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Optimizing cluster survey designs for estimating trachomatous inflammation-follicular within trachoma control programs.
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.
Affiliation
  • Gallini JW; Department of Biostatistics and Bioinformatics, Emory University, Atlanta, Georgia, USA.
  • Sata E; Trachoma Control Program, The Carter Center, Addis Ababa, Ethiopia.
  • Zerihun M; Trachoma Control Program, The Carter Center, Addis Ababa, Ethiopia.
  • Melak B; Trachoma Control Program, The Carter Center, Addis Ababa, Ethiopia.
  • Haile M; Amhara Public Health Institute, Bahir Dar, Amhara, Ethiopia.
  • Zeru T; Amhara Public Health Institute, Bahir Dar, Amhara, Ethiopia.
  • Gessese D; Trachoma Control Program, The Carter Center, Addis Ababa, Ethiopia.
  • Ayele Z; Trachoma Control Program, The Carter Center, Addis Ababa, Ethiopia.
  • Tadesse Z; Trachoma Control Program, The Carter Center, Addis Ababa, Ethiopia.
  • Callahan EK; Trachoma Control Program, The Carter Center, Atlanta, Georgia, USA.
  • Nash SD; Trachoma Control Program, The Carter Center, Atlanta, Georgia, USA. Electronic address: scott.nash@cartercenter.org.
  • Weiss PS; Department of Biostatistics and Bioinformatics, Emory University, Atlanta, Georgia, USA.
Int J Infect Dis ; 116: 101-107, 2022 Mar.
Article in En | MEDLINE | ID: mdl-34965463
ABSTRACT

OBJECTIVES:

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.

METHODS:

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.

RESULTS:

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.

CONCLUSIONS:

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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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Trachoma Type of study: Prevalence_studies / Risk_factors_studies Limits: Humans / Infant Country/Region as subject: Africa Language: En Journal: Int J Infect Dis Journal subject: DOENCAS TRANSMISSIVEIS Year: 2022 Document type: Article Affiliation country: Estados Unidos

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Trachoma Type of study: Prevalence_studies / Risk_factors_studies Limits: Humans / Infant Country/Region as subject: Africa Language: En Journal: Int J Infect Dis Journal subject: DOENCAS TRANSMISSIVEIS Year: 2022 Document type: Article Affiliation country: Estados Unidos
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