Literature DB >> 21646523

Nonlinear effect of climate on plague during the third pandemic in China.

Lei Xu1, Qiyong Liu, Leif Chr Stige, Tamara Ben Ari, Xiye Fang, Kung-Sik Chan, Shuchun Wang, Nils Chr Stenseth, Zhibin Zhang.   

Abstract

Over the years, plague has caused a large number of deaths worldwide and subsequently changed history, not the least during the period of the Black Death. Of the three plague pandemics, the third is believed to have originated in China. Using the spatial and temporal human plague records in China from 1850 to 1964, we investigated the association of human plague intensity (plague cases per year) with proxy data on climate condition (specifically an index for dryness/wetness). Our modeling analysis demonstrates that the responses of plague intensity to dry/wet conditions were different in northern and southern China. In northern China, plague intensity generally increased when wetness increased, for both the current and the previous year, except for low intensity during extremely wet conditions in the current year (reflecting a dome-shaped response to current-year dryness/wetness). In southern China, plague intensity generally decreased when wetness increased, except for high intensity during extremely wet conditions of the current year. These opposite effects are likely related to the different climates and rodent communities in the two parts of China: In northern China (arid climate), rodents are expected to respond positively to high precipitation, whereas in southern China (humid climate), high precipitation is likely to have a negative effect. Our results suggest that associations between human plague intensity and precipitation are nonlinear: positive in dry conditions, but negative in wet conditions.

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Year:  2011        PMID: 21646523      PMCID: PMC3121851          DOI: 10.1073/pnas.1019486108

Source DB:  PubMed          Journal:  Proc Natl Acad Sci U S A        ISSN: 0027-8424            Impact factor:   11.205


  20 in total

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  23 in total

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10.  Analysis of effects of meteorological factors on dengue incidence in Sri Lanka using time series data.

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