ArticleMalaria journal2021
Relationships between test positivity rate, total laboratory confirmed cases of malaria, and malaria incidence in high burden settings of Uganda: an ecological analysis.
Article in Malaria journal, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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11 citing papers in PubMed, 21 citations in OpenAlex.
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- Temporal Trends in Artemisinin Partial Resistance and Other Antimalarial Drug Mutations inmedRxiv : the preprint server for health sciences · 2025Article
- Trend of malaria test positivity rate among pregnant women, Savannah Region, Ghana, 2018-2022.BMC pregnancy and childbirth · 2025Article
- Level of and factors associated with optimal uptake of intermittent preventive treatment for malaria in pregnancy at private-not-for-profit health facilities in Kasese district.PLOS global public health · 2024Article
- Rethinking communications for governance of malaria programs.PLOS global public health · 2023Review
- Impact of different mosquito collection methods on indicators of Anopheles malaria vectors in Uganda.Malaria journal · 2022Article
- East Africa International Center of Excellence for Malaria Research: Impact on Malaria Policy in Uganda.The American journal of tropical medicine and hygiene · 2022Review
- Gender difference in the incidence of malaria diagnosed at public health facilities in Uganda.Malaria journal · 2022Article
- Article
- Associations between environmental covariates and temporal changes in malaria incidence in high transmission settings of Uganda: a distributed lag nonlinear analysis.BMC public health · 2021Article
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14 authors at 3 institutions in 2 countries.
Funding
Abstract
backgroundMalaria surveillance is critical for monitoring changes in malaria morbidity over time. National Malaria Control Programmes often rely on surrogate measures of malaria incidence, including the test positivity rate (TPR) and total laboratory confirmed cases of malaria (TCM), to monitor trends in malaria morbidity. However, there are limited data on the accuracy of TPR and TCM for predicting temporal changes in malaria incidence, especially in high burden settings.
methodsThis study leveraged data from 5 malaria reference centres (MRCs) located in high burden settings over a 15-month period from November 2018 through January 2020 as part of an enhanced health facility-based surveillance system established in Uganda. Individual level data were collected from all outpatients including demographics, laboratory test results, and village of residence. Estimates of malaria incidence were derived from catchment areas around the MRCs. Temporal relationships between monthly aggregate measures of TPR and TCM relative to estimates of malaria incidence were examined using linear and exponential regression models.
resultsA total of 149,739 outpatient visits to the 5 MRCs were recorded. Overall, malaria was suspected in 73.4% of visits, 99.1% of patients with suspected malaria received a diagnostic test, and 69.7% of those tested for malaria were positive. Temporal correlations between monthly measures of TPR and malaria incidence using linear and exponential regression models were relatively poor, with small changes in TPR frequently associated with large changes in malaria incidence. Linear regression models of temporal changes in TCM provided the most parsimonious and accurate predictor of changes in malaria incidence, with adjusted R
conclusionsIn high malaria burden areas of Uganda, site-specific temporal changes in TCM had a strong linear relationship with malaria incidence and were a more useful metric than TPR. However, caution should be taken when comparing changes in TCM across sites.
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