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Haque S, Mengersen K, Barr I, Wang L, Yang W, Vardoulakis S, Bambrick H, Hu W. Towards development of functional climate-driven early warning systems for climate-sensitive infectious diseases: Statistical models and recommendations. ENVIRONMENTAL RESEARCH 2024; 249:118568. [PMID: 38417659 DOI: 10.1016/j.envres.2024.118568] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/27/2023] [Revised: 02/22/2024] [Accepted: 02/25/2024] [Indexed: 03/01/2024]
Abstract
Climate, weather and environmental change have significantly influenced patterns of infectious disease transmission, necessitating the development of early warning systems to anticipate potential impacts and respond in a timely and effective way. Statistical modelling plays a pivotal role in understanding the intricate relationships between climatic factors and infectious disease transmission. For example, time series regression modelling and spatial cluster analysis have been employed to identify risk factors and predict spatial and temporal patterns of infectious diseases. Recently advanced spatio-temporal models and machine learning offer an increasingly robust framework for modelling uncertainty, which is essential in climate-driven disease surveillance due to the dynamic and multifaceted nature of the data. Moreover, Artificial Intelligence (AI) techniques, including deep learning and neural networks, excel in capturing intricate patterns and hidden relationships within climate and environmental data sets. Web-based data has emerged as a powerful complement to other datasets encompassing climate variables and disease occurrences. However, given the complexity and non-linearity of climate-disease interactions, advanced techniques are required to integrate and analyse these diverse data to obtain more accurate predictions of impending outbreaks, epidemics or pandemics. This article presents an overview of an approach to creating climate-driven early warning systems with a focus on statistical model suitability and selection, along with recommendations for utilizing spatio-temporal and machine learning techniques. By addressing the limitations and embracing the recommendations for future research, we could enhance preparedness and response strategies, ultimately contributing to the safeguarding of public health in the face of evolving climate challenges.
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Affiliation(s)
- Shovanur Haque
- Ecosystem Change and Population Health Research Group, School of Public Health and Social Work, Queensland University of Technology, Brisbane, Australia
| | - Kerrie Mengersen
- School of Mathematical Sciences, Queensland University of Technology, Brisbane, Australia; Centre for Data Science (CDS), Queensland University of Technology (QUT), Brisbane, Australia
| | - Ian Barr
- World Health Organization Collaborating Centre for Reference and Research on Influenza, VIDRL, Doherty Institute, Melbourne, Australia; Department of Microbiology and Immunology, University of Melbourne, Victoria, Australia
| | - Liping Wang
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, Division of Infectious disease, Chinese Centre for Disease Control and Prevention, China
| | - Weizhong Yang
- School of Population Medicine and Public Health, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 100730, China
| | - Sotiris Vardoulakis
- HEAL Global Research Centre, Health Research Institute, University of Canberra, ACT Canberra, 2601, Australia
| | - Hilary Bambrick
- National Centre for Epidemiology and Population Health, The Australian National University, ACT 2601 Canberra, Australia
| | - Wenbiao Hu
- Ecosystem Change and Population Health Research Group, School of Public Health and Social Work, Queensland University of Technology, Brisbane, Australia.
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Ming BW, Li L, Huang HN, Ma JJ, Shi C, Xu XH, Yang Z, Ou CQ. The Effectiveness of National Expanded Program on Immunization With Hepatitis A Vaccines in the Chinese Mainland: Interrupted Time-Series Analysis. JMIR Public Health Surveill 2024; 10:e53982. [PMID: 38416563 PMCID: PMC10938223 DOI: 10.2196/53982] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2023] [Revised: 01/08/2024] [Accepted: 01/22/2024] [Indexed: 02/29/2024] Open
Abstract
BACKGROUND The high prevalence of hepatitis A delivered a blow to public health decades ago. The World Health Organization (WHO) set a goal to eliminate viral hepatitis including hepatitis A by 2030. In 2008, hepatitis A vaccines were integrated into the Expanded Program on Immunization (EPI) in China to alleviate the burden of hepatitis A, although the effectiveness of the EPI has not been well investigated. OBJECTIVE We aimed to evaluate the intervention effect at both provincial and national levels on the incidence of hepatitis A in the Chinese mainland from 2005 to 2019. METHODS Based on the monthly reported number of hepatitis A cases from 2005 to 2019 in each provincial-level administrative division, we adopted generalized additive models with an interrupted time-series design to estimate province-specific effects of the EPI on the incidence of hepatitis A among the target population (children aged 2-9 years) from 2005 to 2019. We then pooled province-specific effect estimates using random-effects meta-analyses. We also assessed the effect among the nontarget population and the whole population. RESULTS A total of 98,275 hepatitis A cases among children aged 2-9 years were reported in the Chinese mainland from 2005 to 2019, with an average annual incidence of 5.33 cases per 100,000 persons. Nationally, the EPI decreased the hepatitis A incidence by 80.77% (excess risk [ER] -80.77%, 95% CI -85.86% to -72.92%) during the study period, guarding an annual average of 28.52 (95% empirical CI [eCI] 27.37-29.00) cases per 100,000 persons among the target children against hepatitis A. Western China saw a more significant effect of the EPI on the decrease in the incidence of hepatitis A among the target children. A greater number of target children were protected from onset in Northwest and Southwest China, with an excess incidence rate of -129.72 (95% eCI -135.67 to -117.86) and -66.61 (95% eCI -67.63 to -64.22) cases per 100,000 persons on average, respectively. Intervention effects among nontarget (ER -32.88%, 95% CI -39.76% to -25.21%) and whole populations (ER -31.97%, 95% CI -39.61% to -23.37%) were relatively small. CONCLUSIONS The EPI has presented a lasting positive effect on the containment of hepatitis A in the target population in China. The EPI's effect on the target children also provided a degree of indirect protection for unvaccinated individuals. The continuous surveillance of hepatitis A and the maintenance of mass vaccination should shore up the accomplishment in the decline of hepatitis A incidence to ultimately achieve the goal set by the WHO.
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Affiliation(s)
- Bo-Wen Ming
- State Key Laboratory of Organ Failure Research, Department of Biostatistics, School of Public Health, Southern Medical University, Guangzhou, China
| | - Li Li
- State Key Laboratory of Organ Failure Research, Department of Biostatistics, School of Public Health, Southern Medical University, Guangzhou, China
| | - Hao-Neng Huang
- State Key Laboratory of Organ Failure Research, Department of Biostatistics, School of Public Health, Southern Medical University, Guangzhou, China
| | - Jia-Jun Ma
- State Key Laboratory of Organ Failure Research, Department of Biostatistics, School of Public Health, Southern Medical University, Guangzhou, China
| | - Chen Shi
- State Key Laboratory of Organ Failure Research, Department of Biostatistics, School of Public Health, Southern Medical University, Guangzhou, China
| | - Xiao-Han Xu
- State Key Laboratory of Organ Failure Research, Department of Biostatistics, School of Public Health, Southern Medical University, Guangzhou, China
| | - Zhou Yang
- State Key Laboratory of Organ Failure Research, Department of Biostatistics, School of Public Health, Southern Medical University, Guangzhou, China
| | - Chun-Quan Ou
- State Key Laboratory of Organ Failure Research, Department of Biostatistics, School of Public Health, Southern Medical University, Guangzhou, China
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Lu Y, Zhu H, Hu Z, He F, Chen G. Epidemic Characteristics, Spatiotemporal Pattern, and Risk Factors of Other Infectious Diarrhea in Fujian Province From 2005 to 2021: Retrospective Analysis. JMIR Public Health Surveill 2023; 9:e45870. [PMID: 38032713 PMCID: PMC10722358 DOI: 10.2196/45870] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2023] [Revised: 05/03/2023] [Accepted: 09/05/2023] [Indexed: 12/01/2023] Open
Abstract
BACKGROUND Other infectious diarrhea (OID) continues to pose a significant public health threat to all age groups in Fujian Province. There is a need for an in-depth analysis to understand the epidemiological pattern of OID and its associated risk factors in the region. OBJECTIVE In this study, we aimed to describe the overall epidemic characteristics and spatiotemporal pattern of OID in Fujian Province from 2005 to 2021 and explore the linkage between sociodemographic and environmental factors and the occurrence of OID within the study area. METHODS Notification data for OID in Fujian were extracted from the China Information System for Disease Control and Prevention. The spatiotemporal pattern of OID was analyzed using Moran index and Kulldorff scan statistics. The seasonality of and short-term impact of meteorological factors on OID were examined using an additive decomposition model and a generalized additive model. Geographical weighted regression and generalized linear mixed model were used to identify potential risk factors. RESULTS A total of 388,636 OID cases were recorded in Fujian Province from January 2005 to December 2021, with an average annual incidence of 60.3 (SD 16.7) per 100,000 population. Children aged <2 years accounted for 50.7% (196,905/388,636) of all cases. There was a steady increase in OID from 2005 to 2017 and a clear seasonal shift in OID cases from autumn to winter and spring between 2005 and 2020. Higher maximum temperature, atmospheric pressure, humidity, and precipitation were linked to a higher number of deseasonalized OID cases. The spatial and temporal aggregations were concentrated in Zhangzhou City and Xiamen City for 17 study years. Furthermore, the clustered areas exhibited a dynamic spreading trend, expanding from the southernmost Fujian to the southeast and then southward over time. Factors such as densely populated areas with a large <1-year-old population, less economically developed areas, and higher pollution levels contributed to OID cases in Fujian Province. CONCLUSIONS This study revealed a distinct distribution of OID incidence across different population groups, seasons, and regions in Fujian Province. Zhangzhou City and Xiamen City were identified as the major hot spots for OID. Therefore, prevention and control efforts should prioritize these specific hot spots and highly susceptible groups.
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Affiliation(s)
- Yixiao Lu
- School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, China
| | - Hansong Zhu
- Fujian Provincial Center for Disease Control and Prevention, The Practice Base on the School of Public Health, Fujian Medical University, Fuzhou, China
| | - Zhijian Hu
- Department of Epidemiology and Health Statistics, School of Public Health, Fujian Medical University, Fuzhou, China
| | - Fei He
- Department of Epidemiology and Health Statistics, School of Public Health, Fujian Medical University, Fuzhou, China
| | - Guangmin Chen
- Fujian Provincial Center for Disease Control and Prevention, The Practice Base on the School of Public Health, Fujian Medical University, Fuzhou, China
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Deng LL, Han YJ, Li ZW, Wang DY, Chen T, Ren X, He GX. Epidemiological characteristics of seven notifiable respiratory infectious diseases in the mainland of China: an analysis of national surveillance data from 2017 to 2021. Infect Dis Poverty 2023; 12:99. [PMID: 37953290 PMCID: PMC10642048 DOI: 10.1186/s40249-023-01147-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2023] [Accepted: 10/11/2023] [Indexed: 11/14/2023] Open
Abstract
BACKGROUND Respiratory infectious diseases (RIDs) remain a pressing public health concern, posing a significant threat to the well-being and lives of individuals. This study delves into the incidence of seven primary RIDs during the period 2017-2021, aiming to gain deeper insights into their epidemiological characteristics for the purpose of enhancing control and prevention strategies. METHODS Data pertaining to seven notifiable RIDs, namely, seasonal influenza, pulmonary tuberculosis (PTB), mumps, scarlet fever, pertussis, rubella and measles, in the mainland of China between 2017 and 2021 were obtained from the National Notifiable Disease Reporting System (NNDRS). Joinpoint regression software was utilized to analyze temporal trends, while SaTScan software with a Poisson probability model was used to assess seasonal and spatial patterns. RESULTS A total of 11,963,886 cases of the seven RIDs were reported during 2017-2021, and yielding a five-year average incidence rate of 170.73 per 100,000 individuals. Among these RIDs, seasonal influenza exhibited the highest average incidence rate (94.14 per 100,000), followed by PTB (55.52 per 100,000), mumps (15.16 per 100,000), scarlet fever (4.02 per 100,000), pertussis (1.10 per 100,000), rubella (0.59 per 100,000), and measles (0.21 per 100,000). Males experienced higher incidence rates across all seven RIDs. PTB incidence was notably elevated among farmers and individuals aged over 65, whereas the other RIDs primarily affected children and students under 15 years of age. The incidences of PTB and measles exhibited a declining trend from 2017 to 2021 (APC = -7.53%, P = 0.009; APC = -40.87%, P = 0.02), while the other five RIDs peaked in 2019. Concerning seasonal and spatial distribution, the seven RIDs displayed distinct characteristics, with variations observed for the same RIDs across different regions. The proportion of laboratory-confirmed cases fluctuated among the seven RIDs from 2017 to 2021, with measles and rubella exhibiting higher proportions and mumps and scarlet fever showing lower proportions. CONCLUSIONS The incidence of PTB and measles demonstrated a decrease in the mainland of China between 2017 and 2021, while the remaining five RIDs reached a peak in 2019. Overall, RIDs continue to pose a significant public health challenge. Urgent action is required to bolster capacity-building efforts and enhance control and prevention strategies for RIDs, taking into account regional disparities and epidemiological nuances. With the rapid advancement of high-tech solutions, the development and effective implementation of a digital/intelligent RIDs control and prevention system are imperative to facilitate precise surveillance, early warnings, and swift responses.
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Affiliation(s)
- Le-le Deng
- National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 102206, China
| | - Ya-Jun Han
- National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 102206, China
| | - Zhuo-Wei Li
- National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 102206, China
| | - Da-Yan Wang
- National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 102206, China
| | - Tao Chen
- National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 102206, China.
| | - Xiang Ren
- Division of Infectious Disease, Key Laboratory of Surveillance and Early-Warning On Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing, 102206, China.
| | - Guang-Xue He
- National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 102206, China.
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Zhan Y, Gu H, Li X. Study on association factors of intestinal infectious diseases based-Bayesian spatio-temporal model. BMC Infect Dis 2023; 23:720. [PMID: 37875791 PMCID: PMC10598920 DOI: 10.1186/s12879-023-08665-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2023] [Accepted: 10/03/2023] [Indexed: 10/26/2023] Open
Abstract
BACKGROUND Intestinal infectious diseases (IIDs) are a significant public health issue in China, and the incidence and distribution of IIDs vary greatly by region and are affected by various factors. This study aims to describe the spatio-temporal trends of IIDs in the Chinese mainland and investigate the association between socioeconomic and meteorological factors with IIDs. METHODS In this study, IIDs in mainland China from 2006 to 2017 was analyzed using data obtained from the China Center for Disease Control and Prevention. Spatio-temporal mapping techniques was employed to visualize the spatial and temporal distribution of IIDs. Additionally, mean center and standard deviational ellipse analyses were utilized to examine the spatial trends of IIDs. To investigate the potential associations between IIDs and meteorological and socioeconomic variables, spatiotemporal zero-inflated Poisson and negative binomial models was employed within a Bayesian framework. RESULTS During the study period, the occurrence of most IIDs has dramatically reduced, with uneven reductions in different diseases. Significant regional differences were found among IIDs and influential factors. Overall, the access rate to harmless sanitary toilets (ARHST) was positively associated with the risk of cholera (RR: 1.73, 95%CI: 1.08-2.83), bacillary dysentery (RR: 1.32, 95%CI: 1.06-1.63), and other intestinal infectious diseases (RR: 1.88, 95%CI: 1.52-2.36), and negatively associated with typhoid fever (RR: 0.66, 95%CI: 0.51-0.92), paratyphoid fever (RR: 0.71, 95%CI: 0.55-0.92). Urbanization is only associated with hepatitis E (RR: 2.48, 95%CI: 1.12-5.72). And GDP was negatively correlated with paratyphoid fever (RR: 0.82, 95%CI: 0.70-0.97), and bacillary dysentery (RR: 0.77, 95%CI: 0.68-0.88), and hepatitis A (RR: 0.84, 95%CI: 0.73-0.97). Humidity showed positive correlation with some IIDs except for amoebic dysentery (RR: 1.64, 95%CI: 1.23-2.17), while wind speed showed a negative correlation with most IIDs. High precipitation was associated with an increased risk of typhoid fever (RR: 1.52, 95%CI: 1.09-2.13), and high temperature was associated with an increased risk of typhoid fever (RR: 2.82, 95%CI: 2.06-3.89), paratyphoid fever (RR: 2.79, 95%CI: 2.02-3.90), and HMFD (RR: 1.34, 95%CI: 1.01-1.77). CONCLUSIONS This research systematically and quantitatively studied the effect of socioeconomic and meteorological factors on IIDs, which provided causal clues for future studies and guided government planning.
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Affiliation(s)
- Yancen Zhan
- Department of Big Data in Health Sciences, and Center for Clinical Big Data and Statistics, Second Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, 310058, Zhejiang, China
| | - Hua Gu
- The Cancer Hospital, University of Chinese Academy of Sciences (Zhejiang Cancer Hospital), Institute of Basic Medicine and Cancer, Chinese Academy of Sciences, Hangzhou, 310022, China
| | - Xiuyang Li
- Department of Big Data in Health Sciences, and Center for Clinical Big Data and Statistics, Second Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, 310058, Zhejiang, China.
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Yu X, Fang M, Li Y, Yu J, Cheng L, Ding S, Kou Z. Epidemiological characteristics and spatio-temporal analysis of brucellosis in Shandong province, 2015-2021. BMC Infect Dis 2023; 23:669. [PMID: 37814221 PMCID: PMC10561485 DOI: 10.1186/s12879-023-08503-6] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2022] [Accepted: 07/31/2023] [Indexed: 10/11/2023] Open
Abstract
BACKGROUND Brucellosis is one of the major public health problems in China, it not only causes huge economic losses to the society, but also threatens the human's physical and mental health. The reported cases of brucellosis in Shandong province were at a high level, therefore, it is necessary for us to understand the epidemic characteristics and distribution trend of Brucellosis in Shandong province. This study aims to describe the epidemiological characteristics and spatial clustering characteristics of brucellosis in Shandong Province, provide a reference for the scientific prevention and control. METHODS Human brucellosis data in Shandong province from 2015 to 2021 were obtained from the China Information System for Disease Control and Prevention, the data were analyzed by descriptive epidemiological methods, spatial autocorrelation analysis and spatial-temporal cluster analysis methods use ArcGIS and SaTScan software, the results were presented in ArcMap. RESULTS A total of 22,251 human cases of brucellosis were reported, the annual incidence ranged between 2.41/100,000 and 4.07/100,000 from 2015 to 2021 in Shandong province, incidence has been decreasing year by year, while there was a significant increase in 2021. The distribution of brucellosis was of a seasonal trend, mainly concentrating during March to August. The age of the cases was mainly concentrated in the 30-74 age ranges, the average annual incidence rate was significantly higher in males than in females. The spatial analysis showed that the epidemics were mainly concentrated in the north and southwest. For the spatial autocorrelation analysis, a high global autocorrelation was observed at the county level, and the high-high clusters mainly distributed in the north and southwest region. For the spatio-temporal scanning, the most likely cluster areas mainly distributed in the north area, and then gradually moved southward, and the radius of clustered narrowed. CONCLUSIONS Human brucellosis remains a common challenge, particularly in northern region in spring and summer. More disease prevention and control measures should be taken in high-risk populations, and such higher-risk susceptible areas to reduce the incidence of brucellosis and ensure the health of the people.
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Affiliation(s)
- Xiaolin Yu
- Institute for Communicable Disease Control and Prevention, Shandong provincial Center for Disease Control and Prevention, Jinan, Shandong, China
| | - Ming Fang
- Institute for Communicable Disease Control and Prevention, Shandong provincial Center for Disease Control and Prevention, Jinan, Shandong, China
| | - Yan Li
- Institute for Communicable Disease Control and Prevention, Shandong provincial Center for Disease Control and Prevention, Jinan, Shandong, China
| | - Jianmei Yu
- Institute for Communicable Disease Control and Prevention, Shandong provincial Center for Disease Control and Prevention, Jinan, Shandong, China
- Department of public health and health management, Shandong First Medical University, Jinan, Shandong, China
| | - Lixiao Cheng
- Institute for Communicable Disease Control and Prevention, Shandong provincial Center for Disease Control and Prevention, Jinan, Shandong, China
| | - Shujun Ding
- Institute for Communicable Disease Control and Prevention, Shandong provincial Center for Disease Control and Prevention, Jinan, Shandong, China
| | - Zengqiang Kou
- Institute for Communicable Disease Control and Prevention, Shandong provincial Center for Disease Control and Prevention, Jinan, Shandong, China.
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Zhu Z, Feng Y, Gu L, Guan X, Liu N, Zhu X, Gu H, Cai J, Li X. Spatio-temporal pattern and associate factors of intestinal infectious diseases in Zhejiang Province, China, 2008-2021: a Bayesian modeling study. BMC Public Health 2023; 23:1652. [PMID: 37644452 PMCID: PMC10464402 DOI: 10.1186/s12889-023-16552-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2023] [Accepted: 08/17/2023] [Indexed: 08/31/2023] Open
Abstract
BACKGROUND Despite significant progress in sanitation status and public health awareness, intestinal infectious diseases (IID) have caused a serious disease burden in China. Little was known about the spatio-temporal pattern of IID at the county level in Zhejiang. Therefore, a spatio-temporal modelling study to identify high-risk regions of IID incidence and potential risk factors was conducted. METHODS Reported cases of notifiable IID from 2008 to 2021 were obtained from the China Information System for Disease Control and Prevention. Moran's I index and the local indicators of spatial association (LISA) were calculated using Geoda software to identify the spatial autocorrelation and high-risk areas of IID incidence. Bayesian hierarchical model was used to explore socioeconomic and climate factors affecting IID incidence inequities from spatial and temporal perspectives. RESULTS From 2008 to 2021, a total of 101 cholera, 55,298 bacterial dysentery, 131 amoebic dysentery, 5297 typhoid, 2102 paratyphoid, 27,947 HEV, 1,695,925 hand, foot and mouth disease (HFMD), and 1,505,797 other infectious diarrhea (OID) cases were reported in Zhejiang Province. The hot spots for bacterial dysentery, OID, and HEV incidence were found mainly in Hangzhou, while high-high cluster regions for incidence of enteric fever and HFMD were mainly located in Ningbo. The Bayesian model showed that Areas with a high proportion of males had a lower risk of BD and enteric fever. People under the age of 18 may have a higher risk of IID. High urbanization rate was a protective factor against HFMD (RR = 0.91, 95% CI: 0.88, 0.94), but was a risk factor for HEV (RR = 1.06, 95% CI: 1.01-1.10). BD risk (RR = 1.14, 95% CI: 1.10-1.18) and enteric fever risk (RR = 1.18, 95% CI:1.10-1.27) seemed higher in areas with high GDP per capita. The greater the population density, the higher the risk of BD (RR = 1.29, 95% CI: 1.23-1.36), enteric fever (RR = 1.12, 95% CI: 1.00-1.25), and HEV (RR = 1.15, 95% CI: 1.09-1.21). Among climate variables, higher temperature was associated with a higher risk of BD (RR = 1.32, 95% CI: 1.23-1.41), enteric fever (RR = 1.41, 95% CI: 1.33-1.50), and HFMD (RR = 1.22, 95% CI: 1.08-1.38), and with lower risk of HEV (RR = 0.83, 95% CI: 0.78-0.89). Precipitation was positively correlated with enteric fever (RR = 1.04, 95% CI: 1.00-1.08), HFMD (RR = 1.03, 95% CI: 1.00-1.06), and HEV (RR = 1.05, 95% CI: 1.03-1.08). Higher HFMD risk was also associated with increasing relative humidity (RR = 1.20, 95% CI: 1.16-1.24) and lower wind velocity (RR = 0.88, 95% CI: 0.84-0.92). CONCLUSIONS There was significant spatial clustering of IID incidence in Zhejiang Province from 2008 to 2021. Spatio-temporal patterns of IID risk could be largely explained by socioeconomic and meteorological factors. Preventive measures and enhanced monitoring should be taken in some high-risk counties in Hangzhou city and Ningbo city.
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Affiliation(s)
- Zhixin Zhu
- Department of Big Data in Health Science, and Center for Clinical Big Data and Statistics, The Second Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, 310058, China
| | - Yan Feng
- Department of Infectious Disease Control and Prevention, Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, 310051, China
| | - Lanfang Gu
- Department of Big Data in Health Science, and Center for Clinical Big Data and Statistics, The Second Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, 310058, China
| | - Xifei Guan
- Department of Big Data in Health Science, and Center for Clinical Big Data and Statistics, The Second Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, 310058, China
| | - Nawen Liu
- Department of Big Data in Health Science, and Center for Clinical Big Data and Statistics, The Second Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, 310058, China
| | - Xiaoxia Zhu
- Department of Big Data in Health Science, and Center for Clinical Big Data and Statistics, The Second Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, 310058, China
| | - Hua Gu
- The Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital), Institute of Basic Medicine and Cancer, Chinese Academy of Sciences, Hangzhou, 310022, China
| | - Jian Cai
- Department of Infectious Disease Control and Prevention, Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, 310051, China.
| | - Xiuyang Li
- Department of Big Data in Health Science, and Center for Clinical Big Data and Statistics, The Second Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, 310058, China.
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Ming BW, Yang Z, Yan ZL, Shi C, Xu XH, Li L, Ou CQ. Impact of urbanization on morbidity of hepatitis A: a national panel study in China during 2005-2018. Infect Dis Poverty 2023; 12:56. [PMID: 37231511 DOI: 10.1186/s40249-023-01104-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2023] [Accepted: 05/09/2023] [Indexed: 05/27/2023] Open
Abstract
BACKGROUND The effect of urbanization on the morbidity of hepatitis A remains unclear. We aimed to estimate the association between various urbanization-related indices and hepatitis A morbidity in China. METHODS Data on the annual morbidity of hepatitis A, urbanization-related measures (i.e., gross domestic product per capita, the number of hospitalization beds per 1000 persons, illiteracy rate, tap water coverage, motor vehicles per 100 persons, population density, and the proportion of arable land), and meteorological factors in 31 provincial-level administrative divisions of Chinese mainland during 2005-2018 were collected from the National Population and Health Science Data Sharing Platform, China Statistical Yearbooks, and the China Meteorological Data Sharing Service System, respectively. Generalized linear mixed models were applied to quantify the impacts of different urbanization-related indices on the morbidity of hepatitis A in China after adjusting for covariates. RESULTS A total of 537,466 hepatitis A cases were reported in China during 2005-2018. The annual morbidity had a decline of 79.4% from 5.64 cases to 1.16 cases per 100,000 people. There were obvious spatial variations with higher morbidity in western China. Nationally, gross domestic product per capita and the number of hospitalization beds per 1000 persons increased from 14,040 to 64,644 CNY and from 2.45 to 6.03 during 2005-2018, respectively. The illiteracy rate decreased from 11.0 to 4.9%. Gross domestic product per capita [relative risk (RR) = 0.96, 95% confidence interval (CI): 0.92-0.99], and the number of hospitalization beds per 1000 persons (RR = 0.79, 95% CI: 0.75-0.83) were associated with the declined morbidity of hepatitis A. By contrast, the increased morbidity of hepatitis A was linked to the illiteracy rate (RR = 1.04, 95% CI: 1.02-1.06). Similar influential factors were detected for children and adults, with greater effects witnessed for children. CONCLUSIONS People in the western region suffered the heaviest burden of hepatitis A in Chinese mainland. Nationally, there was a sharp decline in the morbidity of hepatitis A. The urbanization process was associated with the reduction of hepatitis A morbidity in China during 2005-2018.
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Affiliation(s)
- Bo-Wen Ming
- State Key Laboratory of Organ Failure Research, Department of Biostatistics, Guangdong Provincial Key Laboratory of Tropical Disease Research, School of Public Health, Southern Medical University, Guangzhou, 510515, Guangdong, China
| | - Zhou Yang
- State Key Laboratory of Organ Failure Research, Department of Biostatistics, Guangdong Provincial Key Laboratory of Tropical Disease Research, School of Public Health, Southern Medical University, Guangzhou, 510515, Guangdong, China
| | - Ze-Lin Yan
- State Key Laboratory of Organ Failure Research, Department of Biostatistics, Guangdong Provincial Key Laboratory of Tropical Disease Research, School of Public Health, Southern Medical University, Guangzhou, 510515, Guangdong, China
| | - Chen Shi
- State Key Laboratory of Organ Failure Research, Department of Biostatistics, Guangdong Provincial Key Laboratory of Tropical Disease Research, School of Public Health, Southern Medical University, Guangzhou, 510515, Guangdong, China
| | - Xiao-Han Xu
- State Key Laboratory of Organ Failure Research, Department of Biostatistics, Guangdong Provincial Key Laboratory of Tropical Disease Research, School of Public Health, Southern Medical University, Guangzhou, 510515, Guangdong, China
| | - Li Li
- State Key Laboratory of Organ Failure Research, Department of Biostatistics, Guangdong Provincial Key Laboratory of Tropical Disease Research, School of Public Health, Southern Medical University, Guangzhou, 510515, Guangdong, China.
| | - Chun-Quan Ou
- State Key Laboratory of Organ Failure Research, Department of Biostatistics, Guangdong Provincial Key Laboratory of Tropical Disease Research, School of Public Health, Southern Medical University, Guangzhou, 510515, Guangdong, China.
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Li CH, Mao JJ, Wu YJ, Zhang B, Zhuang X, Qin G, Liu HM. Combined impacts of environmental and socioeconomic covariates on HFMD risk in China: A spatiotemporal heterogeneous perspective. PLoS Negl Trop Dis 2023; 17:e0011286. [PMID: 37205641 DOI: 10.1371/journal.pntd.0011286] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2022] [Accepted: 04/05/2023] [Indexed: 05/21/2023] Open
Abstract
BACKGROUND Understanding geospatial impacts of multi-sourced influencing factors on the epidemic of hand-foot-and-mouth disease (HFMD) is of great significance for formulating disease control policies tailored to regional-specific needs, yet the knowledge is very limited. We aim to identify and further quantify the spatiotemporal heterogeneous effects of environmental and socioeconomic factors on HFMD dynamics. METHODS We collected monthly province-level HFMD incidence and related environmental and socioeconomic data in China during 2009-2018. Hierarchical Bayesian models were constructed to investigate the spatiotemporal relationships between regional HFMD and various covariates: linear and nonlinear effects for environmental covariates, and linear effects for socioeconomic covariates. RESULTS The spatiotemporal distribution of HFMD cases was highly heterogeneous, indicated by the Lorenz curves and the corresponding Gini indices. The peak time (R2 = 0.65, P = 0.009), annual amplitude (R2 = 0.94, P<0.001), and semi-annual periodicity contribution (R2 = 0.88, P<0.001) displayed marked latitudinal gradients in Central China region. The most likely cluster areas for HFMD were located in south China (Guangdong, Guangxi, Hunan, Hainan) from April 2013 to October 2017. The Bayesian models achieved the best predictive performance (R2 = 0.87, P<0.001). We found significant nonlinear associations between monthly average temperature, relative humidity, normalized difference vegetation index and HFMD transmission. Besides, population density (RR = 1.261; 95%CI, 1.169-1.353), birth rate (RR = 1.058; 95%CI, 1.025-1.090), real GDP per capita (RR = 1.163; 95%CI, 1.033-1.310) and school vacation (RR = 0.507; 95%CI, 0.459-0.559) were identified to have positive or negative effects on HFMD respectively. Our model could successfully predict months with HFMD outbreaks versus non-outbreaks in provinces of China from Jan 2009 to Dec 2018. CONCLUSIONS Our study highlights the importance of refined spatial and temporal data, as well as environmental and socioeconomic information, on HFMD transmission dynamics. The spatiotemporal analysis framework may provide insights into adjusting regional interventions to local conditions and temporal variations in broader natural and social sciences.
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Affiliation(s)
- Chun-Hu Li
- Joint Division of Clinical Epidemiology, Affiliated Hospital of Nantong University, School of Public Health of Nantong University, Nantong, China
| | - Jun-Jie Mao
- Joint Division of Clinical Epidemiology, Affiliated Hospital of Nantong University, School of Public Health of Nantong University, Nantong, China
| | - You-Jia Wu
- Department of Pediatrics, Affiliated Hospital of Nantong University, Nantong, China
| | - Bin Zhang
- Department of Infectious Diseases, Affiliated Hospital of Nantong University, Nantong, China
| | - Xun Zhuang
- Department of Epidemiology and Biostatistics, School of Public Health of Nantong University, Nantong, China
| | - Gang Qin
- Joint Division of Clinical Epidemiology, Affiliated Hospital of Nantong University, School of Public Health of Nantong University, Nantong, China
- Department of Infectious Diseases, Affiliated Hospital of Nantong University, Nantong, China
| | - Hong-Mei Liu
- School of Transportation and Civil Engineering of Nantong University, Nantong, China
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Zhang N, Mou D, Li T, Chen Z, Ma C, Liang L, He Q. Integrated analysis reveals important differences in the gut and oropharyngeal microbiota between children with mild and severe hand, foot and mouth disease. Emerg Microbes Infect 2023; 12:2192819. [PMID: 36927539 PMCID: PMC10071984 DOI: 10.1080/22221751.2023.2192819] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/18/2023]
Abstract
Little is known about alternation and difference in gut microbiota between patients with mild and severe hand, foot and mouth disease (HFMD). We investigated the differences in gut and oropharynx microbiotas between mild and severe HFMD in young children and changes in bacterial profiles as the disease progresses from acute to convalescent phase. Forty-two patients with confirmed HFMD were studied, among which thirty-two had severe HFMD and ten had mild HFMD. First rectal swabs were collected from all patients at an average of 2 days (acute phase) after the onset of symptoms, and second rectal swabs were collected from 8 severe patients at day 9 (convalescent phase) after the onset. Oropharyngeal swabs were obtained from 10 patients in the acute phase and 6 in the convalescent phase. 16S rRNA sequencing was performed for all 70 samples. Compared with mild HFMD, severe HFMD exhibited significantly decreased diversity and richness of gut microbiota. Gut microbiota bacterial profiles observed in the acute and convalescent phases resembled each other, but differed from those in mild cases. Additionally, 50% of patients with severe HFMD in the acute phase harbored a dominant pathobiontic bacterial genus. However, none of patients with mild HFMD had such bacteria. Similar bacterial compositions in oropharynx microbiota were detected between mild and severe cases. Our findings indicate that severe HFMD exhibits significantly impaired diversity of gut microbiota and frequent gut and oropharyngeal inflammation-inducing bacteria. However, the results should be interpreted with caution as the number of the subjects was limited.
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Affiliation(s)
- Nan Zhang
- Department of Medical Microbiology, Capital Medical University. No. 10 Xi Tou Tiao, You'an Meng Wai, Feng Tai District, Beijing 100069, China (N.Z.: ; Z.C.: )
| | - Danlei Mou
- Department of Infectious Disease, Beijing Youan Hospital, Capital Medical University, No. 8 Xi TouTiao, You'an Men Wai, Feng Tai District, Beijing 100069, China (D.M.: ; T.L.: ; C.M.: ; L.L.: )
| | - Tongzeng Li
- Department of Infectious Disease, Beijing Youan Hospital, Capital Medical University, No. 8 Xi TouTiao, You'an Men Wai, Feng Tai District, Beijing 100069, China (D.M.: ; T.L.: ; C.M.: ; L.L.: )
| | - Zhiyun Chen
- Department of Medical Microbiology, Capital Medical University. No. 10 Xi Tou Tiao, You'an Meng Wai, Feng Tai District, Beijing 100069, China (N.Z.: ; Z.C.: )
| | - Chunhua Ma
- Department of Infectious Disease, Beijing Youan Hospital, Capital Medical University, No. 8 Xi TouTiao, You'an Men Wai, Feng Tai District, Beijing 100069, China (D.M.: ; T.L.: ; C.M.: ; L.L.: )
| | - Lianchun Liang
- Department of Infectious Disease, Beijing Youan Hospital, Capital Medical University, No. 8 Xi TouTiao, You'an Men Wai, Feng Tai District, Beijing 100069, China (D.M.: ; T.L.: ; C.M.: ; L.L.: )
| | - Qiushui He
- Department of Medical Microbiology, Capital Medical University. No. 10 Xi Tou Tiao, You'an Meng Wai, Feng Tai District, Beijing 100069, China (N.Z.: ; Z.C.: ).,Institute of Biomedicine, University of Turku, Kiinamyllynkatu 10, Turku 20520, Finland (Q.H.: )
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11
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Mei K, Kou R, Bi Y, Liu Y, Huang J, Li W. A study of primary health care service efficiency and its spatial correlation in China. BMC Health Serv Res 2023; 23:247. [PMID: 36915124 PMCID: PMC10012696 DOI: 10.1186/s12913-023-09197-x] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2022] [Accepted: 02/19/2023] [Indexed: 03/16/2023] Open
Abstract
BACKGROUND China's primary health care system has undergone major changes since the new round of medical reform in 2009, but the current status of primary health care institution service efficiency is still unsatisfactory. The purpose of this study is to compare and evaluate the China's primary health care institution service efficiency and provide a reference for improving the efficiency and promoting the development of primary health care institution. METHODS Based on panel data of 31 provinces (municipalities directly under the central government and autonomous regions) in mainland China from 2011 to 2020, using the super efficiency slack-based measure-data envelopment analysis model, to analyze the data from a static perspective, and the changes in the efficiency of primary health care services were analyzed from a dynamic perspective by using the Malmquist index method. Spatial autocorrelation analysis method was used to verify the spatial correlation of primary health care service efficiency among various regions. RESULTS The number of Primary health care institutions increased from 918,000 in 2011 to 970,000 in 2020. The average primary health care institution service efficiency in the northeastern region including Jilin (0.324), Heilongjiang (0.460), Liaoning (0.453) and northern regions such as Shaanxi (0.344) and Neimenggu (0.403) was at a low level, while the eastern coastal regions such as Guangdong (1.116), Zhejiang (1.211), Shanghai (1.402) have higher average service efficiency levels. The global Moran's I showed the existence of spatial autocorrelation, and the local Moran's I index suggested that the problem of uneven regional development was prominent, showing a contiguous regional distribution pattern. Among them, H-H (high-efficiency regions) were mainly concentrated in Jiangsu, Anhui and Shanghai, and L-L regions (low-efficiency regions) were mostly in northern and northeastern China. CONCLUSION The service efficiency of primary health care institution in China showed a rising trend in general, but the overall average efficiency was still at a low level, and there were significant geographical differences, which showed a spatial distribution of "high in the east and low in the west, high in the south and low in the north". The northwestern region, after receiving relevant support, has seen a rapid development of primary health care, and its efficiency was steadily improving and gradually reaching a high level. The average primary health care institution service efficiency in the northeastern region including the northern region of China was at a low level, while the average efficiency in the eastern coastal region and some economically developed regions was high, which also verifies the dependence and high symbiosis of primary health care institution service efficiency on regional economy.
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Affiliation(s)
- Kangni Mei
- School of Public Health, Weifang Medical University, Weifang, 261053, Shandong, China
| | - Ruxin Kou
- School of Public Health, Weifang Medical University, Weifang, 261053, Shandong, China
| | - Yuqing Bi
- School of Public Health, Weifang Medical University, Weifang, 261053, Shandong, China
| | - Yuzhuo Liu
- School of Management, Weifang Medical University, Weifang, 261053, Shandong, China
| | - Jingwen Huang
- School of Public Health, Weifang Medical University, Weifang, 261053, Shandong, China
| | - Wei Li
- School of Public Health, Weifang Medical University, Weifang, 261053, Shandong, China.
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Deng L, Han Y, Wang J, Liu H, Li G, Wang D, He G. Epidemiological Characteristics of Notifiable Respiratory Infectious Diseases in Mainland China from 2010 to 2018. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2023; 20:3946. [PMID: 36900957 PMCID: PMC10002032 DOI: 10.3390/ijerph20053946] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/27/2022] [Revised: 02/20/2023] [Accepted: 02/21/2023] [Indexed: 06/18/2023]
Abstract
Respiratory infectious diseases (RIDs) pose threats to people's health, some of which are serious public health problems. The aim of our study was to explore epidemic situations regarding notifiable RIDs and the epidemiological characteristics of the six most common RIDs in mainland China. We first collected the surveillance data of all 12 statutory notifiable RIDs for 31 provinces in mainland China that reported between 2010 and 2018, and then the six most prevalent RIDs were selected to analyze their temporal, seasonal, spatiotemporal and population distribution characteristics. From 2010 to 2018, there were 13,985,040 notifiable cases and 25,548 deaths from RIDs in mainland China. The incidence rate of RIDs increased from 109.85/100,000 in 2010 to 140.85/100,000 in 2018. The mortality from RIDs ranged from 0.18/100,000 to 0.24/100,000. The most common RIDs in class B were pulmonary tuberculosis (PTB), pertussis, and measles, while those in class C were seasonal influenza, mumps and rubella. From 2010 to 2018, the incidence rate of PTB and rubella decreased; however, pertussis and seasonal influenza increased, with irregular changes in measles and mumps. The mortality from PTB increased from 2015 to 2018, and the mortality from seasonal influenza changed irregularly. PTB was mainly prevalent among people over 15 years old, while the other five common RIDs mostly occurred among people younger than 15 years old. The incidence of the six common RIDs mostly occurred in winter and spring, and they were spatiotemporally clustered in different areas and periods. In conclusion, PTB, seasonal influenza and mumps remain as public health problems in China, suggesting that continuous government input, more precise interventions, and a high-tech digital/intelligent surveillance and warning system are required to rapidly identify emerging events and timely response.
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Affiliation(s)
- Lele Deng
- National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China
| | - Yajun Han
- National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China
| | - Jinlong Wang
- National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China
| | - Haican Liu
- State Key Laboratory for Infectious Disease Prevention and Control, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China
| | - Guilian Li
- State Key Laboratory for Infectious Disease Prevention and Control, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China
| | - Dayan Wang
- National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China
| | - Guangxue He
- National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China
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13
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Chen Y, Dai B, Han S, Duan G, Yang H, Chen S, Ji W, Jin Y. Arising Concerns of Atypical Manifestations in Patients with Hand, Foot, and Mouth Disease. Vaccines (Basel) 2023; 11:vaccines11020405. [PMID: 36851282 PMCID: PMC9966249 DOI: 10.3390/vaccines11020405] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2023] [Revised: 02/03/2023] [Accepted: 02/06/2023] [Indexed: 02/12/2023] Open
Abstract
Hand, foot, and mouth disease (HFMD) is a mild exanthematous, febrile disease, but it also remains a threat to global public health. HFMD is characterized by a brief febrile illness in children and with a typical skin rash of the hand and foot, with or without mouth ulcers. However, the morphology and distribution of vesicles, as well as accompanying symptoms, are varied among atypical HFMD. An upsurge in atypical presentations of HFMD caused by Coxsackievirus A6 (CVA6), including Gianotti-Crosti-like eruptions, eczema coxsackium, petechial/purpuric eruption, and vesiculobullous exanthema, can be difficult to diagnose clinically as it may mimic other severe skin diseases, such as eczema herpeticum, varicella, disseminated zoster, and erythema multiforme major. The recognition of the distinguishing features of atypical HFMD is vital for an accurate and timely diagnosis, as is initiating appropriate laboratory evaluation and supportive care. Clinicians must identify the wide range of cutaneous and mucosal alterations caused by atypical HFMD. A systemic, high-quality overview of atypical HFMD is needed for advances in better strategies for clinical diagnosis and treatment. Hence, this review is aimed at summarizing the available data on clinical investigations and differential diagnostics to provide a scientific guide for the timely diagnosis of HFMD for preventing serious complications.
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Affiliation(s)
- Yu Chen
- Department of Epidemiology, College of Public Health, Zhengzhou University, Zhengzhou 450001, China
| | - Bowen Dai
- Department of Epidemiology, College of Public Health, Zhengzhou University, Zhengzhou 450001, China
| | - Shujie Han
- Department of Epidemiology, College of Public Health, Zhengzhou University, Zhengzhou 450001, China
| | - Guangcai Duan
- Department of Epidemiology, College of Public Health, Zhengzhou University, Zhengzhou 450001, China
- Academy of Medical Sciences, Zhengzhou University, Zhengzhou 450001, China
| | - Haiyan Yang
- Department of Epidemiology, College of Public Health, Zhengzhou University, Zhengzhou 450001, China
| | - Shuaiyin Chen
- Department of Epidemiology, College of Public Health, Zhengzhou University, Zhengzhou 450001, China
| | - Wangquan Ji
- Department of Epidemiology, College of Public Health, Zhengzhou University, Zhengzhou 450001, China
- Academy of Medical Sciences, Zhengzhou University, Zhengzhou 450001, China
- Correspondence: (W.J.); (Y.J.)
| | - Yuefei Jin
- Department of Epidemiology, College of Public Health, Zhengzhou University, Zhengzhou 450001, China
- Correspondence: (W.J.); (Y.J.)
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14
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Zheng J, Zhang N, Shen G, Liang F, Zhao Y, He X, Wang Y, He R, Chen W, Xue H, Shen Y, Fu Y, Zhang WH, Zhang L, Bhatt S, Mao Y, Zhu B. Spatiotemporal and Seasonal Trends of Class A and B Notifiable Infectious Diseases in China: A Retrospective Analysis (Preprint). JMIR Public Health Surveill 2022; 9:e42820. [PMID: 37103994 PMCID: PMC10176137 DOI: 10.2196/42820] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2022] [Revised: 03/27/2023] [Accepted: 03/29/2023] [Indexed: 03/31/2023] Open
Abstract
BACKGROUND China is the most populous country globally and has made significant achievements in the control of infectious diseases over the last decades. The 2003 SARS epidemic triggered the initiation of the China Information System for Disease Control and Prevention (CISDCP). Since then, numerous studies have investigated the epidemiological features and trends of individual infectious diseases in China; however, few considered the changing spatiotemporal trends and seasonality of these infectious diseases over time. OBJECTIVE This study aims to systematically review the spatiotemporal trends and seasonal characteristics of class A and class B notifiable infectious diseases in China during 2005-2020. METHODS We extracted the incidence and mortality data of 8 types (27 diseases) of notifiable infectious diseases from the CISDCP. We used the Mann-Kendall and Sen's methods to investigate the diseases' temporal trends, Moran I statistic for their geographical distribution, and circular distribution analysis for their seasonality. RESULTS Between January 2005 and December 2020, 51,028,733 incident cases and 261,851 attributable deaths were recorded. Pertussis (P=.03), dengue fever (P=.01), brucellosis (P=.001), scarlet fever (P=.02), AIDS (P<.001), syphilis (P<.001), hepatitis C (P<.001) and hepatitis E (P=.04) exhibited significant upward trends. Furthermore, measles (P<.001), bacillary and amebic dysentery (P<.001), malaria (P=.04), dengue fever (P=.006), brucellosis (P=.03), and tuberculosis (P=.003) exhibited significant seasonal patterns. We observed marked disease burden-related geographic disparities and heterogeneities. Notably, high-risk areas for various infectious diseases have remained relatively unchanged since 2005. In particular, hemorrhagic fever and brucellosis were largely concentrated in Northeast China; neonatal tetanus, typhoid and paratyphoid, Japanese encephalitis, leptospirosis, and AIDS in Southwest China; BAD in North China; schistosomiasis in Central China; anthrax, tuberculosis, and hepatitis A in Northwest China; rabies in South China; and gonorrhea in East China. However, the geographical distribution of syphilis, scarlet fever, and hepatitis E drifted from coastal to inland provinces during 2005-2020. CONCLUSIONS The overall infectious disease burden in China is declining; however, hepatitis C and E, bacterial infections, and sexually transmitted infections continue to multiply, many of which have spread from coastal to inland provinces.
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Affiliation(s)
- Junyao Zheng
- China Institute for Urban Governance, Shanghai Jiao Tong University, Shanghai, China
- School of International and Public Affairs, Shanghai Jiao Tong University, Shanghai, China
| | - Ning Zhang
- School of Public Policy and Administration, Xi'an Jiaotong University, Xi'an, China
| | - Guoquan Shen
- School of Public Administration and Policy, Renmin University of China, Beijing, China
| | - Fengchao Liang
- School of Public Health and Emergency Management, Southern University of Science and Technology, Shenzhen, China
| | - Yang Zhao
- The George Institute for Global Health, Peking University Health Science Center, Beijing, China
- WHO Collaborating Centre on Implementation Research for Prevention and Control of Noncommunicable Diseases, Melbourne, Australia
| | - Xiaochen He
- School of Public Policy and Administration, Xi'an Jiaotong University, Xi'an, China
| | - Ying Wang
- School of Public Policy and Administration, Xi'an Jiaotong University, Xi'an, China
| | - Rongxin He
- Vanke School of Public Health, Tsinghua University, Beijing, China
| | - Wenna Chen
- Center for Chinese Public Administration Research and School of Government, Sun Yat-sen University, Guangzhou, China
| | - Hao Xue
- Stanford Center on China's Economy and Institutions, Stanford University, Stanford, CA, United States
| | - Yue Shen
- Laboratory for Urban Future, School of Urban Planning and Design, Peking University Shenzhen Graduate School, Shenzhen, China
| | - Yang Fu
- Department of public administration, School of Government, Shenzhen University, Shenzhen, China
| | - Wei-Hong Zhang
- International Centre for Reproductive Health, Department of Public Health and Primary Care, Ghent University, Ghent, Belgium
| | - Lei Zhang
- China-Australia Joint Research Center for Infectious Diseases, School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an, China
- Artificial Intelligence and Modelling in Epidemiology Program, Melbourne Sexual Health Centre, Alfred Health, Melbourne, Australia
- Central Clinical School, Faculty of Medicine, Monash University, Melbourne, Australia
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, China
| | - Samir Bhatt
- MRC Centre for Global Infectious Disease Analysis and the Abdul Latif Jameel Institute for Disease and Emergency Analytics, School of Public Health, Imperial College, London, United Kingdom
- Section of Epidemiology, Department of Public Health, University of Copenhagen, Copenhagen, Denmark
| | - Ying Mao
- School of Public Policy and Administration, Xi'an Jiaotong University, Xi'an, China
| | - Bin Zhu
- School of Public Health and Emergency Management, Southern University of Science and Technology, Shenzhen, China
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15
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Zheng J, Shen G, Hu S, Han X, Zhu S, Liu J, He R, Zhang N, Hsieh CW, Xue H, Zhang B, Shen Y, Mao Y, Zhu B. Small-scale spatiotemporal epidemiology of notifiable infectious diseases in China: a systematic review. BMC Infect Dis 2022; 22:723. [PMID: 36064333 PMCID: PMC9442567 DOI: 10.1186/s12879-022-07669-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2022] [Accepted: 08/03/2022] [Indexed: 11/20/2022] Open
Abstract
Background The prevalence of infectious diseases remains one of the major challenges faced by the Chinese health sector. Policymakers have a tremendous interest in investigating the spatiotemporal epidemiology of infectious diseases. We aimed to review the small-scale (city level, county level, or below) spatiotemporal epidemiology of notifiable infectious diseases in China through a systematic review, thus summarizing the evidence to facilitate more effective prevention and control of the diseases. Methods We searched four English language databases (PubMed, EMBASE, Cochrane Library, and Web of Science) and three Chinese databases (CNKI, WanFang, and SinoMed), for studies published between January 1, 2004 (the year in which China’s Internet-based disease reporting system was established) and December 31, 2021. Eligible works were small-scale spatial or spatiotemporal studies focusing on at least one notifiable infectious disease, with the entire territory of mainland China as the study area. Two independent reviewers completed the review process based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Results A total of 18,195 articles were identified, with 71 eligible for inclusion, focusing on 22 diseases. Thirty-one studies (43.66%) were analyzed using city-level data, 34 (47.89%) were analyzed using county-level data, and six (8.45%) used community or individual data. Approximately four-fifths (80.28%) of the studies visualized incidence using rate maps. Of these, 76.06% employed various spatial clustering methods to explore the spatial variations in the burden, with Moran’s I statistic being the most common. Of the studies, 40.85% explored risk factors, in which the geographically weighted regression model was the most commonly used method. Climate, socioeconomic factors, and population density were the three most considered factors. Conclusions Small-scale spatiotemporal epidemiology has been applied in studies on notifiable infectious diseases in China, involving spatiotemporal distribution and risk factors. Health authorities should improve prevention strategies and clarify the direction of future work in the field of infectious disease research in China. Supplementary Information The online version contains supplementary material available at 10.1186/s12879-022-07669-9.
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Affiliation(s)
- Junyao Zheng
- China Institute for Urban Governance, Shanghai Jiao Tong University, Shanghai, China.,School of International and Public Affairs, Shanghai Jiao Tong University, Shanghai, China
| | - Guoquan Shen
- School of Public Administration and Policy, Renmin University of China, Beijing, China
| | - Siqi Hu
- School of Public Policy and Administration, Xi'an Jiaotong University, Xi'an, China
| | - Xinxin Han
- School of Public Health and Emergency Management, Southern University of Science and Technology, Shenzhen, 518055, Guangdong, China
| | - Siyu Zhu
- School of Public Policy and Administration, Xi'an Jiaotong University, Xi'an, China
| | - Jinlin Liu
- School of Public Policy and Administration, Northwestern Polytechnical University, Xi'an, China
| | - Rongxin He
- Vanke School of Public Health, Tsinghua University, Beijing, China
| | - Ning Zhang
- School of Public Policy and Administration, Xi'an Jiaotong University, Xi'an, China.,MRC Centre for Global Infectious Disease Analysis and the Abdul Latif Jameel Institute for Disease and Emergency Analytics, School of Public Health, Imperial College, London, UK
| | - Chih-Wei Hsieh
- Department of Public Policy, City University of Hong Kong, Hong Kong, China
| | - Hao Xue
- Freeman Spogli Institute for International Studies, Stanford University, Stanford, CA, USA
| | - Bo Zhang
- Department of Earth System Science, Tsinghua University, Beijing, China
| | - Yue Shen
- Laboratory for Urban Future, School of Urban Planning and Design, Peking University Shenzhen Graduate School, Shenzhen, China
| | - Ying Mao
- School of Public Policy and Administration, Xi'an Jiaotong University, Xi'an, China
| | - Bin Zhu
- School of Public Health and Emergency Management, Southern University of Science and Technology, Shenzhen, 518055, Guangdong, China.
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16
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Wang RN, Zhang YC, Yu BT, He YT, Li B, Zhang YL. Spatio-temporal evolution and trend prediction of the incidence of Class B notifiable infectious diseases in China: a sample of statistical data from 2007 to 2020. BMC Public Health 2022; 22:1208. [PMID: 35715790 PMCID: PMC9204078 DOI: 10.1186/s12889-022-13566-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2022] [Accepted: 05/23/2022] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND With the accelerated global integration and the impact of climatic, ecological and social environmental changes, China will continue to face the challenge of the outbreak and spread of emerging infectious diseases and traditional ones. This study aims to explore the spatial and temporal evolutionary characteristics of the incidence of Class B notifiable infectious diseases in China from 2007 to 2020, and to forecast the trend of it as well. Hopefully, it will provide a reference for the formulation of infectious disease prevention and control strategies. METHODS Data on the incidence rates of Class B notifiable infectious diseases in 31 provinces, municipalities and autonomous regions of China from 2007 to 2020 were collected for the prediction of the spatio-temporal evolution and spatial correlation as well as the incidence of Class B notifiable infectious diseases in China based on global spatial autocorrelation and Autoregressive Integrated Moving Average (ARIMA). RESULTS From 2007 to 2020, the national incidence rate of Class B notifiable infectious diseases (from 272.37 per 100,000 in 2007 to 190.35 per 100,000 in 2020) decreases year by year, and the spatial distribution shows an "east-central-west" stepwise increase. From 2007 to 2020, the spatial clustering of the incidence of Class B notifiable infectious diseases is significant and increasing year by year (Moran's I index values range from 0.189 to 0.332, p < 0.05). The forecasted incidence rates of Class B notifiable infectious diseases nationwide from 2021 to 2024 (205.26/100,000, 199.95/100,000, 194.74/100,000 and 189.62/100,000) as well as the forecasted values for most regions show a downward trend, with only some regions (Guangdong, Hunan, Hainan, Tibet, Guangxi and Guizhou) showing an increasing trend year by year. CONCLUSIONS The current study found that since there were significant regional disparities in the prevention and control of infectious diseases in China between 2007 and 2020, the reduction of the incidence of Class B notifiable infectious diseases requires the joint efforts of the surrounding provinces. Besides, special attention should be paid to provinces with an increasing trend in the incidence of Class B notifiable infectious diseases to prevent the re-emergence of certain traditional infectious diseases in a particular province or even the whole country, as well as the outbreak and spread of emerging infectious diseases.
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Affiliation(s)
- Ruo-Nan Wang
- School of Health Management, Southern Medical University, Guangzhou, 510515, China
| | - Yue-Chi Zhang
- Bussiness School, University of Aberdeen, Aberdeen, UK
| | - Bo-Tao Yu
- School of Health Management, Southern Medical University, Guangzhou, 510515, China
| | - Yan-Ting He
- School of Health Management, Southern Medical University, Guangzhou, 510515, China
| | - Bei Li
- School of Health Management, Southern Medical University, Guangzhou, 510515, China.
| | - Yi-Li Zhang
- School of Health Management, Southern Medical University, Guangzhou, 510515, China.
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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] [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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18
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Liu R, Chen Y, Liu H, Huang X, Zhou F. Epidemiological trends and sociodemographic factors associated with acute hemorrhagic conjunctivitis in mainland China from 2004 to 2018. Virol J 2022; 19:34. [PMID: 35232483 PMCID: PMC8889670 DOI: 10.1186/s12985-022-01758-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2021] [Accepted: 02/08/2022] [Indexed: 11/30/2022] Open
Abstract
Background Acute hemorrhagic conjunctivitis (AHC) is classified as a class C notifiable infectious disease in China and poses a great threat to public health. This study aimed to investigate the epidemiological trends and hotspots of AHC in mainland China. Sociodemographic factors that could contribute to early warning of AHC were further explored. Methods Yearly and monthly incidences of acute hemorrhagic conjunctivitis by date and region from 2004 to 2018 were extracted from the Data Center of China Public Health Science. Joinpoint regression and spatial autocorrelation analysis were performed to explore the epidemiological trends and hotspots of AHC. A generalized linear model was then applied to explore the relationship between sociodemographic factors and AHC incidence. Results The average annual AHC incidence was 3.58/100,000 in mainland China. The first-level spatial and temporal aggregation areas were distributed in Guangxi, Hainan, Guangdong, Guizhou, Hunan, Jiangxi, Fujian, Chongqing, Hubei, Anhui, and Zhejiang, with gathering times from 2010/1/1 to 2010/12/31 (RR = 20.13, LLR = 474,522.89, P < 0.01). After 2010, the AHC incidence was stable (APC = − 8.37, 95% CI: − 23.02–9.06). However, it was significantly increased in low- and middle-income provinces (AAPC = 10.65, 95% CI: 0.62–21.68, AAPC = 11.94, 95% CI: 0.62–24.53). The peak of AHC occurred during the August to October period. Children who age 0–3 years are identified as high-risk group with AHC incidence significantly increased (APC = 31.54, 95% CI: 0.27–72.56). Birth rate, population ages 0–14 (% of total population), passenger traffic, and urban population (% of total population) were positively associated with the AHC incidence, while per capita gross domestic product was negatively associated with the AHC incidence. Conclusion Overall, the AHC incidence was stable after 2010 in China, but it was significantly increased in low- and middle-income provinces. Regions with a high birth rate, population ages 0–14 (% of the total population), passenger traffic, urban population (% of the total population) and low per capita gross domestic product are at high risk of incidences of AHC. In the future, public health policy and resource priority for AHC in regions with these characteristics are necessary. Supplementary Information The online version contains supplementary material available at 10.1186/s12985-022-01758-6.
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Affiliation(s)
- Rong Liu
- Institute for Disaster Management and Reconstruction, Sichuan University, Chengdu, 610000, China
| | - Yuxing Chen
- Institute of Chronic and Non-Communicable Disease Control and Prevention, Hubei Provincial Center for Disease Control and Prevention, No. 35 Zhuodaoquan North Road, Hongshan District, Wuhan, 430079, China
| | - Hao Liu
- Institute of Chronic and Non-Communicable Disease Control and Prevention, Hubei Provincial Center for Disease Control and Prevention, No. 35 Zhuodaoquan North Road, Hongshan District, Wuhan, 430079, China
| | - Xihui Huang
- Subject Teaching (English), College of Foreign Languages, Fujian Normal University, Fuzhou, 350000, China
| | - Fang Zhou
- Institute of Chronic and Non-Communicable Disease Control and Prevention, Hubei Provincial Center for Disease Control and Prevention, No. 35 Zhuodaoquan North Road, Hongshan District, Wuhan, 430079, China.
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19
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Chen J, Lin Z, Li LA, Li J, Wang Y, Pan Y, Yang J, Xu C, Zeng X, Xie X, Xiao L. Ten years of China's new healthcare reform: a longitudinal study on changes in health resources. BMC Public Health 2021; 21:2272. [PMID: 34903184 PMCID: PMC8670033 DOI: 10.1186/s12889-021-12248-9] [Citation(s) in RCA: 25] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2021] [Accepted: 11/16/2021] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND China launched a new round of healthcare-system reform in 2009 and proposed the goal of equal and guaranteed essential medical and health services for all by 2020. We aimed to investigate the changes in China's health resources over the past ten years after the healthcare reform. METHODS Data were collected from the China Statistical Yearbook and China Health Statistics Yearbook from 2009 to 2018. Four categories and ten indicators of health resources were analyzed. A descriptive analysis was used to present the overall condition. The Health Resource Density Index was applied to showcase health-resource distribution in demographic and geographic dimensions. The global and local Moran's I were used to assess the spatial autocorrelation of health resources. Concentration Index (CI) was used to quantify the equity of health-resource distribution. A Geo-Detector model and Geographic Weighted Regression (GWR) were applied to assess the association between gross domestic product (GDP) per capita and health resources. RESULTS Health resources have increased over the past ten years. The global and local Moran's I suggested spatial aggregation in the distribution of health resources. Hospital beds were concentrated in wealthier areas, but this inequity decreased yearly (from CI=0.0587 in 2009 to CI=0.0021 in 2018). Primary medical and health institutions (PMHI) and their beds were concentrated in poorer areas (CI remained negative). Healthcare employees were concentrated in wealthier areas (CI remained positive). In 2017, the q-statistics indicated that the explanatory power of GDP per capita to beds, health personnel, and health expenditure was 40.7%, 50.3%, and 42.5%, respectively. The coefficients of GWR remained positive with statistical significance, indicating the positive association between GDP per capita and health resources. CONCLUSIONS From 2009 to 2018, the total amount of health resources in China has increased substantially. Spatial aggregation existed in the health-resources distribution. Health resources tended to be concentrated in wealthier areas. When allocating health resources, the governments should take economic factors into account.
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Affiliation(s)
- Jiang Chen
- Department of Medical Affairs, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Zhuochen Lin
- Department of Medical Affairs, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Li-An Li
- Department of Medical Affairs, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Jing Li
- Department of Medical Affairs, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Yuyao Wang
- Department of Medical Affairs, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Yu Pan
- Department of Medical Affairs, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Jie Yang
- Department of Medical Affairs, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Chuncong Xu
- Department of Medical Affairs, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Xiaojing Zeng
- Department of Medical Affairs, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Xiaoxu Xie
- School of Public Health, Fujian Medical University, Fuzhou, China.
| | - Liangcheng Xiao
- Department of Medical Affairs, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.
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20
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Zhang Y, Zhang M, Kang D, Sun W, Yang C, Wei R. Spatio-temporal analysis of bacillary dysentery in Sichuan province, China, 2011-2019. BMC Infect Dis 2021; 21:1033. [PMID: 34602058 PMCID: PMC8489051 DOI: 10.1186/s12879-021-06738-9] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2021] [Accepted: 09/24/2021] [Indexed: 11/23/2022] Open
Abstract
Background Bacillary dysentery (BD) is a common infectious disease in China and causes enormous economic burdens. The purpose of this study was to describe the epidemiological characteristics of BD and to identify its possible hot spots and potentially high-risk areas in Sichuan province of China. Methods In this study, we collected monthly BD incidence reports of 181 counties in Sichuan province, China, from January 2011 to December 2019. Descriptive statistics were used to evaluate the epidemic characteristics of BD. Moran’s I index was applied to investigate the yearly patterns of the spatial distribution. And spatio-temporal scanning statistics with the spatial unit set as county and the temporal unit set as month were used to investigate the possible high-risk region. Meanwhile, the circular moving windows were also employed in the spatio-temporal scanning to scan the study areas. Results The annual incidence of BD ranged between 16.13/100,000 and 6.17/100,000 person-years from 2011 to 2019 in Sichuan. The majority of the cases were children aged 5 years or younger. For the descriptive statistics, a peak from May to October was observed in temporal analysis, the epidemics were mainly concentrated in the northwest and southwest of Sichuan in spatial analysis. After 2016, the scope of BD significantly narrowed and severe epidemic areas were relatively stable. For the spatial autocorrelation analysis, a high global autocorrelation was observed at the county level, and the high–high clusters mainly distributed in the northwest and southwest of Sichuan. For the spatio-temporal scanning, the spatiotemporal clusters of BD occurred every year from 2011 to 2019. The most likely cluster areas mainly distributed in the southwest and northwest of Sichuan at the beginning, and then gradually concentrated in the southwest. The secondary cluster mainly concentrated in the northwest and its surrounding areas. Moreover, the 2nd secondary cluster was relatively small and mainly distributed in the central area. No clusters were noted in eastern Sichuan. Conclusions Based on our current analysis, BD is still a common challenge in Sichuan, especially for counties in the southwest and northwest in summer and autumn. More disease prevention and control measures should be taken in such higher-risk susceptible areas at a certain time to allocate the public health resources rationally, and finally reduce the spread of BD.
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Affiliation(s)
- Yao Zhang
- Department of Emergency Management, Sichuan Center for Diseases Control and Prevention, Chengdu, 610041, China
| | - Mengyuan Zhang
- Department of Emergency Management, Sichuan Center for Diseases Control and Prevention, Chengdu, 610041, China
| | - Dianju Kang
- Department of Emergency Management, Sichuan Center for Diseases Control and Prevention, Chengdu, 610041, China
| | - Wei Sun
- Department of Emergency Management, Sichuan Center for Diseases Control and Prevention, Chengdu, 610041, China
| | - Changhong Yang
- Department of Emergency Management, Sichuan Center for Diseases Control and Prevention, Chengdu, 610041, China.
| | - Rongjie Wei
- Department of Emergency Management, Sichuan Center for Diseases Control and Prevention, Chengdu, 610041, China.
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21
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Guo X, Lan Z, Wen Y, Zheng C, Rong Z, Liu T, Chen S, Yang X, Zheng H, Wu W. Synbiotics Supplements Lower the Risk of Hand, Foot, and Mouth Disease in Children, Potentially by Providing Resistance to Gut Microbiota Dysbiosis. Front Cell Infect Microbiol 2021; 11:729756. [PMID: 34660342 PMCID: PMC8515124 DOI: 10.3389/fcimb.2021.729756] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2021] [Accepted: 08/27/2021] [Indexed: 11/17/2022] Open
Abstract
Background Hand, foot and mouth disease (HFMD) is an acute enterovirus-induced disease. Gut microbiota dysbiosis has been identified as a factor that plays an important role in enteral virus infection, but the gut microbiota profile in hand, foot and mouth disease has rarely been studied in a large population. Methods A total of 749 children (HFMD: n = 262, healthy control: n = 487) aged 2 to 7 years were recruited from hospitals and communities in the period from May to July, 2017. Clinical and demographical information was collected by trained personnel, and fecal samples were collected and processed for 16S ribosomal RNA(rRNA) gene sequencing. Results We observed a significant alteration in the microbiota profile of children with HFMD compared with that of control children. Patients with enteroviruses A71(EV71) positive had more dysbiotic gut microbiota than those with coxsackievirus A16 (CAV16) positive. We found that Prevotella and Streptococcus were enriched in children with HFMD, whereas beneficial bacteria, including Bifidobacterium and Faecalibacterium, were depleted. Children with synbiotics supplements had lower risk of HFMD and we observed that the gut microbiota of HFMD patients who were administered synbiotics exhibited potential resistance to the dysbiosis detected in HFMD. Conclusions This study suggested that the gut microbiota of patients with hand, foot and mouth disease exhibits dysbiosis and that synbiotics supplements potentially helps maintain the homeostasis of the gut flora.
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Affiliation(s)
- Xiaoying Guo
- Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China
- School of Public Health, Southern Medical University, Guangzhou, China
| | - Zixin Lan
- The Second Clinical Medical College, Southern Medical University, Guangzhou, China
| | - Yaling Wen
- School of Mathematics and Computational Science, Guilin University of Electronic Technology, Guangxi, China
| | - Chanjiao Zheng
- Modern Service Industry Department, Guangzhou Technician College, Guangzhou, China
| | - Zuhua Rong
- Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China
| | - Tao Liu
- Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China
| | - Siyi Chen
- Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China
| | - Xingfen Yang
- School of Public Health, Southern Medical University, Guangzhou, China
| | - Huimin Zheng
- Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China
| | - Wei Wu
- Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China
- School of Public Health, Southern Medical University, Guangzhou, China
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22
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Boudou M, Cleary E, ÓhAiseadha C, Garvey P, McKeown P, O'Dwyer J, Hynds P. Spatiotemporal epidemiology of cryptosporidiosis in the Republic of Ireland, 2008-2017: development of a space-time "cluster recurrence" index. BMC Infect Dis 2021; 21:880. [PMID: 34454462 PMCID: PMC8401175 DOI: 10.1186/s12879-021-06598-3] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2021] [Accepted: 08/22/2021] [Indexed: 11/24/2022] Open
Abstract
Background Ireland frequently reports the highest annual Crude Incidence Rates (CIRs) of cryptosporidiosis in the EU, with national CIRs up to ten times the EU average. Accordingly, the current study sought to examine the spatiotemporal trends associated with this potentially severe protozoan infection. Methods Overall, 4509 cases of infection from January 2008 to December 2017 were geo-referenced to a Census Small Area (SA), with an ensemble of geo-statistical approaches including seasonal decomposition, Local Moran’s I, and space–time scanning used to elucidate spatiotemporal patterns of infection. Results One or more confirmed cases were notified in 3413 of 18,641 Census SAs (18.3%), with highest case numbers occurring in the 0–5-year range (n = 2672, 59.3%). Sporadic cases were more likely male (OR 1.4) and rural (OR 2.4), with outbreak-related cases more likely female (OR 1.4) and urban (OR 1.5). Altogether, 55 space–time clusters (≥ 10 confirmed cases) of sporadic infection were detected, with three “high recurrence” regions identified; no large urban conurbations were present within recurrent clusters. Conclusions Spatiotemporal analysis represents an important indicator of infection patterns, enabling targeted epidemiological intervention and surveillance. Presented results may also be used to further understand the sources, pathways, receptors, and thus mechanisms of cryptosporidiosis in Ireland. Supplementary Information The online version contains supplementary material available at 10.1186/s12879-021-06598-3.
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Affiliation(s)
- M Boudou
- Environmental Sustainability and Health Institute (ESHI), Technological University Dublin, Greenway Hub, Grangegorman, Dublin 7, D07 H6K8, Republic of Ireland.
| | - E Cleary
- Environmental Sustainability and Health Institute (ESHI), Technological University Dublin, Greenway Hub, Grangegorman, Dublin 7, D07 H6K8, Republic of Ireland
| | - C ÓhAiseadha
- Department of Public Health, Health Service Executive (HSE), Dr. Steevens' Hospital, Dublin 8, Republic of Ireland
| | - P Garvey
- Health Protection Surveillance Centre, 25 Middle Gardiner Street, Dublin 1, Republic of Ireland
| | - P McKeown
- Health Protection Surveillance Centre, 25 Middle Gardiner Street, Dublin 1, Republic of Ireland
| | - J O'Dwyer
- School of Biological, Earth and Environmental Sciences, Environmental Research Institute (ERI), University College Cork, Cork, Republic of Ireland.,Irish Centre for Research in Applied Geosciences (iCRAG), University College Dublin, Dublin 4, Republic of Ireland
| | - Paul Hynds
- Environmental Sustainability and Health Institute (ESHI), Technological University Dublin, Greenway Hub, Grangegorman, Dublin 7, D07 H6K8, Republic of Ireland. .,Irish Centre for Research in Applied Geosciences (iCRAG), University College Dublin, Dublin 4, Republic of Ireland.
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Spatial-temporal heterogeneity and meteorological factors of hand-foot-and-mouth disease in Xinjiang, China from 2008 to 2016. PLoS One 2021; 16:e0255222. [PMID: 34339424 PMCID: PMC8328314 DOI: 10.1371/journal.pone.0255222] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2020] [Accepted: 07/12/2021] [Indexed: 12/23/2022] Open
Abstract
The study aims to depict the temporal and spatial distributions of hand-foot-and-mouth disease (HFMD) in Xinjiang, China and reveal the relationships between the incidence of HFMD and meteorological factors in Xinjiang. With the national surveillance data of HFMD in Xinjiang and meteorological parameters in the study area from 2008 to 2016, in GeoDetector Model, we examined the effects of meteorological factors on the incidence of HFMD in Xinjiang, China, tested the spatial-temporal heterogeneity of HFMD risk, and explored the temporal-spatial patterns of HFMD through the spatial autocorrelation analysis. From 2008 to 2016, the HFMD distribution showed a distinct seasonal pattern and HFMD cases typically occurred from May to July and peaked in June in Xinjiang. Relative humidity, precipitation, barometric pressure and temperature had the more significant influences on the incidence of HFMD than other meteorological factors with the explanatory power of 0.30, 0.29, 0.29 and 0.21 (P<0.000). The interaction between any two meteorological factors had a nonlinear enhancement effect on the risk of HFMD. The relative risk in Northern Xinjiang was higher than that in Southern Xinjiang. Global spatial autocorrelation analysis results indicated a fluctuating trend over these years: the positive spatial dependency on the incidence of HFMD in 2008, 2010, 2012, 2014 and 2015, the negative spatial autocorrelation in 2009 and a random distribution pattern in 2011, 2013 and 2016. Our findings revealed the correlation between meteorological factors and the incidence of HFMD in Xinjiang. The correlation showed obvious spatiotemporal heterogeneity. The study provides the basis for the government to control HFMD based on meteorological information. The risk of HFMD can be predicted with appropriate meteorological factors for HFMD prevention and control.
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Chen C, Guan Z, Huang C, Jiang D, Liu X, Zhou Y, Yan D, Zhang X, Zhou Y, Ding C, Lan L, Lin Y, Wu J, Li L, Yang S. Epidemiological Trends and Hotspots of Other Infectious Diarrhea (OID) in Mainland China: A Population-Based Surveillance Study From 2004 to 2017. Front Public Health 2021; 9:679853. [PMID: 34368054 PMCID: PMC8339203 DOI: 10.3389/fpubh.2021.679853] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2021] [Accepted: 06/03/2021] [Indexed: 12/17/2022] Open
Abstract
Background: The incidence of other infectious diarrhea (OID) ranked second in class C notifiable disease in China. It has posed a great threat to public health of all age groups. The aim of this study was to investigate the epidemiological trends and hotspots of OID in mainland China. Materials and Methods: Incidence and mortality data for OID stratified by date, age and region from 2004 to 2017 was extracted from the data-center of China public health science. Joinpoint regression and space-time analyses were performed to explore the epidemiological trends and hotspots of OID. Results: The average annual incidence of OID was 60.64/100,000 and it showed an increased trend in the mainland China especially after 2006 (APC = 4.12, 95 CI%: 2.06-6.21). Children of 0-4 year age group accounts for 60.00% (5,820,897/11,414,247) of all cases and its incidence continuously increased though 2004-2017 (APC = 6.65, 95 CI%: 4.39-8.96). The first-level spatial and temporal aggregation areas were located in Beijing and Tianjin, with the gathering time from 2005/1/1 to 2011/12/31 (RR = 5.52, LLR = 572893.59, P < 0.001). The secondary spatial and temporal aggregation areas covered Guangdong, Guangxi, Hainan and Guizhou from 2011/1/1 to 2017/12/31 (RR = 1.98, LLR = 242292.72, P < 0.001). OID of Tianjin and Beijing presented a decreased trend since 2006. However, the incidence of OID in Guangdong, Guangxi, Hainan and Guizhou showed increased trends through 2004-2017. Conclusion: Our study showed that OID showed a constantly increasing trend and brought considerable burden in China especially in the 0-4 age group. The high-risk periods and clusters of regions for OID were identified, which will help government develop disease-specific and location-specific interventive measures.
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Affiliation(s)
| | | | | | | | | | | | | | | | | | | | | | | | - Jie Wu
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Lanjuan Li
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Shigui Yang
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
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Ding L, Zhang N, Zhu B, Liu J, Wang X, Liu F, Mao Y. Spatiotemporal characteristics and meteorological determinants of hand, foot and mouth disease in Shaanxi Province, China: a county-level analysis. BMC Public Health 2021; 21:374. [PMID: 33596869 PMCID: PMC7890844 DOI: 10.1186/s12889-021-10385-9] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2020] [Accepted: 02/03/2021] [Indexed: 01/08/2023] Open
Abstract
BACKGROUND Hand, foot and mouth disease (HFMD) is one of the common intestinal infectious diseases worldwide and has caused huge economic and disease burdens in many countries. The average annual incidence rate of HFMD was 11.66% in Shaanxi during the time span from 2009 to 2018. There are distinct differences within Shaanxi, as it is a special region that crosses three temperature zones. Hence, in this study, a spatiotemporal analysis of Shaanxi was performed to reveal the characteristics of the distribution of HFMD and to explore the meteorological determinants of HFMD. METHODS The county-level and municipal data from Shaanxi Province from 2009 to 2018 were applied to research the spatiotemporal characteristics of HFMD and its meteorological determinants. Time series and spatial autocorrelation analyses were applied to assess the spatiotemporal characteristics of HFMD. This study used spatial econometric panel models to explore the relationship between HFMD and meteorological factors based on the data of 107 counties and 10 municipalities. RESULTS The incidence rate of HFMD displayed no variable trend throughout the whole research period. A high incidence rate of HFMD was observed from June to September, corresponding to a time when the climate is characterized by heavy rain, high temperature, and high humidity. The high-incidence areas were mainly located in the central region in Shaanxi, whereas the low-incidence spots were mainly found in Northern Shaanxi. Regarding the meteorological factors analysed in this study, in general, the incidence rate of HFMD in specific regions was positively associated with the rainfall, temperature and humidity. CONCLUSION These results could be applied by the government and the general public to take effective measures to prevent disease. Region-targeted policies could be enacted and implemented in the future according to specific situations in different areas and the relevant meteorological determinants. Additionally, meteorological conditions normally extend to a wide-ranging region; thus, cooperation among surrounding regions is necessary.
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Affiliation(s)
- Li Ding
- School of Humanities and Social Science, Xi’an Jiaotong University, Xi’an, China
- Health Commission of Xi’an, Xi’an, China
| | - Ning Zhang
- School of Public Policy and Administration, Xi’an Jiaotong University, Xi’an, China
- Research Center for the Belt and Road Health Policy and Health Technology Assessment, Xi’an Jiaotong University, Xi’an, China
| | - Bin Zhu
- Research Center for the Belt and Road Health Policy and Health Technology Assessment, Xi’an Jiaotong University, Xi’an, China
- Department of Public Policy, City University of Hong Kong, Hong Kong, China
| | - Jinlin Liu
- Research Center for the Belt and Road Health Policy and Health Technology Assessment, Xi’an Jiaotong University, Xi’an, China
- Water H. Shorenstein Asia-Pacific Research Center, Stanford University, Stanford, CA USA
| | - Xue Wang
- Research Center for the Belt and Road Health Policy and Health Technology Assessment, Xi’an Jiaotong University, Xi’an, China
- The Second Affiliated Hospital of Xi’an Jiaotong University, Xi’an, China
| | - Feng Liu
- Shaanxi Provincial Centre of Disease Control and Prevention, Xi’an, China
| | - Ying Mao
- School of Public Policy and Administration, Xi’an Jiaotong University, Xi’an, China
- Research Center for the Belt and Road Health Policy and Health Technology Assessment, Xi’an Jiaotong University, Xi’an, China
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Notifiable Respiratory Infectious Diseases in China: A Spatial-Temporal Epidemiology Analysis. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2020; 17:ijerph17072301. [PMID: 32235375 PMCID: PMC7177391 DOI: 10.3390/ijerph17072301] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/19/2019] [Revised: 03/25/2020] [Accepted: 03/26/2020] [Indexed: 12/21/2022]
Abstract
Nowadays, tuberculosis, scarlet fever, measles, influenza, and mumps are five major notifiable respiratory infectious diseases (RIDs) in China. The objective of this study was to describe, visualize, and compare the spatial-temporal distributions of these five RIDs from 2006 to 2016. In addition to descriptive epidemiology analysis, seasonality and spatial autocorrelation analysis were also applied to explore the epidemiologic trends and spatial changing patterns of the five RIDs, respectively. The results indicated that the incidence of tuberculosis, measles, and mumps presented a downtrend trend, while those of scarlet fever and influenza was in a strong uptrend across the research period. The incidences of the five diseases all peaked in spring. There were significant spatial disparities in the distribution of tuberculosis, scarlet fever, and measles cases, with the hotspots mainly located in the western plateau region, northern plain region, and southern mountainous region. To conclude, notable epidemiological differences were observed across regions, indicating that some provincial units should pay more attention to prevent and control respiratory infectious diseases.
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Spatiotemporal Epidemiology of Varicella in Chongqing, China, 2014-2018. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2020; 17:ijerph17020662. [PMID: 31968545 PMCID: PMC7013978 DOI: 10.3390/ijerph17020662] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/20/2019] [Revised: 01/15/2020] [Accepted: 01/16/2020] [Indexed: 12/23/2022]
Abstract
Although immunization against varicella using vaccines has been proven to be significant and effective in the past decades, varicella remains a major public health concern for many developing countries. Varicella vaccination has not been introduced into routine immunization programs in China, and varicella outbreaks have continued to occur. Taking the city of Chongqing, which has a high prevalence of varicella, as an example, this study explored the spatiotemporal epidemiology of varicella. Based on the reported data of varicella cases from 1 January 2014 to 31 December 2018 in Chongqing, hot spots and space-time clusters of varicella were identified using spatial autocorrelation analysis and scan statistics. Within this period, a total of 112,273 varicella cases were reported in Chongqing (average annual incidence: 73.44 per 100,000), including one death. The incidence of varicella showed an increasing trend with significant seasonal peaks, which occurred during April to July and October to January of the following year. The total ratio of male to female patients affected was 1.10:1. Children under the age of 15 and students accounted for the majority of the patient population. The hotspots detected through local spatial autocorrelation analysis, and the most likely clusters identified by scan analysis, were primarily in the main urban districts of Chongqing. The secondary clusters were mostly detected in northeast and southwest Chongqing. There were obvious spatial dependence and spatiotemporal clustering characteristics of varicella in Chongqing from 2014 to 2018. High-risk districts, populations, and peak periods were found in this study, which could be helpful in implementing varicella prevention and control programs, and in adjusting vaccination strategies for the varicella vaccine based on actual conditions.
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