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Profile and dynamics of infectious diseases: a population-based observational study using multi-source big data

Authors :
Lin Zhao
Hai-Tao Wang
Run-Ze Ye
Zhen-Wei Li
Wen-Jing Wang
Jia-Te Wei
Wan-Yu Du
Chao-Nan Yin
Shan-Shan Wang
Jin-Yue Liu
Xiao-Kang Ji
Yong-Chao Wang
Xiao-Ming Cui
Xue-Yuan Liu
Chun-Yu Li
Chang Qi
Li-Li Liu
Xiu-Jun Li
Fu-Zhong Xue
Wu-Chun Cao
Source :
BMC Infectious Diseases, Vol 22, Iss 1, Pp 1-12 (2022)
Publication Year :
2022
Publisher :
BMC, 2022.

Abstract

Abstract Background The current surveillance system only focuses on notifiable infectious diseases in China. The arrival of the big-data era provides us a chance to elaborate on the full spectrum of infectious diseases. Methods In this population-based observational study, we used multiple health-related data extracted from the Shandong Multi-Center Healthcare Big Data Platform from January 2013 to June 2017 to estimate the incidence density and describe the epidemiological characteristics and dynamics of various infectious diseases in a population of 3,987,573 individuals in Shandong province, China. Results In total, 106,289 cases of 130 infectious diseases were diagnosed among the population, with an incidence density (ID) of 694.86 per 100,000 person-years. Besides 73,801 cases of 35 notifiable infectious diseases, 32,488 cases of 95 non-notifiable infectious diseases were identified. The overall ID continuously increased from 364.81 per 100,000 person-years in 2013 to 1071.80 per 100,000 person-years in 2017 (χ 2 test for trend, P

Details

Language :
English
ISSN :
14712334
Volume :
22
Issue :
1
Database :
Directory of Open Access Journals
Journal :
BMC Infectious Diseases
Publication Type :
Academic Journal
Accession number :
edsdoj.bf23e4f05c2d46bab614847dd8d05285
Document Type :
article
Full Text :
https://doi.org/10.1186/s12879-022-07313-6