A new approach to eliminating malaria in the Philippines

After a decade of steady advances in fighting malaria, global progress has significantly slowed down. The Philippines is committed to eliminating the disease by 2030, but this is challenged by residual malaria transmission – where infection rates fall but the proportion of individuals missed by the surveillance system and conventional diagnostic methods increases.

This UK-Philippines research collaboration has led to a new integrated diagnostic approach, nearly doubling the number of people detected and treated for malaria in southern Palawan, where more than 90 percent of national malaria cases are reported. The team combined novel and simple-to-use approaches to disease surveillance to expand the coverage of malaria diagnostic services in rural clinics to reach high-risk indigenous groups.

The project aimed to identify individuals with low level infections and locate them in the community. It greatly improved the accuracy with which cases could be geographically identified by using tablet-based mapping – an approach which has huge potential and can be applied beyond malaria to a range of infections.

Researchers developed the capacity of rural health facilities to effectively monitor malaria transmission through government health systems, and demonstrated how community health workers, if well trained and supported, can be at the frontline of detection and surveillance not only of malaria but also of other diseases.

The research has built awareness, secured commitment and fostered knowledge exchange among local health and field workers, scientists, funders and policy makers including the Asia Pacific Malaria Elimination Network and the World Health Organisation. The project’s outcomes will be relevant to other malaria endemic countries.

"We think the simple addition of screening all facility attendees not just those who are sick, even if only periodically, has the potential to speed up malaria elimination in the Philippines."
Dr Fe Espino and Professor Chris Drakeley

The project was shortlisted for the Newton Prize 2019.