The effects of population structure and healthcare heterogeneity on novel pathogen detection

Music City Center 

Improving novel pathogen surveillance systems is of paramount importance, as detecting infections while at low prevalence can guide interventions to prevent epidemics and pandemics. The probability of surveillance system failure can be modeled using a framework that considers the probability of detection for a single case, π, and population size. However, accounting for population structure in disease incidence and π, and for subpopulation sizes, can reduce bias in quantifying surveillance system performance. We created models that incorporate these considerations: an "endemic model", which assumes emergence of a variant of a circulating pathogen, and an "outbreak model", which assumes an outbreak of a novel virus. Surveillance system failure probability estimates were higher using the outbreak model, and negatively correlated π and probability of local outbreak, which is likely in rural areas, resulted in higher failure probabilities. These results have ramifications for policy, as overestimation of surveillance system performance may lead to a reduction in the overall level, or efficacious distribution of, resources for epidemic and pandemic prevention.

epidemiology

surveillance

population structure 

Section on Statistics in Epidemiology