Exploring the usefulness of Functional Data Analysis for Health Surveillance

Zezhong Wang; Inez Maria Zwetsloot

Exploring the usefulness of Functional Data Analysis for Health Surveillance

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

Abstract

Health surveillance is the process of ongoing systematic collection, analysis, interpretation, and dissemination of health data for the purpose of preventing and controlling disease, injury, and other health problems. Health surveillance data is often recorded continuously over a selected time interval or intermittently at several discrete time points. These can often be treated as functional data, and hence functional data analysis (FDA) can be applied to model and analyze these type of health data. One objective in health surveillance is early event detection. Statistical process monitoring tools are often used for online event detecting. In this paper, we explore the usefulness of FDA for prospective health surveillance and propose two strategies for monitoring using control charts. We apply these strategies to monthly ovitrap index data. These vector data are used in Hong Kong as part of its dengue control plan.

Original language	English
Title of host publication	XIII^th INTERNATIONAL WORKSHOP on Intelligent Statistical Quality Control 2019
Subtitle of host publication	PROCEEDINGS
Publisher	City University of Hong Kong
Pages	261-276
Publication status	Published - Aug 2019
Event	13th International Workshop on Intelligent Statistical Quality Control 2019, ISQC 2019 - City University of Hong Kong, Hong Kong, China Duration: 12 Aug 2019 → 14 Aug 2019 http://www.cityu.edu.hk/csie/ISQC2019/index.htm

Publication series

Name	International Workshop on Intelligent Statistical Quality Control, ISQC

Conference

Conference	13th International Workshop on Intelligent Statistical Quality Control 2019, ISQC 2019
Place	Hong Kong, China
Period	12/08/19 → 14/08/19
Internet address	http://www.cityu.edu.hk/csie/ISQC2019/index.htm

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

Research Keywords

Control Chart
Dengue surveillance
Functional Data Analysis (FDA)
Functional Principal Component Analysis (FPCA)
Health Surveillance
Statistical Process Monitoring (SPM)

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title = "Exploring the usefulness of Functional Data Analysis for Health Surveillance",

abstract = "Health surveillance is the process of ongoing systematic collection, analysis, interpretation, and dissemination of health data for the purpose of preventing and controlling disease, injury, and other health problems. Health surveillance data is often recorded continuously over a selected time interval or intermittently at several discrete time points. These can often be treated as functional data, and hence functional data analysis (FDA) can be applied to model and analyze these type of health data. One objective in health surveillance is early event detection. Statistical process monitoring tools are often used for online event detecting. In this paper, we explore the usefulness of FDA for prospective health surveillance and propose two strategies for monitoring using control charts. We apply these strategies to monthly ovitrap index data. These vector data are used in Hong Kong as part of its dengue control plan.",

keywords = "Control Chart, Dengue surveillance, Functional Data Analysis (FDA), Functional Principal Component Analysis (FPCA), Health Surveillance, Statistical Process Monitoring (SPM), Control Chart, Dengue surveillance, Functional Data Analysis (FDA), Functional Principal Component Analysis (FPCA), Health Surveillance, Statistical Process Monitoring (SPM), Control Chart, Dengue surveillance, Functional Data Analysis (FDA), Functional Principal Component Analysis (FPCA), Health Surveillance, Statistical Process Monitoring (SPM)",

author = "Zezhong Wang and Zwetsloot, \{Inez Maria\}",

year = "2019",

month = aug,

language = "English",

series = "International Workshop on Intelligent Statistical Quality Control, ISQC",

publisher = "City University of Hong Kong",

pages = "261--276",

booktitle = "XIIIth INTERNATIONAL WORKSHOP on Intelligent Statistical Quality Control 2019",

note = "13th International Workshop on Intelligent Statistical Quality Control 2019, ISQC 2019 ; Conference date: 12-08-2019 Through 14-08-2019",

url = "http://www.cityu.edu.hk/csie/ISQC2019/index.htm",

}

Wang, Z & Zwetsloot, IM 2019, Exploring the usefulness of Functional Data Analysis for Health Surveillance. in XIII^th INTERNATIONAL WORKSHOP on Intelligent Statistical Quality Control 2019: PROCEEDINGS. International Workshop on Intelligent Statistical Quality Control, ISQC, City University of Hong Kong, pp. 261-276, 13th International Workshop on Intelligent Statistical Quality Control 2019, ISQC 2019, Hong Kong, China, 12/08/19.

Exploring the usefulness of Functional Data Analysis for Health Surveillance. / Wang, Zezhong ; Zwetsloot, Inez Maria.
XIII^th INTERNATIONAL WORKSHOP on Intelligent Statistical Quality Control 2019: PROCEEDINGS. City University of Hong Kong, 2019. p. 261-276 (International Workshop on Intelligent Statistical Quality Control, ISQC).

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

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T1 - Exploring the usefulness of Functional Data Analysis for Health Surveillance

AU - Wang, Zezhong

AU - Zwetsloot, Inez Maria

PY - 2019/8

Y1 - 2019/8

N2 - Health surveillance is the process of ongoing systematic collection, analysis, interpretation, and dissemination of health data for the purpose of preventing and controlling disease, injury, and other health problems. Health surveillance data is often recorded continuously over a selected time interval or intermittently at several discrete time points. These can often be treated as functional data, and hence functional data analysis (FDA) can be applied to model and analyze these type of health data. One objective in health surveillance is early event detection. Statistical process monitoring tools are often used for online event detecting. In this paper, we explore the usefulness of FDA for prospective health surveillance and propose two strategies for monitoring using control charts. We apply these strategies to monthly ovitrap index data. These vector data are used in Hong Kong as part of its dengue control plan.

AB - Health surveillance is the process of ongoing systematic collection, analysis, interpretation, and dissemination of health data for the purpose of preventing and controlling disease, injury, and other health problems. Health surveillance data is often recorded continuously over a selected time interval or intermittently at several discrete time points. These can often be treated as functional data, and hence functional data analysis (FDA) can be applied to model and analyze these type of health data. One objective in health surveillance is early event detection. Statistical process monitoring tools are often used for online event detecting. In this paper, we explore the usefulness of FDA for prospective health surveillance and propose two strategies for monitoring using control charts. We apply these strategies to monthly ovitrap index data. These vector data are used in Hong Kong as part of its dengue control plan.

KW - Control Chart

KW - Dengue surveillance

KW - Functional Data Analysis (FDA)

KW - Functional Principal Component Analysis (FPCA)

KW - Health Surveillance

KW - Statistical Process Monitoring (SPM)

KW - Control Chart

KW - Dengue surveillance

KW - Functional Data Analysis (FDA)

KW - Functional Principal Component Analysis (FPCA)

KW - Health Surveillance

KW - Statistical Process Monitoring (SPM)

KW - Control Chart

KW - Dengue surveillance

KW - Functional Data Analysis (FDA)

KW - Functional Principal Component Analysis (FPCA)

KW - Health Surveillance

KW - Statistical Process Monitoring (SPM)

UR - https://www.scopus.com/pages/publications/85086451861

UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-85086451861&origin=recordpage

M3 - RGC 32 - Refereed conference paper (with host publication)

T3 - International Workshop on Intelligent Statistical Quality Control, ISQC

SP - 261

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BT - XIIIth INTERNATIONAL WORKSHOP on Intelligent Statistical Quality Control 2019

PB - City University of Hong Kong

T2 - 13th International Workshop on Intelligent Statistical Quality Control 2019, ISQC 2019

Y2 - 12 August 2019 through 14 August 2019

ER -

Exploring the usefulness of Functional Data Analysis for Health Surveillance

Abstract

Publication series

Conference

UN SDGs

Research Keywords

Other Access Options

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