Association Between Hemorrhagic Fever with Renal Syndrome Epidemic and Climate Factors in Heilongjiang Province, China

Overview

Journal Am J Trop Med Hyg

Specialty Tropical Medicine

Date 2013 Sep 11

PMID 24019443

Citations 19

Authors

Chang-Ping Li

Zhuang Cui

Shen-Long Li

Ricardo J Soares Magalhaes

Bao-Long Wang

Cui Zhang

Hai-Long Sun

Cheng-Yi Li

Liu-Yu Huang

Jun Ma

Wen-Yi Zhang

Affiliations

Soon will be listed here.

Abstract

The purpose of this study was to quantify the relationship between climate variation and transmission of hemorrhagic fever with renal syndrome (HFRS) in Heilongjiang Province, a highly endemic area for HFRS in China. Monthly notified HFRS cases and climatic data for 2001-2009 in Heilongjiang Province were collected. Using a seasonal autoregressive integrated moving average model, we found that relative humidity with a one-month lag (β = -0.010, P = 0.003) and a three-month lag (β = 0.008, P = 0.003), maximum temperature with a two-month lag (β = 0.082, P = 0.028), and southern oscillation index with a two-month lag (β = -0.048, P = 0.019) were significantly associated with HFRS transmission. Our study also showed that predicted values expected under the seasonal autoregressive integrated moving average model were highly consistent with observed values (Adjusted R(2) = 83%, root mean squared error = 108). Thus, findings may help add to the knowledge gap of the role of climate factors in HFRS transmission in China and also assist national local health authorities in the development/refinement of a better strategy to prevent HFRS transmission.

Citing Articles

Investigating the impact of climatic and environmental factors on HFRS prevalence in Anhui Province, China, using satellite and reanalysis data.

Liu Y, Liu C, Wang L, Chen X, Qiao H, Zhang Y Front Public Health. 2024; 12:1447501.

PMID: 39411492 PMC: 11475030. DOI: 10.3389/fpubh.2024.1447501.

Asymmetric impact of climatic parameters on hemorrhagic fever with renal syndrome in Shandong using a nonlinear autoregressive distributed lag model.

Wang Y, Liang Z, Qing S, Xi Y, Xu C, Lin F Sci Rep. 2024; 14(1):9739.

PMID: 38679612 PMC: 11056385. DOI: 10.1038/s41598-024-58023-9.

The Spatiotemporal Pattern and Its Determinants of Hemorrhagic Fever With Renal Syndrome in Northeastern China: Spatiotemporal Analysis.

Wang Y, Wei X, Jia R, Peng X, Zhang X, Yang M JMIR Public Health Surveill. 2023; 9:e42673.

PMID: 37200083 PMC: 10236282. DOI: 10.2196/42673.

Climate and socio-economic factors drive the spatio-temporal dynamics of HFRS in Northeastern China.

Wang Y, Wei X, Xiao X, Yin W, He J, Ren Z One Health. 2022; 15:100466.

PMID: 36532667 PMC: 9754969. DOI: 10.1016/j.onehlt.2022.100466.

Estimating the Long-Term Epidemiological Trends and Seasonality of Hemorrhagic Fever with Renal Syndrome in China.

Xiao Y, Li Y, Li Y, Yu C, Bai Y, Wang L Infect Drug Resist. 2021; 14:3849-3862.

PMID: 34584428 PMC: 8464322. DOI: 10.2147/IDR.S325787.

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