Causality between Air Quality Index and Influenza-Like Illness: Based on Nonlinear Dynamics Method

Exploring the causality between urban air pollution and human influenza infection can effectively help people to carry out effective and accurate prevention and control measures, especially today when influenza diseases continue to break out. In this paper, with the help of the big data platform, we investigate the non-linear characteristics of air quality index (AQI) and influenza-like illness (ILI%) and used the Convergent Cross Mapping (CCM) method to investigate the two variables' causality for the first time. Based on the CCM test results, the average AQI and the concentration of the five main air pollutants in the 15 sample cities in the south China and ILI% show obvious nonlinear and weak coupling characteristics and a one-way causal relationship. We also use data to prove that correlation is a necessary but insufficient condition for causality. The research in this article has enriched the interactive effects between air pollution and human influenza in experience and has important practical significance for urban managers to control air pollution and allocate medical resources.