{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,26]],"date-time":"2026-06-26T05:20:37Z","timestamp":1782451237681,"version":"3.54.5"},"reference-count":80,"publisher":"BMJ","issue":"3","license":[{"start":{"date-parts":[[2025,3,27]],"date-time":"2025-03-27T00:00:00Z","timestamp":1743033600000},"content-version":"unspecified","delay-in-days":26,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":["bmj.com"],"crossmark-restriction":true},"short-container-title":["BMJ Open"],"accepted":{"date-parts":[[2025,2,28]]},"published-print":{"date-parts":[[2025,3]]},"abstract":"<jats:sec>\n                  <jats:title>Objective<\/jats:title>\n                  <jats:p>Malaria is a major public health concern in most developing countries, with children under 5 years being mainly at risk. We investigated the contribution of individual and community-level covariates to the risk of malaria infection (treatment with artemisinin-based combination therapy for fever or tested positive for malaria via a rapid diagnostic test within 2 weeks prior to the survey) in children under 5 years in Ghana.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Design<\/jats:title>\n                  <jats:p>Population-based secondary cross-sectional study on the 2019 Ghana Malaria Indicator Survey<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Setting<\/jats:title>\n                  <jats:p>Ghana.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Participants and methods<\/jats:title>\n                  <jats:p>Secondary malaria data on 3004 mothers and their children under 5 years from the recent 2019 Ghana Malaria Indicator Survey were analysed. Bayesian multilevel modelling under Hamiltonian Monte Carlo is applied to malaria data.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Results<\/jats:title>\n                  <jats:p>The results indicate a weighted malaria prevalence of 29.7% (95% CI: 0.28 to 0.31) among children under 5, and nearly 10% (8.9%) of the risk of malaria infection significantly varied by community differences. The average annual rainfall positively correlates with the prevalence of malaria in a community, while temperature and the built-population index inversely influence it. At the cluster level, the average annual rainfall significantly increased the risk of malaria infection among children under 5 years (adjusted OR (aOR)=17.46, 95% CrI: 1.86 to 167.34). Malaria infections among children under 5 are attributed to household\/individual and community-level characteristics. Children from rich households (aOR=0.66, 95% CrI: 0.50 to 0.87), who sleep under insecticide-treated nets (ITNs) (aOR=0.79, 95% CrI: 0.65 to 0.95) and are not anaemic have significantly reduced the risk of malaria infection than those from poor households, children with severe anaemia and those who do not sleep under ITNs at night. Children under 5 years from Gurma (aOR=1.82, 95% CrI: 1.92 to 2.86) ethnic backgrounds are linked to a high risk of contracting malaria, while those from the Mole-Dagbani (aOR=0.70, 95% CrI: 0.51 to 0.98) and Grusi (aOR=0.55, 95% CrI: 0.32 to 0.93) ethnic groups have significantly reduced the risk of malaria infection. All other considered factors were not significantly associated with malaria risk among children under 5 years in this study.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Conclusion<\/jats:title>\n                  <jats:p>Malaria remains a serious health burden to children under 5 years. These findings call for individual and community-level measures, including improved sanitation and preventive education campaigns, to help reduce malaria infections among children under 5 in Ghana, to mitigate malaria infections among children under 5 in Ghana, thereby promoting their health and quality of life (Sustainable Development Goal 3).<\/jats:p>\n               <\/jats:sec>","DOI":"10.1136\/bmjopen-2024-088910","type":"journal-article","created":{"date-parts":[[2025,3,28]],"date-time":"2025-03-28T04:04:06Z","timestamp":1743134646000},"page":"e088910","update-policy":"https:\/\/doi.org\/10.1136\/crossmarkpolicy","source":"Crossref","is-referenced-by-count":5,"title":["Malaria prevalence dynamics and risk covariates among children under 5 in Ghana: insights from a Bayesian multilevel approach"],"prefix":"10.1136","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3140-2649","authenticated-orcid":false,"given":"Killian Asampana","family":"Asosega","sequence":"first","affiliation":[{"name":"Department of Statistics and Actuarial Science, Kwame Nkrumah University of Science and Technology, Kumasi, Ashanti Region, Ghana"},{"name":"Department of Mathematics and Statistics, University of Energy and Natural Resources, Sunyani, Ghana"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Atinuke Olusola","family":"Adebanji","sequence":"additional","affiliation":[{"name":"Department of Statistics and Actuarial Science, Kwame Nkrumah University of Science and Technology, Kumasi, Ashanti Region, Ghana"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Eric Nimako","family":"Aidoo","sequence":"additional","affiliation":[{"name":"Department of Statistics and Actuarial Science, Kwame Nkrumah University of Science and Technology, Kumasi, Ashanti Region, Ghana"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ellis","family":"Owusu-Dabo","sequence":"additional","affiliation":[{"name":"Department of Global and International Health, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0195-225X","authenticated-orcid":false,"given":"Kassim","family":"Tawiah","sequence":"additional","affiliation":[{"name":"Department of Statistics and Actuarial Science, Kwame Nkrumah University of Science and Technology, Kumasi, Ashanti Region, Ghana"},{"name":"Department of Mathematics and Statistics, University of Energy and Natural Resources, Sunyani, Ghana"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"239","published-online":{"date-parts":[[2025,3,27]]},"reference":[{"key":"2025101814462062000_15.3.e088910.1","unstructured":"W.H. 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