Evidence map›Paper›PMID 30824911›Full record

ArticleAmerican journal of epidemiology2019

Estimating the Impact of Tuberculosis Case Detection in Constrained Health Systems: An Example of Case-Finding in South Africa.

Thomas Sumner, Fiammetta Bozzani, Don Mudzengi, Piotr Hippner, Rein M Houben, Vicky Cardenas, Anna Vassall, Richard G White

Open access · hybridAbstract read
In one paragraph

Article in American journal of epidemiology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 2 pooled it
1.7field-weighted citation impact, top 17% 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

11 citing papers in PubMed, 2 syntheses or guidelines pooled it, 20 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Article
  4. Impact of Community-Wide Tuberculosis Active Case Finding and Human Immunodeficiency Virus Testing on Tuberculosis Trends in Malawi.Clinical infectious diseases : an official publication of the Infectious Diseases Society of America · 2023
    Article
  5. 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
  6. Article
  7. Article
  8. Article
  9. Article
  10. Informing Balanced Investment in Services and Health Systems: A Case Study of Priority Setting for Tuberculosis Interventions in South Africa.Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research · 2020
    Article
  11. 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

8 authors at 2 institutions in 2 countries.

Thomas SumnerTB Modelling Group, TB Centre, Centre for the Mathematical Modelling of Infectious Disease, Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, United Kingdom.
Fiammetta BozzaniDepartment of Global Health and Development, London School of Hygiene and Tropical Medicine, London, United Kingdom.
Don MudzengiAurum Institute, Johannesburg, South Africa.
Piotr HippnerAurum Institute, Johannesburg, South Africa.
Rein M HoubenTB Modelling Group, TB Centre, Centre for the Mathematical Modelling of Infectious Disease, Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, United Kingdom.
Vicky CardenasAurum Institute, Johannesburg, South Africa.
Anna VassallDepartment of Global Health and Development, London School of Hygiene and Tropical Medicine, London, United Kingdom.
Richard G WhiteTB Modelling Group, TB Centre, Centre for the Mathematical Modelling of Infectious Disease, Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, United Kingdom.
London School of Hygiene & Tropical Medicine · GBAurum Institute · ZA

Funding

Medical Research Council MR/P002404/1
6 · The paper itself

Abstract

Mathematical models are increasingly being used to compare strategies for tuberculosis (TB) control and inform policy decisions. Models often do not consider financial and other constraints on implementation and may overestimate the impact that can be achieved. We developed a pragmatic approach for incorporating resource constraints into mathematical models of TB. Using a TB transmission model calibrated for South Africa, we estimated the epidemiologic impact and resource requirements (financial, human resource (HR), and diagnostic) of 9 case-finding interventions. We compared the model-estimated resources with scenarios of future resource availability and estimated the impact of interventions under these constraints. Without constraints, symptom screening in public health clinics and among persons receiving care for human immunodeficiency virus infection was predicted to lead to larger reductions in TB incidence (9.5% (2.5th-97.5th percentile range (PR), 8.6-12.2) and 14.5% (2.5th-97.5th PR, 12.2-16.3), respectively) than improved adherence to diagnostic guidelines (2.7%; 2.5th-97.5th PR, 1.6-4.1). However, symptom screening required large increases in resources, exceeding future HR capacity. Even under our most optimistic HR scenario, the reduction in TB incidence from clinic symptom screening was 0.2%-0.9%-less than that of improved adherence to diagnostic guidelines. Ignoring resource constraints may result in incorrect conclusions about an intervention's impact and may lead to suboptimal policy decisions. Models used for decision-making should consider resource constraints.

Indexed as

Contact TracingHIV InfectionsHumansIncidenceModels, TheoreticalSouth AfricaTuberculosishealth resourcesmathematical modelsSouth Africatuberculosis

Identifiers

PMID30824911
PMCPMC6545281
OpenAlexW2918564090

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.