Published in PLOS One on 2026-07-06, this study is presented as an attributed evidence briefing. The excerpts below are the original researchers’ words, reproduced under their Creative Commons Attribution licence. HealthSignal has selected the abstract and, where needed, opening background paragraphs; the complete methods, results, limitations and references remain in the linked paper.
Original authors: Erick Jacob Okek, Winnie Nambatya, Loyce Nakalembe, Silvia Awor, Benson Musinguzi, Amos Drasiku, Sande James Obondo, Martin Lukindu, Julius Lutwama, Jonathan Kayondo, Moses Ocan
Source: PLOS One • DOI 10.1371/journal.pone.0352455
Read the complete primary study ↗ · Creative Commons Attribution licence
From the researchers
Abstract
Indoor residual spraying (IRS) and insecticide treated bed nets (ITNs) used either singly or in combination are the main mass mosquito vector control measures for malaria control. Despite their widespread use, malaria transmission rates remain high, the burden is unacceptably huge, and yet the disease is completely preventable. This study measured the impact of compounds used in different types and campaigns of IRS and ITNs, different permutations of IRS + ITNs on malaria test positivity rates in high disease transmission settings of Yumbe district and Gulu district.
The Ministry of Health’s District Health Information System 2 (DHIS 2) records on distribution of ITNs, IRS schedules and malaria cases by gender, age and geographical location (Gulu and Yumbe districts) collected over a five-year period (DHIS 2 records accessed on 11th February 2025) were used in the final analysis. Data collection was done using a checklist developed in an Excel spreadsheet. Data on the following were extracted; socio-demographic characteristics, number of monthly malaria tests, monthly numbers of positive malaria tests, the type of Insecticide Treated Nets (ITNs) distributed, the type of Indoor Residual Spray (IRS) applied and the time points that the interventions were deployed. The data was exported into STATA ver 17.0,cleaned and additional variables generated prior to the interrupted time series and Difference in Difference analysis. The monthly malaria test positivity rate (TPR) was calculated while adjusting for variability in rainfall, temperature and relative humidity. A regression analysis and graphical plots using the Generalized Estimation Equation (GEE) population average models were performed.
After controlling for monthly variation in rainfall, temperature, and relative humidity, the deployment of malaria vector control interventions in Yumbe district led to a much faster reduction in TPR of 0.006 units/0.56% per month; p < 0.00 (about 5 times faster than Gulu district). The 2020 distribution of Yorkool ITNs in Yumbe did not significantly change the long-term trend in TPR of the district relative to Gulu that maintained distribution of PermaNets ITN (trend change difference = 0.0111, beta = −0.0054, 95% CI:0.1145, 0.1038, p = 0.923). Fludora Fusion demonstrated a profound impact. The difference-in-differences interaction term was highly statistically significant, showing an absolute 21.2% drop in the Malaria Test Positivity Rate in Yumbe District relative to Gulu district (beta = −0.2123, 95% CI: −0.2801, −0.1444, p < 0.001). Following a co-deployment of Actellic 300 CS IRS+ Royal Guard ITNs in Yumbe and distribution of PermaNet ITNs in Gulu, the difference-in-differences interaction term was highly statistically significant, demonstrating an absolute 25.1% drop in the Malaria Test Positivity Rate in Yumbe District compared to Gulu district (beta = −0.2508, 95%CI:-0.3279, −0.1737,p < 0.001).
Reading this evidence
Use the full paper to check the study design, participant selection, comparator and outcome definitions before drawing a practical conclusion. An association does not by itself show cause and effect. A reported performance measure needs its denominator and uncertainty. A finding from a particular facility, sample or time period should retain that scope when it is discussed elsewhere.
This briefing makes the source accessible within the wider public health desk. It does not assess an individual patient or certify a product. When considering relevance to another health system, examine the original authors’ account of context and limitations, then seek local implementation evidence. The related reporting below provides other studies to read alongside this one; it is a topic connection, rather than a claim that their results are directly comparable.
© 2026 Erick Jacob Okek, Winnie Nambatya, Loyce Nakalembe, Silvia Awor, Benson Musinguzi, Amos Drasiku, Sande James Obondo, Martin Lukindu, Julius Lutwama, Jonathan Kayondo, Moses Ocan. Excerpts reproduced under CC BY. Selection, formatting and contextual notes by HealthSignal. The researchers are the authors of the source study, not members of HealthSignal’s staff.
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