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- Phylogenetic and genome-wide mutational analysis of SARS-CoV-2 strains circulating in Nigeria: no implications for attenuated COVID-19 outcomes
- Daniel B. Kolawole, Malachy I. Okeke
- Osong Public Health Res Perspect. 2022;13(2):101-113. Published online April 22, 2022
- DOI: https://doi.org/10.24171/j.phrp.2021.0329
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Abstract
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- Objectives
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the causative agent of coronavirus disease 2019 (COVID-19). The COVID-19 incidence and mortality rates are low in Nigeria compared to global trends. This research mapped the evolution of SARS-CoV-2 circulating in Nigeria and globally to determine whether the Nigerian isolates are genetically distinct from strains circulating in regions of the world with a high disease burden. Methods: Bayesian phylogenetics using BEAST 2.0, genetic similarity analyses, and genomewide mutational analyses were used to characterize the strains of SARS-CoV-2 isolated in Nigeria. Results: SARS-CoV-2 strains isolated in Nigeria showed multiple lineages and possible introductions from Europe and Asia. Phylogenetic clustering and sequence similarity analyses demonstrated that Nigerian isolates were not genetically distinct from strains isolated in other parts of the globe. Mutational analysis demonstrated that the D614G mutation in the spike protein, the P323L mutation in open reading frame 1b (and more specifically in NSP12), and the R203K/ G204R mutation pair in the nucleocapsid protein were most prevalent in the Nigerian isolates. Conclusion: The SARS-CoV-2 strains in Nigeria were neither phylogenetically nor genetically distinct from virus strains circulating in other countries of the world. Thus, differences in SARS-CoV-2 genomes are not a plausible explanation for the attenuated COVID-19 outcomes in Nigeria.
- 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
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- 7 Crossref
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Abstract
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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.
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Citations
Citations to this article as recorded by
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Journal of High Speed Networks.2023; 29(1): 41. CrossRef - 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
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BMC Infectious Diseases.2022;[Epub] CrossRef - A hybrid simulation model to study the impact of combined interventions on Ebola epidemic
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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
- A secure data fitting scheme based on CKKS homomorphic encryption for medical IoT
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