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- W2912779672 abstract "Vector-borne diseases, transmitted by the bite of infected arthropod species, remain a serious public health threat and have become a great burden on economy and society in the world. China has experienced considerable changes in climate over the last decade. The potential impact of climate change on transmission of vector-borne diseases poses a threat to the Chinese people. Plague is a deadly infectious disease and the third plague pandemic is believed to have originated in China. Using the spatial and temporal human plague records in China from 1850 to 1964, it was found that the associations between human plague intensity and precipitation are nonlinear: positive in dry conditions, but negative in wet conditions. Based on long-term epidemiological data (1772-1964) of Chinese plague foci, the plague was found in diverse environments using a clustering method and an ecological niche model. Concerns regarding the impact of global warming on vector–borne diseases have intensified interest in the relationship between temperature and Dengue Fever (DF) incidence. With climate warming, the distribution of Ae. albopictus would expand its geographic limit and the potential transmission of dengue fever would increase, using GIS and CLIMAX model analysis. Minimum temperature and wind velocity are significant predictors of dengue incidence in Guangzhou, China for the period of 2001-2006. Climate change will increase the opportunities for malaria transmission in traditionally malarious areas, in areas the disease has been controlled, as well as in new areas. Time series analysis, GEE and GIS were conducted to analyze the association between climatic factors and the yearly incidence of malaria in Yongcheng city. Significant factors contributing to malaria incidence were maximum temperature at one month lag, average humidity at one month lag, and malaria incidence of the previous month. In China, the monthly trends of HFRS were significantly associated with local temperature, relative humidity, precipitation, air pressure, and wind velocity of the different previous months using principal components regression model. In addition, the ARIMA model was found to be a very useful tool for forecasting the incidence of HFRS in recent years." @default.
- W2912779672 created "2019-02-21" @default.
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- W2912779672 date "2013-09-19" @default.
- W2912779672 modified "2023-09-23" @default.
- W2912779672 title "Research on climate, climate change and vector borne diseases in China" @default.
- W2912779672 doi "https://doi.org/10.1289/isee.2013.s-3-07-04" @default.
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