The practicality of Malaysia dengue outbreak forecasting model as an early warning system-Reference-Cited by-同舟云学术

The practicality of Malaysia dengue outbreak forecasting model as an early warning system

Published:2022-09 Issue:3 Volume:7 Page:510-525
ISSN:2468-0427
Container-title:Infectious Disease Modelling
language:en
Short-container-title:Infectious Disease Modelling

Author:

Ismail Suzilah,Fildes Robert,Ahmad Rohani,Wan Mohamad Ali Wan Najdah,Omar Topek

Publisher

Elsevier BV

Subject

Applied Mathematics,Infectious Diseases,Health Policy

Reference86 articles.

1. Correlational analysis of air pollution index levels on dengue surveillance data: A retrospective study in melaka, Malaysia;Ahmad Khairul Hakim;Journal of Sustainability Science and Management,2020

2. Temperature and dengue virus infection in mosquitoes: Independent effects on the immature and adult stages;Alto;The American Journal of Tropical Medicine and Hygiene,2013

3. Modeling the spread of dengue in Singapore;Ang,2002

4. Developing global climate anomalies suggest potential disease risks for 2006-2007;Anyamba;International Journal of Health Geographics,2006

5. Association of temperature and rainfall with Aedes mosquito population in 17th College of Universiti Putra Malaysia;Banulata;Malaysian Journal of Medicine and Health Sciences,2021

Cited by 5 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. Temporal and interaction dynamics of dengue cases, entomological and meteorological variables in Melaka, Malaysia: A multivariate time series analysis;2024-08-31

2. AI-based epidemic and pandemic early warning systems: A systematic scoping review;Health Informatics Journal;2024-07

3. A Coupled Statistical and Deterministic Model for Forecasting Climate-Driven Dengue Incidence in Selangor, Malaysia;Bulletin of Mathematical Biology;2024-05-28

4. Digital Transformation in the Control of Neglected Tropical Diseases: A Scoping Review;Current Tropical Medicine Reports;2024-04-10

5. Comparison of classical machine learning and ensemble techniques in the context of dengue severity prediction;2023 IEEE Colombian Caribbean Conference (C3);2023-11-22