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Contagion by COVID-19 in the Cities: Commuting distance and Residential Density matter?

Author

Listed:
  • Denis Fernandes Alves
  • Raul da Mota Silveira
  • Andre Luis Squarize Chagas
  • Tatiane Almeida de Menezes
Abstract
[This study addresses COVID-19 infection and its relationship with the city's constructive intensity, commuting time to work, and labor market dynamics during the lockdown period. Microdata from formal workers in the city of Recife are used, adjusting a probability model for disease contraction. We identified positive and significant relationships between these urban characteristics and increased contagion, controlling for various factors such as neighborhood, individual characteristics, comorbidities, occupations, and economic activities. Our results indicate that greater distance to employment increases the probability of infection. The same applies to constructive intensity, suggesting that residences in denser areas, such as apartments in buildings, condominiums, and informal settlements, elevate the chances of contracting the disease. It is also observed that formal workers with completed higher education have lower infection risks, while healthcare professionals on the frontline of combating the disease face higher risks. Overall, the lockdown was effective in reducing contagion by limiting people's mobility during the specified period.]

Suggested Citation

  • Denis Fernandes Alves & Raul da Mota Silveira & Andre Luis Squarize Chagas & Tatiane Almeida de Menezes, 2024. "Contagion by COVID-19 in the Cities: Commuting distance and Residential Density matter?," Working Papers, Department of Economics 2024_07, University of São Paulo (FEA-USP).
  • Handle: RePEc:spa:wpaper:2024wpecon07
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    References listed on IDEAS

    as
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    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    Commuting; floor-area-ratio (FAR); lockdown; COVID-19; Recife;
    All these keywords.

    JEL classification:

    • C38 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Classification Methdos; Cluster Analysis; Principal Components; Factor Analysis
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • R11 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Regional Economic Activity: Growth, Development, Environmental Issues, and Changes
    • R12 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Size and Spatial Distributions of Regional Economic Activity; Interregional Trade (economic geography)

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