West Nile Virus Risk Assessment and Forecasting Using Statistical and Dynamical Models

Ahmed Abdelrazec; Yurong Cao; Xin Gao; Huaiping Zhu; Paul Proctor; Hui Zheng

doi:10.1002/9781118630013.ch4

West Nile Virus Risk Assessment and Forecasting Using Statistical and Dynamical Models

Ahmed Abdelrazec^*
, Yurong Cao
, Xin Gao
, Huaiping Zhu
, Paul Proctor
, Hui Zheng

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

1 Scopus citations

Abstract

To strengthen the anticipation capacity of West Nile virus (WNV), we develop a new index, which accounts for both the weather condition (temperature and precipitation) and the impact of bird population, in a dynamical model. The index is created by determining the dynamical minimum infection rate (DMIR) of WNV introduction into Ontario, Canada, through different pathways. DMIR is the first index that uses the dynamical models to test and forecast the weekly risk of WNV, by explicitly considering the temperature impact on mosquito abundance. We have compared this new index with another index of minimum infection rate (MIR) by using surveillance data from Peel region, Ontario, to verify our formula.

Original language	English
Title of host publication	Analyzing and Modeling Spatial and Temporal Dynamics of Infectious Diseases
Publisher	Wiley-Blackwell
Pages	77-95
Number of pages	19
ISBN (Electronic)	9781118630013
ISBN (Print)	9781118629932
DOIs	https://doi.org/10.1002/9781118630013.ch4
State	Published - 30 Jan 2015
Externally published	Yes

Bibliographical note

Publisher Copyright:
© 2015 John Wiley & Sons, Inc. All rights reserved.

Keywords

Dynamical minimum infection rate
Dynamical models
Mosquito abundance
Risk assessment
Temperature
West Nile virus

ASJC Scopus subject areas

General Medicine

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10.1002/9781118630013.ch4

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abstract = "To strengthen the anticipation capacity of West Nile virus (WNV), we develop a new index, which accounts for both the weather condition (temperature and precipitation) and the impact of bird population, in a dynamical model. The index is created by determining the dynamical minimum infection rate (DMIR) of WNV introduction into Ontario, Canada, through different pathways. DMIR is the first index that uses the dynamical models to test and forecast the weekly risk of WNV, by explicitly considering the temperature impact on mosquito abundance. We have compared this new index with another index of minimum infection rate (MIR) by using surveillance data from Peel region, Ontario, to verify our formula.",

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AU - Abdelrazec, Ahmed

AU - Cao, Yurong

AU - Gao, Xin

AU - Zhu, Huaiping

AU - Proctor, Paul

AU - Zheng, Hui

PY - 2015/1/30

Y1 - 2015/1/30

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AB - To strengthen the anticipation capacity of West Nile virus (WNV), we develop a new index, which accounts for both the weather condition (temperature and precipitation) and the impact of bird population, in a dynamical model. The index is created by determining the dynamical minimum infection rate (DMIR) of WNV introduction into Ontario, Canada, through different pathways. DMIR is the first index that uses the dynamical models to test and forecast the weekly risk of WNV, by explicitly considering the temperature impact on mosquito abundance. We have compared this new index with another index of minimum infection rate (MIR) by using surveillance data from Peel region, Ontario, to verify our formula.

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KW - Dynamical models

KW - Mosquito abundance

KW - Risk assessment

KW - Temperature

KW - West Nile virus

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M3 - Chapter

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EP - 95

BT - Analyzing and Modeling Spatial and Temporal Dynamics of Infectious Diseases

PB - Wiley-Blackwell

ER -

West Nile Virus Risk Assessment and Forecasting Using Statistical and Dynamical Models

Abstract

Bibliographical note

Keywords

ASJC Scopus subject areas

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