Smartphone app helps to lower cholera risk

Bangladeshi scientist Firdausi Qadri won the Ramon Magsaysay Award – ‘Asia’s Nobel Prize – for her work on creating more affordable cholera and typhoid vaccines – Copyright AFP/File MUNIR UZ ZAMAN

The seventh cholera pandemic, which began in 1961, continues to this day. The pandemic has annually afflicted millions and claimed tens of thousands of lives. Recognized by the World Health Organization as the longest-lasting pandemic in history, cholera spreads through contamination of household water sources by the Vibrio cholerae bacterium, often from poor sanitation infrastructure.

In nations such as Bangladesh, where cholera is endemic due to high population density and inadequate access to clean water and sanitation facilities, the disease poses a significant public health risk.

Some scientists take the view that for high-risk populations, providing these areas with an early warning system for local cholera risks can be beneficial for health management. This includes measures like encouraging households to adopt safer water, sanitation, and hygiene practices, thereby reducing susceptibility to cholera infection.

Supported, in part, by NASA and administrated by Resources for the Future, Kevin Boyle and colleagues from Moravian University, Penn State, and the University of Rhode Island have assessed the feasibility of implementing a smartphone app designed to convey cholera risk forecasts to households to mitigate the threat of cholera in Bangladesh. This forms part of early warning measures.

The research is titled “Early warning systems, mobile technology, and cholera aversion: Evidence from rural Bangladesh,” and it appears in the Journal of Environmental Economics and Management.

For the research, the team developed CholeraMap, an Android-based smartphone application that conveys cholera risk forecasts to households. The app enables users to access risk predictions – from low to medium to high – for both their community and individual home locations.

The app also offered guidance on understanding the cholera threat associated with their household locations and provided essential public health information to reduce cholera exposure.

This type of reporting is useful since cholera risk is seasonal, changing weather patterns make historical cholera risk predictions less dependable, indicating a need for predictive models. Environmental scientists worked on a predictive model for monthly cholera risk in Bangladesh. The researchers proceeded to investigated how to best communicate these predictions directly to vulnerable populations.

To develop the cholera threat model, the scientists utilized remote sensing data such as rainfall observations, anomalies, forecasts, temperature, and elevation as well as data on population density and past cholera incidence. This model was then calibrated for Matlab, a rural sub-district of Bangladesh.

To test out the software, the CholeraMap application was installed on the smartphones of approximately 750 households across Matlab. Another 750 households received a companion app – CholeraApp – which provided publicly available information about preventing cholera. Finally, as a control, 500 households that did not receive access to either app were tracked.

To assess the impacts of CholeraMap on household behaviours and health, the researchers conducted surveys among the participating households before and after the application’s installation. The respondents were asked about their households’ water use, sanitation and hygiene practices, recent health experiences, water security, and their experiences using CholeraMap.

The scientists discovered that households using smartphone apps decreased their dependency on surface water, a significant source of cholera transmission. Surface water serves as a crucial water source in Matlab, especially for activities such as laundry, dishwashing, and bathing. By minimizing their reliance on surface water, households using CholeraMap were lowering their risk of contracting the disease through proactive measures.

The analysis, overall, appears to demonstrate that everyday people will respond and act in their own interests when presented with better health-related information.