Evidence map›Paper›PMID 29879917›Full record

ArticleBMC infectious diseases2018

Tuberculosis case finding using population-based disease surveillance platforms in urban and rural Kenya.

Godfrey Bigogo, Kevin Cain, Diana Nyole, Geoffrey Masyongo, Joshua Auko Auko, Newton Wamola, Albert Okumu, Janet Agaya, Joel Montgomery, Martien Borgdorff and 1 more

Open access · goldAbstract read
In one paragraph

Article in BMC infectious diseases, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed, 1 pooled it
1.3field-weighted citation impact, top 18% 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

6 citing papers in PubMed, 1 synthesis or guideline pooled it, 11 citations in OpenAlex.

  1. A systematic review of the number needed to screen for active TB among people living with HIV.The international journal of tuberculosis and lung disease : the official journal of the International Union against Tuberculosis and Lung Disease · 2021
    Pooled it
  2. Advance Warning and Response Systems in Kenya: A Scoping Review.medRxiv : the preprint server for health sciences · 2025
    Article
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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 2 institutions in 3 countries.

Godfrey BigogoCentre for Global Health Research, Kenya Medical Research Institute, P.O Box 1578 -, Kisumu, 40100, Kenya. Gbigogo@kemricdc.org.
Kevin CainU.S. Centers for Disease Control and Prevention, Atlanta, USA.
Diana NyoleCentre for Global Health Research, Kenya Medical Research Institute, P.O Box 1578 -, Kisumu, 40100, Kenya.
Geoffrey MasyongoCentre for Global Health Research, Kenya Medical Research Institute, P.O Box 1578 -, Kisumu, 40100, Kenya.
Joshua Auko AukoCentre for Global Health Research, Kenya Medical Research Institute, P.O Box 1578 -, Kisumu, 40100, Kenya.
Newton WamolaCentre for Global Health Research, Kenya Medical Research Institute, P.O Box 1578 -, Kisumu, 40100, Kenya.
Albert OkumuCentre for Global Health Research, Kenya Medical Research Institute, P.O Box 1578 -, Kisumu, 40100, Kenya.
Janet AgayaCentre for Global Health Research, Kenya Medical Research Institute, P.O Box 1578 -, Kisumu, 40100, Kenya.
Joel MontgomeryU.S. Centers for Disease Control and Prevention, Atlanta, USA.
Martien BorgdorffU.S. Centers for Disease Control and Prevention, Atlanta, USA.
Deron BurtonU.S. Centers for Disease Control and Prevention, Atlanta, USA.
Kenya Medical Research Institute · KECenters for Disease Control and Prevention · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundTuberculosis (TB) case finding is an important component of TB control because it can reduce transmission of Mycobacterium tuberculosis (MTB) through prompt detection and treatment of infectious patients.

methodsUsing population-based infectious disease surveillance (PBIDS) platforms with links to health facilities in Kenya we implemented intensified TB case finding in the community and at the health facilities, as an adjunct to routine passive case finding conducted by the national TB program. From 2011 to 2014, PBIDS participants ≥15 years were screened either at home or health facilities for possible TB symptoms which included cough, fever, night sweats or weight loss in the preceding 2 weeks. At home, participants with possible TB symptoms had expectorated sputum collected. At the clinic, HIV-infected participants with possible TB symptoms were invited to produce sputum. Those without HIV but with symptoms lasting 7 days including the visit day had chest radiographs performed, and had sputum collected if the radiographs were abnormal. Sputum samples were tested for the presence of MTB using the Xpert MTB/RIF assay. TB detection rates were calculated per 100,000 persons screened.

resultsOf 11,191 participants aged ≥15 years screened at home at both sites, 2695 (23.9%) reported possible TB symptoms, of whom 2258 (83.8%) produced sputum specimens. MTB was detected in 32 (1.4%) of the specimens resulting in a detection rate of 286/100,000 persons screened. At the health facilities, a total of 11,762 person were screened, 7500 (63.8%) had possible TB symptoms of whom 1282 (17.1%) produced sputum samples. MTB was detected in 69 (5.4%) of the samples, resulting in an overall detection rate of 587/100,000 persons screened. The TB detection rate was higher in persons with HIV compared to those without at both home (HIV-infected - 769/100,000, HIV-uninfected 141/100,000, rate ratio (RR) - 5.45, 95% CI 3.25-22.37), and health facilities (HIV-infected 3399/100,000, HIV-uninfected 294/100,000, RR 11.56, 95% CI 6.18-18.44).

conclusionFacility-based intensified TB case finding detected more TB cases per the number of specimens tested and the number of persons screened, including those with HIV, than home-based TB screening and should be further evaluated to determine its potential programmatic impact.

Indexed as

AdultAgedAmbulatory Care FacilitiesFemaleHIV InfectionsHumansKenyaMaleMass ScreeningMiddle AgedMycobacterium tuberculosisPopulation SurveillanceRural PopulationSputumTuberculosisUrban PopulationCase-findingKenyaTuberculosis

Identifiers

PMID29879917
PMCPMC5992751
OpenAlexW2806675070

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.