Social, Behavioral, and Cultural factors of HIV in Malawi: Semi-Automated Systematic Review

Abstract

Background Demographic and sociobehavioral factors are strong drivers of HIV infection rates in sub-Saharan Africa. These factors are often studied in qualitative research but ignored in quantitative analyses. However, they provide in-depth insight into the local behavior and may help to improve HIV prevention. Objective To obtain a comprehensive overview of the sociobehavioral factors influencing HIV prevalence and incidence in Malawi, we systematically reviewed the literature using a newly programmed tool for automatizing part of the systematic review process. Methods Due to the choice of broad search terms (“HIV AND Malawi”), our preliminary search revealed many thousands of articles. We, therefore, developed a Python tool to automatically extract, process, and categorize open-access articles published from January 1, 1987 to October 1, 2019 in the PubMed, PubMed Central, JSTOR, Paperity, and arXiV databases. We then used a topic modelling algorithm to classify and identify publications of interest. Results Our tool extracted 22,709 unique articles; 16,942 could be further processed. After topic modelling, 519 of these were clustered into relevant topics, of which 20 were kept after manual screening. We retrieved 7 more publications after examining the references so that 27 publications were finally included in the review. Reducing the 16,942 articles to 519 potentially relevant articles using the software took 5 days. Several factors contributing to the risk of HIV infection were identified, including religion, gender and relationship dynamics, beliefs, and sociobehavioral attitudes. Conclusions Our software does not replace traditional systematic reviews, but it returns useful results to broad queries of open-access literature in under a week, without a priori knowledge. This produces a “seed dataset” of relevance that could be further developed. It identified known factors and factors that may be specific to Malawi. In the future, we aim to expand the tool by adding more social science databases and applying it to other sub-Saharan African countries.

Factors Associated with the Risk of HIV Infection among HIV-exposed Infants in Malawi: 2013-2020

“…The risk of HIV acquisition among infants exposed to HIV in our study was almost two times higher than that observed in South Africa [8] [9] but similar to other studies conducted in Malawi and settings India [10] [11] [16]. Consistent with other studies, the risk of HIV infection of the HEI was higher with older age at DNA-PCR sample collection [12].…”

“…Our findings also demonstrate considerable heterogeneity in risk of HIV infection among the HEI in Malawi. Several spatial epidemiological studies indicate spatial variation of diseases which could be attributed to social and cultural factors [14] [15] [16]. Generally, studies of HIV epidemiology in Malawi have been highly predominant in the districts in the southern region followed by the central and northern regions [13] [17].…”

Factors associated with the risk of HIV infection among HIV-exposed infants in Malawi: 2013–2020

“…The prevalence of HIV acquisition among infants exposed to HIV in our study was almost two times higher than that observed in South Africa 11 12 but similar to other studies conducted in Malawi and India. [13][14][15] Consistent with other studies, the prevalence of HIV infection of the HEI was higher with older age at DNA-PCR sample Open access collection. 16 With the high prevalence of HIV infection being observed among EID in the Northern Region of Malawi, it is imperative to consider the northern region with quality improvement projects aimed at bringing down the HIV infection risk among HEI.…”

“…Several spatial epidemiological studies indicate spatial variation of diseases which could be attributed to social and cultural factors. 15 18 19 Generally, studies of HIV epidemiology in Malawi have been highly predominant in the districts in the southern region, followed by the central and northern regions. 17 20 The spatial pattern of the risk of HIV infection would imply the need to target PMTCT interventions in the districts with high risk of paediatric HIV acquisition in order to improve the health of the children and the women.…”

Living Health Technology Assessment: Issues, Challenges and Opportunities

“…To identify the RCT studies without the requirement of manual screening, RobotSearch uses a high recall and validated machine learning classifier that is capable of ordering retrieved papers by study sample size and quality (i.e., risk of bias). Similar tools offer efficiency in the searching and study selection stages, where algorithms built in programmes such as Python can narrow down potentially relevant articles in fields where many thousands of articles are published (e.g., HIV [ 25 ]).…”