Environmental factors and mobility predict seasonality of COVID-19 in the Netherlands


This article was originally published here

Approx Res. March 4, 2022: 113030. doi: 10.1016/j.envres.2022.113030. Online ahead of print.


BACKGROUND: We have recently shown that the seasonal trends in the incidence of COVID-19 and the incidence of ILI are very similar, in a country in the temperate climate zone, such as the Netherlands. We hypothesize that in the Netherlands, the same environmental factors and mobility patterns that are associated with the seasonality of influenza-like illnesses are also predictors of the seasonality of COVID-19.

METHODS: We used meteorological, pollen/hay fever and mobility data from the Netherlands. For COVID-19 Reproduction Number (Ryou), we used daily estimates from the Netherlands Institute of Public Health. For all datasets, we selected the overlap period of COVID-19 and the first allergy season: February 17, 2020 to September 21, 2020 (n=218). Backward stepwise multiple linear regression was used to develop an environmental prediction model of the Ryou of COVID-19. Next, we investigated whether adding mobility trends to an environmental model improved predictive power.

RESULTS: By stepwise multiple linear regression, four highly significant predictors (p you of COVID-19 and has a good and highly significant fit: F(4, 213) = 374.2, p you (F(4, 213) = 181.3, p

CONCLUSIONS: We conclude that the combined mobility and environment model can adequately predict the seasonality of COVID-19 in a country with a temperate climate like the Netherlands. In this model, higher solar radiation, higher temperature, and hay fever are linked to reduced reproduction of COVID-19, and higher mobility to indoor recreation places is linked to increased spread of COVID-19. 19.

PMID:35257688 | DOI:10.1016/j.envres.2022.113030


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