02648nas a2200301 4500000000100000008004100001260001600042653002400058653002700082653002100109653001800130100001500148700001100163700001400174700001200188700001200200700001100212700001400223700001200237700001400249700001600263700001200279700001300291245012300304856015300427520175200580022001402332 2021 d bElsevier BV10aInfectious Diseases10aMicrobiology (medical)10aGeneral Medicine10aSurvey design1 aGallini JW1 aSata E1 aZerihun M1 aMelak B1 aHaile M1 aZeru T1 aGessese D1 aAyele Z1 aTadesse Z1 aCallahan EK1 aNash SD1 aWeiss PS00aOptimizing cluster survey designs for estimating trachomatous inflammation-follicular within trachoma control programs uhttps://www.sciencedirect.com/science/article/pii/S1201971221012546/pdfft?md5=1343b19fa7b5afa04922f5e462e1b0ff&pid=1-s2.0-S1201971221012546-main.pdf3 a
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. Work remains to mathematically evaluate current trachoma survey designs. We aimed to characterize the effects of the number of units sampled on the precision and cost of trachomatous inflammation-follicular (TF) estimates.
We simulated a population of 30 districts 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 on precision, proportion of incorrect and low MDA decisions made, and estimated cost.
Number of clusters sampled had a greater impact on precision than 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 (providing adequate precision while minimizing cost) design 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.
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