Evidence map›Paper›PMID 38290754›Full record

ArticleGlobal health, science and practice2024

Improving TB Case Detection Through Active Case-Finding: Results of Multiple Intervention Strategies in Hard-to-Reach Riverine Areas of Southern Nigeria.

Joseph N Chukwu, Cosmas Kenan Onah, Edmund Ndudi Ossai, Charles C Nwafor, Chukwuka Alphonsus, Okechukwu E Ezeakile, Ngozi Murphy-Okpala, Chinwe C Eze, Obioma Chijioke-Akaniro, Anthony Meka and 3 more

Abstract read
In one paragraph

Article in Global health, science and practice, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

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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

13 authors.

Joseph N ChukwuGerman Leprosy and Tuberculosis Relief Association, Enugu, Nigeria.
Cosmas Kenan OnahDepartment of Community Medicine, Alex Ekwueme Federal University Teaching Hospital Abakaliki, Abakaliki, Nigeria. onahcosyo@gmail.com.
Edmund Ndudi OssaiDepartment of Community Medicine, Ebonyi State University, Abakaliki, Nigeria.
Charles C NwaforGerman Leprosy and Tuberculosis Relief Association, Enugu, Nigeria.
Chukwuka AlphonsusGerman Leprosy and Tuberculosis Relief Association, Enugu, Nigeria.
Okechukwu E EzeakileGerman Leprosy and Tuberculosis Relief Association, Enugu, Nigeria.
Ngozi Murphy-OkpalaGerman Leprosy and Tuberculosis Relief Association, Enugu, Nigeria.
Chinwe C EzeGerman Leprosy and Tuberculosis Relief Association, Enugu, Nigeria.
Obioma Chijioke-AkaniroNational Tuberculosis, Leprosy and Buruli Ulcer Control Program, Abuja, Nigeria.
Anthony MekaGerman Leprosy and Tuberculosis Relief Association, Enugu, Nigeria.
Martin I NjokuGerman Leprosy and Tuberculosis Relief Association, Enugu, Nigeria.
Francis S IyamaGerman Leprosy and Tuberculosis Relief Association, Enugu, Nigeria.
Ngozi EkekeGerman Leprosy and Tuberculosis Relief Association, Enugu, Nigeria.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundA major challenge to TB control globally is low case detection, largely due to routine health facility-based passive case-finding employed by national TB control programs. Active case-finding is a risk-population-based screening approach that has been established to be effective in TB control. This intervention aimed to increase TB case detection in hard-to-reach areas in southern Nigeria.

methodsUsing a descriptive cross-sectional design, we conducted implementation research in 15 hard-to-reach riverine local government areas with historically recognized low TB case notification rates. Individuals with TB symptoms were screened using multiple strategies. Data were collected quarterly over a 4-year period using reporting tools and checklists. Descriptive analysis was done with Microsoft Excel spreadsheet 2019.

resultsA total of 1,089,129 individuals were screened: 16,576 in 2017; 108,102 in 2018; 697,165 in 2019; and 267,286 in 2020. Of those screened, 24,802 (2.3%) were identified as presumptive TB, of which 88.8% were tested and 10% were diagnosed with TB (0.23% of those screened). TB notifications more than doubled, increasing by 183.3% and 137.5% in the initial implementation and scale-up, respectively. On average, 441 individuals needed to be screened to diagnose 1 TB case. The cases, predominantly males (56.1%) and aged 15 years and older (77.4%), comprised 71.9% bacteriologically confirmed drug-sensitive TB, 25.8% clinically diagnosed drug-sensitive TB, and 2.3% drug-resistant cases. Detection sources included community outreach (1,786), health facilities (505), people living with HIV (57), and household contacts of bacteriologically confirmed TB cases (123). Remarkably, 98.1% of diagnosed TB cases commenced treatment.

conclusionsWe found a significant yield in TB case notifications, more than doubling the baseline figures. Given these successful results, we recommend prioritizing resources to support active case-finding strategies in national programs, especially in hard-to-reach areas with high-risk populations, to address TB more comprehensively.

Indexed as

TuberculosisCross-Sectional StudiesFemaleHealth FacilitiesHumansMaleMass ScreeningNigeria

Identifiers

PMID38290754
PMCPMC10906553

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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.