About: A time-trend ecological study for identifying flood-sensitive infectious diseases in Guangxi, China from 2005 to 2012

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About: A time-trend ecological study for identifying flood-sensitive infectious diseases in Guangxi, China from 2005 to 2012 Goto Sponge NotDistinct Permalink

An Entity of Type : schema:ScholarlyArticle, within Data Space : wasabi.inria.fr associated with source document(s)

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type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	A time-trend ecological study for identifying flood-sensitive infectious diseases in Guangxi, China from 2005 to 2012
Creator	Liu, Qiyong Ding, Guoyong Hou, Haifeng Jiang, Baofa Li, Dong Li, Xiaomei Li, Xuewen Liu, Xuena Xing, Weijia Zhang, Baofang
Source	Elsevier; Medline; PMC
abstract	Abstract Background Flood-related damage can be very severe and include health effects. Among those health impacts, infectious diseases still represent a significant public health problem in China. However, there have been few studies on the identification of the spectrum of infectious diseases associated with floods in one area. This study aimed to quantitatively identify sensitive infectious diseases associated with floods in Guangxi, China. Methods A time-trend ecological design was conducted. A descriptive analysis was first performed to exclude infectious diseases with low incidence from 2005 to 2012 in ten study sites of Guangxi. The Wilcoxon rank-sum test was applied to examine the difference in the ten-day attack rate of infectious diseases between the exposure and control periods with different lagged effects. Negative binomial, zero-inflated Poisson and zero-inflated negative binomial models were used to examine the relationship and odd ratios (ORs) of the risk of floods on infectious diseases of preliminary screening. Results A total of 417,271 infectious diseases were notified. There were 11 infectious diseases associated with floods in the preliminary screening process for flood-sensitive infectious diseases. The strongest effect was shown with a 0–9 ten-day lag in different infectious diseases. Multivariate analysis showed that floods were significantly associated with an increased the risk of bacillary dysentery (odds ratio (OR) = 1.268, 95% confidence interval (CI): 1.072–1.500), acute haemorrhagic conjunctivitis (AHC, OR = 3.230, 95% CI: 1.976–5.280), influenza A (H1N1) (OR = 1.808, 95% CI: 1.721–1.901), tuberculosis (OR = 1.200, 95% CI: 1.036–1.391), influenza (OR = 2.614, 95% CI: 1.476–4.629), Japanese encephalitis (OR = 2.334, 95% CI: 1.119–4.865), and leptospirosis (OR = 1.138, 95% CI: 1.075–1.205), respectively. Conclusion The spectrum of infectious diseases which are associated with floods are bacillary dysentery, AHC, influenza A (H1N1), tuberculosis, influenza, Japanese encephalitis and leptospirosis in Guangxi. Floods can result in differently increased risk of these diseases, and public health action should be taken to control a potential risk of these diseases after floods.
has issue date	2019-09-30(xsd:dateTime)
bibo:doi	10.1016/j.envres.2019.108577
bibo:pmid	31306984
has license	els-covid
sha1sum (hex)	ec2e48e04cf44079c26155ee6d4ba37e2c404c52
schema:url	https://doi.org/10.1016/j.envres.2019.108577
resource representing a document's title	A time-trend ecological study for identifying flood-sensitive infectious diseases in Guangxi, China from 2005 to 2012
has PubMed Central identifier	PMC7094502
has PubMed identifier	31306984
schema:publication	Environmental Research
resource representing a document's body	covid:ec2e48e04cf44079c26155ee6d4ba37e2c404c52#body_text
is schema:about of	named entity 'There' named entity 'infectious diseases' named entity 'Methods' named entity 'control' named entity 'ORs' named entity 'damage' named entity 'models' named entity 'sensitive' named entity '2012' named entity 'CHINA' named entity '417' named entity 'INFECTIOUS DISEASES' named entity 'RELATED' named entity 'EXCLUDE' named entity 'PROCESS' named entity 'SCREENING' named entity 'VERY SEVERE' named entity 'FLOODS' named entity 'SPECTRUM' named entity 'LEPTOSPIROSIS ' named entity 'ACUTE HAEMORRHAGIC CONJUNCTIVITIS' named entity '500' named entity 'TAKEN' named entity 'BACKGROUND' named entity 'USED' named entity 'DIFFERENT' named entity 'PERFORMED' named entity 'PUBLIC HEALTH' named entity 'THESE' named entity 'LOW' named entity 'TO EXAMINE' named entity 'METHODS' named entity 'DISEASES' named entity 'RESULTS' named entity 'HAVE' named entity 'INCLUDE' named entity 'STUDY' named entity 'RATIO' named entity 'ANALYSIS' named entity 'INFLUENZA A' named entity 'RATIOS' named entity 'DESCRIPTIVE' named entity 'TIME' named entity 'STUDIES' named entity 'HEALTH PROBLEM' named entity 'TO CONTROL' named entity 'INFECTIOUS DISEASES' named entity 'SENSITIVE' named entity 'GUANGXI' named entity 'FLOOD' named entity 'BACILLARY DYSENTERY' named entity '200' named entity 'RELATIONSHIP' named entity 'JAPANESE ENCEPHALITIS' named entity 'EFFECT' named entity 'FLOOD' named entity 'ZERO' named entity 'CHINA' named entity '072' named entity '036' named entity 'TREND' named entity 'IDENTIFY' named entity 'TOTAL' named entity 'PRELIMINARY' named entity '901' named entity 'SENSITIVE' named entity 'AHC' named entity 'EFFECTS' named entity 'RISK OF' named entity 'ECOLOGICAL DESIGN' named entity 'IDENTIFYING' named entity 'TIME'

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