The introduction of lockdown policies to contain the transmission of Covid-19 led to a debate on what type of lockdowns were warranted, and whether the benefits justified the accompanying economic contractions. In this context, this article seeks to quantify the intergenerational mortality trade-off in pandemic mitigation in low- and middle-income countries, as the disease and lockdown policies affect the mortality of younger and older people differently.

At the start of the Covid-19 pandemic, governments across the world introduced unprecedented lockdown policies to contain disease transmission. Lockdown severity was remarkably similar across countries at different levels of development. On a scale of 0 to 100, the mean (average) Oxford–Blavatnik lockdown stringency index in April 2020 was 79 in low-income countries, and 78 in high-income countries. 

A debate soon erupted on what type of lockdowns were warranted, and whether the benefits of such policies justified the accompanying dramatic economic contractions. In a recent study (Ma et al. 2021), we cast new light on this debate by focussing on an intergenerational mortality trade-off that we argue is inherent in pandemic mitigation, as the disease and the lockdown policies affect the mortality of younger and older people differently. 

In the early days of the pandemic, evidence emerged that Covid-19 mortality risk increases substantially with age (Verity et al. 2020). On the other hand, previous research has shown that infant and child mortality in low- and middle-income countries is higher during economic contractions (Baird et al. 2011). Thus, in developing countries, a lockdown would be expected to primarily save the lives of older adults, perhaps at the cost of higher child mortality due to severe reductions in aggregate economic activity (if shocks to household income were not compensated by other assistance). 

To formalise and quantify this trade-off, our analysis relies on a ‘macro-susceptible-infected-recovered’¹ disease transmission model that features agents whose behaviours vary by age group, and a country-group-specific relationship between economic downturns and child mortality. 

Low-, middle-, and high-income countries differ along several relevant dimensions. First, economic contractions raise child mortality in poorer countries, but not in rich ones. We estimate that a 1% decrease in per capita GDP (gross domestic product) can increase under-five mortality by up to 0.15 deaths per 1,000 children in low-income countries. Second, the demographic composition of poorer countries features a larger ratio of young children to old people. Since survival rates of the former may be diminished by an economic downturn, while the latter are most vulnerable to dying from Covid-19, a lockdown in lower income countries could lead to more recession-induced deaths per Covid-19 fatality averted, other things equal. Third, the preponderance of community-related transmission in low-income countries, as opposed to work or market-place transmission, might render government-mandated lockdowns comparatively less effective at reducing the spread of infections. Finally, low healthcare capacity in poorer countries lowers the benefits from ‘flattening the curve’ with lockdowns, as hospitals are quickly overwhelmed since the average number of hospital beds per capita in high-income countries is seven times higher than in low-income countries. 

Our model is calibrated to data for 85 countries across all income levels. We then simulate economic and disease-related outcomes in two scenarios: one with no government intervention, and one in which a uniform seven-week lockdown is implemented in all countries. The simulations suggest that relative to the no-intervention scenario, the uniform lockdown could, under certain circumstances, lead to 1.76 children’s lives lost due to the economic contraction per Covid-19 fatality averted in low-income countries. That is, lockdowns could, under certain circumstances, actually increase the overall (Covid-19 plus non-Covid-19) mortality for the lowest income countries. The ratio stands at 0.59 and 0.06 in lower-middle-income and upper-middle-income countries, respectively. The specific lockdown used in the simulations was chosen to mimic policies adopted during the early months of the pandemic but is not designed to capture all the complexities of mobility and social gathering restrictions imposed by countries. Rather, the simulations aim at highlighting the large heterogeneity in outcomes, following a uniform policy. The fundamental mortality trade-off across the different ages would apply also to different types of lockdowns. 

Our analysis relies on the epidemiological information that was available in March-April 2020 when the first lockdown decisions were taken. As such, it ignores the introduction of vaccines – unfortunately still not yet sufficiently available in several low-income countries – as well as the emergence of newer, likely more infectious variants (Davies et al. 2021), which confers a global public good quality to domestic mitigation policies. 

Our analysis highlights and quantifies a trade-off between human lives, namely children versus adults. The results are consistent with work documenting falling living standards and food insecurity in developing countries in the past year as a partial consequence of lockdown policies (Egger et al. 2021, Drèze and Somanchi 2021). 

It is important to stress that our analysis does not imply that lockdown policies should not be implemented in low-income countries. Rather, it highlights how the trade-offs differ for countries of different income levels. We find that lockdowns would still be needed, but those that would take the aforementioned trade-offs into account naturally tend to be shorter and milder in low-income countries. 

Finally, to mitigate some of the worst potential outcomes – the negative impacts on child mortality and household poverty of lockdown policies necessary to protect older individuals – could be attenuated or mitigated using targetted social assistance, such as cash transfers towards poor households, and families with young children and pregnant women. 

A version of this article was originally published on the World Bank’s Lets Talk Development Blog. 

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Note:

1. This is a combination of an economic model of labour and income, with an epidemiological model of infection and recovery, or death. 

Further Reading

• Baird, Saira, Jed Friedman and Norbert Schady (2011), “Aggregate income shocks and infant mortality in the developing world”, The Review of Economics and Statistics, 93(3): 847-856. Available here.
• Davies, Nicholas G et al. (2021), “Estimated transmissibility and impact of SARS-CoV-2 lineage B.1.1.7 in England”, Science, 372(6538).
• Drèze, J and A Somanchi (2021), ‘The Covid-19 crisis and food security’, Ideas for India, 21 June.
• Egger, Dennis et al. (2021), “Falling living standards during the COVID-19 crisis: Quantitative evidence from nine developing countries”, Science Advances, 7(6).
• Ma, L, G Shapira, D de Walque, Q Do, J Friedman and A Levchenko (2021), ‘The Intergenerational Mortality Tradeoff of COVID-19 Lockdown Policies’, World Bank Policy Research Working Paper No. 9677.
• Verity, Robert et al. (2020), “Estimates of the severity of coronavirus disease 2019: a model-based analysis”, The Lancet, 20(6): 669-677.