Evidence map›Paper›PMID 35788400›Full record

ArticleJournal of clinical epidemiology2022

HIV suppression was maintained during the COVID-19 pandemic in Malawi: a program-level cohort study.

Thokozani Kalua, Matthias Egger, Andreas Jahn, Tiwonge Chimpandule, Rose Kolola, Nanina Anderegg

Open access · hybridAbstract read
In one paragraph

Article in Journal of clinical epidemiology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed, 2 pooled it
2.0field-weighted citation impact, top 12% 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

13 citing papers in PubMed, 2 syntheses or guidelines pooled it, 21 citations in OpenAlex.

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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

6 authors at 2 institutions in 4 countries.

Thokozani KaluaInstitute of Social and Preventive Medicine, University of Bern, Bern, Switzerland; Department of HIV and AIDS, Malawi Ministry of Health, Lilongwe, Malawi.
Matthias EggerInstitute of Social and Preventive Medicine, University of Bern, Bern, Switzerland; Centre for Infectious Disease Epidemiology and Research, Faculty of Health Sciences, University of Cape Town, Cape Town, South Africa; Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK.
Andreas JahnDepartment of HIV and AIDS, Malawi Ministry of Health, Lilongwe, Malawi; I-TECH Malawi, Lilongwe, Malawi.
Tiwonge ChimpanduleDepartment of HIV and AIDS, Malawi Ministry of Health, Lilongwe, Malawi; I-TECH Malawi, Lilongwe, Malawi.
Rose KololaDepartment of HIV and AIDS, Malawi Ministry of Health, Lilongwe, Malawi.
Nanina AndereggInstitute of Social and Preventive Medicine, University of Bern, Bern, Switzerland; Centre for Infectious Disease Epidemiology and Research, Faculty of Health Sciences, University of Cape Town, Cape Town, South Africa. Electronic address: nanina.anderegg@ispm.unibe.ch.
Public Health Institute of Malawi · MWUniversity of Bern · CH

Funding

Observational Antiretroviral Studies In Southern Africa (OASIS) CollaborationU01AI069924 · NIAID · UNIVERSITAT BERN · PI Cleophas Chimbetete, Mary-Ann Davies · 2006 to 2026
$55.9M
NIAID NIH HHS U01 AI069924
6 · The paper itself

Abstract

BACKGROUND AND

objectivesMeasures introduced to reduce the spread of SARS-CoV-2 by the Malawi government and the national HIV care program might have compromised treatment outcomes of patients living with HIV on antiretroviral therapy (ART). We studied viral load (VL) outcomes before and during the COVID-19 epidemic in Malawi.

methodsIn this population-based cohort study, we included all routine VL measurements collected from July 2019 to December 2020 in about 650 ART clinics in Malawi. We examined differences between pandemic periods (before/during COVID-19) for i) VL monitoring, and ii) VL suppression (VLS: <1,000 copies/ml). For i) we studied the number of VL measurements over time and assessed predictors of missed measurements before and during COVID-19 in logistic regression models. For ii) we estimated the odds of VLS before and during the COVID-19 epidemic stratified by treatment regimen using generalized estimation equations adjusted for age, sex, time on ART, and type of biological sample. We imputed missing treatment regimens by population-calibrated multiple imputation.

resultsWe included 607,894 routine VL samples from 556,281 patients. VL testing declined during COVID-19 (243,729; 40%) compared to before COVID-19 (365,265; 60%), but predictors of missing tests were similar in the two periods. VLS rates increased slightly from 93% before to 94% during COVID-19. Compared to before COVID-19, the odds of VLS increased during COVID-19 for patients on protease inhibitor-based (PI) regimens (adjusted odds ratio [aOR] 1.22, 95% CI: 0.99-1.49) and for patients on integrase strand transfer inhibitor-based (INSTI) regimens (aOR 1.10, 95% CI: 1.03-1.17). There was no difference in VLS between the two periods among patients on nonnucleoside reverse transcriptase inhibitor-based (NNRTI) regimens. VLS varied by age, sex, regimen, and duration on ART, ranging from 45.1% (95% CI 40.3-50.0%) to 97.2% (95% CI 96.9-97.4%).

conclusionThere was a significant decline in VL monitoring during COVID-19, but we did not find clear evidence that the pandemic reduced VL suppression rates. Routine scheduled VL monitoring, targeted adherence support, and timely regimen switches for patients with treatment failure remain critical to improving VLS.

Indexed as

Anti-HIV AgentsCOVID-19HIV InfectionsCohort StudiesHumansMalawiPandemicsSARS-CoV-2Viral LoadAnti-HIV AgentsARTCOVID-19HIVMalawiSARS-CoV-2Suppression of HIV replication

Identifiers

PMID35788400
PMCPMC9249434
OpenAlexW4283775972

What OpenQuestion holds

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Registered trials

None linked

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.