Evidence map›Paper›PMID 38341211›Full record

Observational studyBMJ open2024

Enhanced active case finding of drug-resistant tuberculosis in Namibia: a protocol for the hotspots, hospitals, and households (H3TB) study.

Olga Shavuka, Etuhole Iipumbu, Lorraine Boois, Gunar Günther, Graeme Hoddinott, Hsien-Ho Lin, Emmanuel Nepolo, Stefan Niemann, Nunurai Ruswa, James Seddon and 1 more

Abstract readObservational Study
In one paragraph

Observational study in BMJ open, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

11 authors.

Olga ShavukaDepartment of Human Biological and Translational Medical Sciences, University of Namibia, Windhoek, Khomas, Namibia.
Etuhole IipumbuDepartment of Human Biological and Translational Medical Sciences, University of Namibia, Windhoek, Khomas, Namibia.
Lorraine BooisDepartment of Human Biological and Translational Medical Sciences, University of Namibia, Windhoek, Khomas, Namibia.
Gunar GüntherDepartment of Human Biological and Translational Medical Sciences, University of Namibia, Windhoek, Khomas, Namibia.
Graeme HoddinottDesmond Tutu TB Centre, Department of Pediatrics and Child Health, Stellenbosch University Faculty of Medicine and Health Sciences, Cape Town, Western Cape, South Africa.ORCID 0000-0001-5915-8126
Hsien-Ho LinNational Taiwan University, Taipei, Taiwan.
Emmanuel NepoloDepartment of Human Biological and Translational Medical Sciences, University of Namibia, Windhoek, Khomas, Namibia.
Stefan NiemannDepartment of Human Biological and Translational Medical Sciences, University of Namibia, Windhoek, Khomas, Namibia.
Nunurai RuswaNational Tuberculosis and Leprosy Programme (NTLP), Windhoek, Namibia.
James SeddonDesmond Tutu TB Centre, Department of Pediatrics and Child Health, Stellenbosch University Faculty of Medicine and Health Sciences, Cape Town, Western Cape, South Africa.
Mareli M ClaassensDepartment of Human Biological and Translational Medical Sciences, University of Namibia, Windhoek, Khomas, Namibia mcla@sun.ac.za.ORCID 0000-0002-5927-284X

Funding

Medical Research Council MR/T008814/1
6 · The paper itself

Abstract

introductionNamibia is a high tuberculosis (TB)-burden country with an estimated incidence of 460/100 000 (around 12 000 cases) per year. Approximately 4.5% of new cases and 7.9% of previously treated TB cases are multidrug resistant (MDR) and 47% of patients with MDR-TB are HIV coinfected. Published data suggest a clustering of MDR-TB transmission in specific areas. Identifying transmission clusters is key to implementing high-yield and cost-effective interventions. This includes knowing the yield of finding TB cases in high-transmission zones (eg, community hotspots, hospitals or households) to deliver community-based interventions. We aim to identify such transmission zones for enhanced case finding and evaluate the effectiveness of this approach. METHODS AND ANALYSIS: H3TB is an observational cross-sectional study evaluating MDR-TB active case finding strategies. Sputum samples from MDR-TB cases in three regions of Namibia will be evaluated by whole genome sequencing (WGS) in addition to routine sputum investigations (Xpert MTB/RIF, culture and drug susceptibility testing). We will collect information on household contacts, use of community spaces and geographical map intersections between participants, synthesising these data to identify transmission hotspots. We will look at the feasibility, acceptability, yield and cost of case finding strategies in these hotspots, and in households of patients with MDR-TB and visitors of hospitalised patients with MDR-TB. A compartmental transmission dynamic model will be constructed to evaluate the impact and cost-effectiveness of the strategies if scaled. ETHICS AND DISSEMINATION: Ethics approval was obtained. Participants will give informed consent. H3TB will capitalise on a partnership with the Ministry of Health and Social Services to follow up individuals diagnosed with MDR-TB and integrate WGS data with innovative contact network mapping, to allow enhanced case finding. Study data will contribute towards a systems approach to TB control. Equally important, it will serve as a role model for similar studies in other high-incidence settings.

Indexed as

Antibiotics, AntitubercularTuberculosis, Multidrug-ResistantCross-Sectional StudiesDrug Resistance, BacterialHospitalsHumansMicrobial Sensitivity TestsNamibiaAntibiotics, AntitubercularDiagnostic microbiologyEpidemiologyPublic healthTuberculosis

Identifiers

PMID38341211
PMCPMC10862302

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.