A PHP Error was encountered

Severity: Warning

Message: file_get_contents(https://...@pubfacts.com&api_key=b8daa3ad693db53b1410957c26c9a51b4908&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests

Filename: helpers/my_audit_helper.php

Line Number: 176

Backtrace:

File: /var/www/html/application/helpers/my_audit_helper.php
Line: 176
Function: file_get_contents

File: /var/www/html/application/helpers/my_audit_helper.php
Line: 250
Function: simplexml_load_file_from_url

File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3122
Function: getPubMedXML

File: /var/www/html/application/controllers/Detail.php
Line: 575
Function: pubMedSearch_Global

File: /var/www/html/application/controllers/Detail.php
Line: 489
Function: pubMedGetRelatedKeyword

File: /var/www/html/index.php
Line: 316
Function: require_once

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

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 (HN) (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 (HN), 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.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7094502PMC
http://dx.doi.org/10.1016/j.envres.2019.108577DOI Listing

Publication Analysis

Top Keywords

infectious diseases
48
diseases associated
16
associated floods
16
diseases
14
infectious
12
time-trend ecological
8
flood-sensitive infectious
8
2005 2012
8
public health
8
spectrum infectious
8

Similar Publications

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!