Evidence map›Paper›PMID 31509177›Full record

SynthesisAmerican journal of epidemiology2020

Estimating the Intracluster Correlation Coefficient for the Clinical Sign "Trachomatous Inflammation-Follicular" in Population-Based Trachoma Prevalence Surveys: Results From a Meta-Regression Analysis of 261 Standardized Preintervention Surveys Carried Out in Ethiopia, Mozambique, and Nigeria.

Colin K Macleod, Robin L Bailey, Michael Dejene, Oumer Shafi, Biruck Kebede, Nebiyu Negussu, Caleb Mpyet, Nicholas Olobio, Joel Alada, Mariamo Abdala and 3 more

Abstract readMeta-Analysis
In one paragraph

Synthesis in American journal of epidemiology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing 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

19 citing papers in PubMed.

  1. Trial
  2. Discrepancy Between Active Trachoma and Tests of Chlamydial Infection in Alto Amazonas, Peru.Clinical infectious diseases : an official publication of the Infectious Diseases Society of America · 2026
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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.

Colin K MacleodClinical Research Department, London School of Hygiene & Tropical Medicine, London, United Kingdom.
Robin L BaileyClinical Research Department, London School of Hygiene & Tropical Medicine, London, United Kingdom.
Michael DejeneMichael Dejene Public Health Consultancy Services, Addis Ababa, Ethiopia.
Oumer ShafiFederal Ministry of Health, Addis Ababa, Ethiopia.
Biruck KebedeFederal Ministry of Health, Addis Ababa, Ethiopia.
Nebiyu NegussuFederal Ministry of Health, Addis Ababa, Ethiopia.
Caleb MpyetDepartment of Ophthalmology, Queen Mamohato Memorial Hospital, Maseru, Lesotho.
Nicholas OlobioNational Trachoma Control Program, Department of Public Health, Federal Ministry of Health, Abuja, Nigeria.
Joel AladaDepartment of Ophthalmology, Queen Mamohato Memorial Hospital, Maseru, Lesotho.
Mariamo AbdalaOphthalmology Department, Ministry of Health, Maputo, Mozambique.
Rebecca WillisTask Force for Global Health, Decatur, Georgia.
Richard HayesMRC Tropical Epidemiology Group, Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, United Kingdom.
Anthony W SolomonClinical Research Department, London School of Hygiene & Tropical Medicine, London, United Kingdom.

Funding

Medical Research Council MR/R010161/1Wellcome TrustWellcome Trust 098521
6 · The paper itself

Abstract

Sample sizes in cluster surveys must be greater than those in surveys using simple random sampling in order to obtain similarly precise prevalence estimates, because results from subjects examined in the same cluster cannot be assumed to be independent. Therefore, a crucial aspect of cluster sampling is estimation of the intracluster correlation coefficient (ρ): the degree of relatedness of outcomes in a given cluster, defined as the proportion of total variance accounted for by between-cluster variation. In infectious disease epidemiology, this coefficient is related to transmission patterns and the natural history of infection; its value also depends on particulars of survey design. Estimation of ρ is often difficult due to the lack of comparable survey data with which to calculate summary estimates. Here we use a parametric bootstrap model to estimate ρ for the ocular clinical sign "trachomatous inflammation-follicular" (TF) among children aged 1-9 years within population-based trachoma prevalence surveys. We present results from a meta-regression analysis of data from 261 such surveys completed using standardized methods in Ethiopia, Mozambique, and Nigeria in 2012-2015. Consistent with the underlying theory, we found that ρ increased with increasing overall TF prevalence and smaller numbers of children examined per cluster. Estimates of ρ for TF were independently higher in Ethiopia than in the other countries.

Indexed as

Correlation of DataChildChild, PreschoolCluster AnalysisCross-Sectional StudiesEthiopiaFemaleHumansInfantMaleMozambiqueNigeriaPrevalenceRegression AnalysisTrachomaclusteringintracluster correlation coefficientprevalencesurveystrachomatrachomatous inflammation—follicular

Identifiers

PMID31509177
PMCPMC7119302

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.