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This phase of epidemiology deals with observing, describing and recording the occurrence and evolution of disordered states of health in a population and seeks to discover their causes and prevent them. It is carried out by answering:
"Who" refers to the specific characteristics such as breed, age, sex, etc. of the animals that are (or are not) cases. These characteristics are also termed host factors.
The rationale for approaching the study of diseases in populations in the manner described in the preceding paragraphs may be found in two premises of modern epidemiology.
These are:
4.5.1.1 A Rate:
A rate is used in epidemiology to measure the frequency of events (cases) as they occur over time. Rates express the probability of occurrence of some event.
A rate is of the form:
where:
r = the number of cases that occur during a specified interval of time;
4.5.1.2 A proportion:
A proportion is of the same form as a rate; (c being equal to 100 or % since proportions are usually expressed as percent - %).
4.5.1.3 An Index:
An index is an estimate of a rate and is used when it is impossible to count directly the population at risk (n). The denominator is then obtained by counting some parameter which approximates the population at risk.
4.5.1.4 A ratio (K):
A ratio (k) expresses the relationship between a numerator and a denominator that does not include the numerator. For example:
where:
The two categories of rates most commonly used are:
- (1) those measuring disease events (morbidity rates), and
- (2) those measuring deaths (mortality rates).
4.5.1.6 Morbidity rates
These are measures of risk, i.e. measures of probability -- the probability of an individual in the population to be a case at a given point in time (prevalence rate) or to become a case within a stated time period (incidence rate).
The formula for prevalence rate (PR) is:
where:
The prevalence rate (PR) is an inventory type measure.
4.5.1.7 The incidence rate (IR)
The incidence rate (IR) is a more dynamic measure of risk counting only the new cases occurring during the specified time interval (usually one year) in the numerator. The denominator (population at risk: r) is an average of that population over the same time interval.
This average can be computed as:
Where:
Therefore:
where:
4.5.1.8 The Attack rate (AR)
The attack rate (AR) is a special incidence rate used in investigations of disease outbreaks. Although only new cases are counted in the numerator (as for the incidence rate) the denominator is always rt0, i.e. the population at risk (and directly exposed at the beginning of the outbreak, rather than an average population. The reason is that outbreaks are usually of relatively short duration and except for attrition due to the outbreak itself the population does not change appreciably.
4.5.1.9 Mortality rates
4.5.1.9.1 Crude mortality rate
Or crude death rate is one in which the total number of deaths are counted (numerator), regardless of cause of death or age at death, and divided by the average population (obviously all are at risk).
4.5.1.9.2 Case fatality rate
Counts deaths due to a given disease: the denominator includes the total number of animals affected, i.e. the cases. The case fatality rate is a measure of the virulence or severity of the disease and answers the question:
How many of those that get the disease will eventually die because of it?
Deaths from a specified cause or disease are also counted in the numerator of the proportional mortality rate; however, the denominator includes all animals that died, regardless of cause. It answers the question:
What proportion of deaths can be attributed to a given cause or disease?
4.5.1.9.3 Factor-specific morbidity and mortality rates
The more specific a rate used to measure a disease in two populations, the more reliable is the comparison between the two.
4.5.1.9.4 Factor-specific rate
Factor-specific rate is a rate that takes into account a specified factor such as a host factor, e.g. age.
The age specific prevalence rate for 2 to 4 year old animals is computed by dividing all cases in 2 to 4 year old by the total number of 2 to 4 year old animals in the population at risk.
A factor-specific rate therefore adjusts for differences in the distribution of that factor in the population. Some examples of factor-specific mortality rates are age-specific mortality rate and cause-specific mortality rate. The most common application of the age-specific mortality rate is in its use for measuring deaths in very young animals, i.e. calf-, piglet-, or lamb-mortality rate.
4.5.1.9.5 Miscellaneous measures of disease:
Measures of production, reproduction, and recovery can also be expressed as rates and ratios. These are sensitive indicators of the health status of the animals in a herd or a flock.
To understand the effect of time as a factor in determining the epidemiologic study of infections.
Time is one of the important variables used in the description of patterns of occurrence of diseases (infections) in populations. Time in itself may not affect the presence or absence of an infection per se; however, through time, the influence of other determinants such as climate (season), light, age, demographic changes, nutrition, etc. are superimposed and the effects that one sees over time may be indicative of the pattern of long or short term occurrence of some disease entity (whatever the underlying causes may be).
4.6.2.1 Clustering of disease events in time:
The timing of onset of cases rather follows one of three patterns.
- a. Cases may occur sporadically, i.e. they do not seem to be associated with any other identifiable factor, nor with each other.
- b. Cases ray occur regularly. If this is the case, one would attempt to explain the pattern in light of other events happening in a similarly regular fashion.
- c. Cases may occur in clusters, a pattern typical of outbreaks or epidemics.
4.6.2.2 The epidemic curve:
The epidemic curve represents in a graphic form the onset of cases of the disease, either as a histogram, a bar graph, or a frequency polygon. The frequency of new cases (or outbreaks) is plotted on the ordinate (y-axis) over a time scale on the abscissa (x-axis). A typical epidemic curve may have four segments:
- 1) the endemic level,
- 2) an ascending part,
- 3) a plateau,
- 4) a descending part, and, at times a secondary peak.
The first limb of the curve which represents the endemic level, i.e. the expected level of disease, should be drawn first. The actual epidemic curve is then superimposed. An epidemic is said to prevail when the frequency of cases (or outbreaks) in a population clearly exceeds the normally expected level for a given area and season,
- Propagating epidemic
- Pandemic - an epidemic takes international proportions.
- A secondary peak in an epidemic is usually due to:
- a. introduction of susceptible animals into the previously epidemic area, or
- b. movement of infected animals from the epidemic area and contact with susceptible animals.
The main peak of the curve is at times preceded by a smaller peak which could represent the index cases, i.e. the first cases to occur. The interval between this first peak and the beginning of the next or main peak could indicate the incubation period.
4.6.2.3 Other Time Patterns:
- a. Diurnal and other short term patterns - e.g. photoperiodism
- b. Seasonal variations
- c. Cyclical fluctuations
- d. Secular trends
- e. Random or erratic variations which occur in totally unpredictable fashion.
To understand the effect of space as a factor in determining the epidemiologic study of infections.
Spatial distribution patterns of infections or other diseases are just as important as are temporal patterns in describing the epidemiology of a disease (health) in a population. Geographic limits of distribution as well as spatial clusterings within defined localities could be indicative of a true nonrandom pattern of a disease frequency per unit of a population at risk. The basic question to ask here is how disease events relate to and affect spatial distributions.
4.7.2.1 Population density
The number of animals per unit area could influence the probability of animal contacts. If the density is high, the chances for contacts amongst animals is high and the vice versa is true for lower densities. If an infectious disease is introduced, its spatial patterns and rate of spread could be influenced by the density of the animal population and the contact rare amongst animals. This concept of a contact rate of a probability of contact especially between a healthy (at risk) and an infectious agent is vital in determining the dynamics of epidemics and endemic situations in herds.
- Open and closed animal populations -
- Movement and spread of diseases in an area -
- Natural geographic barriers such as rivers, valleys, plains etc.
4.7.2.2 Mapping disease events:
Two main techniques:
- a. Cartographic or mapping
- b. Cluster analysis
4.7.2.3 Cartographic methods:
- Spot maps and frequency maps
- Isodemic maps
- Contour (or isopleth) maps and computer generated maps
4.7.2.4 Cluster Analysis:
The aggregation (clustering) of disease in time, space or in both time and space is vital epidemiologic information that could be used in identifying and quantifying common environmental determinants or sources of infections so that the prevention or control of such diseases could be expedited.
Clustering of cases may occur in time and in location. The concept of time-place-clustering can be incorporated in the definitions of the terms pandemic, epidemic, endemic and sporadic as shown in the following table.
Pattern Type
Temporal Clustering
Spatial Clustering
Epidemic
Yes
Yes
Endemic
No
Yes
Sporadic
No
No
Pandemic
Yes
No
Host experience and exposure potential: the probability that an individual will be exposed to a given disease agent. Any host factor can influence exposure potential. Age is important in determining exposure potential, especially in humans. For example, an infant almost invariably is sheltered from all members of society except the immediate family. The immunity at this age is quite low. As the individual enters adult life, he/she has matured sexually and begins to earn a living. Both are factors which bring him into contact with new, potentially disease-producing situations. As old age approaches, the individual becomes less mobile, thus decreasing the exposure potential. The naturally acquired immunity at this age often is high. These age specific exposure potentials have a very definite bearing on the age pattern of various diseases.
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