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Article ; Online: Network model and analysis of the spread of Covid-19 with social distancing.

Maheshwari, Parul / Albert, Réka

Applied network science

2020 Volume 5, Issue 1, Page(s) 100

Abstract: ... The network and the disease parameters are informed by the existing literature on Covid-19. Using this model ... that could be mediators of disease spread. The nodes of this network are individuals and different types ... required to follow social distancing. Networks are a great way to represent interactions among people and ...

Abstract	The first mitigation response to the Covid-19 pandemic was to limit person-to-person interaction as much as possible. This was implemented by the temporary closing of many workplaces and people were required to follow social distancing. Networks are a great way to represent interactions among people and the temporary severing of these interactions. Here, we present a network model of human-human interactions that could be mediators of disease spread. The nodes of this network are individuals and different types of edges denote family cliques, workplace interactions, interactions arising from essential needs, and social interactions. Each individual can be in one of four states: susceptible, infected, immune, and dead. The network and the disease parameters are informed by the existing literature on Covid-19. Using this model, we simulate the spread of an infectious disease in the presence of various mitigation scenarios. For example, lockdown is implemented by deleting edges that denote non-essential interactions. We validate the simulation results with the real data by matching the basic and effective reproduction numbers during different phases of the spread. We also simulate different possibilities of the slow lifting of the lockdown by varying the transmission rate as facilities are slowly opened but people follow prevention measures like wearing masks etc. We make predictions on the probability and intensity of a second wave of infection in each of these scenarios.
Language	English
Publishing date	2020-12-29
Publishing country	Switzerland
Document type	Journal Article
ISSN	2364-8228
ISSN (online)	2364-8228
DOI	10.1007/s41109-020-00344-5
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Network model and analysis of the spread of Covid-19 with social distancing

Parul Maheshwari / Réka Albert

Applied Network Science, Vol 5, Iss 1, Pp 1-

2020 Volume 13

Abstract: ... and dead. The network and the disease parameters are informed by the existing literature on Covid-19 ... among people and the temporary severing of these interactions. Here, we present a network model of human–human ... interactions that could be mediators of disease spread. The nodes of this network are individuals and different ...

Abstract	Abstract The first mitigation response to the Covid-19 pandemic was to limit person-to-person interaction as much as possible. This was implemented by the temporary closing of many workplaces and people were required to follow social distancing. Networks are a great way to represent interactions among people and the temporary severing of these interactions. Here, we present a network model of human–human interactions that could be mediators of disease spread. The nodes of this network are individuals and different types of edges denote family cliques, workplace interactions, interactions arising from essential needs, and social interactions. Each individual can be in one of four states: susceptible, infected, immune, and dead. The network and the disease parameters are informed by the existing literature on Covid-19. Using this model, we simulate the spread of an infectious disease in the presence of various mitigation scenarios. For example, lockdown is implemented by deleting edges that denote non-essential interactions. We validate the simulation results with the real data by matching the basic and effective reproduction numbers during different phases of the spread. We also simulate different possibilities of the slow lifting of the lockdown by varying the transmission rate as facilities are slowly opened but people follow prevention measures like wearing masks etc. We make predictions on the probability and intensity of a second wave of infection in each of these scenarios.
Keywords	Epidemic spreading ; SIR model ; Social network ; Network science ; COVID-19 ; Reproduction number ; Applied mathematics. Quantitative methods ; T57-57.97
Subject code	612
Language	English
Publishing date	2020-12-01T00:00:00Z
Publisher	SpringerOpen
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Book ; Online: Network model and analysis of the spread of Covid-19 with social distancing

Maheshwari, Parul / Albert, Réka

2020

Abstract	The first mitigation response to the Covid-19 pandemic was to limit person-to-person interaction as much as possible. This was implemented by the temporary closing of many workplaces and people were required to follow social distancing. Networks are a great way to represent interactions among people and the temporary severing of these interactions. Here, we present a network model of human-human interactions that could be mediators of disease spread. The nodes of this network are individuals and different types of edges denote family cliques, workplace interactions, interactions arising from essential needs, and social interactions. Each individual can be in one of four states: susceptible, infected, immune, and dead. The network and the disease parameters are informed by the existing literature on Covid-19. Using this model, we simulate the spread of an infectious disease in the presence of various mitigation scenarios. For example, lockdown is implemented by deleting edges that denote non-essential interactions. We validate the simulation results with the real data by matching the basic and effective reproduction numbers during different phases of the spread. We also simulate different possibilities of the slow lifting of the lockdown by varying the transmission rate as facilities are slowly opened but people follow prevention measures like wearing masks etc. We make predictions on the probability and intensity of a second wave of infection in each of these scenarios. Comment: 16 pages, 10 figures
Keywords	Physics - Physics and Society ; Quantitative Biology - Populations and Evolution ; covid19
Publishing date	2020-06-16
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article: Network model and analysis of the spread of Covid-19 with social distancing

Maheshwari, Parul / Albert, R'eka

Abstract	The first mitigation response to the Covid-19 pandemic was to limit person-to-person interaction as much as possible. This was implemented by the temporary closing of many workplaces and people were required to follow social distancing. Networks are a great way to represent interactions among people and the temporary severing of these interactions. Here, we present a network model of human-human interactions that could be mediators of disease spread. The nodes of this network are individuals and different types of edges denote family cliques, workplace interactions, interactions arising from essential needs, and social interactions. Each individual can be in one of four states: susceptible, infected, immune, and dead. The network and the disease parameters are informed by the existing literature on Covid-19. Using this model, we simulate the spread of an infectious disease in the presence of various mitigation scenarios. For example, lockdown is implemented by deleting edges that denote non-essential interactions. We validate the simulation results with the real data by matching the basic and effective reproduction numbers during different phases of the spread. We also simulate different possibilities of the slow lifting of the lockdown by varying the transmission rate as facilities are slowly opened but people follow prevention measures like wearing masks etc. We make predictions on the probability and intensity of a second wave of infection in each of these scenarios.
Keywords	covid19
Publisher	ArXiv
Document type	Article
Database	COVID19

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Article ; Online: A network approach to understanding social distancing behaviour during the first UK lockdown of the COVID-19 pandemic.

Gibson-Miller, Jilly / Zavlis, Orestis / Hartman, Todd K / Bennett, Kate M / Butter, Sarah / Levita, Liat / Martinez, Anton P / Mason, Liam / McBride, Orla / McKay, Ryan / Murphy, Jamie / Shevlin, Mark / Stocks, Thomas V A / Bentall, Richard P

Psychology & health

2022 Volume 39, Issue 1, Page(s) 109–127

Abstract: Objective: Given the highly infectious nature of COVID-19, social distancing practices are key ... of the COVID-19 Psychological Research Consortium (C19PRC) Study. Using a network approach, we examined ... social distancing behaviour during the first UK lockdown. The COM-B model was successful in predicting particular ...

Abstract	Objective: Given the highly infectious nature of COVID-19, social distancing practices are key in stemming the spread of the virus. We aimed to assess the complex interplay among psychological factors, socio-demographic characteristics and social distancing behaviours within the framework of the widely used Capability, Opportunity, Motivation-Behaviour (COM-B) model. Design: The present research employed network psychometrics on data collected during the first UK lockdown in April 2020 as part of the COVID-19 Psychological Research Consortium (C19PRC) Study. Using a network approach, we examined the predictions of psychological and demographic variables onto social distancing practices at two levels of analysis: macro and micro. Results: Our findings revealed several factors that influenced social distancing behaviour during the first UK lockdown. The COM-B model was successful in predicting particular aspects of social-distancing via the influence of psychological capability and motivation at the macro-and micro-levels, respectively. Notably, demographic variables, such as education, income, and age, were directly and uniquely predictive of certain social distancing behaviours. Conclusion: Our findings reveal psychological factors that are key predictors of social distancing behaviour and also illustrate how demographic variables directly influence such behaviour. Our research has implications for the design of empirically-driven interventions to promote adherence to social distancing practices in this and future pandemics. Supplemental data for this article is available online at.
MeSH term(s)	Humans ; COVID-19/epidemiology ; COVID-19/prevention & control ; Pandemics ; Physical Distancing ; SARS-CoV-2 ; Communicable Disease Control ; United Kingdom/epidemiology
Language	English
Publishing date	2022-03-28
Publishing country	England
Document type	Journal Article
ZDB-ID	625255-2
ISSN	1476-8321 ; 0887-0446
ISSN (online)	1476-8321
ISSN	0887-0446
DOI	10.1080/08870446.2022.2057497
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Article: The impact of covid on network utilization: An analysis on domain popularity

Affinito, A. / Botta, A. / Ventre, G.

25th IEEE International Workshop on Computer Aided Modeling and Design of Communication Links and Networks, CAMAD 2020

Abstract: ... that the COVID-19 pandemic represents a very interesting situation from the network utilization point of view and ... in China, and for weeks later, in other countries of the world, isolation and social distancing measures ... in social media like Facebook App of messaging services and collaboration, like WhatsApp and Skype, have been used ...

Abstract	The emergency related to the Coronavirus has impacted everyone's life From the first weeks of 2020, in China, and for weeks later, in other countries of the world, isolation and social distancing measures have been adopted to avoid the spread of the virus, forcing people worldwide to isolate themselves in their homes This represents a unique case of study to understand the impact of such measures on Internet utilization In this paper, we provide insights on the use of different categories of Internet applications We use two complementary sources of information: the lists from Alexa and Cisco Umbrella regarding the top 1 Million websites and domains used worldwide Our results show that, during lockdowm time, the most used applications have been Youtube followed by Netflix, Facebook, Whatsapp and Skype This shows how users have looked for consolation in entertainment apps such as youtube, Netflix, and in social media like Facebook App of messaging services and collaboration, like WhatsApp and Skype, have been used to communicate with friends and families while also used for smart working Contrasting the results from the two lists, we also uncover important difference in the usage from different kids of devices We believe that the COVID-19 pandemic represents a very interesting situation from the network utilization point of view and we shed light on how such situation impacted the use of the Internet applications © 2020 IEEE
Keywords	covid19
Publisher	WHO
Document type	Article
Note	WHO #Covidence: #900799
Database	COVID19

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Article ; Online: Evaluating the impacts of non-pharmaceutical interventions on the transmission dynamics of COVID-19 in Canada based on mobile network.

Xue, Ling / Jing, Shuanglin / Wang, Hao

PloS one

2021 Volume 16, Issue 12, Page(s) e0261424

Abstract: ... of the COVID-19 epidemic. The simulation results indicate that social distancing and constricting human ... The COVID-19 outbreak has caused two waves and spread to more than 90% of Canada's provinces ... the transmission dynamics of COVID-19. The model takes into account the heterogeneity of mitigation strategies ...

Abstract	The COVID-19 outbreak has caused two waves and spread to more than 90% of Canada's provinces since it was first reported more than a year ago. During the COVID-19 epidemic, Canadian provinces have implemented many Non-Pharmaceutical Interventions (NPIs). However, the spread of the COVID-19 epidemic continues due to the complex dynamics of human mobility. We develop a meta-population network model to study the transmission dynamics of COVID-19. The model takes into account the heterogeneity of mitigation strategies in different provinces of Canada, such as the timing of implementing NPIs, the human mobility in retail and recreation, grocery and pharmacy, parks, transit stations, workplaces, and residences due to work and recreation. To determine which activity is most closely related to the dynamics of COVID-19, we use the cross-correlation analysis to find that the positive correlation is the highest between the mobility data of parks and the weekly number of confirmed COVID-19 from February 15 to December 13, 2020. The average effective reproduction numbers in nine Canadian provinces are all greater than one during the time period, and NPIs have little impact on the dynamics of COVID-19 epidemics in Ontario and Saskatchewan. After November 20, 2020, the average infection probability in Alberta became the highest since the start of the COVID-19 epidemic in Canada. We also observe that human activities around residences do not contribute much to the spread of the COVID-19 epidemic. The simulation results indicate that social distancing and constricting human mobility is effective in mitigating COVID-19 transmission in Canada. Our findings can provide guidance for public health authorities in projecting the effectiveness of future NPIs.
MeSH term(s)	Basic Reproduction Number/statistics & numerical data ; COVID-19/epidemiology ; COVID-19/prevention & control ; COVID-19/transmission ; Canada/epidemiology ; Epidemics/prevention & control ; Humans ; Incidence ; Models, Statistical ; Physical Distancing ; Quarantine/methods ; SARS-CoV-2 ; Travel/statistics & numerical data
Language	English
Publishing date	2021-12-29
Publishing country	United States
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ISSN	1932-6203
ISSN (online)	1932-6203
DOI	10.1371/journal.pone.0261424
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Dynamics of COVID-19 under social distancing measures are driven by transmission network structure.

Nande, Anjalika / Adlam, Ben / Sheen, Justin / Levy, Michael Z / Hill, Alison L

PLoS computational biology

2021 Volume 17, Issue 2, Page(s) e1008684

Abstract: ... epidemic model to examine the effects of COVID-19 clinical progression and transmission network structure ... the spread of COVID-19. The impact of these measures has been inconsistent, with some regions rapidly nearing ... and efficacy of interventions needed to control second waves of COVID-19 as well as other similar ...

Abstract	In the absence of pharmaceutical interventions, social distancing is being used worldwide to curb the spread of COVID-19. The impact of these measures has been inconsistent, with some regions rapidly nearing disease elimination and others seeing delayed peaks or nearly flat epidemic curves. Here we build a stochastic epidemic model to examine the effects of COVID-19 clinical progression and transmission network structure on the outcomes of social distancing interventions. Our simulations show that long delays between the adoption of control measures and observed declines in cases, hospitalizations, and deaths occur in many scenarios. We find that the strength of within-household transmission is a critical determinant of success, governing the timing and size of the epidemic peak, the rate of decline, individual risks of infection, and the success of partial relaxation measures. The structure of residual external connections, driven by workforce participation and essential businesses, interacts to determine outcomes. We suggest limited conditions under which the formation of household "bubbles" can be safe. These findings can improve future predictions of the timescale and efficacy of interventions needed to control second waves of COVID-19 as well as other similar outbreaks, and highlight the need for better quantification and control of household transmission.
MeSH term(s)	Algorithms ; COVID-19/epidemiology ; COVID-19/prevention & control ; COVID-19/transmission ; China/epidemiology ; Cluster Analysis ; Communicable Disease Control/methods ; Computer Simulation ; Disease Progression ; Epidemics ; Hospitalization ; Humans ; Models, Theoretical ; Physical Distancing ; Residence Characteristics
Language	English
Publishing date	2021-02-03
Publishing country	United States
Document type	Journal Article ; Research Support, N.I.H., Extramural
ZDB-ID	2193340-6
ISSN	1553-7358 ; 1553-734X
ISSN (online)	1553-7358
ISSN	1553-734X
DOI	10.1371/journal.pcbi.1008684
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Reconstructing a COVID-19 outbreak within a religious group using social network analysis simulation in Korea.

Kim, Namje / Kang, Su Jin / Tak, Sangwoo

Epidemiology and health

2021 Volume 43, Page(s) e2021068

Abstract: ... with a social network analysis (SNA) approach was used to simulate a COVID-19 outbreak. A discrete-time stochastic ... simulation model was used to simulate the spread of COVID-19 within the Sarang Jeil church. A counterfactual ... Conclusions: SNA is an effective tool for monitoring and controlling outbreaks of COVID-19 and ...

Abstract	Objectives: We reconstructed a coronavirus disease 2019 (COVID-19) outbreak to examine how a large cluster at a church setting spread before being detected and estimate the potential effectiveness of complying with mask-wearing guidelines recommended by the government. Methods: A mathematical model with a social network analysis (SNA) approach was used to simulate a COVID-19 outbreak. A discrete-time stochastic simulation model was used to simulate the spread of COVID-19 within the Sarang Jeil church. A counterfactual experiment using a calibrated baseline model was conducted to examine the potential benefits of complying with a mask-wearing policy. Results: Simulations estimated a mask-wearing ratio of 67% at the time of the outbreak, which yielded 953.8 (95% confidence interval [CI], 937.3 to 970.4) cases and was most consistent with the confirmed data. The counterfactual experiment with 95% mask-wearing estimated an average of 45.6 (95% CI, 43.4 to 47.9) cases with a standard deviation of 20.1. The result indicated that if the church followed government mask-wearing guidelines properly, the outbreak might have been one-twentieth the size. Conclusions: SNA is an effective tool for monitoring and controlling outbreaks of COVID-19 and other infectious diseases. Although our results are based on simulations and are thus limited, the precautionary implications of social distancing and mask-wearing are still relevant. Since person-to-person contacts and interactions are unavoidable in social and economic life, it may be beneficial to develop precise measures and guidelines for particular organizations or places that are susceptible to cluster outbreaks.
MeSH term(s)	COVID-19 ; Disease Outbreaks ; Humans ; Republic of Korea/epidemiology ; SARS-CoV-2 ; Social Network Analysis
Language	English
Publishing date	2021-09-16
Publishing country	Korea (South)
Document type	Journal Article
ZDB-ID	2590698-7
ISSN	2092-7193 ; 2092-7193
ISSN (online)	2092-7193
ISSN	2092-7193
DOI	10.4178/epih.e2021068
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Article ; Online: Pediatric and geriatric immunity network mobile computational model for COVID-19

Priya, K. Banu / Rajendran, P. / M., Sandeep Kumar / J., Prabhu / Rajendran, Sukumar / Kumar, P.J. / P., Thanapal / Christopher, Jabez / R., Jothikumar

International Journal of Pervasive Computing and Communications

2020 Volume 16, Issue 4, Page(s) 321–330

Abstract: ... people immunity network model for COVID- 19 patients. For the analysis part, the data's on COVID-19 cases ... social distancing. The novel model in this work focus on the Indian scenario and thereby may help Indian ... the authors developed a pediatric and geriatric person’s immunity network-based mobile computational model ...

Abstract	Purpose The computational model proposed in this work uses the data's of COVID-19 cases in India. From the analysis, it can be observed that the proposed immunity model decides the recovery rate of COVID −19 patients; moreover, the recovery rate does not depend on the age of the patients. These analytic models can be used by public health professionals, hospital administrators and epidemiologists for strategic decision-making to enhance health requirements based on various demographic and social factors of those affected by the pandemic. Mobile-based computational model can be used to compute the travel history of the affected people by accessing the near geographical maps of the path traveled. Design/methodology/approach In this paper, the authors developed a pediatric and geriatric person’s immunity network-based mobile computational model for COVID-19 patients. As the computational model is hard to analyze mathematically, the authors simplified the computational model as general COVID-19 infected people, the computational immunity model. The model proposed in this work used the data's of COVID-19 cases in India. Findings This study proposes a pediatric and geriatric people immunity network model for COVID- 19 patients. For the analysis part, the data's on COVID-19 cases in India was used. In this model, the authors have taken two sets of people (pediatric and geriatric), both are facing common symptoms such as fever, cough and myalgia. From the analysis, it was observed and also proved that the immunity level of patients decides the recovery rate of COVID-19 patients and the age of COVID-19 patients has no significant influence on the recovery rate of the patient. Originality/value COVID-19 has created a global health crisis that has had a deep impact on the way we perceive our world and our everyday lives. Not only the rate of contagion and patterns of transmission threatens our sense of agency, but the safety measures put in place to contain the spread of the virus also require social distancing. The novel model in this work focus on the Indian scenario and thereby may help Indian health organizations for future planning and organization. The factors model in this work such as age, immunity level, recovery rate can be used by machine leaning models for predicting other useful outcomes.
Keywords	Theoretical Computer Science ; General Computer Science ; covid19
Language	English
Publisher	Emerald
Publishing country	uk
Document type	Article ; Online
ZDB-ID	2423858-2
ISSN	1742-738X ; 1742-7371
ISSN (online)	1742-738X
ISSN	1742-7371
DOI	10.1108/ijpcc-06-2020-0054
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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