schools. Extending vaccination coverage in students, complemented by regular testing with good adherence, are essential steps to keep schools open when highly transmissible variants are circulating. FUNDING: EU Framework Programme for Research and Innovation Horizon 2020, Horizon Europe Framework Programme, Agence Nationale de la Recherche, ANRS-Maladies Infectieuses Émergentes.


Subject(s)
COVID-19 , SARS-CoV-2 , COVID-19/epidemiology , COVID-19/prevention & control , Child , Humans , Pandemics/prevention & control , SARS-CoV-2/genetics , Schools , Vaccination
10.
EuropePMC; 2022.
Preprint in English | EuropePMC | ID: ppcovidwho-330712

ABSTRACT

Transmission heterogeneity is a notable feature of the severe acute respiratory syndrome (SARS) and coronavirus disease 2019 (COVID-19) epidemics, though previous efforts to estimate how heterogeneity changes over time are limited. Using contact tracing data, we compared the epidemiology of SARS and COVID-19 infection in Hong Kong in 2003 and 2020-21 and estimated time-varying transmission heterogeneity ( k t ) by fitting negative binomial models to offspring distributions generated across variable observation windows. k t fluctuated over time for both COVID-19 and SARS on a continuous scale though SARS exhibited significantly greater (p < 0.001) heterogeneity compared to COVID-19 overall and in-time. For COVID-19, k t declined over time and was significantly associated with increasingly stringent non-pharmaceutical interventions though similar evidence for SARS was inconclusive. Underdetection of sporadic COVID-19 cases led to a moderate overestimation of k t , indicating COVID-19 heterogeneity of could be greater than observed. Time-varying or real-time estimates of transmission heterogeneity could become a critical indicator for epidemic intelligence in the future.

11.
Nat Commun ; 13(1): 1414, 2022 03 17.
Article in English | MEDLINE | ID: covidwho-1751713

ABSTRACT

With vaccination against COVID-19 stalled in some countries, increasing vaccine accessibility and distribution could help keep transmission under control. Here, we study the impact of reactive vaccination targeting schools and workplaces where cases are detected, with an agent-based model accounting for COVID-19 natural history, vaccine characteristics, demographics, behavioural changes and social distancing. In most scenarios, reactive vaccination leads to a higher reduction in cases compared with non-reactive strategies using the same number of doses. The reactive strategy could however be less effective than a moderate/high pace mass vaccination program if initial vaccination coverage is high or disease incidence is low, because few people would be vaccinated around each case. In case of flare-ups, reactive vaccination could better mitigate spread if it is implemented quickly, is supported by enhanced test-trace-isolate and triggers an increased vaccine uptake. These results provide key information to plan an adaptive vaccination rollout.


Subject(s)
COVID-19 , Workplace , COVID-19/prevention & control , Humans , Schools , Systems Analysis , Vaccination
12.
Am J Epidemiol ; 191(7): 1224-1234, 2022 Jun 27.
Article in English | MEDLINE | ID: covidwho-1722205

ABSTRACT

Several studies have characterized the effectiveness of vaccines against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections. However, estimates of their impact on transmissibility remain limited. Here, we evaluated the impact of isolation and vaccination (7 days after the second dose) on SARS-CoV-2 transmission within Israeli households. From December 2020 to April 2021, confirmed cases were identified among health-care workers of the Sheba Medical Centre and their family members. Recruited households were followed up with repeated PCR for at least 10 days after case confirmation. Data were analyzed using a data augmentation Bayesian framework. A total of 210 households with 215 index cases were enrolled; 269 out of 667 (40%) susceptible household contacts developed a SARS-CoV-2 infection. Of those, 170 (63%) developed symptoms. Compared with unvaccinated and unisolated adult/teenager (aged >12 years) contacts, vaccination reduced the risk of infection among unisolated adult/teenager contacts (relative risk (RR) = 0.21, 95% credible interval (CrI): 0.08, 0.44), and isolation reduced the risk of infection among unvaccinated adult/teenager (RR = 0.12, 95% CrI: 0.06, 0.21) and child contacts (RR = 0.17, 95% CrI: 0.08, 0.32). Infectivity was reduced in vaccinated cases (RR = 0.25, 95% CrI: 0.06, 0.77). Within households, vaccination reduces both the risk of infection and of transmission if infected. When contacts were unvaccinated, isolation also led to important reductions in the risk of transmission.

13.
Anaesthesia, critical care & pain medicine ; 2022.
Article in English | EuropePMC | ID: covidwho-1710265
14.
EuropePMC; 2021.
Preprint in English | EuropePMC | ID: ppcovidwho-322958

ABSTRACT

Background: The methods to ascertain cases of an emerging infectious disease are typically biased toward cases with more severe disease, which can affect estimates of the average infection-severity profile. We examine the potential for using data from secondary cases, identified through transmission studies or contact tracing of index cases, to characterize disease severity.Methods: We extracted information on reported symptoms, disease severity and fatality risk among index cases and secondary cases, from previous reviews of contact tracing studies for pandemic influenza A(H1N1)pdm09, Middle East Respiratory Syndrome (MERS) and Coronavirus Disease 2019 (COVID-19). We compared severity profiles between index cases and secondary cases and inferred the potential for ascertainment bias in confirmed cases.Findings. Overall, index cases had more severe illness on average than secondary cases, for each disease. For COVID-19 and influenza A(H1N1)pdm09, the proportions of index cases with fever and cough were 1.3-fold to 1.6-fold higher than for secondary cases. For COVID-19, the proportion of index cases with asymptomatic infection, severe/critical illness and death were 54% lower, 39% higher and 82% higher than for secondary cases, respectively. For MERS, the fatality risk among index cases was 73% higher than for secondary cases. For COVID-19 in China, we estimated that 68% (95% Credible interval (CrI): 43%, 85%) and 56% (95% CrI: 42%, 68%) of index cases were missed due to ascertainment bias, for Guangzhou and Wuhan, respectively.Interpretation: Information on disease severity in secondary cases should be less susceptible to ascertainment bias and could inform estimates of disease severity and the proportion of missed index cases.Funding: This project was supported by the Health and Medical Research Fund, Food andHealth Bureau, Government of the Hong Kong Special Administrative Region (grant no. COVID190118) and the Collaborative Research Fund (Project No. C7123-20G) of the Research Grants Council of the Hong Kong SAR Government.BJC is supported by the AIR@innoHK program of the Innovation and Technology Commission of the Hong Kong SAR Government.Declaration of Interest: BJC reports honoraria from Sanofi Pasteur, GSK, Moderna and Roche. Theauthors report no other potential conflicts of interest.

15.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-304776

ABSTRACT

Superspreading events have characterised previous epidemics of severe acute respiratory syndrome coronavirus (SARS-CoV) and Middle East respiratory syndrome coronavirus (MERS-CoV) infections. Using contact tracing data, we identified and characterized SARS-CoV-2 clusters in Hong Kong. Given a superspreading threshold of 6-8 secondary cases, we identified 5-7 probable superspreading events and evidence of substantial overdispersion in transmissibility, and estimated that 20% of cases were responsible for 80% of local transmission. Among terminal cluster cases, 27% (45/167) ended in quarantine. Social exposures produced a greater number of secondary cases compared to family or work exposures (p<0.001) while delays between symptom onset and isolation did not reliably predict the number of individual secondary cases or resulting cluster sizes. Public health authorities should focus on rapid tracing and quarantine of contacts, along with physical distancing to prevent superspreading events in high-risk social environments.

17.
Euro Surveill ; 26(48)2021 12.
Article in English | MEDLINE | ID: covidwho-1613503

ABSTRACT

BackgroundMany countries implemented national lockdowns to contain the rapid spread of SARS-CoV-2 and avoid overburdening healthcare capacity.AimWe aimed to quantify how the French lockdown impacted population mixing, contact patterns and behaviours.MethodsWe conducted an online survey using convenience sampling and collected information from participants aged 18 years and older between 10 April and 28 April 2020.ResultAmong the 42,036 survey participants, 72% normally worked outside their home, and of these, 68% changed to telework during lockdown and 17% reported being unemployed during lockdown. A decrease in public transport use was reported from 37% to 2%. Participants reported increased frequency of hand washing and changes in greeting behaviour. Wearing masks in public was generally limited. A total of 138,934 contacts were reported, with an average of 3.3 contacts per individual per day; 1.7 in the participants aged 65 years and older compared with 3.6 for younger age groups. This represented a 70% reduction compared with previous surveys, consistent with SARS-CoV2 transmission reduction measured during the lockdown. For those who maintained a professional activity outside home, the frequency of contacts at work dropped by 79%.ConclusionThe lockdown affected the population's behaviour, work, risk perception and contact patterns. The frequency and heterogeneity of contacts, both of which are critical factors in determining how viruses spread, were affected. Such surveys are essential to evaluate the impact of lockdowns more accurately and anticipate epidemic dynamics in these conditions.


Subject(s)
COVID-19 , RNA, Viral , Age Factors , Communicable Disease Control , France/epidemiology , Humans , SARS-CoV-2
18.
Euro Surveill ; 27(1)2022 01.
Article in English | MEDLINE | ID: covidwho-1613513

ABSTRACT

Europe has experienced a large COVID-19 wave caused by the Delta variant in winter 2021/22. Using mathematical models applied to Metropolitan France, we find that boosters administered to ≥ 65, ≥ 50 or ≥ 18 year-olds may reduce the hospitalisation peak by 25%, 36% and 43% respectively, with a delay of 5 months between second and third dose. A 10% reduction in transmission rates might further reduce it by 41%, indicating that even small increases in protective behaviours may be critical to mitigate the wave.


Subject(s)
COVID-19 Vaccines/administration & dosage , COVID-19 , Immunization, Secondary , COVID-19/prevention & control , France/epidemiology , Humans , SARS-CoV-2 , Seasons , Vaccination
19.
EuropePMC; 2021.
Preprint in English | EuropePMC | ID: ppcovidwho-296557

ABSTRACT

Evaluating the characteristics of emerging SARS-CoV-2 variants of concern is essential to inform pandemic risk assessment. A variant may grow faster if it produces a larger number of secondary infections (transmissibility advantage) or if the timing of secondary infections (generation time) is better. So far, assessments have largely focused on deriving the transmissibility advantage assuming the generation time was unchanged. Yet, knowledge of both is needed to anticipate impact. Here we develop an analytical framework to investigate the contribution of both the transmissibility advantage and generation time to the growth advantage of a variant. We find that the growth advantage depends on the epidemiological context (level of epidemic control). More specifically, variants conferring earlier transmission are more strongly favoured when the historical strains have fast epidemic growth, while variants conferring later transmission are more strongly favoured when historical strains have slow or negative growth. We develop these conceptual insights into a statistical framework to infer both the transmissibility advantage and generation time of a variant. On simulated data, our framework correctly estimates both parameters when it covers time periods characterized by different epidemiological contexts. Applied to data for the Alpha and Delta variants in England and in Europe, we find that Alpha confers a +54% [95% CI, 45-63%] transmissibility advantage compared to previous strains, and Delta +140% [98-182%] compared to Alpha, and mean generation times are similar to historical strains for both variants. This work helps interpret variant frequency and will strengthen risk assessment for future variants of concern.

20.
Nat Commun ; 12(1): 6895, 2021 11 25.
Article in English | MEDLINE | ID: covidwho-1537311

ABSTRACT

The shielding of older individuals has been proposed to limit COVID-19 hospitalizations while relaxing general social distancing in the absence of vaccines. Evaluating such approaches requires a deep understanding of transmission dynamics across ages. Here, we use detailed age-specific case and hospitalization data to model the rebound in the French epidemic in summer 2020, characterize age-specific transmission dynamics and critically evaluate different age-targeted intervention measures in the absence of vaccines. We find that while the rebound started in young adults, it reached individuals aged ≥80 y.o. after 4 weeks, despite substantial contact reductions, indicating substantial transmission flows across ages. We derive the contribution of each age group to transmission. While shielding older individuals reduces mortality, it is insufficient to allow major relaxations of social distancing. When the epidemic remains manageable (R close to 1), targeting those most contributing to transmission is better than shielding at-risk individuals. Pandemic control requires an effort from all age groups.


Subject(s)
COVID-19/prevention & control , COVID-19/transmission , SARS-CoV-2 , Adolescent , Adult , Age Factors , Aged , Aged, 80 and over , COVID-19/epidemiology , COVID-19 Vaccines , Child , Child, Preschool , Computer Simulation , Female , France/epidemiology , Hospitalization/statistics & numerical data , Humans , Infant , Infant, Newborn , Male , Middle Aged , Pandemics/prevention & control , Physical Distancing , Young Adult
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