Complex PM2.5 Pollution and Hospital Admission for Respiratory Diseases over Big Data in Cloud Environment

Yi Zhou,Lianshui Li

doi:10.1155/2020/1301047

Abstract

With the establishment of China’s national air quality monitoring network, large amounts of monitoring data are available for different kinds of users. How to process and use this big data is a tough problem for users: most users have limited computing power, and new data are collected at every moment. Cloud computing may be an efficient and low-cost way to solve this problem. This paper investigates a problem of a complex system: the impact of PM2.5 on hospitalization for respiratory diseases. A change-point detection method based on grey relation analysis was used to solve this problem. Daily air pollution monitoring data and patient data were used in this study. Our results showed that (1) PM2.5 pollution showed a positive correlation on hospital admission for respiratory disease; (2) most patients went to hospital 2 days after PM2.5 pollution events; and (3) male, children, and old people were significantly affected by PM2.5 pollution. Our study is of great significance to help the government formulate suitable policies to reduce the damage caused by PM2.5 pollution and help hospitals allocate medical resources efficiently.

Highlights

Speaking, the development of the global economy, especially in the ird World countries, is closely related to environmental problems
Among all hospital admission records, respiratory system diseases account for 42.34%, the largest among all diseases. 46.26% patients were children, 14.72% were older people, and disease percentage for age 0–14 and 65+ was much higher than that of population proportion, which means children and older people were more likely to suffer from respiratory diseases; about 54.33% patients were male, and disease percentage for males was higher than population proportion for males, which suggested that men are more susceptible to respiratory diseases
We utilized the Grey relation analysis (GRA)-CP to study the correlation between PM2.5 pollution and hospitalization for respiratory diseases based on the analysis of the daily air pollution datasets and daily records of hospital admission

Summary

Introduction

The development of the global economy, especially in the ird World countries, is closely related to environmental problems. The rapid development of Chinese economy and the acceleration of urbanization make the contradiction between economic growth and environment more and more prominent. With a population of over 1.4 billion, China’s air pollution situation is extraordinary [1]. The annual death toll from air pollution in China is over million [2] and cost about China’s 2.0% GDP (gross domestic product) [3]. In 2012, the newly revised Ambient Air Quality Standard went into effect [4], and China began to build national air quality monitoring network. By the end of 2019, more than 1,400 national urban air quality monitoring stations have been built and scheduled to increase the number of monitoring stations to nearly 1,800 by the end of 2025

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Methods

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Discussion

Conclusion