{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"institution":[{"name":"medRxiv"}],"indexed":{"date-parts":[[2026,7,29]],"date-time":"2026-07-29T23:22:03Z","timestamp":1785367323104,"version":"3.55.0"},"posted":{"date-parts":[[2025,9,7]]},"group-title":"Epidemiology","reference-count":35,"publisher":"openRxiv","license":[{"start":{"date-parts":[[2025,9,7]],"date-time":"2025-09-07T00:00:00Z","timestamp":1757203200000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"accepted":{"date-parts":[[2026,6,23]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                <jats:p>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 previously been published. Using data from 40 prevalence surveys, we estimated 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 \u22641.5 and &gt;5.7 per 100 person-years, sample sizes between 300-2000 allowed good precision of SCR estimation. We anticipate a standard trachoma prevalence survey with 30 clusters and 30 households per cluster should provide \u226580% power to determine that an SCR \u22641.2 falls below a 2.2 threshold and SCR \u22655.7 falls above a 4.5 threshold. Our results support estimation of serological data via the recommended population-based survey design for trachoma surveillance.<\/jats:p>","DOI":"10.1101\/2025.09.05.25334960","type":"posted-content","created":{"date-parts":[[2025,9,8]],"date-time":"2025-09-08T02:10:15Z","timestamp":1757297415000},"source":"Crossref","is-referenced-by-count":7,"title":["Design considerations for incorporating serological monitoring into trachoma prevalence surveys"],"prefix":"10.64898","author":[{"given":"Everlyn","family":"Kamau","sequence":"first","affiliation":[{"name":"Francis I. Proctor Foundation, University of California San Francisco, San Francisco, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Katherine","family":"Gass","sequence":"additional","affiliation":[{"name":"Neglected Tropical Diseases Support Center, Task Force for Global Health, Atlanta, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Emma M.","family":"Harding-Esch","sequence":"additional","affiliation":[{"name":"London School of Hygiene & Tropical Medicine, London, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Martha Idal\u00ed","family":"Saboy\u00e1 D\u00edaz","sequence":"additional","affiliation":[{"name":"Department of Prevention, Control, and Elimination of Communicable Diseases, Pan American Health Organization, Washington DC, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Pearl Anne","family":"Ante-Testard","sequence":"additional","affiliation":[{"name":"Francis I. 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