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Zhao L, Wang HT, Ye RZ, Li ZW, Wang WJ, Wei JT, Du WY, Yin CN, Wang SS, Liu JY, Ji XK, Wang YC, Cui XM, Liu XY, Li CY, Qi C, Liu LL, Li XJ, Xue FZ, Cao WC. Profile and dynamics of infectious diseases: a population-based observational study using multi-source big data. BMC Infect Dis 2022; 22:332. [PMID: 35379167 PMCID: PMC8977827 DOI: 10.1186/s12879-022-07313-6] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2021] [Accepted: 03/24/2022] [Indexed: 12/02/2022] Open
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 (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). Conclusions 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. Supplementary Information The online version contains supplementary material available at 10.1186/s12879-022-07313-6.
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Affiliation(s)
- Lin Zhao
- Institute of EcoHealth, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, China.,Department of Occupational Health and Occupational Medicine, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, China
| | - Hai-Tao Wang
- Institute of EcoHealth, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, China
| | - Run-Ze Ye
- Institute of EcoHealth, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, China
| | - Zhen-Wei Li
- Institute of EcoHealth, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, China
| | - Wen-Jing Wang
- Institute of EcoHealth, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, China
| | - Jia-Te Wei
- Institute of EcoHealth, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, China
| | - Wan-Yu Du
- Institute of EcoHealth, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, China
| | - Chao-Nan Yin
- Institute of EcoHealth, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, China
| | - Shan-Shan Wang
- Institute of EcoHealth, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, China
| | - Jin-Yue Liu
- Institute of EcoHealth, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, China
| | - Xiao-Kang Ji
- Institute for Medical Dataology, School of Public Health, Cheeloo College of Medicine, Shandong University, 12550 Erhuan Donglu, Jinan, 250002, China
| | - Yong-Chao Wang
- Institute for Medical Dataology, School of Public Health, Cheeloo College of Medicine, Shandong University, 12550 Erhuan Donglu, Jinan, 250002, China
| | - Xiao-Ming Cui
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, 20 Dong-da Street, Fengtai District, Beijing, 100071, China
| | - Xue-Yuan Liu
- Institute of EcoHealth, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, China
| | - Chun-Yu Li
- Institute for Medical Dataology, School of Public Health, Cheeloo College of Medicine, Shandong University, 12550 Erhuan Donglu, Jinan, 250002, China
| | - Chang Qi
- Institute for Medical Dataology, School of Public Health, Cheeloo College of Medicine, Shandong University, 12550 Erhuan Donglu, Jinan, 250002, China
| | - Li-Li Liu
- Institute for Medical Dataology, School of Public Health, Cheeloo College of Medicine, Shandong University, 12550 Erhuan Donglu, Jinan, 250002, China
| | - Xiu-Jun Li
- Institute for Medical Dataology, School of Public Health, Cheeloo College of Medicine, Shandong University, 12550 Erhuan Donglu, Jinan, 250002, China
| | - Fu-Zhong Xue
- Institute for Medical Dataology, School of Public Health, Cheeloo College of Medicine, Shandong University, 12550 Erhuan Donglu, Jinan, 250002, China.
| | - Wu-Chun Cao
- Institute of EcoHealth, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, China. .,State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, 20 Dong-da Street, Fengtai District, Beijing, 100071, China.
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