Meteorological factors and risk of hemorrhagic fever with renal syndrome in Guangzhou, southern China, 2006–2015

Wei, Yuehong; Wang, Yang; Li, Xiaoning; Qin, Pengzhe; Lü, Ying; Xu, Jing; Chen, Shouyi; Yang, Zhicong

doi:10.1371/journal.pntd.0006604

Cited by 37 publications

(37 citation statements)

References 28 publications

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“…Temperature is another important driver (IRR = 1.195, 95% CI 1.024-1.395) for the pertussis infection in this work. Temperature has been shown to be in relation to many contagious diseases, such as scarlet fever 65 , HFRS 20 , bacillary dysentery 21 , and human brucellosis 22 . Similarly, in the present work, we found that the monthly average temperature is positively correlated with the number of pertussis cases, which can also be used to explain the peak phenomenon of pertussis incidence observed in hot weather in our study and previous other studies 53,66 .…”

Section: Discussionmentioning

confidence: 99%

“…In recent years, the relationship between weather variability and contagious diseases has received increasingly wide attention, because climatic drivers may play a pivotal role in the dynamics, distribution, and transmission of contagious diseases via impacting the growth and development of pathogenic agents, population dynamics of hosts and human behaviors, and thus can be deemed as early warning signals for the dynamic epidemics of contagious diseases 15,16 . Presently, many publications have found that meteorological parameters are closely related to the incidences of scarlet fever 17 , tuberculosis 18 , dengue fever 19 , hemorrhagic fever with renal syndrome (HFRS) 20 , bacillary dysentery 21 , human brucellosis 22 , hand, foot and mouth disease (HFMD) 23 , etc. Prior studies also reported the relationship between weather parameters and pertussis.…”

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confidence: 99%

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The long-term effects of meteorological parameters on pertussis infections in Chongqing, China, 2004–2018

Wang

Ren

et al. 2020

Sci Rep

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Evidence on the long-term influence of climatic variables on pertussis is limited. This study aims to explore the long-term quantitative relationship between weather variability and pertussis. Data on the monthly number of pertussis cases and weather parameters in Chongqing in the period of 2004–2018 were collected. Then, we used a negative binomial multivariable regression model and cointegration testing to examine the association of variations in monthly meteorological parameters and pertussis. Descriptive statistics exhibited that the pertussis incidence rose from 0.251 per 100,000 people in 2004 to 3.661 per 100,000 persons in 2018, and pertussis was a seasonal illness, peaked in spring and summer. The results from the regression model that allowed for the long-term trends, seasonality, autoregression, and delayed effects after correcting for overdispersion showed that a 1 hPa increment in the delayed one-month air pressure contributed to a 3.559% (95% CI 0.746–6.293%) reduction in the monthly number of pertussis cases; a 10 mm increment in the monthly aggregate precipitation, a 1 °C increment in the monthly average temperature, and a 1 m/s increment in the monthly average wind velocity resulted in 3.641% (95% CI 0.960–6.330%), 19.496% (95% CI 2.368–39.490%), and 3.812 (95% CI 1.243–11.690)-fold increases in the monthly number of pertussis cases, respectively. The roles of the mentioned weather parameters in the transmission of pertussis were also evidenced by a sensitivity analysis. The cointegration testing suggested a significant value among variables. Climatic factors, particularly monthly temperature, precipitation, air pressure, and wind velocity, play a role in the transmission of pertussis. This finding will be of great help in understanding the epidemic trends of pertussis in the future, and weather variability should be taken into account in the prevention and control of pertussis.

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Section: Discussionmentioning

confidence: 99%

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confidence: 99%

The long-term effects of meteorological parameters on pertussis infections in Chongqing, China, 2004–2018

Wang

Ren

et al. 2020

Sci Rep

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“…Previous studies focused on large scale evaluations of HFRS epidemiology, especially country and city level, [3][4][5][6][7][8] and these studies gave a global description of HFRS transmission in China. Given that small-scale studies will yield more precise and a better quantification of the local characteristics of HFRS transmission, the present study chose four high-risk HFRSaffected counties from Heilongjiang and Shaanxi provinces, where the largest number of HFRS cases are documented in China.…”

Section: Introductionmentioning

confidence: 99%

Environmental Determinants of Hemorrhagic Fever with Renal Syndrome in High-Risk Counties in China: A Time Series Analysis (2002–2012)

Han

et al. 2018

The American Journal of Tropical Medicine and Hygiene

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The transmission pattern of hemorrhagic fever with renal syndrome (HFRS) is associated with environmental conditions, including meteorological factors and land-cover. In the present study, the association between HFRS and environmental factors (including maximum temperature, relative humidity, rainfall, and normalized difference vegetation index) were explored in two typical counties in Northeast and two counties in Northwest China with severe HFRS outbreaks by using seasonal autoregressive integrated moving average model with exogenous variables (SARIMAX). The results showed that rainfall with 3- to 4-month lag was closely associated with HFRS in the two counties in Northeast China, whereas relative humidity with 1- or 5-month lag significantly impacts HFRS transmission in the two counties in Northwest China. Moreover, the SARIMAX models exhibit accurate forecasting ability of HFRS cases. Our findings provide scientific support for local HFRS monitoring and control, and the development of a HFRS early warning system.

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“…1). The causes for the summer peak and the variation of the number of cases in different years may be explained by the warm temperature, high humidity and high precipitation in the sub-tropical Lingnan region, where Guangzhou is located (19).…”

Section: Discussionmentioning

confidence: 99%

Spatial epidemiology of hemorrhagic fever with renal syndrome and rodent hantavirus infection in Guangzhou city, China: lessons learned from a study with long-term surveillance data

Chen

Liang

et al. 2019

Preprint

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Background: Though Guangzhou city is not a region with a high burden of hemorrhagic fever with renal syndrome (HFRS) comparing with other areas in China, outbreaks still occur in the city due to the existence of urban rodents and a large urban population at risk. In this study, descriptive temporal analysis and geographic information system (GIS)-based spatial analysis were performed on reported HFRS cases and rodent surveys with the goals of identifying risk areas for public health interventions and presenting the methods and outcomes of the surveillance that can be studied by similar urban settings. Methods: Period prevalence and the number of positive cases at different geographical scales of the city during 2008-2016 were calculated and summarized based on HFRS and rodent-borne disease surveillance data. Spatial point pattern analyses were conducted to describe global and local clustering effects of different measurements of human HFRS and rodent hantavirus at old-town and whole-city levels. Results: Geographical distributions of HFRS cases and traps with hantavirus antibody-carrying rodents from 2008 to 2016 were mapped at the city and old-district levels in the aspect of the crude number of positive cases and period prevalence. The weighted K-function suggested that no global clustering effect existed for both the rodent and human cases in different scales of the city. Using Gi*(d) statistic, 22 significant local clusters of high infection (P<0.05) with different radius were discovered for the human and rodent surveillance data, and a zoonotic link was built based on the overlay of clusters of the two species. Also, the seasonal occurrence of HFRS presented a summer peak in the city. Conclusion: The applications of descriptive temporal analysis, GIS and spatial point pattern analysis, offer ways to quantify zoonotic hantavirus risks across different times and spatial scales and to further recognize putative environmental determinants potentially influential in increased disease risks. The study also fills information gaps about hantavirus surveillance in the non-endemic region, and the methods used for rodent survey in China for controlling HFRS, which is not well documented.

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Meteorological factors and risk of hemorrhagic fever with renal syndrome in Guangzhou, southern China, 2006–2015

Cited by 37 publications

References 28 publications

The long-term effects of meteorological parameters on pertussis infections in Chongqing, China, 2004–2018

The long-term effects of meteorological parameters on pertussis infections in Chongqing, China, 2004–2018

Environmental Determinants of Hemorrhagic Fever with Renal Syndrome in High-Risk Counties in China: A Time Series Analysis (2002–2012)

Spatial epidemiology of hemorrhagic fever with renal syndrome and rodent hantavirus infection in Guangzhou city, China: lessons learned from a study with long-term surveillance data

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