{"title":"Application of the UNAIDS Incidence Patterns Model to Determine the Distribution of New HIV Infection in Lagos State, Nigeria.","authors":"Toriola Femi-Adebayo, Monsurat Adeleke, Bisola Adebayo, Temitope Fadiya, Bukola Popoola, Opeyemi Ogundimu, Funmilade O Adepoju, Ayotomiwa Salawu, Oladipupo Fisher, Olusegun Ogboye, Leopold Zekeng","doi":"10.1177/23259582241238653","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Identifying patterns in the distribution of new HIV infections in the population is critical for HIV programmatic interventions. This study aimed to determine the distribution of New HIV infection by applying the incidence patterns mathematical model to data from Lagos state.</p><p><strong>Methods: </strong>The incidence patterns model (IPM) software is a mathematical model developed by UNAIDS to estimate the demographic and epidemic patterns of HIV infections. This model was adapted in Lagos state to predict the distribution of new HIV infections among specified risk groups in the next 12 months.</p><p><strong>Results: </strong>The IPM predicted a total HIV incidence of 37 cases per 100 000 individuals (3979 new infections) will occur among the 15 to 49 subpopulations. The results also showed that sero-concordant HIV-negative couples with external partners (29%), female sex workers (26%), men-having-sex-with-men (18%), and previously married females (6%) accounted for the majority of the estimated new HIV infections. Overall, key populations constitute almost half (48%) of the estimated number of new HIV infections.</p><p><strong>Conclusion: </strong>The study helped to identify the population groups contributing significantly to new HIV infections. Therefore, priority interventions should be focused on these groups.</p>","PeriodicalId":17328,"journal":{"name":"Journal of the International Association of Providers of AIDS Care","volume":"23 ","pages":"23259582241238653"},"PeriodicalIF":2.2000,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10956134/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of the International Association of Providers of AIDS Care","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1177/23259582241238653","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"INFECTIOUS DISEASES","Score":null,"Total":0}
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Abstract
Background: Identifying patterns in the distribution of new HIV infections in the population is critical for HIV programmatic interventions. This study aimed to determine the distribution of New HIV infection by applying the incidence patterns mathematical model to data from Lagos state.
Methods: The incidence patterns model (IPM) software is a mathematical model developed by UNAIDS to estimate the demographic and epidemic patterns of HIV infections. This model was adapted in Lagos state to predict the distribution of new HIV infections among specified risk groups in the next 12 months.
Results: The IPM predicted a total HIV incidence of 37 cases per 100 000 individuals (3979 new infections) will occur among the 15 to 49 subpopulations. The results also showed that sero-concordant HIV-negative couples with external partners (29%), female sex workers (26%), men-having-sex-with-men (18%), and previously married females (6%) accounted for the majority of the estimated new HIV infections. Overall, key populations constitute almost half (48%) of the estimated number of new HIV infections.
Conclusion: The study helped to identify the population groups contributing significantly to new HIV infections. Therefore, priority interventions should be focused on these groups.
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