FloDisMod: A Framework for Flood and Disease Modeling


  • Dr Tamer Oraby

    University of Texas Rio Grande Valley, United States

  • Prof Clint Dawson

  • Dr Katherine Brown

    University of Texas at Austin, United States

  • Dr Eirik Valseth


Project summary

Climate-sensitive infectious diseases more often than ever pose a threat to humankind with pandemic potential. Soil and water-borne infectious diseases outbreaks are linked to seasonal weather patterns and extreme weather conditions in the coastal areas, such as coastal flooding and storm surge, which will be becoming more frequent and persistent due to the predictive climate change.

To better understand the dynamics of the relationship between soil and water-borne infectious diseases with climate and more importantly predict outcomes in the future, particularly in areas with potential emerging situations, we are proposing the development of an openly accessible computational tool that would be accessible to non-expert users, i.e. researchers and health professionals, and allow them to use available climate inputs and epidemiological information to facilitate analysis, prediction and visualization of data relevant to infectious disease studied, as a means of informing policies in disease management.