Abstract / Summary
Objectives: Large international events draw visitors worldwide, but how much do they add to infectious disease importation risk beyond everyday travel? We developed a schedule-driven, uncertainty-aware framework to estimate this added risk and applied it to the 2026 FIFA World Cup as a case study. Methods: Three nested Poisson models represent baseline travel, event-related growth, and schedule-driven allocation of additional visitors by venue and date, with Monte Carlo simulation propagating uncertainty in disease under-reporting and travel-while-infected probability. We applied the approach to five diseases across 11 US host cities during the June 2026 World Cup group stage using only publicly available data, evaluated against independently reported dengue case counts, with measles as an additional qualitative check. Results: Relative to 2026 travel without the tournament, the World Cup added 1.0-6.5% to expected importations under schedule-driven routing, versus 2.9-8.5% under routing that ignores the match schedule. Dengue, malaria, and pertussis had the highest modeled importation levels, and the probability of at least one infected dengue or pertussis arrival exceeded 0.99 at 10 of 11 cities. Comparison with 2024 dengue and 2022 measles surveillance data showed a significant rank correlation between modeled and reported dengue cases (Spearman rho= 0.83). Conclusions: This approach provides an empirically grounded way to assess importation risk during large international events using only freely available data, identifying where public health planning may be most useful. For the World Cup case study, the tournament's own contribution was modest once fans were routed by the actual match schedule rather than as ordinary travelers.