ORIGINAL RESEARCH article
Front. Public Health
Sec. Infectious Diseases: Epidemiology and Prevention
This article is part of the Research TopicThe Quintuple of Climate Change, Landscape Modification, Globalization, Pathogen Adaptation and OutbreaksView all 3 articles
Integrating forest data and health facility surveys to optimise risk-based malaria surveillance in the Philippines
Provisionally accepted
Kimberly M Fornace1*
Ralph A Reyes2
Maria Lourdes Macalinao2
Jun-Sik LIM1
Alison Paolo N Bareng2Jennifer S Luchavez2
Julius Clemence Hafalla3
Fe Espino2
Jason Matthiopoulos4
Chris Drakeley3- 1National University Singapore Saw Swee Hock School of Public Health, Singapore, Singapore
- 2Research Institute for Tropical Medicine, Muntinlupa, Philippines
- 3London School of Hygiene & Tropical Medicine, London, United Kingdom
- 4University of Glasgow, Glasgow, United Kingdom
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Malaria transmission is highly spatially heterogeneous. Within Southeast Asia, forested landscapes are associated both with increased malaria transmission and reduced healthcare access. Identifying environments with malaria foci is a priority for control and elimination programmes. Here, we integrate health facility and environmental data to identify optimal surveillance approaches across a forested district in the Philippines. We conducted convenience surveys of health facility attendees utilising tablet-based applications to geolocate participant residences. Malaria infection was assessed using both routine (microscopy and rapid diagnostic test) and molecular methods. Integrating remote-sensing derived data, we assessed how fine-scale environmental factors influence the spatial distributions of malaria infections, diagnostic sensitivity and health-seeking behaviour. We evaluated costs and probability of detecting malaria foci for multiple surveillance approaches using different diagnostic methods and target populations defined by landscape data. We demonstrate that health facility-based surveys increase the probability of detecting malaria infections by increasing numbers of individuals screened and spatial coverage of surveillance systems. We additionally show sensitivity of routine malaria diagnostics varies spatially, with the decreased sensitivity in forests. By targeting diagnostic methods to high-risk environments, we developed a model approach for how to use landscape data within disease surveillance systems. Risk-based surveillance incorporating forest data is highly cost-effective and increases the probability of detecting malaria foci over three-fold compared to routine surveillance. Together, this illustrates the essential role of environmental data in designing risk-based surveillance to provide an operationally feasible and cost-effective method to characterise malaria transmission.
Keywords: Malaria, surveillance, land use change, spaaal epidemiology, Easy Access Groups
Received: 05 Sep 2025; Accepted: 28 Nov 2025.
Copyright: © 2025 Fornace, Reyes, Macalinao, LIM, Bareng, Luchavez, Hafalla, Espino, Matthiopoulos and Drakeley. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Kimberly M Fornace
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