scholarly journals Measuring the impact of Ebola control measures in Sierra Leone

2015 ◽  
Vol 112 (46) ◽  
pp. 14366-14371 ◽  
Author(s):  
Adam J. Kucharski ◽  
Anton Camacho ◽  
Stefan Flasche ◽  
Rebecca E. Glover ◽  
W. John Edmunds ◽  
...  
Keyword(s):  
Sierra Leone ◽  
Ebola Virus ◽  
Virus Disease ◽  
Credible Interval ◽  
Additional Treatment ◽  
Control Measures ◽  
Direct Result ◽  
Epidemic Dynamics ◽  
International Response ◽  
The Impact

Between September 2014 and February 2015, the number of Ebola virus disease (EVD) cases reported in Sierra Leone declined in many districts. During this period, a major international response was put in place, with thousands of treatment beds introduced alongside other infection control measures. However, assessing the impact of the response is challenging, as several factors could have influenced the decline in infections, including behavior changes and other community interventions. We developed a mathematical model of EVD transmission, and measured how transmission changed over time in the 12 districts of Sierra Leone with sustained transmission between June 2014 and February 2015. We used the model to estimate how many cases were averted as a result of the introduction of additional treatment beds in each area. Examining epidemic dynamics at the district level, we estimated that 56,600 (95% credible interval: 48,300–84,500) Ebola cases (both reported and unreported) were averted in Sierra Leone up to February 2, 2015 as a direct result of additional treatment beds being introduced. We also found that if beds had been introduced 1 month earlier, a further 12,500 cases could have been averted. Our results suggest the unprecedented local and international response led to a substantial decline in EVD transmission during 2014–2015. In particular, the introduction of beds had a direct impact on reducing EVD cases in Sierra Leone, although the effect varied considerably between districts.

scholarly journals The impact of active surveillance and health education on an Ebola virus disease cluster — Kono District, Sierra Leone, 2014–2015

2016 ◽  
Vol 16 (1) ◽  
Author(s):  
Tasha Stehling-Ariza ◽  
Alexander Rosewell ◽  
Sahr A. Moiba ◽  
Brima Berthalomew Yorpie ◽  
Kai David Ndomaina ◽  
...  
Keyword(s):  
Health Education ◽  
Sierra Leone ◽  
Active Surveillance ◽  
Ebola Virus ◽  
Virus Disease ◽  
Ebola Virus Disease ◽  
Disease Cluster ◽  
The Impact ◽  
Kono District

scholarly journals Transmission dynamics of Ebola virus disease and intervention effectiveness in Sierra Leone

2016 ◽  
Vol 113 (16) ◽  
pp. 4488-4493 ◽  
Author(s):  
Li-Qun Fang ◽  
Yang Yang ◽  
Jia-Fu Jiang ◽  
Hong-Wu Yao ◽  
David Kargbo ◽  
...  
Keyword(s):  
Sierra Leone ◽  
Ebola Virus ◽  
Virus Disease ◽  
Atmospheric Temperature ◽  
Transmission Dynamics ◽  
Ebola Virus Disease ◽  
Transmission Model ◽  
Household Transmission ◽  
Secondary Infections ◽  
The Impact

Sierra Leone is the most severely affected country by an unprecedented outbreak of Ebola virus disease (EVD) in West Africa. Although successfully contained, the transmission dynamics of EVD and the impact of interventions in the country remain unclear. We established a database of confirmed and suspected EVD cases from May 2014 to September 2015 in Sierra Leone and mapped the spatiotemporal distribution of cases at the chiefdom level. A Poisson transmission model revealed that the transmissibility at the chiefdom level, estimated as the average number of secondary infections caused by a patient per week, was reduced by 43% [95% confidence interval (CI): 30%, 52%] after October 2014, when the strategic plan of the United Nations Mission for Emergency Ebola Response was initiated, and by 65% (95% CI: 57%, 71%) after the end of December 2014, when 100% case isolation and safe burials were essentially achieved, both compared with before October 2014. Population density, proximity to Ebola treatment centers, cropland coverage, and atmospheric temperature were associated with EVD transmission. The household secondary attack rate (SAR) was estimated to be 0.059 (95% CI: 0.050, 0.070) for the overall outbreak. The household SAR was reduced by 82%, from 0.093 to 0.017, after the nationwide campaign to achieve 100% case isolation and safe burials had been conducted. This study provides a complete overview of the transmission dynamics of the 2014−2015 EVD outbreak in Sierra Leone at both chiefdom and household levels. The interventions implemented in Sierra Leone seem effective in containing the epidemic, particularly in interrupting household transmission.

scholarly journals Mathematical modeling and comparative analysis of the Ebola epidemic reveal effective control measures

2019 ◽  
Author(s):  
Junlong Li ◽  
Caiping Song ◽  
Jingya Yang ◽  
Jingmin Zheng ◽  
Lina Zhou ◽  
...  
Keyword(s):  
Mathematical Modeling ◽  
Comparative Analysis ◽  
Sierra Leone ◽  
Development Process ◽  
Ebola Virus ◽  
Virus Disease ◽  
Control Measures ◽  
Effective Control ◽  
Epidemic Outbreak ◽  
And Control

Abstract The Ebola virus disease (EVD) is a highly contagious disease which is caused by the Ebola virus . Various measures were used to prevent and control the spread of EVD. The aim of this study was to find out the most critical measures to prevent and control the spread of EVD. Both mathematical modeling and comparative analysis were used to explore the development process of EVD outbreak in Guinea, Liberia and Sierra Leone. The results of comparative analysis showed quarantined individuals before infection (R 2 = 0.848, ε = 1.012), safe burial teams (R 2 = 0.772, ε = 0.385), and the Ebola treatment units (ETU) bed (R 2 = 0.690, ε = 0.432) could significantly influence the incidence of EVD which were consistent with the results of mathematical modeling. These findings indicted that a timely and effective quarantine played a significant role in preventing and controlling the spread of EVD, and the findings would help us prevent and control the epidemic outbreak of new infectious disease in the future.

scholarly journals PO 8473 IMPACT OF EBOLA ON SLEEPING SICKNESS IN COASTAL GUINEA: A RETROSPECTIVE ANALYSIS (2012–2017) FROM THE GUINEAN NATIONAL CONTROL PROGRAMME

2019 ◽  
Vol 4 (Suppl 3) ◽  
pp. A42.2-A42
Author(s):  
Oumou Camara ◽  
Hamidou Ilboudo ◽  
Mariame Camara ◽  
Eric Ouattara ◽  
Alexandre Duvignaud ◽  
...  
Keyword(s):  
Retrospective Analysis ◽  
Ebola Virus ◽  
Virus Disease ◽  
Public Health Problem ◽  
Control Programme ◽  
Control Measures ◽  
Republic Of The Congo ◽  
Set Up ◽  
Elimination Goal ◽  
The Impact

BackgroundCoastal Guinea harbours the most active human African trypanosomiasis (HAT) foci in West Africa. The Guinean government and its partners are conducting HAT control activities to reduce the burden of this neglected tropical disease and, as set-up by WHO, to eliminate it as a public health problem by 2020. Unfortunately, control efforts were deeply impaired during the Ebola outbreak that struck the country in 2014–2015. The aim of the study was to evaluate the impact of this unprecedented outbreak on HAT screening and care activities and more generally on T. brucei gambiense transmission.MethodsA retrospective analysis of the data collected by the HAT-NCP between 2012 and 2013 (pre-Ebola period) and 2014–2015 (Ebola outbreak) has shown an interruption of active HAT screening activities and a rapid decrease of passive HAT screening activities as the Ebola outbreak was spreading. During the Ebola epidemic, HAT patients were also diagnosed in a later stage of the disease and attendance to post-treatment control visits was also severely affected.ResultsOnly 59 HAT patients were diagnosed and treated during the Ebola outbreak (January 2014–October 2015) as compared to 154 before the outbreak (February 2012–December 2013). This potentially large undiagnosed human reservoir of trypanosomes may have contributed to increased transmission levels. After Guinea was declared free of Ebola virus disease, screening activities (both passive and active) were progressively resumed. In 2016 and 2017, Guinea reported 107 and 140 HAT cases, respectively (almost twice as much as during the pre-Ebola period) and became the second most affected country after the Democratic Republic of the Congo.ConclusionA major lesson taken from the Ebola outbreak is that disruption of medical care may lead to a quick HAT burst in areas of high transmission. Current HAT control measures combining screening and tsetse control interventions will help to stay on course for the elimination goal.

scholarly journals Ebola virus disease outbreak in Nigeria: transmission dynamics and rapid control

2015 ◽  
Author(s):  
Christian L Althaus ◽  
Nicola Low ◽  
Emmanuel O. Musa ◽  
Faisal Shuaib ◽  
Sandro Gsteiger
Keyword(s):  
Ebola Virus ◽  
Reproduction Number ◽  
Time Window ◽  
Index Case ◽  
Virus Disease ◽  
Control Measures ◽  
Ebola Virus Disease ◽  
Transmission Model ◽  
The Individual ◽  
The Impact

International air travel has already spread Ebola virus disease (EVD) to major cities as part of the unprecedented epidemic that started in Guinea in December 2013. An infected airline passenger arrived in Nigeria on July 20, 2014 and caused an outbreak in Lagos and then Port Harcourt. After a total of 20 reported cases, including 8 deaths, Nigeria was declared EVD free on October 20, 2014. We quantified the impact of early control measures in preventing further spread of EVD in Nigeria and calculated the risk that a single undetected case will cause a new outbreak. We fitted an EVD transmission model to data from the outbreak in Nigeria and estimated the individual reproduction number of the index case at 9.0 (95% confidence interval [CI]: 5.2-15.6). We also found that the net reproduction number fell below unity 15 days (95% CI: 11-21 days) after the arrival of the index case. Hence, our study illustrates the time window for successful containment of EVD outbreaks caused by infected air travelers.

scholarly journals Ebola virus disease outbreak in Nigeria: lessons to learn

2014 ◽  
Author(s):  
Christian L Althaus ◽  
Sandro Gsteiger ◽  
Nicola Low
Keyword(s):  
Ebola Virus ◽  
Reproduction Number ◽  
Virus Disease ◽  
Control Measures ◽  
Ebola Virus Disease ◽  
Transmission Model ◽  
Port Harcourt ◽  
Airline Passenger ◽  
Net Reproduction ◽  
The Impact

International air travel has already spread Ebola virus disease (EVD) to major cities as part of the unprecedented epidemic that started in Guinea in December 2013. An infected airline passenger arrived in Nigeria on July 20, 2014 and caused an outbreak in Lagos and then Port Harcourt. After a total of 20 reported cases, including 8 deaths, Nigeria was declared EVD free on October 20, 2014. We quantified the impact of early control measures in preventing further spread of EVD in Nigeria and calculated the risk that a single undetected case will cause a new outbreak. We fitted an EVD transmission model to data from the outbreak in Nigeria and estimated the basic reproduction number R0 = 9.0 (95% confidence interval [CI]: 5.2-15.6). We also found that the net reproduction number Rt fell below unity 15 days (95% CI: 11-21 days) after the arrival of the index case. Using the estimated value of R0 in Nigeria, we calculated that the risk of an outbreak from a single undetected case was 89% (95% CI: 81-94%). Even though R0 in Nigeria was high, EVD outbreaks caused by infected air travelers can be successfully contained if control measures are rapidly implemented.

scholarly journals Ebola virus disease outbreak in Nigeria: transmission dynamics and rapid control

2015 ◽  
Author(s):  
Christian L Althaus ◽  
Nicola Low ◽  
Emmanuel O. Musa ◽  
Faisal Shuaib ◽  
Sandro Gsteiger
Keyword(s):  
Ebola Virus ◽  
Reproduction Number ◽  
Time Window ◽  
Index Case ◽  
Virus Disease ◽  
Control Measures ◽  
Ebola Virus Disease ◽  
Transmission Model ◽  
The Individual ◽  
The Impact

International air travel has already spread Ebola virus disease (EVD) to major cities as part of the unprecedented epidemic that started in Guinea in December 2013. An infected airline passenger arrived in Nigeria on July 20, 2014 and caused an outbreak in Lagos and then Port Harcourt. After a total of 20 reported cases, including 8 deaths, Nigeria was declared EVD free on October 20, 2014. We quantified the impact of early control measures in preventing further spread of EVD in Nigeria and calculated the risk that a single undetected case will cause a new outbreak. We fitted an EVD transmission model to data from the outbreak in Nigeria and estimated the individual reproduction number of the index case at 9.0 (95% confidence interval [CI]: 5.2-15.6). We also found that the net reproduction number fell below unity 15 days (95% CI: 11-21 days) after the arrival of the index case. Hence, our study illustrates the time window for successful containment of EVD outbreaks caused by infected air travelers.

scholarly journals Ebola virus disease outbreak in Nigeria: transmission dynamics and rapid control

2014 ◽  
Author(s):  
Christian L Althaus ◽  
Sandro Gsteiger ◽  
Emmanuel O. Musa ◽  
Faisal Shuaib ◽  
Nicola Low
Keyword(s):  
Ebola Virus ◽  
Reproduction Number ◽  
Time Window ◽  
Virus Disease ◽  
Control Measures ◽  
Ebola Virus Disease ◽  
Transmission Model ◽  
Airline Passenger ◽  
Net Reproduction ◽  
The Impact

International air travel has already spread Ebola virus disease (EVD) to major cities as part of the unprecedented epidemic that started in Guinea in December 2013. An infected airline passenger arrived in Nigeria on July 20, 2014 and caused an outbreak in Lagos and then Port Harcourt. After a total of 20 reported cases, including 8 deaths, Nigeria was declared EVD free on October 20, 2014. We quantified the impact of early control measures in preventing further spread of EVD in Nigeria and calculated the risk that a single undetected case will cause a new outbreak. We fitted an EVD transmission model to data from the outbreak in Nigeria and estimated the basic reproduction number R0 = 9.0 (95% confidence interval [CI]: 5.2-15.6). We also found that the net reproduction number Rt fell below unity 15 days (95% CI: 11-21 days) after the arrival of the index case. Using the estimated value of R0 in Nigeria, we calculated that the risk of an outbreak from a single undetected case was 89% (95% CI: 81-94%). Even though R0 can be high, our study illustrates the time window for successful containment of EVD outbreaks caused by infected air travelers.

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