Introduction to Biostatistics and Epidemiology

Flashcards covering key concepts from the lecture notes on biostatistics and epidemiology.

What is biostatistics?

The branch of statistics responsible for interpreting scientific data in biology, public health, and medicine.

Why is biostatistics important in health sciences?

It informs public health policy and decision-making; evaluates new treatments and interventions; identifies disease risk factors; and aids in accurate diagnosis and prognosis.

What is Descriptive Biostatistics?

Summarizes data using numbers and graphs (e.g., mean, median, frequency). Example: average hemoglobin level in a population.

What is Inferential Biostatistics?

Makes predictions or inferences from sample data using probability, hypothesis testing, and confidence intervals. Example: testing if a new diagnostic test is more accurate.

What is epidemiology?

The study of the distribution and determinants of health-related states or events in specified populations and the application of this study to the control of health problems.

Why is epidemiology important in health sciences?

It looks at patterns in groups, is essential for public health surveillance, outbreak control, and informing health policy.

What does Distribution refer to in core epidemiologic concepts?

The frequency and pattern of health events in a population (who is affected, where, and when).

What are determinants in epidemiology?

Factors or causes that influence the occurrence of health problems; can be biological, behavioral, environmental, or social.

What are outcomes in epidemiology?

Morbidity, mortality, and recovery

What does 'population-based' mean in epidemiology?

The unit of analysis is the population, not the individual.

What is the application of epidemiology?

Prevention and intervention strategies, health policy creation, and program evaluation.

Example of distribution in epidemiology

More dengue cases occur during the rainy season in Metro Manila.

Example of determinants in epidemiology

Poor water drainage and standing water can lead to more mosquito breeding and dengue cases.

What are epidemiologic outcomes?

Morbidity, mortality, and recovery as health outcomes.

What is a population-based example in epidemiology?

Tracking how many people in Cebu tested positive for COVID-19 in July.

What is the applied/analytic epidemiology used for?

Examines causes and associations using case-control, cohort, and experimental studies; uses data for interventions.

What does Descriptive Epidemiology describe?

Describes disease occurrence by person, place, time (e.g., COVID-19 incidence by region).

What does Analytic (Applied) Epidemiology do?

Examines causes and associations; uses case-control, cohort, and experimental studies to implement interventions.

Types of data: Quantitative vs Qualitative

Quantitative data are numerical; Qualitative (Categorical) data are categories.

What is discrete quantitative data?

Countable, finite values (e.g., number of red blood cells per mm³).

What is continuous quantitative data?

Measurable, infinite values within a range (e.g., weight, serum cholesterol).

What is nominal qualitative data?

Categories with no inherent order (e.g., blood type).

What is ordinal qualitative data?

Ordered categories (e.g., tumor stage, Likert scale).

Independent variable in epidemiologic studies?

The variable that is manipulated or categorized to observe its effect (e.g., smoking status).

Dependent variable in epidemiologic studies?

The outcome being measured (e.g., lung cancer incidence).

Confounding variable?

A factor associated with both exposure and outcome that can distort the observed association (e.g., age).

Controlled variable?

A variable kept constant to prevent affecting the outcome (e.g., laboratory temperature).

What are the four levels of measurement?

Nominal, Ordinal, Interval, and Ratio.

Nominal level: definition and example

Categories with no order (e.g., blood type). Analysis: frequency and mode.

Ordinal level: definition and example

Ordered categories (e.g., cancer stages, Likert scale). Analysis: median and non-parametric tests.

Interval level: definition and example

Ordered with equal intervals, no true zero (e.g., temperature in °C). Analysis: mean, standard deviation, correlation.

Ratio level: definition and example

Ordered with equal intervals and a true zero (e.g., weight, age, blood pressure). Analysis: all statistical operations.

Incidence rate?

New confirmed cases per week (per population).

Prevalence?

Total active cases in a region at a given time.

Case Fatality Rate (CFR)?

Percentage of deaths among confirmed cases.

Reproductive number (R0)?

Transmission potential; average number of secondary cases produced by a typical infected person in a susceptible population.

Role of Biostatistics in medicine?

Provides the math behind medical evidence.

Role of Epidemiology?

Frames the understanding of disease in populations and guides surveillance, policy, and interventions.

Why are data types and measurement levels important?

They guide study design, data analysis, and interpretation to ensure sound science.

Public health relevance of epidemiology?

Informs outbreak response, vaccination campaigns, resource allocation, and community health education.

Key reference for biostatistics?

Daniel, W. W., & Cross, C. L. (2018). Biostatistics: A Foundation for Analysis in the Health Sciences.

Key reference for epidemiology?

Gordis, L. (2014). Epidemiology (5th ed.).