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Brief Module Description

Top[PLEASE NOTE: All webcast recordings in LumiNUS: https://luminus.nus.edu.sg]

This module provides students with the foundational knowledge of epidemiology and biostatistics, and introduces students to the key principles of qualitative research methods. Students will learn how to quantify the burden of disease in populations, identify potential risk factors, develop and test hypotheses. Key considerations for the design of observational, interventional, and screening studies, and basic skills related to the analyses and interpretation of data from such studies will be emphasised. Students will gain an appreciation of the complementary nature of qualitative and quantitative research methodologies in answering public health questions.

Learning Outcomes

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At the completion of this course students should be able to

1.     Articulate the underlying principles of qualitative and quantitative research methods, including their strengths, limitations and applications for public health research
2.     Demonstrate an understanding of commonly used methods in qualitative research work, with an emphasis on in-depth interviews and focus group discussion
3.     Display awareness of the common public health data sources, and discuss strengths and limitations of these data sources
4. Describe global indicators of disease burden (such as life-expectancy, YLL and DALYs) and calculate measures of disease frequency such as incidence and prevalence to quantify the burden of disease in communities.
5.     Summarise and display quantitative data
6.     Summarise data using scatter plots and correlation to understand the relationship between two variables
7.     Interpret epidemiological data to describe patterns of disease occurrence and to develop hypothesis about potential risk factors for outcomes
8.    Translate research objectives into clear, testable hypothesis and become familiar with the application of statistical tests such as chi-square, Barnards exact test, t-test, Mann Whitney’s test, ANOVA and Kaplan-Meier curves, for testing
        hypothesis with categorical and continuous outcomes.
9.   Critically appraise observational and experimental study designs by understanding the structure of these designs, their strengths and limitations, sources of bias and confounding, and effect modification
10. Calculate and interpret measures of association for observational and experimental study designs
11. Understand the fundamentals of type-1 and type-2 errors, power and detectable effect size, and how it relates to hypothesis testing
12. Demonstrate an understanding of the key considerations of screening tests in public health including screening tests properties, validity and application of screening tests, and epidemiological consideration (including lead-time bias, and length bias) for evaluating the effectiveness of screening as a preventive measure.
13. Interpret ROC curves in describing and comparing screening and diagnostic tests.
14. Demonstrate an understanding of probability, conditional probability, Bayes theorem and probability trees.
15. Describe ethical considerations for designing, analysing and reporting public health data
16. Understand the basic principles of and develop an appreciation for the use of mixed methods
17. Critically evaluate published literature with regards to study question, appropriate choice of methods, study design, ethics and interpretation of findings

Schedule

TopThis module is offered on Mondays (6-9 pm), Thursdays (6-9 pm) and Saturdays (9-12 nn), starting 13 August 2018. Please refer to the Module Schedule under weblinks and the Lesson Plan for more details.

Prerequisites

TopNil.

Teaching Modes

TopPre-class videos/reading, pre-class exercises, lectures, tutorials, application sessions, STATA labs, quizzes, paper critique.

Consultation

TopLecturers' office hours: Mondays 5-6pm and Thursdays 5-6pm.
The hour before classes will be office hour by the lecturer who will be lecturing on that day.

Teaching Assistants' consultation: Mondays 3-5pm and Wednesdays 3-5pm. (Strictly by appointment only)
You may contact the Teaching Assistants for a consultation session at the following email: sph5002.phrm@gmail.com
Please email for an appointment with your questions.

Syllabus

TopDescriptive Epidemiology
§       Describe the role that epidemiology and biostatistics play in public health research and practice
§       Describe the sources of data on mortality and morbidity, their advantages and limitations
§       Understand the concept of population-at-risk, and the various measures used to denote incidence and prevalence of ill-health.
§       Compute and interpret measures of disease occurrence : prevalence and incidence measures
§       Identify appropriate and inappropriate uses of numbers, rates and proportions in epidemiologic data and interpret patterns of occurrence of disease
     (in relation to person, place and time)
§       Describe the global indicators of burden of disease (both mortality & morbidity measures, including life expectancy, YPLL, DALYs)
§       Compare mortality/morbidity between different populations, or over time, and understand the pitfalls and limitations inherent in these comparisons
§       Understand conceptually simple direct and indirect standardisation to adjust for differences between populations being compared; and interpret
     age- adjusted rates and standardised mortality ratios
§       Recognise data types: variables, categorical (nominal/ordinal), continuous
§       Apply tabular, graphical techniques to summarise public health data
§       Understand & apply summary measures (frequencies, central tendencies, standard deviations, counts, & other measures of dispersion
§       Describe and compare relationships between two variables using cross tabulations, scatterplots, correlations
§       Interpret differences in distributions with visual displays e.g. boxplots, histograms

Key study design concepts
§       Introduction to the different types of quantitative study designs
§       Describe causation and understand the importance of bias, chance and confounding in limiting causal inference
§       Understand measurement error and types of measurement error (systematic and random)
§       Describe the difference between absolute and relative risk, and the use of these measures in public health settings

Prevalence
§       Understand the principles of cross-sectional /prevalence studies
§       Describe biases in prevalence studies
§    Become familiar with ways to graphically represent survey data
§       Interpret confidence intervals

Interventional studies
§       Describe study design features of clinical trials
§       Calculate and interpret measures of association related to clinical trials
§       Describe the general principles related to validity in an interventional trial, and interpret results from such studies
§       Describe factors affecting the generalisability of trial results
§       Demonstrate understanding of special considerations for preventive trials and public health interventions, including

Trials involving complex interventions
‘Pragmatic’ trials
Cluster randomised trials

§       Demonstrate a clear understanding of the ethical issues related to interventional studies in public health
§       Introduce hypothesis testing, translate research objectives into clear, testable hypothesis.
§       Understand categorical outcomes hypothesis testing: chisq test, Barnard’s exact test
§       Understand continuous outcomes hypothesis testing: t-test, t-test, Mann-Whitney, ANOVA, Kaplan-Meier curves

Observational studies
§       Understand key distinguishing features of observational studies (cross-sectional, case-control and cohort)
§       Compute and interpret appropriate measures of associations based on study design
§       Understand confounding and its impact on internal validity
§       Identify sources of selection bias and information bias and articulate design changes to manage these errors
§       Describe elements of the study design which influence internal and external validity
§       Demonstrate an understanding of effect modification and interaction
§       Demonstrate an understanding of the strengths and weakness of different study designs (critical appraisal of published literature)
§       Describe basic principles of type I, type II errors, power and detectable effect sizes,

Screening
§       Define and explain how the validity of a screening/diagnostic test is determined, and calculate and interpret specificity,
             sensitivity for individual tests and combinations of tests, and understand their application
§       Understand and interpret ROC curves in describing and comparing screening/diagnostic tests
§       Calculate and interpret predictive values and understand their application
§       Interpret common measures used for denoting reliability/repeatability of tests
§       Describe and apply epidemiologic considerations in evaluating effectiveness of screening as a preventive measure in public
             health, including lead-time and length bias
§       Have a basic understanding of probability, conditional probably, Bayes rules, and probability trees

Ethical dilemmas
§       Sensitise students to potential sources of ethical dilemmas in public health research and practice (study design, resource
              prioritisation, fishing trips)

Introduction to qualitative methods and mixed methods
§       General principles of qualitative methods
§       Recognise the rationale and challenges of mixed- methods approaches
§       Describe the complementary aspects of qualitative and quantitative methods

Assessment

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(a)	Class Participation	10%
(b)	MCQ (pre-class)	10%
(c)	QUIZ (best 3 of 4)	60%
(d)	Final Exam - Paper Critique	20%
	TOTAL	100%

Disclamier

TopWhen a student is unable to attend the required sessions, an excuse may be granted for limited time periods upon the production of evidence of illness, misadventure or leave of absence having been granted. Students must inform the Education Office if any of the above has taken place.