Human specimens Sample sources

Su rv ei lla nc e o f ant im ic ro bi al r es ist an ce 1

1.5.2 Sample information

It is important to record basic information on each sample. This will allow more comprehensive analysis of laboratory data, help clarify potential biases for different sample types, and help identify critical control points for mitigating antimicrobial resistance emergence and spread. For isolates from humans, the following basic information should be included with each specimen: age or date of birth, sex, date of specimen collection, specimen type, geographical location town or city, state or province, etc., hospitalization status, and, if hospitalized, date of admission to the hospital. Other useful information that could be obtained from sentinel sites or during special studies may include recent travel history, previous and current antimicrobial use, immune status, whether the sample was collected as part of an outbreak investigation and, if so, any data from the investigation, including the known or suspected food source. For isolates from retail foods, the following information should be included with each specimen: date, type of store and location, type of food raw, or processed, or ready-to-eat, animal species, processing plant identification, origin imported or domestic, whether fresh or frozen, organic, conventional or other production system, and if the food was prepackaged or subject to in-store processing. Most information can be captured simply by filing a copy of the package label. For food animal samples collected during production, each sample should include the following information: animal species, date and place of collection, state or country of origin imported or domestic, age and clinical status of the animal, and possibly the history of antimicrobial use in animals and on the farm. Additional information on food animal samples should include whether the sample was from ill or healthy animals, and from an individual animal or a pooled sample from several animals. For samples collected at slaughter, information may include the state or country of origin of the animal domestic or imported, slaughter class e.g. dairy or beef cattle, the processing plant, age of animal, source of the specimen rectal swab, caecal sample, etc. and, if possible, the address or postal code of the farm of origin.

1.5.3 Sampling strategy

The relative strengths and limitations of sampling methods should be considered when establishing a programme of integrated surveillance of antimicrobial resistance in foodborne bacteria and when interpreting and comparing results. Sampling may be active prospective or passive samples collected for other purposes, random or systematic, statistically-based or convenience-based. Sentinel surveillance, which relies on specific providers, healthcare facilities, laboratories, or other sources reporting a disease or condition under surveillance, may also be employed. If sentinel laboratories are used for provision of data or isolates for the integrated antimicrobial resistance surveillance system, data from sentinel laboratories may include antimicrobial susceptibility results. Sentinel surveillance requires fewer resources and is often more complete and timely than population-based surveillance, but it may not be representative of the entire population. In order to permit analysis of antimicrobial resistance trends, sampling should be done on a continuous or regular basis using consistent methods. For surveys and periodic surveillance studies, the frequency of testing should be decided on the basis of the incidence and seasonality of the bacteria or diseases under surveillance. In some established programmes of integrated surveillance of antimicrobial resistance in foodborne bacteria, samples are collected monthly. If resources are not adequate for such frequent testing, isolates should be collected periodically throughout the year from different sites, in sufficient numbers, to identify trends. Several statistical methods can be used to calculate the number of isolates needed for testing sample size. Sample size will depend on the desired precision for estimates of the prevalence of resistance and the magnitude of change in resistance to be detected over a specified period of time in a certain population denominator. Sample size also depends on the initial or expected prevalence of resistance and the size of the population to be monitored. Furthermore, sample size also depends on the desired level of statistical 1 1