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There are two high‐level indications for diagnostic testing on a population level, including (i) disease surveillance and (ii) diagnosis and management of a disease outbreak. Surveillance has been defined as “the use of data to monitor health problems to facilitate their prevention or control” (United States Department of Health and Human Services 2012). It involves the active collection of data, such as clinical signs and diagnostic test results, within an at‐risk population and is used to set priorities, plan and conduct disease control programs, and assess the effectiveness of control efforts (United States Department of Health and Human Services 2012). In the animal shelter, disease surveillance can help identify and document common conditions in incoming animals, detect disease trends within the shelter, and identify emerging diseases (Hurley and Pesavento 2013).

Though disease surveillance often occurs informally, such as monitoring for general trends during daily rounds, scheduled and formalized surveillance can provide more objective, actionable data. One example of this might be a periodic evaluation of fecal samples from dogs admitted within one week to assess concordance with prophylactic deworming protocols. The mathematical goal of surveillance testing is to detect at least one animal with the infection or disease of interest and not to determine prevalence in the shelter population; therefore, the ideal number of animals to test should be calculated based on the lowest assumed rate of infection and the desired confidence limits. Sampling enough animals to ensure at least 90% probability of detection is recommended (Table 4.6).

In addition to testing clinically healthy animals, it is useful to perform disease surveillance in cohorts of animals with specific clinical syndromes. For example, collecting oropharyngeal swabs from cats with clinical signs of upper respiratory disease may help guide empirical treatments and direct husbandry practices in order to minimize disease transmission once particular pathogens are identified. This type of surveillance may help inform preventive care practices and be helpful in understanding baseline disease characteristics should frequency or severity of clinical syndromes increase or animals fail to respond to treatment as expected.

Table 4.6 Surveillance testing sample sizes for ≥90% probability of detection (National Research Council 1991).

Assumed Infection Rate (%)	Number of Animals to Test
2	120
3	80
4	60
5	45
10	25
15–20	15
25–30	10
≥40	5

The frequency of surveillance is dependent upon the importance of the specific disease to the management of the population, historical trends, and resource availability; typical intervals include monthly, quarterly, biannual, or annual testing (National Research Council 1991). Results should be interpreted in terms of time (e.g. seasonal disease trends), location (e.g. building, ward, housing unit), and the individuals affected (e.g. species, age, sex, clinical signs) (United States Department of Health and Human Services 2012).

Diagnostic testing plays a key role in individual animal risk assessment during a disease outbreak response. Definitive identification of the cause of an infectious disease outbreak is a critical step in its mitigation and control (O'Quin 2013). In such circumstances, consideration should be given to testing of animals that are presumed to be infected; exposed and at risk of infection; exposed but not at risk of infection; and those not yet exposed (Hurley and Pesavento 2013). Testing every animal is generally not necessary and may not yield more actionable results. Though the precise number of patients to test will depend on the stage of infection, diagnostic test accuracy, and disease prevalence, a minimum of three to six samples for both GI and respiratory diseases have been recommended in human outbreak investigations (British Columbia Provincial Infection Control Network 2011; Plantenga et al. 2011). See Chapter 6 for more information on this topic.