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Environmental Sampling and Analytical Methods (ESAM) Program







The degree of agreement between an observed value and an accepted reference value. Accuracy includes random error (precision) and systematic error (bias or recovery) that are caused by sampling and analysis. A data quality indicator.

(U.S. EPA 1992) (U.S. EPA 2004) 

Airborne Transmission

Situations where droplet nuclei (residue from evaporated droplets) or dust particles containing microorganisms can remain suspended in air for long periods of time. These organisms must be capable of surviving for long periods of time outside the body and must be resistant to drying. Airborne transmission allows organisms to enter the upper and lower respiratory tracts.

(CDC 2012)


The systematic or persistent distortion of a measurement process which deprives the result of representativeness (i.e., the expected sample measurement is different than the sample's true value.) A data quality indicator.

 (U.S. EPA 2016)

Binary Data

Data that can only have two possible values.

(U.S. EPA 2002b)


The comparison of a measurement standard or instrument with another standard or instrument to report or eliminate, by adjustment, any variation (deviation) in accuracy of the item being compared. The levels of calibration standards should bracket the range of levels for which actual measurements are to be made.

(U.S. EPA 1992)

Censoring (data)

Data that includes both detected and non-detected results. Expressing a positive analytical measurement falling below the LOQ as less than the established quantification limit or expressing a non-detect result as less than the detection limit. 

(U.S. EPA 2006b) (U.S. EPA 2014b)

Chain of Custody

Provides a chronological record of who has possessed the sample(s) from the moment of collection through receipt in the laboratory, to the eventual destruction or disposal.  Also documents all analyses that were performed on the samples.

(U.S. EPA 2018d)


Assessment of the extent, location, and magnitude of contamination.  Characterization systematically expands on the initial assessment findings to identify other contaminated locations and determine the contamination footprint at the affected locations, in order to better define the boundaries. The sampling information, specifics of the incident, and the data collected during the initial assessment might take on many forms and might come from several different groups involved in the initial response and assessment activities. The data will be evaluated and reviewed, and used to assist in formulating the objectives, strategy, and approach for the characterization phase. The information that results from the characterization affects and shapes the planning and implementation of the remediation phase.

(Carlsen et al. 2012); (U.S. EPA 2017); (U.S. EPA 2018d)

Combined Targeted and Probabilistic Sampling

Uses Bayesian statistical methodology to combine results from targeted and probabilistic samples to make statistical confidence statements. This sampling approach ensures that samples are collected from locations perceived as most likely to be contaminated (through targeted samples) while protecting against the possibility that contamination may exist in less likely areas (through probabilistic samples).

(Sego et al. 2007; Sego et al. 2010; U.S. EPA 2018d)


The degree to which different methods or data agree or can be represented as similar. Comparability describes the confidence that two data sets can contribute to a common analysis and interpolation. Comparability for sampling primarily involves sampling designs and time periods, while analytical comparability focuses on whether different laboratories were used, the units of measure, and sample preparation procedures. A data quality indicator.

(U.S. EPA 1992; U.S. EPA 2014a; U.S. EPA 2016)


A measure of the amount of valid data obtained from a measurement system compared with the amount that was expected to be obtained under correct, normal conditions. A data quality indicator.

(U.S. EPA 2014a; U.S. EPA 2016)

Composite Sampling

Sampling method used where several samples are physically mixed into a larger composite sample. The entire composite sample may be measured for desired information, or one or more random sub-samples may be measured individually. In general, individual samples which are composited must be the same size or volume and the composite sample must be completely mixed. Composite sampling can be useful for estimating mean concentration of a substance, and if appropriate, compositing can result in substantial savings where the cost of analyzing individual samples is high.

(U.S. EPA 2002b)

Confidence interval

Statistically, a measure of the probability of taking action when action is required or that an observed value is correct. A confidence limit is a value above or below a measured parameter that is likely to be observed at a specified level of confidence.

(U.S. EPA 2002b)

Culture (method)

Preferred and definitive method (gold standard) to assess the viability of a target organism, in addition to determining its presence. Common culture-based protocols include: (1) bacterial assays that use either selective growth (preferential growth of a bacteria) or non-selective growth (general or non-specific growth) media and colony formation or turbidity as an indicator of bacterial growth and (2) viral assays that use cultured mammalian host cells (e.g., total culturable virus assay [TCVA]) and either cytopathic effects or plaque formation as an indicator of virus growth or replication. Less common, but important for viability assessment, are culture-based protocols for protozoa and helminths.

(U.S. EPA 2018d)


Facts or figures from which conclusions can be inferred.

(U.S. EPA 2016)

Data of Known Quality

Data are of known quality when the qualitative and quantitative components associated with their derivation are documented appropriately for their intended use and such documentation is verifiable and defensible.

(U.S. EPA 2006c)

Data Quality Assessment

The evaluation of environmental data to determine if they meet the quality criteria required for a specific application.

(U.S. EPA 2016)

Data Quality Indicators

A performance measure for sampling and analytical procedures; a quantitative measure of the achievement of data quality objectives; qualitative statistics and quantitative descriptors that are used to interpret the degree of acceptability or utility of data to the user. The principal data quality indicators are precision, accuracy, comparability, completeness, and representativeness.

(U.S. EPA 2002a; U.S. EPA 2016)

Data Quality Objectives

Qualitative and quantitative statements of the overall level of uncertainty that a decision maker is willing to accept in results or decisions derived from environmental data. DQOs provide the statistical framework for planning and managing environmental data operations consistent with the data user's needs.                

(U.S. EPA 2002a; U.S. EPA 2006c; U.S. EPA 2016)

Data Review

The evaluation process that determines the quality of reported analytical results. It involves examination of raw data (e.g., instrument output), quality control and method parameters, and statistical analyses by a professional with knowledge of the tests performed.

(U.S. EPA 2006a)

Data Transformation

Any mathematical function that is applied to every point in a data set. By transforming the data, assumptions that are not satisfied in the original data can be satisfied by the transformed data.

(U.S. EPA 2006b)

Data Usability

The process of determining and ensuring that the quality of the data produced meets the intended use of the data and the criteria set forth in the QAPP.

(U.S. EPA 2018b)

Data Validation

The process of determining that the data satisfy the requirements as defined by the data user.

(U.S. EPA 2016)

Decontamination Verification

This phase involves monitoring decontamination processes to confirm decontamination has been conducted according to the specified parameters. Examples include use of biological indicators used during fumigation, monitoring decontaminant concentrations, and documentation of process parameters.

(Carlsen et al. 2012); U.S. (U.S. EPA 2018d)


The ability to withstand any reasonable challenge related to the veracity of integrity of laboratory documents and derived data.

(U.S. EPA 2016)

Detection Limit

A measure of the capability of an analytical method of distinguished samples that do not contain a specific analyte from a sample that contains a low concentration of the analyte; the level of target analyte that can be determined to be different from zero by a single measurement at a stated level of probability DLs are analyte- and matrix-specific and may be laboratory dependent.

(U.S. EPA 2002b)

Discrete Data

Data where there is a real scale but not all values are possible (e.g. ‘number of eggs in a nest’ or ‘number of species in a sample’).

(Dytham 2011)


(1) The concentration of an environmental contaminant at a point over time, over an area, or within a volume; (2) a probability function (density function, mass function, distribution function) used to describe a set of observations or a population from which the observations are generated.

(U.S. EPA 2002b)


Description of the data collection activities sufficient to be able to evaluate the completeness, comparability, representativeness, precision, and accuracy of the analytical data sets; types of documentation can include sampling and analysis plan, standard operating procedures, field and analytical records, and chain-of-custody records.

(U.S. EPA 2006a)

Direct Contact Transmission

Direct contact transmission requires physical contact between an infected person and a susceptible person, and the physical transfer of microorganisms. This type of transmission requires close contact with an infected individual, and will usually occur between members of the same household or close friends and family.

(CDC 2012)

Droplet Transmission

Transfer of diseases by infected droplets contacting surfaces of the eye, nose, or mouth. Droplets containing microorganisms can be generated when an infected person coughs, sneezes, or talks. Droplets can also be generated during certain medical procedures, such as bronchoscopy. Droplets are too large to be airborne for long periods of time, and quickly settle out of air.

(CDC 2012)

Environmental Data

Any measurements or information that describe environmental processes, location, or conditions; ecological or health effects consequences; or the performance of environmental technologies. For EPA, environmental data include information collected directly from measurements, produced from models, and complied from others sources such as data bases or the literature.

(U.S. EPA 2002b)

Environmental Sample

A sample of any material that is collected from an environmental source.

(U.S. EPA 2016)

Equipment Blank

This control is performed by passing sterile reagent grade water or buffer through the equipment and processing the water as if it were a PCR negative control. If this control is found to be positive, all analysis should cease until the source of the problem is identified. Equipment blanks should then be run more frequently until it is shown that the problem has been corrected.

(U.S. EPA 2004)

False Negative

Estimation that an analyte is not present when it actually is present. Also called a Type II (beta) error or false acceptance decision error.

(U.S. EPA 2002b; U.S. EPA 2016)

False Positive

Estimation that an analyte is present when it is actually not present. Also called a Type I (alpha) error or false rejection decision error. 

(U.S. EPA 2002b; U.S. EPA 2016)

Fecal-oral Transmission

Associated with organisms that infect the digestive system. Microorganisms enter the body through ingestion of contaminated food and water. Inside the digestive system (usually within the intestines) these microorganisms multiply and are shed from the body in feces.

(CDC 2016)

Field Blank

A sample used to identify and estimate contamination immediately before and after sampling (evaluation of protocols), during sample shipment, and for samples awaiting measurement in the laboratory.

(U.S. EPA and USGS 2014)

Geometic Mean

The antilog of the mean of the logged data; it is always smaller than the arithmetic mean.

(Dytham 2011; U.S. EPA 1992)


Represents the pathogens potential to generally cause adverse effects normally healthy humans.

(U.S. EPA 2007)


Procedure that utilizes specific antibodies to detect specific antigens. Two common types of immunoassays are the enzyme-linked immunosorbent assay (ELISA) and immunomagnetic separation (IMS).

(U.S. EPA 2018d)

Indirect Contact Transmission

Situations where a susceptible person is infected from contact with a contaminated surface or fomite (vehicle-borne transmission) or through vector borne transmission.

(CDC 2012)


The ability of a pathogen to enter, survive, and multiply in a host.

(U.S. EPA 2007)

Inhibition Positive Control

A sample used to verify that interfering constituents from an environmental matrix carried over from the isolation of the organism or nucleic acids do not inhibit the PCR.

(U.S. EPA 2004)

Intended Use of Data Collection: Decision-making

Making a choice between alternative conditions and usually occurs during regulatory activities, emergency responses, and other contexts where action is taken.

(U.S. EPA 2006c)

Intended Use of Data Collection: Estimation

The evaluation of the magnitude of an environmental parameter or characteristic. Estimation usually supports longer term Agency activities, such as scientific background for rulemaking. For example, estimation of the density of fecal indicator organisms in water, or the microbial sources that contribute to pathogen and indicator fluctuations in watersheds. The resulting estimate might be used in further research, input to a model, or perhaps eventually to support decision making.

(U.S. EPA 2006c)

Internal Positive Control

The internal positive controls of known concentrations consists of a simple DNA template material for the assay target added to its own dedicated PCR reaction run in parallel with the samples on a test. A positive test result in this reaction validates the function not only of the shared master mix components tested by an internal control, but also uniquely shows the function of target-specific primers and probes. These controls might form the basis for a standard curve for quantitative assays by allowing the quantitation standard to take into direct account possible variations in extraction efficiency across a range of target concentrations

(U.S. EPA 2004)


The ability to degrade and migrate through the extracellular matrix.

(U.S. EPA 2007)

Limit of Detection (LOD)

Minimum amount of analyte that can be detected reliably and distinguished from a known and characterized background with a given level of confidence; LODs establish a baseline detection value for optimal conditions.

(U.S. EPA 2012b)

Limit of Quantification (LOQ)

Lowest amount of analyte that can be measured with acceptable precision and accuracy as required by data quality objectives.

(U.S. EPA 2012b)

Lognormal Distribution

An important probability distribution when analyzing

environmental data where normality cannot be assumed. Bounded on the left by 0, has a fatter right-tail than the normal distribution, and has a right-skewed shape.

(U.S. EPA 2006b)


The type of media in which the analyte of interest is contained (e.g., waste water, storm water)

(U.S. EPA 2004)

Matrix Spike

A sample used for quality control in which a known amount of the target analyte is added to a specified amount of matrix. These samples can be used to evaluate the effect of the matrix on the recovery efficiency and performance of a method.

(U.S. EPA 2004)

Measurement Quality Objective

The acceptance threshold or goal that the data quality indicator must achieve

(U.S. EPA 2018d)

Media (growth)

Liquid or gel designed to support the growth of microorganisms or cells; different types of media support the growth of different microorganisms or cells.

(U.S. EPA 2018d)

Method Blank

A sample used to simulate the sample matrix conditions and analyzed using the exact same calibration standards, samples, and quality control samples. Intended to discover any bias in the analysis and detect within-batch variability of the blank response.

(U.S. EPA 2004)

Method Positive Control

Verify that the entire method is performing properly and

is capable of amplifying the target nucleic acid from the

organism of interest

(U.S. EPA 2004)

Most Probable Number (MPN)

A statistically derived estimate of the presence of microorganisms based on the presence or absence of growth in serially diluted samples.

(U.S. EPA 2012a)

Media Blank

Unexposed samples not taken to the field or shipped. Media blank results are used for background correction of sample readings and for recovery studies.

(U.S. EPA 2018d)

Negative Control

A control with a known negative outcome.

(U.S. EPA 2012b)


Data generated from analysis that fall below the detection limit of the analytical procedure.

(U.S. EPA 2006b)

Normal Distribution

A symmetrical, continuous distribution and is described by two parameters: the mean, μ (mu, describing the position), and the standard deviation, σ (sigma, describing the spread). These two parameters are estimated from samples and assigned the letters m and s. The most important distribution in statistics and it is often assumed that data are distributed in this way.

(Dytham 2011)

Null hypothesis

The “baseline” condition and will be rejected in favor of the alternative hypothesis only when there is overwhelming evidence the null cannot be true.

(U.S. EPA 2002b)

Opportunistic Microorganism

Refers to potential to cause adverse human outcomes under certain environmental and health conditions, most often when the host is compromised.

(U.S. EPA 2007)


Data points well outside the range of others).

(Dytham 2011)


Microorganisms (e.g., bacteria, viruses, or parasites) that can cause disease in humans, animals and plants.

(U.S. EPA 2007)


The ability to cause a disease state, it is the cumulative effect of virulence and invasiveness.

(U.S. EPA 2007)

PCR Positive Control

Verify that the PCR master mix and reagents were

prepared correctly to produce amplification of the

target nucleic acid

(U.S. EPA 2004)

PCR Negative Control

Verify that no contaminating nucleic acid has been introduced into the master mix

(U.S. EPA 2004)


The ability of the microorganism to survive in the environment of host.

(U.S. EPA 2007)

Performance or Acceptance Criteria

Statements of the type and content of deliverables and results that are necessary to assess the usability of data for risk assessment. Specific limits placed on the characteristic of an item, process, or service.

(U.S. EPA 2002b; U.S. EPA 2006c)

Plaque assay

Standard method used to determine virus concentration in terms of infectious dose. Viral plaque assays determine the number of plaque forming units (PFU) in a virus sample, which is one measure of virus quantity. One variation is the focus forming assay.

(U.S. EPA 2018d)

Poisson Distribution

A distribution describing the number of times an event occurs in a unit of time or space. Usually a sample of time or space is taken and the number of events recorded.

(Dytham 2011)

Polymerase Chain Reaction (PCR)

Laboratory technique used to make multiple copies of a segment of DNA. PCR is very precise and can be used to amplify, or copy, a specific DNA target from a mixture of DNA molecules.

(U.S. EPA 2004; U.S. EPA 2018d)

Post-Decontamination Sampling

Assessment of the body of data generated to verify that the originally contaminated environment has been sufficiently decontaminated to meet cleanup endpoints. As part of this sampling, a body of data of adequate quantity and quality is developed to enable Incident Command (IC)/Unified Command (UC) to verify that the originally contaminated environment has been sufficiently decontaminated to allow re-occupancy of the area without the use of personal protective equipment (PPE) or other protective measures.

(OSHA 2002; U.S. EPA 2017)


A measure of how closely values from replicate measurements of a sample agree with each other. Usually expressed as standard deviation, variance, or range in either absolute or relative terms. A data quality indicator.

(U.S. EPA 2004; U.S. EPA 2016)

Probabilistic Sampling – Simple Random Sampling

Most fundamental type of probabilistic sampling. Sampling locations are selected completely at random from a population of possible locations.

(Carlsen et al. 2012; U.S. EPA 2002b);  (U.S. EPA 2018d)

Probabilistic Sampling – Stratified Sampling

A sampling area is subdivided into separate strata (for example, within or outside the ventilation zone) and a sampling approach is implemented separately within each stratum.

(U.S. EPA 2002b; U.S. EPA 2018d)

Probabilistic Sampling – Systematic Sampling

Consists of collecting samples at locations or over time in a specified pattern. Systematic sampling ensures that the target population is fully and uniformly represented by the set of samples collected. To make systematic sampling a probabilistic sampling approach, the initial sampling location is chosen at random.

(Carlsen et al. 2012); (U.S. EPA 2018d)


A code appended to an analytical result that indicates possible qualitative or quantitative uncertainty in the result.

(U.S. EPA 1989)


A observation that is assigned to a category that, although it may be coded as a number, has no numerical value (e.g., positive/negative or presence/absence).

(Dytham 2011)

Quality Assurance (QA)

An integrated system of activities involving planning, quality control, quality assessment, reporting, and quality improvement to ensure that a product or service meets defined standards of quality with a stated level of confidence.

(U.S. EPA 2016)

Quality Assurance Project Plan (QAPP)

A document describing in comprehensive detail the necessary QA, QC, and other technical activities that must be implemented to ensure that the results of the work performed will satisfy the stated performance objectives and criteria.

(U.S. EPA 2014a; U.S. EPA 2016)

Quality Control (QC)

The overall system of technical activities that measures the attributes and performance of a process, item, or service against defined standards to verify that they meet the stated requirements established by the customer; operational techniques and activities that are used to fulfill requirements for quality.

(U.S. EPA 2001a; U.S. EPA 2001b; U.S. EPA 2016)


An observation that has a meaningful numerical value. It can be either a direct observation or a count.

(Dytham 2011)


The total amount of the analyte found in the sample, corrected for background, divided by the amount of the analyte added into the sample.

(U.S. EPA 2004)

Recovery Efficiency

The recovery of an analyte in an assay is the detector response obtained from an amount of the analyte added to and extracted from the biological matrix, compared to the detector response obtained for the true concentration of the pure authentic standard.

(U.S. EPA 2012b; U.S. EPA 2018d)


The degree of agreement between independent test results produced by the same analyst, using the same test method and equipment on random aliquots of the same sample within a short time period.

(U.S. EPA 2002a)


An additional sample that allows for averaging two or more samples to ensure the most accurate results and improves quality assurance.

(U.S. EPA 2012b)


The ability for microorganism to multiply within the environment or host.

(U.S. EPA 2007)


The degree to which data accurately and precisely represent a characteristic of a population, a parameter variation at a sampling point, a process condition, or an environmental condition. A data quality indicator.

(U.S. EPA 2002b; U.S. EPA 2016)

Sample Integrity

The maintenance of the sample in the same condition as when sampled.

(U.S. EPA 2018d)

Sample Preservation

Techniques that stabilize parameters of interest by retarding chemical or biological changes.

(U.S. EPA 2012b)

Sample Processing

The processing of biologically contaminated environmental samples prior to sample analysis in order to remove debris, chemical components, and biological impurities.

(Silvestri et al. 2014; Silvestri et al. 2016; U.S. EPA 2018d)

Sample Process Control, or Internal Control

Functions like the target in its ability to be collected, concentrated and detected. A sample process control, or internal control, may be required or needed when the target organism is low in prevalence and highly pathogenic (i.e., low infectious dose), or if the surrogate is an indicator for a specific pathogen or set of pathogens.

(U.S. EPA 2012b)

Sampled Population

Part of the target population (see definition of “target population” below) that is accessible and available for sampling. Ideally, the sampled population and the target population are the same. If they are not, then professional judgment is used to verify that data drawn from the sampled population is appropriate for drawing conclusions about the target population.

(U.S. EPA 2002b)

Sampling Unit

The member of the population that may be selected for sampling, such as individual trees, or a specific volume of air or water.

(U.S. EPA 2002b)


Yielding an approximation of the quantity or amount of a substance; falling short of a quantitative result.

(Sandle 2015)


(1) The capability of a method or instrument to discriminate between small differences in analyte concentration; (2) A qualitative description of an instrument’s or analytical method’s detection limit. The sensitivity of a test can be described as the proportion of all positive results detected that were truly positive. All positives are the sum of (detected) true positives (TP) and (undetected) false negatives (FN). Sensitivity is therefore: TP / (TP + FN) × 100%.

(U.S. EPA 2004; U.S. EPA 2012b)


The specificity of a test can be described as the proportion of all negatives it detects that truly were negative. All negatives are the sum of (detected) true negatives (TN) and false positives (FP). Specificity is therefore: TN / (TN + FP) × 100%

(U.S. EPA 2004; U.S. EPA 2012b)

Spiked Sample/Positive Control

Known amounts of analyte are added to a sample and the percent recovery is calculated. Used to test an analytical method at varying concentrations of analyte.

(U.S. EPA 2018d)

Standard Deviation

Measure of the dispersion or imprecision of a sample or population distribution as expressed as the square root of the variance and has the same unit of measurement as the mean. The standard deviation is calculated as the square root of the variance.

(U.S. EPA 2002b)

Standard Operating Procedures (SOPs)

A written document that details the method for an operation, analysis, or action with thoroughly prescribed techniques and step. Some SOPs are officially approved as the method for performing certain routine or repetitive tasks.

(U.S. EPA 2001b; U.S. EPA 2014a)

Substitution (data)

The process of replacing a variable in an expression with it’s a different value.

(U.S. EPA 2006b)

Target Population

The set of all units that comprise the items of interest in a scientific study, that is, the population about which the decision maker wants to be able to draw conclusions.

(U.S. EPA 2002b)

Targeted Sampling

Each member of the population from which the sample was selected has a known probability of selection. When a probabilistic sampling approach is used, statistical inferences may be made from the sampling data about the sampled population.

(Carlsen et al. 2012); (U.S. EPA 2018d)

Taxonomy and Strain

Definition of the hazards with respect to traditional biological classification taxonomy and strain variations have potentially a large impact on risk assessment. The difference in dose response range between isolates and strain can be orders of magnitude. Some strains may not be infective to humans, in addition the ratio of different strains the environment can fluctuate.

(U.S. EPA 2007)


The ability of the microorganism to survive, replicate, and passed through animate or inanimate matrixes and stay infected

(U.S. EPA 2007)


This is conducting a risk assessment in such a manner that all of the scientific analyses, uncertainties, assumptions and science policies which underlie the decisions made throughout the risk assessment are clearly stated (i.e., made readily apparent). For risk assessment to be transparent, methods, and assumptions should be clearly stated and understandable to the intended audience, so that the audience is able to evaluate the adequacy of the data and methods.

(USDA and EPA 2012)


Uncertainty is imperfect knowledge of the microbiological hazard (e.g., its virulence), environmental pathways/processes, or the human populations under consideration (from MRA). Uncertainty represents a lack of knowledge about factors affecting risk assessments and can lead to inaccurate or biased estimates or risk and hazard. Some of the types of uncertainty include scenario uncertainty, parameter uncertainty, and model uncertainty. Uncertainty can be reduced by further study. NRC Definition: Lack or incompleteness of information. Quantitative uncertainty analysis attempts to analyze and describe the degree to which a calculated value may differ from the true value; it sometimes uses probability distributions. Uncertainty depends on the quality, quantity, and relevance of data and on the reliability and relevance of models and assumptions.

(USDA and EPA 2012)

Uncertainty Analysis

This is used to estimate the uncertainty associated with model inputs, assumptions, and structure/form and the process of interpreting the influence of uncertainty on the results of a risk assessment.

(USDA and EPA 2012)

Validated Method

The process that demonstrates the suitability of an analytic method for its intended purpose

(U.S. EPA 2012b)


This refers to the observed differences attributable to true heterogeneity or diversity in a parameter. Examples include human physiological variation (e.g., natural variation in body weight, height, breathing rate, drinking water intake rate), weather variability, variation in soil types, and differences in contaminant concentrations in the environment. Variability is usually not reducible by further measurements of study, but it can be better characterized. NRC Definition: Variability refers to true differences in attributes due to heterogeneity or diversity. Variability is usually not reducible by further measurements of study, although it can be better characterized.

(USDA and EPA 2012)

Vector-borne Transmission

Vectors are animals that are capable of transmitting diseases. Examples of vectors are flies, mites, fleas, ticks, rats, and dogs.

(CDC 2012; CDC 2018)


The ability of the pathogen to defeat the host defenses, increase the severity and longevity of the symptoms.

(U.S. EPA 2007)

Waste Characterization

Assessment of the waste based on all available information [e.g., sampling results] to document that the waste meets regulatory requirements and any additional requirements of waste receivers prior to off-site disposal. 

(U.S. EPA 2018a)

Glossary References

  • Carlsen T et al. (2012) Remediation Guidance for Major Airports after a Bioterrist Attack. vol LLNL-TR-562207. Lawrence Livermore National Laboratory.
  • CDC (2012) Lesson 1: Introduction to Epidemiology. Section 10. Chain of Infection. In: Principles of Epidemiology in Public Health Practice, Third Edition An Introduction to Applied Epidemiology and Biostatistics. Centers for Disease Control and Prevention. Available at: Last accessed 11/06/18.
  • CDC (2016) About Parasites. Centers for Disease Control and Prevention. Available at: Last accessed 11/06/18.
  • CDC (2018) About the Division of Vector-Borne Diseases. Centers for Disease Control and Prevention, National Center for Emerging and Zoonotic Infectious Diseases (NCEZID). Available at: Last accessed 11/06/18.
  • Dytham C (2011) Choosing and Using Statistics: A Biologist's Guide. Third Edition. Wiley-Blackwell. Blackwell Science, Oxford.
  • OSHA (2002) Anthrax eTool. Occupational Safety and Health Administration. Washington, D.C. Available at:
  • Sandle T (2015) Approaching Microbiological Method Validation. Available at: Exit. Last accessed 2/23/17.
  • Sego LH et al. (2007) An environmental sampling model for combining judgement and randomly placed samples. Pacific Northwest National Laboratory for the U.S. Department of Energy. PNNL-16636.
  • Sego LH, Shulman S, Anderson KK, Wilson JE, Pulsipher BA, Sieber WE (2010) Acceptance sampling using judgemental and randomly selected samples. Pacific Northwest National Laboratories. Richland, WA. PNNL 19315.
  • Silvestri EE, Perkins SD, Feldhake D, Nichols T, F.W. Schaefer I (2014) Recent literature review of soil processing methods for recovery of Bacillus anthracis spores Ann Microbiol 65:1215-1226. DOI 1210:1007/s13213-13014-10932-x
  • Silvestri EE, Perkins SD, Rice EW, Stone H, Schaefer FW (2016) Review of processing and analytical methods for Francisella tularensis in soil and water Annals of Microbiology 66:77-89 doi:10.1007/s13213-015-1144-8
  • U.S. EPA (1989) Risk Assessment Guidance for Superfund Volume I Human Health Evaluation Manual (Part A) Interim Final. U.S. Environmental Protection Agency, Office of Emergency and Remedial Response, Washington, DC. EPA/540/1-89/002.
  • U.S. EPA (1992) Guidelines for exposure assessment. U.S. Environmental Protection Agency, Risk Assessment Forum, Washington, D.C. EPA/600/Z-92/001.
  • U.S. EPA (2001a) EPA Requirements for Quality Assurance Project Plans, EPA QA/R-5. U.S. Environmental Protection Agency: Washington, DC. EPA/240/B-01/003 U.S. EPA (2001b) EPA Requirements for Quality Management Plans, QA/R-2. U.S. Environmental Protection Agency. Washington, D.C. EPA/240/B-01/002.
  • U.S. EPA (2002a) Guidance for Developing Quality Systems for Environmental Programs. QA/G-1. U.S. Environmental Protection Agency, Office of Environmental Information. EPA/240/R-02/008
  • U.S. EPA (2002b) Guidance on choosing a sampling design for environmental data collection for use in developing a quality assurance project plan. EPA QA/G-5S. U.S. Environmental Protection Agency. Washington, D.C. EPA 240/R-02/005.
  • U.S. EPA (2004) Quality Assurance/Quality Control Guidance for Laboratories Performing PCR Analyses on Environmental Samples. U.S. Environmental Protection Agency, Cincinnati, OH. EPA 815-B-04-001
  • U.S. EPA (2006a) Data Quality Assessment: A Reviewer's Guide. EPA QA/G-9R. U.S. Environmental Protection Agency. Washington, DC. EPA/240/B-06/002.
  • U.S. EPA (2006b) Data Quality Assessment: Statistical Tools for Practitioners, EPA QA/G-9S. U.S. Environmental Protection Agency, Washington, DC. EPA/240/B-06/003
  • U.S. EPA (2006c) Guidance on Systematic Planning Using the Data Quality Objectives Process EPA QA/G-4. U.S. Environmental Protection Agency, Washington, DC. EPA 240-B-06-001
  • U.S. EPA (2007) Thesaurus of Terms Used in Microbial Risk Assessment. U.S. Environmental Protection Agency, Office of Water. Available at: Last accessed June 21, 2018
  • U.S. EPA (2012a) Most Probable Number (MPN) Calculator Version 2.0. U.S. Environmental Protection Agency. Available at:
  • U.S. EPA (2012b) Validation of U.S. EPA Environmental Sampling Techniques that Support the Detection and Recovery of Microorganisms. U.S. Environmental Protection Agency, Forum on Environmental Measurements (FEM) Method Validation Team. Minor Revision: November 28, 2017. FEM Document Number 2012-01
  • U.S. EPA (2014a) Compendium: Project Quality Assurance and Quality Control: Chapter 1. U.S. Environmental Protection Agency, Washington, DC. SW846 Update V. Available at:
  • U.S. EPA (2014b) Evaluation of Options for Interpreting Environmental Microbiology Field Data Results having Low Spore Counts. U.S. Enviromental Protection Agency, Cincinnati, OH. EPA 600/R-14/331.
  • U.S. EPA (2017) Selected Analytical Methods for Environmental Remediation and Recovery (SAM). U.S. Environmental Protection Agency: Washington, DC, 2017. EPA/600/R-17/356.
  • U.S. EPA (2018a) Best Practices to Minimize Laboratory Resources for Waste Characterization During a Wide-Area Release of Chemical Warfare Agents. U.S. Environmental Protection Agency, Cincinnati, OH
  • U.S. EPA (2018b) Draft Guidance on Data Usability Evaluation for Collected and Existing Data, EPA QA/G-8. U.S. Environmental Protection Agency. Contact Robert Tallent ( for access
  • U.S. EPA (2016) QA Glossary. U.S. Environmental Protection Agency, Environmental Monitoring & Assessment Program, Available at: Last accessed 6/10/20.
  • U.S. EPA (2018d) Sampling, Laboratory, and Data Considerations for Microbial Data Collected in the Field. U.S. Environmental Protection Agency, Cincinnati, OH. EPA/600/R-18/164
  • U.S. EPA, USGS (2014) USEPA/USGS Sample Collection Protocol for Bacterial Pathogens in Surface Soil. U.S. Environmental Protection Agency and U.S. Geological Survey. EPA/600/R-14/027.
  • USDA, EPA (2012) Microbial risk assessment guideline: Pathogenic organisms with focus on food and water. U.S. Department of Agriculture/Food Safety and Inspection Services and the U.S. Environmental Protection Agency. FSIS Publication no: USDA/FSIS/2012-001; EPA publication no. EPA/100/J12/001

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