Indirect and direct effects of nighttime light on COVID-19 mortality using satellite image mapping approach

Sci Rep. 2024 Oct 23;14(1):25063. doi: 10.1038/s41598-024-75484-0.

Abstract

The COVID-19 pandemic has highlighted the importance of understanding environmental factors in disease transmission. This study aims to explore the spatial association between nighttime light (NTL) from satellite imagery and COVID-19 mortality. It particularly examines how NTL serves as a pragmatic proxy to estimate human interaction in illuminated nocturnal area, thereby impacting viral transmission dynamics to neighboring areas, which is defined as spillover effect. Analyzing 43,199 COVID-19 deaths from national mortality data during January 2020 and October 2022, satellite-derived NTL data, and various environmental and socio-demographic covariates, we employed the Spatial Durbin Error Model to estimate the direct and indirect effect of NTL on COVID-19 mortality. Higher NTL was initially directly linked to increased COVID-19 mortality but this association diminished over time. The spillover effect also changed: during the early 3rd wave (December 2020 - February 2021), a unit (nanoWatts/sr/cm2) increase in NTL led to a 7.9% increase in neighboring area mortality (p = 0.013). In contrast, in the later 7th wave (July - September 2022), dominated by Omicron, a unit increase in NTL resulted in an 8.9% decrease in mortality in neighboring areas (p = 0.029). The shift from a positive to a negative spillover effect indicates a change in infection dynamics during the pandemic. The study provided a novel approach to assess nighttime human activity and its influence on disease transmission, offering insights for public health strategies utilizing satellite imagery, particularly when direct data collection is impractical while the collection from space is readily available.

Keywords: COVID-19; Mortality; Nighttime light; Satellite imagery; Spillover effect.

MeSH terms

  • COVID-19* / mortality
  • COVID-19* / transmission
  • Humans
  • Light
  • Pandemics
  • SARS-CoV-2*
  • Satellite Imagery*