Evidence map›Paper›PMID 33428611›Full record

ArticlePLoS medicine2021

Estimating HIV pre-exposure prophylaxis need and impact in Malawi, Mozambique and Zambia: A geospatial and risk-based analysis.

Dominik Stelzle, Peter Godfrey-Faussett, Chuan Jia, Obreniokibo Amiesimaka, Mary Mahy, Delivette Castor, Ioannis Hodges-Mameletzis, Lastone Chitembo, Rachel Baggaley, Shona Dalal

Abstract read
In one paragraph

Article in PLoS medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
–field-weighted citation impact
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

12 citing papers in PubMed.

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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

10 authors.

Dominik StelzleCenter for Global Health, Department of Neurology, Technical University, Munich, Germany.ORCID 0000-0001-6743-2818
Peter Godfrey-FaussettStrategic Information Department, UNAIDS, Geneva, Switzerland.
Chuan JiaGlobal HIV, Hepatitis and STIs Programmes, World Health Organization, Geneva, Switzerland.
Obreniokibo AmiesimakaCenter for Global Health, Department of Neurology, Technical University, Munich, Germany.
Mary MahyStrategic Information Department, UNAIDS, Geneva, Switzerland.
Delivette CastorDepartment of Medicine, Division of Infectious Diseases, Columbia University Irving Medical Center, New York, New York, United States of America.ORCID 0000-0002-0988-9489
Ioannis Hodges-MameletzisGlobal HIV, Hepatitis and STIs Programmes, World Health Organization, Geneva, Switzerland.
Lastone ChitemboWorld Health Organization, Lusaka, Zambia.
Rachel BaggaleyGlobal HIV, Hepatitis and STIs Programmes, World Health Organization, Geneva, Switzerland.
Shona DalalGlobal HIV, Hepatitis and STIs Programmes, World Health Organization, Geneva, Switzerland.

Funding

PEPFARWorld Health Organization 001
6 · The paper itself

Abstract

backgroundPre-exposure prophylaxis (PrEP), a WHO-recommended HIV prevention method for people at high risk for acquiring HIV, is being increasingly implemented in many countries. Setting programmatic targets, particularly in generalised epidemics, could incorporate estimates of the size of the population likely to be eligible for PrEP using incidence-based thresholds. We estimated the proportion of men and women who would be eligible for PrEP and the number of HIV infections that could be averted in Malawi, Mozambique, and Zambia using prioritisation based on age, sex, geography, and markers of risk. METHODS AND

findingsWe analysed the latest nationally representative Demographic and Health Surveys (DHS) of Malawi, Mozambique, and Zambia to determine the proportion of adults who report behavioural markers of risk for HIV infection. We used prevalence ratios (PRs) to quantify the association of these factors with HIV status. Using a multiplier method, we combined these proportions with the number of new HIV infections by district, derived from district-level modelled HIV estimates. Based on these numbers, different scenarios were analysed for the minimum number of person-years on PrEP needed to prevent 1 HIV infection (NNP). An estimated total of 38,000, 108,000, and 46,000 new infections occurred in Malawi, Mozambique, and Zambia in 2016, corresponding with incidence rates of 0.43, 0.63, and 0.57 per 100 person-years. In these countries, 9%-20% of new infections occurred among people with a sexually transmitted infection (STI) in the past 12 months and 40%-42% among people with either an STI or a non-regular sexual partner (NP) in the past 12 months (STINP). The models estimate that around 50% of new infections occurred in districts with incidence rates ≥1.0% in Mozambique and Zambia and ≥0.5% in Malawi. In Malawi, Mozambique, and Zambia, 35.1%, 21.9%, and 12.5% of the population live in these high-incidence districts. In the most parsimonious scenario, if women aged 15-34 years and men 20-34 years with an STI in the past 12 months living in high-incidence districts were to take PrEP, it would take a minimum of 65.8 person-years on PrEP to avert 1 HIV infection per year in Malawi, 35.2 in Mozambique, and 16.4 in Zambia. Our findings suggest that 3,300, 5,200, and 1,700 new infections could be averted per year in the 3 countries, respectively. Limitations of our study are that these values are based on modelled estimates of HIV incidence and self-reported behavioural risk factors from national surveys.

conclusionsA large proportion of new HIV infections in these 3 African countries were estimated to occur among people who had either an STI or an NP in the past year, providing a straightforward means to set PrEP targets. Greater prioritisation of PrEP by district, sex, age, and behavioural risk factors resulted in lower NNPs thereby increasing PrEP cost-effectiveness, but also diminished the overall impact on reducing new infections.

Indexed as

Pre-Exposure ProphylaxisAdultAnti-HIV AgentsFemaleGeographic Information SystemsHIV InfectionsHumansIncidenceMalawiMaleMozambiquePrevalenceRiskRisk AssessmentSexually Transmitted DiseasesZambiaAnti-HIV Agents

Identifiers

PMID33428611
PMCPMC7799816

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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.