Selected article for: "space time spread and urban area"

Author: Leveau, Carlos Marcelo
Title: Difusión espacio-temporal de muertes por COVID-19 en Argentina
  • Cord-id: 7po23ojc
  • Document date: 2021_3_24
  • ID: 7po23ojc
    Snippet: OBJECTIVES. Describe the space-time spread of COVID-19 deaths and analyze its socio-spatial inequalities in Argentina. METHODS. COVID-19 deaths in Argentina as of October 17, 2020 were analyzed using data onday, month, and year, and place of residence. The space-time permutation scan method was used to detect the presence of space-time clusters. Poverty levels, population densities, and percentage of older adults in the population were compared for areas in high-mortality clusters and low-mortal
    Document: OBJECTIVES. Describe the space-time spread of COVID-19 deaths and analyze its socio-spatial inequalities in Argentina. METHODS. COVID-19 deaths in Argentina as of October 17, 2020 were analyzed using data onday, month, and year, and place of residence. The space-time permutation scan method was used to detect the presence of space-time clusters. Poverty levels, population densities, and percentage of older adults in the population were compared for areas in high-mortality clusters and low-mortality clusters. RESULTS. Five high-mortality clusters were detected between March 21 and August 27 in the Greater Buenos Aires conurbation and the northeast of the province of Buenos Aires. Low-mortality clusters were located on the periphery of the urban area from mid-September to mid-October and in central and northwestern Argentina between late April and late August. High-mortality clusters were located in areas with higher population densities and higher percentages of older adults in population, comparedto low-mortality clusters. CONCLUSIONS. No high-mortality clusters were detected between September and mid-October. Norhave we detected a spatial spread of deaths to areas of low socioeconomic status at the national level. Our results support the first phase of the mortality spread model, affecting the largest urban area in Argentina.

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