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Risk-based surveillance

Complex 2-stage risk-based surveillance - calculation of surveillance sensitivity based on herd testing data

Herd-level risk factor

Animal-level risk factor

Diagnostic test

Paste herd testing data in the space below. Include only one row per herd sampled. Data columns can be in any order but must include columns for the number of high-risk animals tested (labeled 'HRTested'), the number of low-risk animals tested (labeled 'LRTested') and herd risk-group (labeled 'HerdRisk'). 'HerdRisk' must be coded as high-risk = 1 and low-risk = 0. Columns for herd id and proportion of the herd that is high-risk (labeled 'HRProportion') are optional. A header row specifying column names must also be included.

Download example data

This page calculates the surveillance sensitivity for complex risk-based surveillance with 2-stage sampling, based on actual herd-testing data. For example, a survey in which high risk herds are preferentially targeted for testing, and high-risk animals preferentially targeted within selected herds. In addition, different test sensitivities can be applied to high-risk and low-risk animals in each sampled herd (i.e. sensitivity is based on risk-group). If test sensitivity varies between groups but there is no difference in risk of disease use a relative risk value of 1. The analysis is based on actual sampling results for each herd, assuming that all results are negative.

The analysis assumes 2-stage sampling to account for clustering of disease (for example at the herd, flock or village level) and that the effective specificity of the surveillance system is equal to one (all positives are followed up to ensure that they are not false positives):

Two risk factors are considered, one at the herd level and one at the animal level. For each risk factor the following information is required:

  • The relative risk: this measures the risk of herds (or animals) in the high-risk group being infected, relative to the risk of herds (animals) in the low-risk group being infected. For risk-based surveillance, this should usually be greater than 1; and
  • The population proportion: this is the proportion of herds (or animals) from their respective populations that are in the high-risk group. Herd-specific values will be used where available, or the population value entered here will be used where herd-specific values are not available.

In addition, the following parameters are required:

  • The design prevalence at the herd and animal levels: this is the assumed prevalence of disease (proportion of infected herds and infected animals respectively), if the disease is present in the population. It is used as a standard by which the sensitivity of the surveillance can be evaluated;
  • For the diagnostic test, performance depends on risk group:
    •   . The sensitivity of the test for animals in the high risk group; and
    •   . The sensitivity of the test for animals in the low risk group.
  • Prior confidence of freedom: this is the estimated confidence that the population was free of disease (at the design prevalence) before the surveillance was done and is used to estimate confidence of freedom following completion of the surveillance; and
  • Detailed data on the number of animals tested in each herd, including: herd-risk group, number of high-risk animals tested, number of low-risk animals tested, herd id (optional) and herd-specific population proportion of high-risk animals (optional). Include only one row of data per herd sampled.

Outputs include:

  • The sensitivity of the surveillance system, or in other words, the probability that the surveillance system would detect at least one infected animal if disease was present at the specified design prevalence;
  • The probability of freedom, or confidence that the disease is NOT present at the design prevalence (equivalent to the negative predictive value of the surveillance system);
  • The sensitivity of the system and confidence of freedom for assumed representative sampling;
  • The sensitivity ratio - this indicates how much more sensitivity the risk-based approach achieves, relative to a representative approach;
  • Effective probabilities of infection (EPI) for high-risk and low-risk herds (and for high-risk and low-risk animals in each herd). EPI values approaching 100% suggest that, based on the values used for relative risk, population proportions and design prevalence, close to 100% of herds (or animals) in the high-risk group are expected to be infected. If this is unreasonable you may need to review the input values. Values over 100% mean that the model is invalid and processing will be stopped, with an error message. Input values must be changed to ensure EPI values are appropriate;
  • Numbers of high-risk and low-risk herds tested and the total;
  • A summary of herd-sensitivities achieved in tested herds for risk-based and representative sampling; and
  • Risk-based and representative herd-sensitivities and sensitivity ratio achieved in individual herds.