Course overview
The Infectious Disease Epidemiology & Data Analysis Training Workshop equips public health professionals, epidemiologists, surveillance officers, laboratory personnel and health researchers with practical skills to investigate infectious disease patterns, analyze epidemiological data and support evidence-based disease prevention and control.
An applied professional training workshop combining infectious disease epidemiology, statistical data analysis, outbreak investigation and public health decision-making.
The Infectious Disease Epidemiology & Data Analysis Training Workshop provides practical training in disease surveillance, outbreak investigation, epidemiological statistics, risk factor analysis and public health data visualization. Designed for public health professionals, epidemiologists, surveillance officers, laboratory personnel and health researchers, the workshop develops the skills needed to analyze infectious disease patterns, interpret epidemiological evidence and support effective disease prevention and control programmes.
Course objectives
- Explain the principles of infectious disease epidemiology and disease transmission.
- Communicate findings effectively to public health teams, decision-makers and communities.
- Prepare epidemiological reports, dashboards and data visualizations.
- Interpret epidemiological findings for public health interventions and policy decisions.
- Analyze temporal and geographical patterns of infectious diseases.
- Identify risk factors and interpret associations between exposures and health outcomes.
- Apply descriptive and inferential statistical methods to infectious disease data.
- Clean, validate, organize and analyze epidemiological datasets.
- Design and interpret infectious disease surveillance and outbreak investigation activities.
- Calculate and interpret incidence, prevalence, mortality, case-fatality ratios and other epidemiological indicators.
Who should attend
Epidemiologists, public health officers, disease surveillance officers, infectious disease specialists, medical and laboratory professionals, health information management officers, monitoring and evaluation professionals, biostatisticians, public health researchers, university lecturers, postgraduate students in epidemiology and public health, NGO and humanitarian health professionals, ministry of health and county health department personnel.
Course content
- Module 1: Foundations of Infectious Disease Epidemiology Definitions and scope of infectious disease epidemiology, communicable and emerging infectious diseases, sources and reservoirs of infection, modes of transmission, host-agent-environment relationsh
- Module 2: Infectious Disease Transmission Dynamics Chain of infection, incubation and infectious periods, basic and effective reproduction numbers, direct and indirect transmission, epidemic growth and decline, herd immunity concepts, transmission pattern
- Module 3: Epidemiological Measures and Indicators Incidence and prevalence, attack rates and secondary attack rates, morbidity and mortality indicators, case-fatality ratio, relative risk and odds ratio, attributable risk, person-time measures, interpreta
- Module 4: Infectious Disease Surveillance Systems Passive and active surveillance, sentinel and syndromic surveillance, event-based surveillance, laboratory-based surveillance, indicator-based reporting, case notification procedures, data quality and comp
- Module 5: Outbreak Detection and Investigation Recognizing unusual disease patterns, verifying outbreaks, developing case definitions, case finding and contact identification, line-list preparation, descriptive outbreak analysis, epidemic curves, hypothes
- Module 6: Epidemiological Study Designs Descriptive epidemiology, cross-sectional studies, case-control studies, cohort studies, ecological studies, experimental and intervention studies, selection of appropriate study designs, sampling methods, exposure
- Module 7: Epidemiological Data Management and Quality Assurance Data collection tools, data dictionaries and coding systems, dataset structure and organization, missing values and duplicate records, validation rules and consistency checks, outlier identif
- Module 8: Descriptive Statistics and Data Visualization Frequency distributions, proportions and rates, measures of central tendency and dispersion, stratification by age and sex, tables and charts, epidemic curves, weekly and monthly disease trends, comp
- Module 9: Statistical Analysis of Infectious Disease Data Probability and sampling distributions, confidence intervals, hypothesis testing, chi-square tests, comparison of means and proportions, correlation analysis, interpretation of p-values, statistica
- Module 10: Risk Factor Analysis and Regression Modelling Exposure and outcome relationships, confounding and effect modification, crude and adjusted associations, logistic regression, linear and count-data regression concepts, multivariable analysis, inte
- Module 11: Time-Series Analysis and Epidemic Trends Analysis of daily, weekly and monthly case counts, seasonality and long-term trends, moving averages, epidemic growth patterns, detection of unusual increases, introduction to time-series forecasting, in
- Module 12: Geographic Epidemiology and Disease Mapping Person-place-time analysis, spatial distribution of infectious diseases, mapping cases and rates, geographic variation in disease burden, hotspot identification, population denominators and spatial co
- Module 13: Laboratory, Clinical and Surveillance Data Integration Interpretation of laboratory-confirmed and suspected cases, linking clinical and epidemiological records, diagnostic test sensitivity and specificity, positive and negative predictive value
- Module 14: Public Health Data Visualization, Reporting and Decision-Making Design of epidemiological dashboards, selection of appropriate indicators, visualizing outbreaks and trends, communicating uncertainty, preparing epidemiological situation reports,
- Module 15: Integrated Practical Exercise and Capstone Project Importing an infectious disease dataset, data cleaning and validation, calculation of epidemiological indicators, descriptive and statistical analysis, outbreak trend visualization, risk factor
General notes
- Practical Exercises and Expected Outputs Calculate incidence, prevalence and case-fatality ratios — epidemiological indicators worksheet, clean a disease surveillance dataset — validated analysis-ready dataset, develop a case definition and line list — standardized outbreak investigation template, analyze an outbreak dataset by person, place and time — descriptive epidemiological summary, construct an epidemic curve — outbreak trend chart, conduct a case-control analysis — exposure and disease association report, perform regression analysis — risk factor analysis summary, analyze weekly disease trends — time-series visualization, map infectious disease cases — disease distribution map, integrate laboratory and surveillance records — reconciled disease dataset, build a disease monitoring dashboard — interactive public health dashboard, complete a capstone analysis — epidemiological report with evidence-based recommendations.
- Recommended Software and Tools Excel, Python, R, SPSS, Stata, Power BI, QGIS, DHIS2, KoboToolbox, Epi Info, SQL, GPS-enabled devices, enterprise AI tools.
- Training Methodology The workshop uses facilitator-led presentations, guided practical sessions, real-world public health case studies, group discussions, worked statistical examples, hands-on software demonstrations, outbreak investigation simulations, individual and group assignments, dataset-based exercises and a final capstone project. Participants work with sample or appropriately anonymized infectious disease datasets to develop practical analytical and reporting skills.
- Expected Learning Outcomes Participants will be able to clean and analyze infectious disease datasets, calculate and interpret epidemiological indicators, identify changes in disease trends, investigate potential outbreaks, assess disease-associated risk factors, visualize geographical and temporal patterns, prepare surveillance dashboards and communicate findings that support public health decisions.
- infectious disease data analysis training, epidemiology workshop, outbreak investigation training, disease surveillance data analysis, public health statistics training, epidemiological modelling, infectious disease surveillance, public health data analytics.
Frequently asked questions
1. Do I need advanced statistical knowledge?
Basic familiarity with public health concepts and data interpretation is helpful. The training introduces core epidemiological measures before progressing to statistical analysis and regression modelling.
2. Will the workshop include practical data analysis?
Yes. Participants work with sample datasets to practice data cleaning, epidemiological calculations, outbreak analysis, statistical testing, data visualization and report preparation.
3. 3. Which software will be covered?
Depending on participant needs and the training setup, the workshop may use Excel, Python, R, SPSS, Stata, Power BI, QGIS, DHIS2 and Epi Info.
4. Will participants learn outbreak investigation?
Yes. The workshop covers outbreak verification, case definitions, case finding, line-listing, epidemic curves, hypothesis generation, risk factor analysis and outbreak reporting.
5. What practical outputs will participants develop?
Participants can develop a cleaned epidemiological dataset, an outbreak analysis worksheet, an epidemic curve, a statistical analysis summary, a disease visualization or dashboard, and a final epidemiological report.
Schedule & fees
| Dates | Location | Duration | Fee (USD) |
|---|
| 01/02/2027 - 12/02/2027 |
Nairobi,kenya or Virtual |
10 Days |
$2,000 |
| 05/04/2027 - 16/04/2027 |
Arusha,Tanzania |
10 Days |
$3,000 |
| 02/08/2027 - 13/08/2027 |
Zanzibar,Tanzania |
10 Days |
$3,500 |
| 23/08/2027 - 03/09/2027 |
Kigali,Rwanda |
10 Days |
$3,500 |
| 04/10/2027 - 15/10/2027 |
Accra,Ghana |
10 Days |
$3,500 |