PROJECT SUMMARY Trachoma remains the leading infectious cause of blindness. The World Health Organization (WHO) has targeted trachoma for elimination as a public health problem by 2030. The WHO’s elimination strategy recommends population-based surveys of children aged 1-9 years. Surveys are crucial for deciding which districts require antibiotic treatments, and also for deciding which districts have eliminated trachoma. Currently, WHO recommends training staff to assess the clinical signs of trachoma in the field. To be certified, a grader must be able to identify trachoma in children in a community-based setting. But field grading is subjective— especially in eyes with borderline findings—leading to variability in estimates of trachoma. And as trachoma elimination proceeds, countries are left with fewer children with trachoma, making it increasingly difficult to certify graders during the training. Conjunctival photography could solve some of these problems, but the best methods for grading photographs and interpreting the data have not been established. This secondary data analysis grant proposal seeks to provide insights on the best use of conjunctival photographs for trachoma control. We propose secondary data analyses of more than 20,000 conjunctival photographs that have been collected as part of several previous NIH-funded studies. Photographs have been collected from over 130 communities in Ethiopia and Peru, captured on a random sample of children aged 0-9 years of age in each community. The data set thus consists of population-based samples, making them similar to those recommended by WHO. In addition to the conjunctival photographs, conjunctival swabs were also collected for each child and processed for the cause of trachoma, Chlamydia trachomatis. We propose several analyses. First, we will compare the trachoma grades of 25 trachoma experts to see if these graders can be grouped into clusters who grade similarly. We will assess which group’s grades are most strongly correlated with ocular chlamydia, providing guidance on exactly how we should be defining the gold standard photo-grade for trachoma. Second, we will explore different ways to combine multiple grades from a single photograph into a consensus grade, providing guidance on how many graders should grade each photograph and which statistical model will provide the most precision and validity. Finally, we will compare the use of a granular grading system versus a binary grading system to determine if the more granular system results in more accurate estimates of trachoma. These analyses will greatly improve our understanding of the best methods for grading and analyzing conjunctival photographs for trachoma, and thus contribute to the effort for global elimination of trachoma.