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Identifying Flood-Related Infectious Diseases in Anhui Province, China: A Spatial and Temporal Analysis
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 wit...
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Published in: | The American journal of tropical medicine and hygiene 2016-04, Vol.94 (4), p.741-749 |
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description | 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. |
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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.</description><identifier>ISSN: 0002-9637</identifier><identifier>EISSN: 1476-1645</identifier><identifier>DOI: 10.4269/ajtmh.15-0338</identifier><identifier>PMID: 26903612</identifier><language>eng</language><publisher>United States: The American Society of Tropical Medicine and Hygiene</publisher><subject>China - epidemiology ; Communicable Diseases - epidemiology ; Communicable Diseases - etiology ; Diarrhea - epidemiology ; Diarrhea - etiology ; Disasters ; Dysentery, Bacillary - epidemiology ; Dysentery, Bacillary - etiology ; Floods ; Freshwater ; Hepatitis A virus ; Humans ; Incidence ; Malaria - epidemiology ; Malaria - etiology ; Models, Statistical ; Poisson Distribution ; Regression Analysis ; Spatio-Temporal Analysis ; Weather</subject><ispartof>The American journal of tropical medicine and hygiene, 2016-04, Vol.94 (4), p.741-749</ispartof><rights>The American Society of Tropical Medicine and Hygiene.</rights><rights>The American Society of Tropical Medicine and Hygiene 2016</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c486t-ab2c5ae7e5adaa425dca8de926eb481a4daa3292e5e94f5858d6a8fe0542bc1d3</citedby></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC4824213/pdf/$$EPDF$$P50$$Gpubmedcentral$$H</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC4824213/$$EHTML$$P50$$Gpubmedcentral$$H</linktohtml><link.rule.ids>230,314,727,780,784,885,27924,27925,53791,53793</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/26903612$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Gao, Lu</creatorcontrib><creatorcontrib>Zhang, Ying</creatorcontrib><creatorcontrib>Ding, Guoyong</creatorcontrib><creatorcontrib>Liu, Qiyong</creatorcontrib><creatorcontrib>Jiang, Baofa</creatorcontrib><title>Identifying Flood-Related Infectious Diseases in Anhui Province, China: A Spatial and Temporal Analysis</title><title>The American journal of tropical medicine and hygiene</title><addtitle>Am J Trop Med Hyg</addtitle><description>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.</description><subject>China - epidemiology</subject><subject>Communicable Diseases - epidemiology</subject><subject>Communicable Diseases - etiology</subject><subject>Diarrhea - epidemiology</subject><subject>Diarrhea - etiology</subject><subject>Disasters</subject><subject>Dysentery, Bacillary - epidemiology</subject><subject>Dysentery, Bacillary - etiology</subject><subject>Floods</subject><subject>Freshwater</subject><subject>Hepatitis A virus</subject><subject>Humans</subject><subject>Incidence</subject><subject>Malaria - epidemiology</subject><subject>Malaria - etiology</subject><subject>Models, Statistical</subject><subject>Poisson Distribution</subject><subject>Regression Analysis</subject><subject>Spatio-Temporal Analysis</subject><subject>Weather</subject><issn>0002-9637</issn><issn>1476-1645</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2016</creationdate><recordtype>article</recordtype><recordid>eNqNkUFvFDEMhSMEokvhyBXlyIEpcSbJZDggrRYKK1UCQTlH3sSzm2omWSazlfbfM0tLBTdOlu3PT7YfYy9BXChp2rd4Mw27C9CVqGv7iC1ANaYCo_RjthBCyKo1dXPGnpVyIwRYCfCUnc2DojYgF2y7DpSm2B1j2vLLPudQfaMeJwp8nTryU8yHwj_EQlio8Jj4Mu0OkX8d821Mnt7w1S4mfMeX_Psep4g9xxT4NQ37PM7JMmF_LLE8Z0867Au9uI_n7Mflx-vV5-rqy6f1anlVeWXNVOFGeo3UkMaAqKQOHm2gVhraKAuo5motW0maWtVpq20waDsSWsmNh1Cfs_d3uvvDZqDg5-PmNdx-jAOOR5cxun87Ke7cNt86ZaWSUM8Cr-8FxvzzQGVyQyye-h4Tza9w0LRKC2iM-Q-0aa3VACe0ukP9mEsZqXvYCIQ7-eh---hAu5OPM__q7zMe6D_G1b8AL-yb5A</recordid><startdate>20160401</startdate><enddate>20160401</enddate><creator>Gao, Lu</creator><creator>Zhang, Ying</creator><creator>Ding, Guoyong</creator><creator>Liu, Qiyong</creator><creator>Jiang, Baofa</creator><general>The American Society of Tropical Medicine and Hygiene</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope><scope>7T2</scope><scope>7U2</scope><scope>C1K</scope><scope>F1W</scope><scope>H95</scope><scope>H97</scope><scope>L.G</scope><scope>M7N</scope><scope>5PM</scope></search><sort><creationdate>20160401</creationdate><title>Identifying Flood-Related Infectious Diseases in Anhui Province, China: A Spatial and Temporal Analysis</title><author>Gao, Lu ; 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subjects | China - epidemiology Communicable Diseases - epidemiology Communicable Diseases - etiology Diarrhea - epidemiology Diarrhea - etiology Disasters Dysentery, Bacillary - epidemiology Dysentery, Bacillary - etiology Floods Freshwater Hepatitis A virus Humans Incidence Malaria - epidemiology Malaria - etiology Models, Statistical Poisson Distribution Regression Analysis Spatio-Temporal Analysis Weather |
title | Identifying Flood-Related Infectious Diseases in Anhui Province, China: A Spatial and Temporal Analysis |
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