GIS and Remote Sensing for Public Health and Epidemiology Course

Introduction

The GIS and Remote Sensing for Public Health and Epidemiology Course is designed to empower public health professionals, researchers, and policy makers with the knowledge and skills needed to harness geospatial technologies in understanding, managing, and responding to health-related challenges. As spatial factors increasingly influence health outcomes—from the spread of infectious diseases to access to healthcare services—GIS (Geographic Information Systems) and Remote Sensing (RS) have become essential tools in modern public health practice.

This course introduces participants to the principles and applications of GIS and RS in the context of public health and epidemiology. Participants will learn how to collect, process, and analyze spatial data to identify patterns of disease distribution, monitor health risks, map vulnerable populations, and evaluate health interventions. Special attention will be given to how satellite imagery and spatial analysis can support disease surveillance, emergency response, and environmental health assessments.

Through hands-on training, case studies, and practical exercises, participants will work with GIS platforms and publicly available health and environmental datasets. They will develop the skills to create thematic health maps, perform hotspot analysis, model disease spread, and assess spatial access to healthcare services. The integration of mobile data collection tools and cloud-based geospatial platforms will also be explored to enhance real-time data-driven decision-making.

By the end of the course, participants will be equipped to apply GIS and Remote Sensing technologies to strengthen public health planning, disease prevention, and response strategies. Whether addressing communicable diseases, tracking environmental health hazards, or supporting health equity initiatives, participants will gain actionable insights and tools to improve health outcomes through spatial intelligence.

Duration

10 Days

Who should attend?

This course is suitable to:

·       Public health officers, epidemiologists, and disease surveillance professionals working at national, regional, or community levels

·       Health program managers and planners from government health departments, NGOs, and international health organizations

·       Medical researchers and biostatisticians interested in incorporating spatial analysis in health research

·       GIS analysts and technicians supporting public health mapping, planning, and intervention monitoring

·       Environmental health specialists dealing with spatial risk factors like water quality, pollution, and vector-borne diseases

·       Emergency response and disaster management personnel involved in epidemic mapping and health crisis response

·       Health informatics and data management professionals working with health information systems and digital health platforms

·       Staff from international development agencies and humanitarian organizations involved in health and disease mapping initiatives

Course Objectives

By the end of the course, the participant should be able to:

·       To equip participants with a comprehensive understanding of all data-related aspects of GIS, including spatial data models, data input methods, editing, visualization, metadata creation, and spatial database management for health applications.

·       To develop a clear understanding of the components, architecture, and capabilities of GIS, and how they can be applied to solve public health and epidemiological problems.

·       To build capacity in handling and analyzing spatial data for public health decision-making, disease surveillance, and resource allocation.

·       To enhance participants’ ability to conduct advanced spatial and statistical analyses on geographic health data, with emphasis on disease mapping, clustering, and spatial modeling.

·       To improve data management, geospatial analysis, and data integration skills to support evidence-based public health interventions.

·       To enable participants to perform spatial and temporal analyses of epidemiological data, including trends, hotspots, and predictive modeling using GIS tools.

·       To introduce practical methods for capturing, processing, manipulating, and visualizing geospatial data related to public health and healthcare systems.

·       To demonstrate the role of GIS as a decision support system in health policy planning, emergency response, and healthcare service delivery.

·       To train participants in mapping and georeferencing health facilities, disease prevalence, environmental risk factors, and demographic distributions.

·       To foster understanding of the use of remote sensing for monitoring environmental conditions that influence health, such as air quality, land use, water sources, and climate-related risks.

·       To promote the integration of mobile data collection tools (e.g., ODK, KoboToolbox) with GIS for real-time public health assessments and outbreak tracking.

·       To introduce participants to open-source and cloud-based geospatial platforms (e.g., QGIS, Google Earth Engine, ArcGIS Online) for effective mapping, sharing, and collaboration in public health initiatives.

·       To provide case-based learning opportunities where participants apply GIS and RS in real-world health challenges such as vector-borne disease mapping, maternal and child health access, and pandemic response planning.

Course Content

 Module 1: Introduction to Epidemiology, Public Health, and Geospatial Technologies

• Overview of key concepts in epidemiology and public health
• Role of location and space in disease surveillance and public health interventions
• Introduction to GIS and Remote Sensing in a public health context
• The value of spatial thinking in addressing public health challenges
• Planning and setting up a GIS system for health data management
• Overview of geospatial software tools (QGIS, ArcGIS, Google Earth Engine)

Module 2: GIS Data Sources and Management in Public Health

• Data types and formats in GIS for public health and epidemiology
• Public health GIS data sources (census, health surveys, satellite imagery, field data)
• GIS database creation and management for health data
• Working with and integrating multiple data formats: shapefiles, spreadsheets, GPS data
• Data cleaning, transformation, symbolization, and geocoding of health datasets
• Hands-on exercises in spatial data import, validation, and management

Module 3: Mobile Data Collection and Real-Time Health Mapping

• Mobile-based data collection techniques using ODK, KoBoToolbox, and Survey123
• Designing health data collection forms and questionnaires
• Integrating field-collected data with GIS platforms
• Real-time data syncing and visualization using cloud-based dashboards
• Use of mobile apps and drones in disease outbreak monitoring

Module 4: Spatial Mapping and Visualization in Health and Epidemiology

• Thematic mapping of public health indicators and project interventions
• Spatial distribution mapping of priority diseases (HIV/AIDS, TB, Malaria, COVID-19, etc.)
• Mapping vulnerable populations and health risk zones (e.g. MARPs, IDPs)
• Health facilities and resource mapping using spatial layers and buffers
• Map styling, legend design, and cartographic standards for health communication
• Creating dynamic web maps for public health communication

Module 5: GIS Applications for Disease Monitoring and Emergency Response

• Spatial-temporal disease surveillance and trend mapping
• Hotspot detection and cluster analysis of outbreaks
• GIS for tracking disease transmission routes and progression
• GIS as a Decision Support System (DSS) for public health response
• Case studies: disaster risk management, emergency health planning, vaccination logistics
• Use of Artificial Intelligence and Machine Learning in spatial health analytics

Module 6: Participatory GIS and Mobile GIS in Health Interventions

• Principles and practices of Participatory GIS (PGIS) in community health planning
• Public participation mapping for disease vulnerability and intervention prioritization
• Mobile GIS for rapid health assessments, monitoring, and surveillance
• Case studies: integrating GIS with Electronic Medical Records (EMRs) and HMIS
• Community-driven spatial data for health equity and inclusion

Module 7: Remote Sensing for Environmental Health and Risk Assessment

• Introduction to Remote Sensing concepts and platforms for health applications
• Monitoring environmental factors influencing public health (e.g. water quality, pollution, temperature, land use)
• Satellite data in tracking vector habitats (e.g., mosquitoes, ticks)
• Case studies: air quality, climate-sensitive diseases, flood-prone areas
• Using Sentinel, MODIS, and Landsat data for health-environment linkages

Module 8: Basic Statistical and Spatial Analysis for Public Health

• Data preparation and validation in Excel for health statistics
• Sorting, filtering, cleaning, and auditing health data
• Descriptive statistics and trend analysis
• Creating and interpreting graphs, charts, and dashboards
• Pivot tables, pivot charts, and summary reports
• Introduction to hypothesis testing and probability distributions
• Measures of precision and analysis of variance (ANOVA)
• Regression analysis and correlation in public health data
• Spatial statistics and geo-statistical modeling in health (e.g., spatial autocorrelation, interpolation, spatial regression)

Module 9: Data Quality Assurance and Reporting

• Key principles of data quality management in public health GIS
• Techniques for verifying and validating spatial health data
• Reporting spatial analysis results for public health decision-making
• Developing interactive reports, dashboards, and story maps for health stakeholders
• Open data and interoperability in global health information systems

Module 10: Spatial Epidemiology and Disease Modeling

• Introduction to spatial epidemiology and spatial distribution patterns
• Spatio-temporal analysis of disease outbreaks
• Disease risk modeling using GIS
• Kernel density estimation and heatmap generation for hotspot detection
• Emerging Topic: Predictive disease modeling using geostatistical methods and AI

Module 11: Climate Change, Health, and Spatial Analysis

• Assessing the impact of climate variability on disease patterns
• Mapping climate-sensitive diseases (e.g., malaria, dengue, cholera)
• Integrating climate data (rainfall, temperature, humidity) into health GIS
• Early warning systems for climate-related health risks
• Emerging Topic: Climate-health vulnerability mapping for adaptation planning

Module 12: Health Equity, Social Determinants & GIS

• Mapping access to healthcare and health inequities
• Spatial analysis of social determinants of health (income, education, housing, etc.)
• Using GIS to support Universal Health Coverage (UHC) planning
• Emerging Topic: Geo-visualization of disparities in health outcomes and services

Module 13: Data Ethics, Privacy, and Governance in Health GIS

• Ethical considerations in collecting and using spatial health data
• Ensuring patient privacy and data confidentiality in health mapping
• Legal and institutional frameworks for public health geospatial data
• Emerging Topic: Implementing FAIR (Findable, Accessible, Interoperable, Reusable) data principles in health informatics

Module 14: Integration of GIS with Health Information Systems (HIS)

• Overview of national and global Health Information Systems (e.g., DHIS2)
• Integrating GIS with routine health surveillance systems
• Linking GIS tools with EMRs and mobile health platforms
• Emerging Topic: Geospatial analytics in health system strengthening

Module 15: Geospatial Technologies for Immunization and Outbreak Response

• GIS for vaccination campaign planning and coverage monitoring
• Mapping cold chain infrastructure and supply routes
• Real-time mapping of disease incidence during epidemics
• Emerging Topic: Use of drones and geofencing in emergency health logistics

Training Approach

This course will be delivered by our skilled trainers who have vast knowledge and experience as expert professionals in the fields. The course is taught in English and through a mix of theory, practical activities, group discussion and case studies. Course manuals and additional training materials will be provided to the participants upon completion of the training.

Tailor-Made Course

This course can also be tailor-made to meet organization requirement. For further inquiries, please contact us on: Email: training@upskilldevelopment.com Tel: +254 721 331 808

Training Venue 

The training will be held at our Upskill Training Centre. We also offer training for a group at requested location all over the world. The course fee covers the course tuition, training materials, two break refreshments, and buffet lunch.

Visa application, travel expenses, airport transfers, dinners, accommodation, insurance, and other personal expenses are catered by the participant

Certification

Participants will be issued with Upskill certificate upon completion of this course.

Airport Pickup and Accommodation

Airport pickup and accommodation is arranged upon request. For booking contact our Training Coordinator through Email: training@upskilldevelopment.com, +254 721 331 808 

Terms of Payment

Unless otherwise agreed between the two parties payment of the course fee should be done 3 working days before commencement of the training so as to enable us to prepare better.