Paolo Bosetti

Background: The 2022 global mpox outbreak was linked to clade IIb viruses that previously circulated in Nigeria. Genomic evidence suggests that, in Nigeria, sustained human-to-human transmission may have begun as early as 2016. Methods: Using a stochastic branching process model, we investigated the conditions under which mpox could have persisted at low levels in Nigeria between 2016 and April 2022 without triggering a clearly recognized outbreak and quantified the potential hidden burden of infection and international exportation. Results: We found that when R is close to 1 and secondary infections show low variability (low heterogeneity, i.e. no superspreading), sustained but slow transmission can persist with non-negligible probability. Under our baseline modelling assumptions (R = 1.0, Poisson offspring distribution), 9% of simulations resulted in cryptic epidemics that lasted throughout the study period. Conditional on a trajectory being classified as cryptic under this scenario, the average epidemic size was 8500 infections (95% prediction interval: 2900–17 000) per cryptic epidemic, compared with 241 confirmed cases reported. This implies substantial under-ascertainment with a detection rate of 2.8% (95% prediction interval: 1.4–8.3%). Estimated exportations to Europe and North America were consistent with the small number of documented travel-associated cases before 2022. Conclusions: These findings support the plausibility of prolonged, low-level mpox transmission in Nigeria prior to the recognized global outbreak.

Accurately capturing time-varying human behavior remains a major challenge for real-time epidemic modeling and response. During the COVID-19 pandemic, synthetic contact matrices derived from mobility and behavioral data emerged as a scalable alternative to empirical contact surveys, yet their comparative performance remained unclear. Here, we systematically evaluate synthetic and empirical age-stratified contact matrices in France from March 2020 to May 2022, comparing contact patterns and their ability to reproduce observed epidemic dynamics. While both sources captured similar temporal trends in contacts, empirical matrices recorded 3.4 times more contacts for individuals under 19 than synthetic matrices during school-open periods. The model parameterized with synthetic matrices provided the best fit to hospital admissions and best captured hospitalization patterns for adolescents, adults, and seniors, whereas deviations remained for children across both models. Neither matrix allowed models to fully reproduce serological trends in children, highlighting the challenges both approaches face in capturing their disease-relevant contacts. The weekly update of synthetic matrices enabled smoother reconstructions of hospitalization trends during transitional phases, while empirical matrices required strong assumptions between survey waves. These findings support synthetic matrices as a reliable, flexible, cost-effective operational tool for real-time epidemic modeling, and highlight the need for routine collection of age-stratified mobility data to improve pandemic response.

Accurately capturing time-varying human behavior remains a major challenge for real-time epidemic modeling and response. During the COVID-19 pandemic, synthetic contact matrices derived from mobility and behavioral data emerged as a scalable alternative to empirical contact surveys, yet their comparative performance remained unclear. Here, we systematically evaluate synthetic and empirical age-stratified contact matrices in France from March 2020 to May 2022, comparing contact patterns and their ability to reproduce observed epidemic dynamics. While both sources captured similar temporal trends in contacts, empirical matrices recorded 3.4 times more contacts for individuals under 19 than synthetic matrices during school-open periods. The model parameterized with synthetic matrices provided the best fit to hospital admissions and best captured hospitalization patterns for adolescents, adults, and seniors, whereas deviations remained for children across both models. Neither matrix allowed models to fully reproduce serological trends in children, highlighting the challenges both approaches face in capturing their disease-relevant contacts. The weekly update of synthetic matrices enabled smoother reconstructions of hospitalization trends during transitional phases, while empirical matrices required strong assumptions between survey waves. These findings support synthetic matrices as a reliable, flexible, cost-effective operational tool for real-time epidemic modeling, and highlight the need of routine collection of age-stratified mobility data to improve pandemic response.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants of concern (VOCs) now arise in the context of heterogeneous human connectivity and population immunity. Through a large-scale phylodynamic analysis of 115,622 Omicron BA.1 genomes, we identified >6,000 introductions of the antigenically distinct VOC into England and analyzed their local transmission and dispersal history. We find that six of the eight largest English Omicron lineages were already transmitting when Omicron was first reported in southern Africa (22 November 2021). Multiple datasets show that importation of Omicron continued despite subsequent restrictions on travel from southern Africa as a result of export from well-connected secondary locations. Initiation and dispersal of Omicron transmission lineages in England was a two-stage process that can be explained by models of the country’s human geography and hierarchical travel network. Our results enable a comparison of the processes that drive the invasion of Omicron and other VOCs across multiple spatial scales.

Significance: The recent increase in large-scale migration trends generates several concerns about public health in destination countries, especially in the presence of massive incoming human flows from countries with a disrupted healthcare system. Here, we analyze the flow of 3.5 M Syrian refugees toward Turkey to quantify the risk of measles outbreaks. Our results suggest that heterogeneity in immunity, population distribution, and human-mobility flows is mostly responsible for such a risk: In fact, adequate policies of social integration and vaccine campaigns provide the most effective strategies to reduce measles disease risks for both migrant and hosting populations.