VPH 81: Epidemiology 1st Hour Coverage PDF
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This document provides a comprehensive overview of epidemiology. It explains early perspectives on diseases, different types of disease occurrence like endemic, epidemic, and sporadic diseases, and the concept of disease causation.
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VPH 81: EPIDEMIOLOGY 1ST HOUR COVERAGE Early Perspectives on Epidemiology 2. Quantitative investigations Early man and Disease - Surveys 1. Demons - Monitorin...
VPH 81: EPIDEMIOLOGY 1ST HOUR COVERAGE Early Perspectives on Epidemiology 2. Quantitative investigations Early man and Disease - Surveys 1. Demons - Monitoring - Man attibute disease to supernatural beings - Surveillance - Treatment by placation, sacrifice, exorcism - Studies (experimental cross-sectional, case-control, - Disease caused by evil spirits cohort) 2. Divine wrath - Modeling - Disease a product of displeased supreme being - Evaluation of disease control 3. Metaphysical Medicine - Presence of occult forces beyond the physical universe - The moon, stars and planets were considered to affect health Pre-scientific theory on disease 4. Universe of natural law - Disease a result of the derangement of four humours of the body which is associated with four properties (air, earth, water and fire) - External forces causes disease (miasmata) 5. Contagion - Transmission of disease for one animal to another - Advances in identification of microbes Impetus for Change 1. The first period – emergence of priest-healers 2. The second period: 1st century AD 1762 - Specialized in equine medicine and surgery Patterns of Disease Occurrence - Based on metaphysical theory 1. Endemic 3. The 3rd period: 1762-1884 - Usual frequency of occurrence of a disease in a - the improvement of farm hygiene, slaughter population and treatment - Constant presence of a disease in a population 4. The 4th period: 1884-1960 o Holoendemic – most animals affected - Animal plaques continued o Hyperendemic – high proportion of animals - Treatment based on laboratory diagnosis affected - Mass testing for control and prevention o Mesoendemic – moderate proportion of animals affected Modern Epidemiology o Hypoendemic – relatively small proportion of 5. The 5th period animals affected - Focus on disease casualty (multifactorial theory of disease 2. Epidemic - New control strategies (surveillance and monitoring) - Occurrence of a disease to a level in excess of the - Emerging trends (veterinary services, animal welfare expected level and national and international disease reporting - Clustering of disease in both space and time o Pandemic – very large scale epidemic (many Epidemiology (Scopes and Basic Concepts) countries affected) The study of diseases in populations Objectives of Epidemiology: 3. Sporadic - Disease occurs rarely and without regularity - Determination of the origin of a disease whose cause (irregularly and haphazardly) is unknown - Creating small localized outbreaks - Investigation and control of a disease whose cause is either unknown or poorly understood Cause of Disease - Acquisition of information on the ecology and natural history of a disease Koch’s Postulates; organism is causal if: - Planning and monitoring of disease control program - It is present in all cases of the disease - Assessments of the economic effects of a disease - It does not occur in another disease as a fortuitous and analysis of the costs and economic benefits of and non-pathogenic parasite alternative control programs - Isolated in pure culture from an animal; induces the same disease in other animals Applications: Evan’s Postulates; consistent with modern concepts of - Descriptive epidemiology causation o Involves observing and recording diseases and - The proportion of individuals with the disease should possible causal factors be significantly higher in those exposed to the o May generate hypothesis supposed cause than in those who are not - Analytical epidemiology – Analysis of observations - Exposure to the supposed cause should be present using suitable diagnostic and statistical tests more commonly in those with then those without - Experimental epidemiology the disease; when all other risks factors are held - Theoretical epidemiology – use of mathematical constant models - The number of new causes of disease should be significantly higher in those exposed to the supposed Components of Epidemiology cause than in those not so exposed (prospective 1. Qualitative investigations studies) - Natural history of diseases - The proportion of individuals with the disease should - Causal hypothesis testing be significantly higher in those exposed to the supposed cause than in those who are not kting Page 1 VPH 81: EPIDEMIOLOGY 1ST HOUR COVERAGE - Exposure to the supposed cause should be present Causal Model 2 more commonly in those with then those without Direct and indirect causes represent a chain of actions, the disease; when all other risks factors are held with the indirect causes activating the direct causes. constant When many such relationships occur, a number of - The number of new causes of disease should be factors can act at the same level (but not necessarily at significantly higher in those exposed to the supposed the same intensity) and there may be several levels, cause than in those not so exposed (prospective producing a web of causation (multifactorial) studies) - Experimental reproduction of the disease should occur with greater frequency in animals appropriately exposed to the supposed cause. - Elimination or modification of the supposed cause should decrease the frequency of occurrence of the disease. - Prevention or modification of the hosts’ response should decrease or eliminate the disease. - All relationships and associations should be biologically and epidemiologically credible Variables Confounding Variable – any observable event that can vary, e.g., - Confounding is the effect of an extraneous variable weight and age of animal, number of cases of disease that can wholly or partly account for an apparent - Study variable – any variable that is being association between variables. considered in an investigation. - Confounding can produce a spurious association - Response variable – variable that is affected by between study variables, or can mask a real another variable. association. A confounding variable must: - Explanatory variable – variable that affects another o Be a risk factor for the disease that is being variable (response). studied; and o Be associated with the explanatory variable, but Associations not be a consequence of exposure to it. Types of Associations – association is the degree of dependence or independence between two variables. Causation Hypotheses Two main types of association: Formulating a Causal Hypothesis - Non-statistical association – association between a 1. Epidemiological investigation of cause must describe disease and a hypothesized causal factor that arises time, place and population. by chance - Time: association with year, season, month, day or - Statistical association even hour should be considered. This may provide o Positively statistically associated – occur information on climatic influences, incubation together more frequently than would be periods and sources of infection. expected by chance. - Place: geographic distribution of the disease may o Negatively statistically associated – occur indicate an association with local geological, together less frequently than would be expected management or ecological factors. by chance. - Population: type of animal that is affected is of considerable importance. 2. Hypothesis – an explanation or proposition that can be tested by facts that are known or can be obtained. Elements of epidemiological hypothesis: must specify - The population - The cause being considered - The expected effect - The dose-response relationship - The time-response relationship Causal Models Methods in formulating Epidemiological Causal Model 1 Hypothesis: Types of causes: - Method of Difference – if the frequency of a disease - Sufficient cause – if it inevitably produces an effect. is markedly different under two different Different sufficient causes may have component circumstances and some factor can be identified in causes. one circumstance that is absent in the other, this - Necessary cause – must always be present to factor or its absence, may be a cause of the disease. produce an effect. - Method of Agreement – if a factor is common to a number of different circumstances that have been Component causes: found to be associated with the presence of the - Predisposing factors – which increase the level of disease, the factor may be a cause of the disease. susceptibility (e.g., age, immune status) - Method of Concomitant Variation – involves the - Enabling factors, which facilitate manifestation of search for some factor whose frequency or strength the disease (e.g., housing and nutrition) varies with the frequency of the disease. - Precipitating factors, which are associated with the - Methods of Analogy – the distribution of the disease definitive onset of disease (e.g., many toxic and may be sufficiently similar to that of some other infective agents) disease that has been more completely and - Reinforcing factors, which tend to aggravate the successfully investigated to suggest that certain presence of a disease (e.g., repeated exposure to an causes may be common to the two (process of infectious agent in the absence of an immune deductive reasoning) response) kting Page 2 VPH 81: EPIDEMIOLOGY 1ST HOUR COVERAGE 3. Some Considerations in the Formation of Hypothesis: - New hypothesis are commonly formed by relating observations from several different fields. - The stronger a statistical association, the more likely it to suggest a causal hypothesis. - Observation of change in frequency of a disease over time have been very productive of hypothesis. - An isolated or unusual case should receive particular attention in the formation of hypothesis. - Observations that appear in conflict or create a paradox are particularly worthy of consideration. 4. Aspects of association to be considered in attempting to distinguish causal from non-causal association - Strength of association – magnitude of the ration of incidence rates. Strong associations are more likely to be causal than weak associations because if they were due to confounding or some other bias, the biasing association would have to be even stronger and would therefore presumably be evident. - Consistency – repeated observation of an association in different populations under different circumstances. Lack of consistency, however, does not rule out a causal association because some effects are produced by their causes only under unusual circumstances (complementary component causes). - Specificity – a cause lead to a single effect, not multiple effects. - Temporality – cause precede the effect on time. - Biological gradient – presence of a dose response curve. - Plausibility – biologic plausibility. - Coherence – a cause and effect interpretation for an association does not conflict with hat is known of the natural history and biology of the disease. - Experimental evidence - Analogy kting Page 3