title: Identifying Flood-Related Infectious Diseases in Anhui Province, China: A Spatial and Temporal Analysis.
abstract: The aim of this study was to explore infectious diseases related to the 2007 Huai River flood in Anhui Province, China. The study was based on the notified incidences of infectious diseases between June 29 and July 25 from 2004 to 2011. Daily incidences of notified diseases in 2007 were compared with the corresponding daily incidences during the same period in the other years (from 2004 to 2011, except 2007) by Poisson regression analysis. Spatial autocorrelation analysis was used to test the distribution pattern of the diseases. Spatial regression models were then performed to examine the association between the incidence of each disease and flood, considering lag effects and other confounders. After controlling the other meteorological and socioeconomic factors, malaria (odds ratio [OR] = 3.67, 95% confidence interval [CI] = 1.77-7.61), diarrhea (OR = 2.16, 95% CI = 1.24-3.78), and hepatitis A virus (HAV) infection (OR = 6.11, 95% CI = 1.04-35.84) were significantly related to the 2007 Huai River flood both from the spatial and temporal analyses. Special attention should be given to develop public health preparation and interventions with a focus on malaria, diarrhea, and HAV infection, in the study region.
authors.affiliation: Department of Epidemiology and Health Statistics, School of Public Health, Shandong University, Shandong Province, People's Republic of China; School of Public Health, China Studies Centre, The University of Sydney, New South Wales, Australia; School of Public Health, Center for Climate Change and Health, Shandong University, Shandong Province, People's Republic of China; Department of Occupational and Environmental Health, School of Public Health, Taishan Medical College, Shandong Province, People's Republic of China; State Key Laboratory for Infectious Diseases Prevention and Control, National Institute for Communicable Disease Control and Prevention, China Centers for Disease Control and Prevention, Beijing City, People's Republic of China.
authors.forename: Lu
authors.initials: L
authors.lastname: Gao
authors.affiliation: Department of Epidemiology and Health Statistics, School of Public Health, Shandong University, Shandong Province, People's Republic of China; School of Public Health, China Studies Centre, The University of Sydney, New South Wales, Australia; School of Public Health, Center for Climate Change and Health, Shandong University, Shandong Province, People's Republic of China; Department of Occupational and Environmental Health, School of Public Health, Taishan Medical College, Shandong Province, People's Republic of China; State Key Laboratory for Infectious Diseases Prevention and Control, National Institute for Communicable Disease Control and Prevention, China Centers for Disease Control and Prevention, Beijing City, People's Republic of China.
authors.forename: Ying
authors.initials: Y
authors.lastname: Zhang
authors.affiliation: Department of Epidemiology and Health Statistics, School of Public Health, Shandong University, Shandong Province, People's Republic of China; School of Public Health, China Studies Centre, The University of Sydney, New South Wales, Australia; School of Public Health, Center for Climate Change and Health, Shandong University, Shandong Province, People's Republic of China; Department of Occupational and Environmental Health, School of Public Health, Taishan Medical College, Shandong Province, People's Republic of China; State Key Laboratory for Infectious Diseases Prevention and Control, National Institute for Communicable Disease Control and Prevention, China Centers for Disease Control and Prevention, Beijing City, People's Republic of China.
authors.forename: Guoyong
authors.initials: G
authors.lastname: Ding
authors.affiliation: Department of Epidemiology and Health Statistics, School of Public Health, Shandong University, Shandong Province, People's Republic of China; School of Public Health, China Studies Centre, The University of Sydney, New South Wales, Australia; School of Public Health, Center for Climate Change and Health, Shandong University, Shandong Province, People's Republic of China; Department of Occupational and Environmental Health, School of Public Health, Taishan Medical College, Shandong Province, People's Republic of China; State Key Laboratory for Infectious Diseases Prevention and Control, National Institute for Communicable Disease Control and Prevention, China Centers for Disease Control and Prevention, Beijing City, People's Republic of China.
authors.forename: Qiyong
authors.initials: Q
authors.lastname: Liu
authors.affiliation: Department of Epidemiology and Health Statistics, School of Public Health, Shandong University, Shandong Province, People's Republic of China; School of Public Health, China Studies Centre, The University of Sydney, New South Wales, Australia; School of Public Health, Center for Climate Change and Health, Shandong University, Shandong Province, People's Republic of China; Department of Occupational and Environmental Health, School of Public Health, Taishan Medical College, Shandong Province, People's Republic of China; State Key Laboratory for Infectious Diseases Prevention and Control, National Institute for Communicable Disease Control and Prevention, China Centers for Disease Control and Prevention, Beijing City, People's Republic of China bjiang@sdu.edu.cn.
authors.forename: Baofa
authors.initials: B
authors.lastname: Jiang
mesh_terms: D002681:China / Q000453:epidemiology; D003141:Communicable Diseases / Q000453:epidemiology* / Q000209:etiology; D003967:Diarrhea / Q000453:epidemiology / Q000209:etiology; D004190:Disasters; D004405:Dysentery, Bacillary / Q000453:epidemiology / Q000209:etiology; D055868:Floods; D006801:Humans; D015994:Incidence; D008288:Malaria / Q000453:epidemiology / Q000209:etiology; D015233:Models, Statistical; D016012:Poisson Distribution; D012044:Regression Analysis; D062211:Spatio-Temporal Analysis; D014887:Weather