Evidence map›Paper›PMID 25658592›Full record

ArticlePloS one2015

Cost-effectiveness analysis of community active case finding and household contact investigation for tuberculosis case detection in urban Africa.

Juliet N Sekandi, Kevin Dobbin, James Oloya, Alphonse Okwera, Christopher C Whalen, Phaedra S Corso

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 50 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
50citing papers in PubMed, 4 pooled it
2.3field-weighted citation impact, top 12% 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

50 citing papers in PubMed, 4 syntheses or guidelines pooled it, 73 citations in OpenAlex.

  1. Pooled it
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  19. Cost to perform door-to-door universal sputum screening for TB in a high-burden community.The international journal of tuberculosis and lung disease : the official journal of the International Union against Tuberculosis and Lung Disease · 2023
    Article
  20. Exhaled Mycobacterium tuberculosis Predicts Incident Infection in Household Contacts.Clinical infectious diseases : an official publication of the Infectious Diseases Society of America · 2023
    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

6 authors at 2 institutions in 2 countries.

Juliet N SekandiDepartment of Epidemiology and Biostatistics, College of Public Health, University of Georgia, Athens, Georgia, United States of America; Department of Epidemiology and Biostatistics, School of Public Health, College of Health Sciences, Makerere University, Kampala, Uganda.
Kevin DobbinDepartment of Epidemiology and Biostatistics, College of Public Health, University of Georgia, Athens, Georgia, United States of America.
James OloyaDepartment of Epidemiology and Biostatistics, College of Public Health, University of Georgia, Athens, Georgia, United States of America.
Alphonse OkweraSchool of Medicine, College of Health Sciences, Makerere University, Kampala, Uganda.
Christopher C WhalenDepartment of Epidemiology and Biostatistics, College of Public Health, University of Georgia, Athens, Georgia, United States of America.
Phaedra S CorsoDepartment of Health Policy and Management, College of Public Health, University of Georgia, Athens, Georgia, United States of America.
University of Georgia · USMakerere University · UG

Funding

Community Transmission of Tuberculosis Urban AfricaR01AI093856 · NIAID · UNIVERSITY OF GEORGIA · PI WHALEN, CHRISTOPHER C. · 2012 to 2021
$5.7M
NIAID NIH HHS R01 AI093856
6 · The paper itself

Abstract

introductionCase detection by passive case finding (PCF) strategy alone is inadequate for detecting all tuberculosis (TB) cases in high burden settings especially Sub-Saharan Africa. Alternative case detection strategies such as community Active Case Finding (ACF) and Household Contact Investigations (HCI) are effective but empirical evidence of their cost-effectiveness is sparse. The objective of this study was to determine whether adding ACF or HCI compared with standard PCF alone represent cost-effective alternative TB case detection strategies in urban Africa.

methodsA static decision modeling framework was used to examine the costs and effectiveness of three TB case detection strategies: PCF alone, PCF+ACF, and PCF+HCI. Probability and cost estimates were obtained from National TB program data, primary studies conducted in Uganda, published literature and expert opinions. The analysis was performed from the societal and provider perspectives over a 1.5 year time-frame. The main effectiveness measure was the number of true TB cases detected and the outcome was incremental cost-effectiveness ratios (ICERs) expressed as cost in 2013 US$ per additional true TB case detected.

resultsCompared to PCF alone, the PCF+HCI strategy was cost-effective at US$443.62 per additional TB case detected. However, PCF+ACF was not cost-effective at US$1492.95 per additional TB case detected. Sensitivity analyses showed that PCF+ACF would be cost-effective if the prevalence of chronic cough in the population screened by ACF increased 10-fold from 4% to 40% and if the program costs for ACF were reduced by 50%.

conclusionsUnder our baseline assumptions, the addition of HCI to an existing PCF program presented a more cost-effective strategy than the addition of ACF in the context of an African city. Therefore, implementation of household contact investigations as a part of the recommended TB control strategy should be prioritized.

Indexed as

Cost-Benefit AnalysisDecision Support TechniquesFamily CharacteristicsHumansMass ScreeningPrevalenceResidence CharacteristicsTuberculosisUgandaUrbanization

Identifiers

PMID25658592
PMCPMC4319733
OpenAlexW1992047982

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.