Slums and Pandemics

Brotherhood, Luiz; Cavalcanti, Tiago; Mata, Daniel Da; Santos, Cezar

doi:10.2139/ssrn.3665695

Cited by 21 publications

(20 citation statements)

References 31 publications

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“…We find this to be one of the strongest correlates of the COVID-19 deaths' age-share difference. Researchers have suggested that the virus may spread faster in the developing world because of the higher prevalence of large, often multi-family, multi-generational households living together in cramped conditions (Brotherhood et al, 2020a). Our results suggest that this is also related to larger shares of non-elderly individuals in COVID-19 deaths.…”

Section: Socioeconomic and Housing Conditionsmentioning

confidence: 55%

“…Another dimension of housing conditions that we also find to be connected with the age-share difference in COVID-19 deaths is the presence of slums. Brotherhood et al (2020a) model COVID-19 dynamics in alternative scenarios, with and without favelas, and find that overall mortality increases with the presence of these informal neighborhoods. First, we find a positive correlation in the main model between the age-shares difference in COVID-19 deaths and the share of the local population that lives in favelas.…”

Section: Socioeconomic and Housing Conditionsmentioning

confidence: 99%

“…Second, we contribute to the broader literature on the different impacts of the COVID-19 pandemic between countries of different income levels. Prior research has argued that the health and economic effects of COVID-19 are likely to be more severe in lower-income countries for a wide variety of reasons, including: higher labor informality rates (Alfaro et al, 2020;Busso et al, 2020); higher reliance on daily income for basic subsistence (Alon et al, 2020;Hausmann and Schetter, 2020); and worse housing conditions (Brotherhood et al, 2020a;. At the same time, researchers have suggested that social distancing policies may be less cost-effective in poorer countries, partly because their younger populations imply fewer COVID-19 deaths (Alon et al, 2020;Barnett-Howell and Mobarak, 2020;Walker et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

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The Younger Age Profile of COVID-19 Deaths in Developing Countries

Chauvin¹,

Fowler²,

Herrera³

2020

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This paper examines why a larger share of COVID-19 deaths occurs among young and middle-aged adults in developing countries than in high-income countries. Using novel data at the country, city, and patient levels, we investigate the drivers of this gap in terms of the key components of the standard Susceptible-Infected-Recovered framework. We obtain three main results. First, we show that the COVID-19 mortality age gap is not explained by younger susceptible populations in developing countries. Second, we provide indirect evidence that higher infection rates play a role, showing that variables linked to faster COVID-19 spread such as residential crowding and labor informality are correlated with younger mortality age profiles across cities. Third, we show that lower recovery rates in developing countries account for nearly all of the higher death shares among young adults, and for almost half of the higher death shares among middle-aged adults. Our evidence suggests that lower recovery rates in developing countries are driven by a higher prevalence of preexisting conditions that have been linked to more severe COVID-19 complications, and by more limited access to hospitals and intensive care units in some countries.

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Section: Socioeconomic and Housing Conditionsmentioning

confidence: 55%

Section: Socioeconomic and Housing Conditionsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

The Younger Age Profile of COVID-19 Deaths in Developing Countries

Chauvin¹,

Fowler²,

Herrera³

2020

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“…In India, for example, the susceptibility appears to be smaller in slums. [20, 21] If indeed true, one could explain invoking immunity, but the origin is not clear.…”

Section: Theoretical Formulation: Distribution Based Modelmentioning

confidence: 99%

Persistence of a pandemic in the presence of susceptibility and infectivity distributions in a population: Mathematical model

Mukherjee

Mondal

Bagchi

2021

Preprint

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The birth and death of a pandemic can be region specific. Pandemic seems to make repeated appearance in some places which is often attributed to human neglect and seasonal change. However, difference could arise from different distributions of inherent susceptibility (σinh) and external infectivity (ιext) from one population to another. These are often ignored in the theoretical treatments of an infectious disease progression. While the former is determined by the immunity of an individual towards a disease, the latter depends on the duration of exposure to the infection. Here we model the spatio-temporal propagation of a pandemic using a generalized SIR (Susceptible-Infected-Removed) model by introducing the susceptibility and infectivity distributions to comprehend their combined effects. These aspects have remained inadequately addressed till date. We consider the coupling between σinh and ιext through a new critical infection parameter (γc). We find that the neglect of these distributions, as in the naive SIR model, results in an overestimation in the estimate of the herd immunity threshold. That is, the presence of the distributions could dramatically reduce the rate of spread. Additionally, we include the effects of long-range migration by seeding new infections in a region. We solve the resulting master equations by performing Kinetic Monte Carlo Cellular Automata (KMC-CA) simulations. Importantly, our simulations can reproduce the multiple infection peak scenario of a pandemic. The latent interactions between disease migration and the distributions of susceptibility and infectivity can render the progression a character vastly different from the naive SIR model. In particular, inclusion of these additional features renders the problem a character of a living percolating system where the disease cluster can survive by spatial migration.

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“…Individuals living in informal settlements (often called “slums”) are in a structurally disadvantaged position to cope with a health crisis such as the COVID-19 pandemic [19-23]. Around one billion people live in an informal settlement in the global south, a number that has massively increased in the past decades [24-26].…”

Section: Introductionmentioning

confidence: 99%

The Socioeconomic Impact of COVID-19 in Urban Informal Settlements

Gil

Domínguez

Undurraga

et al. 2021

Preprint

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The COVID-19 pandemic has reached almost every corner of the world. Without a pharmaceutical solution, governments have been forced to implement regulations and public policies to control social behavior and prevent the spread of the virus. There is dramatic evidence of the social and economic effects of these measures and their disparate impact on vulnerable communities. Individuals living in urban informal settlements are in a structurally disadvantaged position to cope with a health crisis such as the COVID-19 pandemic. This paper examines the socioeconomic impact of the crisis brought by the pandemic in informal settlements in Chile. We use a three-wave panel study to compare the situation in informal settlements before and during the health crisis. We show that households living in informal settlements are paying a high toll. Their employment loss is dramatic, substantially larger than the loss reported in the general population, and has particularly affected the inmigrant population. We also find that the pandemic has triggered neighborhood cooperation within the settlements. Targeted government assistance programs have reached these communities; however, this group’s coverage is not enough to counteract the magnitude of the crisis. Our results suggest that governments, the non-profit sector, and the community need to urgently provide economic support and protections to individuals living in informal settlements and consider this opportunity for long-term improvements in these marginalized communities.HighlightsGovernments have implemented large-scale non-pharmaceutical interventions to control the spread of the COVID-19 pandemicThese measures have had dramatic social and economic effects on the population, particularly affecting vulnerable communitiesIndividuals living in urban informal settlements are in a structurally disadvantaged position to cope with this crisisUsing panel data, we document a dramatic employment loss among informal settlements dwellers, substantially larger than the general populationThe pandemic has also triggered neighborhood cooperation within the settlements as well as targeted government assistance, but not enough to counteract the magnitude of the economic loss

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Slums and Pandemics

Cited by 21 publications

References 31 publications

The Younger Age Profile of COVID-19 Deaths in Developing Countries

The Younger Age Profile of COVID-19 Deaths in Developing Countries

Persistence of a pandemic in the presence of susceptibility and infectivity distributions in a population: Mathematical model

The Socioeconomic Impact of COVID-19 in Urban Informal Settlements

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