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

Authors :
Zhao, Lin
Wang, Hai-Tao
Ye, Run-Ze
Li, Zhen-Wei
Wang, Wen-Jing
Wei, Jia-Te
Du, Wan-Yu
Yin, Chao-Nan
Wang, Shan-Shan
Liu, Jin-Yue
Ji, Xiao-Kang
Wang, Yong-Chao
Cui, Xiao-Ming
Liu, Xue-Yuan
Li, Chun-Yu
Qi, Chang
Liu, Li-Li
Li, Xiu-Jun
Xue, Fu-Zhong
Cao, Wu-Chun
Source :
BMC Infectious Diseases. 4/4/2022, Vol. 22 Issue 1, p1-12. 12p.
Publication Year :
2022

Abstract

<bold>Background: </bold>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.<bold>Methods: </bold>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.<bold>Results: </bold>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 (χ2 test for trend, P < 0.0001). Urban areas had a significantly higher ID than rural areas, with a relative risk of 1.25 (95% CI 1.23-1.27). Adolescents aged 10-19 years had the highest ID of varicella, women aged 20-39 years had significantly higher IDs of syphilis and trichomoniasis, and people aged ≥ 60 years had significantly higher IDs of zoster and viral conjunctivitis (all P < 0.05).<bold>Conclusions: </bold>Infectious diseases remain a substantial public health problem, and non-notifiable diseases should not be neglected. Multi-source-based big data are beneficial to better understand the profile and dynamics of infectious diseases. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
14712334
Volume :
22
Issue :
1
Database :
Academic Search Index
Journal :
BMC Infectious Diseases
Publication Type :
Academic Journal
Accession number :
156111557
Full Text :
https://doi.org/10.1186/s12879-022-07313-6