Evidence map›Paper›PMID 42638710›Full record

ArticleFrontiers in tuberculosis2025

Optimizing use of data and evidence-related tools to complement routine surveillance systems for tuberculosis program planning.

Rachel M Fiorillo, Eveline Klinkenberg, Christina Braccio, Daniel Chin, Stavia Turyahabwe, Moses Arinaitwe, Razia Fatima, Taye Letta, Binh Hoa Nguyen, Aiban Ronoh and 10 more

Abstract read
In one paragraph

Article in Frontiers in tuberculosis, 2025. 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

20 authors.

Rachel M FiorilloInfectious Disease Department, CDC Foundation, Atlanta, GA, United States.
Eveline KlinkenbergConnect TB, The Hague, Netherlands.
Christina BraccioDivision of Global HIV and Tuberculosis, U.S. Centers for Disease Control and Prevention, Atlanta, GA, United States.
Daniel ChinGlobal Health, Gates Foundation, Seattle, WA, United States.
Stavia TuryahabweTuberculosis/Leprosy Control Division, Ministry of Health, Kampala, Uganda.
Moses ArinaitweKNCV TB Plus, The Hague, Netherlands.
Razia FatimaUnited Nations Office for Project Services, Copenhagen, Denmark.
Taye LettaNational Tuberculosis, Leprosy, and Other Lung Disease Prevention and Control Program, Ethiopian Ministry of Health, Addis Ababa, Ethiopia.
Binh Hoa NguyenVietnam National Tuberculosis Control Program, Ministry of Health, Hanoi, Vietnam.
Aiban RonohDivision of Tuberculosis and Lung Health, Ministry of Health, Nairobi, Kenya.
Charalambos SismanidisGlobal TB Programme, World Health Organization, Geneva, Switzerland.
Nnamdi B NwaneriThe Global Fund to Fight AIDS, Tuberculosis and Malaria, Geneva, Switzerland.
Kenneth G CastroHubert Department of Global Health and Department of Epidemiology, Emory University Rollins School of Public Health, Atlanta, GA, United States.
Kathy FiekertKNCV TB Plus, The Hague, Netherlands.
Fukushi MorishitaIntegrated Communicable Disease Unit, World Health Organization Regional Office for the Western Pacific, Manila, Philippines.
Suvanand SahuStop TB Partnership, Geneva, Switzerland.
Sevim AhmedovUnited States Agency for International Development, Washington, DC, United States.
Harry HauslerTB HIV Care, Cape Town, South Africa.
Anand DateDivision of Global HIV and Tuberculosis, U.S. Centers for Disease Control and Prevention, Atlanta, GA, United States.
Jennifer B HarrisDivision of Global HIV and Tuberculosis, U.S. Centers for Disease Control and Prevention, Atlanta, GA, United States.

Funding

Bill & Melinda Gates Foundation INV-006616
6 · The paper itself

Abstract

Background: Challenges and gaps with routine tuberculosis (TB) data and surveillance systems are well-known. To address them, numerous TB data and evidence-related tools (e.g. surveys, assessments) have been developed to help countries collect, analyze, and use TB-related data. The "TB Data Optimization Project" aimed to assess the use and usefulness of these tools and propose best practices. Methods: Phase one of this mixed-methods project included structured key informant interviews (KIIs) with TB data experts, literature review, and mapping tools' indicators and metrics. Phase two consisted of case studies in five countries (Ethiopia, Kenya, Pakistan, Uganda, and Vietnam). Structured KIIs and a use case discussion were conducted with TB program staff and partners in each country, and TB-related documents were reviewed. Phase three was an online survey for national TB programs. Qualitative data were recorded, transcribed, coded, and inductively analyzed. Quantitative data were analyzed descriptively. Findings were triangulated and summarized into key themes. Results: Seventy-two KIIs were conducted, 42 countries completed surveys, and 212 documents were reviewed. Six key themes emerged: usefulness, opportunities and challenges with planning and implementation, technical assistance and financial support, timing and coordination, motivating factors for implementation, and the role of tools in relation to routine data systems. The tools provide critical information and most were considered worth the investment. Challenges include suboptimal implementation of the recommendations from the tools, poor timing and coordination of implementation, and insufficient capacity building. A set of best practices was developed. Conclusion: While the long-term goal is to strengthen and integrate routine data systems, TB data tools currently play an important role in filling gaps. Findings from this project provide considerations for optimal use of TB data tools; however, there is still need for further guidance on selecting the most critical tools to fill gaps during TB programmatic and strategic planning.

Indexed as

data toolsdata utilizationprogram planningstrategic planningtuberculosis care cascadetuberculosis supplemental data

Identifiers

PMID42638710
PMCPMC13491421

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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.