Evidence map›Paper›PMID 34713620›Full record

ArticleJournal of the International AIDS Society2021

Changes in HIV treatment differentiated care uptake during the COVID-19 pandemic in Zambia: interrupted time series analysis.

Youngji Jo, Sydney Rosen, Karla Therese L Sy, Bevis Phiri, Amy N Huber, Muya Mwansa, Hilda Shakwelele, Prudence Haimbe, Mpande M Mwenechanya, Priscilla Lumano-Mulenga and 1 more

Open access · goldAbstract read
In one paragraph

Article in Journal of the International AIDS Society, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
4.7field-weighted citation impact, top 5% 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, 17 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

11 authors at 5 institutions in 4 countries.

Youngji JoSection of Infectious Diseases, Department of Medicine, Boston Medical Center, Boston, Massachusetts, USA.
Sydney RosenDepartment of Global Health, Boston University School of Public Health, Boston, Massachusetts, USA.ORCID 0000-0002-6560-2964
Karla Therese L SyDepartment of Global Health, Boston University School of Public Health, Boston, Massachusetts, USA.
Bevis PhiriClinton Health Access Initiative, Lusaka, Zambia.
Amy N HuberHealth Economics and Epidemiology Research Office, Department of Internal Medicine, School of Clinical Medicine, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa.
Muya MwansaMinistry of Health, Lusaka, Zambia.
Hilda ShakweleleClinton Health Access Initiative, Lusaka, Zambia.
Prudence HaimbeClinton Health Access Initiative, Lusaka, Zambia.
Mpande M MwenechanyaThe Centre for Infectious Disease Research in Zambia, Lusaka, Zambia.
Priscilla Lumano-MulengaMinistry of Health, Lusaka, Zambia.
Brooke E NicholsDepartment of Global Health, Boston University School of Public Health, Boston, Massachusetts, USA.ORCID 0000-0003-4682-4999
Boston University · USMinistry of Health · ZMBoston Medical Center · USCentre for Infectious Disease Research in Zambia · ZMUniversity of the Witwatersrand · ZA

Funding

BU Clinical HIV/AIDS Research Training Program (BU-CHART)T32AI052074 · NIAID · BOSTON UNIVERSITY MEDICAL CAMPUS · PI Benjamin P. Linas · 2003 to 2026
$6.7M
Optimal Medication Dispensing for People Living with HIV with and without Other Chronic Diseases in Zambia: A Mathematical ModelF32MH128120 · NIMH · BOSTON MEDICAL CENTER · PI JO, YOUNGJI · 2021 to 2022
$150k
NIAID NIH HHS T32 AI052074NIMH NIH HHS F32 MH128120
6 · The paper itself

Abstract

introductionDifferentiated service delivery (DSD) models aim to improve the access of human immunodeficiency virus treatment on clients and reduce requirements for facility visits by extending dispensing intervals. With the advent of the COVID-19 pandemic, minimising client contact with healthcare facilities and other clients, while maintaining treatment continuity and avoiding loss to care, has become more urgent, resulting in efforts to increase DSD uptake. We assessed the extent to which DSD coverage and antiretroviral treatment (ART) dispensing intervals have changed during the COVID-19 pandemic in Zambia.

methodsWe used client data from Zambia's electronic medical record system (SmartCare) for 737 health facilities, representing about three-fourths of all ART clients nationally. We compared the numbers and proportional distributions of clients enrolled in DSD models in the 6 months before and 6 months after the first case of COVID-19 was diagnosed in Zambia in March 2020. Segmented linear regression was used to determine whether the outbreak of COVID-19 in Zambia further accelerated the increase in DSD scale-up. RESULTS AND DISCUSSION: Between September 2019 and August 2020, 181,317 clients aged 15 or older (81,520 and 99,797 from 1 September 2019 to 1 March 2020 and from 1 March to 31 August 2020, respectively) enrolled in DSD models in Zambia. Overall participation in all DSD models increased over the study period, but uptake varied by model. The rate of acceleration increased in the second period for home ART delivery (152%),

conclusionsParticipation in DSD models for stable ART clients in Zambia increased after the advent of COVID-19, but dispensing intervals diminished. Eliminating obstacles to longer dispensing intervals, including those related to supply chain management, should be prioritized to achieve the expected benefits of DSD models and minimize COVID-19 risk.

Indexed as

Anti-HIV AgentsCOVID-19HIV InfectionsHumansInterrupted Time Series AnalysisPandemicsSARS-CoV-2ZambiaAnti-HIV Agentsantiretroviral treatmentCOVID-19differentiated service deliveryHIV service deliverymulti-month dispensingZambia

Identifiers

PMID34713620
PMCPMC8554218
OpenAlexW3208208822

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.