Public Health requires a trans-disciplinary approach to tackle the breadth and depth of the
issues it faces. Public health decisions are reached through the compilation of multiple data …

This work is aimed at understanding and unifying information on epidemiological modelling
methods and how those methods relate to public policy addressing human health …

In April 2015, the Institute of Medicine convened a workshop to explore the potential uses of
simulation and other types of modeling for the purpose of selecting and refining potential …

Environmental health risks such as household air pollution due to burning solid fuels,
inadequate water, sanitation, and hygiene, and chemical pollution disproportionately affect …

Using computational approaches utilizing large datasets to investigate public health
information is an important mechanism for institutions seeking to identify strategies for …

Résumé The past decade has produced overwhelming evidence that changes in the health
status of individuals, measured by well-defined quantitative clinical endpoints, can, in many …

Computational social science has had a profound impact on the study of health and disease,
mainly by providing new data sources for all of the primary Ws—what, who, when, and …

Over the past decade, public health has seen an explosion in the collection of data beyond
routine programmatic data. From vast quantities of patients' electronic medical records …

Epidemiological models-which help us understand and forecast the spread of infectious
disease-can be valuable tools for public health. However, barriers exist that can make it …

Mathematical models are increasingly relied upon as decision support tools, which estimate
risks and generate recommendations to underpin public health policies. However, there are …