TY  - JOUR
AU  - Magazzino, Cosimo
AU  - Mele, Marco
PY  - 2021
DA  - 2021/05/06
TI  - A Neural Network Evidence of the Nexus Among Air Pollution, Economic Growth, and COVID-19 Deaths in the Hubei Area
JO  - Advances in Environmental and Engineering Research
SP  - 008
VL  - 02
IS  - 02
AB  - In this study, we used an image neural network model to assess the relationship between economic growth, pollution (PM2.5, PM10, and CO2), and deaths from COVID-19 in the Hubei area (China). Data analysis, neural network analysis, and deep learning experiments were carried out to assess the relationship among COVID-19 deaths, air pollution, and economic growth in China (Hubei province, the epicenter of the COVID-19 pandemic). We collected daily data at a city level from January 20 to July 31, 2020. We used main cities in the Hubei province, with data on confirmed COVID-19 deaths, air pollution (expressed in µg/m3 as PM2.5, PM10, and CO2), and per capita economic growth. Following the most recent contributions on the relationship among air pollution, GDP, and diffusion of COVID-19, we generated an algorithm capable of identifying a neural connection among these variables. The results confirmed a strong predictive relationship for the Hubei area between changes in the economic growth, fine particles, and deaths from COVID-19. These results would recommend adequate environmental reforms to policymakers to contain the spread and adverse effects of the virus. Therefore, there is a requirement to reconsider the system of transport and return to production by combining it with economic growth to protect the planet.
SN  - 2766-6190
UR  - https://doi.org/10.21926/aeer.2102008
DO  - 10.21926/aeer.2102008
ID  - Magazzino2021
ER  -