{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,6]],"date-time":"2026-07-06T18:16:36Z","timestamp":1783361796545,"version":"3.54.6"},"reference-count":22,"publisher":"Public Library of Science (PLoS)","issue":"7","license":[{"start":{"date-parts":[[2026,7,6]],"date-time":"2026-07-06T00:00:00Z","timestamp":1783296000000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["www.plosone.org"],"crossmark-restriction":false},"short-container-title":["PLoS One"],"abstract":"\n Background<\/jats:title>\n 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\u2009+\u2009ITNs on malaria test positivity rates in high disease transmission settings of Yumbe district and Gulu district.<\/jats:p>\n <\/jats:sec>\n \n Method<\/jats:title>\n \n The Ministry of Health\u2019s 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 11\n th<\/jats:sup>\n 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.\n <\/jats:p>\n <\/jats:sec>\n \n Results<\/jats:title>\n 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\u2009<\u20090.00 (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\u2009=\u20090.0111, beta\u2009=\u2009\u22120.0054, 95% CI:0.1145, 0.1038, p\u2009=\u20090.923). 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\u2009=\u2009\u22120.2123, 95% CI: \u22120.2801, \u22120.1444, p\u2009<\u20090.001). 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\u2009=\u2009\u22120.2508, 95%CI:-0.3279, \u22120.1737,p\u2009<\u20090.001).<\/jats:p>\n <\/jats:sec>\n \n Conclusion<\/jats:title>\n In areas of high malaria transmission, deployment of either ITNs alone, IRS alone, or in combination can be an effective tool for malaria case reduction. However, a more sustained and significant reduction is achieved through the simultaneous deployment of IRS and ITNs. Crucially, the efficacy of these combined interventions is highly shaped by the specific classes of insecticides and active compounds utilized within the deployed ITN types and IRS campaigns.<\/jats:p>\n <\/jats:sec>","DOI":"10.1371\/journal.pone.0352455","type":"journal-article","created":{"date-parts":[[2026,7,6]],"date-time":"2026-07-06T17:37:25Z","timestamp":1783359445000},"page":"e0352455","update-policy":"https:\/\/doi.org\/10.1371\/journal.pone.corrections_policy","source":"Crossref","is-referenced-by-count":0,"title":["Combination of different intervention strategies for malaria mosquito vector control in Uganda: A review of secondary data of two districts with moderate to high disease transmission"],"prefix":"10.1371","volume":"21","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2836-7141","authenticated-orcid":true,"given":"Erick 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James","family":"Obondo","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Martin","family":"Lukindu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Julius","family":"Lutwama","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jonathan","family":"Kayondo","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Moses","family":"Ocan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"340","published-online":{"date-parts":[[2026,7,6]]},"reference":[{"issue":"10","key":"pone.0352455.ref001","doi-asserted-by":"crossref","DOI":"10.1016\/S2542-5196(24)00172-4","article-title":"Malaria vector control in sub-Saharan Africa: complex trade-offs to combat the growing threat of insecticide resistance","volume":"8","author":"RM 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