Interruption of tuberculosis detection and care during the Ebola virus disease epidemic (2014–2015) in Liberia: time-series analyses for 2013–2017

Objective: Interrupted time-series analyses, using 5 years of routinely collected health information system data, were conducted to estimate the magnitude of impact of the 2014–2015 Ebola virus disease (EVD) epidemic and determine trends in tuberculosis (TB) care services in Liberia. Methods: A segm...

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Bibliographic Details
Main Authors: Keith L. Gray, Naomi F. Walker, Frederick Martineau, Nahid Bhadelia, Wahdae-mai Harmon-Gray, Laura A. Skrip, Jean DeMarco, Patrick Konwloh, Nelson Dunbar
Format: Article
Language:English
Published: Elsevier 2021-11-01
Series:International Journal of Infectious Diseases
Subjects:
Online Access:http://www.sciencedirect.com/science/article/pii/S1201971221006755
Description
Summary:Objective: Interrupted time-series analyses, using 5 years of routinely collected health information system data, were conducted to estimate the magnitude of impact of the 2014–2015 Ebola virus disease (EVD) epidemic and determine trends in tuberculosis (TB) care services in Liberia. Methods: A segmented linear regression model was used to generate estimates and predictions for trends for three TB service indicators before, during, and after EVD, from January 2013 to December 2017. Results: It was found that the number of presumptive TB cases declined significantly at the start of the EVD outbreak, with an estimated loss of 3222 cases (95% confidence interval (CI) −5691 to −752; P = 0.014). There was also an estimated loss of 709 cases per quarter post-EVD (95% CI −1346 to −71; P = 0.032). However, over the post-EVD period, quarterly increases were observed in the proportion of smear-positive to presumptive cases (1.45%, 95% CI 0.38% to 2.5%; P = 0.011) and the proportion of treatment success to TB cases evaluated (3.3%, 95% CI 0.82% to 5.79%; P = 0.013). Conclusions: These findings suggest that the EVD outbreak (2014–2015) negatively affected TB care services. Rigorous quantitative analyses can be used to assess the magnitude of interruption and advocate for preparedness in settings with limited healthcare capacity.
ISSN:1201-9712