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 …

Recent advances in clinical prediction for diarrheal etiology in low-and middle-income
countries have revealed that addition of weather data improves predictive performance …

Infectious disease outbreaks play an important role in global morbidity and mortality. Real-
time epidemic forecasting provides an opportunity to predict geographic disease spread as …

Background Infectious diarrhea can lead to a considerable global disease burden. Thus, the
accurate prediction of an infectious diarrhea epidemic is crucial for public health authorities …

Accurate infectious disease forecasting can inform efforts to prevent outbreaks and mitigate
adverse impacts. This study compares the performance of statistical, machine learning (ML) …

Introduction Diarrhea is still a significant global public health problem. There are currently no
systematic evaluation of the modeling areas and approaches to predict diarrheal illness …

Epidemics of communicable diseases place a huge burden on public health infrastructures
across the world. Producing accurate and actionable forecasts of infectious disease …

Infectious disease forecasting is gaining traction in the public health community; however,
limited systematic comparisons of model performance exist. Here we present the results of a …

Background Diarrhea remains a significant public health problem and poses a considerable
financial burden on Ghana's health insurance scheme. In order to prioritize district-level …

It is predicted that the integration of climate-based early warning systems into existing action
plans will facilitate the timely provision of interventions to diarrheal disease epidemics in …