Pandemics, while devastating for populations at large, deliver a disproportionate impact when they sweep through the dense informal settlements of developing countries with their narrow alleyways and broken dwellings. Death rates, high everywhere, soared through such places during the COVID-19 crisis.
Until recently, however, no research had been conducted on the role of informal settlements in shaping the economic and health dynamics of pandemics.
A Look at COVID in Brazil’s Informal Settlements
A group of colleagues and I decided to study the effect of COVID and the potential effect of efforts to combat it on the large informal settlements of Rio de Janeiro and São Paulo, where 22% and 11% of the cities’ inhabitants live. Using geo-localized data from millions of mobile phones to track population movements, we found that after the imposition of nonpharmaceutical interventions to contain the pandemic, like lockdowns and the closing of schools, restaurants and retail shops, it was harder for people in the informal settlements to stay at home and refrain from social distancing.
Income in the informal settlements of those cities is about a third of that in other neighborhoods, and their impoverished population can’t afford to be too cautious when deciding whether to work or not, even if it means working in crowded public places. The price they paid during COVID, however, in infections and deaths was high. Using an economic model we developed, we found that people living in informal settlements representing 22% of Rio’s population suffered 30% of its fatalities and made a disproportionate sacrifice towards achieving herd immunity. In a world without informal settlements, people living outside them would suffer higher rates of infection and death than they did.
Weighing Different Policy Options
We also used our economic model to consider different pandemic policy options, including those related to health insurance and access. Virtually nobody in informal settlements—and a minority of people outside them—has private health insurance. As a result, private hospitals have excess capacity and public hospitals lack capacity. What would happen, however, if we pooled all intensive care units in Rio and offered them to all people who needed one, essentially replicating the experience of universal health care? During the COVID pandemic all population groups would have won: the total death rate from the disease would have fallen by 28% relative to a scenario with no policy.
Shelter-at-home policies, we found, delay the dynamics of the disease, buying time, but hardly change overall death rates if vaccines or new treatments are not introduced quickly. Lighter lockdowns, in this regard, work better. They slow rates of infection, easing the burden on hospital resources and saving lives. But strict lockdowns generate deep economic downturns in the short run and are ineffective from a health perspective over longer periods. They contain the disease so much that when lifted, the health dynamics are similar to a no policy scenario. The unthinkable policy of locking down one particular group, rather than the other, would actually cause the welfare of both groups to fall, as deaths would shift from the sheltered group to the other, while harming people from the sheltered group with restrictions in their ability to move about and go about their lives.
By a similar logic, cash transfers to the poor could save lives. They would allow people living in informal settlements a kind of light lockdown, in which they could potentially afford to be more cautious, work fewer days, and suffer fewer infections—proof of the efficacy of a policy option crucial to balancing the impacts of a disease outbreak among different economic groups.
The Long-Term Threat of Pandemics
There are currently more than a billion people living in informal settlements across cities worldwide, with more than 110 million—one in five—living in the informal settlements of Latin America and the Caribbean. These are densely packed, overcrowded places—in Rio and São Paulo, population density in informal settlements is five times that of other neighborhoods—where tight spaces and poverty can make social distancing measures hard to effectively realize. Several epidemics have emerged over the last 20 years (Ebola and three lethal coronaviruses). The understanding of policy options to deal with such epidemics is crucial, both for the poor in informal settlements and for the wider population. Economic models, such as ours, which help us simulate different policy options where real world data is lacking, are essential tools in this quest, allowing us to understand the efficacy of different policies and do better the next time a pandemic hits.
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