It is tempting to think that we can learn lessons from how other countries have handled COVID-19, and from studying those outcomes. But, warn Linda Hantrais (LSE) and Susanne MacGregor (LSHTM), we should avoid drawing simplistic conclusions.
Just as underlying health conditions and socio-economic factors affect the likelihood of contracting and dying from COVID, underlying societal and political factors hampered the application of policy lessons. Countries at the epicentre of the first wave of the pandemic might have been expected to learn from their own experience, and to pass on lessons about successes and failures to other countries as the virus spread. But the capacity of governments to learn how to prevent or contain new waves was constrained by both endogenous and exogenous factors.
Populations do not all face the same risk of contracting or dying from COVID. Psychological, institutional, and strategic factors all play a role in how well a country’s government can contain the virus, prevent excess mortality and control future outbreaks. Countries do not adopt the same policy instruments, or achieve the same effects by applying them, thereby limiting the value of later attempts to identify causal explanations for the success or failure of policy responses.
Problems were amplified where there were entrenched political divisions, unstable, dysfunctional or populist governments and sceptical electorates. By contrast, as historians and political scientists predicted, governments did better in places with political stability and consensus, public trust in governments and in the scientific evidence on which they relied as a basis for policy choices, a strong sense of individual and social responsibility and respect for the rule of law. In their analysis of the handling of COVID in New Zealand, a country that is in many ways culturally closer to the UK than Singapore, South Korea or Vietnam, political scientists have attributed success in ‘curve crushing’ to anticipatory policymaking and point out the need for long-term planning rather than ‘reactive’ policymaking.
The odds were stacked more heavily against some governments than others
Contextual factors are key not only in determining why countries were deemed to be successful in dealing with the impact of the pandemic on social and economic life, but also in understanding whether successes could be replicated in other environments. Demographers and social policy analysts have found that the odds were stacked more heavily against some governments than others. Human overpopulation and teeming cities, for example, make it harder to control infections. Evidence accumulated in the early phase of the pandemic suggested that Western countries with densely populated, high urban concentrations and internationally connected populations, in conjunction with high old age dependency ratios and high rates of underlying health conditions (obesity, diabetes) would be more likely to record larger numbers of cases and COVID deaths. Other socio-demographic, economic and environmental factors included poorly funded and equipped public healthcare provision, and underdeveloped technological infrastructures. Ethnicity, crowded living conditions and precarious working arrangements were shown to compound the risk of contracting and dying from the virus once it became established in a population.
Recognising that ‘the nature of the policy responses around COVID-19 were not only unknown but also contested and highly uncertain’, a case was made for disentangling empirically verifiable natural dimensions of the pandemic from socially and psychologically constructed ones. Factors shaping policy responses could then be identified as ‘the nature of national leadership, the organisation of government and civil society, and blindspots towards the vulnerabilities of certain population segments’.
Work on previous pandemics demonstrated that policies would be needed to deal with the socio-economic inequalities that they exacerbate. In the context of COVID, while new technologies offered digital solutions for monitoring and tracking the disease, and for socio-economic groups able to access online schooling and home working, it intensified existing inequalities by starkly exposing whole swathes of populations deprived of such access. These inequities extended to inequalities in the distribution of vaccines and varying attitudes to vaccination, as well as the role played by misinformation, reflecting the importance of nurturing trust in both politicians and experts, and countering the harmful influence of social media by careful management and delivery of modern communication strategies.
Efficacious vaccines and the spread of new variants of the virus changed the dynamics of the pandemic in 2021. Gradually, valuations of scientific advice began to take account of the great socio-cultural diversity between and within countries, and of the multiple factors influencing the transmission, lethality, and impacts of COVID on social, economic and cultural life and attitudes towards vaccination. Governments face deep-seated dilemmas in assessing the costs and benefits of the policy options they adopt, and successful policy responses implemented in one jurisdiction could not always be readily transferred to another.
A wide-ranging analysis of contrasting outcomes in lower-income countries (India, Nigeria, sub-Saharan Africa) − known to have been hardest hit by infectious diseases such as malaria, typhoid, diphtheria, HIV − and high-income countries (US, Europe) that suffered far larger numbers of COVID deaths in 2020 gives the lie to much of the received wisdom. Siddhartha Mukherjee suggests that various combinations of dynamic factors must be at work. The predictive value of age, family living arrangements, public health policy responses, and public compliance could not explain major discrepancies in the impact of the pandemic at different stages in its development. He acknowledges that under-reporting was a serious problem in some of the lower income countries, but more important was the indirect effect of the virus on death rates due to disruptions to medical care and prevention programmes. Other factors were the need for a greater understanding of the immunological and socio-ecological profiles in populations, and the role played by strong leadership.
These factors are important in understanding variations not only in the public health impacts of the pandemic but also in state responses to COVID, and in assessing whether some countries had learnt more than others from their experiences, and whether they applied this knowledge. The policy learning process is complex and we should avoid explanations that attribute it to simple causal relationships.
This post represents the views of the author and not those of the COVID-19 blog, nor LSE.