Model-guided geospatial surveillance system for antimalarial drug resistance
Issued Date
2026-01-01
Resource Type
eISSN
27673375
Scopus ID
2-s2.0-105028972649
Journal Title
Plos Global Public Health
Volume
6
Issue
1 January
Rights Holder(s)
SCOPUS
Bibliographic Citation
Plos Global Public Health Vol.6 No.1 January (2026)
Suggested Citation
Gupta A., Harrison L.E., Nain M., Phulgenda S.S., Chhajed R., Kumar R.S., Das A., Rahi M., Guerin P.J., Anvikar A.R., Dhorda M., Flegg J.A., Bharti P.K. Model-guided geospatial surveillance system for antimalarial drug resistance. Plos Global Public Health Vol.6 No.1 January (2026). doi:10.1371/journal.pgph.0004717 Retrieved from: https://repository.li.mahidol.ac.th/handle/123456789/114838
Title
Model-guided geospatial surveillance system for antimalarial drug resistance
Author's Affiliation
Academy of Scientific and Innovative Research (AcSIR)
Nuffield Department of Medicine
Mahidol Oxford Tropical Medicine Research Unit
School of Mathematics and Statistics
National Institute of Malaria Research India
Vector Control Research Centre India
WorldWide Antimalarial Resistance Network
Infectious Diseases Data Observatory
Nuffield Department of Medicine
Mahidol Oxford Tropical Medicine Research Unit
School of Mathematics and Statistics
National Institute of Malaria Research India
Vector Control Research Centre India
WorldWide Antimalarial Resistance Network
Infectious Diseases Data Observatory
Corresponding Author(s)
Other Contributor(s)
Abstract
Disease surveillance activities are usually resource-constrained and should be optimised to generate the most informative scientific findings, and to make the best use of time, finances, and personnel. India has a high population density, diverse geography and climatic conditions, and difficult terrain. With respect to malaria, Plasmodium falciparum and Plasmodium vivax are endemic, with substantial variability of transmission across the country. While for P. vivax, drug efficacy appears to be homogeneous within the country, for P. falciparum malaria, the drug resistance pattern varies from the northeastern region to the central region. Accounting for these complexities, we develop a decision-making framework guided by geospatial modelling outputs to identify prospective study sites for surveillance of molecular markers of antimalarial drug resistance in P. falciparum malaria in India. We first retrieve existing data on the prevalence of validated markers of resistance to artesunate and sulfadoxine-pyrimethamine from the World Wide Antimalarial Resistance Network (WWARN) Surveyor database. We then incorporate these data into a geostatistical model to estimate the prevalence of these markers across India and identify areas with high median estimated marker prevalence and high uncertainty. Finally, we create an interactive dashboard using the RShiny software package to simplify the process of selecting sites for future molecular surveillance. Our framework helps to ensure that operational decision-making is supported by data and modelling outputs. We demonstrate the utility of our framework by selecting sites for molecular surveillance of P. falciparum malaria in India. Copyright: