Development of Early Warning Models
Development of Early Warning Models
This chapter provides brief introductions to the basic models and algorithms for the early warning of infectious diseases. First, it describes several types and principles of early warning models. It then discusses several indicators for evaluating the effectiveness of early warning models.
Shewhart chart, Ratio chart, Historical limits method, Moving Percentile Method, EWMA, CUSUM method, Spatio-temporal scan statistics, Algorithm evaluation
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Lan, Yajia
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Zhou, Dinglun
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Zhang, Honglong
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Lai, Shengjie
b57a5fe8-cfb6-4fa7-b414-a98bb891b001
25 April 2017
Lan, Yajia
1c3b4eec-04e2-4852-898d-af5ab6a95b07
Zhou, Dinglun
4dcccc41-a503-4e9b-aca4-7c06f8ae3bf8
Zhang, Honglong
35d0ccf0-0422-4fcd-a949-a74a83f75e51
Lai, Shengjie
b57a5fe8-cfb6-4fa7-b414-a98bb891b001
Lan, Yajia, Zhou, Dinglun, Zhang, Honglong and Lai, Shengjie
(2017)
Development of Early Warning Models.
In,
Yang, Weizhong
(ed.)
Early Warning for Infectious Disease Outbreak Theory and Practice.
1 ed.
London.
Elsevier, .
Record type:
Book Section
Abstract
This chapter provides brief introductions to the basic models and algorithms for the early warning of infectious diseases. First, it describes several types and principles of early warning models. It then discusses several indicators for evaluating the effectiveness of early warning models.
Text
Chapter 3 Development of Early Warning Models
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More information
Published date: 25 April 2017
Keywords:
Shewhart chart, Ratio chart, Historical limits method, Moving Percentile Method, EWMA, CUSUM method, Spatio-temporal scan statistics, Algorithm evaluation
Organisations:
WorldPop, Geography & Environment
Identifiers
Local EPrints ID: 411910
URI: http://eprints.soton.ac.uk/id/eprint/411910
PURE UUID: c541d8a6-9a8f-45cc-aa1f-26a4ee74fe91
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Date deposited: 29 Jun 2017 16:31
Last modified: 16 Mar 2024 04:36
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Contributors
Author:
Yajia Lan
Author:
Dinglun Zhou
Author:
Honglong Zhang
Editor:
Weizhong Yang
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