Big-Data-Driven Geo-Spatiotemporal Correlation Analysis between Precursor Pollen and Influenza and its Implication to Novel Coronavirus Outbreak

Abstract

Although studies of many respiratory viruses and pollens are often framed by both seasonal and health related perspectives, pollen has yet to be extensively examined as an important covariate to seasonal respiratory viruses (SRVs) in any context, including a causal one. This study contributes to those goals through an investigation of SRVs and pollen counts at selected regions across the Western Hemisphere. Two complementary decadal-scaled geospatial profiles were developed. One laterally spanned the US and was anchored by detailed pollen information for Albuquerque, New Mexico. The other straddled the equator to include Fortaleza, Brazil. We found that the geospatial and climatological patterns of pollen advancement and decline across the US every year presented a statistically significant correlation to the subsequent emergence and decline of SRVs. Other significant covariates included winds, temperatures, and atmospheric moisture. Our study indicates that areas of the US with lower geostrophic wind baselines are typically areas of persistently higher and earlier influenza like illness (ILI) cases. In addition to that continental- scaled contrast, many sites indicated seasonal highs of geostrophic winds and ILI which were closely aligned. These observations suggest extensive scale-dependent connectivity of viruses to geostrophic circulation. Pollen emergence and its own scale-dependent circulation may contribute to the geospatial and seasonal patterns of ILI. We explore some uncertainties associated with this investigation, and consider the possibility that in a temperate climate, following a Spring pollen emergence, a resulting increase in pollen triggered human Immunoglobulin E (IgE) antibodies may suppress ILIs for several months.