Research Article: Changes in Rodent Abundance and Weather Conditions Potentially Drive Hemorrhagic Fever with Renal Syndrome Outbreaks in Xi’an, China, 2005–2012

Date Published: March 30, 2015

Publisher: Public Library of Science

Author(s): Huai-Yu Tian, Peng-Bo Yu, Angela D. Luis, Peng Bi, Bernard Cazelles, Marko Laine, Shan-Qian Huang, Chao-Feng Ma, Sen Zhou, Jing Wei, Shen Li, Xiao-Ling Lu, Jian-Hui Qu, Jian-Hua Dong, Shi-Lu Tong, Jing-Jun Wang, Bryan Grenfell, Bing Xu, Samuel V. Scarpino. http://doi.org/10.1371/journal.pntd.0003530

Abstract: BackgroundIncreased risks for hemorrhagic fever with renal syndrome (HFRS) caused by Hantaan virus have been observed since 2005, in Xi’an, China. Despite increased vigilance and preparedness, HFRS outbreaks in 2010, 2011, and 2012 were larger than ever, with a total of 3,938 confirmed HFRS cases and 88 deaths in 2010 and 2011.Methods and FindingsData on HFRS cases and weather were collected monthly from 2005 to 2012, along with active rodent monitoring. Wavelet analyses were performed to assess the temporal relationship between HFRS incidence, rodent density and climatic factors over the study period. Results showed that HFRS cases correlated to rodent density, rainfall, and temperature with 2, 3 and 4-month lags, respectively. Using a Bayesian time-series Poisson adjusted model, we fitted the HFRS outbreaks among humans for risk assessment in Xi’an. The best models included seasonality, autocorrelation, rodent density 2 months previously, and rainfall 2 to 3 months previously. Our models well reflected the epidemic characteristics by one step ahead prediction, out-of-sample.ConclusionsIn addition to a strong seasonal pattern, HFRS incidence was correlated with rodent density and rainfall, indicating that they potentially drive the HFRS outbreaks. Future work should aim to determine the mechanism underlying the seasonal pattern and autocorrelation. However, this model can be useful in risk management to provide early warning of potential outbreaks of this disease.

Partial Text: Hantaviruses (family Bunyaviridae, genus Hantavirus) are negative-stranded, trisegmented viruses that cause approximately 200,000 hospitalized cases annually, with case fatality rates of 0.5%–40%, depending on the virus [1,2]. In Eurasia, hemorrhagic fever with renal syndrome (HFRS), a rodent-borne viral disease caused by hantaviruses, is characterized by fever, hemorrhage, headache, back pain, abdominal pain, and acute renal failure and even death [3,4]. From 2006 to 2010, more than 50,000 HFRS cases in China were reported and therefore it remains an important public health issue in developing areas in China (mainly caused by two types of hantaviruses, Hantaan virus, HTNV; and Seoul virus, SEOV) [5–8]. Shaanxi Province is one of the most seriously affected areas in mainland China [5,9]. There were about 99,000 HFRS cases reported, and over 2,537 people have died from HFRS in Shaanxi Province in the last three decades.

This study investigated the association between HFRS outbreaks, environmental conditions, and rodent density. Correlation and wavelet analyses indicated that the climatic and rodent variables have lagged correlations with HFRS incidence. Based on these findings we proposed a set of Bayesian time-series Poisson adjusted models. The best models revealed strong effects of seasonality and autocorrelation and evidence for additional effects of rodent density with a 2-month lag and rainfall with a 2- to 3-month lag. These models predicted HFRS incidence one-month-ahead with pseudo-R2 values of 81–82%. These results are valuable since they point the way to an early warning signal prior to potential HFRS outbreaks via increases in rodent density or rainfall [15,34].

Source:

http://doi.org/10.1371/journal.pntd.0003530

 

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