Evidence map›Paper›PMID 40460097›Full record

ArticlePloS one2025

Factors affecting integration of an early warning system for antimalarial drug resistance within a routine surveillance system in a pre-elimination setting in Sub-Saharan Africa.

Frank M Kagoro, Elizabeth Allen, Jaishree Raman, Aaron Mabuza, Ray Magagula, Gerdalize Kok, Gillian Malatje, Philippe J Guerin, Mehul Dhorda, Richard J Maude and 1 more

Abstract read
In one paragraph

Article in PloS one, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Frank M KagoroCollaborating Centre for Optimising Antimalarial Therapy (CCOAT), Division of Clinical Pharmacology, Department of Medicine, University of Cape Town (UCT), Cape Town, South Africa.ORCID 0000-0003-4608-7167
Elizabeth AllenCollaborating Centre for Optimising Antimalarial Therapy (CCOAT), Division of Clinical Pharmacology, Department of Medicine, University of Cape Town (UCT), Cape Town, South Africa.
Jaishree RamanCentre for Emerging Zoonotic and Parasitic Diseases, National Institute for Communicable Disease (NICD), Sandringham, Gauteng, South Africa.ORCID 0000-0003-0728-3093
Aaron MabuzaCollaborating Centre for Optimising Antimalarial Therapy (CCOAT), Division of Clinical Pharmacology, Department of Medicine, University of Cape Town (UCT), Cape Town, South Africa.
Ray MagagulaMpumalanga Provincial Malaria Elimination Programme, Mpumalanga, South Africa.
Gerdalize KokMpumalanga Provincial Malaria Elimination Programme, Mpumalanga, South Africa.
Gillian MalatjeMpumalanga Provincial Malaria Elimination Programme, Mpumalanga, South Africa.
Philippe J GuerinWorldWide Antimalarial Resistance Network (WWARN), South-East African Regional Hub, UCT, Cape Town, South Africa.
Mehul DhordaMahidol Oxford Tropical Medicine Research Unit (MORU), Faculty of Tropical Medicine, Mahidol University, Bangkok, Thailand.
Richard J MaudeMahidol Oxford Tropical Medicine Research Unit (MORU), Faculty of Tropical Medicine, Mahidol University, Bangkok, Thailand.ORCID 0000-0002-5355-0562
Karen I BarnesCollaborating Centre for Optimising Antimalarial Therapy (CCOAT), Division of Clinical Pharmacology, Department of Medicine, University of Cape Town (UCT), Cape Town, South Africa.ORCID 0000-0002-5547-820X

Funding

Wellcome Trust
6 · The paper itself

Abstract

To address the current threat of antimalarial resistance, countries need innovative solutions for timely and informed decision-making. Integrating molecular surveillance for drug-resistant malaria into routine malaria surveillance in pre-elimination contexts offers a potential early warning mechanism for further investigation and response. However, there is limited evidence on what influences the performance of such a system in resource-limited settings. From March 2018 to February 2020, a sequential mixed-methods study was conducted in primary healthcare facilities in a South African pre-elimination setting to explore factors influencing the flow, quality and linkage of malaria case notification and molecular resistance marker data. Using a process-oriented framework, we undertook monthly and quarterly data linkage and consistency analyses at different levels of the health system, as well as a survey, focus group discussions and interviews to identify potential barriers to, and enhancers of, the roll-out and uptake of this integrated information system. Over two years, 4,787 confirmed malaria cases were notified from 42 primary healthcare facilities in the Nkomazi sub-district, Mpumalanga, South Africa. Of the notified cases, 78.5% (n = 3,758) were investigated, and 55.1% (n = 2,636) were successfully linked to their Plasmodium falciparum molecular resistance marker profiles. Five tangible processes-malaria case detection and notification, sample collection, case investigation, analysis and reporting-were identified within the process-oriented logic model. Workload, training, ease of use, supervision, leadership, and resources were recognized as cross-cutting influencers affecting the program's performance. Approaching malaria elimination, linking molecular markers of antimalarial resistance to routine malaria surveillance is feasible. However, cross-cutting barriers inherent in the healthcare system can influence its success in a resource-limited setting.

Indexed as

AntimalarialsDrug ResistanceMalariaMalaria, FalciparumAfrica South of the SaharaEpidemiological MonitoringFemaleHumansMalePlasmodium falciparumSouth AfricaAntimalarials

Identifiers

PMID40460097
PMCPMC12132925

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.