Long- and Short-Run Asymmetric Effects of Meteorological Parameters on Hemorrhagic Fever with Renal Syndrome in Heilongjiang: A Population-Based Retrospective Study

IF 3.5 2区 农林科学 Q2 INFECTIOUS DISEASES Transboundary and Emerging Diseases Pub Date : 2024-07-30 DOI:10.1155/2024/6080321
Yongbin Wang, Bingjie Zhang, Chenlu Xue, Peiping Zhou, Xinwen Dong, Chunjie Xu
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Abstract

Examining both long-term and short-term effects can enhance the precision and reliability of time series analysis. This study aimed to delve into the asymmetric effects of weather conditions on hemorrhagic fever with renal syndrome (HFRS) in the long and short terms and build a forecasting system. Data comprising monthly HFRS incidents and weather factors in Heilongjiang from January 2004 to December 2019 were extracted. Subsequently, the long- and short-term asymmetric impacts were examined using the autoregressive distributed lag (ARDL) and nonlinear ARDL (NARDL) models. Next, the samples were partitioned into training and testing subsets to evaluate the predictive potential of both models. From 2004 to 2019, HFRS exhibited a declining trend (average annual percentage change = −6.744%, 95% CI: −13.52%–0.563%) and a dual seasonal pattern, with a prominent peak in June and a secondary one in October–December. This study identified long-term asymmetric effects of rainfall (Wald long-run asymmetry (WLR) = 3.292, p = 0.001), wind velocity (WLR = −3.271, p = 0.001), and air pressure (WLR = −6.453, p < 0.001) on HFRS. Additionally, this study observed short-term asymmetric impacts of relative humidity (Wald short-run symmetry (WSR) = −1.547, p = 0.001), rainfall (WSR = −1.984, p = 0.049), and air pressure (WSR = −2.33, p = 0.021) on HFRS. A unit increase in relative humidity, sunshine hours, and air pressure resulted in about 10.9%, 1.9%, and 13.6% decreases in HFRS, respectively; a unit decrease in relative humidity, rainfall, and sunshine hours led to about 6.7%, 1.8%, and 2% decreases in HFRS, respectively. When temperature increased and decreased by one unit, the HFRS incidence increased by 11.6% and 22.5%, respectively. HFRS also varied significantly with the positive and negative changes in differenced (D) temperature, D (relative humidity), D (wind velocity), D (rainfall), D (air pressure), and D (sunshine hours) at 0−3-month delays over the short term. The NARDL model exhibited notably lower error rates in forecasting compared to the ARDL model. Meteorological parameters affect HFRS in both the long and short term, often showing asymmetric effects. The NARDL model, capable of incorporating various weather parameters, proves to be valuable in predicting HFRS epidemic and guiding strategies for prevention and control.

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气象参数对黑龙江出血热合并肾综合征的长短期不对称影响:一项基于人群的回顾性研究
研究长期和短期效应可以提高时间序列分析的精确性和可靠性。本研究旨在探讨天气条件对出血热合并肾综合征(HFRS)的长期和短期非对称影响,并建立预测系统。研究提取了黑龙江省2004年1月至2019年12月的月度出血热肾综合征事件和天气因素数据。随后,利用自回归分布滞后(ARDL)和非线性ARDL(NARDL)模型检验了长短期非对称影响。接下来,将样本划分为训练子集和测试子集,以评估两个模型的预测潜力。从 2004 年到 2019 年,HFRS 呈下降趋势(年均百分比变化率 = -6.744%,95% CI:-13.52%-0.563%),并呈现双重季节性模式,6 月和 10-12 月分别出现一个显著的峰值和一个次要峰值。该研究发现了降雨(Wald longrun asymmetry (WLR) = 3.292,p = 0.001)、风速(WLR = -3.271,p = 0.001)和气压(WLR = -6.453,p < 0.001)对 HFRS 的长期不对称影响。此外,本研究还观察到相对湿度(Wald short-run symmetry (WSR) = -1.547, p = 0.001)、降雨量(WSR = -1.984, p = 0.049)和气压(WSR = -2.33, p = 0.021)对 HFRS 的短期不对称影响。相对湿度、日照时间和气压每增加一个单位,HFRS 分别下降约 10.9%、1.9% 和 13.6%;相对湿度、降雨量和日照时间每减少一个单位,HFRS 分别下降约 6.7%、1.8% 和 2%。当温度上升和下降一个单位时,HFRS 发生率分别增加 11.6% 和 22.5%。在 0-3 个月的短期延迟时间内,HFRS 也随温度差(D)、相对湿度差(D)、风速差(D)、降雨量差(D)、气压差(D)和日照时数差(D)的正负变化而发生明显变化。与 ARDL 模型相比,NARDL 模型的预报误差率明显较低。气象参数在长期和短期内都会影响 HFRS,而且往往表现出不对称的影响。事实证明,NARDL 模型能够纳入各种气象参数,对预测 HFRS 的流行和指导预防与控制策略很有价值。
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来源期刊
Transboundary and Emerging Diseases
Transboundary and Emerging Diseases 农林科学-传染病学
CiteScore
8.90
自引率
9.30%
发文量
350
审稿时长
1 months
期刊介绍: Transboundary and Emerging Diseases brings together in one place the latest research on infectious diseases considered to hold the greatest economic threat to animals and humans worldwide. The journal provides a venue for global research on their diagnosis, prevention and management, and for papers on public health, pathogenesis, epidemiology, statistical modeling, diagnostics, biosecurity issues, genomics, vaccine development and rapid communication of new outbreaks. Papers should include timely research approaches using state-of-the-art technologies. The editors encourage papers adopting a science-based approach on socio-economic and environmental factors influencing the management of the bio-security threat posed by these diseases, including risk analysis and disease spread modeling. Preference will be given to communications focusing on novel science-based approaches to controlling transboundary and emerging diseases. The following topics are generally considered out-of-scope, but decisions are made on a case-by-case basis (for example, studies on cryptic wildlife populations, and those on potential species extinctions): Pathogen discovery: a common pathogen newly recognised in a specific country, or a new pathogen or genetic sequence for which there is little context about — or insights regarding — its emergence or spread. Prevalence estimation surveys and risk factor studies based on survey (rather than longitudinal) methodology, except when such studies are unique. Surveys of knowledge, attitudes and practices are within scope. Diagnostic test development if not accompanied by robust sensitivity and specificity estimation from field studies. Studies focused only on laboratory methods in which relevance to disease emergence and spread is not obvious or can not be inferred (“pure research” type studies). Narrative literature reviews which do not generate new knowledge. Systematic and scoping reviews, and meta-analyses are within scope.
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