Underdetection of cases of COVID-19 in France threatens epidemic control.

As countries in Europe gradually relaxed lockdown restrictions after the first wave, test-trace-isolate strategies became critical to maintain the incidence of coronavirus disease 2019 (COVID-19) at low levels1,2. Reviewing their shortcomings can provide elements to consider in light of the second wave that is currently underway in Europe. Here we estimate the rate of detection of symptomatic cases of COVID-19 in France after lockdown through the use of virological3 and participatory syndromic4 surveillance data coupled with mathematical transmission models calibrated to regional hospitalizations2. Our findings indicate that around 90,000 symptomatic infections, corresponding to 9 out 10 cases, were not ascertained by the surveillance system in the first 7 weeks after lockdown from 11 May to 28 June 2020, although the test positivity rate did not exceed the 5% recommendation of the World Health Organization (WHO)5. The median detection rate increased from 7% (95% confidence interval, 6-8%) to 38% (35-44%) over time, with large regional variations, owing to a strengthening of the system as well as a decrease in epidemic activity. According to participatory surveillance data, only 31% of individuals with COVID-19-like symptoms consulted a doctor in the study period. This suggests that large numbers of symptomatic cases of COVID-19 did not seek medical advice despite recommendations, as confirmed by serological studies6,7. Encouraging awareness and same-day healthcare-seeking behaviour of suspected cases of COVID-19 is critical to improve detection. However, the capacity of the system remained insufficient even at the low epidemic activity achieved after lockdown, and was predicted to deteriorate rapidly with increasing incidence of COVID-19 cases. Substantially more aggressive, targeted and efficient testing with easier access is required to act as a tool to control the COVID-19 pandemic. The testing strategy will be critical to enable partial lifting of the current restrictive measures in Europe and to avoid a third wave.

The impact of spatial connectivity on NPIs effectiveness.

BACKGROUND: France implemented a combination of non-pharmaceutical interventions (NPIs) to manage the COVID-19 pandemic between September 2020 and June 2021. These included a lockdown in the fall 2020 - the second since the start of the pandemic - to counteract the second wave, followed by a long period of nighttime curfew, and by a third lockdown in the spring 2021 against the Alpha wave. Interventions have so far been evaluated in isolation, neglecting the spatial connectivity between regions through mobility that may impact NPI effectiveness. METHODS: Focusing on September 2020-June 2021, we developed a regionally-based epidemic metapopulation model informed by observed mobility fluxes from daily mobile phone data and fitted the model to regional hospital admissions. The model integrated data on vaccination and variants spread. Scenarios were designed to assess the impact of the Alpha variant, characterized by increased transmissibility and risk of hospitalization, of the vaccination campaign and alternative policy decisions. RESULTS: The spatial model better captured the heterogeneity observed in the regional dynamics, compared to models neglecting inter-regional mobility. The third lockdown was similarly effective to the second lockdown after discounting for immunity, Alpha, and seasonality (51% vs 52% median regional reduction in the reproductive number R0, respectively). The 6pm nighttime curfew with bars and restaurants closed, implemented in January 2021, substantially reduced COVID-19 transmission. It initially led to 49% median regional reduction of R0, decreasing to 43% reduction by March 2021. In absence of vaccination, implemented interventions would have been insufficient against the Alpha wave. Counterfactual scenarios proposing a sequence of lockdowns in a stop-and-go fashion would have reduced hospitalizations and restriction days for low enough thresholds triggering and lifting restrictions. CONCLUSIONS: Spatial connectivity induced by mobility impacted the effectiveness of interventions especially in regions with higher mobility rates. Early evening curfew with gastronomy sector closed allowed authorities to delay the third wave. Stop-and-go lockdowns could have substantially lowered both healthcare and societal burdens if implemented early enough, compared to the observed application of lockdown-curfew-lockdown, but likely at the expense of several labor sectors. These findings contribute to characterize the effectiveness of implemented strategies and improve pandemic preparedness.

Impact of January 2021 curfew measures on SARS-CoV-2 B.1.1.7 circulation in France.

Following the spread of the SARS-CoV-2 B.1.1.7 variant, social distancing was strengthened in France in January 2021. Using a two-strain mathematical model calibrated on genomic surveillance, we estimated that curfew measures allowed hospitalisations to plateau by decreasing transmission of the historical strains while B.1.1.7 continued to grow. School holidays appear to have further slowed down progression in February. Without progressively strengthened social distancing, a rapid surge of hospitalisations is expected, despite the foreseen increase in vaccination rhythm.

Tracing and analysis of 288 early SARS-CoV-2 infections outside China: A modeling study.

BACKGROUND: In the early months of 2020, a novel coronavirus disease (COVID-19) spread rapidly from China across multiple countries worldwide. As of March 17, 2020, COVID-19 was officially declared a pandemic by the World Health Organization. We collected data on COVID-19 cases outside China during the early phase of the pandemic and used them to predict trends in importations and quantify the proportion of undetected imported cases. METHODS AND FINDINGS: Two hundred and eighty-eight cases have been confirmed out of China from January 3 to February 13, 2020. We collected and synthesized all available information on these cases from official sources and media. We analyzed importations that were successfully isolated and those leading to onward transmission. We modeled their number over time, in relation to the origin of travel (Hubei province, other Chinese provinces, other countries) and interventions. We characterized the importation timeline to assess the rapidity of isolation and epidemiologically linked clusters to estimate the rate of detection. We found a rapid exponential growth of importations from Hubei, corresponding to a doubling time of 2.8 days, combined with a slower growth from the other areas. We predicted a rebound of importations from South East Asia in the successive weeks. Time from travel to detection has considerably decreased since first importation, from 14.5 ± 5.5 days on January 5, 2020, to 6 ± 3.5 days on February 1, 2020. However, we estimated 36% of detection of imported cases. This study is restricted to the early phase of the pandemic, when China was the only large epicenter and foreign countries had not discovered extensive local transmission yet. Missing information in case history was accounted for through modeling and imputation. CONCLUSIONS: Our findings indicate that travel bans and containment strategies adopted in China were effective in reducing the exportation growth rate. However, the risk of importation was estimated to increase again from other sources in South East Asia. Surveillance and management of traveling cases represented a priority in the early phase of the epidemic. With the majority of imported cases going undetected (6 out of 10), countries experienced several undetected clusters of chains of local transmissions, fueling silent epidemics in the community. These findings become again critical to prevent second waves, now that countries have reduced their epidemic activity and progressively phase out lockdown.

Impact of lockdown on COVID-19 epidemic in Île-de-France and possible exit strategies.

BACKGROUND: More than half of the global population is under strict forms of social distancing. Estimating the expected impact of lockdown and exit strategies is critical to inform decision makers on the management of the COVID-19 health crisis. METHODS: We use a stochastic age-structured transmission model integrating data on age profile and social contacts in Île-de-France to (i) assess the epidemic in the region, (ii) evaluate the impact of lockdown, and (iii) propose possible exit strategies and estimate their effectiveness. The model is calibrated to hospital admission data before lockdown. Interventions are modeled by reconstructing the associated changes in the contact matrices and informed by mobility reductions during lockdown evaluated from mobile phone data. Different types and durations of social distancing are simulated, including progressive and targeted strategies, with large-scale testing. RESULTS: We estimate the reproductive number at 3.18 [3.09, 3.24] (95% confidence interval) prior to lockdown and at 0.68 [0.66, 0.69] during lockdown, thanks to an 81% reduction of the average number of contacts. Model predictions capture the disease dynamics during lockdown, showing the epidemic curve reaching ICU system capacity, largely strengthened during the emergency, and slowly decreasing. Results suggest that physical contacts outside households were largely avoided during lockdown. Lifting the lockdown with no exit strategy would lead to a second wave overwhelming the healthcare system, if conditions return to normal. Extensive case finding and isolation are required for social distancing strategies to gradually relax lockdown constraints. CONCLUSIONS: As France experiences the first wave of COVID-19 pandemic in lockdown, intensive forms of social distancing are required in the upcoming months due to the currently low population immunity. Extensive case finding and isolation would allow the partial release of the socio-economic pressure caused by extreme measures, while avoiding healthcare demand exceeding capacity. Response planning needs to urgently prioritize the logistics and capacity for these interventions.

SARS-CoV-2 infection prevalence and associated factors among primary healthcare workers in France after the third COVID-19 wave.

Data on the SARS-CoV-2 infection among primary health care workers (PHCWs) are scarce but essential to reflect on policy regarding prevention and control measures. We assessed the prevalence of PHCWs who have been infected by SARS-CoV-2 in comparison with modeling from the general population in metropolitan France, and associated factors. A cross-sectional study was conducted among general practitioners (GPs), pediatricians, dental and pharmacy workers in primary care between May and August 2021. Participants volunteered to provide a dried-blood spot for SARS-CoV-2 antibody assessment and completed a questionnaire. The primary outcome was defined as the detection of infection-induced antibodies (anti-nucleocapsid IgG, and for non-vaccinees: anti-Spike IgG and neutralizing antibodies) or previous self-reported infection (positive RT-qPCR or antigenic test, or positive ELISA test before vaccination). Estimates were adjusted using weights for representativeness and compared with prediction from the general population. Poisson regressions were used to quantify associated factors. The analysis included 1612 PHCWs. Weighted prevalences were: 31.7% (95% CI 27.5-36.0) for GPs, 28.7% (95% CI 24.4-33.0) for pediatricians, 25.2% (95% CI 20.6-31.0) for dentists, and 25.5% (95% CI 18.2-34.0) for pharmacists. Estimates were compatible with model predictions for the general population. PHCWs more likely to be infected were: GPs compared to pharmacist assistants (adjusted prevalence ratio [aPR] = 2.26; CI 95% 1.01-5.07), those living in Île-de-France (aPR = 1.53; CI 95% 1.14-2.05), South-East (aPR = 1.57; CI 95% 1.19-2.08), North-East (aPR = 1.81; CI 95% 1.38-2.37), and those having an unprotected contact with a COVID-19 case within the household (aPR = 1.48; CI 95% 1.22-1.80). Occupational factors were not associated with infection. In conclusion, the risk of SARS-CoV-2 exposure for PHCWs was more likely to have occurred in the community rather than at their workplace.

Teachers' Emotional Intelligence, Burnout, Work Engagement, and Self-Efficacy during COVID-19 Lockdown.

Teachers' psychological well-being is a crucial aspect that influences learning in a classroom climate. The aim of the study was to investigate teachers' emotional intelligence, burnout, work engagement, and self-efficacy in times of remote teaching during COVID-19 lockdown. A sample of 65 teachers (Mage = 50.49), from early childhood through lower secondary education, were recruited during a period of school closure to answer self-report questionnaires and other measures assessing study variables. Results showed that during the COVID-19 pandemic, teachers reported higher levels of burnout and lower levels of self-esteem due to multiple challenges related to remote teaching and the growing sense of insecurity regarding health safety in the school environment. However, the negative effects of COVID-19 on teachers' self-efficacy, work engagement, and burnout varied according to their own levels of emotional intelligence. These results demonstrate that emotional intelligence may support teachers in facing these challenges.

Modelling safe protocols for reopening schools during the COVID-19 pandemic in France.

As countries in Europe implement strategies to control the COVID-19 pandemic, different options are chosen regarding schools. Through a stochastic age-structured transmission model calibrated to the observed epidemic in Île-de-France in the first wave, we explored scenarios of partial, progressive, or full school reopening. Given the uncertainty on children's role, we found that reopening schools after lockdown may increase COVID-19 cases, yet protocols exist to keep the epidemic controlled. Under a scenario with stable epidemic activity if schools were closed, reopening pre-schools and primary schools would lead to up to 76% [67, 84]% occupation of ICU beds if no other school level reopened, or if middle and high schools reopened later. Immediately reopening all school levels may overwhelm the ICU system. Priority should be given to pre- and primary schools allowing younger children to resume learning and development, whereas full attendance in middle and high schools is not recommended for stable or increasing epidemic activity. Large-scale test and trace is required to keep the epidemic under control. Ex-post assessment shows that progressive reopening of schools, limited attendance, and strong adoption of preventive measures contributed to a decreasing epidemic after lifting the first lockdown.

Adherence and sustainability of interventions informing optimal control against the COVID-19 pandemic.

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.

In the spring of 2021, social distancing measures were strengthened in France to control the third wave of COVID-19 cases. While such measures are needed to slow the spread of the virus, they have a significant impact on the population's quality of life. Here, we use mathematical modelling based on hospital admission data and behavioural and health data (including data on mobility, indicators of social distancing, risk perception, and mental health) to evaluate optimal COVID-19 control strategies. We look at the effects of interventions, their sustainability and the population's adherence to them over time. We find that shorter, more stringent measures are likely to have similar effects on viral circulation and healthcare burden to long-lasting, less stringent but less sustainable interventions. Our findings have implications for the design and implementation of public health measures to control future COVID-19 waves.

Adherence and sustainability of interventions informing optimal control against the COVID-19 pandemic.

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.

Planning and adjusting the COVID-19 booster vaccination campaign to reduce disease burden.

As public health policies shifted in 2023 from emergency response to long-term COVID-19 disease management, immunization programs started to face the challenge of formulating routine booster campaigns in a still highly uncertain seasonal behavior of the COVID-19 epidemic. Mathematical models assessing past booster campaigns and integrating knowledge on waning of immunity can help better inform current and future vaccination programs. Focusing on the first booster campaign in the 2021/2022 winter in France, we used a multi-strain age-stratified transmission model to assess the effectiveness of the observed booster vaccination in controlling the succession of Delta, Omicron BA.1 and BA.2 waves. We explored counterfactual scenarios altering the eligibility criteria and inter-dose delay. Our study showed that the success of the immunization program in curtailing the Omicron BA.1 and BA.2 waves was largely dependent on the inclusion of adults among the eligible groups, and was highly sensitive to the inter-dose delay, which was changed over time. Shortening or prolonging this delay, even by only one month, would have required substantial social distancing interventions to curtail the hospitalization peak. Also, the time window for adjusting the delay was very short. Our findings highlight the importance of readiness and adaptation in the formulation of routine booster campaign in the current level of epidemiological uncertainty.