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Original Articles
Data Fitting and Scenario Analysis of Vaccination in the 2014 Ebola Outbreak in Liberia
Zhifu Xie
Osong Public Health Res Perspect. 2019;10(3):187-201.   Published online June 30, 2019
DOI: https://doi.org/10.24171/j.phrp.2019.10.3.10
  • 4,106 View
  • 175 Download
  • 7 Citations
AbstractAbstract PDF
Objectives

This study aimed to extend an epidemiological model (SEIHFR) to analyze epidemic trends, and evaluate intervention efficacy.

Methods

SEIHFR was modified to examine disease transmission dynamics after vaccination for the Ebola outbreak. Using existing data from Liberia, sensitivity analysis of various epidemic scenarios was used to inform the model structure, estimate the basic reproduction number ℜ0 and investigate how the vaccination could effectively change the course of the epidemic.

Results

If a randomized mass vaccination strategy was adopted, vaccines would be administered prophylactically or as early as possible (depending on the availability of vaccines). An effective vaccination rate threshold for Liberia was estimated as 48.74% among susceptible individuals. If a ring vaccination strategy was adopted to control the spread of the Ebola virus, vaccines would be given to reduce the transmission rate improving the tracing rate of the contact persons of an infected individual.

Conclusion

The extended SEIHFR model predicted the total number of infected cases, number of deaths, number of recoveries, and duration of outbreaks among others with different levels of interventions such as vaccination rate. This model may be used to better understand the spread of Ebola and develop strategies that may achieve a disease-free state.

Citations

Citations to this article as recorded by  
  • Risk-averse multi-stage stochastic programming to optimizing vaccine allocation and treatment logistics for effective epidemic response
    Xuecheng Yin, İ Esra Büyüktahtakın
    IISE Transactions on Healthcare Systems Engineerin.2022; 12(1): 52.     CrossRef
  • Model-based evaluation of the impact of prophylactic vaccination applied to Ebola epidemics in Sierra Leone and Democratic Republic of Congo
    Ravi Potluri, Amit Kumar, Valérie Oriol-mathieu, Thierry Van Effelterre, Laurent Metz, Hitesh Bhandari
    BMC Infectious Diseases.2022;[Epub]     CrossRef
  • A secure data fitting scheme based on CKKS homomorphic encryption for medical IoT
    Yunxuan Su, Xu An Wang, Weidong Du, Yu Ge, Kaiyang Zhao, Ming Lv
    Journal of High Speed Networks.2022; : 1.     CrossRef
  • A hybrid simulation model to study the impact of combined interventions on Ebola epidemic
    Peiyu Chen, Wenhui Fan, Xudong Guo, Constantinos Siettos
    PLOS ONE.2021; 16(7): e0254044.     CrossRef
  • Transmission dynamics of the COVID‐19 outbreak and effectiveness of government interventions: A data‐driven analysis
    Yaqing Fang, Yiting Nie, Marshare Penny
    Journal of Medical Virology.2020; 92(6): 645.     CrossRef
  • Impact of prophylactic vaccination strategies on Ebola virus transmission: A modeling analysis
    Ravi Potluri, Amit Kumar, Vikalp Maheshwari, Charlie Smith, Valerie Oriol Mathieu, Kerstin Luhn, Benoit Callendret, Hitesh Bhandari, Malaya Kumar Sahoo
    PLOS ONE.2020; 15(4): e0230406.     CrossRef
  • Modeling the 2014–2015 Ebola Virus Disease Outbreaks in Sierra Leone, Guinea, and Liberia with Effect of High- and Low-risk Susceptible Individuals
    Qianying Lin, Salihu S. Musa, Shi Zhao, Daihai He
    Bulletin of Mathematical Biology.2020;[Epub]     CrossRef
One-Step Reverse Transcription-Polymerase Chain Reaction for Ebola and Marburg Viruses
Sun-Whan Park, Ye-Ji Lee, Won-Ja Lee, Youngmee Jee, WooYoung Choi
Osong Public Health Res Perspect. 2016;7(3):205-209.   Published online June 30, 2016
DOI: https://doi.org/10.1016/j.phrp.2016.04.004
  • 1,862 View
  • 23 Download
  • 5 Citations
AbstractAbstract PDF
Objectives
Ebola and Marburg viruses (EBOVs and MARVs, respectively) are causative agents of severe hemorrhagic fever with high mortality rates in humans and nonhuman primates. In 2014, there was a major Ebola outbreak in various countries in West Africa, including Guinea, Liberia, Republic of Sierra Leone, and Nigeria. EBOV and MARV are clinically difficult to diagnose and distinguish from other African epidemic diseases. Therefore, in this study, we aimed to develop a method for rapid identification of the virus to prevent the spread of infection.
Methods
We established a conventional one-step reverse transcription-polymerase chain reaction (RT-PCR) assay for these pathogens based on the Superscript Reverse Transcriptase-Platinum Taq polymerase enzyme mixture. All assays were thoroughly optimized using in vitro-transcribed RNA.
Results
We designed seven primer sets of nucleocapsid protein (NP) genes based on sequences from seven filoviruses, including five EBOVs and two MARVs. To evaluate the sensitivity of the RT-PCR assay for each filovirus, 10-fold serial dilutions of synthetic viral RNA transcripts of EBOV or MARV NP genes were used to assess detection limits of viral RNA copies. The potential for these primers to cross react with other filoviruses was also examined. The results showed that the primers were specific for individual genotype detection in the examined filoviruses.
Conclusion
The assay established in this study may facilitate rapid, reliable laboratory diagnosis in suspected cases of Ebola and Marburg hemorrhagic fevers.

Citations

Citations to this article as recorded by  
  • Marburg Virus Disease – A Mini-Review
    Sandip Chakraborty, Deepak Chandran, Ranjan K. Mohapatra, Mahmoud Alagawany, Mohd Iqbal Yatoo, Md. Aminul Islam, Anil K. Sharma, Kuldeep Dhama
    Journal of Experimental Biology and Agricultural S.2022; 10(4): 689.     CrossRef
  • Marburgviruses: An Update
    Caterina M Miraglia
    Laboratory Medicine.2019; 50(1): 16.     CrossRef
  • Ebola virus: A global public health menace: A narrative review
    Shamimul Hasan, SyedAnsar Ahmad, Rahnuma Masood, Shazina Saeed
    Journal of Family Medicine and Primary Care.2019; 8(7): 2189.     CrossRef
  • Fast and Parallel Detection of Four Ebola Virus Species on a Microfluidic-Chip-Based Portable Reverse Transcription Loop-Mediated Isothermal Amplification System
    Xue Lin, Xiangyu Jin, Bin Xu, Ruliang Wang, Rongxin Fu, Ya Su, Kai Jiang, Han Yang, Ying Lu, Yong Guo, Guoliang Huang
    Micromachines.2019; 10(11): 777.     CrossRef
  • The current landscape of nucleic acid tests for filovirus detection
    David J. Clark, John Tyson, Andrew D. Sails, Sanjeev Krishna, Henry M. Staines
    Journal of Clinical Virology.2018; 103: 27.     CrossRef
Modeling the Spread of Ebola
Tae Sug Do, Young S. Lee
Osong Public Health Res Perspect. 2016;7(1):43-48.   Published online February 28, 2016
DOI: https://doi.org/10.1016/j.phrp.2015.12.012
  • 1,931 View
  • 17 Download
  • 13 Citations
AbstractAbstract PDF
Objectives
This study aims to create a mathematical model to better understand the spread of Ebola, the mathematical dynamics of the disease, and preventative behaviors.
Methods
An epidemiological model is created with a system of nonlinear differential equations, and the model examines the disease transmission dynamics with isolation through stability analysis. All parameters are approximated, and results are also exploited by simulations. Sensitivity analysis is used to discuss the effect of intervention strategies.
Results
The system has only one equilibrium point, which is the disease-free state (S,L,I,R,D) = (N,0,0,0,0). If traditional burials of Ebola victims are allowed, the possible end state is never stable. Provided that safe burial practices with no traditional rituals are followed, the endemic-free state is stable if the basic reproductive number, R0, is less than 1. Model behaviors correspond to empirical facts. The model simulation agrees with the data of the Nigeria outbreak in 2004: 12 recoveries, eight deaths, Ebola free in about 3 months, and an R0 value of about 2.6 initially, which signifies swift spread of the infection. The best way to reduce R0 is achieving the speedy net effect of intervention strategies. One day's delay in full compliance with building rings around the virus with isolation, close observation, and clear education may double the number of infected cases.
Conclusion
The model can predict the total number of infected cases, number of deaths, and duration of outbreaks among others. The model can be used to better understand the spread of Ebola, educate about prophylactic behaviors, and develop strategies that alter environment to achieve a disease-free state. A future work is to incorporate vaccination in the model when the vaccines are developed and the effects of vaccines are known better.

Citations

Citations to this article as recorded by  
  • Mathematical Models for Typhoid Disease Transmission: A Systematic Literature Review
    Sanubari Tansah Tresna, Subiyanto, Sudradjat Supian
    Mathematics.2022; 10(14): 2506.     CrossRef
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    Mohammed Subhi Hadi, Bülent Bilgehan
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    Seda İğret Araz
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    Lagès Nadège Mouanguissa, Abdul A. Kamara, Xiangjun Wang
    Mathematical Methods in the Applied Sciences.2021; 44(7): 5739.     CrossRef
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    PLOS ONE.2021; 16(8): e0239352.     CrossRef
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    Hamdi Friji, Raby Hamadi, Hakim Ghazzai, Hichem Besbes, Yehia Massoud
    IEEE Access.2021; 9: 13266.     CrossRef
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    Abdul A. Kamara, Xiangjun Wang, Lagès Nadège Mouanguissa
    Applied Mathematics and Computation.2020; 367: 124776.     CrossRef
  • Modelling the daily risk of Ebola in the presence and absence of a potential vaccine
    Stéphanie M.C. Abo, Robert Smith
    Infectious Disease Modelling.2020; 5: 905.     CrossRef
  • Data Fitting and Scenario Analysis of Vaccination in the 2014 Ebola Outbreak in Liberia
    Zhifu Xie
    Osong Public Health and Research Perspectives.2019; 10(3): 187.     CrossRef
  • Effect of sexual transmission on the West Africa Ebola outbreak in 2014: a mathematical modelling study
    Dongmei Luo, Rongjiong Zheng, Duolao Wang, Xueliang Zhang, Yi Yin, Kai Wang, Weiming Wang
    Scientific Reports.2019;[Epub]     CrossRef
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    International Journal of Biomathematics.2018; 11(07): 1850093.     CrossRef
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    Joan M. King, Chetan Tiwari, Armin R. Mikler, Martin O’Neill
    Disaster Medicine and Public Health Preparedness.2018; 12(5): 563.     CrossRef
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Brief Reports
Round-up of GHSA Steering Group and Action Packages in 2015
GHSA Steering Group Secretariat, GHSA Preparation Task Force Team
Osong Public Health Res Perspect. 2015;6(6 Suppl):S28-S33.   Published online December 31, 2015
DOI: https://doi.org/10.1016/j.phrp.2015.12.007
  • 1,787 View
  • 16 Download
  • 1 Citations
AbstractAbstract PDF
All Global Health Security Agenda (GHSA) Steering Group Members remain strongly committed to accelerating measurable progress and implementing concrete commitments toward a world safe and secure from infectious disease threats, recognizing the devastation of the Ebola epidemic and the clear interdependence of health in the 21st century. All GHSA Steering Group members reinforced that GHSA is supportive of International Health Regulations implementation, as well as components of other global health security frameworks such as the World Organization for Animal Health Performance of Veterinary Services pathway. The GHSA will continue to focus on multilateral engagement. The GHSA Steering Group is committed to engaging non-state actors and agreed to discuss next steps toward engaging the private sector.

Citations

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  • Strengthening health systems in Africa: a case study of the Kenya field epidemiology training program for local frontline health workers
    Zeinab Gura Roka, Jane Githuku, Mark Obonyo, Waqo Boru, Tura Galgalo, Samuel Amwayi, Jackson Kioko, David Njoroge, James Anthony Ransom
    Public Health Reviews.2017;[Epub]     CrossRef
Global Health Security: The Lessons from the West African Ebola Virus Disease Epidemic and MERS Outbreak in the Republic of Korea
GHSA Preparation Task Force Team
Osong Public Health Res Perspect. 2015;6(6 Suppl):S25-S27.   Published online December 31, 2015
DOI: https://doi.org/10.1016/j.phrp.2015.12.006
  • 1,705 View
  • 22 Download
  • 7 Citations
AbstractAbstract PDF
The Ebola virus disease outbreak in West Africa and the Middle East Respiratory Syndrome outbreak in the Republic of Korea have given huge impacts in different aspects. Health security is no more a new coinage. Global health security became more realistic in its practical application. In the perspective of global health, it will be helpful to peruse lessons learned from the Ebola outbreak in West Africa and MERS outbreak in Korea.

Citations

Citations to this article as recorded by  
  • Next generation sequencing of SARS-CoV-2 genomes: challenges, applications and opportunities
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    Sulzhan Bali, Jessica Taaffe
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Ebola Hemorrhagic Fever and the Current State of Vaccine Development
Joo Eun Hong, Kee-Jong Hong, Woo Young Choi, Won-Ja Lee, Yeon Hwa Choi, Chung-Hyeon Jeong, Kwang-il Cho
Osong Public Health Res Perspect. 2014;5(6):378-382.   Published online December 31, 2014
DOI: https://doi.org/10.1016/j.phrp.2014.09.006
  • 2,102 View
  • 15 Download
  • 5 Citations
AbstractAbstract PDF
Current Ebola virus outbreak in West Africa already reached the total number of 1,323 including 729 deaths by July 31st. the fatality is around 55% in the southeastern area of Guinea, Sierra Leone, Liberia, and Nigeria. The number of patients with Ebola Hemorrhagic Fever (EHF) was continuously increasing even though the any effective therapeutics or vaccines has not been developed yet. The Ebola virus in Guinea showed 98% homology with Zaire Ebola Virus.Study of the pathogenesis of Ebola virus infection and assess of the various candidates of vaccine have been tried for a long time, especially in United States and some European countries. Even though the attenuated live vaccine and DNA vaccine containing Ebola viral genes were tested and showed efficacy in chimpanzees, those candidates still need clinical tests requiring much longer time than the preclinical development to be approved for the practical treatment.It can be expected to eradicate Ebola virus by a safe and efficient vaccine development similar to the case of smallpox virus which was extinguished from the world by the variola vaccine.

Citations

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    Current Opinion in Pharmacology.2021; 60: 46.     CrossRef
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Invited Original Article
Incubation Period of Ebola Hemorrhagic Virus Subtype Zaire
Martin Eichner, Scott F. Dowell, Nina Firese
Osong Public Health Res Perspect. 2011;2(1):3-7.   Published online June 30, 2011
DOI: https://doi.org/10.1016/j.phrp.2011.04.001
  • 2,771 View
  • 14 Download
  • 39 Citations
AbstractAbstract PDF
Objectives
Ebola hemorrhagic fever has killed over 1300 people, mostly in equatorial Africa. There is still uncertainty about the natural reservoir of the virus and about some of the factors involved in disease transmission. Until now, a maximum incubation period of 21 days has been assumed.
Methods
We analyzed data collected during the Ebola outbreak (subtype Zaire) in Kikwit, Democratic Republic of the Congo, in 1995 using maximum likelihood inference and assuming a log-normally distributed incubation period.
Results
The mean incubation period was estimated to be 12.7 days (standard deviation 4.31 days), indicating that about 4.1% of patients may have incubation periods longer than 21 days.
Conclusion
If the risk of new cases is to be reduced to 1% then 25 days should be used when investigating the source of an outbreak, when determining the duration of surveillance for contacts, and when declaring the end of an outbreak.

Citations

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PHRP : Osong Public Health and Research Perspectives