Assessing the impact of human mobility to predict regional excess death in Ecuador

Sci Rep. 2022 Jan 10;12(1):370. doi: 10.1038/s41598-021-03926-0.

Abstract

COVID-19 outbreaks have had high mortality in low- and middle-income countries such as Ecuador. Human mobility is an important factor influencing the spread of diseases possibly leading to a high burden of disease at the country level. Drastic control measures, such as complete lockdown, are effective epidemic controls, yet in practice one hopes that a partial shutdown would suffice. It is an open problem to determine how much mobility can be allowed while controlling an outbreak. In this paper, we use statistical models to relate human mobility to the excess death in Ecuador while controlling for demographic factors. The mobility index provided by GRANDATA, based on mobile phone users, represents the change of number of out-of-home events with respect to a benchmark date (March 2nd, 2020). The study confirms the global trend that more men are dying than expected compared to women, and that people under 30 show less deaths than expected, particularly individuals younger than 20 with a death rate reduction between 22 and 27%. The weekly median mobility time series shows a sharp decrease in human mobility immediately after a national lockdown was declared on March 17, 2020 and a progressive increase towards the pre-lockdown level within two months. Relating median mobility to excess deaths shows a lag in its effect: first, a decrease in mobility in the previous two to three weeks decreases excess death and, more novel, we found an increase of mobility variability four weeks prior increases the number of excess deaths.

MeSH terms

  • Adult
  • Algorithms
  • COVID-19 / epidemiology
  • COVID-19 / mortality*
  • COVID-19 / virology
  • Cause of Death*
  • Communicable Disease Control / methods
  • Communicable Disease Control / statistics & numerical data*
  • Ecuador / epidemiology
  • Female
  • Geography
  • Humans
  • Male
  • Pandemics / prevention & control
  • Population Dynamics
  • Risk Factors
  • SARS-CoV-2 / physiology
  • Survival Rate
  • Time Factors
  • Transportation / statistics & numerical data*
  • Travel / statistics & numerical data*
  • Young Adult