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10.1016/j.scitotenv.2020.143182 http://scihub22266oqcxt.onion/10.1016/j.scitotenv.2020.143182 33131881!7580695!33131881     free     free     free Warning: file_get_contents(https://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?dbfrom=pubmed&id=33131881&cmd=llinks): Failed to open stream: HTTP request failed! 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Can pollen explain the seasonality of flu-like illnesses in the Netherlands?|pdf=|usr=}}{{33131881}} gab.com Text Can pollen explain the seasonality of flu-like illnesses in the Netherlands JO: Sci Total Environ http://www.kidney.de/pget.php?&tw=1&pmid=33131881 #FOAvip 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/m(3), 120 allergenic pollen grains/m(3), and a solar radiation of 510 J/cm(2) 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. Twit Text FOAVip Can pollen explain the seasonality of flu-like illnesses in the Netherlands ????Sci Total Environ http://www.kidney.de/pget.php?&tw=1&pmid=33131881 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=33131881 #FOAvip English Wikipedia <ref>{{Cite pmid|33131881}}</ref> Can pollen explain the seasonality of flu-like illnesses in the Netherlands? #MMPMID33131881 Hoogeveen MJ; van Gorp ECM; Hoogeveen EK Sci Total Environ 2021[Feb]; 755 (Pt 2): 143182 PMID33131881show ga 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/m(3), 120 allergenic pollen grains/m(3), and a solar radiation of 510 J/cm(2) 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. |*COVID-19[MESH] |Humans[MESH] |Netherlands/epidemiology[MESH] |Pollen[MESH] |SARS-CoV-2[MESH]Can pollen explain the seasonality of flu-like illnesses in the Nether(epmc).pdf DeepDyve Pubget Overpricing