4.6 Article

Co-distribution of Light At Night (LAN) and COVID-19 incidence in the United States

Journal

BMC PUBLIC HEALTH
Volume 21, Issue 1, Pages -

Publisher

BMC
DOI: 10.1186/s12889-021-11500-6

Keywords

Light at night (LAN); COVID-19

Funding

  1. Yale University

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The study found a significant positive correlation between LAN intensity and COVID-19 cases-rate/1 k in New York and Connecticut, suggesting that circadian disruption of ambient light may increase the COVID-19 infection rate by affecting an individual's immune functions. Additionally, differences in demographic structure and lockdown policies across states play a role in COVID-19 infections.
Background Light at night (LAN) as a circadian disruption factor may affect the human immune system and consequently increase an individual's susceptibility to the severity of infectious diseases, such as COVID-19. COVID-19 infections spread differently in each state in the United States (US). The current analysis aimed to test whether there is an association between LAN and COVID-19 cases in 4 selected US states: Connecticut, New York, California, and Texas. Methods We analyzed clustering patterns of COVID-19 cases in ArcMap and performed a multiple linear regression model using data of LAN and COVID-19 incidence with adjustment for confounding variables including population density, percent below poverty, and racial factors. Results Hotspots of LAN and COVID-19 cases are located in large cities or metro-centers for all 4 states. LAN intensity is associated with cases/1 k for overall and lockdown durations in New York and Connecticut (P < 0.001), but not in Texas and California. The overall case rates are significantly associated with LAN in New York (P < 0.001) and Connecticut (P < 0.001). Conclusions We observed a significant positive correlation between LAN intensity and COVID-19 cases-rate/1 k, suggesting that circadian disruption of ambient light may increase the COVID-19 infection rate possibly by affecting an individual's immune functions. Furthermore, differences in the demographic structure and lockdown policies in different states play an important role in COVID-19 infections.

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