This presentation deals with Epidemiology and Biostatistics and their common function of providing tools to prevent and control diseases in population.
In the beginning there are few slides introducing the concepts of Epidemiology,
Biostatistics and Public Health and their connection, together with related concepts of disease vs health and symptom vs sign. Then, I treated each subject individually.
Epidemiology emphasis distribution of diseases introducing concepts like endemic, epidemic and pandemic. The level of disease is assessed through rates. Important rates like incidence and prevalence as well as different types of rates like crude, specific and adjusted are presented.
Another important chapter in epidemiology is preventing the disease. I introduced all the three levels of prevention together with examples for each. In primary prevention we focus on the risk factors. They are determined through epidemiological studies. I defined all the types of epidemiological studies and I introduced the details of finding risk factors for case control and cohort study using specific formulas like odds ratio or relative risk. In secondary prevention we focus on the screening tests and I introduced all the important concepts related to the screening tests. In the tertiary prevention we focus on the treatment of the disease to prevent complications. Random control trials and other interventional studies are used by epidemiology to determine the best therapeutical regimen for the disease.
This section ends up with the most common mistakes related to the design and the application of the epidemiological studies, also known as bias in research.
Biostatistics deals with categories and events. I presented probabilities related to the events occurring together and the way categories can be measured through ordinal rank or interval/ratio scales. Then, I compared the two main parts of biostatistics, descriptive and inferential. Descriptive statistics deals with normal distribution AKA bell shaped distribution, mean, median, mode and various normal distributions other than bell shaped.
Inferential statistics deals with standardized normal distribution, standard deviation, standard error, standard score, confidence intervals, p value, type I alfa, type II beta error and the power of the study. Each of these concepts are defined and related to each other in the slides I named “Hypothesis testing in biostatistics”. This is mainly about how we find the risk factors associated to the disease through statistical studies and formulas.
This section ends up with a slide I dedicated to the statistical studies related to the survival rates in population.