Global comparison of influenza A and B epidemiology identifies consistent geographic and socio-demographic predictors

Seasonal influenza outbreaks are caused by types A and B that together account for an estimated 3-5 million severe cases each year. Most attention has focused on influenza A viruses (IAVs) due to their rapid evolutionary dynamics and high disease burden, and has been concentrated in well-observed high-income regions. Here, we use a macroecological approach to compare and contrast the global epidemiology of IAVs and influenza B viruses (IBVs) across 111 countries and 15 influenza seasons (2010-2024). We first show how temporal correlations between countries depends on both distance and geographic region. For both IAV and IBV, we find high overall synchrony among northern temperate countries, whereas tropical countries display marked heterogeneity. At the longer time scale of influenza seasons, we next quantify sampling intensity, positivity, seasonality, fade-out dynamics and the timing and variability of epidemic peaks. We then describe how these long-term epidemiological outcomes change in association with a suite of 17 geographic, climatic, and socio-economic variables. In addition, we document persistent surveillance gaps, particularly in Africa, and highlight ongoing but spatially variable impacts of the SARS-CoV-2 pandemic-era on sampling. Overall, we find strong correspondence between the macroscopic features of IAV and IBV epidemiology, with critical roles played by geography and climate (especially latitude and temperature), economics (per capita GDP) and demographics (population size and per capita birth rate). Significance StatementThe global circulation of seasonal influenza A and B viruses (IAV and IBV) imposes major human health impacts each year that very widely across space and time. An improved understanding of these dynamics could improve public health preparedness, response, and intervention efforts. Here we offer a comprehensive comparison of IAV and IBV dynamics across 15 seasons, 111 countries, and six continents. We demonstrate the impact of distance and region on temporal correlation, quantify how measures of influenza seasonality change with geographic and socioeconomic factors, and predict how frequently influenza cases are absent from countries. Our study finds widespread similarities between IAV and IBV (along with key differences), documents notable geographic clusters of countries with shared dynamics, and highlights persistent gaps in global influenza surveillance.