Quantifying the Impact of Climatic Factors on Dengue Incidence Using Generalized Linear Mixed Model with Spatio-Temporal Bayesian Poisson Random Effects Approach-Reference-Cited by-同舟云学术

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Quantifying the Impact of Climatic Factors on Dengue Incidence Using Generalized Linear Mixed Model with Spatio-Temporal Bayesian Poisson Random Effects Approach

Published:2021 Issue: Volume: Page:328-340
ISSN:1865-0929
Container-title:Communications in Computer and Information Science
language:
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Author:

Sapri Nik Nur Fatin Fatihah,Wan Yaacob Wan Fairos,Yap Bee Wah

Publisher

Springer Singapore

Link

https://link.springer.com/content/pdf/10.1007/978-981-16-7334-4_24

Reference32 articles.

1. Central for Disease Control and Prevention (CDC). Dengue (2021). https://www.cdc.gov/dengue/. Accessed 01 June 2020

2. World Health Organization. Dengue and severe dengue (2021) http://www.who.int/mediacentre/factsheets/fs117/en/. Accessed 01 June 2020

3. Lai, Y.: The climatic factors affecting dengue fever outbreaks in Southern Taiwan: an application of symbolic data analysis. BioMed. Eng. OnLine 17(148), 49–62 (2018)

4. Alkhaldy, I.: modelling the association of dengue fever cases with temperature and relative humidity in Jeddah, Saudi Arabia—a generalised linear model with break-point analysis. Acta Trop. 168, 9–15 (2017)

5. Talagala, T.: Distributed lag nonlinear modelling approach to identify relationship between climatic factors and dengue incidence in Colombo district, Sri Lanka. Epidemiol. Biostat. Public Health 12(4), e11522-1–e11522-8 (2015)

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