Estimates of the reproduction ratio from epidemic surveillance may be biased in spatially structured populations (preprint)

An accurate and timely estimate of the reproduction ratio R of an infectious disease epidemic is crucial to make projections on its evolution and set up the appropriate public health response. Estimates of R routinely come from statistical inference on timelines of cases or their proxies like symptomatic cases, hospitalizatons, deaths. Here, however, we prove that these estimates of R may not be accurate if the population is made up of spatially distinct communities, as the interplay between space and mobility may hide the true epidemic evolution from surveillance data. This means that surveillance may underestimate R over long periods, to the point of mistaking a growing epidemic for a subsiding one, misinforming public health response. To overcome this, we propose a correction to be applied to surveillance data that removes this bias and ensures an accurate estimate of R across all epidemic phases. We use COVID-19 as case study; our results, however, apply to any epidemic where mobility is a driver of circulation, including major challenges of the next decades: respiratory infections (influenza, SARS-CoV-2, emerging pathogens), vector-borne diseases (arboviruses). Our findings will help set up public health response to these threats, by improving epidemic monitoring and surveillance.

The importance of increasing primary vaccinationsagainst COVID-19 in Europe (preprint)

In the European Union, mass vaccination against COVID-19 staved off the strict restrictions that had characterized early epidemic response. Now, vaccination campaigns are focusing on booster doses, and primary vaccinations have all but halted. Still, 52 million European adults are unvaccinated. We investigated if reaching the still unvaccinated population in future vaccination campaigns would substantially decrease the current burden of COVID-19, which is substantial. We focused on vaccination homophily, whereby those who are unvaccinated are mostly in contact with other unvaccinated, making COVID-19 circulation easier. We quantified vaccination homophily and estimated its impact on COVID-19 circulation. We used an online survey of 1,055,286 people from 22 European countries during early 2022. We computed vaccination homophily as the association between reported vaccination status and perceived vaccination uptake among one's own social contacts, using a case-referent design and a hierarchical logistic model. We used this information in an analysis of the COVID-19 reproduction ratio to determine the impact of vaccine homophily in transmission. Vaccination homophily was present and strong everywhere: the average odds ratio of being vaccinated for a 10-percentage-point increase in coverage among contacts was 1.66 (95% CI=(1.60, 1.72)). Homophily was positively associated with the strictness of COVID-19-related restrictions in 2020 (Pearson=0.49, p-value=0.03). In the countries studied, 12%-to-18% of the reproduction ratio would be attributable to vaccine homophily. Reducing vaccination homophily may curb the reproduction ratio substantially even to the point of preventing recurrent epidemic waves. In addition to boosting those already vaccinated, increasing primary vaccination should remain a high priority in future vaccination campaigns, to reduce vaccination homophily: this combined strategy may decrease COVID-19 burden.

Attitudes towards booster, testing and isolation, and their impact on COVID-19 response in winter 2022/2023 in France, Belgium, and Italy (preprint)

European countries are focusing on testing, isolation, and boosting strategies to counter the 2022/2023 winter surge due to Omicron subvariants. However, widespread pandemic fatigue and limited compliance potentially undermine mitigation efforts. To establish a baseline for interventions, we ran a multicountry survey to assess respondents' willingness to receive booster vaccination and comply with testing and isolation mandates. The vast majority of survey participants (N=4,594) was willing to adhere to testing (>91%) and rapid isolation (>88%) across the three countries. Pronounced differences emerged in the declared senior adherence to booster vaccination (73% in France, 94% in Belgium, 86% in Italy). Next, we inferred the vaccine-induced population immunity profile at the winter start from prior vaccination data, immunity waning, and declared booster uptake. Integrating survey and estimated immunity data in a branching process epidemic spreading model, we evaluated the effectiveness and costs of current protocols in France, Belgium, and Italy to manage the winter wave. Model results estimate that testing and isolation protocols would confer significant benefit in reducing transmission (17-24%) with declared adherence. Achieving a mitigating level similar tothe French protocol, the Belgian protocol would require 30% fewer tests and avoid the long isolation periods of the Italian protocol (average of 6 days vs. 11). A cost barrier to test would significantly decrease adherence in France and Belgium, undermining protocols' effectiveness. Simpler mandates for isolation may increase awareness and actual compliance, reducing testing costs, without compromising mitigation. High booster vaccination uptake remains key for the control of the winter wave.

Epidemic graph diagrams as analytics for epidemic control in the data-rich era (preprint)

COVID-19 highlighted how modeling is an integral part of pandemic response. But it also exposed fundamental methodological challenges. As high-resolution data on disease progression, epidemic surveillance, and host behavior are now available, can models turn them into accurate epidemic estimates and reliable public health recommendations? Take the epidemic threshold, which estimates the potential for an infection to spread in a host population, quantifying epidemic risk throughout epidemic emergence, mitigation, and control. While models increasingly integrated realistic host contacts, no parallel development occurred with matching detail in disease progression and interventions. This narrowed the use of the epidemic threshold to oversimplified disease and control descriptions. Here, we introduce the epidemic graph diagrams (EGDs), novel representations to compute the epidemic threshold directly from arbitrarily complex data on contacts, disease and control efforts. We define a grammar of diagram operations to decompose, compare, simplify models, extracting new theoretical understanding and improving computational efficiency. We test EGDs on two public health challenges, influenza and sexually-transmitted infections, to (i) explain the emergence of resistant influenza variants in the 2007-2008 season, and (ii) demonstrate that neglecting non-infectious prodromic stages biases the predicted epidemic risk, compromising control. EGDs are however general, and increase the performance of mathematical modeling to respond to present and future public health challenges.

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

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.

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

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.

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

On March 17, 2020, French authorities implemented a nationwide lockdown to respond to COVID-19 epidemic emergency and curb the surge of patients requiring critical care, similarly to other countries. Evaluating the impact of lockdown on population mobility is important to help characterize the changes in social dynamics that affected viral diffusion. Using travel flows reconstructed from mobile phone trajectories, we measured how lockdown altered mobility patterns 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 long-range trips. Anomalous increases in long-range movements, localized in both time and space, emerged even before lockdown announcement. 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, despite the persistence of some long-range trips. Our findings indicate that lockdown was very effective in reducing population mobility across scales. Caution should be taken in the timing of policy announcements and implementation. Individual response to policy announcements may generate unexpected anomalous behaviors increasing the risk of geographical diffusion. On the other hand, risk awareness may be beneficial in further decreasing mobility in largely affected regions. Our findings help predicting how and where restrictions will be the most effective in reducing the mobility and mixing of the population, thus aiding tuning recommendations in the upcoming weeks, when phasing out lockdown.

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

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 (preprint)

The 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 the public health capacity of a country. Here we evaluate the preparedness and vulnerability of African countries against their risk of importation of 2019-nCoV. We 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 countries 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. Findings: Countries 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. Interpretation: Several 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.