Using weather factors and google data to predict COVID-19 transmission in Melbourne, Australia: A time-series predictive model-Reference-Cited by-同舟云学术

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Using weather factors and google data to predict COVID-19 transmission in Melbourne, Australia: A time-series predictive model

Published:2023-03 Issue:3 Volume:9 Page:e13782
ISSN:2405-8440
Container-title:Heliyon
language:en
Short-container-title:Heliyon

Author:

McClymont Hannah^ORCID,Si Xiaohan^ORCID,Hu Wenbiao^ORCID

Publisher

Elsevier BV

Subject

Multidisciplinary

Reference72 articles.

1. WHO Coronavirus (COVID-19) Dashboard,2022

2. Tracking SARS-CoV-2 Variants,2022

3. Evaluation of the relative virulence of novel SARS-CoV-2 variants: a retrospective cohort study in Ontario, Canada;Fisman;CMAJ,2021

4. SARS-CoV-2 variants, spike mutations and immune escape;Harvey;Nat. Rev. Microbiol.,2021

5. Coronavirus (COVID-19) Case Numbers and Statistics;Department of Health - Australian Government,2022

Cited by 6 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Application of harmony search algorithm in optimizing autoregressive integrated moving average: A study on a data set of Coronavirus Disease 2019;Systems and Soft Computing;2024-12

2. Internet-based Surveillance Systems and Infectious Diseases Prediction: An Updated Review of the Last 10 Years and Lessons from the COVID-19 Pandemic;Journal of Epidemiology and Global Health;2024-08-14

3. LSTM-Powered COVID-19 prediction in central Thailand incorporating meteorological and particulate matter data with a multi-feature selection approach;Heliyon;2024-05

4. The effect of public health interventions on COVID-19 incidence in Queensland, Australia: a spatial cluster analysis;Infectious Diseases;2024-03-06

5. LSTM algorithm optimization for COVID-19 prediction model;Heliyon;2024-02

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