A new perspective from time use research on the effects of social restrictions on COVID-19 behavioral infection risk

Gershuny, Jonathan; Sullivan, Oriel; Sevilla, Almudena; Vega-Rapun, Marga; Foliano, Francesca; Grignon, Juana Lamote de; Harms, Teresa; Walthéry, Pierre

doi:10.1371/journal.pone.0245551

Cited by 28 publications

(39 citation statements)

References 19 publications

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“…This study undertakes an in-depth look into the socio-economic inequality of behavioural responses towards the corona virus pandemic. Despite the high income inequality and poverty in the country, the enhanced behavioural response is comparable to that of other developed countries [13]. There has been an increase in enhanced behavioural responsiveness, with 99% (as against 92% earlier) of respondents reporting some form of change in behaviour as a preventive measure against infection.…”

Section: Discussionmentioning

confidence: 85%

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Behavioural response to the Covid-19 pandemic in South Africa

Kollamparambil

Oyenubi

2021

PLoS ONE

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Background Given the economic and social divide that exists in South Africa, it is critical to manage the health response of its residents to the Covid-19 pandemic within the different socio-economic contexts that define the lived realities of individuals. Objective The objective of this study is to analyse the Covid-19 preventive behaviour and the socio-economic drivers behind the health-response behaviour. Data The study employs data from waves 1 and 2 of South Africa’s nationally representative National Income Dynamics Study (NIDS)—Coronavirus Rapid Mobile Survey (CRAM). The nationally representative panel data has a sample of 7073 individuals in Wave 1 and 5676 individuals in Wave 2. Methods The study uses bivariate statistics, concentration indices and multivariate estimation techniques, ranging from a probit, control-function approach, special-regressor method and seemingly unrelated regression to account for endogeneity while identifying the drivers of the response behaviour. Findings The findings indicate enhanced behavioural responsiveness to Covid-19. Preventive behaviour is evolving over time; the use of face mask has overtaken handwashing as the most utilised preventive measure. Other measures, like social distancing, avoiding close contact, avoiding big groups and staying at home, have declined between the two periods of the study. There is increased risk perception with significant concentration among the higher income groups, the educated and older respondents. Our findings validate the health-belief model, with perceived risk, self-efficacy, perceived awareness and barriers to preventive strategy adoption identified as significant drivers of health-response behaviour. Measures such as social distancing, avoiding close contact, and the use of sanitisers are practised more by the rich and educated, but not by the low-income respondents. Conclusion The respondents from lower socio-economic backgrounds are associated with optimism bias and face barriers to the adoption of preventive strategies. This requires targeted policy attention in order to make response behaviour effective.

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Section: Discussionmentioning

confidence: 85%

“…Literature on behavioural response to Covid-19 is fast emerging [13][14][15][16][17][18]. The limitations highlighted in the context of the pandemic literature prior to Covid-19 holds true for the more recent studies as well.…”

Section: Literature Reviewmentioning

confidence: 99%

Behavioural response to the Covid-19 pandemic in South Africa

Kollamparambil

Oyenubi

2021

PLoS ONE

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“…Complete spatio-temporal accounts of the activities (including their location and social context) and socio-demographic characteristics of representative samples are key to understanding populations' changing behavioral risks of infection [1]. Epidemiological surveys of behavior during the pandemic have focused on measuring social contacts in order to determine risk [2,3,4,5], while social science surveys have mainly focused on asking respondents to estimate the quantity of time they spent in different activities at particular times [6].…”

Section: Introductionmentioning

confidence: 99%

Using time-use diaries to track changing behavior across successive stages of COVID-19 social restrictions

Sullivan

Gershuny

Sevilla

et al. 2021

Proc. Natl. Acad. Sci. U.S.A.

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How did people change their behavior over the different phases of the UK COVID-19 restrictions, and how did these changes affect their risk of being exposed to infection? Time-use diary surveys are unique in providing a complete chronicle of daily behavior: 24-h continuous records of the populations’ activities, their social context, and their location. We present results from four such surveys, collected in real time from representative UK samples, both before and at three points over the course of the current pandemic. Comparing across the four waves, we find evidence of substantial changes in the UK population’s behavior relating to activities, locations, and social context. We assign different levels of risk to combinations of activities, locations, and copresence to compare risk-related behavior across successive “lockdowns.” We find evidence that during the second lockdown (November 2020), there was an increase in high-risk behaviors relative to the first (starting March 2020). This increase is shown to be associated with more paid work time in the workplace. At a time when capacity is still limited both in respect of immunization and track–trace technology, governments must continue to rely on changes in people’s daily behaviors to contain the spread of COVID-19 and similar viruses. Time-use diary information of this type, collected in real time across the course of the COVID-19 pandemic, can provide policy makers with information to assess and quantify changes in daily behaviors and the impact they are likely to have on overall behavioral-associated risks.

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“…Finally, to take exposure duration into account we assigned all activity combinations lasting only one 10-minute timeslot to the lowest risk level (level 1) [21]. For a more detailed description of these risk assignments and their rationale see Table 1 and Gershuny et al 2020 [1]. 3…”

Section: Methodsmentioning

confidence: 99%

“…Complete spatio-temporal accounts of the activities (including their location and social context) and socio-demographic characteristics of representative samples are key to understanding populations’ changing behavioral risks of infection [1]. Epidemiological surveys of behavior during the pandemic have focused on measuring social contacts in order to determine risk [2,3,4,5], while social science surveys have mainly focused on asking respondents to estimate the quantity of time they spent in different activities at particular times [6].…”

Section: Introductionmentioning

confidence: 99%

Using time use diaries to track changing behavior across successive stages of COVID-19 social restrictions

Gershuny

Sullivan

Sevilla

et al. 2021

Preprint

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We present analyses of 24-hour time use diary records of the UK population’s activities, their social context and their location, collected in real time from four successive waves of representative UK samples, both before, and during, the current COVID-19 pandemic. We show changes in behavioral response to social restrictions at three time-points during the pandemic, including across two nationwide lockdowns. Comparing samples across the four waves, we find evidence of substantial changes in the population’s activities, locations and social interactions, which may be interpreted as direct responses to changes in regulations. One of our main motivations was to compare risk-related behavior across the first and second lockdowns. We find suggestive evidence that the second lockdown (recorded late November 2020) was less strictly adhered to than the first (recorded May- June 2020). Holding constant gender, age and social grade, the population spent on average 32 more minutes per day in high risk activities in late November 2020 than in first lockdown. Disaggregating by gender and age group, the difference was found to be statistically significant for all groups, with the exception of those aged 55 and over.Significance statementWhat do people do during lockdown? This set of data is unique in providing time use diary information in real time on changing behavior in the UK in response to each major change in social restrictions. This enables us to directly compare 24-hour continuous and comprehensive information on the populations’ activities, their social context and their location, comparing risk- related behavior during different phases of social restrictions. Holding constant gender, age and social grade, we show that the UK population spent on average 32 more minutes per day in high risk activities in the second UK lockdown in November 2020 than in first lockdown (starting March 2020). This difference was statistically significant.

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A new perspective from time use research on the effects of social restrictions on COVID-19 behavioral infection risk

Cited by 28 publications

References 19 publications

Behavioural response to the Covid-19 pandemic in South Africa

Behavioural response to the Covid-19 pandemic in South Africa

Using time-use diaries to track changing behavior across successive stages of COVID-19 social restrictions

Using time use diaries to track changing behavior across successive stages of COVID-19 social restrictions

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