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Human mobility and weather changes in São Paulo correlate with COVID-19 infection spikes. Reduced recreation and transit, plus increased temperature, preceded new cases by 17 days, highlighting the impact of emergency decrees.

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Area of Science:

  • Epidemiology
  • Environmental Science
  • Data Science

Background:

  • The COVID-19 pandemic's spread is influenced by various factors, including human behavior and environmental conditions.
  • Understanding these relationships is crucial for effective public health interventions.

Purpose of the Study:

  • To analyze the temporal relationship between human mobility, meteorological variables, and COVID-19 infections in São Paulo, Brazil.
  • To identify lead times for these correlations using a novel statistical method.

Main Methods:

  • Utilized distance correlation (DC) to detect nonlinear correlations between time series data.
  • Analyzed human mobility data (recreation, transit, grocery, parks) and meteorological data (temperature, pressure).
  • Examined data from February 26, 2020, to June 28, 2020.

Main Results:

  • Decreased mobility in recreation and transit, along with increased maximal temperature, correlated with new COVID-19 cases after a 17-day lag.
  • Changes in grocery/pharmacy and park mobility, and sudden shifts in maximal pressure, correlated with disease onset 10-11 days prior.
  • Human mobility changes impacted infection rates for up to 19 days.

Conclusions:

  • Human mobility and meteorological factors significantly influence COVID-19 transmission dynamics in São Paulo.
  • The study highlights the importance of public health policies, such as emergency decrees, in mitigating disease spread.