Automation and redistribution of work: the impact of social distancing on live TV production

The COVID-19 pandemic is a serious challenge for societies around the globe as entire populations have fallen victim to the infectious spread and have taken up social distancing. In many countries, people have had to self-isolate and to be confined to their homes for several weeks to months to prevent the spread of the virus. Social distancing measures have had both negative and positive impacts on various aspects of economies, lifestyles, education, transportation, food supply, health, social life, and mental wellbeing. On other hands, due to reduced population movements and the decline in human activities, gas emissions decreased and the ozone layer improved; this had a positive impact on Earth’s weather and environment. Overall, the COVID-19 pandemic has negative effects on human activities and positive impacts on nature. This study discusses the impact of the COVID-19 pandemic on different life aspects including the economy, social life, health, education, and the environment.

Download Full-text

The impact of quarantine on Covid-19 infections

Epidemiologic Methods ◽

10.1515/em-2020-0038 ◽

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.

Download Full-text

The Effects of Social Distancing Policies on non-SARS-CoV-2 Respiratory Pathogens

Open Forum Infectious Diseases ◽

10.1093/ofid/ofab133 ◽

2021 ◽

Author(s):

Jeff Nawrocki ◽

Katherine Olin ◽

Martin C Holdrege ◽

Joel Hartsell ◽

Lindsay Meyers ◽

...

Keyword(s):

Public Health ◽

Influenza A ◽

Detection Rate ◽

Respiratory Illness ◽

Respiratory Pathogens ◽

Public Health Response ◽

Mixed Effect ◽

Detection Rates ◽

Social Distancing ◽

The Impact

Abstract Background The initial focus of the US public health response to COVID-19 was the implementation of numerous social distancing policies. While COVID-19 was the impetus for imposing these policies, it is not the only respiratory disease affected by their implementation. This study aimed to assess the impact of social distancing policies on non-SARS-CoV-2 respiratory pathogens typically circulating across multiple US states. Methods Linear mixed-effect models were implemented to explore the effects of five social distancing policies on non-SARS-CoV-2 respiratory pathogens across nine states from January 1 through May 1, 2020. The observed 2020 pathogen detection rates were compared week-by-week to historical rates to determine when the detection rates were different. Results Model results indicate that several social distancing policies were associated with a reduction in total detection rate, by nearly 15%. Policies were associated with decreases in pathogen circulation of human rhinovirus/enterovirus and human metapneumovirus, as well as influenza A, which typically decrease after winter. Parainfluenza viruses failed to circulate at historical levels during the spring. Total detection rate in April 2020 was 35% less than historical average. Many of the pathogens driving this difference fell below historical detection rate ranges within two weeks of initial policy implementation. Conclusion This analysis investigated the effect of multiple social distancing policies implemented to reduce transmission of SARS-CoV-2 on non-SARS-CoV-2 respiratory pathogens. These findings suggest that social distancing policies may be used as an impactful public health tool to reduce communicable respiratory illness.

Download Full-text

Mining Google and Apple mobility data: temporal anatomy for COVID-19 social distancing

Scientific Reports ◽

10.1038/s41598-021-83441-4 ◽

2021 ◽

Vol 11 (1) ◽

Cited By ~ 2

Author(s):

Corentin Cot ◽

Giacomo Cacciapaglia ◽

Francesco Sannino

Keyword(s):

Infection Rate ◽

The United States ◽

Strong Decrease ◽

Social Distancing ◽

Mobility Data ◽

Actual Measure ◽

The Us ◽

The Impact ◽

Political Decisions ◽

Mobility Reduction

AbstractWe employ the Google and Apple mobility data to identify, quantify and classify different degrees of social distancing and characterise their imprint on the first wave of the COVID-19 pandemic in Europe and in the United States. We identify the period of enacted social distancing via Google and Apple data, independently from the political decisions. Our analysis allows us to classify different shades of social distancing measures for the first wave of the pandemic. We observe a strong decrease in the infection rate occurring two to five weeks after the onset of mobility reduction. A universal time scale emerges, after which social distancing shows its impact. We further provide an actual measure of the impact of social distancing for each region, showing that the effect amounts to a reduction by 20–40% in the infection rate in Europe and 30–70% in the US.

Download Full-text

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

Epidemiologic Methods ◽

10.1515/em-2020-0044 ◽

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.

Download Full-text

The Impact of Work Characteristics on Social Distancing: Implications at the Time of COVID-19

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph18105074 ◽

2021 ◽

Vol 18 (10) ◽

pp. 5074

Author(s):

Keisuke Kokubun ◽

Yoshinori Yamakawa

Keyword(s):

Information Processing ◽

Multiple Regression ◽

Explanatory Power ◽

Work Conditions ◽

Multiple Regression Model ◽

Social Characteristics ◽

Work Characteristics ◽

Social Distancing ◽

Using Data ◽

The Impact

The coronavirus disease (COVID-19) continues to spread globally. While social distancing has attracted attention as a measure to prevent the spread of infection, some occupations find it difficult to implement. Therefore, this study aims to investigate the relationship between work characteristics and social distancing using data available on O*NET, an occupational information site. A total of eight factors were extracted by performing an exploratory factor analysis: work conditions, supervisory work, information processing, response to aggression, specialization, autonomy, interaction outside the organization, and interdependence. A multiple regression analysis showed that interdependence, response to aggression, and interaction outside the organization, which are categorized as ”social characteristics,” and information processing and specialization, which are categorized as “knowledge characteristics,” were associated with physical proximity. Furthermore, we added customer, which represents contact with the customer, and remote working, which represents a small amount of outdoor activity, to our multiple regression model, and confirmed that they increased the explanatory power of the model. This suggests that those who work under interdependence, face aggression, and engage in outside activities, and/or have frequent contact with customers, little interaction outside the organization, and little information processing will have the most difficulty in maintaining social distancing.

Download Full-text

PIN74 The Impact of Social Distancing on Sars-COV-2 Mortality: A US Analysis

Value in Health ◽

10.1016/j.jval.2020.08.915 ◽

2020 ◽

Vol 23 ◽

pp. S557

Author(s):

A. Gurubaran ◽

C. Holy ◽

S. Shah ◽

B. Nandi ◽

H. Dwarakanathan ◽

...

Keyword(s):

Social Distancing ◽

The Impact

Download Full-text

COVD-07. THE IMPACT OF COVID-19 ON PATIENTS AND CAREGIVERS AFFECTED BY BRAIN TUMORS: THE PATIENT NAVIGATOR PERSPECTIVE

Neuro-Oncology ◽

10.1093/neuonc/noaa215.091 ◽

2020 ◽

Vol 22 (Supplement_2) ◽

pp. ii22-ii22

Author(s):

Kyle Walsh

Keyword(s):

Clinical Trials ◽

Brain Tumor ◽

Clinical Care ◽

Structured Interview ◽

Patient Navigator ◽

Structured Interviews ◽

Social Distancing ◽

Tumor Patient ◽

Patient Navigators ◽

The Impact

Abstract BACKGROUND Preliminary evidence indicates that glioma patients are at higher risk for COVID-19 complications due to systemic immunosuppression. Interruptions in cancer care may exacerbate patient and caregiver anxiety, but surveying patients/caregivers about their COVID-19 experiences is often limited by attainable sample sizes and over-reliance upon single-institution experiences. METHODS To explore how COVID-19 is impacting brain tumor patients/caregivers across the U.S., we performed semi-structured interviews with brain tumor patient navigators employed by two different 501(c)3 nonprofit organizations. A semi-structured interview guide was used, utilizing prompts and open-ended questions to facilitate dialogue. A core set of COVID-19 topics were covered, including: financial issues, coping strategies, geographic variability, variability by tumor grade/histology, disruptions in care continuity, accessing clinical trials, psychosocial issues, and end-of-life care. Interviews were audio-recorded, transcribed, and organized by discussion topic to identify emerging themes. Inductive sub-coding was completed using the constant comparison method, within and between transcripts. RESULTS/CONCLUSIONS Ten patient navigators were interviewed between April 15th and May 8th, with interviews lasting approximately one hour (range 38-77minutes). Navigators reported having contact with 183 unique brain tumor families during the pandemic (range 7–38 families per navigator). High concordance emerged across narratives, revealing important considerations for the neuro-oncology workforce. The most prominent theme was increased caregiver burden, attributed to maintaining social distancing by reducing visits from home-health aides and friends/family. A related theme that applied to both patients and caregivers was increased social isolation due to social distancing, suspension of in-person support groups, and church/temple closures. Accessing clinical trials was a recurrent issue, exacerbated by patients’ increasing unwillingness to travel. Glioblastoma patients, especially those with recurrent tumors, expressed greater reluctance to travel. Access to standard-of-care treatment was rarely interrupted, but reduced access to supportive services – especially physical and occupational therapy – was identified as an emerging COVID-related deficiency in clinical care.

Download Full-text