Abstract
BackgroundThe objective of this study was to model the predictors of HIV prevalence in Malawi through a complex sample logistic regression and spatial mapping approach using the national Demographic and Health Survey datasets.MethodsWe conducted a secondary data analysis using the 2015–2016 Malawi Demographic and Health Survey and AIDS Indicator Survey. The analysis was performed in three stages while incorporating population survey sampling weights to: i) interpolate HIV data, ii) identify the spatial clusters with the high prevalence of HIV infection, and iii) perform a multivariate complex sample logistic regression.ResultsIn all, 14,779 participants were included in the analysis with an overall HIV prevalence of 9% (7.0% in males and 10.8% in females). The highest prevalence was found in the southern region of Malawi (13.2%), and the spatial interpolation revealed that the HIV epidemic is worse at the south-eastern part of Malawi. The districts in the high HIV prevalent zone of Malawi are Thyolo, Zomba, Mulanje, Phalombe and Blantyre. In central and northern region, the district HIV prevalence map identified Lilongwe in the central region and Karonga in the northern region as districts that equally deserve attention. People residing in urban areas had a 2.2 times greater risk of being HIV-positive compared to their counterparts in the rural areas (AOR = 2.16; 95%CI = 1.57–2.97). Other independent predictors of HIV prevalence were gender, age, marital status, number of lifetime sexual partners, extramarital partners, the region of residence, condom use, history of STI in the last 12 months, and household wealth index. Disaggregated analysis showed in-depth sociodemographic regional variations in HIV prevalence.ConclusionThese findings identify high-risk populations and regions to be targeted for Pre-Exposure Prophylaxis (PrEP) campaigns, HIV testing, treatment and education to decrease incidence, morbidity, and mortality related to HIV infection in Malawi.
Highlights
The objective of this study was to model the predictors of Human Immunodeficiency Virus (HIV) prevalence in Malawi through a complex sample logistic regression and spatial mapping approach using the national Demographic and Health Survey datasets
People residing in urban areas had a 2.2 times greater risk of being HIV-positive compared to their counterparts in the rural areas (AOR = 2.16, 95%confidence intervals (CI) = 1.57–2.97)
We examined the predictors of HIV infection in Malawi through a complex sample logistic regression and spatial mapping approach using the 2015–2016 Malawi Demographic and Health Survey (2016 MDHS) data
Summary
The objective of this study was to model the predictors of HIV prevalence in Malawi through a complex sample logistic regression and spatial mapping approach using the national Demographic and Health Survey datasets. According to the World Health Organization (WHO), out of the 36.9 million people living with HIV in 2017, more than half (19.6 million) live in sub-Saharan Africa [1]. Eastern and southern Africa are some of the regions badly affected by HIV [5]. According to the Joint United Nations Program on HIV/AIDS, the HIV prevalence among adults in eastern and southern Africa was approximately 6% in 2018, with females disproportionately affected than males [6]. A low-income country in southeast Africa, has one of the highest HIV prevalence rates among adults—estimated at 9%—with about 38,000 people newly diagnosed with HIV in 2018 [5]
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