Literature DB >> 27174415

Projections of hepatitis A virus infection associated with flood events by 2020 and 2030 in Anhui Province, China.

Lu Gao1, Ying Zhang1,2,3, Guoyong Ding4, Qiyong Liu5, Changke Wang6, Baofa Jiang7.   

Abstract

Assessing and responding to health risk of climate change is important because of its impact on the natural and societal ecosystems. More frequent and severe flood events will occur in China due to climate change. Given that population is projected to increase, more people will be vulnerable to flood events, which may lead to an increased incidence of HAV infection in the future. This population-based study is going to project the future health burden of HAV infection associated with flood events in Huai River Basin of China. The study area covered four cities of Anhui province in China, where flood events were frequent. Time-series adjusted Poisson regression model was developed to quantify the risks of flood events on HAV infection based on the number of daily cases during summer seasons from 2005 to 2010, controlling for other meteorological variables. Projections of HAV infection in 2020 and 2030 were estimated based on the scenarios of flood events and demographic data. Poisson regression model suggested that compared with the periods without flood events, the risks of severe flood events for HAV infection were significant (OR = 1.28, 95 % CI 1.05-1.55), while risks were not significant from moderate flood events (OR = 1.16, 95 % CI 0.72-1.87) and mild flood events (OR = 1.14, 95 % CI 0.87-1.48). Using the 2010 baseline data and the flood event scenarios (one severe flood event), increased incidence of HAV infection were estimated to be between 0.126/105 and 0.127/105 for 2020. Similarly, the increased HAV infection incidence for 2030 was projected to be between 0.382/105 and 0.399/105. Our study has, for the first time, quantified the increased incidence of HAV infection that will result from flood events in Anhui, China, in 2020 and 2030. The results have implications for public health preparation for developing public health responses to reduce HAV infection during future flood events.

Entities:  

Keywords:  Hepatitis A virus infection; Poisson regression; Projection; Scenario-based modeling; Time series

Mesh:

Year:  2016        PMID: 27174415     DOI: 10.1007/s00484-016-1174-3

Source DB:  PubMed          Journal:  Int J Biometeorol        ISSN: 0020-7128            Impact factor:   3.787


  47 in total

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Authors:  C H Hau; T T Hien; N T Tien; H B Khiem; P K Sac; V T Nhung; R P Larasati; K Laras; M P Putri; R Doss; K C Hyams; A L Corwin
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9.  Flash flood disaster--Nîmes, France, 1988.

Authors:  P Duclos; O Vidonne; P Beuf; P Perray; A Stoebner
Journal:  Eur J Epidemiol       Date:  1991-07       Impact factor: 8.082

10.  A mixed method to evaluate burden of malaria due to flooding and waterlogging in Mengcheng County, China: a case study.

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Review 3.  Health impact of climate change in cities of middle-income countries: the case of China.

Authors:  Emily Y Y Chan; Janice Y Ho; Heidi H Y Hung; Sida Liu; Holly C Y Lam
Journal:  Br Med Bull       Date:  2019-06-19       Impact factor: 4.291

Review 4.  The Impact of Climate Change on Vaccine-Preventable Diseases: Insights From Current Research and New Directions.

Authors:  Ayesha S Mahmud; Pamela P Martinez; Jingxing He; Rachel E Baker
Journal:  Curr Environ Health Rep       Date:  2020-10-25
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