Course overview
The Public Health Data Visualisation & Dashboard Development Training Workshop equips public health professionals, researchers, healthcare managers and monitoring and evaluation specialists with practical skills to transform complex health data into clear, interactive and actionable visual reports. The training covers data preparation, visualisation principles, public health indicators, statistical charts, trend analysis, geographic visualisation, key performance indicators (KPIs) and interactive dashboard development using tools such as Microsoft Excel, Power BI, Python and Tableau. Participants learn to develop dashboards for disease surveillance, immunisation coverage, maternal and child health, hospital service utilisation, mortality and morbidity trends, and public health programme performance. The course also introduces automated reporting, AI-assisted data analysis and responsible data presentation to support evidence-based planning, monitoring, resource allocation and public health decision-making.
Course objectives
- Prepare, clean and organise public health datasets for visual analysis.
- Automate routine public health reporting and explore AI-assisted visualisation while maintaining data accuracy, confidentiality and ethical standards.
- Apply data storytelling techniques to communicate analytical findings to technical and non-technical audiences.
- Analyse disease trends, health service utilisation, population health indicators and programme performance.
- Develop interactive dashboards using Excel, Power BI or other suitable visualisation tools.
- Select appropriate charts, graphs and visualisation techniques for different public health indicators.
Who should attend
Public health officers, epidemiologists, health information management professionals, health informatics specialists, disease surveillance officers, healthcare programme managers, monitoring and evaluation specialists, MEAL officers, biostatisticians, public health researchers, medical researchers, hospital administrators, health systems planners, NGO and humanitarian health professionals, health policy analysts, health data analysts, data scientists working in healthcare, government health officials, digital health specialists and professionals working in international health organisations.
Course content
- Module 1: Introduction to Public Health Data Visualisation Role of visualisation in public health decision-making, principles of effective data communication, types of public health datasets, data-to-insight workflows, descriptive versus diagnostic visual
- Module 2: Public Health Indicators and Data Preparation Health indicator definitions, numerators and denominators, incidence and prevalence, morbidity and mortality indicators, immunisation coverage, maternal and child health indicators, disease surveilla
- Module 3: Data Visualisation Principles and Chart Selection Bar and column charts, line charts, area charts, scatter plots, histograms, box plots, heatmaps, population pyramids, stacked charts, small multiples, charts for comparisons and trends, selecting
- Module 4: Microsoft Excel for Public Health Charts and Dashboards Importing and cleaning health datasets, Excel tables, formulas for health indicators, sorting and filtering, conditional formatting, pivot tables, pivot charts, slicers, trend analysis, dyn
- Module 5: Power BI for Public Health Dashboard Development Importing healthcare datasets, Power Query data transformation, table relationships, data modelling, introductory DAX measures, calculating health indicators, KPI cards, trend charts, interactive
- Module 6: Python for Public Health Data Visualisation Python notebooks, pandas for data preparation, Matplotlib, Seaborn and Plotly fundamentals, visualising disease incidence, mortality and service utilisation, age and sex comparisons, time-series charts
- Module 7: Disease Surveillance and Epidemiological Dashboards Surveillance data structures, case counts and reporting completeness, epidemic curves, weekly and monthly disease trends, baseline comparisons, outbreak alerts, geographic comparisons, case fat
- Module 8: Health Programme Monitoring and Performance Dashboards Defining programme KPIs, indicator metadata, baseline and target comparisons, immunisation performance, maternal and child health indicators, service coverage, programme outputs and outcomes
- Module 9: Geographic Visualisation and Health Mapping Fundamentals of geographic health data, administrative boundaries, facility locations, choropleth maps, disease distribution maps, service accessibility, regional comparisons, mapping population health
- Module 10: Advanced Visualisation, Automation and AI-Assisted Reporting Interactive dashboard design, dynamic filters, advanced chart selection, automated data refresh, scheduled reporting concepts, report generation workflows, AI-assisted chart selection
- Module 11: Dashboard Quality Assurance, Governance and Communication Dashboard testing, checking calculations and indicator definitions, data reconciliation, validation against source reports, handling missing and delayed data, user acceptance testing, da
- Module 12: Practical Public Health Dashboard Capstone Project Selecting a public health problem, defining dashboard users and objectives, identifying indicators, preparing a dataset, validating data quality, calculating KPIs, selecting suitable charts, de
General notes
- The Public Health Data Visualisation & Dashboard Development Training Workshop provides practical skills in transforming health datasets into interactive dashboards, clear visual reports and actionable public health insights. Participants learn to prepare data, calculate health indicators, visualise disease trends, monitor programme performance and develop dashboards using Microsoft Excel, Power BI and Python. The training covers epidemiological charts, disease surveillance dashboards, immunisation monitoring, maternal and child health indicators, healthcare performance KPIs, geographic visualisation and AI-assisted reporting. Designed for public health professionals, epidemiologists, researchers, healthcare managers and monitoring and evaluation specialists, the course supports effective data communication, evidence-based planning and informed public health decision-making.
- Practical exercises and expected outputs Clean a sample public health dataset, validated dataset and data quality report, visualise disease incidence over time, disease trend charts and interpretation, develop an immunisation coverage dashboard, interactive immunisation performance dashboard, compare health indicators by age and sex, disaggregated health indicator visualisations, create a Power BI dashboard for facility performance, interactive healthcare KPI dashboard, visualise outbreak trends, epidemic curve and surveillance summary, map health service coverage across geographic areas, health facility distribution map, automate a monthly health reporting workflow, reusable reporting template and automated summary, use AI to assist with dashboard narratives, verified analytical commentary, complete a public health dashboard capstone project, final interactive dashboard, indicator documentation and evidence-based recommendations.
- Public Health Data Visualisation Course, Power BI Healthcare Dashboard Training, Health Data Analytics, Public Health Reporting, Disease Surveillance Dashboard, Healthcare KPI Dashboard, Public Health Data Visualisation Training, Excel for Public Health, Python Data Visualisation, Health Monitoring and Evaluation Dashboards, AI in Public Health Reporting.
Frequently asked questions
1. 1. Who should attend this course?
Public health professionals, epidemiologists, health data analysts, healthcare managers, researchers, monitoring and evaluation specialists and professionals responsible for health reporting.
2. 2. Do I need programming experience?
No. The course can begin with Excel and Power BI before introducing Python-based visualisation. Basic spreadsheet skills are helpful.
3. 3. Which dashboards will I learn to develop?
Participants may develop dashboards for disease surveillance, immunisation coverage, maternal and child health, hospital performance, mortality trends, service utilisation and public health programme monitoring.
4. 4. How is AI used in public health visualisation?
AI can assist with chart selection, code development, explanatory summaries and report drafting. Participants learn to verify calculations, avoid unsupported conclusions and protect confidential health information.
5. 5. What practical outputs will I produce?
Participants develop charts, interactive dashboards, KPI summaries, disease trend visualisations, geographic maps where applicable, and a final public health dashboard project.
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 |
Kisumu,Kenya |
10 Days |
$2,000 |
| 05/07/2027 - 16/07/2027 |
Arusha,Tanzania |
10 Days |
$3,000 |
| 06/09/2027 - 17/09/2027 |
Zanzibar,Tanzania |
10 Days |
$3,500 |