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      Spatial and Temporal Statistical Modeling of Hand, Foot, and Mouth Disease and its Characteristics in China: A Review


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          Hand, foot, and mouth disease (HFMD) has been reported in all 31 provinces of mainland China and has become one of the most common infectious diseases in China. Here we review its spatial and temporal patterns in China and related statistical modeling.


          We systematically reviewed the literature on the epidemic characteristics and related models proposed to reveal its spatial and temporal patterns of HFMD in mainland China.


          In mainland China, HFMD is usually caused by enterovirus 71 (EV71) and coxsackievirus A16 (Cox A16). The incidence of HFMD had one or two peaks in a year and presented obvious seasonality. The incidence rate of HFMD was associated with geographical factors, social factors and meteorological variables but it was different in some areas. In most regions of China, the incidence of HFMD was not a random distribution and presented a complex regularity. In this paper, we summarized the spatial autocorrelation analysis, spatial-temporal clustering analysis and time series analysis to the spatial and temporal distribution of HFMD.


          The spatial and temporal analysis can provide important information and contribute to development of effective measurements to control and prevent its transmission.

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          Most cited references67

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          Evaluating cluster alarms: a space-time scan statistic and brain cancer in Los Alamos, New Mexico.

          This article presents a space-time scan statistic, useful for evaluating space-time cluster alarms, and illustrates the method on a recent brain cancer cluster alarms in Los Alamos, NM. The space-time scan statistic accounts for the preselection bias and multiple testing inherent in a cluster alarm. Confounders and time trends can be adjusted for. The observed excess of brain cancer in Los Alamos was not statistically significant. The space-time scan statistic is useful as a screening tool for evaluating which cluster alarms merit further investigation and which clusters are probably chance occurrences.
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            Breast cancer clusters in the northeast United States: a geographic analysis.

            High breast cancer mortality rates have been reported in the northeastern part of the United States, with recent attention focused on Long Island, New York. In this study, the authors investigate whether the high breast cancer mortality is evenly spread over the Northeast, in the sense that any observed clusters of deaths can be explained by chance alone, or whether there are clusters of statistical significance. Demographic data and age-specific breast cancer mortality rates for women were obtained for all 244 counties in 11 northeastern states and for the District of Columbia for 1988-1992. A recently developed spatial scan statistic is used, which searches for clusters of cases without specifying their size or location ahead of time, and which tests for their statistical significance while adjusting for the multiple testing inherent in such a procedure. The basic analysis is adjusted for age, with further analyses examining how the results are affected by incorporating race, urbanicity, and parity as confounding variables. There is a statistically significant and geographically broad cluster of breast cancer deaths in the New York City-Philadelphia, Pennsylvania, metropolitan area (p = 0.0001), which has a 7.4% higher mortality rate than the rest of the Northeast. The cluster remains significant when race, urbanicity, and/or parity are included as confounding variables. Four smaller subclusters within this area are also significant on their own strength: Philadelphia with suburbs (p = 0.0001), Long Island (p = 0.0001), central New Jersey (p = 0.0001), and northeastern New Jersey (p = 0.0001). The elevated breast cancer mortality on Long Island might be viewed less as a unique local phenomenon and more as part of a more general situation involving large parts of the New York City-Philadelphia metropolitan area. The several known and hypothesized risk factors for which we could not adjust and that may explain the detected cluster are most notably age at first birth, age at menarche, age at menopause, breastfeeding, genetic mutations, and environmental factors.
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              Enterovirus 71 outbreak in the People's Republic of China in 2008.


                Author and article information

                Infectious Diseases and Translational Medicine
                Infect. Dis. Transl. Med.
                Infect. Dis. Transl. Med.
                International Biological and Medical Journals Publishing House Co., Limited (Room E16, 3/f, Yongda Commercial Building, No.97, Bonham Stand (Sheung Wan), HongKong )
                30 June 2015
                10 June 2015
                : 1
                : 1
                : 23-29
                From College of Resources and Environment Science, Hunan Normal University, Changsha 410081, China
                Hunan Provincial Center for Disease Control and Prevention, Changsha 410002, China
                School of Public Health, Shandong University, Jinan 250012, China
                From College of Resources and Environment Science, Hunan Normal University, Changsha 410081, China
                State Key Laboratory of Remote Sensing Science, College of Global Change and Earth System Science, Beijing Normal University, Beijing 100875, China
                Author notes
                Correspondence to: Hong Xiao, from College of Resources and Environment Science, Hunan Normal University; Email: xiaohong.hnnu@ 123456gmail.com .

                This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

                Page count
                Figures: 0, Tables: 1, References: 73, Pages: 7

                Medicine,Infectious disease & Microbiology
                spatial and temporal statistical modeling,Hand, foot, and mouth disease,review,China


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