Evidence map›Paper›PMID 32711500›Full record

ArticleBMC public health2020

Spatial analysis of factors associated with HIV infection in Malawi: indicators for effective prevention.

Jerry John Nutor, Henry Ofori Duah, Pascal Agbadi, Precious Adade Duodu, Kaboni W Gondwe

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in BMC public health, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 47 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
47citing papers in PubMed, 1 pooled it
1.5field-weighted citation impact, top 10% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

47 citing papers in PubMed, 1 synthesis or guideline pooled it, 75 citations in OpenAlex.

  1. Wealth, income and HIV in sub-Saharan Africa: a systematic review.Journal of the International AIDS Society · 2025
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors at 4 institutions in 3 countries.

Jerry John NutorDepartment of Family Health Care Nursing, School of Nursing, University of California, San Francisco, USA. jerry.nutor@ucsf.edu.ORCID http://orcid.org/0000-0002-7562-6281
Henry Ofori DuahResearch Department, FOCOS Orthopaedic Hospital, Accra, Ghana.
Pascal AgbadiDepartment of Nursing, Faculty of Allied Health Sciences, College of Health Sciences, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana.
Precious Adade DuoduEast Surrey Hospital, Canada Avenue, Redhill, Surrey, England, UK.
Kaboni W GondweCollege of Nursing, University of Wisconsin-Milwaukee, Milwaukee, WI, USA.
East Surrey Hospital · GBKwame Nkrumah University of Science and Technology · GHMedical College of Wisconsin · USUniversity of California, San Francisco · US

Funding

University of California, San Francisco Population Health and Health Equity Scholar program 7504575
6 · The paper itself

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.

Indexed as

Rural PopulationUrban PopulationAdolescentAdultAgedEpidemicsFemaleHealth SurveysHIV InfectionsHumansLogistic ModelsMalawiMaleMarital StatusMass ScreeningMiddle AgedGender, HIVPre-exposure prophylaxisRisk behaviorRural

Identifiers

PMID32711500
PMCPMC7382788
OpenAlexW3044308133

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.