Social distancing is crucial to slow down the spread of Covid-19. Social distancing behaviour depends on mandatory orders to \u2018stay-at-home\u2019 but also on voluntary compliance, which requires that individuals \u2018internalise the externality\u2019 they would impose on others in their community by not reducing their mobility or not observing social distancing. In other words, it requires that individuals understand that not complying with social distancing measures will have negative effects on people around them.<\/p>\n
Countries vary a great deal in the policy advice given to citizens: from strict lockdowns as in the case of Spain to almost complete voluntary compliance as in the case of Sweden.<\/p>\n
Here, we review evidence from real-time data collected across countries during the pandemic, which provides insights into what influences how people respond to instructions from policy-makers during the pandemic. We discuss the implications for the UK and other countries as governments continue to ease restrictions.<\/p>\n
Adherence to social distancing measures is crucial to slow the spread of Covid-19. Several studies that use real-time data collection in different countries find evidence that social capital and trust in institutions matter for compliance with social distancing during the pandemic.<\/p>\n
Social capital is \u2018the set of values and beliefs that helps a group overcome the free rider problem in the pursuit of socially valuable activities\u2019 (Almond and Verba<\/a>, 1963; Guiso et al<\/a>, 2011). Social capital has been shown to be relevant for contributions to public goods (Putnam<\/a>, 1993; Guiso et al<\/a>, 2016). Higher levels of social capital could therefore be crucial for the ability of citizens to comply voluntarily with social distancing measures, and not just \u2018free ride\u2019 on the good behaviour of others.<\/p>\n Evidence on the relevance of social capital and trust in government spans different countries.<\/p>\n For the United States, one study finds that counties with higher income and education and where people have more trust in science are more likely to observe social distancing measures voluntarily (Brzezinski et al<\/a>, 2020). The authors also note how government action influences but is also affected by communities\u2019 reactions. On the one hand, government policies can further amplify measures already taken at the community level. At the same time, restrictive policies are less necessary when the community acts independently to maintain social distancing measures.<\/p>\n Another study also investigates the importance of social capital for voluntary compliance, using individual and county data for the United States, together with evidence on European regions (Barrios et al<\/a>, 2020. The authors find that a higher level of social capital is strongly correlated with voluntary social distancing.<\/p>\n Similar results on the correlation between civic capital and individual mobility have been found in data from Italian provinces (Durante et al<\/a>, 2020): people limit their movements more in places where there is a stronger sense of community and responsibility to neighbours.<\/p>\n Reduced mobility might be the result of people trying to adhere to social distancing measures. One study analyses data on mobility and trust in government at the regional level in Europe (Bargain et al<\/a>, 2020).<\/p>\n The authors find that \u2018high-trust\u2019 regions decrease their mobility related to inessential activities significantly more than low-trust regions. The efficiency of lockdown policies in terms of mobility reduction also significantly increases with trust: mobility is reduced much more after lockdown in high-trust regions. This is consistent with the idea that trust in institutions improves regulation efficiency and compliance with rules and laws.<\/p>\n Overall, economic evidence suggests that civic capital is correlated with social distancing behaviour across individuals in the same countries, European regions and US counties.<\/p>\n Compliance with social distancing practices is measured using data on mobility. The most common sources, available across countries, are the Google Community Mobility Reports<\/em>, which provide anonymised data on changes in the number of visitors to (or the time spent in) certain categorised places, compared to a baseline.<\/p>\n Other sources are location data from mobile phones provided by private companies. These data allow the calculation of the change in average daily distance travelled from baseline during the pre-Covid-19 period and the change in visits to non-essential retail and services from baseline.<\/p>\n Data on mobility are only an indirect way of measuring compliance with different forms of social distancing (defined as the ability to keep a certain physical space \u2013 usually six feet or two meters \u2013 between an individual and other people outside their home). Getting data on these types of physical practices is almost impossible, implying that all the conclusions reached by existing studies are based on somewhat imprecise proxies.<\/p>\n Important policy implications can be derived from these studies. Public policy responses to pandemics should take account of the population\u2019s civic capital. In places with higher social capital, targeted policies can be as effective as across-the-board lockdowns but with lower economic costs.<\/p>\n In the European context, countries with low levels of social capital (such as Italy) had to impose strict lockdowns with potentially high economic costs, whereas Sweden, where civic capital is very high, had much less restrictive measures, based on the expectation that people would behave safely.<\/p>\n The existing results could also help to inform the re-opening phase. As many countries and states in the United States are re-opening their economies, the natural question to ask is whether voluntary compliance will continue after the restrictions have been lifted. Barrios et al<\/a> (2020) show that after one US state began re-opening, social distancing remained more prevalent in counties with high civic capital.<\/p>\n This can have potentially large implications: according to another study, \u2018limiting movement, whether voluntarily or by order, decreased the virus transmission rate by 49%. While official stay-at-home orders accounted for only a 7% decline in transmission rate, most of the decline attributable to reduced movement stemmed from voluntary changes\u2019 (Chen et al<\/a>, 2020).<\/p>\n The reduction in movement during the pandemic is also driven by the perceived severity of the crisis, filtered through a partisan lens. Evidence from different countries indicates that political beliefs, coupled with differences in media consumption, have important implications for risk perceptions and compliance with social distancing.<\/p>\n A study of Brazil finds that pro-government localities are less inclined to follow social distancing measures if the president dismisses the risks associated with the pandemic, and even more so in places with higher levels of media penetration (Ajzenman et al<\/a>, 2020).<\/p>\n The way in which people consume news and interpret facts is especially relevant for the United States with its increasing political divide, a result shared by many studies, which all find that pro-Trump counties are less prone to maintain social distancing, as a result of different risk perceptions emphasised by different news outlets (Barrios and Hochberg<\/a>, 2020; Allcott et al<\/a>, 2020; and Gadarian et al<\/a>, 2020).<\/p>\n To isolate the role of information, Bursztyn et al<\/a> (2020) study individuals watching two different shows on Fox News: one that warned viewers about the risks of the pandemic (Tucker Carlson Tonight) and one that instead dismissed the risks (Hannity). Carlson\u2019s viewers changed behaviour earlier, and this had an effect on the number of cases and deaths.<\/p>\n Another study examines partisan heterogeneity in response to state-level stay-at-home orders and shows that they are more likely to be followed by Democrats when the governor is a Democrat (Painter and Qiu<\/a>, 2020).<\/p>\n Grossman et al<\/a> (2020) document that governors\u2019 recommendations \u2013 as indicated by their comments on Twitter \u2013 preceded the issuance of stay-at-home orders, and that this had a significant effect on mobility, with the effect stronger for Democratic counties. They also find that both Democratic and Republican counties are equally responsive to Democratic governors; at the same time, Democratic counties are more responsive to Republican governors than Republican counties.<\/p>\n Overall, this body of research shows that individual perceptions about the severity of the virus are strongly influenced by news consumption and whether information comes from someone with similar or different political leanings than themselves. The reliability of messages from political leaders, providing consistent information about the severity of Covid-19, could substantially affect the response to the pandemic.<\/p>\n Related question:<\/strong> Risk in the time of Covid-19: what do we know and not know?<\/a><\/p><\/blockquote>\n Compliance with social distancing during the Covid-19 crisis<\/a>: Paola Giuliano and Imran Rasul draw on real-time data collected across many different countries to document important drivers of compliance with social distancing.<\/p>\n Leaders' speech and risky behaviour during a pandemic<\/a>: Nicolas Ajzenman and colleagues study how municipalities in Brazil react to presidential messages about the risk associated with the pandemic as a function of media penetration.<\/p>\n Civic capital and social distancing: evidence from Italians\u2019 response to Covid-19<\/a>: Ruben Durante and colleagues study the relationship between civic capital and social distancing across Italian provinces.<\/p>\n Political beliefs affect compliance with Covid-19 social distancing orders<\/a>: Marcus\u00a0Painter and Tian Qiu look at the effect of state-level social distancing orders in Democratic and Republican counties.<\/p>\nWhere does the evidence come from?<\/h3>\n
What types of data are used to measure social distancing practices?<\/h3>\n
Can the evidence help in the current re-opening phase?<\/h3>\n
Is the reaction to coronavirus a partisan issue?<\/h3>\n
Where can I found out more?<\/h3>\n
Who are experts on this question?<\/h3>\n
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Authors:\u00a0Imran Rasul<\/a> and\u00a0Paola Giuliano<\/a><\/h5>\n
Photo by Cheekylorns on Adobe Stock<\/h6>\n","protected":false},"featured_media":11442,"template":"","categories":[231,230],"tags":[],"yoast_head":"\n