Can Pollen Explain the Seasonality of Flu-Like Incidence?

Author links: Martijn J.Hoogeveen^aEric C.M.van Gorp^bEllen K.Hoogeveen^c
aDepartment Technical Sciences & Environment, Open University, the Netherlands
^bDepartment of Viroscience and Department of Infectious Diseases, Erasmus Medical Centre, Rotterdam, the Netherlands
^cDepartment of Internal Medicine, Jeroen Bosch Hospital, Den Bosch, the Netherlands

Source: https://doi.org/10.1016/j.scitotenv.2020.143182

Highlights

• Testing pollen-flu seasonality theory for 2016–2020 in the Netherlands, overlapping COVID-19
• Pollen have allergenic and immuno-activating properties.
• Highly significant inverse correlation between pollen and flu-like incidence.
• Solar radiation is a co-inhibitor of flu-like epidemics.
• COVID-19 does not break with seasonality pattern, but more data are needed for conclusion.

Abstract

Current models for flu-like epidemics insufficiently explain multi-cycle seasonality. Meteorological factors alone, including the associated behavior, do not predict seasonality, given substantial climate differences between countries that are subject to flu-like epidemics or COVID-19. Pollen is documented to be allergenic, it plays a role in immuno-activation and defense against respiratory viruses, and seems to create a bio-aerosol that lowers the reproduction number of flu-like viruses. Therefore, we hypothesize that pollen may explain the seasonality of flu-like epidemics, including COVID-19, in combination with meteorological variables.

We have tested the Pollen-Flu Seasonality Theory for 2016–2020 flu-like seasons, including COVID-19, in the Netherlands, with its 17.4 million inhabitants. We combined changes in flu-like incidence per 100 K/Dutch residents (code: ILI) with pollen concentrations and meteorological data. Finally, a predictive model was tested using pollen and meteorological threshold values, inversely correlated to flu-like incidence.

We found a highly significant inverse correlation of r(224) = −0.41 (p < 0.001) between pollen and changes in flu-like incidence, corrected for the incubation period. The correlation was stronger after taking into account the incubation time. We found that our predictive model has the highest inverse correlation with changes in flu-like incidence of r(222) = −0.48 (p < 0.001) when average thresholds of 610 total pollen grains/m³, 120 allergenic pollen grains/m³, and a solar radiation of 510 J/cm² are passed. The passing of at least the pollen thresholds, preludes the beginning and end of flu-like seasons. Solar radiation is a co-inhibitor of flu-like incidence, while temperature makes no difference. However, higher relative humidity increases with flu-like incidence.

We conclude that pollen is a predictor of the inverse seasonality of flu-like epidemics, including COVID-19, and that solar radiation is a co-inhibitor, in the Netherlands.

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