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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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Du WY, Yin CN, Wang HT, Li ZW, Wang WJ, Xue FZ, Zhao L, Cao WC. Infectious diseases among elderly persons: Results from a population-based observational study in Shandong province, China, 2013-2017. J Glob Health 2022; 11:08010. [PMID: 35003717 PMCID: PMC8710039 DOI: 10.7189/jogh.11.08010] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/04/2023] Open
Abstract
Background The health of the elderly is one of the major challenges in today's ageing society. However, research on infectious diseases among the elderly is limited. This study aimed to describe the epidemiological characteristics and dynamics of infectious diseases among the elderly population aged ≥60 years in Shandong province, China. Methods Incidence data for infectious diseases were collected from the Shandong Multi-Center Healthcare Big Data Platform from January 2013 to June 2017, which involved 550 432 elderly persons. We compared the incidence of each infectious disease and disease category, stratified by age, gender, and region. Annual percentage change (APC) was estimated using logarithmic linear regression to examine the incidence trends. Poisson regression was conducted to identify the effect of demographic factors on incidence, with incidence rate ratio (IRR) and their 95% confidence intervals (CIs) estimated. Results A total of 27 595 cases of 102 infectious diseases were reported during the study period, with an overall incidence of 1425.51/100 000 person-years. The most common infectious diseases were respiratory and mucocutaneous diseases among the elderly persons, with annual increases of 17.45% and 20.44%, respectively (both P<0.05). In rural areas, the incidence of respiratory, gastrointestinal, blood- and sex-transmitted, and mucocutaneous infections increased significantly, with APCs of 178.52%, 204.66%, 28.24%, 63.01%, respectively (all P<0.05). Elderly males had a higher risk of infections than that of females, with the highest IRRa of 2.94 (95% confidence interval (CI) = 2.89, 3.00) in respiratory diseases. The elderly aged 85-89 years had a much higher risk of respiratory diseases than those aged 60-64 years (IRRa = 9.85, 95%CI: 9.39, 10.33); however, the risk of blood- and sex-transmitted diseases was highest among the elderly aged 65-69 years (IRRa = 1.24, 95% CI = 1.06, 1.45). Conclusions Ageing population are facing a substantial challenge on infectious diseases. More attention should be paid to infections with significant growth. Targeted strategies and measures on elderly persons in different regions and subgroups are urgently needed.
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Affiliation(s)
- 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
| | - Hai-Tao Wang
- 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
| | - Fu-Zhong Xue
- Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, China
| | - 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
| | - 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, Beijing, China
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Tchole AIM, Li ZW, Wei JT, Ye RZ, Wang WJ, Du WY, Wang HT, Yin CN, Ji XK, Xue FZ, Bachir AM, Zhao L, Cao WC. Epidemic and control of COVID-19 in Niger: quantitative analyses in a least developed country. J Glob Health 2021; 10:020513. [PMID: 33312506 PMCID: PMC7719275 DOI: 10.7189/jogh.10.020513] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022] Open
Abstract
Background The COVID-19 pandemic is challenging the public health response system worldwide, especially in poverty-stricken, war-torn, and least developed countries (LDCs). Methods We characterized the epidemiological features and spread dynamics of COVID-19 in Niger, quantified the effective reproduction number (Rt), evaluated the impact of public health control measures, and estimated the disease burden. Results As of 4 July 2020, COVID-19 has affected 29 communes of Niger with 1093 confirmed cases, among whom 741 (67.8%) were males. Of them 89 cases died, resulting in a case fatality rate (CFR) of 8.1%. Both attack rates and CFRs were increased with age (P < 0.0001). Health care workers accounted for 12.8% cases. Among the reported cases, 39.3% were isolated and treated at home, and 42.3% were asymptomatic. 74.6% cases were clustered in Niamey, the capital of Niger. The Rt fluctuated in correlation to control measures at different outbreak stages. After the authorities initiated the national response and implemented the strictest control measures, Rt quickly dropped to below the epidemic threshold (<1), and maintained low level afterward. The national disability-adjusted life years attributable to COVID-19 was 1267.38 years in total, of which years of life lost accounted for over 99.1%. Conclusions Classic public health control measures such as prohibition of public gatherings, travelling ban, contact tracing, and isolation and quarantine at home, are proved to be effective to contain the outbreak in Niger, and provide guidance for controlling the ongoing COVID-19 pandemic in LDCs.
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Affiliation(s)
- Ali Issakou Malam Tchole
- Institute of EcoHealth, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, P. R. China.,Directorate of Surveillance and Response to Epidemics, Ministry of Public Health, Niamey, Niger
| | - Zhen-Wei Li
- Institute of EcoHealth, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, P. R. China
| | - Jia-Te Wei
- Institute of EcoHealth, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, P. R. China
| | - Run-Ze Ye
- Institute of EcoHealth, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, P. R. China.,State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, P. R. China
| | - Wen-Jing Wang
- Institute of EcoHealth, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, P. R. China
| | - Wan-Yu Du
- Institute of EcoHealth, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, P. R. China
| | - Hai-Tao Wang
- Institute of EcoHealth, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, P. R. China
| | - Chao-Nan Yin
- Institute of EcoHealth, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, P. R. China
| | - Xiao-Kang Ji
- Institute for Medical Dataology, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, P. R. China
| | - Fu-Zhong Xue
- Institute for Medical Dataology, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, P. R. China
| | - Alassan Maman Bachir
- Directorate of Surveillance and Response to Epidemics, Ministry of Public Health, Niamey, Niger
| | - Lin Zhao
- Institute of EcoHealth, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, P. R. China
| | - Wu-Chun Cao
- Institute of EcoHealth, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, P. R. China.,State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, P. R. China
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Zhao L, Feng D, Ye RZ, Wang HT, Zhou YH, Wei JT, de Vlas SJ, Cui XM, Jia N, Yin CN, Li SX, Wang ZQ, Cao WC. Outbreak of COVID-19 and SARS in mainland China: a comparative study based on national surveillance data. BMJ Open 2020; 10:e043411. [PMID: 33060093 PMCID: PMC7565247 DOI: 10.1136/bmjopen-2020-043411] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/04/2020] [Revised: 09/28/2020] [Accepted: 10/02/2020] [Indexed: 01/16/2023] Open
Abstract
OBJECTIVE To compare the epidemiological characteristics and transmission dynamics in relation to interventions against the COVID-19 and severe acute respiratory syndrome (SARS) outbreak in mainland China. DESIGN Comparative study based on a unique data set of COVID-19 and SARS. SETTING Outbreak in mainland China. PARTICIPANTS The final database included 82 858 confirmed cases of COVID-19 and 5327 cases of SARS. METHODS We brought together all existing data sources and integrated them into a comprehensive data set. Individual information on age, sex, occupation, residence location, date of illness onset, date of diagnosis and clinical outcome was extracted. Control measures deployed in mainland China were collected. We compared the epidemiological and spatial characteristics of COVID-19 and SARS. We estimated the effective reproduction number to explore differences in transmission dynamics and intervention effects. RESULTS Compared with SARS, COVID-19 affected more extensive areas (1668 vs 230 counties) within a shorter time (101 vs 193 days) and had higher attack rate (61.8 vs 4.0 per million persons). The COVID-19 outbreak had only one epidemic peak and one epicentre (Hubei Province), while the SARS outbreak resulted in two peaks and two epicentres (Guangdong Province and Beijing). SARS-CoV-2 was more likely to infect older people (median age of 52 years), while SARS-CoV tended to infect young adults (median age of 34 years). The case fatality rate (CFR) of either disease increased with age, but the CFR of COVID-19 was significantly lower than that of SARS (5.6% vs 6.4%). The trajectory of effective reproduction number dynamically changed in relation to interventions, which fell below 1 within 2 months for COVID-19 and within 5.5 months for SARS. CONCLUSIONS China has taken more prompt and effective responses to combat COVID-19 by learning lessons from SARS, providing us with some epidemiological clues to control the ongoing COVID-19 pandemic worldwide.
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Affiliation(s)
- Lin Zhao
- Institute of EcoHealth, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, China
| | - Dan Feng
- Institution of Hospital Management, Medical Innovation Research Division, Chinese PLA General Hospital, Beijing, China
| | - Run-Ze Ye
- Institute of EcoHealth, 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
| | - Yu-Hao Zhou
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, China
| | - Jia-Te Wei
- Institute of EcoHealth, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, China
| | - Sake J de Vlas
- Department of Public Health, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Xiao-Ming Cui
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, China
| | - Na Jia
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, China
| | - Chao-Nan Yin
- Institute of EcoHealth, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, China
| | - Shi-Xue Li
- Institute of EcoHealth, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, China
| | - Zhi-Qiang Wang
- Department of Gastroenterology, The Second Medical Center, Chinese PLA General Hospital, Beijing, China
| | - Wu-Chun Cao
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, China
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