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 Progression of COVID-19 in Indian States - Forecasting Endpoints Using SIR and Logistic Growth Models

2020 ◽  
Author(s):  
Bhoomika Malhotra ◽  
Vishesh Kashyap
Keyword(s):  
Growth Model ◽  
Sir Model ◽  
Logistic Growth ◽  
Indian States ◽  
Health Crisis ◽  
Social Distancing ◽  
First Case ◽  
Logistic Growth Model ◽  
The Government ◽  
The Impact

COVID-19 has led to the most widespread public health crisis in recent history. The first case of the disease was detected in India on 31 January 2019, and confirmed cases stand at 74,281 as of 13 May 2020. Mathematical modeling can be utilized to forecast the final numbers as well as the endpoint of the disease in India and its states, as well as assess the impact of social distancing measures. In the present work, the Susceptible-Infected-Recovered (SIR) model and the Logistic Growth model have been implemented to predict the endpoint of COVID-19 in India as well as three states accounting for over 55% of the total cases - Maharashtra, Gujarat and Delhi. The results using the SIR model indicate that the disease will reach an endpoint in India on 12 September, while Maharashtra, Gujarat and Delhi will reach endpoints on 20 August, 30 July and 9 September respectively. Using the Logistic Regression model, the endpoint for India is predicted on 23 July, while that for Maharashtra, Gujarat and Delhi is 5 July, 23 June and 10 August respectively. It is also observed that the case numbers predicted by the SIR model are greater than those for the Logistic Growth model in each case. The results suggest that the lockdown enacted by the Government of India has had only a moderate impact on the spread of COVID-19, and emphasize the need for firm implementation of social distancing guidelines.

scholarly journals The impact of quarantine on Covid-19 infections

2021 ◽  
Vol 10 (s1) ◽  
Author(s):  
Pablo Marshall
Keyword(s):  
Health System ◽  
Infection Rate ◽  
District Level ◽  
Infection Model ◽  
Social Distancing ◽  
Proposed Model ◽  
Lower Infection ◽  
The Impact ◽  
Lower Infection Rate ◽  
Over Time

Abstract Objectives: Coronavirushas had profound effects on people’s lives and the economy of many countries, generating controversy between the need to establish quarantines and other social distancing measures to protect people’s health and the need to reactivate the economy. This study proposes and applies a modification of the SIR infection model to describe the evolution of coronavirus infections and to measure the effect of quarantine on the number of people infected. Methods: Two hypotheses, not necessarily mutually exclusive, are proposed for the impact of quarantines. According to the first hypothesis, quarantine reduces the infection rate, delaying new infections over time without modifying the total number of people infected at the end of the wave. The second hypothesis establishes that quarantine reduces the population infected in the wave. The two hypotheses are tested with data for a sample of 10 districts in Santiago, Chile. Results: The results of applying the methodology show that the proposed model describes well the evolution of infections at the district level. The data shows evidence in favor of the first hypothesis, quarantine reduces the infection rate; and not in favor of the second hypothesis, that quarantine reduces the population infected. Districts of higher socio-economic levels have a lower infection rate, and quarantine is more effective. Conclusions: Quarantine, in most districts, does not reduce the total number of people infected in the wave; it only reduces the rate at which they are infected. The reduction in the infection rate avoids peaks that may collapse the health system.

scholarly journals Persepsi Masyarakat Terhadap Pemberlakuan Social Distancing Di Masa Pandemi Covid-19 Sebagai Implementasi Modal Sosial

2021 ◽  
Vol 3 (1) ◽  
pp. 25-31
Author(s):  
Ade Suherman ◽  
Tetep Tetep ◽  
Asep Supriyatna ◽  
Eldi Mulyana ◽  
Triani Widyanti ◽  
...  
Keyword(s):  
Social Capital ◽  
Health Condition ◽  
Public Perceptions ◽  
Research Approach ◽  
Community Group ◽  
Social Distancing ◽  
The Government ◽  
The Impact ◽  
Staying At Home ◽  
At Home

The purpose of this study is to analyze and explain public perceptions of the implementation of social distancing during the pandemic as the implementation of social capital. This study was motivated by the phenomenon of the outbreak of the Covid-19 pandemic in a number of countries, including Indonesia. This condition not only affects the economic condition of a country, hinders social interaction among the community, and also has an impact on the health condition of every human being. To avoid the wider spread of Covid-19, the government was forced to adopt social distancing and physical distancing policies in the form of staying at home, working from home, studying, and worshiping at home. This research approach is descriptive qualitative. The data of this research is the impact of social distancing for the community in Tarogong Kidul District, Garut Regency. Sources of data come from several communities with a total of 50 respondents. Collecting data in this study using interview techniques, record, and continue to take notes. The results of the research can be concluded that with the implementation of social distancing in the pandemic period, at least the community can implement social capital which includes informal values ​​or norms that are shared among members of an interrelated community group, which is based on the values ​​of beliefs, norms and networks social and they respect each other, the development of social capital is the creation of increasingly independent groups of people who are able to participate more meaningfully. Social capital can solve citizens' problems, especially with regard to strengthening friendship, repairing and maintaining public service facilities because it has advantages and is the most appropriate, even though there are other social capital in the community.

scholarly journals Epidemiological trend of COVID-19 in Nepal and the importance of social distancing to contain the virus

2020 ◽  
Vol 1 (1) ◽  
pp. 15-25
Author(s):  
Amod K. Pokhrel ◽  
Yadav P. Joshi ◽  
Sopnil Bhattarai
Keyword(s):  
Mitigation Measures ◽  
Contact Tracing ◽  
Limited Information ◽  
Social Distancing ◽  
Mobility Data ◽  
Epidemiological Trend ◽  
Reproduction Numbers ◽  
The Government ◽  
Testing Case ◽  
The Impact

There is limited information on the epidemiology and the effects of mitigation measures on the spread of COVID-19 in Nepal. Using publicly available databases, we analyzed the epidemiological trend, the people's movement trends at different intervals across different categories of places and evaluated implications of social mobility on COVID-19. We also estimated the epidemic peak. As of June 9, 2020, Provinces 2 and 5 have most of the cases. People between 15 and 54 years are vulnerable to becoming infected, and more males than females are affected. The cases are growing exponentially. The growth rate of 0.13 and >1 reproduction numbers (R0) over time (median: 1.48; minimum: 0.58, and maximum: 3.71) confirms this trend. The case doubling time is five days. Google's community mobility data suggest that people strictly followed social distancing measures for one month after the lockdown. By around the 4th week of April, the individual's movement started rising, and social contacts increased. The number of cases peaked on May 12, with 83 confirmed cases in one day. The Susceptible-Exposed-Infectious-Removed (SEIR) model suggests that the epidemic will peak approximately on day 41 (July 21, 2020), and start to plateau after day 80. To contain the spread of the virus, people should maintain social distancing. The Government needs to continue active surveillance, more PCR-based testing, case detection, contact tracing, isolation, and quarantine. The Government should also provide financial support and safety-nets to the citizen to limit the impact of COVID-19.

scholarly journals Using the infection fatality rate to predict the evolution of Covid-19 in Brazil

2020 ◽  
Author(s):  
M. S. Cecconello ◽  
G. L. Diniz ◽  
E. B. Silva
Keyword(s):  
Sir Model ◽  
Fatality Rate ◽  
Social Distancing ◽  
Governmental Agencies ◽  
Transmission Parameters ◽  
The Impact

AbstractIn this work we are going to use estimates of Infection Fatality Rate (IFR) for Covid-19 in order to predict the evolution of Covid-19 in Brazil. To this aim, we are going to fit the parameters of the SIR model using the official deceased data available by governmental agencies. Furthermore, we are going to analyse the impact of social distancing policies on the transmission parameters.

scholarly journals Pengedukasian Umkm Jegeg Bali Tailor melalui Transformasi Digital Selama Pandemi Covid-19 di Tabanan-Bali

2021 ◽  
Vol 9 (1) ◽  
Author(s):  
Kadek Adi Wibawa ◽  
Ni Made Devi Mayanti
Keyword(s):  
Community Service ◽  
Product Packaging ◽  
Social Distancing ◽  
Direct Observations ◽  
Political Implications ◽  
Service Activity ◽  
The Government ◽  
Almost All ◽  
Promotion Process ◽  
The Impact

Abstract. The existence of the Covid-19 pandemic requires people to comply with health protocols established by the government, such as wearing masks, social distancing, traveling outside the house only when there is an interest, and diligently washing their hands properly and using soap. The Covid-19 pandemic has economic, social and political implications not only for big countries but almost all countries in the world. Indonesia is one of the countries affected especially on the economic side. Indonesia which is dominated by Usaha Mikro Kecil Menengah (UMKM) needs to pay special attention to this sector because the contribution of UMKM to the National economy is quite large. The target of this community service is an UMKM that is engaged in the production of sewing women's kebaya and formal clothes. Based on the results of direct observations, there were problems faced by UMKM, namely the problem of lack of product promotion media and the absence of financial records at UMKM. Activities carried out include assisting the online promotion process by utilizing social media and e-commerce, creating logos and product packaging innovations, and making financial records for UMKM. In its implementation, activities are carried out online and offline. This community service activity is expected to help UMKM in the economic sector due to the impact caused by Covid-19.Key Words: The impact of Covid-19, UMKM, online promotions, and product innovationAbstrak. Adanya pandemi Covid-19 mewajibkan masyarakat mematuhi protokol kesehatan yang ditetapkan oleh pemerintah, seperti memakai masker, menjaga jarak atau social distancing, bepergian keluar rumah hanya saat ada kepentingan, dan rajin mencuci tangan dengan benar dan menggunakan sabun. Pandemi Covid-19 memberikan implikasi ekonomi, sosial, dan politik tidak saja pada negara-negara besar akan tetapi hampir seluruh negara di dunia. Indonesia adalah salah satu negara yang terdampak terutama pada sisi ekonomi. Indonesia yang didominasi oleh Usaha Mikro, Kecil, dan Menengah (UMKM) perlu memberikan perhatian khusus terhadap sektor ini karena kontribusi UMKM terhadap perekonomian Nasional yang cukup besar. Sasaran pengabdian pada masyarakat ini merupakan sebuah UMKM yang bergerak dibidang produksi menjahit kebaya wanita dan pakaian formal. Berdasarkan hasil observasi yang  dilakukan secara langsung, ditemukan permasalahan yang dihadapi UMKM ini, yaitu masalah kurangnya media promosi produk dan tidak adanya catatan keuangan pada UMKM. Kegiatan yang dilakukan adalah membantu proses promosi secara online dengan memanfaatkan media sosial dan e-commerce, pembuatan logo dan inovasi kemasan produk, serta pembuatan catatan keuangan untuk UMKM. Dalam pelaksanaannya kegiatan dilakukan secara online dan offline. Kegiatan pengabdian pada masyarakat ini diharapkan dapat membantu UMKM dalam bidang ekonomi akibat dampak yang disebabkan oleh Covid-19.Kata kunci: Dampak Covid-19, UMKM, promosi online, dan inovasi produk

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.

Inverse Problem for Identification of Infectivity and Recovery Rates in SIR Epidemic Models as Functions of Time Illustrated  with Corona Virus Dynamics  up to July 09, 2020

2020 ◽  
Author(s):  
Tchavdar Marinov ◽  
Rossitza Marinova
Keyword(s):  
Inverse Problem ◽  
United States Of America ◽  
Real Data ◽  
The United States ◽  
Sir Model ◽  
Recovery Rates ◽  
Sir Epidemic ◽  
Term Evolution ◽  
Sir Epidemic Models

Abstract This work deals with the inverse problem in epidemiology based on a SIR model with time-dependent infectivity and recovery rates, allowing for a better prediction of the long term evolution of a pandemic. The method is used for investigating the COVID-19 spread by first solving an inverse problem for estimating the infectivity and recovery rates from real data. Then, the estimated rates are used to compute the evolution of the disease. The time-depended parameters are estimated for the World and several countries (The United States of America, Canada, Italy, France, Germany, Sweden, Russia, Brazil, Bulgaria, Japan, South Korea, New Zealand) and used for investigating the COVID-19 spread in these countries.

scholarly journals What drives support for social distancing? Pandemic politics, securitization, and crisis management in Britain

2021 ◽  
pp. 1-21
Author(s):  
Georgios Karyotis ◽  
John Connolly ◽  
Sofía Collignon ◽  
Andrew Judge ◽  
Iakovos Makropoulos ◽  
...  
Keyword(s):  
Crisis Management ◽  
Public Attitudes ◽  
Public Support ◽  
Personal Health ◽  
Social Distancing ◽  
Formative Stage ◽  
Securitization Theory ◽  
The Government ◽  
The Uk ◽  
The Impact

Abstract Support for social distancing measures was, globally, high at the early stages of the COVID-19 pandemic but increasingly came under pressure. Focusing on the UK, this article provides a rigorous exploration of the drivers of public support for social distancing at their formative stage, via mixed methods. Synthesizing insights from crisis management and securitization theory, thematic analysis is employed to map the main frames promoted by the government and other actors on the nature/severity, blame/responsibility, and appropriate response to the pandemic, which ‘follows the science’. The impact of these on public attitudes is examined via a series of regression analyses, drawing on a representative survey of the UK population (n = 2100). Findings challenge the prevailing understanding that support for measures is driven by personal health considerations, socio-economic circumstances, and political influences. Instead, crisis framing dynamics, which the government is well-positioned to dominate, have the greatest impact on driving public attitudes.

scholarly journals The effect of control measures on COVID-19 transmission in South Korea

PLoS ONE ◽  
2021 ◽  
Vol 16 (3) ◽  
pp. e0249262
Author(s):  
Taeyong Lee ◽  
Hee-Dae Kwon ◽  
Jeehyun Lee
Keyword(s):  
Transmission Rate ◽  
School Closure ◽  
Control Measures ◽  
After School ◽  
Epidemic Threshold ◽  
Social Distancing ◽  
Control And Prevention ◽  
Age Structured ◽  
Net Reproduction ◽  
The Impact

Countries around the world have taken control measures to mitigate the spread of COVID-19, including Korea. Social distancing is considered an essential strategy to reduce transmission in the absence of vaccination or treatment. While interventions have been successful in controlling COVID-19 in Korea, maintaining the current restrictions incurs great social costs. Thus, it is important to analyze the impact of different polices on the spread of the epidemic. To model the COVID-19 outbreak, we use an extended age-structured SEIR model with quarantine and isolation compartments. The model is calibrated to age-specific cumulative confirmed cases provided by the Korea Disease Control and Prevention Agency (KDCA). Four control measures—school closure, social distancing, quarantine, and isolation—are investigated. Because the infectiousness of the exposed has been controversial, we study two major scenarios, considering contributions to infection of the exposed, the quarantined, and the isolated. Assuming the transmission rate would increase more than 1.7 times after the end of social distancing, a second outbreak is expected in the first scenario. The epidemic threshold for increase of contacts between teenagers after school reopening is 3.3 times, which brings the net reproduction number to 1. The threshold values are higher in the second scenario. If the average time taken until isolation and quarantine reduces from three days to two, cumulative cases are reduced by 60% and 47% in the first scenario, respectively. Meanwhile, the reduction is 33% and 41%, respectively, for rapid isolation and quarantine in the second scenario. Without social distancing, a second wave is possible, irrespective of whether we assume risk of infection by the exposed. In the non-infectivity of the exposed scenario, early detection and isolation are significantly more effective than quarantine. Furthermore, quarantining the exposed is as important as isolating the infectious when we assume that the exposed also contribute to infection.

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