马来西亚马六甲登革热病例、昆虫学和气象变量的时间和交互动态:多变量时间序列分析

Shazelin Alipitchay, Muhammad Aswad Alias, Sharifah Nur Shahirah Syed Abdul Hamid, Rabizah Hamzah, Norain Mansor, Nurulhusna Ab. Hamid, Hidayatulfathi Othman
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引用次数: 0

摘要

几十年来,登革热病例、昆虫学和气象学变量之间的相互作用一直错综复杂。经过验证的事实对于做出更安全、更可持续的决策非常重要。本研究旨在阐明马来西亚马六甲地区长期和短期动态重点变量之间的关系,以加深对变量及其时间关联的理解。本研究对变量的时间关联、潜在时滞以及所有变量数据集之间的动态相互作用进行量化。研究采用约翰森协整检验和向量误差修正模型来验证长期运行,并考察 2020-2022 年登革热病例、气温、ovitrap 和粘性ovitrap 数据之间的短期偏差。实证结果证明,气温、粘性誘蚊產卵器指數(SOI)和誘蚊產卵器指數(OI)与登革热病例之间存在显著而独特的长期均衡关系。短期均衡结果显示变量之间存在稳健的因果关系。模型拟合阐明了 74.2% 的动态变化。在描述所研究的变量时,VECM 模型在拟合度和复杂性之间进行了很好的权衡。以前的登革热病例预测了新登革热病例的激增,同时保留了周期性模式。该模型预测了粘性誘蚊產卵器的实用性和有效性。该模型还验证了将誘蚊產卵器作为监测工具的有效性,并证实了温度对登革热病例进展的影响。
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Temporal and interaction dynamics of dengue cases, entomological and meteorological variables in Melaka, Malaysia: A multivariate time series analysis
The interaction between dengue cases, entomological and meteorological variables has remained intricate for decades. Validated facts are important to form robust decision making with the adoption of safer and sustainable efforts. This study aims to elucidate the relationship between the variables in the long run and short-term dynamic focusing in Melaka, Malaysia, in an attempt to improve the understanding of the variables and their temporal associations. This study quantifies the variables on their temporal associations, potential time lags, and dynamic interplays between all the variable data sets. The research applies a Johansen Cointegration Test and Vector Error Correction Model to validate long term run and examine short-term deviations among dengue cases, temperature, ovitrap and sticky ovitrap data from 2020-2022. Empirical findings prove that temperature, sticky ovitrap index (SOI) and ovitrap index (OI) has a significant and unique long-run equilibrium relationship with dengue cases. The short-term equilibrium results display a robust causality between variables. The model fit elucidates 74.2% of the dynamics. The VECM model provides an excellent trade-off between goodness of fit and complexity in describing the variables examined. Previous dengue occurrences predicted a surge of new dengue cases while preserving the cyclical pattern. The model predicts the utility and efficacy of sticky ovitraps. It also validates ovitrap use as a surveillance tool and offers substantiation of the influence of temperature on the progression of dengue cases.
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