A new study by researchers at the Big Data Institute shows that how close people live to unsafe water sources strongly predicts their exposure to schistosomiasis, a debilitating waterborne parasitic disease, helping to explain patterns of infection and re-infection. The study is published in Nature Health.
Globally, over 400 million people rely on unsafe water in lakes, rivers, and swamps for drinking, bathing, washing clothes, and livelihoods, putting them at risk of waterborne diseases like schistosomiasis.
The disease affects over 200 million people and can lead to liver and kidney damage, bladder cancer, and premature death in severe cases. It is endemic mainly in areas of sub-Saharan Africa where people lack access to safe water from taps or boreholes, and have to rely on open waterbodies that harbour the parasite. People become infected when parasite larvae from freshwater snails burrow into their skin.
Currently, the main strategy for controlling the disease is by mass treatment of affected populations with the drug praziquantel, but individuals are often reinfected soon afterwards. As a result, the World Health Organization (WHO) recommends combining treatment with other interventions, such as improving access to safe water. However, efforts to design effective prevention strategies require a detailed understanding of how far people travel to use open water sources – information that has been largely missing.
The study, carried out in collaboration with the Division of Vector Born Diseases and Neglected Tropical Diseases at Uganda’s Ministry of Health, aimed to address this. Working in three rural districts of Uganda, the researchers equipped 452 children and adults drawn from the SchistoTrack study with wearable GPS loggers for 10 days. Data were collected at two-minute intervals resulting in over 1 million GPS locations. This allowed researchers to study water contact patterns in great detail.
Combining the GPS data with information about open water site locations and schistosomiasis risk at these sites, the team demonstrated that risk can vary metre-by-metre. How close people lived to water sites strongly predicted their exposure to schistosomiasis, helping to explain why even neighbouring villages may experience different patterns of infection and re-infection.
The data showed that nearly 64% of participants visited at least one open water site while 33% visited at least one tap or borehole. Nearly a quarter of participants visited both open water sites and taps/boreholes, suggesting that safe water access alone does not necessarily reduce the risk of exposure.
The researchers found that open water site usage declined exponentially with distance with 70% of people using water sites within 20m of their homes and less than 5% using sites 1km or further away. The researchers used this finding to develop transmission models that predicted the risk of re-infection.
Dr Melissa Iacovidou from the Big Data Institute at Oxford Population Health, who is one of the study’s co-authors, said ‘The GPS data collected in the study were vital for understanding patterns of human behaviour in these areas and for improving assumptions in individual-based transmission models. Further developing such models can help guide focal interventions in the future.’
Fabian Reitzug, the study’s first author and a former DPhil student at Oxford Population Health, added ‘For many infectious diseases, behavioural factors like open water contact have often made it difficult to understand and predict transmission dynamics. We show that even with this complexity, it is still possible to isolate regularities in human behaviour to guide better intervention strategies and predictive models.’
The authors note that similar models could be used in the future to identify the open water sites that are driving most transmissions. They could also be used to design highly targeted and local interventions such as snail control and to prioritise communities for treatment with praziquantel. They also highlight the potential for a similar approach to be applied to other waterborne diseases.