Optimizing cluster survey designs for estimating trachomatous inflammation–follicular within trachoma control programs

• Published in: International journal of infectious diseases 2022-03, Vol.116, p.101-107
• Main Authors: Gallini, Julia W., Sata, Eshetu, Zerihun, Mulat, Melak, Berhanu, Haile, Mahteme, Zeru, Taye, Gessese, Demelash, Ayele, Zebene, Tadesse, Zerihun, Callahan, E. Kelly, Nash, Scott D., Weiss, Paul S.
• Format: Article
• Language: English
• Subjects: Azithromycin - therapeutic use; costs and cost analysis; Ethiopia; Ethiopia - epidemiology; Humans; Infant; Inflammation; Prevalence; surveys; trachoma; Trachoma - drug therapy; Trachoma - epidemiology; Trachoma - prevention & control
• ISSN: 1201-9712; 1878-3511
• DOI: 10.1016/j.ijid.2021.12.355

•Surveys are the primary tool used to determine the need for trachoma interventions•One-size-fits-all survey designs are likely an inefficient use of funds in many instances•Our study aimed to evaluate the efficiency and precision of alternative survey designs•Sampling < 30 clusters often achieves equally precise estimates, with less cost waste•Survey designs should be evidence based where data are available The World Health Organization recommends mass drug administration (MDA) with azithromycin to eliminate trachoma as a public health problem. MDA decisions are based on prevalence estimates from two-stage cluster surveys. There is a need to mathematically evaluate current trachoma survey designs. Our study aimed to characterize the effects of the number of units sampled on the precision and cost of trachomatous inflammation–follicular (TF) estimates. A population of 30 districts was simulated to represent the breadth of possible TF distributions in Amhara, Ethiopia. Samples of varying numbers of clusters (14–34) and households (10–60) were selected. Sampling schemes were evaluated based on precision, proportion of incorrect and low MDA decisions made, and estimated cost. The number of clusters sampled had a greater impact on precision than the number of households. The most efficient scheme depended on the underlying TF prevalence in a district. For lower prevalence areas (< 10%) the most cost-efficient design (providing adequate precision while minimizing cost) was 20 clusters of 20–30 households. For higher prevalence areas (> 10%), the most efficient design was 15–20 clusters of 20–30 households. For longer-running programs, using context-specific survey designs would allow for practical precision while reducing survey costs. Sampling 15 clusters of 20–30 households in suspected moderate-to-high prevalence districts and 20 clusters of 20–30 households in districts suspected to be near the 5% threshold appears to be a balanced approach.