Ensemble forecast and parameter inference of childhood diarrhea in Chobe District, Botswana ; Epidemics

Diarrheal disease is the second largest cause of mortality in children younger than 5, yet our ability to anticipate and prepare for outbreaks remains limited. Here, we develop and test an epidemiological forecast model for childhood diarrheal disease in Chobe District, Botswana. Our prediction system uses a compartmental susceptible-infected-recovered-susceptible (SIRS) model coupled with Bayesian data assimilation to infer relevant epidemiological parameter values and generate retrospective forecasts. Our model inferred two system parameters and accurately simulated weekly observed diarrhea cases from 2007-2017. Accurate retrospective forecasts for diarrhea outbreaks were generated up to six weeks before the predicted peak of the outbreak, and accuracy increased over the progression of the outbreak. Many forecasts generated by our model system were more accurate than predictions made using only historical data trends. Accurate real-time forecasts have the potential to increase local preparedness for coming outbreaks through improved resource allocation and healthcare worker distribution. ; National Science Foundation Dynamics of Coupled Natural and Human Systems [1518486]; National Institutes of HealthUnited States Department of Health & Human ServicesNational Institutes of Health (NIH) - USA [T32 ES023770] ; This project was made possible by a grant from the National Science Foundation Dynamics of Coupled Natural and Human Systems (Award #1518486, KAA) and by a training grant from National Institutes of Health (T32 ES023770). We would also like to thank the Botswana Ministry of Health, the Chobe District Health Team, Dr. M. Vandewalle, R. Sut-cliffe, L. Nkwalale, M. Heneghan, K. Ramsden, T. Motseothata, S. Vandewalle, C. A. Nichols, and others who contributed importantly to the collection of the health data used in this study.