Slums and pandemics

Firm behavior during an epidemic

We derive a model in which firms operate in an epidemic environment and internalize infections among their employees in the workplace. The model is calibrated to fit the moments of the Covid-19 epidemic. We show that firms have incentives to fight against infections and can do so very effectively by increasing teleworking and rotating employees between on-site work, teleworking, and leave. The fight against infections in firms flattens the aggregate infections curve. Subsidies to teleworking reduce infections and save lives. Subsidies to sick leave reduce the cost of sick workers and raise workplace infections. Firms delay and weaken the fight against infections during economic downturns. We also consider the problem of a government that values output and lives. We show that the government prefers to severely restrict the epidemic by tolerating short-term output losses when it has a high valuation of life.

Maré cohort-profile: a prospective cohort study based in a socially vulnerable community during the COVID-19 pandemic in Rio de Janeiro, Brazil

Background: Socially vulnerable populations were vastly affected by the COVID-19 pandemic. The pandemic significantly impacted Brazil, pressuring its healthcare system for several months, with high mortality rates, even among the youngest population. Cohort studies combining disease surveillance are essential for understanding virus circulation in the community, surrogates of protection, vaccine effectiveness, and demand for health resources. Methods: Here, we present the protocol for a community-based prospective cohort study in the largest complex of favelas (slums) in Rio de Janeiro, Brazil (Complexo da Maré). The study participants are residents initially recruited during a massive vaccination campaign in the community. Five waves of data collection at approximately six-month intervals were planned. The first two waves have been completed at the time of writing this study protocol, and the third is underway. The protocol comprises interviews, blood sampling, and records linkage with secondary data to enrich the profiles of cohort participants and community information. We will describe COVID-19 seroprevalence, socio-demographic characteristics, and the burden of COVID-19, followed by estimating the association of socioeconomic factors and the burden of disease with seroprevalence. Discussion: The primary aims of the study are to assess COVID-19 clinical, epidemiological and genomic profiles and outcomes in residents from Maré, including vaccine effectiveness, surrogates of immune protection, virus transmission in households, and the overall burden of the pandemic.

COVID-19 and the city: Did urbanized countries suffer more fatalities?

In this paper we derive a theoretical model of the spread of a viral infection which we use as basis for an estimation strategy to test four interrelated hypotheses on the relationship between country-level COVID-19 mortality rates and the extent of urban development. Using data covering 81 countries we find evidence that countries with a higher population density, a higher share of the urban population living in the largest city, and countries with a higher urbanization rate had on average the same or fewer COVID-19 fatalities compared to less urbanized countries in 2020. Even though COVID-19 spreads faster in cities, fatalities may be lower, conditional on economic development, trust in government, and a well-functioning health care system. Generally, urbanization and city development are associated with economic development: with the resources urbanized countries have, it is easier for them to manage and maintain stricter lockdowns, and to roll out effective pharmaceutical interventions.

Urban density and COVID-19: understanding the US experience

This paper revisits the debate around the link between population density and the severity of COVID-19 spread in the USA. We do so by conducting an empirical analysis based on graphical evidence, regression analysis and instrumental variable strategies borrowed from the agglomeration literature. Studying the period between the start of the epidemic and the beginning of the vaccination campaign at the end of 2020, we find that the cross-sectional relationship between density and COVID-19 deaths changed as the year evolved. Initially, denser counties experienced more COVID-19 deaths. Yet, by December, the relationship between COVID deaths and urban density was completely flat. This is consistent with evidence indicating density affected the timing of the outbreak-with denser locations more likely to have an early outbreak-yet had no influence on time-adjusted COVID-19 cases and deaths. Using data from Google, Facebook, the US Census and other sources, we investigate potential mechanisms behind these findings.

THE DISTRIBUTIONAL EFFECTS OF COVID-19 AND OPTIMAL MITIGATION POLICIES

This paper develops a quantitative heterogeneous agent-life cycle-epidemiological model that is used to study the aggregate and distributional consequences of COVID-19 and mitigation policies. First, a stay-at-home subsidy is preferred to a lockdown because it reduces deaths by more and output by less. Second, Pareto-improving policies can reduce deaths by nearly 45 percent without any reduction in output relative to no public mitigation. Finally, it is possible to simultaneously improve public health and economic outcomes, suggesting that debates regarding a tradeoff between economic and health objectives may be misguided. This article is protected by copyright. All rights reserved.

Comment on "COVID-19 in segmented societies" by Constantino Hevia, Manuel Macera, and Pablo Andrés Neumeyer

This comment briefly summarizes Hevia et al. (2022), who utilize a unique dataset to shed light on the inequality of the epidemiological burden for low- and high-income individuals in Bogotá. Some suggestions and ideas for future research are provided.