Evidence map›Paper›PMID 41288194›Full record

ArticleMedical decision making : an international journal of the Society for Medical Decision Making2026

Estimating Productivity Losses per HIV Infection due to Premature HIV Mortality in the United States.

Md Hafizul Islam, Harrell W Chesson, Ruiguang Song, Angela B Hutchinson, Ram K Shrestha, Alex Viguerie, Paul G Farnham

Abstract read
In one paragraph

Article in Medical decision making : an international journal of the Society for Medical Decision Making, 2026. 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.

No citing paper in PubMed yet.

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

7 authors.

Md Hafizul IslamCenters for Disease Control and Prevention, National Center for HIV, Viral Hepatitis, STD, and TB Prevention, Atlanta, GA, USA.ORCID 0000-0002-1374-4362
Harrell W ChessonCenters for Disease Control and Prevention, National Center for HIV, Viral Hepatitis, STD, and TB Prevention, Atlanta, GA, USA.ORCID 0000-0002-6695-3141
Ruiguang SongCenters for Disease Control and Prevention, National Center for HIV, Viral Hepatitis, STD, and TB Prevention, Atlanta, GA, USA.
Angela B HutchinsonCenters for Disease Control and Prevention, National Center for HIV, Viral Hepatitis, STD, and TB Prevention, Atlanta, GA, USA.
Ram K ShresthaCenters for Disease Control and Prevention, National Center for HIV, Viral Hepatitis, STD, and TB Prevention, Atlanta, GA, USA.
Alex ViguerieCenters for Disease Control and Prevention, National Center for HIV, Viral Hepatitis, STD, and TB Prevention, Atlanta, GA, USA.
Paul G FarnhamCenters for Disease Control and Prevention, National Center for HIV, Viral Hepatitis, STD, and TB Prevention, Atlanta, GA, USA.

Funding

Intramural CDC HHS CC999999
6 · The paper itself

Abstract

BackgroundUpdated estimates of the productivity losses per HIV infection due to premature HIV mortality are needed to help quantify the economic burden of HIV and inform cost-effectiveness analyses.MethodsWe used the human capital approach to estimate the productivity loss due to HIV mortality per HIV infection in the United States, discounted to the time of HIV infection. We incorporated published data on age-specific annual productivity, life expectancy at HIV diagnosis, life-years lost from premature death among persons with HIV (PWH), the number of years from HIV infection to diagnosis, and the percentage of deaths in PWH attributable to HIV. For the base case, we used 2018 life expectancy data for all PWH in the United States. We also examined scenarios using life expectancy in 2010 and life expectancy for cohorts on antiretroviral therapy (ART). We conducted sensitivity analyses to understand the impact of key input parameters.ResultsWe estimated the base-case overall average productivity loss due to HIV mortality per HIV infection at $65,300 in 2022 US dollars. The base-case results showed a 45% decrease in the estimated productivity loss compared with the results when applying life expectancy data from 2010. Productivity loss was 83% lower for cohorts of PWH on ART compared with the base-case scenario. Results were sensitive to assumptions about percentage of deaths attributable to HIV and heterogeneity in age at death.ConclusionThis study provides valuable insights into the economic impact of HIV mortality, illustrating reductions in productivity losses over time due to advancements in treatments.HighlightsUpdated estimates of productivity losses per HIV infection due to premature HIV mortality can help assess the total economic burden of HIV in the United States.This study estimates productivity losses per HIV infection for overall, by sex, and by varying ages of HIV infection.Advancement in treatment has contributed to a significant reduction in productivity losses due to premature HIV mortality in the United States over the past decade.

Indexed as

Cost of IllnessEfficiencyHIV InfectionsMortality, PrematureAdultCost-Benefit AnalysisFemaleHumansLife ExpectancyMaleMiddle AgedUnited StatesARTHIVpremature HIV mortalityproductivity loss

Identifiers

PMID41288194
PMCPMC13133740

What OpenQuestion holds

Textmetadata
LicenceTDM
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.