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Peer-reviewedCC BY-NCAmerican Journal of Epidemiology

Design considerations for incorporating serological monitoring into trachoma prevalence surveys

  • Everlyn Kamau1
  • Katherine Gass2
  • Emma Michele Harding-Esch3
  • Martha Idalí Saboyá-Díaz4
  • Pearl Anne Ante-Testard1
  • Amir Bedri Kello5
  • Robin L. Bailey3
  • Kimberly Fornace6
  • Anthony W. Solomon7
  • Scott D. Nash8
  • Benjamin F. Arnold9,1,10
  • Global Trachoma Serosurveillance Study Group
10 affiliations
  1. 1Francis I. Proctor Foundation, University of California San Francisco, San Francisco, USA
  2. 2Neglected Tropical Diseases Support Center, Task Force for Global Health, Atlanta, USA
  3. 3London School of Hygiene & Tropical Medicine, London, UK
  4. 4Department of Prevention, Control, and Elimination of Communicable Diseases, Pan American Health Organization, Washington DC, USA
  5. 5World Health Organization Regional Office for Africa, Brazzaville, Congo
  6. 6Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore
  7. 7Malaria and Neglected Tropical Diseases Department, World Health Organization, Geneva, Switzerland
  8. 8The Carter Center, Atlanta, USA
  9. 9Department of Ophthalmology, University of California San Francisco, San Francisco, USA
  10. 10Institute for Global Health Sciences, University of California San Francisco, San Francisco, USA
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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.

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Cite

BibTeXRIS
BibTeX
@article{kamau2026design,
  title = {{Design considerations for incorporating serological monitoring into trachoma prevalence surveys}},
  author = {Everlyn Kamau and Katherine Gass and Emma Michele Harding-Esch and Martha Idalí Saboyá-Díaz and Pearl Anne Ante-Testard and Amir Bedri Kello and Robin L. Bailey and Kimberly Fornace and Anthony W. Solomon and Scott D. Nash and Benjamin F. Arnold and Global Trachoma Serosurveillance Study Group},
  journal = {American Journal of Epidemiology},
  year = {2026},
  month = sep,
  doi = {10.1093/aje/kwag245},
  url = {https://doi.org/10.1093/aje/kwag245},
  note = {CC BY-NC},
}
RIS
TY  - JOUR
TI  - Design considerations for incorporating serological monitoring into trachoma prevalence surveys
AU  - Everlyn Kamau
AU  - Katherine Gass
AU  - Emma Michele Harding-Esch
AU  - Martha Idalí Saboyá-Díaz
AU  - Pearl Anne Ante-Testard
AU  - Amir Bedri Kello
AU  - Robin L. Bailey
AU  - Kimberly Fornace
AU  - Anthony W. Solomon
AU  - Scott D. Nash
AU  - Benjamin F. Arnold
AU  - Global Trachoma Serosurveillance Study Group
PY  - 2026
DA  - 2026/09/30
JO  - American Journal of Epidemiology
DO  - 10.1093/aje/kwag245
UR  - https://doi.org/10.1093/aje/kwag245
AB  - 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.
SN  - 0002-9262
SN  - 1476-6256
ER  -