Background Mathematical models are increasingly used to understand the dynamics of infectious diseases, including "chronic" infections with long generation times. Such models include features that are obscure to most clinicians and decision-makers. Methods Using a model of a hypothetical active case-finding intervention for tuberculosis in India as an example, we illustrate the effects on mod...

Time series regression has been developed and long used to evaluate the short-term associations of air pollution and weather with mortality or morbidity of non-infectious diseases. The application of the regression approaches from this tradition to infectious diseases, however, is less well explored and raises some new issues. We discuss and present potential solutions for five issues often ari...

Infectious diseases affect both animals and humans and cause significant financial losses and loss of lives every year around the world. For developing nations like India the losses are all the more critical because they affect economic growth (i.e. loss of animals and labor). Mathematical models have become important tools in analyzing the spread and control of infectious diseases. The modelli...

Biological processes occur at distinct but interlinked scales of organization. Yet, mathematical models are often focused on a single scale. Recently, there has been a significant interest in creating and using models that link the withinhost dynamics and population level dynamics of infectious diseases. These types of multi-scale models, called immuno-epidemiological models, fall in four categ...