The Library
Back-calculating the incidence of infection of leprosy in a Bayesian framework
Tools
Tools
Tools
Crump, Ron E. and Medley, Graham (2015) Back-calculating the incidence of infection of leprosy in a Bayesian framework. Parasites & Vectors, 8 (1). pp. 1-9. 534. doi:10.1186/s13071-015-1142-5 ISSN 1756-3305.
|
PDF
WRAP_art%3A10.1186%2Fs13071-015-1142-5 (1).pdf - Published Version - Requires a PDF viewer. Available under License Creative Commons Attribution 4.0. Download (1134Kb) | Preview |
Official URL: http://dx.doi.org/10.1186/s13071-015-1142-5
Abstract
Background:
The number of new leprosy cases reported annually is falling worldwide, but remains relatively high in some populations. Because of the long and variable periods between infection, onset of disease, and diagnosis, the recently detected cases are a reflection of infection many years earlier. Estimation of the numbers of sub-clinical and clinical infections would be useful for management of elimination programmes. Back-calculation is a methodology that could provide estimates of prevalence of undiagnosed infections, future diagnoses and the effectiveness of control.
Methods:
A basic back-calculation model to investigate the infection dynamics of leprosy has been developed using Markov Chain Monte Carlo in a Bayesian context. The incidence of infection and the detection delay both vary with calendar time. Public data from Thailand are used to demonstrate the results that are obtained as the incidence of diagnosed cases falls.
Results:
The results show that the underlying burden of infection and short-term future predictions of cases can be estimated with a simple model. The downward trend in new leprosy cases in Thailand is expected to continue. In 2015 the predicted total number of undiagnosed sub-clinical and clinical infections is 1,168 (846–1,546) of which 466 (381–563) are expected to be clinical infections.
Conclusions:
Bayesian back-calculation has great potential to provide estimates of numbers of individuals in health/infection states that are as yet unobserved. Predictions of future cases provides a quantitative measure of understanding for programme managers and evaluators. We will continue to develop the approach, and suggest that it might be useful for other NTD in which incidence of diagnosis is not an immediate measure of infection.
| Item Type: | Journal Article | ||||||||
|---|---|---|---|---|---|---|---|---|---|
| Subjects: | R Medicine > RC Internal medicine | ||||||||
| Divisions: | Faculty of Science, Engineering and Medicine > Science > Life Sciences (2010- ) | ||||||||
| Library of Congress Subject Headings (LCSH): | Leprosy | ||||||||
| Journal or Publication Title: | Parasites & Vectors | ||||||||
| Publisher: | BioMed Central Ltd. | ||||||||
| ISSN: | 1756-3305 | ||||||||
| Official Date: | 22 October 2015 | ||||||||
| Dates: |
|
||||||||
| Volume: | 8 | ||||||||
| Number: | 1 | ||||||||
| Number of Pages: | 9 | ||||||||
| Page Range: | pp. 1-9 | ||||||||
| Article Number: | 534 | ||||||||
| DOI: | 10.1186/s13071-015-1142-5 | ||||||||
| Status: | Peer Reviewed | ||||||||
| Publication Status: | Published | ||||||||
| Access rights to Published version: | Open Access (Creative Commons) | ||||||||
| Date of first compliant deposit: | 11 March 2016 | ||||||||
| Date of first compliant Open Access: | 14 March 2016 | ||||||||
| Funder: | Novartis (Firm) |
Request changes or add full text files to a record
Repository staff actions (login required)
 |
View Item |
Downloads
Downloads per month over past year
