Objectives of epidemiology To identify the cause of disease and risk factors To determine the extent of disease found in community To study the natural history of disease To evaluate existing and new preventive measures To provide foundation for developing public policies
Diagnostic phase Presence of disease is confirmed with evidence of clinical findings and lab diagnosis Root cause of disease is identified
Descriptive phase Describes population at risk and the distribution of disease,both in time and place , within this population Allows a series of hypothesis to be formed about the likely determinants of the disease and the effects of these on the frequency with which the disease occurs in the populations at risk
Investigative phase Implementation of the study hypothesis Study plan Study filing
Experimental phase Testing hypothesis Exposure of drug Study the effect of drug /placebo Collect the clinical data Monitor the effect of drug
Analytical phase Arrangement of data Data mining Statistical analysis Data interpretation
Intervention phase Testing the hypothesis under controlled environment Appropriate methods for the control of the disease are examined either under experimental conditions or in the field Interventions in the disease process are effected by manipulating existing determinants or introducing new ones
Decision-making phase Knowledge of epidemiology of the disease is used to explore the various options available for its control This often involves the modelling of the effects that these different options are likely to have on the incidence of the disease These models can be combined with other models that examine the costs of the various control measures and compare them with benefits, in terms of increased productivity, that these measures are likely to produce Optimum control strategy can be selected as a result of the expected decrease in disease incidence in the populations of livestock at risk
Monitoring phase Which takes place during the implementation of the control measures to ensure that these measures are being properly applied, are having the desired effect on reducing disease incidence Success of control programme are detected
Intervention assigned Comparison group Experimental/ Interventional study Observational study Analytical Descriptive Randomization Yes No Present Absent RCT Non RCT Yes No Case Control Cohort Cross sectional Ecological Case study/report Case series Surveillance Cross sectional Ecological Clinical trial - patients Field trial - Healthy people Community trial
Descriptive studies Case study - report of a single patient Case series - Similar clinical findings of a group of patient Surveillance - Continuous scrutiny of all aspects of a disease pertinent to its effective control Cross sectional - Study of a group of people at a single point of time Ecological - Studies of risk modifying factors on health or other outcomes based on population defined either geographically or temporally (may cause ecological fallacy)
Analytical studies Case control Cohort
Case Control Retrospective ODDs ratio is calculated Suitable for rare disease Less time consuming No problem of loss of follow up/ dropout/ attrition Recall bias, selection bias present Multiple type of exposure leading to same disease can be calculated
If RR = 1 -> No association between exposure and outcome If RR > 1 -> Positive association between exposure and outcome If RR < 1 -> Negative association between exposure and outcome
Cohort Prospective Absolute risk, relative risk, attributable risk is calculated Suitable for rare exposure Much time consuming Temporality of association can be established Natural history of disease can be studied Hawthorne effect Single exposure leading to multiple disease can be studied
Variants of cohort Nested case control - Interim data analysis of an ongoing cohort study Retrospective or historical cohort Mixed cohort - Ambidirectional
Absolute risk - Incidence of disease How many times the exposed group is at higher risk of disease compared to non exposed
To what extent is the exposure responsible for disease in exposed group If the risk factor is eliminated from population, by what % the incidence of the disease will decline in that population
Example AR -> a/(a+b) RR -> {a/(a+b} / {c/(c+d)} OR -> ad/bc ARR->{a/(a+b} - {c/(c+d)} PAR-> ARR*No exposed
Randomized Control Trial Phase 0 : Animals Phase 1: Healthy individuals to know upper tolerable limit and pharmacokinetics Phase 2: Patients to know the effect of drug Phase 3: Patient to compare effect of new drug with pre existing drug Phase 4: Patient for long term effect of drug
Meta analysis Here the data from similar small comparable studies and fresh analysis of the data is done Effective sample size increase, error decrease, power of study increase, level of confidence increase Best method to establish causal inference