It has been suggested that cultural factors can define the pre-existing (or, baseline) social and behavioural characteristics of societies and help to modulate both the public policy response and
individuals’ behavioural responses to the crisis in ways that impact infection transmission dynamics and key health outcomes.7,8,10 Indeed, numerous studies have shown that cultural factors can influence infectious disease dynamics, vaccination rates, infection prevention and control practices, and health outcomes. 6,11–13 For instance, it has been demonstrated that cultural attributes can predict almost half of the variance in Methicillin-resistant Staphylococcus aureus infections among European countries.11 However, no study has explored the impact of cultural/behavioural attributes in the context of the 2020 COVID–19 pandemic. To address this gap, we used meta-analytic methods to explore the global variability of COVID–19 attributed deaths during the first wave of the pandemic using two metrics (crude CFR and the mortality risk) and evaluated the role of demographic, cultural/behavioural, political economic and health-system-related predictors. We focused on mortality rather than the infection rate as this is the most crucial and most reliable metric of the pandemic’s impact given the absence of widespread surveillance and testing in most settings.
With respect to case fatalities (or, the risk of death among confirmed cases of infection), we found that health system resources constraints had the largest impact on case fatalities followed by demographics. A one unit increase in the number of hospital beds per 1,000 individuals led to a ~15–20% reduction in the odds of a fatal outcome among cases; while a unit increase in the proportion of the population over 65 years resulted in a ~6% increase in the odds of fatal outcome. Moreover, the findings highlight that cultural distinctions also play a small but significant role in accounting for the severity of the COVID–19 crisis. We found that a one-unit increase in individualism (vs. collectivism) was associated with ~2–3% increase in the odds of fatal outcome among infected individuals. We also found that a one-unit increase in uncertainty avoidance (i.e., a society’s discomfort with and resistance to unfamiliar phenomenon) was associated with ~1–2% increase in the odds of fatal outcome.
Similar trends were apparent when we evaluated the effects of these covariates on mortality risk (or, the risk of death among the general population). In this case, a one unit increase in the number of hospital beds per 1,000 individuals led to a ~23–26% reduction in the odds of a COVID–19-attributed death; while a unit increase in the proportion of the population over 65 years resulted in a ~11–13% increase in mortality. Cultural/behavioral characteristics also had a significant impact: a one-unit increase along the individualism dimension was associated with ~3–5% increase, while a one-unit increase in the uncertainty avoidance dimension was associated with ~3–4% increase in the odds of a COVID–19-attributed mortality among the population.
In total, demographic, economic, and cultural/behavioural factors could explain approximately half the variability in case fatalities and mortality risk during the initial wave of the pandemic. In terms of cultural characteristics, our analysis found that having a national culture that is more individualistic (vs. collectivist) and a cultural tendency toward uncertainty avoidance were both consistently associated with higher fatalities for both outcomes in all models assessed. Our exploratory analysis also found that a tendency towards long-term orientation vs. short-term normative orientation was also associated with a 2% increase in the odds of case fatality, whereas a greater degree of power distance index was associated with a 3% increase in the odds of a COVID–19 mortality.
In terms of individualism, in general, many European and Anglo-American democracies tend strongly towards individualism, whereas Asian nations display more collectivist attitudes.14,15 Individualism has often been equated with neo-liberal socioeconomic policies that tend to undermine social welfare and lead to weak collective protections.16 As well, individualist attitudes may more broadly lead to social behaviour that focuses on the individual rather than the collective well-being. For instance, in previous investigations, collectivist societies have been shown to be more effective in reducing the transmission of pathogens during outbreaks vs. individualistic ones.13,17 Similarly, individuals from more individualistic nations on the Hofstede dimensions have been shown to have lower vaccination intentions.12 However, a communication of the concept of herd immunity was shown to be able to improve vaccination intentions particularly in societies that lack a collectivistic baseline stance.12
As for uncertainty avoidance, Hofstede describes this dimension as a measure of a nation’s ability to adapt and cope with ambiguity.18 This indicates the degree of discomfort with unstructured, unknown and unexpected situations11,18 Societies with high uncertainty avoidance tend to be more resistant to change and therefore, paradoxically, more risk-tolerant.11 Typically, this characteristics is more common in countries with high degree of bureaucracy.11 For instance, Southern and Eastern European countries display greater uncertainty avoidance, whereas Northern European countries tend to rank lower in this attribute. 18 Past research has highlighted a negative relationship between uncertainty avoidance with both prosocial behaviour (e.g., volunteerism) and rapport building with patients.19–21 Therefore, higher degrees of individualism and uncertainty avoidance could lead to weaker social responses and attention given to vulnerable groups; two factors that can worsen a health crisis.
Moreover, other potentially important cultural factors identified in the current analysis were long-term orientation and power distance, which displayed significantly higher case fatality and mortality risk respectively. Typically, East Asian and European nations tend towards long-term orientation, whereas African countries, Islamic nations, South American nations, and Anglo-American democracies tend towards short-term orientation.22,23 In general, societies with long-term normative orientation tend to be more adaptive, less ideological, and future-focused, whereas those with short-term orientation tend to focus on past and present, respect tradition, norms and social obligations.18,23 A greater focus on the present may therefore lead to stricter immediate emergency measures, which may play a role in more quickly reacting to a crisis in nations with short-term orientation. In terms of power distance, this index measures the level of hierarchy within a society and is an indicator of the extent of deference given by less powerful members in society towards authority figures such as governmental officers.2218 However, societies that rank higher on the power distance index also tend to have greater centralisation of decision-making, lower accountability, as well as a large degree of income inequity.18 High power distance societies tend to therefore have less inclusive and participative decision-making bureaucratic procedures.24 Typically, Eastern European and Asian nations rank higher on the power distance index, while Western nations rank lower.22 In societies with lower degree of power distance, a decentralisation of power may enable more efficient decision-making during a crisis.
In summary, this study makes important contributions to the current scholarship by: 1) examining data from the initial phase of the pandemic, prior to initiation of broader deconfinement; 2) focusing on a collection of countries with important outbreaks during this period, representing an overwhelming majority (~82%) of reported infections world-wide; 3) exploring the variability in COVID–19 fatalities across nations taking into account important demographic, social, economic, and cultural factors; 4) evaluating the robustness of findings and sensitivity to country selection and 5) lastly, this is the first study to our knowledge to show the extent to which culture attributes can impact key health outcomes during the COVID–19 pandemic. The results suggest that in such public health crises (i.e., with limited therapeutic options), baseline cultural and behavioural factors may play an important role in influencing outcomes.12
However, the study also has limitations. The first limitation pertains to the accuracy of the estimated outcomes. The purpose of this study is not to generate a precise estimate of the CFR or mortality rate, which has been previously attempted by others using a variety of statistical approaches.25–28 Rather, the intent is to explore the observed variation in fatalities. Therefore, we only estimate the crude CFR. With this metric, the denominator includes unresolved (or, active) cases resulting in a time-lag bias that likely underestimates the true CFR, particularly in the earlier instances of the outbreak. Nonetheless, the estimated CFRs in this study are more likely to be an overestimate owing to the relatively greater influence of ascertainment bias (i.e., the under-detection of mild and asymptomatic cases resulting from undertesting). Indeed, we find that crude CFR is significantly lower with greater testing coverage of the population, suggesting that expanded testing should reduce CFR estimates by identifying more mild infections. Further, a higher testing coverage could also reflect a better capacity for contact tracing and isolation, which may reduce onward transmission particularly among high-risk groups. A second limitation is related to residual variability resulting from the inconsistency in recording COVID–19- attributable deaths across nations. Further, we have also not evaluated the potential impact of divergent medical management practices; however, as no known effective treatment or vaccine for SARS-CoV–2 is available during this period demographic factors, comorbidities and health system resource capacity are the behavioural responsiveness of societies are more plausible explanations for the variability in deaths at the current time. Finally, the study tends to focus on high- and middle-income nations given the larger epidemic size and data availability in these settings at this time, making it difficult to generalize findings to low-income settings.