Interpreting measures of tuberculosis transmission: A case study on the Portuguese population

19Citations
Citations of this article
69Readers
Mendeley users who have this article in their library.

This article is free to access.

Abstract

Background: Tuberculosis remains a high burden for Human society despite considerable investments in its control. Unique features in the history of infection and transmission dynamics of tuberculosis pose serious limitations on the direct interpretation of surveillance data and call for models that incorporate latent processes and simulate specific interventions.Methods: A transmission model was adjusted to the dataset of active tuberculosis cases reported in Portugal between 2002 and 2009. We estimated key transmission parameters from the data (i.e. time to diagnosis, treatment length, default proportion, proportion of pulmonary TB cases). Using the adjusted model to the Portuguese case, we estimated the total burden of tuberculosis in Portugal. We further performed sensitivity analysis to heterogeneities in susceptibility to infection and exposure intensity.Results: We calculated a mean time to diagnose of 2.81 months and treatment length of 8.80 months in Portugal. The proportion defaulting treatment was calculated as 0.04 and the proportion of pulmonary cases as 0.75. Using these values, we estimated a TB burden of 1.6 million infected persons, corresponding to more than 15% of the Portuguese population. We further described the sensitivity of these estimates to heterogeneity.Conclusions: We showed that the model reproduces well the observed dynamics of the Portuguese data, thus demonstrating its adequacy for devising control strategies for TB and predicting the effects of interventions. © 2014 Lopes et al.; licensee BioMed Central Ltd.

Cite

CITATION STYLE

APA

Lopes, J. S., Rodrigues, P., Pinho, S. T. R., Andrade, R. F. S., Duarte, R., & Gomes, M. G. M. (2014). Interpreting measures of tuberculosis transmission: A case study on the Portuguese population. BMC Infectious Diseases, 14(1). https://doi.org/10.1186/1471-2334-14-340

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free