The intergenerational mortality tradeoff of COVID-19 lockdown policies in low- and middle-income countries

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 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 paper, we cast new light on this debate by focusing on an intergenerational mortality tradeoff 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. On the other hand, previous research has shown that infant and child mortality in low- and middle-income countries is higher during economic contractions. Thus, in developing countries a lockdown would be expected to save the lives primarily 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 formalize and quantify this tradeoff, our analysis relies on a macro-susceptible-infected-recovered disease transmission model that features agents whose behaviors 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 percent decrease in per capita GDP can increase under-5 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 health care 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 low-income countries – as well as the emergence of newer likely more infectious variants, which confers a global public good quality to domestic mitigation policies.

Our paper highlights and quantifies a tradeoff between human lives, namely children vs. 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.

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 tradeoffs differ for countries of different income levels. We find that lockdowns would still be needed, but those that would take the aforementioned tradeoffs 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 targeted social assistance, such as cash transfers, towards poor households and families with young children and pregnant women.

_Links:

_{https://www.bsg.ox.ac.uk/research/research-projects/covid-19-government-response-tracker
https://foreignpolicy.com/2020/04/10/poor-countries-social-distancing-coronavirus/
https://documents1.worldbank.org/curated/en/990621622121589737/pdf/The-Intergenerational-Mortality-Tradeoff-of-COVID-19-Lockdown-Policies.pdf
Estimates of the severity of coronavirus disease 2019: a model-based analysis - The Lancet Infectious Diseases
MIT_REST_110023 847..856 (worldbank.org)
https://advances.sciencemag.org/content/7/6/eabe0997?utm_source=TrendMD&utm_medium=cpc&utm_campaign=TrendMD_1
https://osf.io/preprints/socarxiv/ybrmg
https://science.sciencemag.org/content/372/6538/eabg3055.abstract}