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Population based studies using epidemiological principles are used to understand the culture system and species.Different types of approaches can be taken in this direction. In observational studies nature is allowed to take itscourse while the differences or changes in characteristics of the population are studied without intervention fromthe investigator. Observational studies can be descriptive, longitudinal, cross-sectional or case-control. Descriptivestudies describe the distribution and frequency of a outcome (e.g. disease) in a population. The described patternsmay lead to a hypothesis (for example, EUS occurs normally during cooler months of the year). Longitudinalstudies follow study units through time, observe and record the course of natural events, record frequency ofoutcomes (e.g. disease), look for differences (factors) between groups with and without the selected outcome (e.g.disease). Cross-sectional study gives a snapshot in time, prevalence of outcome (e.g. disease) is measured andcompared among those with and without the risk factor of interest (ex: PCR positivity of PL). Case-control studyselects units with the outcome (e.g. disease) of interest as cases and units without the disease as controls,frequencies of suspected risk factors are then measured for the two groups and compared. The most frequentlyused approach is conducting questionnaire based population survey and then using the information to identify riskfactors.i) Outcomes and AssociationsEpidemiological studies define certain outcomes and use them for separating the population into groups forcomparison. Frequently used outcomes in epidemiology are mortality and disease outbreaks. For example, shrimpponds may be divided into successful ponds and failure ponds based on disease outbreaks, yield, weight atharvest, length of production cycle, etc. Using epidemiological and statistical tools, it is possible to identifyvariables (factors) associated with defined outcomes. Variables statistically associated with successful outcomesare regarded as protective factors. Variables statistically associated with failure outcomes are regarded as riskfactors. The risk/protective factors identified based on a population are mere associations with the outcome andshould not be regarded as either cause of the outcome or solution to the outcome.Sampling is a crucial issue in epidemiological studies. The sample should be random and should represent thetarget population. The results obtained from the sample should have to be generalised to the whole population. Inorder to achieve this, the sample size should be such that the results could be generalised with 95% confidence tothe whole population and should have the power to show the statistical differences between groups. Problems ofbias and how to avoid it is of central importance to the validity of all epidemiological studies. Bias occurs whenobservations do not reflect the true situation. This is because of systematic error such as sample selection bias,sampling bias, measurement bias, etc.The aim of data analysis is to identify risk factors for selected outcomes (e.g. disease outbreaks). Risk factor isany variable having statistical association with the outcome of concern. Positive association suggests increasedrisk (risk factor) while negative association suggests decreased risk (protective factor). Such identifiedassociations are only statistical associations and not the same as the cause.Interventions developed to address the risk factors can be called as better management practices (BMPs). Forexample not drying a pond can be a risk factor for poor production. Therefore, drying the pond before stockingseed becomes a better management practice. BMPs can be developed to address series of risk factorsassociated with various stages in culture operation (pond preparation, seed selection, stocking, water qualitymanagement, feed management, disease management, pond bottom monitoring, harvest and post harvesthandling). Once a set of BMPs are developed based on scientific studies, stakeholder consultations and existingscientific knowledge, it is necessary to test the BMPs and validate them. This is normally carried out through farmdemonstration studies. BMPs are constantly evolving and changing and it is necessary to consider approaches tocontinuously evaluate and improve BMPs.77