scholarly article | Q13442814 |
P50 | author | Crawford W. Revie | Q40954092 |
Fernanda C. Dórea | Q55475730 | ||
P2093 | author name string | Beverly J McEwen | |
Javier Sanchez | |||
W Bruce McNab | |||
P2860 | cites work | Dynamics of the 2001 UK Foot and Mouth Epidemic: Stochastic Dispersal in a Heterogeneous Landscape | Q56937256 |
Statistical Challenges Facing Early Outbreak Detection in Biosurveillance | Q57379640 | ||
A simulation model for assessing aberration detection methods used in public health surveillance for systems with limited baselines | Q30233117 | ||
Systematic review: surveillance systems for early detection of bioterrorism-related diseases | Q30233259 | ||
Retrospective time series analysis of veterinary laboratory data: preparing a historical baseline for cluster detection in syndromic surveillance | Q30577576 | ||
Comparing aberration detection methods with simulated data | Q30984310 | ||
Syndromic surveillance on the epidemiologist's desktop: making sense of much data | Q31006465 | ||
A simulation study comparing aberration detection algorithms for syndromic surveillance | Q33276259 | ||
Development and evaluation of a data-adaptive alerting algorithm for univariate temporal biosurveillance data | Q33499407 | ||
The foot-and-mouth epidemic in Great Britain: pattern of spread and impact of interventions | Q33942479 | ||
Descriptive epidemiology of the 2001 foot-and-mouth disease epidemic in Great Britain: the first five months | Q34110984 | ||
Estimation of the reproduction ratio (R(0)) of bluetongue based on serological field data and comparison with other BTV transmission models. | Q34554742 | ||
Exploratory analysis of methods for automated classification of laboratory test orders into syndromic groups in veterinary medicine | Q34625529 | ||
Using temporal context to improve biosurveillance | Q34762708 | ||
Outbreak detection through automated surveillance: a review of the determinants of detection | Q36649279 | ||
A monitoring system to detect changes in public health surveillance data | Q36739822 | ||
Using laboratory-based surveillance data for prevention: an algorithm for detecting Salmonella outbreaks | Q36880725 | ||
Predicting outbreak detection in public health surveillance: quantitative analysis to enable evidence-based method selection. | Q37129127 | ||
Veterinary syndromic surveillance: Current initiatives and potential for development | Q37884718 | ||
Automated time series forecasting for biosurveillance | Q38463725 | ||
Recombinant temporal aberration detection algorithms for enhanced biosurveillance | Q40162262 | ||
Algorithms for rapid outbreak detection: a research synthesis | Q40434730 | ||
Application of exponential smoothing for nosocomial infection surveillance | Q40946170 | ||
Statistical quality control methods in infection control and hospital epidemiology, part I: Introduction and basic theory | Q41743811 | ||
Stochastic model of the potential spread of highly pathogenic avian influenza from an infected commercial broiler operation in Georgia. | Q43317655 | ||
Landscape fragmentation and foot-and-mouth disease transmission | Q43804761 | ||
Measuring outbreak-detection performance by using controlled feature set simulations. | Q44610647 | ||
Space-time interaction as an indicator of local spread during the 2001 FMD outbreak in the UK. | Q44616514 | ||
Comparison of the early aberration reporting system (EARS) W2 methods to an adaptive threshold method | Q44963157 | ||
An evaluation model for syndromic surveillance: assessing the performance of a temporal algorithm. | Q45996498 | ||
Evaluation and extension of the cusum technique with an application to Salmonella surveillance | Q46349232 | ||
P433 | issue | 83 | |
P304 | page(s) | 20130114 | |
P577 | publication date | 2013-04-10 | |
P1433 | published in | Journal of the Royal Society Interface | Q2492390 |
P1476 | title | Syndromic surveillance using veterinary laboratory data: data pre-processing and algorithm performance evaluation | |
P478 | volume | 10 |
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Q36298297 | A simulation study to evaluate the performance of five statistical monitoring methods when applied to different time-series components in the context of control programs for endemic diseases |
Q64125289 | Animal health syndromic surveillance: a systematic literature review of the progress in the last 5 years (2011-2016) |
Q45758546 | Assessment of Several Algorithms for Outbreak Detection using BovineMeat Inspection Data for Syndromic Surveillance: A Pilot Study on Whole CarcassCondemnation Rate. |
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Q39350029 | Effectiveness and Cost Efficiency of Different Surveillance Components for Proving Freedom and Early Detection of Disease: Bluetongue Serotype 8 in Cattle as Case Study for Belgium, France and the Netherlands |
Q91928815 | Enhancing the monitoring of fallen stock at different hierarchical administrative levels: an illustration on dairy cattle from regions with distinct husbandry, demographical and climate traits |
Q36945193 | Evaluation of a Multivariate Syndromic Surveillance System for West Nile Virus |
Q30932623 | Exploring the surveillance potential of mortality data: nine years of bovine fallen stock data collected in Catalonia (Spain). |
Q38782166 | Influenza detection and prediction algorithms: comparative accuracy trial in Östergötland county, Sweden, 2008-2012. |
Q60394931 | Optimizing syndromic health surveillance in free ranging great apes: The case of Gombe National Park |
Q30883187 | Pilot simulation study using meat inspection data for syndromic surveillance: use of whole carcass condemnation of adult cattle to assess the performance of several algorithms for outbreak detection. |
Q30717793 | Syndromic surveillance using veterinary laboratory data: algorithm combination and customization of alerts |
Q91659748 | Utility of examining fallen stock data to monitor health-related events in equids: Application to an outbreak of West Nile Virus in France in 2015 |
Q33683034 | Value of evidence from syndromic surveillance with cumulative evidence from multiple data streams with delayed reporting |
Q45759692 | Vetsyn: Veterinary Syndromic Surveillance Streamlined into one RPackage. |
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