Introduction to statistical methods for biosurveillance : with an emphasis on syndromic surveillance / / Ronald D. Fricker, Jr.

• Author: ProQuest (Firm); Fricker, Ronald D., 1960-
• TeilnehmendeR: ProQuest (Firm)
• Year of Publication: 2013
• Language: English
• Physical Description: xvi, 399 p. :; ill., maps.

"While the public health philosophy of the 20th Century -- emphasizing prevention -- is ideal for addressing natural disease outbreaks, it is not sufficient to confront 21st Century threats where adversaries may use biological weapons agents as part of a long-term campaign of aggression and terror. Health care providers and public health officers are among our first lines of defense. Therefore, we are building on the progress of the past three years to further improve the preparedness of our public health and medical systems to address current and future BW [biological warfare] threats and to respond with greater speed and flexibility to multiple or repetitive attacks." Homeland Security Presidential Directive 21 Bioterrorism is not a new threat in the 21st century -- thousands of years ago the plague and other contagious diseases were used in warfare -- but today the potential for catastrophic outcomes is greater than it has ever been. To address this threat, the medical and public health communities are putting various measures in place, including systems designed to pro-actively mon- itor populations for possible disease outbreaks"--Provided by publisher.

Table of Contents

Machine generated contents note: Part I. Introduction to Biosurveillance: 1. Overview; 2. Biosurveillance data; Part II. Situational Awareness: 3. Situational awareness for biosurveillance; 4. Descriptive statistics for displaying the situation; 5. Statistical models for evaluating the situation; Part III. Early Event Detection: 6. Design and performance evaluation; 7. Univariate temporal methods; 8. Multivariate temporal methods; 9. Spatio-temporal methods; Part IV. Putting It All Together: 10. Simulating biosurveillance data; 11. Applying the temporal methods to real data; 12. Comparing methods to better understand and improve; 13. Frontiers, open questions, and future research.