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      Spatio-Temporal Epidemiology of Viral Hepatitis in China (2003–2015): Implications for Prevention and Control Policies

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          Abstract

          Viral hepatitis, as one of the most serious notifiable infectious diseases in China, takes heavy tolls from the infected and causes a severe economic burden to society, yet few studies have systematically explored the spatio-temporal epidemiology of viral hepatitis in China. This study aims to explore, visualize and compare the epidemiologic trends and spatial changing patterns of different types of viral hepatitis (A, B, C, E and unspecified, based on the classification of CDC) at the provincial level in China. The growth rates of incidence are used and converted to box plots to visualize the epidemiologic trends, with the linear trend being tested by chi-square linear by linear association test. Two complementary spatial cluster methods are used to explore the overall agglomeration level and identify spatial clusters: spatial autocorrelation analysis (measured by global and local Moran’s I) and space-time scan analysis. Based on the spatial autocorrelation analysis, the hotspots of hepatitis A remain relatively stable and gradually shrunk, with Yunnan and Sichuan successively moving out the high-high (HH) cluster area. The HH clustering feature of hepatitis B in China gradually disappeared with time. However, the HH cluster area of hepatitis C has gradually moved towards the west, while for hepatitis E, the provincial units around the Yangtze River Delta region have been revealing HH cluster features since 2005. The space-time scan analysis also indicates the distinct spatial changing patterns of different types of viral hepatitis in China. It is easy to conclude that there is no one-size-fits-all plan for the prevention and control of viral hepatitis in all the provincial units. An effective response requires a package of coordinated actions, which should vary across localities regarding the spatial-temporal epidemic dynamics of each type of virus and the specific conditions of each provincial unit.

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          GeoDa: An Introduction to Spatial Data Analysis

          Luc Anselin, Ibnu Syabri, Youngihn Kho (2006)
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            Spatial-Temporal Clusters and Risk Factors of Hand, Foot, and Mouth Disease at the District Level in Guangdong Province, China

            Te Deng, Yong Huang, Shicheng Yu … (2013)
            Objective Hand, foot, and mouth disease (HFMD) has posed a great threat to the health of children and become a public health priority in China. This study aims to investigate the epidemiological characteristics, spatial-temporal patterns, and risk factors of HFMD in Guangdong Province, China, and to provide scientific information for public health responses and interventions. Methods HFMD surveillance data from May 2008 to December 2011were provided by the Chinese Center for Disease Control and Prevention. We firstly conducted a descriptive analysis to evaluate the epidemic characteristics of HFMD. Then, Kulldorff scan statistic based on a discrete Poisson model was used to detect spatial-temporal clusters. Finally, a spatial paneled model was applied to identify the risk factors. Results A total of 641,318 HFMD cases were reported in Guangdong Province during the study period (total population incidence: 17.51 per 10,000). Male incidence was higher than female incidence for all age groups, and approximately 90% of the cases were children years old. Spatial-temporal cluster analysis detected four most likely clusters and several secondary clusters (P<0.001) with the maximum cluster size 50% and 20% respectively during 2008–2011. Monthly average temperature, relative humidity, the proportion of population years, male-to-female ratio, and total sunshine were demonstrated to be the risk factors for HFMD. Conclusion Children years old, especially boys, were more susceptible to HFMD and we should take care of their vulnerability. Provincial capital city Guangzhou and the Pearl River Delta regions had always been the spatial-temporal clusters and future public health planning and resource allocation should be focused on these areas. Furthermore, our findings showed a strong association between HFMD and meteorological factors, which may assist in predicting HFMD incidence.
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              Detecting Spatial-Temporal Clusters of HFMD from 2007 to 2011 in Shandong Province, China

              Yunxia Liu, Xianjun Wang, Yanxun Liu … (2013)
              Background Hand, foot, and mouth disease (HFMD) has caused major public health concerns worldwide, and has become one of the leading causes of children death. China is the most serious epidemic area with a total of 3,419,149 reported cases just from 2008 to 2010, and its different geographic areas might have different spatial epidemiology characteristics at different spatial-temporal scale levels. We conducted spatial and spatial-temporal epidemiology analysis to HFMD at county level in Shandong Province, China. Methods Based on the China National Disease Surveillance Reporting and Management System, the spatial-temporal database of HFMD from 2007 to 2011 was built. The global autocorrelation statistic (Moran’s I) was first used to detect the spatial autocorrelation of HFMD cases in each year. Purely Spatial scan statistics combined with Space-time scan statistic were used to detect epidemic clusters. Results The annual average incidence rate was 93.70 per 100,000 in Shandong Province. Most HFMD cases (93.94%) were aged within 0–5 years old with an average male-to-female sex ratio 1.71, and the incidence seasonal peak was between April and July. The dominant pathogen was EV71 (47.35%), and CoxA16 (26.59%). HFMD had positive spatial autocorrelation at medium spatial scale level (county level) with higher Moran’s I from 0.31 to 0.62 (P<0.001). Seven spatial-temporal clusters were detected from 2007 to 2011 in the landscape of the whole Shandong, with EV71 or CoxA16 as the dominant pathogen for most hotspots areas. Conclusions The spatial-temporal clusters of HFMD wandered around the whole Shandong Province during 2007 to 2011, with EV71 or CoxA16 as the dominant pathogen. These findings suggested that a real-time spatial-temporal surveillance system should be established for identifying high incidence region and conducting prevention to HFMD timely.
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                Author and article information

                Journal
                Journal ID (nlm-ta): Int J Environ Res Public Health
                Journal ID (iso-abbrev): Int J Environ Res Public Health
                Journal ID (publisher-id): ijerph
                Title: International Journal of Environmental Research and Public Health
                Publisher: MDPI
                ISSN (Print): 1661-7827
                ISSN (Electronic): 1660-4601
                Publication date (Electronic): 02 April 2018
                Publication date (Print): April 2018
                Volume: 15
                Issue: 4
                Electronic Location Identifier: 661
                Affiliations
                [1 ]School of Public Policy and Administration, Xi’an Jiaotong University, 28 Xianning West Road, Xi’an 710049, China; binzhu2-c@ 123456my.cityu.edu.hk (B.Z.); liujinlin_xjtu@ 123456stu.xjtu.edu.cn (J.L.)
                [2 ]Department of Public Policy, City University of Hong Kong, Tat Chee Avenue, Kowloon, Hong Kong, China
                [3 ]College of Management, Shenzhen University, Nanhai Ave 3688, Shenzhen 518060, China; yangfu6-c@ 123456my.cityu.edu.hk
                [4 ]School of Human Settlements and Civil Engineering, Xi’an Jiaotong University, 28 Xianning West Road, Xi’an 710049, China; zhangbo0505@ 123456stu.xjtu.edu.cn
                Author notes
                [* ]Correspondence: mao_ying@ 123456mail.xjtu.edu.cn ; Tel.: +86-029-8266-5482
                Author information
                https://orcid.org/0000-0002-0091-6356
                Article
                Publisher ID: ijerph-15-00661
                DOI: 10.3390/ijerph15040661
                PMC ID: 5923703
                PubMed ID: 29614809
                SO-VID: 5aca3025-7628-42bb-bc1f-d5eecc3d8d97
                Copyright © © 2018 by the authors.
                License:

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( http://creativecommons.org/licenses/by/4.0/).

                History
                Date received : 13 February 2018
                Date accepted : 30 March 2018
                Categories
                Subject: Article

                ScienceOpen disciplines: Public health
                Keywords: viral hepatitis,spatio-temporal epidemiology,spatial autocorrelation,space-time scan,moran’s i,hav,hbv,hcv,hev,china
                Data availability:
                ScienceOpen disciplines: Public health
                Keywords: viral hepatitis, spatio-temporal epidemiology, spatial autocorrelation, space-time scan, moran’s i, hav, hbv, hcv, hev, china

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