Evidence map›Paper›PMID 33173893›Full record

ArticlemedRxiv : the preprint server for health sciences2020

Estimating the potential impact of COVID-19-related disruptions on HIV incidence and mortality among men who have sex with men in the United States: a modelling study.

Kate M Mitchell, Dobromir Dimitrov, Romain Silhol, Lily Geidelberg, Mia Moore, Albert Liu, Chris Beyrer, Kenneth H Mayer, Stefan Baral, Marie-Claude Boily

Open access · greenAbstract readPreprint
In one paragraph

Article in medRxiv : the preprint server for health sciences, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed, 8 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

10 authors at 5 institutions in 2 countries.

Kate M MitchellMRC Centre for Global Infectious Disease Analysis, School of Public Health, Imperial College London, London, United Kingdom.
Dobromir DimitrovVaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, Washington, United States.
Romain SilholMRC Centre for Global Infectious Disease Analysis, School of Public Health, Imperial College London, London, United Kingdom.
Lily GeidelbergMRC Centre for Global Infectious Disease Analysis, School of Public Health, Imperial College London, London, United Kingdom.
Mia MooreVaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, Washington, United States.
Albert LiuDepartment of Medicine, University of California San Francisco, San Francisco, California, United States.
Chris BeyrerDepartment of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, United States.
Kenneth H MayerThe Fenway Institute, Fenway Health, Boston, Massachusetts, United States.
Stefan BaralDepartment of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, United States.
Marie-Claude BoilyMRC Centre for Global Infectious Disease Analysis, School of Public Health, Imperial College London, London, United Kingdom.
Imperial College London · GBFred Hutch Cancer Center · USJohns Hopkins University · USHarvard University · USUniversity of California, San Francisco · US

Funding

SDMC: HPTN 084 Pregnancy SupplementUM1AI068617 · NIAID · FRED HUTCHINSON CANCER RESEARCH CENTER · PI Elizabeth Renata Brown, Deborah J Donnell · 2011 to 2026
$204.9M
Medical Research Council MC_PC_19012Medical Research Council MR/R015600/1NIAID NIH HHS UM1 AI068617
6 · The paper itself

Abstract

backgroundDuring the COVID-19 pandemic, gay and other men who have sex with men (MSM) in the United States (US) report similar or fewer sexual partners and reduced HIV testing and care access. Pre-exposure prophylaxis (PrEP) use has declined. We estimated the potential impact of COVID-19 on HIV incidence and mortality among US MSM.

methodsWe used a calibrated HIV transmission model for MSM in Baltimore, Maryland, and available data on COVID-19-related disruptions to predict impacts of data-driven reductions in sexual partners(0%,25%,50%), condom use(5%), HIV testing(20%), viral suppression(10%), PrEP initiations(72%), PrEP use(9%) and ART initiations(50%), exploring different disruption durations and magnitudes. We estimated the median (95% credible interval) change in cumulative new HIV infections and deaths among MSM over one and five years, compared with a scenario without COVID-19-related disruptions.

findingsA six-month 25% reduction in sexual partners among Baltimore MSM, without HIV service changes, could reduce new HIV infections by 12·2%(11·7,12·8%) and 3·0%(2·6,3·4%) over one and five years, respectively. In the absence of changes in sexual behaviour, the six-month data-driven disruptions to condom use, testing, viral suppression, PrEP initiations, PrEP use and ART initiations combined were predicted to increase new HIV infections by 10·5%(5·8,16·5%) over one year, and by 3·5%(2·1,5·4%) over five years. A 25% reduction in partnerships offsets the negative impact of these combined service disruptions on new HIV infections (overall reduction 3·9%(-1·0,7·4%), 0·0%(-1·4,0·9%) over one, five years, respectively), but not on HIV deaths (corresponding increases 11·0%(6·2,17·7%), 2·6%(1·5,4·3%)). The predicted impacts of reductions in partnerships or viral suppression doubled if they lasted 12 months or if disruptions were twice as large.

interpretationMaintaining access to ART and adherence support is of the utmost importance to minimise excess HIV-related mortality due to COVID-19 restrictions in the US, even if accompanied by reductions in sexual partnerships.

fundingNIH. RESEARCH IN CONTEXT:

Identifiers

PMID33173893
PMCPMC7654885
OpenAlexW3095904328

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.