Preliminary evaluation of voluntary event cancellation as a countermeasure against the COVID-19 outbreak in Japan as of 11 March, 2020

Reproduction Number ◽

Preliminary Evaluation ◽

Recovery Model ◽

Reporting Delay ◽

AbstractBackgroundTo control COVID-19 outbreak in Japan, sports and entertainment events were canceled in Japan for two weeks from 26 February to 11 March. It has been designated as voluntary event cancellation (VEC).ObjectThis study predicts the effectiveness of VEC enduring and after its implementation.MethodWe applied a simple susceptible–infected–recovery model to data of patients with symptoms in Japan during 14 January to VEC introduction and after VEC introduction to 8 March. We adjusted the reporting delay in the latest few days.ResultsResults suggest that the basic reproduction number, R0, before VEC introduced as 2.50 with a 95% confidence interval (CI) was [2.43, 2.55] and the effective reproduction number, Rv, after VEC introduced as 1. 88; its 95% CI was [1.68,2.02].Discussion and ConclusionResults demonstrated that VEC can reduce COVID-19 infectiousness by 35%, but R0 remains higher than one.

Estimation of the basic reproduction number, average incubation time, asymptomatic infection rate, and case fatality rate for COVID-19: Meta-analysis and sensitivity analysis

10.1101/2020.04.28.20083758 ◽

2020 ◽

Cited By ~ 3

Author(s):

Wenqing He ◽

Grace Y. Yi ◽

Yayuan Zhu

Keyword(s):

Confidence Interval ◽

Incubation Time ◽

Case Fatality Rate ◽

Reproduction Number ◽

Meta Analysis ◽

Case Fatality ◽

Asymptomatic Infection ◽

Fatality Rate ◽

AbstractThe coronavirus disease 2019 (COVID-19) has been found to be caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). However, comprehensive knowledge of COVID-19 remains incomplete and many important features are still unknown. This manuscripts conduct a meta-analysis and a sensitivity study to answer the questions: What is the basic reproduction number? How long is the incubation time of the disease on average? What portion of infections are asymptomatic? And ultimately, what is the case fatality rate? Our studies estimate the basic reproduction number to be 3.15 with the 95% interval (2.41, 3.90), the average incubation time to be 5.08 days with the 95% confidence interval (4.77, 5.39) (in day), the asymptomatic infection rate to be 46% with the 95% confidence interval (18.48%, 73.60%), and the case fatality rate to be 2.72% with 95% confidence interval (1.29%, 4.16%) where asymptomatic infections are accounted for.

A Dynamic Model of Human and Livestock Tuberculosis Spread and Control in Urumqi, Xinjiang, China

Computational and Mathematical Methods in Medicine ◽

10.1155/2016/3410320 ◽

2016 ◽

Vol 2016 ◽

pp. 1-10

Author(s):

Shan Liu ◽

Aiqiao Li ◽

Xiaomei Feng ◽

Xueliang Zhang ◽

Kai Wang

Keyword(s):

Sensitivity Analysis ◽

Confidence Interval ◽

Dynamic Model ◽

Reproduction Number ◽

Model Parameters ◽

Epidemiological Investigation ◽

Dynamical Behaviors ◽

And Control ◽

We establish a dynamical model for tuberculosis of humans and cows. For the model, we firstly give the basic reproduction numberR0. Furthermore, we discuss the dynamical behaviors of the model. By epidemiological investigation of tuberculosis among humans and livestock from 2007 to 2014 in Urumqi, Xinjiang, China, we estimate the parameters of the model and study the transmission trend of the disease in Urumqi, Xinjiang, China. The reproduction number in Urumqi for the model is estimated to be 0.1811 (95% confidence interval: 0.123–0.281). Finally, we perform some sensitivity analysis of several model parameters and give some useful comments on controlling the transmission of tuberculosis.

Superspreading quantified from bursty epidemic trajectories

Scientific Reports ◽

10.1038/s41598-021-03126-w ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Julius B. Kirkegaard ◽

Kim Sneppen

Keyword(s):

Confidence Interval ◽

Reproduction Number ◽

Community Level ◽

Individual Variations ◽

AbstractThe quantification of spreading heterogeneity in the COVID-19 epidemic is crucial as it affects the choice of efficient mitigating strategies irrespective of whether its origin is biological or social. We present a method to deduce temporal and individual variations in the basic reproduction number directly from epidemic trajectories at a community level. Using epidemic data from the 98 districts in Denmark we estimate an overdispersion factor k for COVID-19 to be about 0.11 (95% confidence interval 0.08–0.18), implying that 10 % of the infected cause between 70 % and 87 % of all infections.

Forecast of the COVID-19 outbreak, collapse of medical facilities, and lockdown effects in Tokyo, Japan

10.1101/2020.04.02.20051490 ◽

2020 ◽

Cited By ~ 3

Author(s):

Junko Kurita ◽

Tamie Sugawara ◽

Yasushi Ohkusa

Keyword(s):

Confidence Interval ◽

Reproduction Number ◽

Sir Model ◽

Age Classes ◽

Number Of Patients ◽

Medical Facilities ◽

China And Japan ◽

AbstractBackgroundThe number of patients of COVID-19 in Tokyo has been increasing gradually through the end of March, 2020.ObjectSupport for policymaking requires forecasting of the entire course and outcome of the outbreak including the date of collapse of medical facilities if a lockdown is not initiated. Moreover, the effects of a lockdown must be considered when choosing to initiate one.MethodData of Tokyo patients with symptoms during January 14 – March 28, 2020 were used to formulate a susceptible–infected–recovered (SIR) model using three age classes and to estimate the basic reproduction number (R0). Based on the estimated R0, We inferred outbreak outcomes including the date of collapse of medical facilities if a lockdown were not enacted. Then we estimate the lockdown effects.ResultsResults suggest R0 as 2.86, with a 95% confidence interval of [2.73, 2.97]. Collapse of medical facilities can be expected to occur on April 26 if no lockdown occurs. The total number of deaths can be expected to be half a million people. If a lockdown were enacted from April 6, and if more than 60% of trips outside the home were restricted voluntarily, then a collapse of medical facilities could be avoided.Discussion and ConclusionThe estimated R0 was similar to that found from other studies conducted in China and Japan. Results demonstrate that a lockdown with reasonable cooperation of residents can avoid a collapse of medical facilities and save 0.25 million mortality cases.

COVID-19 Outbreak Forecasting and Effects of Self-Restraint Against Excursions in Tokyo, Japan, as of the End of March, 2020, Before the Emergency Declaration on April 7, 2020

Journal of Disaster Research ◽

10.20965/jdr.2021.p0006 ◽

2021 ◽

Vol 16 (1) ◽

pp. 6-11

Author(s):

Yoshiyuki Sugishita ◽

Junko Kurita ◽

Tamie Sugawara ◽

Yasushi Ohkusa ◽

◽

...

Keyword(s):

Confidence Interval ◽

Medical Care ◽

Reproduction Number ◽

Sir Model ◽

Age Classes ◽

Medical Resources ◽

Care Services ◽

In Tokyo, Japan, coronavirus disease 2019 (COVID-19) cases have been increasing gradually since late March 2020. This study was aimed to predict the effects of self-restraint against excursions in Tokyo before the emergency declaration of April 7, 2020. Data of symptomatic patients collected between January 14 and March 28, 2020, in Tokyo, were used to formulate a susceptible–infected–recovered (SIR) model using three age classes and estimate the basic reproduction number (R0). Based on the estimated R0, we inferred outbreak outcomes and medical burdens if self-restraint against excursions had not been enacted. Thereafter, we estimated the effects of self-restraint against excursions. The results suggested an R0 value of 2.86, with a 95% confidence interval of 2.73–2.97. It is likely that the exhaustion of medical resources could have occurred on April 28, 2020, if no self-restraint against excursions had occurred. If self-restraint against excursions had been enacted from April 6, 2020, and more than 60% of trips outside the home had been restricted voluntarily, medical care services would then have been predicted to be maintained. Our suggestion might have contributed to countermeasures against COVID-19 in Tokyo.

Variability of Individual Infectiousness Derived from Aggregate Statistics of COVID-19

10.1101/2021.01.15.21249870 ◽

2021 ◽

Author(s):

Julius B. Kirkegaard ◽

Kim Sneppen

Keyword(s):

Confidence Interval ◽

Reproduction Number ◽

Community Level ◽

Individual Variations ◽

The quantification of spreading heterogeneity in the COVID-19 epidemic is crucial as it affects the choice of efficient mitigating strategies irrespective of whether its origin is biological or social. We present a method to deduce temporal and individual variations in the basic reproduction number R directly from epidemic trajectories at a community level. Using epidemic data from the 98 districts in Denmark we estimate an overdispersion factor k for COVID-19 to be about 0.11 (95% confidence interval 0.08 – 0.18), implying that 10 % of the infected cause between 70 % to 87 % of all infections.

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

J ◽

10.3390/j4020008 ◽

2021 ◽

Vol 4 (2) ◽

pp. 86-100

Author(s):

Nita H. Shah ◽

Ankush H. Suthar ◽

Ekta N. Jayswal ◽

Ankit Sikarwar

Keyword(s):

Reproduction Number ◽

Transmission Rate ◽

Sir Model ◽

Time Dependent ◽

Contact Rate ◽

Distribution Maps ◽

Fundamental Parameters ◽

Different Order ◽

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.

Impact of early detection and vaccination strategy in COVID-19 eradication program in Jakarta, Indonesia

BMC Research Notes ◽

10.1186/s13104-021-05540-9 ◽

2021 ◽

Vol 14 (1) ◽

Author(s):

Dipo Aldila ◽

Brenda M. Samiadji ◽

Gracia M. Simorangkir ◽

Sarbaz H. A. Khosnaw ◽

Muhammad Shahzad

Keyword(s):

Mathematical Model ◽

Reproduction Number ◽

Vaccination Strategy ◽

Vaccination Rate ◽

Rapid Testing ◽

Social Distancing ◽

Rapid Spread ◽

Vaccine Potential ◽

Abstract Objective Several essential factors have played a crucial role in the spreading mechanism of COVID-19 (Coronavirus disease 2019) in the human population. These factors include undetected cases, asymptomatic cases, and several non-pharmaceutical interventions. Because of the rapid spread of COVID-19 worldwide, understanding the significance of these factors is crucial in determining whether COVID-19 will be eradicated or persist in the population. Hence, in this study, we establish a new mathematical model to predict the spread of COVID-19 considering mentioned factors. Results Infection detection and vaccination have the potential to eradicate COVID-19 from Jakarta. From the sensitivity analysis, we find that rapid testing is crucial in reducing the basic reproduction number when COVID-19 is endemic in the population rather than contact trace. Furthermore, our results indicate that a vaccination strategy has the potential to relax social distancing rules, while maintaining the basic reproduction number at the minimum possible, and also eradicate COVID-19 from the population with a higher vaccination rate. In conclusion, our model proposed a mathematical model that can be used by Jakarta’s government to relax social distancing policy by relying on future COVID-19 vaccine potential.

Mathematical analysis of a measles transmission dynamics model in Bangladesh with double dose vaccination

Scientific Reports ◽

10.1038/s41598-021-95913-8 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Md Abdul Kuddus ◽

M. Mohiuddin ◽

Azizur Rahman

Keyword(s):

Reproduction Number ◽

Transmission Rate ◽

Equilibrium Points ◽

Rank Correlation ◽

Dynamical Analysis ◽

Model Parameters ◽

Progression Rate ◽

Double Dose ◽

AbstractAlthough the availability of the measles vaccine, it is still epidemic in many countries globally, including Bangladesh. Eradication of measles needs to keep the basic reproduction number less than one $$(\mathrm{i}.\mathrm{e}. \, \, {\mathrm{R}}_{0}<1)$$ ( i . e . R 0 < 1 ) . This paper investigates a modified (SVEIR) measles compartmental model with double dose vaccination in Bangladesh to simulate the measles prevalence. We perform a dynamical analysis of the resulting system and find that the model contains two equilibrium points: a disease-free equilibrium and an endemic equilibrium. The disease will be died out if the basic reproduction number is less than one $$(\mathrm{i}.\mathrm{e}. \, \, {\mathrm{ R}}_{0}<1)$$ ( i . e . R 0 < 1 ) , and if greater than one $$(\mathrm{i}.\mathrm{e}. \, \, {\mathrm{R}}_{0}>1)$$ ( i . e . R 0 > 1 ) epidemic occurs. While using the Routh-Hurwitz criteria, the equilibria are found to be locally asymptotically stable under the former condition on $${\mathrm{R}}_{0}$$ R 0 . The partial rank correlation coefficients (PRCCs), a global sensitivity analysis method is used to compute $${\mathrm{R}}_{0}$$ R 0 and measles prevalence $$\left({\mathrm{I}}^{*}\right)$$ I ∗ with respect to the estimated and fitted model parameters. We found that the transmission rate $$(\upbeta )$$ ( β ) had the most significant influence on measles prevalence. Numerical simulations were carried out to commissions our analytical outcomes. These findings show that how progression rate, transmission rate and double dose vaccination rate affect the dynamics of measles prevalence. The information that we generate from this study may help government and public health professionals in making strategies to deal with the omissions of a measles outbreak and thus control and prevent an epidemic in Bangladesh.

Persistence in seasonally varying predator–prey systems via the basic reproduction number

Nonlinear Analysis Real World Applications ◽

10.1016/j.nonrwa.2015.11.007 ◽

2016 ◽

Vol 30 ◽

pp. 73-98 ◽

Cited By ~ 12

Author(s):

Maurizio Garrione ◽

Carlota Rebelo

Keyword(s):

Reproduction Number ◽

Predator Prey ◽