Using geospatial mapping to enhance policy decisions and track malaria drug resistance

WWARN Published Date

Resistance to the artemisinin component of artemisinin combination therapies (ACTs),has emerged in parts of Southeast Asia. Locations with low malaria transmission and intense drug selection pressure are seen as potential hot spots for new outbreaks of drug resistant malaria.  The identification of hot spots requires strategies for surveillance of current resistant parasites and definition of efficient paths for further assessments of new sites of resistance.

Spatial models have been applied recently to estimate the geographic distribution of malaria infection and antimalarial drug resistance. However, while some studies have used computer models to generate predictive maps, there has been little emphasis on using these maps to improve data collection.  

Geospatial modelling can use the prevalence of antimalarial drug resistance markers in sampled sites to identify areas where there is insufficient evidence to predict the prevalence of those markers in unsampled locations.  A team of WWARN contributors recently published a study in the International Journal of Health Geographics describing a method known as ‘smart surveillance’. Smart surveillance uses geospatial modelling to identify locations for future sampling that would reduce the uncertainty of the predictions of marker prevalence in the regions of most interest. 

The study used both published and unpublished data on the prevalence of mutant alleles of the K13 marker of artemisinin resistance from five countries in the Greater Mekong region of Southeast Asia. The current prevalence in sampled sites was used to design an efficient path for gathering evidence needed to identify optimal locations where further sampling would be most informative. 

Smart surveillance acts as a cost-effective and efficient way of monitoring the geographic distribution of antimalarial drug resistance in endemic regions,” says Dr Eric Grist, lead author and former mathematical modeller at WWARN. “This technique can be used to assist in efforts to eliminate malaria in low transmission areas where there is a greater risk of the emergence of antimalarial resistance.”

There is a practical constraint on the number of new sites that can be used for sampling. This innovative method explores ways to optimise sampling site selection” adds Prof Philippe Guérin, Director of WWARN.

Geospatial mapping, such as this smart surveillance technique, is crucial for maximising our limited resources and enhancing the efficiency of sampling.” says Prof Richard Maude, Head of Malaria Epidemiology at Mahidol-Oxford Tropical Medicine Research Unit, Bangkok, Thailand “Application of tools that provide geospatial information can help to inform policy decisions by providing guidance for strategic allocation of resources.”

This technique can be more broadly applied to geostatistical mapping in other diseases. These approaches can be used to support deployment of resources and rapid response to newly emerging resistance and other infections.

To complement these mathematical modelling endeavours, WWARN teams are developing and refining a number of data visualisation tools to help monitor the distribution of drug resistance genes in parasites over time and space. These include four molecular surveyors; the K13 Surveyor, the Vivax Surveyor, the pfmdr1 & pfcrt Surveyor, and the pfdhfr & pfdhps Surveyor. Visit the website soon to see the pfmdr1 & pfcrt Surveyor updated with an Asia regional map.

Publication details:

Grist E, et al. Optimal health and disease management using spatial uncertainty: a geographic characterization of emergent artemisinin-resistant Plasmodium falciparum distributions in Southeast Asia. International Journal of Health Geographics, 23 October 2016. 15:37. DOI: 10.1186/s12942-016-0064-6