| Preface |
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xi | |
| Acknowledgments |
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xv | |
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Part I Introduction to Biosurveillance |
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3 | (20) |
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1.1 What Is Biosurveillance? |
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5 | (5) |
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1.2 Biosurveillance Systems |
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10 | (5) |
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1.3 Biosurveillance Utility and Effectiveness |
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15 | (5) |
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1.4 Discussion and Summary |
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20 | (3) |
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23 | (32) |
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25 | (1) |
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2.2 Types of Biosurveillance Data |
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26 | (11) |
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37 | (13) |
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2.4 Discussion and Summary |
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50 | (5) |
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Part II Situational Awareness |
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3 Situational Awareness for Biosurveillance |
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55 | (12) |
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3.1 What Is Situational Awareness? |
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57 | (1) |
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3.2 A Theoretical Situational Awareness Model |
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57 | (3) |
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3.3 Biosurveillance Situational Awareness |
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60 | (1) |
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3.4 Extending the Situational Awareness Model: Situated Cognition |
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61 | (3) |
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3.5 Discussion and Summary |
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64 | (3) |
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4 Descriptive Statistics for Comprehending the Situation |
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67 | (44) |
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4.1 Numerical Descriptive Statistics |
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70 | (14) |
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4.2 Graphical Descriptive Statistics |
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84 | (23) |
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4.3 Discussion and Summary |
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107 | (4) |
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5 Statistical Models for Projecting the Situation |
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111 | (38) |
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5.1 Modeling Time Series Data |
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114 | (4) |
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118 | (11) |
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5.3 Regression-Based Models |
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129 | (9) |
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5.4 ARMA and ARIMA Models |
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138 | (3) |
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5.5 Change Point Analysis |
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141 | (4) |
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5.6 Discussion and Summary |
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145 | (4) |
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Part III Early Event Detection |
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6 Early Event Detection Design and Performance Evaluation |
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149 | (29) |
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6.1 Notation and Assumptions |
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152 | (2) |
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6.2 Design Points and Principles |
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154 | (3) |
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6.3 Early Event Detection Methods Differ from Other Statistical Tests |
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157 | (9) |
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6.4 Measuring Early Event Detection Performance |
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166 | (9) |
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6.5 Discussion and Summary |
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175 | (3) |
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7 Univariate Temporal Methods |
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178 | (40) |
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7.1 Historical Limits Detection Method |
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182 | (1) |
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7.2 Shewhart Detection Method |
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183 | (9) |
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7.3 Cumulative Sum Detection Method |
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192 | (11) |
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7.4 Exponentially Weighted Moving Average Detection Method |
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203 | (9) |
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212 | (3) |
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7.6 Discussion and Summary |
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215 | (3) |
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8 Multivariate Temporal and Spatio-temporal Methods |
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218 | (35) |
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8.1 Multivariate Temporal Methods |
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221 | (21) |
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8.2 Spatio-temporal Methods |
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242 | (6) |
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8.3 Discussion and Summary |
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248 | (5) |
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Part IV Putting It All Together |
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9 Applying the Temporal Methods to Real Data |
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253 | (28) |
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9.1 Using Early Event Detection Methods to Detect Outbreaks and Attacks |
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257 | (11) |
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9.2 Assessing How Syndrome Definitions Affect Early Event Detection Performance |
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268 | (11) |
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9.3 Discussion and Summary |
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279 | (2) |
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10 Comparing Methods to Better Understand and Improve Biosurveillance Performance |
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281 | (24) |
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10.1 Performance Comparisons: A Univariate Example |
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285 | (10) |
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10.2 Performance Comparisons: A Multivariate Example |
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295 | (6) |
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10.3 Discussion and Summary |
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301 | (4) |
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A A Brief Review of Probability, Random Variables, and Some Important Distributions |
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305 | (30) |
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308 | (5) |
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313 | (5) |
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A.3 Some Important Probability Distributions |
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318 | (17) |
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B Simulating Biosurveillance Data |
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335 | (31) |
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337 | (6) |
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B.2 Simulating Biosurveillance Data |
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343 | (21) |
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B.3 Discussion and Summary |
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364 | (2) |
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366 | (15) |
| References |
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381 | (10) |
| Author Index |
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391 | (4) |
| Subject Index |
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395 | |