scholarly journals A Mathematical Model for the Effect of Social Distancing on the Spread of COVID-19

2020 ◽  
Vol 6 (1) ◽  
Author(s):  
Anna Singley ◽  
Hannah Callender Highlander

Social distancing is an effective method of impeding the spread of a novel disease such as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), but is dependent on public involvement and is susceptible to failure when sectors of the population fail to participate. A standard SIR model is largely incapable of modeling differences in a population due to the broad generalizations it makes such as uniform mixing and homogeneity of hosts, which results in lost detail and accuracy when modeling heterogeneous populations. By further compartmentalizing an SIR model, via the separation of people within susceptible and infected groups, we can more accurately model epidemic dynamics and predict the eventual outcome, highlighting the importance of societal participation in social distancing measures during novel outbreaks.

Author(s):  
Mohammad Mahmudur Rahman ◽  
Asif Ahmed ◽  
Khondoker Moazzem Hossain ◽  
Tasnima Haque ◽  
Anowar Hussain

ABSTRACTBackgroundCOVID-19 is transmitting worldwide drastically and infected nearly two and half million of people so far. Till date 2144 cases of COVID-19 is confirmed in Bangladesh till 18th April though the stage-3/4 transmission is not validated yet.MethodsTo project the final infection numbers in Bangladesh we used the SIR mathematical model. Confirmed cases of infection data were obtained from Institute of Epidemiology, Disease Control and Research (IEDCR) of BangladeshResultsThe confirmed cases in Bangladesh follow our SIR model prediction cases. By the end of April the predicted cases of infection will be 17450 to 21616 depending on the control strategies. Due to large population and socio-economic characteristics, we assumed 60% social distancing and lockdown can be possible. Assuming that, the predicated final size of infections will be 3782558 on the 92th day from the first infections and steadily decrease to zero infection after 193 daysConclusionTo estimate the impact of social distancing we assumed eight different scenarios, the predicted results confirmed the positive impact of this type of control strategies suggesting that by strict social distancing and lockdown, COVID-19 infection can be under control and then the infection cases will steadily decrease down to zero.


2021 ◽  
Vol 10 (s1) ◽  
Author(s):  
Said Gounane ◽  
Yassir Barkouch ◽  
Abdelghafour Atlas ◽  
Mostafa Bendahmane ◽  
Fahd Karami ◽  
...  

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.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
G. B. Almeida ◽  
T. N. Vilches ◽  
C. P. Ferreira ◽  
C. M. C. B. Fortaleza

AbstractIn 2020, the world experienced its very first pandemic of the globalized era. A novel coronavirus, SARS-CoV-2, is the causative agent of severe pneumonia and has rapidly spread through many nations, crashing health systems and leading a large number of people to death. In Brazil, the emergence of local epidemics in major metropolitan areas has always been a concern. In a vast and heterogeneous country, with regional disparities and climate diversity, several factors can modulate the dynamics of COVID-19. What should be the scenario for inner Brazil, and what can we do to control infection transmission in each of these locations? Here, a mathematical model is proposed to simulate disease transmission among individuals in several scenarios, differing by abiotic factors, social-economic factors, and effectiveness of mitigation strategies. The disease control relies on keeping all individuals’ social distancing and detecting, followed by isolating, infected ones. The model reinforces social distancing as the most efficient method to control disease transmission. Moreover, it also shows that improving the detection and isolation of infected individuals can loosen this mitigation strategy. Finally, the effectiveness of control may be different across the country, and understanding it can help set up public health strategies.


2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Dipo Aldila ◽  
Brenda M. Samiadji ◽  
Gracia M. Simorangkir ◽  
Sarbaz H. A. Khosnaw ◽  
Muhammad Shahzad

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.


Diagnosis ◽  
2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Giuseppe Lippi ◽  
Camilla Mattiuzzi ◽  
Brandon M. Henry

Abstract The worldwide burden of coronavirus disease 2019 (COVID-19) is still unremittingly prosecuting, with nearly 300 million infections and over 5.3 million deaths recorded so far since the origin of the SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) pandemic at the end of the year 2019. The fight against this new highly virulent beta coronavirus appears one of the most strenuous and long challenges that humanity has ever faced, since a definitive treatment has not been identified so far. The adoption of potentially useful physical preventive measures such as lockdowns, social distancing and face masking seems only partially effective for mitigating viral spread, though efficacy and continuation of such measures on the long term is questionable, due to many social and economic reasons. Many COVID-19 vaccines have been developed and are now widely used, though their effectiveness is challenged by several aspects such as low uptake and limited efficacy in some specific populations, as well as by continuous emergence of new mutations in the SARS-CoV-2 genome, accompanying the origin and spread of new variants, which in turn may contribute to further decrease the effectiveness of current vaccines and treatments. This article is hence aimed to provide an updated picture of SARS-CoV-2 variants and mutations that have emerged from November 2019 to present time (i.e., early December 2021).


2018 ◽  
Vol 2018 ◽  
pp. 1-14 ◽  
Author(s):  
Pratchaya Chanprasopchai ◽  
I. Ming Tang ◽  
Puntani Pongsumpun

The dengue disease is caused by dengue virus, and there is no specific treatment. The medical care by experienced physicians and nurses will save life and will lower the mortality rate. A dengue vaccine to control the disease is available in Thailand since late 2016. A mathematical model would be an important way to analyze the effects of the vaccination on the transmission of the disease. We have formulated an SIR (susceptible-infected-recovered) model of the transmission of the disease which includes the effect of vaccination and used standard dynamical modelling methods to analyze the effects. The equilibrium states and their stabilities are investigated. The trajectories of the numerical solutions plotted into the 2D planes and 3D spaces are presented. The main contribution is determining the role of dengue vaccination in the model. From the analysis, we find that there is a significant reduction in the total hospitalization time needed to treat the illness.


2021 ◽  
Author(s):  
Pranesh Padmanabhan ◽  
Rajat Desikan ◽  
Narendra M Dixit

Although severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccines work predominantly by eliciting neutralizing antibodies (NAbs), how the protection they confer depends on the NAb response to vaccination is unclear. Here, we collated and analysed in vitro dose-response curves of >70 NAbs and constructed a landscape defining the spectrum of neutralization efficiencies of NAbs elicited. We mimicked responses of individuals by sampling NAb subsets of known sizes from the landscape and found that they recapitulated responses of convalescent patients. Combining individual responses with a mathematical model of within-host SARS-CoV-2 infection post-vaccination, we predicted how the population-level protection conferred would increase with the NAb response to vaccination. Our predictions captured the outcomes of vaccination trials. Our formalism may help optimize vaccination protocols, given limited vaccine availability.


Author(s):  
Laura Matrajt ◽  
Tiffany Leung

AbstractSARS-CoV-2 has infected over 140,000 people as of March 14, 2020. We use a mathematical model to investigate the effectiveness of social distancing interventions lasting six weeks in a middle-sized city in the US. We explore four social distancing strategies by reducing the contacts of adults over 60 years old, adults over 60 years old and children, all adults (25, 75 or 95% compliance), and everyone in the population. Our results suggest that social distancing interventions can avert cases by 20% and hospitalizations and deaths by 90% even with modest compliance within adults as long as the intervention is kept in place, but the epidemic is set to rebound once the intervention is lifted. Our models suggest that social distancing interventions will buy crucial time but need to occur in conjunction with testing and contact tracing of all suspected cases to mitigate transmission of SARS-CoV-2.


Sign in / Sign up

Export Citation Format

Share Document