As a convenient dichotomy, infectious pathogens have been classified into two groups according to their inherent characteristics. Anderson and May (1979) classified those microscopic pathogens that replicate to high numbers in the host, have a short replication cycle relative to the life span of the host, and generate a significant protective immune response as microparasites.
This group includes viruses, bacteria, chlamydia and rickettsia, and protoctistans (protozoans). These pathogens also require only a single host during their life cycle, although the hosts affected may belong to more than one species.
The second group of pathogens is the macroparasites, which are larger in size (often visible with the unaided eye), do not multiply to large numbers while in the hostbut rather infect the host at a variable level during contact–transmission, and then mature rather than replicate within the host.
These pathogens also generally fail to induce a protective immune response, so reinfection is commonplace. In addition, macroparasites often have complex life cycles involving multiple hosts and significant morphological metamorphoses.
This group includes the monogeneans and digeneans, nematodes, cestodes, copepods, et cetera. In terms of developing models of disease, the pathogens affecting single hosts tend to be simpler to model; models derived for pathogens with multiple hosts, such as Myxobolus cerebralis, are inherently more complex (Roberts 1986).
Major Factors Involved in the Process of Disease:
One of the basic tenets of epidemiologic modeling of disease is that the factors which determine the progress of disease interact in a multiplicative rather than an additive manner. Some essential relationships between pathogen and population are based on the law of mass action originally promulgated for chemical reactions of molecules (Anderson and May 1979).
Therefore, the mathematical constructs deal, in large measure, with the density of individuals per unit area (or volume for fish). Consequently, the models are based on density parameters, although other approaches dealing with life spans and duration of infectiousness have been established (Mollison 1995b).
When whole populations are examined to determine if and how a disease develops, the ‘‘natural’’ population flux dictates the framework of the model to be developed. If one examines a single episode of disease, the assumption is made that there will be no influx of animals due to birth or immigration and no efflux of animals due to emigration.
When acute or subacute diseases are considered this assumption is appropriate because during the short time of epizootic disease, the core population changes little, except for disease-related mortality. On the other hand, when dealing with chronic or recurring diseases that span year-classes and extend to
time periods that include a new susceptible generation of animals, this assumption is not valid. This is also the case when one considers long-term population trends with the objective of estimating the impact of disease over many years.
Incremental reduction of spawning productivity can be magnified over generations and can lead to an accumulated impact more serious than disease on a single generation. For the short-term, single epizootic situation, the following equation holds: Nt 5 St 1 It 1 Rt ; (1) N 5 the population, S 5 the number of uninfected animals susceptible to the disease, I 5 the number of infected individuals, and R 5 the number of ‘‘removed’’ individuals—those that are immune and no longer susceptible or have died.
At any given time t, during the course of an invasion by a pathogen, this dynamic relationship will hold true. This type of model is termed a deterministic S–I–R model (Anderson and May 1979). Under special circumstances where the host never becomes immune and no disease-specific mortalities occur, the equation reduces to a simplified S–I model.
A general graphic representation of the components of the S–I–R model is indicated in Figure 1.
Factors that can affect the subsets of individuals in the population are elements of the environment, characteristics of the host, or characteristics of the pathogen (Snieszko 1978). Characteristics of the pathogen include the ability to infect a particular species of animal, invasiveness (pathogenicity), and virulence factors.
Descriptions of these characteristics are detailed in several textbooks on fish diseases (e.g., Roberts 1986; Austin and Austin 1987; Wolf 1988). Similarly, characteristics of the host have an effect on disease production in that a particular species, or even stock, may be more or less susceptible to being infected by a particular pathogen.
Also, individuals of a particular stock, once infected, may not show clinical signs of disease. The literature is replete with examples of fish stock variability in resistance to diseases caused by pathogens such as infectious pancreatic necrosis virus (IPNV) in trout (Silim et al. 1982); infectious hematopoietic necrosis virus (IHNV) in salmon (Amend and Pietsch 1977); channel catfish virus in catfish (Plumb et al. 1975); or Aeromonas salmonicida, Vibrio salmonicida, and Renibacterium salmoninarum in Atlantic salmon Salmo salar (Gjedrem and Gjoeen 1995).
In addition, certain diseases are only manifest during certain life stages of the host. In the case of viral diseases, for example, IPNV, IHNV, and viral hemorrhagic septicemia have historically been associated with disease only during the early life stages of salmonids (Wolf 1988).
Author:
PAUL W. RENO
