Evidence map›Paper›PMID 40690534›Full record

ArticlePLoS neglected tropical diseases2025

Cost-effectiveness of adding measurement of Chlamydia trachomatis infection and serology to trachoma prevalence surveys in Tanzania and Mozambique.

Emily C Decker, Molly W Adams, William E Oswald, Rebecca M Flueckiger, Jeremiah M Ngondi, Mawo Fall, Ezgi E Yilmaz, Lisa C Brooks, George Kabona, Henis Mior Sitoe and 5 more

Abstract read
In one paragraph

Article in PLoS neglected tropical diseases, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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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

15 authors.

Emily C DeckerDuke University, Durham, North Carolina, United States of America.ORCID 0000-0003-3000-7003
Molly W AdamsRTI International, International Development Group, Washington, Columbia, United States of America.
William E OswaldRTI International, International Development Group, Washington, Columbia, United States of America.
Rebecca M FlueckigerRTI International, International Development Group, Washington, Columbia, United States of America.
Jeremiah M NgondiRTI International, International Development Group, Washington, Columbia, United States of America.
Mawo FallRTI International, International Development Group, Maputo, Maputo, Mozambique.
Ezgi E YilmazCornell University, Dyson School of Applied Economics and Management, Ithaca, New York, United States of America.
Lisa C BrooksRTI International, International Development Group, Washington, Columbia, United States of America.
George KabonaMinistry of Health Community Development Gender Elderly and Children, Dodoma, Dodoma, Tanzania.
Henis Mior SitoeMinistério da Saúde, Maputo, Maputo, Mozambique.
Mabula KasubiMuhimbili University of Health and Allied Sciences, Department of Microbiology, Dar es Salaam, Tanzania.
Tamimo MomadeRTI International, International Development Group, Maputo, Maputo, Mozambique.
Thomas M LietmanThe Francis I. Proctor Foundation, University of California, San Francisco, San Francisco, California, United States of America.
Thuy DoanThe Francis I. Proctor Foundation, University of California, San Francisco, San Francisco, California, United States of America.
Rachel D StelmachRTI International, International Development Group, Washington, Columbia, United States of America.

Funding

RTI InternationalU.S. Agency for International Development (USAID) 7200AA18CA00040
6 · The paper itself

Abstract

backgroundAccurate methods to measure trachoma prevalence are critical to monitor progress and guide mass drug administration as countries near elimination. Currently, countries conduct trachoma prevalence surveys via clinical examination using the simplified trachoma grading system. Grading can have reduced accuracy in low prevalence settings, potentially resulting in errors. Adding ocular swabbing and Chlamydia trachomatis (Ct) infection testing and dried blood spot (DBS) collection and testing can be more sensitive and specific methods for trachoma identification, with potential cost-saving and information benefits. While previous studies have examined the costs of trachoma prevalence surveys, we present the first costing and cost-effectiveness analysis of enhanced trachoma prevalence surveys with ocular swabs and DBS in addition to grading. METHODOLOGY/PRINCIPAL

findingsWe calculated the incremental financial cost of enhanced trachoma prevalence surveys with swabs, DBS, and grading using expenditure records from four districts in Tanzania and four districts in Mozambique in 2022. In Tanzania, the cost per cluster of an enhanced survey was $2,337.39 compared to $459.75 for a standard survey. In Mozambique, the cost per cluster of an enhanced survey was $2,147.12, compared to $1,381.46 for a standard survey. We calculated the incremental cost-effectiveness ratio for each method, defined as the ratio of incremental cost to additional instances of trachoma indicators identified, and explored variation in cost-effectiveness via sensitivity analyses. Adding swabs, DBS, or both was cost-increasing and more effective at identification of trachoma indicators than grading alone. In Tanzania, swabs were the most cost-effective method, while DBS was more cost-effective in Mozambique. Swabs and DBS were less cost-effective when combined than individually. The main factor determining cost-effectiveness was sensitivity. CONCLUSIONS/SIGNIFICANCE: Adding swabs or DBS to trachoma prevalence surveys can be viable, cost-effective methods for identifying trachoma indicators. The additional costs are commensurate with additional information that would support elimination efforts.

Indexed as

Chlamydia trachomatisCost-Benefit AnalysisTrachomaChildChild, PreschoolDried Blood Spot TestingFemaleHumansMaleMozambiquePrevalenceTanzania

Identifiers

PMID40690534
PMCPMC12310039

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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.