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Data from: Impact of the Ebola outbreak on Trypanosoma brucei gambiense infection medical activities in coastal Guinea, 2014-2015: a retrospective analysis from the Guinean national Human African Trypanosomiasis control program

Cite this dataset

Camara, Mariame et al. (2018). Data from: Impact of the Ebola outbreak on Trypanosoma brucei gambiense infection medical activities in coastal Guinea, 2014-2015: a retrospective analysis from the Guinean national Human African Trypanosomiasis control program [Dataset]. Dryad. https://doi.org/10.5061/dryad.036ds

Abstract

Background: The 2014–2015 Ebola outbreak massively hit Guinea. The coastal districts of Boffa, Dubreka and Forecariah, three major foci of Human African Trypanosomiasis (HAT), were particularly affected. We aimed to assess the impact of this epidemic on sleeping sickness screening and caring activities. Methodology/Principal findings: We used preexisting data from the Guinean sleeping sickness control program, collected between 2012 and 2015. We described monthly: the number of persons (i) screened actively; (ii) or passively; (iii) treated for HAT; (iv) attending post-treatment follow-up visits. We compared clinical data, treatment characteristics and Disability Adjusted Life-Years (DALYs) before (February 2012 to December 2013) and during (January 2014 to October 2015) the Ebola outbreak period according to available data. Whereas 32,221 persons were actively screened from February 2012 to December 2013, before the official declaration of the first Ebola case in Guinea, no active screening campaigns could be performed during the Ebola outbreak. Following the reinforcement and extension of HAT passive surveillance system early in 2014, the number of persons tested passively by month increased from 7 to 286 between April and September 2014 and then abruptly decreased to 180 until January 2015 and to none after March 2015. 213 patients initiated HAT treatment, 154 (72%) before Ebola and 59 (28%) during the Ebola outbreak. Those initiating HAT therapy during Ebola outbreak were recruited through passive screening and diagnosed at a later stage 2 of the disease (96% vs. 55% before Ebola, p<0.0001). The proportion of patients attending the 3 months and 6 months post-treatment follow-up visits decreased from 44% to 10% (p <0.0001) and from 16% to 3% (p = 0.017) respectively. The DALYs generated before the Ebola outbreak were estimated to 48.7 (46.7–51.5) and increased up to 168.7 (162.7–174.7), 284.9 (277.1–292.8) and 466.3 (455.7–477.0) during Ebola assuming case fatality rates of 2%, 5% and 10% respectively among under-reported HAT cases. Conclusions/Significance: The 2014–2015 Ebola outbreak deeply impacted HAT screening activities in Guinea. Active screening campaigns were stopped. Passive screening dramatically decreased during the Ebola period, but trends could not be compared with pre-Ebola period (data not available). Few patients were diagnosed with more advanced HAT during the Ebola period and retention rates in follow-up were lowered. The drop in newly diagnosed HAT cases during Ebola epidemic is unlikely due to a fall in HAT incidence. Even if we were unable to demonstrate it directly, it is much more probably the consequence of hampered screening activities and of the fear of the population on subsequent confirmation and linkage to care. Reinforced program monitoring, alternative control strategies and sustainable financial and human resources allocation are mandatory during post Ebola period to reduce HAT burden in Guinea.

Usage notes

Location

Guinea