Establishing a standard method for analysing case detection delay in leprosy using a Bayesian modelling approach.

ABSTRACT:

Background

Leprosy is an infectious disease caused by Mycobacterium leprae and remains a source of preventable disability if left undetected. Case detection delay is an important epidemiological indicator for progress in interrupting transmission and preventing disability in a community. However, no standard method exists to effectively analyse and interpret this type of data. In this study, we aim to evaluate the characteristics of leprosy case detection delay data and select an appropriate model for the variability of detection delays based on the best fitting distribution type.

Methods

Two sets of leprosy case detection delay data were evaluated: a cohort of 181 patients from the post exposure prophylaxis for leprosy (PEP4LEP) study in high endemic districts of Ethiopia,

SUBMITTER: Hambridge T 

PROVIDER: S-EPMC9940321 | biostudies-literature | 2023 Feb

REPOSITORIES: biostudies-literature