scholarly journals Phylogenomics and phylodynamics of SARS-CoV-2 genomes retrieved from India

2020 ◽  
Vol 15 (11) ◽  
pp. 747-753
Author(s):  
Sameera Farah ◽  
Ashwin Atkulwar ◽  
Manas Ranjan Praharaj ◽  
Raja Khan ◽  
Ravikumar Gandham ◽  
...  
Keyword(s):  
Population Dynamics ◽  
Severe Acute Respiratory Syndrome ◽  
Basic Reproduction Number ◽  
Reproduction Number ◽  
Phylogenetic Network ◽  
Effective Population ◽  
Current State ◽  
Whole Genomes ◽  
Indian Isolates ◽  
Community Transmission

Background: This is the first phylodynamic study attempted on SARS-CoV-2 genomes from India to infer the current state of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) evolution using phylogenetic network and growth trends. Materials & Methods: Out of 286 retrieved whole genomes from India, 138 haplotypes were used to build a phylogenetic network. The birth–death serial model (BDSIR) package of BEAST2 was used to calculate the reproduction number of SARS-CoV-2. Population dynamics were investigated using the stamp date method as implemented in BEAST2 and BEAST 1.10.4. Results: A median-joining network revealed two ancestral clusters. A high basic reproduction number of SARS-CoV-2 was found. An exponential rise in the effective population size of Indian isolates was detected. Conclusion: The phylogenetic network reveals dual ancestry and possibility of community transmission of SARS-CoV-2 in India.

scholarly journals Phylogenomics and phylodynamics of SARS-CoV-2 retrieved genomes from India

2020 ◽  
Author(s):  
Sameera Farah ◽  
Ashwin Atkulwar ◽  
Manas Ranjan Praharaj ◽  
Raja Khan ◽  
Ravikumar Gandham ◽  
...  
Keyword(s):  
Genome Sequencing ◽  
Vaccine Development ◽  
Reproduction Number ◽  
Bayesian Skyline Plot ◽  
Development Programs ◽  
Effective Population ◽  
Whole Genomes ◽  
Indian Isolates ◽  
Spanish Flu ◽  
Community Transmission

AbstractThe ongoing SARS-CoV-2 pandemic is one of the biggest outbreaks after the Spanish flu of 1918. Understanding the epidemiology of viral outbreaks is the first step towards vaccine development programs. This is the first phylodynamics study attempted on of SARS-CoV-2 genomes from India to infer its current evolution in the context of an ongoing pandemic. Out of 286 retrieved SARS-CoV-2 whole genomes from India, 138 haplotypes were generated and analyzed. Median-joining network was built to investigate the relatedness of SARS-CoV-2 haplotypes in India. The BDSIR package of BEAST2 was used to calculate the reproduction number (R0) and the infectious rate of the virus. Past and current population trend was investigated using the stamp date method in coalescent Bayesian skyline plot, implemented in BEAST2 and by exponential growth prior in BEAST 1.10.4. Median-joining network reveals two distinct ancestral clusters A and B showing genetic affinities with Wuhan outbreak sample. The network also illustrates the autochthonous development of isolates in a few instances. High basic reproduction number of SARS-nCoV-2 in India points towards the phase of active community transmission. The Bayesian skyline plot revel exponential rise in the effective population size (Ne) of Indian isolates from the first week of January to the first week of April 2020. More genome sequencing and analyses of the virus will be required in coming days to monitor COVID19 after the upliftment of lock down in India.

scholarly journals A Conceptual Discussion About the Basic Reproduction Number of Severe Acute Respiratory Syndrome Coronavirus 2 in Healthcare Settings

2020 ◽  
Author(s):  
Laura Temime ◽  
Marie-Paule Gustin ◽  
Audrey Duval ◽  
Niccolò Buetti ◽  
Pascal Crépey ◽  
...  
Keyword(s):  
Severe Acute Respiratory Syndrome ◽  
Basic Reproduction Number ◽  
Reproduction Number ◽  
Healthcare Settings ◽  
Contact Data ◽  
Conceptual Discussion ◽  
The Basic Reproduction Number

Abstract To date, no specific estimate of R0 for SARS-CoV-2 is available for healthcare settings. Using interindividual contact data, we highlight that R0 estimates from the community cannot translate directly to healthcare settings, with pre-pandemic R0 values ranging 1.3–7.7 in 3 illustrative healthcare institutions. This has implications for nosocomial COVID-19 control.

scholarly journals The basic reproduction number of COVID-19 across Africa

2021 ◽  
Author(s):  
Sarafa Adewale Iyaniwura ◽  
Muhammad Rabiu Musa ◽  
Jummy F. David ◽  
Jude Dzevela Kong
Keyword(s):  
Bayesian Inference ◽  
Severe Acute Respiratory Syndrome ◽  
Basic Reproduction Number ◽  
Reproduction Number ◽  
Transmission Dynamics ◽  
Clear Understanding ◽  
Seir Model ◽  
The World ◽  
Bayesian Inference Framework ◽  
The Basic Reproduction Number

The pandemic of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) took the world by surprise. Following the first outbreak of COVID-19 in December 2019, several models have been developed to study and understand its transmission dynamics. Although the spread of COVID-19 is being slowed down by vaccination and other interventions, there is still a need to have a clear understanding of the evolution of the pandemic across countries, states and communities. To this end, there is a need to have a clearer picture of the initial spread of the disease in different regions. In this project, we used a simple SEIR model and a Bayesian inference framework to estimate the basic reproduction number of COVID-19 across Africa. Our estimates vary between 1.98 (Sudan) and 9.66 (Mauritius), with a median of 3.67 (90% CrI: 3.31 - 4.12). The estimates provided in this paper will help to inform COVID-19 modeling in the respective countries/regions.

scholarly journals Serial interval and basic reproduction number of SARS-CoV-2 Omicron variant in South Korea

2021 ◽  
Author(s):  
Dasom Kim ◽  
Jisoo Jo ◽  
Jun-Sik Lim ◽  
Sukhyun Ryu
Keyword(s):  
South Korea ◽  
Basic Reproduction Number ◽  
Reproduction Number ◽  
Credible Interval ◽  
Serial Interval ◽  
Community Transmission ◽  
The Mean ◽  
The Basic Reproduction Number

South Korea is experiencing the community transmission of the SARS-CoV-2 Omicron variant (B.1.1.529). We estimated that the mean of the serial interval was 2.22 days, and the basic reproduction number was 1.90 (95% Credible Interval, 1.50-2.43) for the Omicron variant outbreak in South Korea.

scholarly journals Unraveling the Myths of R0 in Controlling the Dynamics of COVID-19 Outbreak: a Modelling Perspective

2020 ◽  
Author(s):  
Mohd Hafiz Mohd ◽  
Fatima Sulayman
Keyword(s):  
Dynamical Systems ◽  
Severe Acute Respiratory Syndrome ◽  
Basic Reproduction Number ◽  
Reproduction Number ◽  
Transmission Dynamics ◽  
False Detection ◽  
Medical Resources ◽  
The World ◽  
Exogenous Factors ◽  
Substantial Morbidity

ABSTRACTCOVID-19 is an emerging and rapidly evolving pandemic around the world, which causes severe acute respiratory syndrome and results in substantial morbidity and mortality. To examine the transmission dynamics of COVID-19 and its interactions with some exogenous factors such as limited medical resources and false detection problems, we employ a simple epidemiological model and analyse this system using modelling and dynamical systems techniques. We discover some contrasting findings with respect to the observations of basic reproduction number, and we investigate how the issues of limited medical resources and false detection problems affect the COVID-19 pandemic outbreak.

scholarly journals How Many Can You Infect? Simple (and Naive) Methods of Estimating the Reproduction Number

2020 ◽  
Vol 3 (1) ◽  
pp. 28-36
Author(s):  
H. Susanto ◽  
V.R. Tjahjono ◽  
A. Hasan ◽  
M.F. Kasim ◽  
N. Nuraini ◽  
...  
Keyword(s):  
Basic Reproduction Number ◽  
Exponential Growth ◽  
Reproduction Number ◽  
Sir Model ◽  
Epidemic Outbreak ◽  
Numerical Approximations ◽  
Expected Number ◽  
Slowing Down ◽  
Policy Responses ◽  
Current State

This is a pedagogical paper on estimating the number of people that can be infected by one infectious person during an epidemic outbreak, known as the reproduction number. Knowing the number is crucial for developing policy responses. There are generally two types of such a number, i.e., basic and effective (or instantaneous). While basic reproduction number is the average expected number of cases directly generated by one case in a population where all individuals are susceptible, effective reproduction number is the number of cases generated in the current state of a population. In this paper, we exploit the deterministic susceptibleinfected-removed (SIR) model to estimate them through three different numerical approximations. We apply the methods to the pandemic COVID-19 in Italy to provide insights into the spread of the disease in the country. We see that the effect of the national lockdown in slowing down the disease exponential growth appearedabout two weeks after the implementation date. We also discuss available improvements to the simple (and naive) methods that have been made by researchers in the field. Authors of this paper are members of the SimcovID (Simulasi dan Pemodelan COVID-19 Indonesia) collaboration.

scholarly journals Modeling the impact of host resistance on structured tick population dynamics

2020 ◽  
Vol 1 (1) ◽  
pp. 65-84
Author(s):  
Mahnaz Alavinejad ◽  
Jemisa Sadiku ◽  
Jianhong Wu
Keyword(s):  
Population Dynamics ◽  
Basic Reproduction Number ◽  
Reproduction Number ◽  
Immunological Response ◽  
Positive Equilibrium ◽  
Tick Population ◽  
Delay Differential ◽  
The Impact ◽  
Grooming Behaviour ◽  
The Basic Reproduction Number

For a variety of tick species, the resistance, behavioural and immunological response of hosts has been reported in the biological literature but its impact on tick population dynamics has not been mathematically formulated and analyzed using dynamical models reflecting the full biological stages of ticks. Here we develop and simulate a delay differential equation model, with a particular focus on resistance resulting in grooming behaviour. We calculate the basic reproduction number using the spectral analysis of delay differential equations with positive feedback, and establish the existence and uniqueness of a positive equilibrium when the basic reproduction number exceeds unit. We also conduct numerical and sensitivity analysis about the dependence of this positive equilibrium on the the parameter relevant to grooming behaviour. We numerically obtain the relationship between grooming behaviour and equilibrium value at different stages.

scholarly journals Are the SIR and SEIR models suitable to estimate the basic reproduction number for the CoViD-19 epidemic?

2020 ◽  
Author(s):  
Hyun Mo Yang ◽  
Luis Pedro Lombardi Junior ◽  
Ariana Campos Yang
Keyword(s):  
Severe Acute Respiratory Syndrome ◽  
Basic Reproduction Number ◽  
Reproduction Number ◽  
Fatality Rate ◽  
Deterministic Models ◽  
Paulo State ◽  
Transmission Chain ◽  
The World ◽  
History Of ◽  
The Basic Reproduction Number

AbstractThe transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) becomes pandemic but presents different incidences in the world. Mathematical models were formulated to describe the coronavirus disease 2019 (CoViD-19) epidemic in each country or region. At the beginning of the pandemic, many authors used the SIR (susceptible, infectious, and recovered compartments) and SEIR (including exposed compartment) models to estimate the basic reproduction number R0 for the CoViD-19 epidemic. These simple deterministic models assumed that the only available collection of the severe CoViD-19 cases transmitted the SARS-CoV-2 and estimated lower values for R0, ranging from 1.5 to 3.0. However, the major flaw in the estimation of R0 provided by the SIR and SEIR models was that the severe CoViD-19 patients were hospitalized, and, consequently, not transmitting. Hence, we proposed a more elaborate model considering the natural history of CoViD-19: the inclusion of asymptomatic, pre-symptomatic, mild and severe CoViD-19 compartments. The model also encompassed the fatality rate depending on age. This SEAPMDR model estimated R0 using the severe CoViD-19 data from São Paulo State (Brazil) and Spain, yielding higher values for R0, that is, 6.54 and 5.88, respectively. It is worth stressing that this model assumed that severe CoViD-19 cases were not participating in the SARS-CoV-2 transmission chain. Therefore, the SIR and SEIR models are not suitable to estimate R0 at the beginning of the epidemic by considering the isolated severe CoViD-19 data as transmitters.

scholarly journals District-wise estimation of Basic reproduction number (R0) for COVID-19 in India in the initial phase

2021 ◽  
Author(s):  
Pratip Shil ◽  
Nitin M. Atre ◽  
Avinash A. Patil ◽  
Babasaheb V. Tandale ◽  
Priya Abraham
Keyword(s):  
Basic Reproduction Number ◽  
Initial Phase ◽  
Reproduction Number

scholarly journals Fractional SIR-Model for Estimating Transmission Dynamics of COVID-19 in India

J ◽  
2021 ◽  
Vol 4 (2) ◽  
pp. 86-100
Author(s):  
Nita H. Shah ◽  
Ankush H. Suthar ◽  
Ekta N. Jayswal ◽  
Ankit Sikarwar
Keyword(s):  
Basic Reproduction Number ◽  
Reproduction Number ◽  
Transmission Rate ◽  
Sir Model ◽  
Time Dependent ◽  
Contact Rate ◽  
Distribution Maps ◽  
Fundamental Parameters ◽  
Different Order ◽  
The Basic Reproduction Number

In this article, a time-dependent susceptible-infected-recovered (SIR) model is constructed to investigate the transmission rate of COVID-19 in various regions of India. The model included the fundamental parameters on which the transmission rate of the infection is dependent, like the population density, contact rate, recovery rate, and intensity of the infection in the respective region. Looking at the great diversity in different geographic locations in India, we determined to calculate the basic reproduction number for all Indian districts based on the COVID-19 data till 7 July 2020. By preparing district-wise spatial distribution maps with the help of ArcGIS 10.2, the model was employed to show the effect of complete lockdown on the transmission rate of the COVID-19 infection in Indian districts. Moreover, with the model's transformation to the fractional ordered dynamical system, we found that the nature of the proposed SIR model is different for the different order of the systems. The sensitivity analysis of the basic reproduction number is done graphically which forecasts the change in the transmission rate of COVID-19 infection with change in different parameters. In the numerical simulation section, oscillations and variations in the model compartments are shown for two different situations, with and without lockdown.

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