2010•Unpublished venueRequires access

Recent research in public health surveillance and health management

Kwok‐Leung Tsui, David M. Goldsman, Wei Jiang, Zoie Shui-Yee Wong

Open publisher page 4 citations

Abstract

While the challenges of the next pandemic outbreak are overwhelming, either from swine flu, other infectious disease, bioterrorism, timely detection of disease outbreaks is most important for public health surveillance and society safety and stability. In public health surveillance, the objective is to systematically collect, analyze, and interpret public health data (chronic or infectious diseases) in order to understand trends, to detect changes in disease incidence and death rates, and to plan, implement, and evaluate public health practice. Recently much research has been conducted to develop methods and algorithms for health surveillance and disease detection. This paper presents an overview and reviews the recent research methods on temporal and spatiotemporal surveillance. Specific research challenges and future research directions are discussed. A real life example is used to compare the performance of three currently used surveillance methods, scan, EWMA, and CUSUM.

About this research paper

What this paper is about

While the challenges of the next pandemic outbreak are overwhelming, either from swine flu, other infectious disease, bioterrorism, timely detection of disease outbreaks is most important for public health surveillance and society safety and stability. In public health surveillance, the objective is to systematically collect, analyze, and interpret public health data (chronic or infectious diseases) in order to understand trends, to detect changes in disease incidence and death rates, and to plan, implement, and evaluate public health practice. Recently much research has been conducted to develop methods and algorithms for health surveillance and disease detection. This paper presents an overview and reviews the recent research methods on temporal and spatiotemporal surveillance. Specific research challenges and future research directions are discussed. A real life example is used to compare the performance of three currently used surveillance methods, scan, EWMA, and CUSUM.

Why it matters

OpenAlex reports 4 citations for this work. Citation counts describe recorded attention and do not establish research quality.

Key contribution

A contribution statement is not available in the OpenAlex record.

Method / approach

Method details are not available in the OpenAlex metadata.

Main findings

Findings are not separately available in the OpenAlex metadata.

Limitations

Limitations are not available in the OpenAlex metadata.

Applications

Application details are not available in the OpenAlex metadata.

Available abstract

While the challenges of the next pandemic outbreak are overwhelming, either from swine flu, other infectious disease, bioterrorism, timely detection of disease outbreaks is most important for public health surveillance and society safety and stability. In public health surveillance, the objective is to systematically collect, analyze, and interpret public health data (chronic or infectious diseases) in order to understand trends, to detect changes in disease incidence and death rates, and to plan, implement, and evaluate public health practice. Recently much research has been conducted to develop methods and algorithms for health surveillance and disease detection. This paper presents an overview and reviews the recent research methods on temporal and spatiotemporal surveillance. Specific research challenges and future research directions are discussed. A real life example is used to compare the performance of three currently used surveillance methods, scan, EWMA, and CUSUM.

Key concepts: Disease surveillance, Public health, Public health surveillance, CUSUM, Pandemic, Outbreak, Infectious disease (medical specialty), Environmental health

Related papers

Back to paper searchBrowse research topicsOriginal source
Recent research in public health surveillance and health management — Research Paper | ScholarLens