Early Transmission Dynamics of Novel Coronavirus (COVID-19) in Nigeria

On 31 December 2019, the World Health Organization (WHO) was notified of a novel coronavirus disease in China that was later named COVID-19. On 11 March 2020, the outbreak of COVID-19 was declared a pandemic. The first instance of the virus in Nigeria was documented on 27 February 2020. This study provides a preliminary epidemiological analysis of the first 45 days of COVID-19 outbreak in Nigeria. We estimated the early transmissibility via time-varying reproduction number based on the Bayesian method that incorporates uncertainty in the distribution of serial interval (time interval between symptoms onset in an infected individual and the infector), and adjusted for disease importation. By 11 April 2020, 318 confirmed cases and 10 deaths from COVID-19 have occurred in Nigeria. At day 45, the exponential growth rate was 0.07 (95% confidence interval (CI): 0.05–0.10) with a doubling time of 9.84 days (95% CI: 7.28–15.18). Separately for imported cases (travel-related) and local cases, the doubling time was 12.88 days and 2.86 days, respectively. Furthermore, we estimated the reproduction number for each day of the outbreak using a three-weekly window while adjusting for imported cases. The estimated reproduction number was 4.98 (95% CrI: 2.65–8.41) at day 22 (19 March 2020), peaking at 5.61 (95% credible interval (CrI): 3.83–7.88) at day 25 (22 March 2020). The median reproduction number over the study period was 2.71 and the latest value on 11 April 2020, was 1.42 (95% CrI: 1.26–1.58). These 45-day estimates suggested that cases of COVID-19 in Nigeria have been remarkably lower than expected and the preparedness to detect needs to be shifted to stop local transmission.

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Novel Coronavirus in Nigeria: Epidemiological analysis of the first 45 days of the pandemic

10.1101/2020.04.14.20064949 ◽

2020 ◽

Cited By ~ 1

Author(s):

Oyelola A. Adegboye ◽

Adeshina I. Adekunle ◽

Ezra Gayawan

Keyword(s):

Doubling Time ◽

Reproduction Number ◽

Infected Individual ◽

World Health ◽

Time Interval ◽

Epidemiological Analysis ◽

Serial Interval ◽

Novel Coronavirus ◽

Health Organization ◽

Local Transmission

AbstractBackgroundOn December 31, 2019, the World Health Organization (WHO) was notified of a novel coronavirus in China that was later named COVID-19. On March 11, 2020, the outbreak of COVID-19 was declared a pandemic. The first instance of the virus in Nigeria was documented on February 27, 2020.MethodsThis study provides a preliminary epidemiological analysis of the first 45 days of COVID-19 outbreak in Nigeria quantifying. We estimated the early transmissibility via time-varying reproduction number based on Bayesian method that incorporates uncertainty in the distribution of serial interval (time interval between symptoms onset in an infected individual and the infector) and adjusted for disease importation.FindingsBy April 11, 2020, 318 confirmed cases and 10 deaths from COVID-19 have occurred in Nigeria. At day 45, the exponential growth rate was 0.07 (95% Confidence Interval (CI): 0.05 – 0.10) with doubling time of 9.84 days (95% CI: 7.28 – 15.18). Separately for travel related and local cases the doubling time was 12.88 days and 2.86 days, respectively. Furthermore, we estimated the reproduction number for each day of the outbreak using three-weekly window while adjusting for travel related cases. The estimated reproduction number was 4.98 (95% CrI: 2.65 – 8.41) at day 22 (March 19, 2020), peaking at 5.61 (95% CrI: 3.83 –7.88) at day 25 (March 22, 2020). The median reproduction number over the study period was 2.71 and the latest value at April 11, 2020 was 1.42 (95% CI: 1.26 – 1.58).InterpretationThese 45-day estimates suggested that cases of COVID-19 in Nigeria have been remarkably lower than expected and the preparedness to detect needs to be shifted to stop local transmission.FundingNone

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Implementation of the Integrated Care of Older People (ICOPE) App in Primary Care: New Technologies in Geriatric Care during Quarantine of COVID-19 and Beyond

Journal of Frailty & Aging ◽

10.14283/jfa.2020.24 ◽

2020 ◽

pp. 1-2

Author(s):

D. Sanchez-Rodriguez ◽

C. Annweiler ◽

S. Gillain ◽

B. Vellas

Keyword(s):

New Technologies ◽

Health Care Systems ◽

Action Plan ◽

Credible Interval ◽

Therapeutic Interventions ◽

World Health ◽

Global Priority ◽

Care Systems ◽

Novel Coronavirus ◽

Health Organization

The COVID-19 pandemic due to a novel coronavirus (SARS-CoV-2) in December 2019 has rapidly spread worldwide. The mortality rate is about 2.3% in general population, with high human-to-human transmission of 0.41 (credible interval [0.27, 0.55]), and nasopharyngeal asymptomatic carriers act as vectors within the population (1). The World Health Organization (WHO) declared the pandemic on March 2020, and established objectives and action plan. First, WHO aimed at limiting the transmission of SARS-CoV-2, which required large isolation actions (country borders lockdown and individual quarantine). Second, WHO aimed at guiding and supporting the different health care systems across countries. Finally, developing therapeutic interventions appeared as a global priority as available evidence were still scarce (1). More than 860 clinical trials are ongoing worldwide.

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Modeling the early evolution of the COVID-19 in Brazil: Results from a Susceptible–Infectious–Quarantined–Recovered (SIQR) model

International Journal of Modern Physics C ◽

10.1142/s0129183120501351 ◽

2020 ◽

Vol 31 (10) ◽

pp. 2050135 ◽

Cited By ~ 7

Author(s):

Nuno Crokidakis

Keyword(s):

Severe Acute Respiratory Syndrome ◽

Doubling Time ◽

Reproduction Number ◽

Early Evolution ◽

World Health ◽

Initial Growth ◽

Department Of Health ◽

The World ◽

Health Organization ◽

The Basic Reproduction Number

The world evolution of the severe acute respiratory syndrome coronavirus 2 (SARS-Cov2 or simply COVID-19) led the World Health Organization to declare it a pandemic. The disease appeared in China in December 2019, and it has spread fast around the world, especially in European countries like Italy and Spain. The first reported case in Brazil was recorded in February 26, and after that the number of cases grew fast. In order to slow down the initial growth of the disease through the country, confirmed positive cases were isolated to not transmit the disease. To better understand the early evolution of COVID-19 in Brazil, we apply a Susceptible–Infectious–Quarantined–Recovered (SIQR) model to the analysis of data from the Brazilian Department of Health, obtained from February 26, 2020 through March 25, 2020. Based on analytical and numerical results, as well on the data, the basic reproduction number is estimated to [Formula: see text]. In addition, we estimate that the ratio between unidentified infectious individuals and confirmed cases at the beginning of the epidemic is about 10, in agreement with previous studies. We also estimated the epidemic doubling time to be [Formula: see text] days.

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A mathematical model for simulating the transmission of Wuhan novel Coronavirus

10.1101/2020.01.19.911669 ◽

2020 ◽

Cited By ~ 28

Author(s):

Tianmu Chen ◽

Jia Rui ◽

Qiupeng Wang ◽

Zeyu Zhao ◽

Jing-An Cui ◽

...

Keyword(s):

Network Model ◽

Reproduction Number ◽

Human Infection ◽

World Health ◽

Unknown Etiology ◽

Transmission Network ◽

The World ◽

Infection Source ◽

Novel Coronavirus ◽

Health Organization

AbstractAs reported by the World Health Organization, a novel coronavirus (2019-nCoV) was identified as the causative virus of Wuhan pneumonia of unknown etiology by Chinese authorities on 7 January, 2020. In this study, we developed a Bats-Hosts-Reservoir-People transmission network model for simulating the potential transmission from the infection source (probable be bats) to the human infection. Since the Bats-Hosts-Reservoir network was hard to explore clearly and public concerns were focusing on the transmission from a seafood market (reservoir) to people, we simplified the model as Reservoir-People transmission network model. The basic reproduction number (R0) was calculated from the RP model to assess the transmissibility of the 2019-nCoV.

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Dynamics of HIV-TB Co-Infection Model

Axioms ◽

10.3390/axioms9010029 ◽

2020 ◽

Vol 9 (1) ◽

pp. 29 ◽

Cited By ~ 2

Author(s):

Nita H Shah ◽

Nisha Sheoran ◽

Yash Shah

Keyword(s):

Reproduction Number ◽

Equilibrium Points ◽

Infected Individual ◽

World Health ◽

Infection Model ◽

Model Parameters ◽

Progression Of Disease ◽

Linear Differential ◽

Health Organization ◽

Immunodeficiency Syndrome

According to World Health Organization (WHO), the population suffering from human immunodeficiency virus (HIV) infection over a period of time may suffer from TB infection which increases the death rate. There is no cure for acquired immunodeficiency syndrome (AIDS) to date but antiretrovirals (ARVs) can slow down the progression of disease as well as prevent secondary infections or complications. This is considered as a medication in this paper. This scenario of HIV-TB co-infection is modeled using a system of non-linear differential equations. This model considers HIV-infected individual as the initial stage. Four equilibrium points are found. Reproduction number R0 is calculated. If R0 >1 disease persists uniformly, with reference to the reproduction number, backward bifurcation is computed for pre-AIDS (latent) stage. Global stability is established for the equilibrium points where there is no Pre-AIDS TB class, point without co-infection and for the endemic point. Numerical simulation is carried out to validate the data. Sensitivity analysis is carried out to determine the importance of model parameters in the disease dynamics.

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Estimation of R0 for COVID-19 in India through different mathematical model and their comparison

International Journal of Community Medicine and Public Health ◽

10.18203/2394-6040.ijcmph20210218 ◽

2021 ◽

Vol 8 (2) ◽

pp. 660

Author(s):

Nidhi Dwivedi ◽

Sujata Gupta ◽

Archana Dwivedi

Keyword(s):

Basic Reproduction Number ◽

Large Scale ◽

Reproduction Number ◽

Virus Disease ◽

Central China ◽

World Health ◽

Family Welfare ◽

Mathematical Methods ◽

Novel Coronavirus ◽

Health Organization

Background: The cases of novel coronavirus (COVID- 2019)-infected pneumonia started since the 19th of December, 2019, in Wuhan (Central China). A large scale outbreak of the disease resulted in a pandemic. This outbreak of the COVID -19 disease has spread on a wide scale. World health organization (WHO) has identified the ongoing outbreak of corona virus disease (COVID 2019) as pandemic on 11 March 2020. Basic reproduction number (R0)- is one of the most important predictors of epidemic severity. It can help to understand the path of the epidemic and to assess the effectiveness of the various interventions to control the epidemic. The purpose of this study is to estimate R0 by using five methods based on the Indian COVID-19 dataset and compare them. Methods: We obtained data on daily confirmed, recovered and deaths cases from official site of ministry of health and family welfare. We implemented 5 mathematical methods to calculate R0. We estimated the number of active cases till 14th of April. We also compare these methods to find out the best method to predict R0.Results: The estimated R0 for the AR, EG, ML, TD, and gamma-distributed methods were 1.0004, 2.102, 1.895, 1.872 and 1.46 respectively. The computed R0 in the TD method is closer to the actual R0 and have a good fit on data as confirmed with MSE criterion.Conclusions: Awareness of the basic reproduction number of COVID-19 is useful for controlling the spread of disease and for planning. It is therefore necessary to know the best method that has better performance.

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The epidemiologic parameters for COVID-19: A Systematic Review and Meta-Analysis

10.1101/2020.05.02.20088385 ◽

2020 ◽

Author(s):

Neda Izadi ◽

Niloufar Taherpour ◽

Yaser Mokhayeri ◽

Sahar Sotoodeh Ghorbani ◽

Khaled Rahmani ◽

...

Keyword(s):

Observational Studies ◽

Web Of Science ◽

Control Strategies ◽

Meta Analysis ◽

Case Fatality ◽

World Health ◽

Policy Makers ◽

Serial Interval ◽

Novel Coronavirus ◽

Health Organization

IntroductionThe World Health Organization (WHO) declared the outbreak to be a public health emergency and international concern and recognized it as a pandemic. The aim of this study was to estimate the epidemiologic parameters of novel coronavirus (COVID-19) pandemic for clinical and epidemiological help.MethodsFour electronic databases including Web of Science, Medline (PubMed), Scopus and Google Scholar were searched for literature published from early December 2019 up to 23 March 2020. The “metan” command was used to perform a fixed or random effects analysis. Cumulative meta-analysis was performed using the “metacum” command.ResultsTotally 76 observational studies were included in the analysis. The pooled estimate for R0 was 2.99 (95% CI: 2.71-3.27) for COVID-19. The overall R0 was 3.23, 1.19, 3.6 and 2.35 for China, Singapore, Iran and Japan, respectively. The overall Serial Interval, doubling time, incubation period were 4.45, 4.14 and 4.24 days for COVID-19. In addition, the overall estimation for growth rate and case fatality rate for COVID-19 were 0.38% and 3.29%, respectively.ConclusionCalculating the pooled estimate of the epidemiological parameters of COVID-19 as an emerging disease, could reveal epidemiological features of the disease that consequently pave the way for health policy makers to think more about control strategies.

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Estimation of the SARS-CoV-2 specific reproduction number in SAARC countries: A 60-days Data-driven analysis

Journal of Applied and Natural Science ◽

10.31018/jans.v12i4.2397 ◽

2020 ◽

Vol 12 (4) ◽

pp. 628-634

Author(s):

Mohammed Nizam Uddin ◽

A.N.M. Rezaul Karim ◽

Sofi Mahmud Parvez ◽

RiazMahmud ◽

H. M. Shahadat Ali ◽

...

Keyword(s):

Sri Lanka ◽

Reproduction Number ◽

Data Driven ◽

World Health ◽

Wuhan City ◽

Global Pandemic ◽

Reproduction Numbers ◽

Precautionary Measures ◽

Novel Coronavirus ◽

Health Organization

Novel coronavirus disease-2019 (COVID-19) was acknowledged as a global pandemic by WHO, which was first observed at the end of December 2019 in Wuhan city, China, caused by extreme acute respiratory syndrome coronavirus2 (SARS-CoV-2). According to the Weekly operation Update on COVID-19 (November 13, 2020) of the World Health Organization, more than 53 million confirmed cases are reported, including 1.3 million deaths. Various precautionary measures have been taken worldwide to reduce its transmission, and extensive researches are going on. The purpose of this analysis was to determine the initial number of reproductions (Ro) of the coronavirus of SAARC countries named Afghanistan, Bangladesh, India, Pakistan, Bhutan, Nepal, the Maldives, and Sri-Lanka for the first 60 days as the growth is exponential in the early 60 days. The reproduction numbers of coronavirus for Afghanistan, Bangladesh, India, Pakistan, Bhutan, the Maldives, Nepal, and Sri Lanka are 1.47, 3.86, 2.07, 1.43, 1.31, 3.22, 1.75, and 2.39 respectively. The basic reproduction number (R0) 3.86 for Bangladesh and 1.31 for Bhutan indicated that up to 60-days of the outbreak COVID-19, the epidemic was more severe in Bangladesh and less severe in Bhutan among all the SAARC countries. Our predictions can be helpful in planning alertness and taking the appropriate measures to monitor it.

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Analysis of Intervention Effectiveness Using Early Outbreak Transmission Dynamics to Guide Future Pandemic Management and Decision-Making in Kuwait

10.1101/2021.01.07.21249409 ◽

2021 ◽

Author(s):

Michael G. Tyshenko ◽

Tamer Oraby ◽

Joseph Craig Longenecker ◽

Harri Vainio ◽

Janvier Gasana ◽

...

Keyword(s):

Decision Making ◽

Reproduction Number ◽

Control Measures ◽

World Health ◽

Transmission Model ◽

Mobility Data ◽

Imported Cases ◽

Community Transmission ◽

Health Organization ◽

Case Data

Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) is a World Health Organization designated pandemic that can result in severe symptoms and death that disproportionately affects older patients or those with comorbidities. Kuwait reported its first imported cases of COVID-19 on February 24, 2020. Analysis of data from the first three months of community transmission of the COVID-19 outbreak in Kuwait can provide important guidance for decision-making when dealing with future SARS-CoV-2 epidemic wave management. The analysis of intervention scenarios can help to evaluate the possible impacts of various outbreak control measures going forward which aim to reduce the effective reproduction number during the initial outbreak wave. Herein we use a modified susceptible-exposed-asymptomatic-infectious-removed (SEAIR) transmission model to estimate the outbreak dynamics of SARS-CoV-2 transmission in Kuwait. We fit case data from the first 96 days in the model to estimate the basic reproduction number and used Google mobility data to refine community contact matrices. The SEAIR modelled scenarios allow for the analysis of various interventions to determine their effectiveness. The model can help inform future pandemic wave management, not only in Kuwait but for other countries as well.

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Current updates on COVID-19 - A review

International Journal of Novel Trends in Pharmaceutical Sciences ◽

10.26452/ijntps.v10i1.1141 ◽

2020 ◽

Vol 10 (1) ◽

pp. 1-8

Author(s):

Ghotekar D S ◽

Vishal N Kushare ◽

Sagar V Ghotekar

Keyword(s):

World Health Organization ◽

Common Cold ◽

Respiratory Diseases ◽

Gastrointestinal Diseases ◽

Hubei Province ◽

World Health ◽

The World ◽

The Common ◽

Novel Coronavirus ◽

Health Organization

Coronaviruses are a family of viruses that cause illness such as respiratory diseases or gastrointestinal diseases. Respiratory diseases can range from the common cold to more severe diseases. A novel coronavirus outbreak was first documented in Wuhan, Hubei Province, China in December 2019. The World Health Organization (WHO) has declared the coronavirus disease 2019 (COVID-19) a pandemic. A global coordinated effort is needed to stop the further spread of the virus. A novel coronavirus (nCoV) is a new strain that has not been identified in humans previously. Once scientists determine exactly what coronavirus it is, they give it a name (as in the case of COVID-19, the virus causing it is SARS-CoV-2).

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