Quantitative, model-based estimates of variability in the serial interval of Plasmodium falciparum malaria

Abstract

AbstractBackground: The serial interval is a fundamentally important quantity in infectious disease epidemiology that has numerous applications to inferring patterns of transmission from case data. Many of these applications are apropos to efforts to eliminate Plasmodium falciparum (Pf) malaria from locations throughout the world, yet the serial interval for this disease is poorly understood quantitatively.Results: To obtain a quantitative estimate of the serial interval for Pf malaria, we took the sum of components of the Pf malaria transmission cycle based on a combination of mathematical models and empirical data. During this process, we identified a number of factors that account for substantial variability in the serial interval across different contexts. Treatment with antimalarial drugs roughly halves the serial interval, seasonality results in different serial intervals at different points in the transmission season, and variability in within-host dynamics results in many individuals whose serial intervals do not follow average behavior.Conclusions: These results have important implications for epidemiological applications that rely on quantitative estimates of the serial interval of Pf malaria and other diseases characterized by prolonged infections and complex ecological drivers.