Early Warning for Infectious Disease Outbreak

Theory and Practice

Weizhong Yang

• Publisher: Academic Press
• Year: 2017
• ISBN:
  9780128124833
• Topic: Technology & Engineering
• Subtopic: Industrial Health & Safety
• Index: Technology & Engineering

Early Warning for Infectious Disease Outbreak: Theory and Practice is divided into three parts, with the first section introducing basic theory and key technologies of early warning and the basic principles of infectious disease surveillance. The second section introduces the technical details in the process of establishment, operation and usage of CIDARS and Pudong Syndromic Surveillance and the Early Warning System of the Shanghai World Expo.

The third part explores the study of early warning technology, collecting some useful exploration in the fields of infectious diseases involving sentinel setting, data analysis, influence factors study, calculation and evaluation of early warning models.

• Provide insights into the theory and practice of early warning systems that have been evaluated and shown to be effective
• Presents a synopsis of current state-of-the-art practices and a starting point for the development and evaluation of new methods
• Covers applied research and complete case studies that focus on local, regional, national and international implementation
• Includes techniques from other fields, such as intelligence and engineering
• Explores future innovations in biosurveillance, including advances in analytical methods, modeling and simulation
• Addresses policy and organizational issues related to the construction of biosurveillance systems

Part 1

Theories and Key Technologies of Infectious Disease Early Warning

Introduction to Theories and Key Technologies of Infectious Disease Early Warning

This first part includes Chapters 1–6, which introduce the basic theory and key technology of infectious disease surveillance and early warning, as well as the data analysis and outbreak early detection model development, signal verification and response, and development and evaluation of an early warning system.

Chapter 1

Introduction

Weizhong Yang⁎; Yajia Lan^†; Qiao Sun^‡; Jinfeng Wang^§; Zhongjie Li⁎ ^⁎ Chinese Center for Disease Control and Prevention, Beijing, China
^† Sichuan University, Chengdu, China
^‡ Shanghai Pudong New Area Center for Disease Control and Prevention, Shanghai, China
^§ Institute of Geographic Sciences and Natural Resources Research Chinese Academy of Sciences, Beijing, China

Abstract

This chapter provides an overview of the basic theory of early warning for infectious diseases, including definitions of surveillance, early warning and prediction; the characteristics of early warning (surveillance, information for action, timeliness, insufficiency, and the uncertainty of information); a conceptual framework of an early warning system for infectious diseases (the target setting, data collection and analysis, disseminating early warning signals, response actions, and evaluation); classifying early warning based on the data sources (case-based, event-based, laboratory-based, or syndromic surveillance). The significance of early warning for infectious diseases, the status quo and research and application trends in the field are also highlighted.

Keywords

Infectious disease; Outbreak; Surveillance; Early warning; Aberration detection; Prediction; Definition; Classification; Framework; China

In recent years, emerging infectious diseases (EIDs), such as Middle East Respiratory Syndrome (MERS), Ebola and Zika virus diseases, have indicated that infectious diseases pose a current and major global health threat to humanity. The rapid global movement of people and goods increases the hidden dangers and the potential spread of infectious diseases across international borders. EIDs that occur in one part of the world may be found in other places within a short period of time. In 2015, for instance, MERS was imported into South Korea by an infected traveler, resulting in an increased number of MERS cases (186 cases total) and one exported case to China in only 2 months (Moran, 2015). Early detection and identification of abnormal increases in surveillance data are essential for the effective control of infectious disease outbreaks and subsequent spread of emerging or unexplained diseases.

The early warning of infectious diseases is to analyze surveillance data with specialized technologies for early detection and warning of notable aberrations. “Surveillance” and “early warning” are closely connected: the former provide the foundation for the latter, and the latter is an essential application of the former. In recent years, the rapid development of epidemiology, bioinformatics, computer science, measurement and statistics, systems engineering, environmental science, geography, medicine, veterinary science, artificial intelligence, and other surveillance-related interdisciplinary theories and technologies have boosted the rapid development of surveillance and early warning technologies with an increasingly important role in controlling infectious diseases.

1.1 Basic Terminologies: Surveillance, Early Warning, and Prediction

Disease surveillance often refers to the continuous, systematic collection, analysis, and interpretation of disease outbreaks and their related factors and to the use of such findings in guiding disease control practice. Infectious disease surveillance is often the earliest and most commonly used field. The most basic applications of surveillance include describing the magnitude and patterns of infectious diseases, predicting epidemic trends, early detecting outbreaks, and discovering EIDs. Surveillance data can be directly applied to formulating, implementing and evaluating infectious disease control programs to help decision makers rationally plan and allocate resources and to inform public health education (Wagner et al., 2006).

Infectious disease early warning sends out signals related to an outbreak of infectious disease(s), before or at the early stage of the event(s) in order to warn people of the potential public health risks, and scope or extent of its occurrence. Different terms are used in the documentation to describe infectious diseases warning, and among the most commonly used are “early warning” and “outbreak detection,” and the term “detection of aberration” refers to infectious disease early warning based on quantitative data analysis. Early warning generally analyzes surveillance information, giving out timely warnings on any signs or abnormalities in line with laws, regulations, and relevant provisions of the emergency plan, allowing for the facilitation and ease of making appropriate and corresponding recommendations.

Early warning system for infectious disease is an essential component of public health emergency work and has four characteristics:

(1) Surveillance information-based: Scientific early warning must be based on timely and accurate surveillance data. Information on the occurrence and influencing factors of infectious diseases can be collected via several effective and sensitive surveillance systems and channels and analyzed to reveal the occurrence and development of infectious diseases for timely detection of “abnormal increase” of the incidence, so as to warn relevant responsible departments, institutions, and population that may be affected by the diseases.

(2) Timeliness: It is essential for infectious disease early warning to be timely in its detection and warning during the early stages of outbreaks. During the course of the outbreak, the negative impact caused by infectious diseases rapidly increase over time. As shown in Fig. 1.1, when people in the community are infected with the Ebola virus, cases will increase rapidly without timely detection or measures to control the epidemic (WHO, 2016). Early warning provides an opportunity to implement response measures early that may otherwise be missed. For a specific early warning system, timeliness is represented by the lag time between the onset of the outbreak and when the outbreak is actually detected by the early warning system. Therefore, enhancing timeliness means reducing the lag time, either by using different types of data, improving the collection of surveillance data, or by adopting optimized early warning algorithms.

Fig. 1.1 Cumulative number of suspected, probable, and confirmed cases of the Ebola virus in Guinea, Liberia, and Sierra Leone, Mar. 25, 2014 to Jan. 17, 2016, by date from the WHO Situation Report, n=28,602.

(3) Information for action: The aim of early warning is to provide evidence-based guidance resulting in an informed and targeted response for th...

Table of contents

• Cover image
• Title page
• Table of Contents
• Copyright
• Dedication
• List of contributors
• Foreword
• Preface
• Acknowledgments
• List of abbreviations
• Part 1: Theories and Key Technologies of Infectious Disease Early Warning
• Part 2: Practices and Implementation of Early Warning
• Part 3: Exploratory Research on Early Warning Technology
• Index