Routine surveillance data can provide an early warning system for antimalarial resistance in pre-elimination areas in Africa

In the first published study of its kind, a new WWARN paper in the Malaria Journal has created near-real-time maps to support antimalarial drug resistance monitoring, using routine malaria surveillance data and individually patient linked data on molecular markers of antimalarial drug resistance.

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The independent emergence and spread of clinically significant artemisinin-resistant Plasmodium falciparum malaria has recently been confirmed in Rwanda and Uganda with molecular markers associated with artemisinin resistance increasingly being detected across Africa. Surveillance to promptly detect and effectively respond to anti-malarial resistance is generally limited in most malaria-endemic African countries, especially in those with low transmission intensities, whose communities may be at higher risk of antimalarial resistance.

Over a two-year period, from March 2018 to February 2020, researchers from the University of Cape Town Collaborating Centre for Optimising Antimalarial Therapy (CCOAT); South African National Institute for Communicable Diseases (NICD); Mahidol Oxford Tropical Medicine Research Unit (MORU); and the WorldWide Antimalarial Resistance Network (WWARN), collected and assessed spatiotemporal changes in antimalarial drug resistance molecular markers in a pre-elimination area in South Africa. As part of this study, they mapped the near-real-time linkage of individual patient antimalarial resistance profiles with their case notifications and treatment response reports to guide evidence-based decision-making. The researchers were able to increase the linkage of routine individual malaria case demographic and molecular data to 75% in the Nkomazi sub-district, Mpumalanga. If this successful pilot were scaled-up, it could be used as an early warning system to assist in rapidly and efficiently monitoring antimalarial drug resistance and to identify areas requiring further investigation and interventions. Tools developed during this project have been made available among the over 120 tools and resources on the WWARN website.

First author Dr Frank Kagoro, a PhD Student at CCOAT and WWARN, said: "Robust drug resistance monitoring is a significant challenge. We were able to increase the collection accuracy of the GPS coordinates of the notified malaria case households from 48% at baseline to 89% to create near-real-time prevalence maps of anti-malarial drug resistance markers. The greatest improvements in the surveillance metrics studied were observed following on-site supervision and were sustained at a moderately high level for more than six months after the last on-site supervision visit."

"The lessons we have learnt in this study could inform scale-up to provincial, national and regional malaria elimination programmes, and may be relevant for other antimicrobial resistance surveillance initiatives", said Prof Karen I Barnes who supervised this study.


Malaria case investigators receiving an in-class training on usage of GPS devices and capturing location information in Nkomazi sub-district, Mpumalanga

Malaria case investigators receiving an in-class training on usage of GPS devices and capturing location information in Nkomazi sub-district, Mpumalanga


Dr Jaishree Raman, co-supervisor from the NICD, adds "This use of routine surveillance data to track antimalarial drug resistance has proved sustainable. While no kelch-13 mutations were detected during the pilot study, we have since detected 14 kelch-13 mutations at at codons 494, 509, 578,605, 613, 651, 678 and 706. Although none of these mutations have been associated reduced parasite clearance, their presence is an indicator of drug pressure on artemether-lumefantrine in the region, and the increased chances of mutations surviving in a parasite population with limited diversity".


Distribution of confirmed malaria cases and molecular markers of artemisinin and lumefantrine drug "resistance" in Nkomazi sub-district, Mpumalanga (March 2018–February 2020). Distribution of P. falciparum malaria cases by 5 × 5 km grid, artemisinin Plasmodium falciparum k13 (left) and lumefantrine (right) mdr186ASN/crt76LYS molecular markers of "resistance", denoted by their susceptibility

"Distribution of confirmed malaria cases and molecular markers of artemisinin and lumefantrine drug "resistance" in Nkomazi sub-district, Mpumalanga (March 2018–February 2020). Distribution of P. falciparum malaria cases by 5 × 5 km grid, artemisinin Plasmodium falciparum k13 (left) and lumefantrine (right) mdr186ASN/crt76LYS molecular markers of "resistance", denoted by their susceptibility"

 

Read the full paper, Making data map worthy enhancing routine malaria data to support surveillance and mapping of Plasmodium falciparum antimalarial resistance in a pre-elimination sub-Saharan African setting: a molecular and spatiotemporal epidemiology study

 

About WWARN

Since 2009, the WorldWide Antimalarial Research Network (WWARN) has generated innovative tools and reliable evidence to inform the malaria community on the factors affecting the efficacy of antimalarial medicines. In the field of poverty-related infectious diseases, data are scarce and scattered across institutions around the world. WWARN collates and standardises anonymised individual patient data (IPD) from many trials and studies conducted across the endemic regions so that they can then be harmonised and analysed as a single dataset, increasing the statistical power needed to answer key questions in malaria research.

WWARN's repository holds over 200k IPD and shares the resulting evidence widely to inform both policymakers and future researchers globally to continually advance knowledge and build capacity for evidence-based practice. Find out more at info@wwarn.org