ArticleScientific reports2024
Asymmetric impact of climatic parameters on hemorrhagic fever with renal syndrome in Shandong using a nonlinear autoregressive distributed lag model.
Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- The effects of meteorological factors on hemorrhagic fever with renal syndrome in Yichun, China: a major Apodemus-type endemic city.Scientific reports · 2026Article
- Epidemiological Characteristics of Hemorrhagic Fever with Renal Syndrome in Longyou County, China.Viruses · 2025Article
- Risk of hemorrhagic fever with renal syndrome associated with meteorological factors in diverse epidemic regions: a nationwide longitudinal study in China.Infectious diseases of poverty · 2025Article
- Asymmetric association between meteorological factors and human infections with hemorrhagic fever with renal syndrome: A 16-year ecological trend study in Shaanxi, China.One health (Amsterdam, Netherlands) · 2024Article
- Long- and short-run asymmetric impacts of climate variation on tuberculosis based on a time series study.Scientific reports · 2024Article
- Long- and Short-Run Asymmetric Effects of Meteorological Parameters on Hemorrhagic Fever with Renal Syndrome in Heilongjiang: A Population-Based Retrospective Study.Transboundary and emerging diseases · 2024Article
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6 authors.
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Abstract
Hemorrhagic fever with renal syndrome (HFRS) poses a major threat in Shandong. This study aimed to investigate the long- and short-term asymmetric effects of meteorological factors on HFRS and establish an early forecasting system using autoregressive distributed lag (ARDL) and nonlinear ARDL (NARDL) models. Between 2004 and 2019, HFRS exhibited a declining trend (average annual percentage change = - 9.568%, 95% CI - 16.165 to - 2.451%) with a bimodal seasonality. A long-term asymmetric influence of aggregate precipitation (AP) (Wald long-run asymmetry [WLR] = - 2.697, P = 0.008) and aggregate sunshine hours (ASH) (WLR = 2.561, P = 0.011) on HFRS was observed. Additionally, a short-term asymmetric impact of AP (Wald short-run symmetry [WSR] = - 2.419, P = 0.017), ASH (WSR = 2.075, P = 0.04), mean wind velocity (MWV) (WSR = - 4.594, P < 0.001), and mean relative humidity (MRH) (WSR = - 2.515, P = 0.013) on HFRS was identified. Also, HFRS demonstrated notable variations in response to positive and negative changes in ∆MRH(-), ∆AP(+), ∆MWV(+), and ∆ASH(-) at 0-2 month delays over the short term. In terms of forecasting, the NARDL model demonstrated lower error rates compared to ARDL. Meteorological parameters have substantial long- and short-term asymmetric and/or symmetric impacts on HFRS. Merging NARDL model with meteorological factors can enhance early warning systems and support proactive measures to mitigate the disease's impact.
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