The Introduction to Epidemiology and Medical Statistics Training Course offered by Oxford Training Centre provides healthcare professionals, public health practitioners, and medical researchers with essential knowledge and analytical tools for understanding disease patterns and applying statistical analysis in health-related contexts. This foundational programme combines epidemiologic concepts with biostatistical techniques to prepare participants for interpreting population health trends, guiding data-driven healthcare strategies, and evaluating the outcomes of medical interventions.
Participants will develop core competencies in epidemiology and medical statistics training, including how to calculate and interpret incidence, prevalence, and mortality rates, construct epidemiological study designs, and use statistical reasoning to support decision-making in public health. Emphasis is placed on applying quantitative methods in epidemiological research, with practical training in data analysis, visualisation, and reporting.
As part of industry-relevant Healthcare Management Training Courses, this course equips professionals with the skills necessary for training in public health surveillance and medical statistics, enabling them to effectively analyse and act on health data in diverse settings. Topics such as statistical methods in epidemiology, confidence intervals and p-values in medical research, and descriptive and analytical epidemiology are embedded throughout the curriculum to support evidence-based assessments and improve health outcomes.
The training integrates practical exercises with real-world datasets to reinforce understanding of health statistics and epidemiology training concepts. Through expert instruction and interactive learning, participants will become confident in using introductory epidemiology and biostatistics course methodologies for research, policy development, and operational performance in healthcare systems.
Objectives
- Understand key principles and terminology related to foundations of epidemiology and statistics
- Apply descriptive and analytical epidemiology to monitor and interpret disease patterns
- Use statistical reasoning in health sciences for accurate assessment and reporting
- Calculate and interpret incidence, prevalence, and mortality rates
- Apply quantitative epidemiology methods to evaluate public health interventions
- Develop appropriate epidemiological study designs and statistical evaluation frameworks
- Gain practical knowledge in basics of statistical modelling in epidemiology
- Conduct and interpret hypothesis testing using confidence intervals and p-values in medical research
- Implement sampling techniques and data collection in health studies for reliable findings
- Strengthen analytical capacity in medical data collection, analysis, and interpretation
Target Audience
- Public health professionals and epidemiologists seeking foundational or refresher knowledge
- Clinical researchers and medical officers involved in data interpretation and study design
- Health analysts and statisticians working on public health projects or clinical trials
- Hospital managers and administrators seeking insights into data-driven decision-making in public health
- Professionals involved in disease surveillance and outbreak investigation
- Biostatistics educators and postgraduate students in medical or public health fields
- NGO and global health organisation staff monitoring and evaluating programme outcomes
- Government health personnel engaged in health trends and statistical reporting
- Quality assurance and health planning teams requiring analytical skills for population health and statistics
How Will Attendees Benefit?
- Gain comprehensive understanding of introductory epidemiology and biostatistics course components
- Enhance ability to assess health interventions using epidemiologic inference and causality principles
- Apply statistical methods in epidemiology for clinical and policy-related research
- Interpret and communicate findings on risk, prevalence, and incidence rates
- Build capacity in using data for public health data analysis training and programme evaluation
- Create and implement evidence-based public health training course frameworks
- Understand patterns of disease and design targeted responses using valid indicators
- Develop confidence in using software and statistical tools for real-time public health decisions
- Participate in collaborative health research projects using global best practices in epidemiology training course standards
- Improve quality and accuracy in public health reporting and evidence generation
Course Content
Module 1: Foundations of Epidemiology and Health Data
- Introduction to epidemiology training course concepts and public health relevance
- Definitions and calculation of incidence, prevalence, and mortality rates
- Overview of key indicators in health statistics and epidemiology training
Module 2: Epidemiological Study Design and Analysis
- Design of descriptive and analytical studies
- Evaluating causation using epidemiologic inference and causality methods
- Choosing the right study design based on research objectives
Module 3: Data Collection and Sampling Strategies
- Essentials of medical data collection, analysis, and interpretation
- Implementing sampling techniques and data collection in health studies
- Managing data quality and addressing selection bias
Module 4: Statistical Foundations in Health Research
- Overview of statistical reasoning in health sciences
- Applying probability, normal distribution, and hypothesis testing
- Role of confidence intervals and p-values in medical research
Module 5: Descriptive and Analytical Epidemiology Tools
- Summarising population data using rates, proportions, and ratios
- Comparing groups using risk differences and ratios
- Linking descriptive and analytical epidemiology to decision-making
Module 6: Biostatistics and Health Metrics
- Using introduction to biostatistical tools for health research
- Application of basic statistical techniques with health examples
- Reporting outcomes in a policy or clinical context
Module 7: Quantitative Methods and Statistical Modelling
- Introduction to quantitative epidemiology methods
- Basics of correlation, regression, and data modelling
- Case applications of basics of statistical modelling in epidemiology
Module 8: Disease Surveillance and Outbreak Management
- Principles of disease surveillance and outbreak investigation
- Surveillance systems, field reports, and early warning indicators
- Linking surveillance data to health system response strategies
Module 9: Public Health Reporting and Data Interpretation
- Structuring and presenting data for health trends and statistical reporting
- Building dashboards and health bulletins
- Interpretation of trends to inform interventions
Module 10: Applied Epidemiology in Policy and Practice
- Integrating findings into public health planning
- Scenario-based applications from real-world outbreaks and studies
- Leading assessments using evidence-based public health training course methodologies