Design considerations for incorporating serological monitoring into trachoma prevalence surveys

Clicks: 20
ID: 330758
2026
Free PDF
Article Quality & Performance Metrics
Overall Quality
Not rated
Combines reader engagement with the AI quality analysis. This article has not been analysed, so there is no overall score — reader engagement is measured and shown alongside.
AI Quality Assessment
Not analyzed
Readership in this journal
Emerging

Ranked #195 of 378 articles by views in american journal of epidemiology

Most read Least read

Bar heights use a square-root scale. Only the 120 most-read articles are drawn; the journal has 378 in total.

Mint this article as an NFT
Not yet minted

Create a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.

5 SUSD one-off · no wallet required
Sign in to mint
Abstract
Serology is increasingly used to monitor infection transmission and disease elimination. Embedding dried blood spot collection in trachoma surveys allows transmission intensity inference through population-level seroconversion rate (SCR) estimation, but no formal assessment of required sample size has been published. Using serology data from 40 trachoma prevalence surveys, we estimated seroprevalence intra-cluster correlation coefficient, a key design parameter, and assessed survey design considerations for incorporating serological monitoring. Design scenarios focused on proposed operational SCR thresholds (2.2 [no action needed] and 4.5 [action needed] per 100 child years) for interpretation of serological data in low-transmission and post-elimination settings. We evaluated SCR estimation in 42 two-stage designs by calculating precision (confidence interval width around an SCR value) and power (the measure of deviation of suggested thresholds to the SCR value). When the SCR is ≤1.5 and >5.7 per 100 person-years, sample sizes between 300-2000 allowed good precision of SCR estimation. We anticipate a standard prevalence survey with 30 clusters and 30 households per cluster should provide ≥80% power to determine that an SCR ≤1.2 falls below a 2.2 threshold and SCR ≥5.7 falls above a 4.5 threshold. Our results support collection of serological data via the recommended survey design for trachoma surveillance.
Reference Key
openalex_W4414076608 Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Everlyn Kamau, Katherine Gass, Emma Michele Harding-Esch, Martha Idalí Saboyá-Díaz, Pearl Anne Ante-Testard, Amir Bedri Kello, Robin L. Bailey, Kimberly Fornace, Anthony W. Solomon, Scott D. Nash, Benjamin F. Arnold, on behalf of Global Trachoma Serosurveillance Study Group
Are you one of these authors? Claim your profile
Journal american journal of epidemiology
Year 2026
DOI
10.1093/aje/kwag245
URL
https://doi.org/10.1093/aje/kwag245
Keywords Keywords not found

Citations

No citations found. To add a citation, contact the admin at info@scimatic.org

Comments

No comments yet. Be the first to comment on this article.