The Creation and Rapid Deployment of a Preparedness Plan for Ebola Virus Disease: Lessons from a Large Healthcare System

2015 ◽  
Vol 43 (6) ◽  
pp. S15-S16
Author(s):  
Julia Moody ◽  
Scott Cormier ◽  
Jason Hickok ◽  
Edward Septimus ◽  
Ravi Chari ◽  
...  
2021 ◽  
Vol 6 (3) ◽  
pp. p28
Author(s):  
Elizabeth Armstrong-Mensah ◽  
Bianca Tenney ◽  
Victoria Hawley

Between 2014 and 2016, the three West African countries of Guinea, Liberia and Sierra Leone experienced the deadliest Ebola virus disease (EVD) outbreak in sub-Saharan Africa. Two years later, a tenth epidemic recurred in the Democratic Republic of Congo (DRC), specifically in the North Kivu and Ituri provinces, which lasted until June 2020. Though they occurred in different countries, a review of how the EVD outbreaks in Guinea, Liberia, Sierra Leone, and the DRC were handled by the respective country governments, reveal gaps in disease detection, response and action due to lack of surveillance, an EVD preparedness plan, and weak health systems. This perspective discusses the EVD outbreaks in Guinea, Liberia, Sierra Leone, and the DRC, their effects, and draws attention to gaps that need to be addressed by these countries in order to be better prepared to handle future outbreaks. Acting on the proposed recommendations will not only benefit Guinea, Liberia, Sierra Leone, and the DRC in the future, but will be of benefit to EVD susceptible countries in sub-Saharan Africa, as we live in a global community where diseases are no respecters of boundaries.


2017 ◽  
Vol 25 (04) ◽  
pp. 587-603 ◽  
Author(s):  
YUSUKE ASAI ◽  
HIROSHI NISHIURA

The effective reproduction number [Formula: see text], the average number of secondary cases that are generated by a single primary case at calendar time [Formula: see text], plays a critical role in interpreting the temporal transmission dynamics of an infectious disease epidemic, while the case fatality risk (CFR) is an indispensable measure of the severity of disease. In many instances, [Formula: see text] is estimated using the reported number of cases (i.e., the incidence data), but such report often does not arrive on time, and moreover, the rate of diagnosis could change as a function of time, especially if we handle diseases that involve substantial number of asymptomatic and mild infections and large outbreaks that go beyond the local capacity of reporting. In addition, CFR is well known to be prone to ascertainment bias, often erroneously overestimated. In this paper, we propose a joint estimation method of [Formula: see text] and CFR of Ebola virus disease (EVD), analyzing the early epidemic data of EVD from March to October 2014 and addressing the ascertainment bias in real time. To assess the reliability of the proposed method, coverage probabilities were computed. When ascertainment effort plays a role in interpreting the epidemiological dynamics, it is useful to analyze not only reported (confirmed or suspected) cases, but also the temporal distribution of deceased individuals to avoid any strong impact of time dependent changes in diagnosis and reporting.


2021 ◽  
Vol 12 (1) ◽  
Author(s):  
T. R. W. Tipton ◽  
Y. Hall ◽  
J. A. Bore ◽  
A. White ◽  
L. S. Sibley ◽  
...  

AbstractZaireebolavirus (EBOV) is a highly pathogenic filovirus which can result in Ebola virus disease (EVD); a serious medical condition that presents as flu like symptoms but then often leads to more serious or fatal outcomes. The 2013–16 West Africa epidemic saw an unparalleled number of cases. Here we show characterisation and identification of T cell epitopes in surviving patients from Guinea to the EBOV glycoprotein. We perform interferon gamma (IFNγ) ELISpot using a glycoprotein peptide library to identify T cell epitopes and determine the CD4+ or CD8+ T cell component response. Additionally, we generate data on the T cell phenotype and measure polyfunctional cytokine secretion by these antigen specific cells. We show candidate peptides able to elicit a T cell response in EBOV survivors and provide inferred human leukocyte antigen (HLA) allele restriction. This data informs on the long-term T cell response to Ebola virus disease and highlights potentially important immunodominant peptides.


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