Probable Relationship between COVID-19, Pollutants and Meteorology: A Case Study at Santiago, Chile

We present here a study about the possible spread of covid-19 pandemic between human’s beings through aerosols contained in urban air polluted by respirable particulate matter and tropospheric ozone, as well incidence local meteorology an area with orographic basin characteristics certain period time. Hourly time-series data three meteorological variables—temperature, relative humidity, wind speed—and pollutants—PM10, PM2.5 O3—were considered together hourly from highest number accumulated sick's seven communes—chosen at random—in Santiago, Chile, studying probable link them. From epidemic perspective, infected patients was linked to pollutant variables, generating new time-series. Nonlinear analysis chaos theory formalism applied these time-series, obtaining largest Lyapunov exponent, correlation dimension, Kolmogorov entropy, Hurst exponent Lempel-Ziv complexity. Our preliminary results show pollution variables can be part elements fraction that give sustainability growth favor spread, making sick’s curve chaotic complex. In addition, environmental could worsen disease conditions like coronavirus (COVID-19) infection. For all complexity turned out 0 1 which is indicative connectivity chaos. The entropy were positive also exhibits found greater than 0.5 less for indicating long-term autocorrelation. Finally, dimension 5, revealing constructed are not random.