Development of Reporting Guidelines for Animal Health Surveillance-AHSURED.

With the current trend in animal health surveillance toward risk-based designs and a gradual transition to output-based standards, greater flexibility in surveillance design is both required and allowed. However, the increase in flexibility requires more transparency regarding surveillance, its activities, design and implementation. Such transparency allows stakeholders, trade partners, decision-makers and risk assessors to accurately interpret the validity of the surveillance outcomes.

A modified TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) applied to choosing appropriate selection methods in ongoing surveillance for Avian Influenza in Canada.

To achieve an appropriate and efficient sample in a surveillance program, the goals of the program should drive a careful consideration of the selection method or combination of selection methods to be applied. Therefore, the ongoing analysis and assessment of a surveillance system may include an assessment of the ability of the applied selection methods to generate an appropriate sample. There may be opinions from many technical experts (TEs) and many criteria to consider in a surveillance system so there is a need for methods to combine knowledge, priorities and preferences from a group of TEs.

Assessing the sensitivity of bovine tuberculosis surveillance in Canada's cattle population, 2009-2013.

The objectives of this study were (1) to estimate the annual sensitivity of Canada's bTB surveillance system and its three system components (slaughter surveillance, export testing and disease investigation) using a scenario tree modelling approach, and (2) to identify key model parameters that influence the estimates of the surveillance system sensitivity (SSSe). To achieve these objectives, we designed stochastic scenario tree models for three surveillance system components included in the analysis. Demographic data, slaughter data, export testing data, and disease investigation data from 2009 to 2013 were extracted for input into the scenario trees.

Comparing capture-recapture methods for estimation of the size of small and medium-sized populations using empirical data on commercial turkey farms in Canada.

The study objectives were (1) to conduct a systematic review of the performance of capture-recapture methods; (2) to use empirical data to estimate population size in a small-sized population (turkey breeder farms) and a medium-sized population (meat turkey farms) by applying two-source capture-recapture methods (the Lincoln-Petersen, the Chapman, and Chao's lower-bound estimators) and multi-source capture-recapture methods (the log-linear modeling and sample coverage approaches); and (3) to compare the performance of these methods in predicting the true population sizes (2007 data). Our set-up was unique in that we knew the population sizes for turkey breeder farms (99) and meat turkey farms (592) in Canada in 2007, which we applied as our true population sizes, and had surveillance data from the Canadian Notifiable Avian Influenza Surveillance System (2008-2012). We defined each calendar year of sampling as a data source.

Estimation of the population size of Canadian commercial poultry farms by log-linear capture-recapture analysis.

The objective of this study was to estimate the population size of Canadian poultry farms in 3 subpopulations (British Columbia, Ontario, and Other) by poultry category. We used data for 2008 to 2011 from the Canadian Notifiable Avian Influenza (NAI) Surveillance System (CanNAISS). Log-linear capture-recapture models were applied to estimate the number of commercial chicken and turkey farms.

Adapting a scenario tree model for freedom from disease as surveillance progresses: the Canadian notifiable avian influenza model.

Scenario tree models with temporal discounting have been applied in four continents to support claims of freedom from animal disease. Recently, a second (new) model was developed for the same population and disease. This is a natural development because surveillance is a dynamic process that needs to adapt to changing circumstances - the difficulty is the justification for, documentation of, presentation of and the acceptance of the changes.

A population health surveillance theory.

Objectives: Despite its extensive use, the term "Surveillance" often takes on various meanings in the scientific literature pertinent to public health and animal health. A critical appraisal of this literature also reveals ambiguities relating to the scope and necessary structural components underpinning the surveillance process. The authors hypothesized that these inconsistencies translate to real or perceived deficiencies in the conceptual framework of population health surveillance.

Conceptual evaluation of population health surveillance programs: method and example.

Veterinary and public health surveillance programs can be evaluated to assess and improve the planning, implementation and effectiveness of these programs. Guidelines, protocols and methods have been developed for such evaluation. In general, they focus on a limited set of attributes (e.

A scenario tree model for the Canadian Notifiable Avian Influenza Surveillance System and its application to estimation of probability of freedom and sample size determination.

In 2008, Canada designed and implemented the Canadian Notifiable Avian Influenza Surveillance System (CanNAISS) with six surveillance activities in a phased-in approach. CanNAISS was a surveillance system because it had more than one surveillance activity or component in 2008: passive surveillance; pre-slaughter surveillance; and voluntary enhanced notifiable avian influenza surveillance. Our objectives were to give a short overview of two active surveillance components in CanNAISS; describe the CanNAISS scenario tree model and its application to estimation of probability of populations being free of NAI virus infection and sample size determination.