{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,17]],"date-time":"2026-07-17T06:04:50Z","timestamp":1784268290326,"version":"3.55.0"},"reference-count":11,"publisher":"Wiley","issue":"2","license":[{"start":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T00:00:00Z","timestamp":1780272000000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T00:00:00Z","timestamp":1780272000000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Public Health Challenges"],"published-print":{"date-parts":[[2026,6]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:p>\n                    This study presents a novel, context\u2010specific mathematical modeling framework for predicting and monitoring COVID\u201019 transmission in Rwanda, addressing the increasing demand for integrated and data\u2010driven public health decision\u2010support tools. The model incorporates localized epidemiological dynamics, transmission pathways, and major intervention measures, including lockdowns, vaccination, quarantine, and home\u2010based care, which is considered a critical factor influencing disease transmission. Using a system of differential equations, the framework models transition among infected, home\u2010based care, hospitalized, recovered, and deceased populations. The model was calibrated and validated using Rwanda's national COVID\u201019 surveillance data collected between March 2020 and December 2022, covering multiple epidemic waves and intervention phases. Calibration utilized time\u2010series data on confirmed cases, active infections, hospitalizations, intensive care unit admissions, recoveries, and mortality. Detailed home\u2010based care records improved the estimation of transmission and recovery parameters. Parameter optimization was performed through least\u2010squares fitting and cross\u2010validation techniques. Model performance was assessed using the root mean square error (RMSE) and the coefficient of determination (\n                    <jats:italic>R<\/jats:italic>\n                    <jats:sup>2<\/jats:sup>\n                    ) metrics. Validation through out\u2010of\u2010sample predictions demonstrated strong accuracy in capturing infection trends and healthcare burden. An interactive dashboard complements the framework by enabling real\u2010time analytics, forecasting, and evidence\u2010based public health decision\u2010making.\n                  <\/jats:p>","DOI":"10.1002\/puh2.70287","type":"journal-article","created":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T11:49:39Z","timestamp":1780314579000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Integration of Developed Mathematical Model for Predicting and Monitoring the Spread of Epidemics and Pandemics: The Case of COVID\u201019 in Rwanda"],"prefix":"10.1002","volume":"5","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2464-2377","authenticated-orcid":false,"given":"Jean Marie","family":"Ntaganda","sequence":"first","affiliation":[{"name":"Department of Mathematics School of Science College of Science and Technology University of Rwanda  Kigali Rwanda"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Innocent","family":"Ngaruye","sequence":"additional","affiliation":[{"name":"Department of Mathematics School of Science College of Science and Technology University of Rwanda  Kigali Rwanda"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Denis","family":"Ndanguza","sequence":"additional","affiliation":[{"name":"Department of Mathematics School of Science College of Science and Technology University of Rwanda  Kigali Rwanda"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2026,6,1]]},"reference":[{"key":"e_1_2_10_2_1","doi-asserted-by":"publisher","DOI":"10.1038\/nature06536"},{"key":"e_1_2_10_3_1","doi-asserted-by":"publisher","DOI":"10.1186\/s12879\u2010018\u20103443\u20108"},{"key":"e_1_2_10_4_1","doi-asserted-by":"publisher","DOI":"10.5334\/aogh.3172"},{"key":"e_1_2_10_5_1","doi-asserted-by":"publisher","DOI":"10.1007\/s41745\u2010020\u201000200\u20106"},{"key":"e_1_2_10_6_1","first-page":"99","article-title":"Compartmental Mathematical Modelling of Dynamic Transmission of COVID\u201019 in Rwanda","volume":"6","author":"Mpinganzima L.","year":"2023","journal-title":"International Journal of Infectious Diseases: Regions"},{"key":"e_1_2_10_7_1","doi-asserted-by":"publisher","DOI":"10.1186\/s40537\u2010025\u201001245\u2010z"},{"key":"e_1_2_10_8_1","doi-asserted-by":"publisher","DOI":"10.26577\/JMMCS.2022.v116.i4.08"},{"key":"e_1_2_10_9_1","doi-asserted-by":"publisher","DOI":"10.7717\/peerj\u2010cs.2874"},{"key":"e_1_2_10_10_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41598\u2010022\u201024967"},{"key":"e_1_2_10_11_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41598\u2010023\u201033499\u2010z"},{"key":"e_1_2_10_12_1","doi-asserted-by":"publisher","DOI":"10.3390\/bioengineering11090906"}],"container-title":["Public Health Challenges"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/pdf\/10.1002\/puh2.70287","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/full-xml\/10.1002\/puh2.70287","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/pdf\/10.1002\/puh2.70287","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,7,17]],"date-time":"2026-07-17T05:11:27Z","timestamp":1784265087000},"score":1,"resource":{"primary":{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/10.1002\/puh2.70287"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,6]]},"references-count":11,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2026,6]]}},"alternative-id":["10.1002\/puh2.70287"],"URL":"https:\/\/doi.org\/10.1002\/puh2.70287","archive":["Portico"],"relation":{},"ISSN":["2769-2450","2769-2450"],"issn-type":[{"value":"2769-2450","type":"print"},{"value":"2769-2450","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,6]]},"assertion":[{"value":"2025-07-31","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2026-05-14","order":2,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2026-06-01","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}],"article-number":"e70287"}}