AIM: To find an optimal cluster size and number of clusters for a reasonable estimate of the prevalence of @entity231 in @entity1 aged > or = 50 years in 19 rural districts of a state in India. MATERIALS: Cluster sampling methodology was used in 19 rural districts of Karnataka State, India. In each district, 15 clusters were randomly selected and 90 @entity1 aged > or = 50 years were examined in each cluster. As a result the visual acuity and lens status of a total of 22,218 @entity1 were assessed. METHODS: For each district, the design effect for cluster size ranging from 20 to 90 was calculated and the optimal cluster size and the required number of clusters to achieve an accuracy of 1% errors and 80% confidence was assessed. RESULTS: The age and gender adjusted prevalence of @entity231 varied from 1.58% to 7.24%, which justifies district level surveys. The design effect is nearly 1.5 for clusters of sizes 30 and 40. With an average prevalence of 4.93% with 1% error and 80% confidence level, the optimal number of clusters is 37 and 28 for a cluster size of 30 and 40 respectively and the average sample size for a district around 1100. CONCLUSIONS: Rapid assessments for @entity231 in those aged > or = 50 years can be conducted at district level in India with existing resources and at affordable costs. These provide reliable data, essential for effective monitoring and planning. Other parameters, for instance, surgical coverage can also be assessed. The availability of standardized software for data entry and analysis and strict adherence to survey procedures is essential.

Rapid assessment of prevalence of XXXX at district level.

@entity1 :: ('9606', 'Species') :: ['people'] @entity231 :: ('MESH:D002386', 'Disease') :: ['cataract blindness']
@entity231 :: (MESH:D002386,Disease) :: ['cataract blindness']
