scholarly journals Modeling and analysis of COVID-19 infected persons during repeated waves in Japan

2021 ◽  
Author(s):  
Koichi Hashiguchi
Keyword(s):  
Curve Fitting ◽  
Sir Model ◽  
Cumulative Number ◽  
Initial Number ◽  
Modeling And Analysis ◽  
Social Distancing ◽  
Repeated Infection ◽  
The Social ◽  
Positive Rate ◽  
Order Of Magnitude

A model for estimating the number of COVID-19 infected persons (infecteds) is proposed based on the exponential function law of the SIR model. This model is composed of several equations expressing the number of infecteds, considering the onset after an incubation period, infectivity, wavy infection persistence with repeated infection spread and convergence with insufficient quarantine. This model is applied to the infection in Japan, which is currently suffering from the 5th wave, and the initial number of infecteds and various related parameters are calculated by curve fitting of the cumulative number of infecteds to the total cases in the database. As a minimum boundary of the number of infecteds for the infection continuation up to the 5th wave, the initial number of infecteds at the outbreak of infection is more than an order of magnitude higher than the actual initial cases. A convergence ratio (cumulative number of infecteds / total cases) at the end of the first wave is obtained as 1.5. The quarantine rate and social distancing ratio based on the SIQR model are evaluated, and the social distancing ratio increases sharply just after the government's declaration of emergency. The quarantine rate closely equals the positive rate by PCR tests, meaning that the number of infecteds, which had been unknown, is on the order of almost the same as the number of tests.

scholarly journals Modelling the Potential Impact of Social Distancing on the COVID-19 Epidemic in South Africa

2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
F. Nyabadza ◽  
F. Chirove ◽  
C. W. Chukwu ◽  
M. V. Visaya
Keyword(s):  
South Africa ◽  
Deterministic Model ◽  
Cumulative Number ◽  
The Novel ◽  
Social Distancing ◽  
The Social ◽  
Potential Impact ◽  
Policy Direction ◽  
Novel Coronavirus ◽  
The Impact

The novel coronavirus (COVID-19) pandemic continues to be a global health problem whose impact has been significantly felt in South Africa. With the global spread increasing and infecting millions, containment efforts by countries have largely focused on lockdowns and social distancing to minimise contact between persons. Social distancing has been touted as the best form of response in managing a rapid increase in the number of infected cases. In this paper, we present a deterministic model to describe the impact of social distancing on the transmission dynamics of COVID-19 in South Africa. The model is fitted to data from March 5 to April 13, 2020, on the cumulative number of infected cases, and a scenario analysis on different levels of social distancing is presented. The model shows that with the levels of social distancing under the initial lockdown level between March 26 and April 13, 2020, there would be a projected continued rise in the number of infected cases. The model also looks at the impact of relaxing the social distancing measures after the initial announcement of the lockdown. It is shown that relaxation of social distancing by 2% can result in a 23% rise in the number of cumulative cases whilst an increase in the level of social distancing by 2% would reduce the number of cumulative cases by about 18%. The model results accurately predicted the number of cases after the initial lockdown level was relaxed towards the end of April 2020. These results have implications on the management and policy direction in the early phase of the epidemic.

scholarly journals Epidemiological Modeling of COVID-19 in Saudi Arabia: Spread Projection, Awareness, and Impact of Treatment

2020 ◽  
Vol 10 (17) ◽  
pp. 5895 ◽  
Author(s):  
Yousef Alharbi ◽  
Abdulrahman Alqahtani ◽  
Olayan Albalawi ◽  
Mohsen Bakouri
Keyword(s):  
Saudi Arabia ◽  
Information Criterion ◽  
Sir Model ◽  
Cumulative Number ◽  
Epidemiological Modeling ◽  
Social Distancing ◽  
Epidemic Size ◽  
Statistical Indices ◽  
First Case ◽  
The Impact

The first case of COVID-19 originated in Wuhan, China, after which it spread across more than 200 countries. By 21 July 2020, the rapid global spread of this disease had led to more than 15 million cases of infection, with a mortality rate of more than 4.0% of the total number of confirmed cases. This study aimed to predict the prevalence of COVID-19 and to investigate the effect of awareness and the impact of treatment in Saudi Arabia. In this paper, COVID-19 data were sourced from the Saudi Ministry of Health, covering the period from 31 March 2020 to 21 July 2020. The spread of COVID-19 was predicted using four different epidemiological models, namely the susceptible–infectious–recovered (SIR), generalized logistic, Richards, and Gompertz models. The assessment of models’ fit was performed and compared using four statistical indices (root-mean-square error (RMSE), R squared (R2), adjusted R2 ( Radj2), and Akaike’s information criterion (AIC)) in order to select the most appropriate model. Modified versions of the SIR model were utilized to assess the influence of awareness and treatment on the prevalence of COVID-19. Based on the statistical indices, the SIR model showed a good fit to reported data compared with the other models (RMSE = 2790.69, R2 = 99.88%, Radj2 = 99.98%, and AIC = 1796.05). The SIR model predicted that the cumulative number of infected cases would reach 359,794 and that the pandemic would end by early September 2020. Additionally, the modified version of the SIR model with social distancing revealed that there would be a reduction in the final cumulative epidemic size by 9.1% and 168.2% if social distancing were applied over the short and long term, respectively. Furthermore, different treatment scenarios were simulated, starting on 8 July 2020, using another modified version of the SIR model. Epidemiological modeling can help to predict the cumulative number of cases of infection and to understand the impact of social distancing and pharmaceutical intervention on the prevalence of COVID-19. The findings from this study can provide valuable information for governmental policymakers trying to control the spread of this pandemic.

scholarly journals Forecasting the Spread of COVID-19 under Different Reopening Strategies

2020 ◽  
Author(s):  
Meng Liu ◽  
Raphael Thomadsen ◽  
Song Yao
Keyword(s):  
United States ◽  
Growth Rate ◽  
Population Density ◽  
The United States ◽  
Sir Model ◽  
Social Distancing ◽  
Mobility Data ◽  
The Social ◽  
The Us ◽  
Case Data

ABSTRACTWe combine COVID-19 case data with demographic and mobility data to estimate a modified susceptible-infected-recovered (SIR) model for the spread of this disease in the United States. We find that the incidence of infectious COVID-19 individuals has a concave effect on contagion, as would be expected if people have inter-related social networks. We also demonstrate that social distancing and population density have large effects on the rate of contagion. The social distancing in late March and April substantially reduced the number of COVID-19 cases. However, the concave contagion pattern means that when social distancing measures are lifted, the growth rate is considerable but will not be exponential as predicted by standard SIR models. Furthermore, counties with the lowest population density could likely avoid high levels of contagion even with no social distancing. We forecast rates of new cases for COVID-19 under different social distancing norms and find that if social distancing is eliminated there will be a massive increase in the cases of COVID-19, about double what would occur if the US only restored to 50% of the way to normalcy.

scholarly journals Covid-19 in Latin America countries: Course of the pandemic and the different responses towards control

2020 ◽  
Author(s):  
Julia Moreira Pescarini ◽  
Ismael H Silveira ◽  
Jaime A Souza-Filho ◽  
Rosana Aquino ◽  
Mauricio L Barreto ◽  
...  
Keyword(s):  
Latin America ◽  
Social Mobility ◽  
Latin American ◽  
Mortality Rates ◽  
Healthcare Systems ◽  
Cumulative Number ◽  
Social Distancing ◽  
First Case ◽  
Incidence And Mortality ◽  
The Social

Abstract Background: The emergence of COVID-19 in Latin America occurred within a troubled political, economic and social context, with growing trends of poverty and social inequality challenging already overburdened and underfinanced local healthcare systems. In the absence of a vaccine or of any treatment for COVID-19, public health measures such as social distancing had to be adopted. The objective of this paper is to describe the course of the COVID-19 pandemic in Latin American countries and to summarize the social distancing measures implemented in each one of these countries, discussing the changes that took place in the social mobility of the populations and their potential effects on the course of the epidemic up to June 2020. Results: Brazil has the highest cumulative number of cases and deaths; however, cumulative incidence rates are higher in Peru and Chile, while the highest cumulative mortality rates are in Ecuador, Peru and Brazil. Some countries implemented social distancing measures before the first case was registered, culminating in lockdown in eight countries before detection of the 100th case. The measures that appear to have had the greatest impact in reducing mobility include, in addition to lockdown, the closure of schools and prohibition of events. In general, the countries that implemented social distancing measures earlier and where the reduction in social mobility was greatest also recorded lower incidence and mortality rates. Brazil and Mexico failed to adopt lockdown and the number of cases of the disease continues to grow. Conclusions: As occurred in other continents, control of the COVID-19 pandemic was better in countries that were faster in adopting more restrictive measures. Nevertheless, this equation does not appear to guarantee a positive outcome in all settings, possibly due to the considerable social inequalities and chronic deficiencies of the healthcare systems, with the scenario being even more complex in view of the recurring political crises and the negationist view of some national leaders. The COVID-19 pandemic continues to spread in Latin America and exposes these contradictions. Further studies are required to gain a greater understanding and generate lessons on how to manage such a complex crisis.

scholarly journals Modelling the potential impact of social distancing on the COVID-19 epidemic in South Africa

2020 ◽  
Author(s):  
F. Nyabadza ◽  
F. Chirove ◽  
W. Chukwu ◽  
M.V. Visaya
Keyword(s):  
South Africa ◽  
Deterministic Model ◽  
Cumulative Number ◽  
The Novel ◽  
Social Distancing ◽  
The Social ◽  
Potential Impact ◽  
Policy Direction ◽  
Novel Coronavirus ◽  
The Impact

AbstractThe novel coronavirus (COVID-19) pandemic continues to be a global health problem whose impact has been significantly felt in South Africa. Social distancing has been touted as the best form of response in managing a rapid increase in the number of infected cases. In this paper, we present a deterministic model to model the impact of social distancing on the transmission dynamics of COVID-19 in South Africa. The model is fitted to the currently available data on the cumulative number of infected cases and a scenario analysis on different levels of social distancing are presented. The results show a continued rise in the number of cases in the lock down period with the current levels of social distancing albeit at a lower rate. The model shows that the number of cases will rise to above 4000 cases by the end of the lockdown. The model also looks at the impact of relaxing the social distancing measures after the initial announcement of the lock down measures. A relaxation of the social distancing by 2% can result in a 23% rise in the number of cumulative cases while on the other hand increasing the levels of social distancing by 2% would reduce the number of cumulative cases by about 18%. These results have implications on the management and policy direction in the early phases of the epidemic.

scholarly journals Tourist Route Optimization in the Context of Covid-19 Pandemic

2021 ◽  
Vol 13 (10) ◽  
pp. 5492
Author(s):  
Cristina Maria Păcurar ◽  
Ruxandra-Gabriela Albu ◽  
Victor Dan Păcurar
Keyword(s):  
Travelling Salesman Problem ◽  
Route Planning ◽  
Route Optimization ◽  
Travelling Salesman ◽  
Social Distancing ◽  
Tourist Destinations ◽  
Innovative Method ◽  
The Social ◽  
Immediate Response

The paper presents an innovative method for tourist route planning inside a destination. The necessity of reorganizing the tourist routes within a destination comes as an immediate response to the Covid-19 crisis. The implementation of the method inside tourist destinations can bring an important advantage in transforming a destination into a safer one in times of Covid-19 and post-Covid-19. The existing trend of shortening the tourist stay length has been accelerated while the epidemic became a pandemic. Moreover, the wariness for future pandemics has brought into spotlight the issue of overcrowded attractions inside a destination at certain moments. The method presented in this paper proposes a backtracking algorithm, more precisely an adaptation of the travelling salesman problem. The method presented is aimed to facilitate the navigation inside a destination and to revive certain less-visited sightseeing spots inside a destination while facilitating conformation with the social distancing measures imposed for Covid-19 control.

scholarly journals An adaptive social distancing SIR model for COVID-19 disease spreading and forecasting

2021 ◽  
Vol 10 (s1) ◽  
Author(s):  
Said Gounane ◽  
Yassir Barkouch ◽  
Abdelghafour Atlas ◽  
Mostafa Bendahmane ◽  
Fahd Karami ◽  
...  
Keyword(s):  
Mathematical Theory ◽  
Real Data ◽  
Sir Model ◽  
Epidemic Threshold ◽  
Social Distancing ◽  
Sir Epidemic ◽  
Proposed Model ◽  
Disease Spreading ◽  
The Government ◽  
The Impact

Abstract Recently, various mathematical models have been proposed to model COVID-19 outbreak. These models are an effective tool to study the mechanisms of coronavirus spreading and to predict the future course of COVID-19 disease. They are also used to evaluate strategies to control this pandemic. Generally, SIR compartmental models are appropriate for understanding and predicting the dynamics of infectious diseases like COVID-19. The classical SIR model is initially introduced by Kermack and McKendrick (cf. (Anderson, R. M. 1991. “Discussion: the Kermack–McKendrick Epidemic Threshold Theorem.” Bulletin of Mathematical Biology 53 (1): 3–32; Kermack, W. O., and A. G. McKendrick. 1927. “A Contribution to the Mathematical Theory of Epidemics.” Proceedings of the Royal Society 115 (772): 700–21)) to describe the evolution of the susceptible, infected and recovered compartment. Focused on the impact of public policies designed to contain this pandemic, we develop a new nonlinear SIR epidemic problem modeling the spreading of coronavirus under the effect of a social distancing induced by the government measures to stop coronavirus spreading. To find the parameters adopted for each country (for e.g. Germany, Spain, Italy, France, Algeria and Morocco) we fit the proposed model with respect to the actual real data. We also evaluate the government measures in each country with respect to the evolution of the pandemic. Our numerical simulations can be used to provide an effective tool for predicting the spread of the disease.

scholarly journals Decline in Marriage Associated with the COVID-19 Pandemic in the United States

2020 ◽  
Vol 6 ◽  
pp. 237802312098032
Author(s):  
Brandon G. Wagner ◽  
Kate H. Choi ◽  
Philip N. Cohen
Keyword(s):  
United States ◽  
The United States ◽  
Cumulative Number ◽  
Short Term ◽  
Know How ◽  
The Social ◽  
Reporting Delays ◽  
Social Upheaval ◽  
Near Future ◽  
Do So

In the social upheaval arising from the coronavirus disease 2019 (COVID-19) pandemic, we do not yet know how union formation, particularly marriage, has been affected. Using administration records—marriage certificates and applications—gathered from settings representing a variety of COVID-19 experiences in the United States, the authors compare counts of recorded marriages in 2020 against those from the same period in 2019. There is a dramatic decrease in year-to-date cumulative marriages in 2020 compared with 2019 in each case. Similar patterns are observed for the Seattle metropolitan area when analyzing the cumulative number of marriage applications, a leading indicator of marriages in the near future. Year-to-date declines in marriage are unlikely to be due solely to closure of government agencies that administer marriage certification or reporting delays. Together, these findings suggest that marriage has declined during the COVID-19 outbreak and may continue to do so, at least in the short term.

scholarly journals Perception and Preference for Home-Based Telework in the COVID-19 Era: A Gender-Based Analysis in Hanoi, Vietnam

2021 ◽  
Vol 13 (6) ◽  
pp. 3179
Author(s):  
Minh Hieu Nguyen ◽  
Jimmy Armoogum
Keyword(s):  
Gender Inequality ◽  
Sustainable Development Goal ◽  
Related Factors ◽  
Social Distancing ◽  
Work Related ◽  
Home Based ◽  
The Social ◽  
The Government ◽  
Gender Based ◽  
Using Data

The rapid and widespread of COVID-19 has caused severe multifaceted effects on society but differently in women and men, thereby preventing the achievement of gender equality (the 5th sustainable development goal of the United Nations). This study, using data of 355 teleworkers collected in Hanoi (Vietnam) during the first social distancing period, aims at exploring how (dis)similar factors associated with the perception and the preference for more home-based telework (HBT) for male teleworkers versus female peers are. The findings show that 56% of female teleworkers compared to 45% of male counterparts had a positive perception of HBT within the social distancing period and 63% of women desired to telework more in comparison with 39% of men post-COVID-19. Work-related factors were associated with the male perception while family-related factors influenced the female perception. There is a difference in the effects of the same variables (age and children in the household) on the perception and the preference for HBT for females. For women, HBT would be considered a solution post-COVID-19 to solve the burden existing pre-COVID-19 and increasing in COVID-19. Considering gender inequality is necessary for the government and authorities to lessen the adverse effects of COVID-19 on the lives of citizens, especially female ones, in developing countries.

Social Distancing Using AI and Deep Learning

2021 ◽  
Vol 9 (VII) ◽  
pp. 1816-1822
Author(s):  
Mr. Kiran Mudaraddi
Keyword(s):  
Deep Learning ◽  
Object Detection ◽  
Open Source ◽  
Suggested Method ◽  
Video Frame ◽  
Social Distancing ◽  
The Social ◽  
The Impact

The paper presents a deep learning-based methodology for detecting social distancing in order to assess the distance between people in order to mitigate the impact of the coronavirus pandemic. The input was a video frame from the camera, and the open-source object detection was pre-trained. The outcome demonstrates that the suggested method is capable of determining the social distancing measures between many participants in a video.

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