Evidence map›Paper›PMID 40228857›Full record

ArticleBMJ open2025

Tuberculosis service delivery challenges and their mitigations during the COVID-19 pandemic in Tanzania: a qualitative study.

Doreen Pamba, Erica Samson Sanga, Wiston William, Happiness Mvungi, Hamim Omary, Theresia Setebe, Willyhelmina Olomi, Chacha Mangu, Issa Sabi, Robert Balama and 5 more

Abstract read
In one paragraph

Article in BMJ open, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

15 authors.

Doreen PambaResearch Programs, National Institute for Medical Research-Mbeya Medical Research Center, Mbeya, Tanzania dpamba@nimr-mmrc.org.ORCID http://orcid.org/0000-0002-6822-5682
Erica Samson SangaNational Institute for Medical Research-Mwanza Medical Research Center, Mwanza, Tanzania.ORCID http://orcid.org/0000-0002-1764-545X
Wiston WilliamNational Institute for Medical Research-Mbeya Medical Research Center, Mbeya, Tanzania.
Happiness MvungiKibong'oto Infectious Diseases Hospital, Sanya Juu, Tanzania.
Hamim OmaryNational Tuberculosis and Leprosy Control Programme, Dodoma, Tanzania.
Theresia SetebeNational Institute for Medical Research-Mwanza Medical Research Center, Mwanza, Tanzania.
Willyhelmina OlomiNational Institute for Medical Research-Mbeya Medical Research Center, Mbeya, Tanzania.
Chacha ManguNational Institute for Medical Research-Mbeya Medical Research Center, Mbeya, Tanzania.
Issa SabiNational Institute for Medical Research-Mbeya Medical Research Center, Mbeya, Tanzania.
Robert BalamaNational Tuberculosis and Leprosy Control Programme, Dodoma, Tanzania.
Emmanuel MatechiNational Tuberculosis and Leprosy Control Programme, Dodoma, Tanzania.
Riziki KisongaNational Tuberculosis and Leprosy Control Programme, Dodoma, Tanzania.
Allan TarimoNational Tuberculosis and Leprosy Control Programme, Dodoma, Tanzania.
Nyanda Elias NtinginyaNational Institute for Medical Research-Mbeya Medical Research Center, Mbeya, Tanzania.
Lucas MagangaNational Institute for Medical Research-Mbeya Medical Research Center, Mbeya, Tanzania.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo describe challenges posed by COVID-19 on tuberculosis (TB) commodity supply, care cascade, active case finding and responses taken by healthcare workers (HCWs) and community health workers (CHWs) during the first year of the pandemic (March 2020 to February 2021).

designA qualitative descriptive study involving 25 in-depth interviews and 10 focus group discussions conducted in July 2022.

setting37 TB treatment facilities were purposively selected from seven regions due to high TB case notifications in 2019 and their provision of TB and COVID-19 services during the first year of the pandemic (March 2020 to February 2021).

participantsPurposive selection of 58 HCWs and 55 CHWs who provided TB services in the first year of the COVID-19 pandemic.

resultsHCWs reported unusual stockouts and delayed receipt of GeneXpert cartridges and sputum containers. TB services faced a decline in client attendance, as clients were hesitant to undergo TB screening, sputum sample collection and contact tracing due to fear of contracting or being diagnosed with COVID-19 and subsequently being quarantined. To mitigate these challenges, HCWs used alternative containers for sputum sample collection, optimised GeneXpert cartridge use by prioritising GeneXpert testing for TB risk groups and diagnosed TB by microscopy, chest X-ray and sputum pooling method. Moreover, they extended drug refill schedules to minimise the risk of contracting COVID-19 in clinics. CHWs used mobile communication for client tracing and focused household visits on TB risk groups.

conclusionCOVID-19 disrupted TB commodity availability and TB treatment-seeking behaviour. Adaptations like multi-month drug refills and optimised GeneXpert use supported the TB healthcare system's resilience. While these adaptations offer valuable insights for strengthening TB service delivery, their effectiveness and sustainability require further evaluation. Thus, prospective studies could clarify their long-term impact. National Tuberculosis Program could consider adapting these practices postpandemic, with appropriate modifications to suit different contexts.

Indexed as

COVID-19Delivery of Health CareTuberculosisAdultCommunity Health WorkersContact TracingFemaleFocus GroupsHealth PersonnelHumansMaleMiddle AgedQualitative ResearchSARS-CoV-2TanzaniaCOVID-19Health ServicesQUALITATIVE RESEARCHTuberculosis

Identifiers

PMID40228857
PMCPMC11997816

What OpenQuestion holds

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LicenceCC BY-NC
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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.