projects

Proactive data-driven disease detection in wastewater

Completed
A pair of gloved hands hold a syringe and culture medium, in front of a scene of a refugee camp.
Dzaleka Refugee Camp, in Malawi, hosts more than 53,000 refugees.
Original photo: UNHCR/Tiksa Negeri. Design: UNHCR/Kiunga Isaac.
Programme
UNHCR Innovation Incubator
Fund
Data Innovation Fund | Incubator
Start Date
Total Project Cost
USD 117,800.000
Country
Malawi
Project Team
UNHCR Malawi , Public Health Institute of Malawi , Malawi University of Science and Technology , University of Louisville , Emory University

Challenge

Dzaleka camp has limited capacity and resources to clinically test forcibly displaced persons for infectious diseases. Meanwhile, refugees are especially vulnerable to such diseases, given their poor healthcare access and living conditions.

Solution

Pilot the use of wastewater-based epidemiology (WBE) at the camp, to identify pathogens of concern, estimate their prevalence, and improve and accelerate the response. WBE has been shown to predict some disease outbreaks days before clinical testing.

Impact

Proactive detection of and response to infectious disease outbreaks, driving improved health outcomes.

Project impact

147
wastewater samples collected over 19 weeks from 7 pit latrines and 1 desludging truck
54952
refugees and asylum seekers in the camp, whom the surveillance system aims to protect
1
replicable operational framework for wastewater surveillance in refugee camps

Other information

Refugees living in densely populated camps with non-sewered sanitation are highly vulnerable to cholera and other water-borne outbreaks, yet wastewater and environmental surveillance (WES) had never been systematically applied in a refugee setting. Funded by the Data Innovation Fund, UNHCR Malawi piloted the first WES system in Dzaleka camp during the country's 2022–2024 cholera outbreak, collecting 147 samples from high-use pit latrines and a desludging pump truck over 19 weeks. The project, co-led with the Public Health Institute of Malawi, Malawi University of Science and Technology and US academic partners, generating one of the first WES datasets for refugees globally. It produced a peer-reviewed operational framework using locally available culture methods, affordable, scalable and adaptable to any refugee camp globally. The model now provides a proof of concept for anticipating outbreaks in humanitarian settings and is ready for replication across camps with non-sewered sanitation.

Read more about this project in our webstory.