Optimizing cluster survey designs for estimating trachomatous inflammation-follicular within trachoma control...

Area of Science:

• Public Health
• Epidemiology
• Ophthalmology

Background:

• Trachoma elimination relies on mass drug administration (MDA) guided by prevalence data.
• Current MDA decisions use two-stage cluster surveys, necessitating evaluation of their efficiency.
• Mathematical assessment of trachoma survey designs is needed to optimize resource allocation.

Purpose of the Study:

• To evaluate how varying sample sizes impact the precision and cost of trachomatous inflammation-follicular (TF) estimates.
• To mathematically characterize the effects of cluster and household numbers on survey design for trachoma elimination programs.

Main Methods:

• Simulated a population of 30 districts in Amhara, Ethiopia, with diverse TF prevalence.
• Evaluated sampling schemes with varying numbers of clusters (14-34) and households (10-60).
• Assessed schemes based on precision, MDA decision accuracy, and estimated costs.

Main Results:

• The number of clusters sampled significantly influenced precision more than household numbers.
• Optimal survey design varied by district TF prevalence.
• For <10% prevalence, 20 clusters of 20-30 households were most cost-efficient; for >10% prevalence, 15-20 clusters of 20-30 households were optimal.

Conclusions:

• Context-specific survey designs can enhance precision and reduce costs for long-term trachoma programs.
• A balanced approach involves sampling 15-20 clusters (20-30 households each) for moderate-to-high prevalence districts.
• Sampling 20 clusters (20-30 households each) is recommended for districts near the 5% TF prevalence threshold.