Yidan Meng1, Vincent Zhu1, Yong Zhu2. 1. Department of Environmental Health Sciences, Yale University School of Public Health, New Haven, CT, 06520, USA. 2. Department of Environmental Health Sciences, Yale University School of Public Health, New Haven, CT, 06520, USA. yong.zhu@yale.edu.
Abstract
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.
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-19infections 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-19infection 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-19infections.
Authors: Jason R Anderson; Ian Carroll; M Andrea Azcarate-Peril; Amber D Rochette; Leslie J Heinberg; Christine Peat; Kristine Steffen; Lisa M Manderino; James Mitchell; John Gunstad Journal: Sleep Med Date: 2017-08-02 Impact factor: 3.492
Authors: Flavia Rodrigues da Silva; Renato de Carvalho Guerreiro; Henrique de Araújo Andrade; Eduardo Stieler; Andressa Silva; Marco Túlio de Mello Journal: Chronobiol Int Date: 2020-05-20 Impact factor: 2.877
Authors: Richard G Stevens; David E Blask; George C Brainard; Johnni Hansen; Steven W Lockley; Ignacio Provencio; Mark S Rea; Leslie Reinlib Journal: Environ Health Perspect Date: 2007-09 Impact factor: 9.031