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Government policies, national culture and social distancing during the first wave of the COVID-19 pandemic: International evidence.

ABSTRACT: We assess the impact of national culture and government policies on social distancing to fight COVID-19 across major economies during the first wave of the pandemic. To do so, we regress government stringency index from Oxford COVID-19 government response tracker together with Hofstede's national culture scores on social distancing data from Google mobility reports. We find that government stringency has a far larger impact on social distancing than national culture. Social distancing increases with government stringency. We find two cultural dimensions matter: social distancing decreases with 'Long-term Orientation'; the opposite is true for 'Indulgence'. Our results convey that policymakers must act decisively rather than blaming the culture.

SUBMITTER: Wang Y

PROVIDER: S-EPMC9759369 | biostudies-literature | 2021 Mar

REPOSITORIES: biostudies-literature

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Government policies, national culture and social distancing during the first wave of the COVID-19 pandemic: International evidence.

Wang Yan Y

Safety science 20201226

We assess the impact of national culture and government policies on social distancing to fight COVID-19 across major economies during the first wave of the pandemic. To do so, we regress government stringency index from Oxford COVID-19 government response tracker together with Hofstede's national culture scores on social distancing data from Google mobility reports. We find that government stringency has a far larger impact on social distancing than national culture. Social distancing increases ...[more]

PMID: 36570788

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Project description:BackgroundSocial distancing policies were of utmost importance during the early stages of the COVID-19 pandemic. These policies aimed to mitigate the severity of local outbreaks by altering public behavior. However, if the severity of the pandemic reduces, the impact of these policies on actual behavior may decrease. This study aims to examine, from a global perspective, whether the impact of social distancing policies on actual mobility is moderated by local pandemic severity and whether this moderating effect varies across cultural value contexts.MethodsWe combined multiple publicly available global datasets for structural equation model analysis. 17,513 rows of data from 57 countries included in all databases were analyzed. Multilevel moderated moderation models were constructed to test the hypotheses.ResultsMore stringent policies in a region mean less regional mobility (β = -0.572, p < 0.001). However, the severity of local outbreaks negatively moderated this effect (β = -0.114, p < 0.001). When the pandemic was not severe, the influence of policy intensity on mobility weakened. Furthermore, based on Schwartz's cultural values theory, cultural values of autonomy (β = -0.109, p = 0.011), and egalitarianism (β = -0.108, p = 0.019) reinforced the moderating effect of pandemic severity. On the other hand, cultural values of embeddedness (β = 0.119, p = 0.006) and hierarchy (β = 0.096, p = 0.029) attenuated the moderating effect.ConclusionsSocial distancing policies aim to reduce the severity of local pandemics; however, the findings reveal that mitigating local pandemics may reduce their impact. Future policymakers should be alert to this phenomenon and introduce appropriate incentives to respond. The results also show that the moderating role of pandemic severity varies across cultures. When policies are promoted to deal with global crises, policymakers must seriously consider the resistance and potential incentives of cultural values.

Project description:ImportanceIn the absence of a national strategy in response to the COVID-19 pandemic, many public health decisions fell to local elected officials and agencies. Outcomes of such policies depend on a complex combination of local epidemic conditions and demographic features as well as the intensity and timing of such policies and are therefore unclear.ObjectiveTo use a decision analytical model of the COVID-19 epidemic to investigate potential outcomes if actual policies enacted in March 2020 (during the first wave of the epidemic) in the St Louis region of Missouri had been delayed.Design, setting, and participantsA previously developed, publicly available, open-source modeling platform (Local Epidemic Modeling for Management & Action, version 2.1) designed to enable localized COVID-19 epidemic projections was used. The compartmental epidemic model is programmed in R and Stan, uses bayesian inference, and accepts user-supplied demographic, epidemiologic, and policy inputs. Hospital census data for 1.3 million people from St Louis City and County from March 14, 2020, through July 15, 2020, were used to calibrate the model.ExposuresHypothetical delays in actual social distancing policies (which began on March 13, 2020) by 1, 2, or 4 weeks. Sensitivity analyses were conducted that explored plausible spontaneous behavior change in the absence of social distancing policies.Main outcomes and measuresHospitalizations and deaths.ResultsA model of 1.3 million residents of the greater St Louis, Missouri, area found an initial reproductive number (indicating transmissibility of an infectious agent) of 3.9 (95% credible interval [CrI], 3.1-4.5) in the St Louis region before March 15, 2020, which fell to 0.93 (95% CrI, 0.88-0.98) after social distancing policies were implemented between March 15 and March 21, 2020. By June 15, a 1-week delay in policies would have increased cumulative hospitalizations from an observed actual number of 2246 hospitalizations to 8005 hospitalizations (75% CrI: 3973-15 236 hospitalizations) and increased deaths from an observed actual number of 482 deaths to a projected 1304 deaths (75% CrI, 656-2428 deaths). By June 15, a 2-week delay would have yielded 3292 deaths (75% CrI, 2104-4905 deaths)-an additional 2810 deaths or a 583% increase beyond what was actually observed. Sensitivity analyses incorporating a range of spontaneous behavior changes did not avert severe epidemic projections.Conclusions and relevanceThe results of this decision analytical model study suggest that, in the St Louis region, timely social distancing policies were associated with improved population health outcomes, and small delays may likely have led to a COVID-19 epidemic similar to the most heavily affected areas in the US. These findings indicate that an open-source modeling platform designed to accept user-supplied local and regional data may provide projections tailored to, and more relevant for, local settings.

Dataset Information

Government policies, national culture and social distancing during the first wave of the COVID-19 pandemic: International evidence.

Publications

Government policies, national culture and social distancing during the first wave of the COVID-19 pandemic: International evidence.

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