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Sunlight and Protection Against Influenza

Slusky et al., Economics & Human Biology, doi:10.1016/j.ehb.2020.100942
Jan 2021  
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Sunlight for COVID-19
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Retrospective study using CDC data on 12,068 state-weeks showing that increased sunlight exposure is associated with reduced influenza rates during peak fall flu season. A 10% increase in relative sunlight exposure decreases the CDC influenza index by 1.1 points out of 10 in September-October. This relationship was driven mostly by the 2009 H1N1 epidemic.
Slusky et al., 31 Jan 2021, peer-reviewed, 2 authors. Contact: david.slusky@ku.edu, richard_zeckhauser@harvard.edu.
This PaperSunlightAll
Sunlight and Protection Against Influenza
David J G Slusky, Richard J Zeckhauser, G Slusky
doi:10.1016/j.ehb.2020.100942</ForCover>->
Medical literature suggests vitamin D protects against respiratory infections • Humans exposed to sunlight produce vitamin D directly • A 10% increase in relative sunlight decreases fall influenza by 1.1 out of 10 • This relationship is driven by almost entirely by the H1N1 epidemic in fall 2009 Abstract Recent medical literature suggests that vitamin D supplementation protects against acute respiratory tract infection. Humans exposed to sunlight produce vitamin D directly. This paper investigates how differences in sunlight, as measured over several years across states and during the same calendar week, affect influenza incidence. We find that sunlight strongly protects against getting influenza. This relationship is driven almost entirely by the severe H1N1 epidemic in fall 2009. A 10% increase in relative sunlight decreases the influenza index in September or October by 1.1 points on a 10-point scale. A second, complementary study employs a separate data set to study flu incidence in counties in New York State. The results are strongly in accord.
Appendix Table B2 considers the typical peak flu months of October to March for the less sunny and more sunny states. While the point estimates are comparable for the two groups, the effect is highly statistically significant (p = 0.003) for the less sunny states and not statistically significant (p = 0.136) for the more sunny states. Appendix Table B4 then expands on Table 3 by stratifying the month-to-month analysis by the same low and high sunniness categories of Appendix Table B2 . While a few coefficients are statistically significant at the 10% level, the only strongly significant coefficient is October for the low sunniness states. However, when pooling September and October, both sets of states have coefficients statistically significant at the 1% level, though the one for the more sunny states is smaller in magnitude. J o u r n a l P r e -p r o o f repeats the Table 2 analyses, but includes an unbalanced panel of all contiguous states, Hawaii, and D.C. (i.e., even those with missing influenza data in some weeks). That table shows a comparable result. It also employs both linear and quadratic specifications. All three specifications find strongly statistically significant results, though obviously at different coefficient magnitudes. Appendix Table C2 drops each of the 28 states in the primary specification, one at a time, to test whether the main result persists if any one state is excluded. The answer is yes. Appendix Table C3 performs the analysis for..
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