Global patterns and drivers of influenza decline during the COVID-19 pandemic

Influenza circulation declined during the COVID-19 pandemic. The timing and extent of decline and its association with interventions against COVID-19 were described for some regions. Here, we provide a global analysis of the influenza decline between March 2020 and September 2021 and investigate its potential drivers. We computed influenza change by country and trimester relative to the 2014-2019 period using the number of samples in the FluNet database. We used random forests to determine important predictors in a list of 20 covariates including demography, weather, pandemic preparedness, COVID-19 incidence, and COVID-19 pandemic response. With a regression tree we then classified observations according to these predictors. We found that influenza circulation decreased globally, with COVID-19 incidence and pandemic preparedness being the two most important predictors of this decrease. The regression tree showed interpretable groups of observations by country and trimester: Europe and North America clustered together in spring 2020, with limited influenza decline despite strong COVID-19 restrictions; in the period afterwards countries of temperate regions, with high pandemic preparedness, high COVID-19 incidence and stringent social restrictions grouped together having strong influenza decline. Conversely, countries in the tropics, with altogether low pandemic preparedness, low reported COVID-19 incidence and low strength of COVID-19 response showed low influenza decline overall. A final group singled out four "zero-Covid" countries, with the lowest residual influenza levels. The spatiotemporal decline of influenza during the COVID-19 pandemic was global, yet heterogeneous. The sociodemographic context and stage of the COVID-19 pandemic showed non-linear associations with this decline. Zero-Covid countries maintained the lowest levels of reduction with strict border controls and despite close-to-normal social activity. These results suggest that the resurgence of influenza could take equally diverse paths. It also emphasises the importance of influenza reseeding in driving countries seasonal influenza epidemics.

Minimizing school disruption under high incidence conditions due to the Omicron variant in early 2022

As record cases due to the Omicron variant are currently registered in Europe, schools remain a vulnerable setting suffering large disruption. Extending previous modeling of SARS-CoV-2 transmission in schools in France, we estimate that at high incidence rates reactive screening protocols (as currently applied in France) require comparable test resources as weekly screening (as currently applied in some Swiss cantons), for considerably lower control. Our findings can be used to define incidence levels triggering school protocols and optimizing their cost-effectiveness.

Evaluating COVID-19 booster vaccination strategies in a partially vaccinated population: a modeling study.

BackgroundAs evidence shows that vaccine immunity to COVID-19 wanes with time and decreases due to variants, several countries are implementing booster vaccination campaigns. The objective of this study was to analyze the morbidity and mortality burdens of different primary and booster vaccination strategies against COVID-19, using France as a case study. MethodsWe used a deterministic, age-structured, compartmental model fitted to hospital admission data and validated against sero-prevalence data in France to analyze the impact of primary and booster vaccination strategies on morbidity and mortality assuming waning of immunity and increased virus transmissibility during winter. FindingsStrategies prioritizing primary vaccinations were systematically more effective than strategies prioritizing boosters. Regarding booster strategies targeting different age groups, their effectiveness varied with the levels of virus transmissibility, and according to the assumed loss of immunity for each age group. If the immunity reduction affects all age groups, people aged 30 to 49 years should be boosted in priority, even for low transmissibility levels. If the immunity reduction is restricted to people older than 65 years, boosting younger people becomes effective only above certain levels of transmissibility. InterpretationIncreasing the primary vaccination coverage should remain a priority to reduce morbidity and mortality due to COVID-19. If a plateau of primary vaccination has been reached, boosting immunity in younger age-groups could prevent more hospitalizations and deaths than boosting the immunity of older people, especially under conditions increasing SARS-CoV-2 transmissibility, or when facing new variants. FundingThe study was partially funded by the French national research agency through project SPHINX-17-CE36-0008-0. Research in contextO_ST_ABSEvidence before this studyC_ST_ABSMany countries have started booster vaccination programs against Covid-19, while others are still struggling to vaccinate their population. However, evidence is scarce regarding the optimal vaccination strategy to pursue in a rapidly evolving epidemiological context. A search of the literature on Nov 27 2021, using the terms (booster OR third dose) AND vaccine AND strategy AND (COVID* OR SARS*) AND (effect OR impact), returned 45 studies on PubMed and 1602 on medRxiv. However, very few studies assessed the public health impact of a booster strategy, and none of them compared different allocations strategies between primary and booster vaccinations, or investigated which age-group should be targeted for booster vaccination to maximize the public health impact of the strategy. Added value of this studyUsing an epidemiological model able to replicate the dynamic of the SARS-CoV-2 epidemic and able to account for the use of multiple vaccines and booster, we analyzed the effectiveness of different vaccination strategies, either based on prioritization of primary vaccination versus booster, or based on the age-group targeted for the booster vaccination. We evaluated the strategies in terms of hospitalizations and deaths avoided, in various epidemic scenarios during winter 2021-2022. To our knowledge, this is the first modeling study evaluating such strategies. We found that increasing primary vaccination of all adults is always more beneficial than giving a booster dose to elderly individuals, and that the age-group to target for a booster dose for optimal effectiveness depends on the level of transmission of the virus. As the level of SARS-CoV-2 transmission increases, boosting immunity in younger age-groups becomes the most effective strategy to decrease hospitalizations and deaths in the general population. Implications of all available evidenceCountries that have not reached the plateau of primary vaccination should focus their effort towards extending the overall primary vaccination coverage rather than boosting the immunity of fully vaccinated people, even for elderly individuals that may be facing waning immunity. When considering booster vaccination, the choice of which age groups to target should consider the level of virus transmissibility in the population. Considering the emergence of new, more transmissible SARS-CoV-2 variants, increasing the worldwide vaccination coverage should remain a priority.

Controlling SARS-CoV-2 in schools using repetitive testing strategies

SARS-CoV-2 remains a worldwide emergency. While vaccines have been approved and are widely administered, these are only available to adults and adolescents in Europe. Therefore, in order to mitigate the spread of more transmissible SARS-CoV-2 variants among children, the use of non-pharmaceutical interventions is still warranted. We investigate the impact of different testing strategies on the SARS-CoV-2 infection dynamics in a primary school environment, using an individual-based modelling approach. Specifically, we consider three testing strategies: 1) symptomatic isolation, where we test symptomatic individuals and isolate them when they test positive, 2) reactive screening, where a class is screened once one symptomatic individual was identified, and 3) repetitive screening, where the school in its entirety is screened on regular time intervals. Through this analysis, we demonstrate that repetitive testing strategies can significantly reduce the attack rate in schools, contrary to a reactive screening approach. Furthermore, we investigate the impact of these testing strategies on the average number of school days lost per child.

Self-testing and vaccination against COVID-19 to minimize school closure

Schools were closed extensively in 2020-2021 to counter COVID-19 spread, impacting students education and well-being. With highly contagious variants expanding in Europe, safe options to maintain schools open are urgently needed. We developed an agent-based model of SARS-CoV-2 transmission in school. We used empirical contact data in a primary and a secondary school, and data from pilot screenings in 683 schools during the 2021 spring Alpha wave in France. We fitted the model to observed school prevalence to estimate the school-specific reproductive number and performed a cost-benefit analysis examining different intervention protocols. We estimated RAlpha=1.40 (95%CI 1.35-1.45) in the primary and RAlpha=1.46 (1.41-1.51) in the secondary school during the wave, higher than Rt estimated from community surveillance. Considering the Delta variant and vaccination coverage in Europe, we estimated RDelta=1.66 (1.60-1.71) and RDelta=1.10 (1.06-1.14) in the two settings, respectively. Under these conditions, weekly screening with 75% adherence would reduce cases by 34% (95%CI 32-36%) in the primary and 36% (35-39%) in the secondary school compared to symptom-based testing. Insufficient adherence was recorded in pilot screening (median [≤]53%). Regular screening would also reduce student-days lost up to 80% compared to reactive closure. Moderate vaccination coverage in students would still benefit from regular screening for additional control (23% case reduction with 50% vaccinated children). COVID-19 pandemic will likely continue to pose a risk for school opening. Extending vaccination coverage in students, complemented by regular testing largely incentivizing adherence, are essential steps to keep schools open, especially under the threat of more contagious variants.

Ignoring spatial heterogeneity in drivers of SARS-CoV-2 transmission in the US will impede sustained elimination

To dissect the transmission dynamics of SARS-CoV-2 in the United States, we integrate parallel streams of high-resolution data on contact, mobility, seasonality, vaccination and seroprevalence within a metapopulation network. We find the COVID-19 pandemic in the US is characterized by a geographically localized mosaic of transmission along an urban-rural gradient, with many outbreaks sustained by between-county transmission. We detect a dynamic tension between the spatial scale of public health interventions and population susceptibility as pre-pandemic contact is resumed. Further, we identify regions rendered particularly at risk from invasion by variants of concern due to spatial connectivity. These findings emphasize the public health importance of accounting for the hierarchy of spatial scales in transmission and the heterogeneous impacts of mobility on the landscape of contagion risk.

Reactive vaccination of workplaces and schools against COVID-19

AbstractAs vaccination against COVID-19 stalls in some countries, increased accessibility and more adaptive approaches may be useful to keep the epidemic 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, individuals demography and behaviour and social distancing. At an equal number of doses reactive vaccination produces a higher reduction in cases compared with non-reactive strategies, in the majority of scenarios. However, at high initial vaccination coverage or low incidence, few people are found to vaccinate around cases, thus the reactive strategy may be less effective than non-reactive strategies with moderate/high vaccination pace. In case of flare-ups, reactive vaccination could hinder 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 deployment.

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

After one year of stop-and-go COVID-19 mitigation, some European countries still experience sustained viral circulation due to the B.1.1.7 variant. As the prospect of phasing out this stage through vaccination draws closer, it is critical to balance the efficacy of long-lasting interventions and their impact on the quality of life. Focusing on the current situation in France, we show that moderate interventions require a much longer time to achieve the same result as high intensity lockdowns, with the additional risk of deteriorating control as adherence wanes. Integrating intensity and duration of social distancing in a data-driven "distress" index, we show that shorter strict lockdowns are largely more performant than longer moderate lockdowns, for similar intermediate distress and infringement on individual freedom. 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.

Impact of national and regional lockdowns on COVID-19 epidemic waves: Application to the 2020 spring wave in France

Several countries have implemented lockdowns to control their COVID-19 epidemic. However, questions like "where" and "when" still require answers. We assessed the impact of national and regional lockdowns considering the French first epidemic wave of COVID-19 as a case study. In a regional lockdown scenario aimed at preventing intensive care units (ICU) saturation, almost all French regions would have had to implement a lockdown within 10 days and 96% of ICU capacities would have been used. For slowly growing epidemics, with a lower reproduction number, the expected delays between regional lockdowns increases. However, the public health costs associated with these delays tend to grow exponentially with time. In a quickly growing pandemic wave, defining the timing of lockdowns at a regional rather than national level delays by a few days the implementation of a nationwide lockdown but leads to substantially higher morbidity, mortality and stress on the healthcare system.

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

Facing B.1.1.7 variant, social distancing was strengthened in France in January 2021. Using a 2-strain mathematical model calibrated on genomic surveillance, we estimated that curfew measures allowed hospitalizations to plateau, by decreasing transmission of the historical strain 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 hospitalizations is expected, despite the foreseen increase in vaccination rhythm.

Underdetection of COVID-19 cases in France in the exit phase following lockdown

A novel testing policy was implemented in May in France to systematically screen potential COVID-19 infections and suppress local outbreaks while lifting lockdown restrictions. 20,736 virologically-confirmed cases were reported in mainland France from May 13, 2020 (week 20, end of lockdown) to June 28 (week 26). Accounting for missing data and the delay from symptom onset to confirmation test, this corresponds to 7,258 [95% CI 7,160-7,336] cases with symptom onset during this period, a likely underestimation of the real number. Using age-stratified transmission models parameterized to behavioral data and calibrated to regional hospital admissions, we estimated that 69,115 [58,072-77,449] COVID-19 symptomatic cases occurred, suggesting that 9 out of 10 cases with symptoms were not ascertained. Median detection rate increased from 7% [6-9]% to 31% [28-35]% over time, with regional estimates varying from 11% (Grand Est) to 78% (Normandy) by the end of June. Healthcare-seeking behavior in COVID-19 suspect cases remained low (31%) throughout the period. Model projections for the incidence of symptomatic cases (4.5 [3.9-5.0] per 100,000) were compatible with estimates integrating participatory and virological surveillance data, assuming all suspect cases consulted. Encouraging healthcare-seeking behavior and awareness in suspect cases is critical to improve detection. Substantially more aggressive and efficient testing with easier access is required to act as a pandemic-fighting tool. These elements should be considered in light of the currently observed resurgence of cases in France and other European countries.

Anatomy of digital contact tracing: role of age, transmission setting, adoption and case detection

The efficacy of digital contact tracing against COVID-19 epidemic is debated: smartphone penetration is limited in many countries, non-uniform across age groups, with low coverage among elderly, the most vulnerable to SARS-CoV-2. We developed an agent-based model to precise the impact of digital contact tracing and household isolation on COVID-19 transmission. The model, calibrated on French population, integrates demographic, contact-survey and epidemiological information to describe the risk factors for exposure and transmission of COVID-19. We explored realistic levels of case detection, app adoption, population immunity and transmissibility. Assuming a reproductive ratio R = 2.6 and 50% detection of clinical cases, a ~20% app adoption reduces peak incidence by ~35%. With R = 1.7, >30% app adoption lowers the epidemic to manageable levels. Higher coverage among adults, playing a central role in COVID-19 transmission, yields an indirect benefit for elderly. These results may inform the inclusion of digital contact tracing within a COVID-19 response plan.

Accommodating individual travel history, global mobility, and unsampled diversity in phylogeography: a SARS-CoV-2 case study.

Spatiotemporal bias in genome sequence sampling can severely confound phylogeographic inference based on discrete trait ancestral reconstruction. This has impeded our ability to accurately track the emergence and spread of SARS-CoV-2, the virus responsible for the COVID-19 pandemic. Despite the availability of unprecedented numbers of SARS-CoV-2 genomes on a global scale, evolutionary reconstructions are hindered by the slow accumulation of sequence divergence over its relatively short transmission history. When confronted with these issues, incorporating additional contextual data may critically inform phylodynamic reconstructions. Here, we present a new approach to integrate individual travel history data in Bayesian phylogeographic inference and apply it to the early spread of SARS-CoV-2, while also including global air transportation data. We demonstrate that including travel history data for each SARS-CoV-2 genome yields more realistic reconstructions of virus spread, particularly when travelers from undersampled locations are included to mitigate sampling bias. We further explore methods to ameliorate the impact of sampling bias by augmenting the phylogeographic analysis with lineages from undersampled locations in the analyses. Our reconstructions reinforce specific transmission hypotheses suggested by the inclusion of travel history data, but also suggest alternative routes of virus migration that are plausible within the epidemiological context but are not apparent with current sampling efforts. Although further research is needed to fully examine the performance of our travel-aware phylogeographic analyses with unsampled diversity and to further improve them, they represent multiple new avenues for directly addressing the colossal issue of sample bias in phylogeographic inference.

Population mobility reductions during COVID-19 epidemic in France under lockdown

On March 17, 2020, French authorities implemented a nationwide lockdown to respond to COVID-19 epidemic and curb the surge of patients requiring critical care, similarly to other countries. Evaluating the impact of lockdown on population mobility is essential to quantify achievable reductions and identify the factors driving the changes in social dynamics that affected viral diffusion. We used temporally resolved travel flows among 1,436 administrative areas of mainland France reconstructed from mobile phone trajectories. We measured mobility changes before and during lockdown at both local and country scales. Lockdown caused a 65% reduction in countrywide number of displacements, and was particularly effective in reducing work-related short-range mobility, especially during rush hours, and recreational trips. Geographical heterogeneities showed anomalous increases in long-range movements even before lockdown announcement that were tightly localized in space. During lockdown, mobility drops were unevenly distributed across regions. They were strongly associated with active population, workers employed in sectors highly impacted by lockdown, and number of hospitalizations per region, and moderately associated with socio-economic level of the region. Major cities largely shrank their pattern of connectivity, reducing it mainly to short-range commuting. Lockdown was effective in reducing population mobility across scales. Caution should be taken in the timing of policy announcements and implementation, as anomalous mobility followed policy announcements that may act as seeding events. On the other hand, risk aversion may be beneficial in further decreasing mobility in largely affected regions. Socio-economic and demographic constraints to the efficacy of restrictions were also identified. The unveiled links between geography, demography, and timing of the response to mobility restrictions may help design interventions that minimize invasiveness while contributing to the current epidemic response. FundingANR projects EVALCOVID-19 (ANR-20-COVI-0007) and DATAREDUX (ANR-19-CE46-0008-03); EU H2020 grants RECOVER (H2020-101003589) and MOOD (H2020-874850); REACTing COVID-19 modeling grant.

Expected impact of reopening schools after lockdown on COVID-19 epidemic in Ile-de-France

As countries in Europe implement strategies to control COVID-19 pandemic, different options are chosen regarding schools. Through a stochastic age-structured transmission model calibrated to the observed epidemic in Ile-de-France in the first wave, we explored scenarios of partial, progressive, or full school reopening. Given the uncertainty on childrens role, we found that reopening schools after lockdown may increase COVID-19 cases, yet protocols exist that maintain the epidemic controlled. Under a scenario with stable epidemic activity if schools were closed, reopening pre-schools and primary schools would lead 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 are required to maintain 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.

Expected impact of lockdown in Ile-de-France and possible exit strategies

BackgroundMore 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. MethodsWe use a stochastic age-structured transmission model integrating data on age profile and social contacts in Ile-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. ResultsWe 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. ConclusionsAs 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.

Assessing the interactions between COVID-19 and influenza in the United States

As healthcare capacities in the US and Europe reach their limits due to a surge in the COVID-19 pandemic, both regions enter the 2020-2021 influenza season. Southern hemisphere countries that had suppressed influenza seasons provide a hopeful example, but the lack of reduction in influenza in the 2019-2020 influenza season and heterogeneity in nonpharmaceutical and pharmaceutical interventions show that we cannot assume the same effect will occur globally. The US and Europe must promote the implementation and continuation of these measures in order to prevent additional burden to healthcare systems due to influenza.

Lessons learnt from 288 COVID-19 international cases: importations over time, effect of interventions, underdetection of imported cases

288 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 importations 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, combined with a slower growth from the other areas. We predicted a rebound of importations from South East Asia in the upcoming weeks. Time from travel to detection has considerably decreased since the first importation, however 6 cases out of 10 were estimated to go undetected. Countries outside China should be prepared for the possible emergence of several undetected clusters of chains of local transmissions.

Preparedness and vulnerability of African countries against introductions of 2019-nCoV

BackgroundThe novel coronavirus (2019-nCoV) epidemic has spread to 23 countries from China. Local cycles of transmission already occurred in 7 countries following case importation. No African country has reported cases yet. The management and control of 2019-nCoV introductions heavily relies on countrys health capacity. Here we evaluate the preparedness and vulnerability of African countries against their risk of importation of 2019-nCoV. MethodsWe used data on air travel volumes departing from airports in the infected provinces in China and directed to Africa to estimate the risk of introduction per country. We determined the countrys capacity to detect and respond to cases with two indicators: preparedness, using the WHO International Health Regulation Monitoring and Evaluation Framework; and vulnerability, with the Infectious Disease Vulnerability Index. Countries were clustered according to the Chinese regions contributing the most to their risk. FindingsCountries at the highest importation risk (Egypt, Algeria, Republic of South Africa) have moderate to high capacity to respond to outbreaks. Countries at moderate risk (Nigeria, Ethiopia, Sudan, Angola, Tanzania, Ghana, Kenya) have variable capacity and high vulnerability. Three clusters of countries are identified that share the same exposure to the risk originating from the provinces of Guangdong, Fujian, and Beijing, respectively. InterpretationSeveral countries in Africa are stepping up their preparedness to detect and cope with 2019-nCoV importations. Resources and intensified surveillance and capacity capacity should be urgently prioritized towards countries at moderate risk that may be ill-prepared to face the importation and to limit onward transmission. FundingThis study was partially supported by the ANR project DATAREDUX (ANR-19-CE46-0008-03) to VC; the EU grant MOOD (H2020-874850) to MG, CP, MK, PYB, VC.