scholarly journals Finding an optimal distance of social distancing for COVID 19

2021 ◽  
Vol 3 (3) ◽  
pp. 206-220
Author(s):  
J Samuel Manoharan

Social distancing is a non-pharmaceutical infection prevention and control approach that is now being utilized in the COVID-19 scenario to avoid or restrict the transmission of illness in a community. As a consequence, the disease transmission, as well as the morbidity and mortality associated with it are reduced. The deadly coronavirus will circulate if the distance between the two persons in each site is used. However, coronavirus exposure must be avoided at all costs. The distance varies due to different nations' political rules and the conditions of their medical embassy. The WHO established a social distance of 1 to 2 metres as the standard. This research work has developed a computational method for estimating the impact of coronavirus based on various social distancing metrics. Generally, in COVID – 19 situations, social distance ranging from long to extremely long can be a good strategy. The adoption of extremely small social distance is a harmful approach to the pandemic. This calculation can be done by using deep learning based on crowd image identification. The proposed work has been utilized to find the optimal social distancing for COVID – 19 and it is identified as 1.89 meter. The purpose of the proposed experiment is to compare the different types of deep learning based image recognition algorithms in a crowded environment. The performance can be measured with various metrics such as accuracy, precision, recall, and true detection rate.

Author(s):  
Mr. Kiran Mudaraddi

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.


2021 ◽  
Author(s):  
Paolo Scarabaggio ◽  
Raffaele Carli ◽  
Graziana Cavone ◽  
Nicola Epicoco ◽  
Mariagrazia Dotoli

The recent trends of the COVID-19 research are being devoted to disease transmission modeling in presence of vaccinated individuals, while the emerging needs are being focused on developing effective strategies for the optimal distribution of vaccine between population. <br>In this context, we propose a novel non-linear time-varying model that effectively supports policy-makers in predicting and analyzing the dynamics of COVID-19 when partially and fully immune individuals are included in the population. Specifically, this paper proposes an accurate SIRUCQHE epidemiological model, with eight compartments (namely, Susceptible, Infected, Removed, Unsusceptible, Contagious, Quarantined, Hospitalized, and Extinct). <br>Differently from the related literature, where the common strategies typically rely on the prioritization of the different classes of individuals, we propose a novel Model Predictive Control approach to optimally control the multi-dose vaccine administration in the case the available number of doses is not sufficient to cover the whole population. Focusing on the minimization of the expected number of deaths, the approach discriminates between the number of first and second doses, thus considering also the possibility that some individuals may receive only one injection if the resulting expected fatalities are low. <br><div>To show the effectiveness of the resulting strategies, we first calibrate the model on the Israeli scenario using real data to get reliable predictions on the pandemic dynamics. Lastly, we estimate the impact of the vaccine administration on the virus dynamics and, in particular, based on validated model, we assess the impact of the first dose of the Pfitzer's vaccine confirming the results of clinical tests.</div><div><br></div><div><br></div><div>Extended version of the paper published in <i>Proceedings of the IEEE 16th International Conference on Automation Science and Engineering (CASE) </i><br> </div><div><b>How to cite:</b> Scarabaggio, P., Carli, R., Cavone, G., Epicoco, N., & Dotoli, M. "Modeling, Estimation, and Optimal Control of Anti-COVID-19 Multi-dose Vaccine Administration." In <i>2021 IEEE 17th International Conference on Automation Science and Engineering</i> (CASE) (pp. 990-995). IEEE.<br></div><div><br></div><div>DOI: <u>https://doi.org/10.1109/CASE49439.2021.9551418</u></div><div><br></div><div><br> </div>


Symmetry ◽  
2020 ◽  
Vol 12 (7) ◽  
pp. 1087 ◽  
Author(s):  
Liviu-Adrian Cotfas ◽  
Camelia Delcea ◽  
R. John Milne ◽  
Mostafa Salari

The novel coronavirus (SARS-CoV-2) has imposed the need for a series of social distancing restrictions worldwide to mitigate the scourge of the COVID-19 pandemic. This applies to many domains, including airplane boarding and seat assignments. As airlines are considering their passengers’ safety during the pandemic, boarding methods should be evaluated both in terms of social distancing norms and the resulting efficiency for the airlines. The present paper analyzes the impact of a series of restrictions that have been imposed or mooted worldwide on the boarding methods used by the airlines, featuring the use of jet-bridges and one-door boarding. To compare the efficacy of classical airplane boarding methods with respect to new social distancing norms, five metrics were used to evaluate their performance. One metric is the time to complete the boarding of the airplane. The other four metrics concern passenger health and reflect the potential exposure to the virus from other passengers through the air and surfaces (e.g., headrests and luggage) touched by passengers. We use the simulation platform in NetLogo to test six common boarding methods under various conditions. The back-to-front by row boarding method results in the longest time to complete boarding but has the advantage of providing the lowest health risk for two metrics. Those two metrics are based on passengers potentially infecting those passengers previously seated in the rows they traverse. Interestingly, those two risks are reduced for most boarding methods when the social distance between adjacent passengers advancing down the aisle is increased, thus indicating an unanticipated benefit stemming from this form of social distancing. The modified reverse pyramid by half zone method provides the shortest time to the completing boarding of the airplane and—along with the WilMA boarding method—provides the lowest health risk stemming from potential infection resulting from seat interferences. Airlines have the difficult task of making tradeoffs between economic productivity and the resulting impact on various health risks.


2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Giacomo Cacciapaglia ◽  
Francesco Sannino

Abstract One of the biggest threats to humanity are pandemics. In our global society they can rage around the world with an immense toll in terms of human, economic and social impact. Forecasting the spreading of a pandemic is, therefore, paramount in helping governments to enforce a number of social and economic measures, apt at curbing the pandemic and dealing with its aftermath. We demonstrate that the epidemic renormalisation group approach to pandemics provides an effective and simple way to investigate the dynamics of disease transmission and spreading across different regions of the world. The framework also allows for reliable projections on the impact of travel limitations and social distancing measures on global epidemic spread. We test and calibrate it on reported COVID-19 cases while unveiling the mechanism that governs the delay in the relative peaks of newly infected cases among different regions of the globe. We discover that social distancing measures are more effective than travel limitations across borders in delaying the epidemic peak. We further provide the link to compartmental models such as the time-honoured SIR-like models. We also show how to generalise the framework to account for the interactions across several regions of the world, replacing or complementing large scale simulations.


Author(s):  
Morgan P. Kain ◽  
Marissa L. Childs ◽  
Alexander D. Becker ◽  
Erin A. Mordecai

AbstractDisease transmission is notoriously heterogeneous, and SARS-CoV-2 is no exception. A skewed distribution where few individuals or events are responsible for the majority of transmission can result in explosive, superspreading events, which produce rapid and volatile epidemic dynamics, especially early or late in epidemics. Anticipating and preventing superspreading events can produce large reductions in overall transmission rates. Here, we present a compartmental (SEIR) epidemiological model framework for estimating transmission parameters from multiple imperfectly observed data streams, including reported cases, deaths, and mobile phone-based mobility that incorporates individual-level heterogeneity in transmission using previous estimates for SARS-CoV-1 and SARS-CoV-2. We parameterize the model for COVID-19 epidemic dynamics by estimating a time-varying transmission rate that incorporates the impact of non-pharmaceutical intervention strategies that change over time, in five epidemiologically distinct settings—Los Angeles and Santa Clara Counties, California; Seattle (King County), Washington; Atlanta (Dekalb and Fulton Counties), Georgia; and Miami (Miami-Dade County), Florida. We find the effective reproduction number ℛE dropped below 1 rapidly following social distancing orders in mid-March, 2020 and remained there into June in Santa Clara County and Seattle, but climbed above 1 in late May in Los Angeles, Miami, and Atlanta, and has trended upward in all locations since April. With the fitted model, we ask: how does truncating the tail of the individual-level transmission rate distribution affect epidemic dynamics and control? We find interventions that truncate the transmission rate distribution while partially relaxing social distancing are broadly effective, with impacts on epidemic growth on par with the strongest population-wide social distancing observed in April, 2020. Given that social distancing interventions will be needed to maintain epidemic control until a vaccine becomes widely available, “chopping off the tail” to reduce the probability of superspreading events presents a promising option to alleviate the need for extreme general social distancing.


2021 ◽  
Vol 9 (F) ◽  
pp. 601-607
Author(s):  
Nor Rumaizah Mohd Nordin ◽  
Fadly Syah Arsad ◽  
Puteri Sofia Nadira Megat Kamaruddin ◽  
Muhammad Hilmi ◽  
Mohd Faizal Madrim ◽  
...  

Background   Similar to other coronaviruses, COVID-19 is transmitted mainly by droplets and is highly transmissible through close proximity or physical contact with an infected person. Countries across the globe have implemented public health control measures to prevent onwards transmission and reduce burden on health care settings. Social or physical distancing was found to be one of appropriate measure based on previous experience with epidemic and pandemic contagious diseases. This study aims to review the latest evidence of the impact of social or physical distancing implemented during COVID-19 pandemic towards COVID-19 and other related infectious disease transmission.   Methodology   The study uses PRISMA review protocol and formulation of research question was based on PICO. The selected databases include Ovid MEDLINE and Scopus. Thorough identification, screening and eligibility process were done, revealed selected 8 articles. The articles then ranked in quality through MMAT.   Results   A total of eight papers included in this analysis. Five studies (USA, Canada, South Korea and the United Kingdom) showed physical distancing had resulted in a reduction in Covid-19 transmission. In comparison, three other studies (Australia, South Korea and Finland) showed a similar decline on other infectious diseases (Human Immunodeficiency Virus (HIV), other sexually transmitted infections (STI), Influenza, Respiratory Syncytial Virus (RSV) and Vaccine-Preventive Disease (VPD). The degree of the distancing policy implemented differ between strict and lenient, with both result in effectiveness in reducing transmission of infectious disease.   Conclusion   Physical or social distancing may come in the form of extreme or lenient measure in effectively containing contagious disease like COVID-19, however the stricter the measure will give more proportionate impact towards the economy, education, mental health issues, morbidity and mortality of non-COVID-19 diseases. Since we need this measure to ensure the reduction of infectious diseases transmission in order to help flattening the curve which allow much needed time for healthcare system to prepare adequately to response, ‘Precision physical distancing” can be implemented which will have more benefit towards the survival of the community as a whole.


Author(s):  
Jana L. Gevertz ◽  
James M. Greene ◽  
Cynthia Sanchez-Tapia ◽  
Eduardo D. Sontag

AbstractMotivated by the current COVID-19 epidemic, this work introduces an epidemiological model in which separate compartments are used for susceptible and asymptomatic “socially distant” populations. Distancing directives are represented by rates of flow into these compartments, as well as by a reduction in contacts that lessens disease transmission. The dynamical behavior of this system is analyzed, under various different rate control strategies, and the sensitivity of the basic reproduction number to various parameters is studied. One of the striking features of this model is the existence of a critical implementation delay (“CID”) in issuing separation mandates: while a delay of about two weeks does not have an appreciable effect on the peak number of infections, issuing mandates even slightly after this critical time results in a far greater incidence of infection. Thus, there is a nontrivial but tight “window of opportunity” for commencing social distancing in order to meet the capacity of healthcare resources. However, if one wants to also delay the timing of peak infections –so as to take advantage of potential new therapies and vaccines– action must be taken much faster than the CID. Different relaxation strategies are also simulated, with surprising results. Periodic relaxation policies suggest a schedule which may significantly inhibit peak infective load, but that this schedule is very sensitive to parameter values and the schedule’s frequency. Furthermore, we considered the impact of steadily reducing social distancing measures over time. We find that a too-sudden reopening of society may negate the progress achieved under initial distancing guidelines, but the negative effects can be mitigated if the relaxation strategy is carefully designed.


Coronaviruses ◽  
2020 ◽  
Vol 01 ◽  
Author(s):  
Ali Mehrabi Tavana ◽  
Mohamadkarim Bahadori

Background:: The coronavirus, which is now spreading around the world as a pandemic, has caused more than 30 million cases and nearly 1000,000 deaths worldwide. No vaccine has been used against the virus so far and there are no specific drugs to cure the patients. This paper examines the impact of coronavirus COVID-19 pandemic on employees’ health, either in governmental or private sector. The aim of this study was to protect staffs against disease in pandemic conditions by identifying the main ways to keep employee healthy during COVID-19 pandemic in different scenarios. Methods:: This paper is a perspective article and different scenario were assessed in order for consideration of employee health. Results:: Two scenarios could be considered first, when, the vaccine against Covid-19 is not available for prevention and the second scenario is that the vaccine is available for all in the world. In both cases, maintaining the health of the staff will be different. If the coronavirus disease will continue to occur in humans as long as access to a safe vaccine is not possible, emphasis on health standards, social distance and wearing the mask is the only way to deal with this dangerous disease. Even, with preparation of vaccine the health standards, social distancing, and wearing of mask must be continued in any situations. Conclusion:: The high level of health for employee must be considered by governments in different scenarios.


Author(s):  
Ms. K. Kusumalatha

The continuous COVID-19 Covid episode has caused a worldwide calamity with its dangerous spreading. due to the shortfall of successful healing specialists and therefore the lack of vaccinations against the infection, populace weakness increments. within the current circumstance, as there aren't any antibodies accessible; hence, social removing is believed to be a sufficient precautionary measure (standard) against the spread of the pandemic infection. the risks of infection spread may be limited by keeping aloof from actual contact among individuals. the rationale for this work is, thusly, to administer a profound learning stage to social distance is additionally executed to create the exactness of the model. Thusly, the popularity calculation utilizes a pre-prepared calculation that's related to an additional prepared the distinguished jumping box centroid's pairwise distances of people are resolved. To appraise social distance infringement between individuals, we utilized an estimation of actual distance to pixel and set a grip. An infringement limit is ready up to assess whether the space esteem breaks the bottom social distance edge. Analyses are done on various video arrangements to check the proficiency of the model. Discoveries show that the created system effectively recognizes folks that walk excessively close and penetrates/abuses social seperation; also, the trade collecting approach upholds the general efficiency of the model. The precision of 91% and 96% achieved by the acknowledgment model without and with move learning, independently. The accompanying precision of the model is 94%


2020 ◽  
Author(s):  
Hamed Tabesh ◽  
Azadeh Saki ◽  
Rozita Saki

Abstract The implementation of social distancing measures for controlling the outbreak of coronavirus disease 2019 (COVID‑19) in different countries has not been at the same level due to differences in policies, economies, and cultures. Hence, the effect of this pandemic on different aspects of societies varies depending on several factors.In this study, we found that the speed of disease transmission is directly related to the odds of being exposed to the disease in the society, that is directly related to the level of practicing social distancing measures. We introduced the weekly growth ratio (WGR) index and proposed an experimental rule model to monitor the current level of social distancing and predict the levels of intervention so as to reduce the WGR and control the sequential peaks. Our model showed that the minimum level of practicing social distancing in the community should be 80% to control the first peak of the disease; but after controlling the first peak, maintaining 50% of social distancing policies continuously keeps the number of cases/deaths constant and prevents the occurrence of a new peak.


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