{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,15]],"date-time":"2026-10-15T05:38:46Z","timestamp":1792042726909,"version":"4.4.0"},"reference-count":83,"publisher":"Wiley","issue":"10","license":[{"start":{"date-parts":[[2025,8,24]],"date-time":"2025-08-24T00:00:00Z","timestamp":1755993600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Tropical Med Int Health"],"published-print":{"date-parts":[[2025,10]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>The expansive scale\u2010up of malaria interventions resulted in substantial reductions in malaria morbidity and mortality in the past 20\u2009years. Intervention effectiveness has traditionally been estimated through research studies and trials, nationally representative surveys, and mathematical modelling. Because of their sheer volume across space and time, data reported routinely through health management information systems can complement and even offer an alternative to surveys and modelling to assess intervention effectiveness, and ultimately impact on health outcomes. This scoping review describes the different analytical approaches for estimating the effectiveness of malaria interventions using routine health management information systems data.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>We examined PubMed using combination searches of the following terms: \u2018malaria\u2019 AND \u2018intervention\u2019 AND \u2018effect*\u2019 OR \u2018impact\u2019 AND \u2018system\u2019 OR \u2018surveillance\u2019. Other key terms such as \u2018routine\u2019 or \u2018information systems\u2019 were not included in the search strategy to have a more comprehensive search and were used during abstract and full text screening. We limited inclusion to studies and analyses that were conducted in the past decade, as that is when countries' routine health management information systems began to substantially mature, with data reported by these systems progressively becoming more robust.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Out of 957 records generated from the PubMed search, following title and abstract screening, 93 were included for full\u2010text review, with 49 records ultimately meeting the inclusion criteria for the scoping review. We summarise included studies by publication year, geography, outcome variables, target populations, interventions assessed, health management information systems data platform used\u2014broadly, analytical approaches used a range of modelling or non\u2010modelling approaches to assess intervention effectiveness.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>This scoping review shows that routine health management information systems data can be used to regularly assess the effectiveness of various malaria interventions\u2014an important exercise to ensure that implemented interventions continue to be effective, have the desired effect, and ultimately help countries progress towards their national strategic goals and targets.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1111\/tmi.70015","type":"journal-article","created":{"date-parts":[[2025,8,25]],"date-time":"2025-08-25T03:54:16Z","timestamp":1756094056000},"page":"1025-1052","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Use of Routine Health Data to Monitor Malaria Intervention Effectiveness: A Scoping Review"],"prefix":"10.1111","volume":"30","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5710-1556","authenticated-orcid":false,"given":"Richard","family":"Reithinger","sequence":"first","affiliation":[{"name":"Country Health Information System and Data Use Program, RTI International  Washington, DC USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7832-2291","authenticated-orcid":false,"given":"Donal","family":"Bisanzio","sequence":"additional","affiliation":[{"name":"Country Health Information System and Data Use Program, RTI International  Washington, DC USA"},{"name":"School of Medicine Nottingham University  Nottingham UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3447-9710","authenticated-orcid":false,"given":"Anya","family":"Cushnie","sequence":"additional","affiliation":[{"name":"Country Health Information System and Data Use Program, John Snow Inc.  Washington, DC USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jessica","family":"Craig","sequence":"additional","affiliation":[{"name":"Country Health Information System and Data Use Program, RTI International  Washington, DC USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2025,8,24]]},"reference":[{"key":"e_1_2_9_2_1","doi-asserted-by":"publisher","DOI":"10.1016\/S0140-6736(23)01249-7"},{"key":"e_1_2_9_3_1","unstructured":"World Health Organization \u201cWorld Malaria Report 2024 \u201d(2024) Geneva: WHO https:\/\/www.who.int\/teams\/global\u2010malaria\u2010programme\/reports\/world\u2010malaria\u2010report\u20102024."},{"key":"e_1_2_9_4_1","unstructured":"World Health Organization \u201cGlobal Technical Strategy for Malaria 2016\u20132030 2021 Update \u201d(2021) Geneva: WHO 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