Digital technology for storm-related malaria response in Mozambique


  • Prof João Ferrão

    UnISCED – Universidade Aberta ISCED, Mozambique

  • Prof Jaideep Srivastava

    University of Minnesota, United States

  • Dr Lin Zhang

    University of Minnesota, United States

  • Dr Kelly Searle

    University of Minnesota, United States

Project summary

Increases in frequency of severe weather events are a hallmark of climate change and impact the effectiveness of malaria control programs.

Mozambique is already experiencing these and does not have the capacity to respond to the infectious disease challenges that co-occur. Digital technology will be used to integrate climate and malaria data to identify areas at risk of malaria in the aftermath of severe weather in a much more comprehensive manner. A time-series model will be used to determine geographic areas of increased malaria risk following severe weather. This will provide the basis of a software platform to quantify and visualize these areas for delivery of malaria control measures.

The overall objective is to improve the response to malaria risk, increase the efficiency of control programs, and decrease morbidity and mortality. The specific goals are to:

1) create a time-series model that determines geographic areas of increased malaria risk due to severe weather events in Mozambique

2) develop and pilot a software platform that predicts geographic areas of high risk following severe weather

3) integrate this platform into the Mozambique malaria control and disaster management programs.

This platform will directly inform the preparation and delivery of malaria control activities after severe weather.