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

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.

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

10.7287/peerj.preprints.569v2 ◽

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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Ebola virus disease outbreak in Nigeria: lessons to learn

10.7287/peerj.preprints.569v1 ◽

2014 ◽

Cited By ~ 1

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.

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

Proceedings of the National Academy of Sciences ◽

10.1073/pnas.1518587113 ◽

2016 ◽

Vol 113 (16) ◽

pp. 4488-4493 ◽

Cited By ~ 52

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.

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A Mathematical Model with Quarantine States for the Dynamics of Ebola Virus Disease in Human Populations

Computational and Mathematical Methods in Medicine ◽

10.1155/2016/9352725 ◽

2016 ◽

Vol 2016 ◽

pp. 1-29 ◽

Cited By ~ 8

Author(s):

Gideon A. Ngwa ◽

Miranda I. Teboh-Ewungkem

Keyword(s):

Ebola Virus ◽

Emergency Services ◽

Reproduction Number ◽

Virus Disease ◽

Initial Response ◽

Control Measures ◽

Ebola Virus Disease ◽

Effective Control ◽

Human Populations ◽

Threshold Parameter

A deterministic ordinary differential equation model for the dynamics and spread of Ebola Virus Disease is derived and studied. The model contains quarantine and nonquarantine states and can be used to evaluate transmission both in treatment centres and in the community. Possible sources of exposure to infection, including cadavers of Ebola Virus victims, are included in the model derivation and analysis. Our model’s results show that there exists a threshold parameter,R0, with the property that when its value is above unity, an endemic equilibrium exists whose value and size are determined by the size of this threshold parameter, and when its value is less than unity, the infection does not spread into the community. The equilibrium state, when it exists, is locally and asymptotically stable with oscillatory returns to the equilibrium point. The basic reproduction number,R0, is shown to be strongly dependent on the initial response of the emergency services to suspected cases of Ebola infection. When intervention measures such as quarantining are instituted fully at the beginning, the value of the reproduction number reduces and any further infections can only occur at the treatment centres. Effective control measures, to reduceR0to values below unity, are discussed.

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Analysis of a Multiscale Model of Ebola Virus Disease

Asian Research Journal of Mathematics ◽

10.9734/arjom/2020/v16i630197 ◽

2020 ◽

pp. 53-69

Author(s):

Duncan O. Oganga ◽

George O. Lawi ◽

Colleta A. Okaka

Keyword(s):

Ebola Virus ◽

Reproduction Number ◽

Virus Disease ◽

Equilibrium Points ◽

Vaccination Strategy ◽

Multiscale Model ◽

Ebola Virus Disease ◽

Disease Spread ◽

The Impact ◽

Disease Free

Multiscale models are ones that link the epidemiological processes dealing with the transmission between hosts and the immunological processes dealing with the dynamics within one host. In this study, a multiscale model of Ebola Virus Disease linking epidemiological and immunological processes has been developed and analysed. The model has considered two infectious classes ; the exposed and the infected individuals. Local and global stability analyses of the Disease Free Equilibrium and the Endemic Equilibrium points of the model show that the disease dies out if the basic reproduction number Rc0 < 1 and persists in the population when Rc0 > 1 respectively. Sensitivity analysis shows that the rate of vaccination, v , is the most sensitive parameter. This indicates that effort should be directed towards implementing an effective vaccination strategy to control the spread of the disease. It has also been established that when treatment efficacy is scaled up, the viral load goes down and consequently, the transmission between hosts is also reduced. The impact of treatment on the disease spread has also been established through the coupling function (L∗) . The study indicates that a higher percentage of the exposed and the infected individuals should be treated to control the spread of the disease within the population.

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