Epidemiology seeks to establish associations between exposure risk as well as condition which are spatially dependent. These attempts fall by natural means within the domain of issues requiring use of spatial evaluation together with the answer, then GIS along with other spatial analysis programs are thus recognized as providing likely transformational capabilities for Public health efforts and epidemiology. The particpants in the training on remote sensing and GIS for public health will even develop statistical data analysis abilities.

Duration: 10 Days

Who Should Attend?

The program is targeted at people working with health data which have no experience by using GIS but would love to find out just how it could be used in the work of theirs.

Course Objectives

• In order to produce Understanding on the various parts of a GIS as well as the job GIS plays in solving public and epidemiological health issues.
• To provide to individuals all data related facets of a GIS, like the information models in GIS, data visualization, data editing, data input, metadata and controlling a spatial database.
• To Handle innovative analyses of geographical information with particular reference to epidemiological associated issues
• Establish understanding on how you can work with spatial GIS and data techniques to solve public health problems and epidemiology.
• In order to introduce participants  to data capture, input, display and manipulation by GIS

• In order to demonstrate In order to individuals, utilization of GIS within mapping overall health amenities along with projects.

Topics Being Covered

The training workshop is going to discuss the application of GIS wearing Public Health underneath the following themes:

Module one

Public health concepts and epidemiology and frameworks

• Introduction to Public health concepts & epidemiology

• Introduction to GIS in Public health context and epidemiology

• Planning for any GIS system installation

• GIS Data energy sources for public health and Epidemiology

• Working having a GIS software

Module two

• Mobile Data Collection applying KoBoToolbox and ODK

Module Three

GIS information management in public health and epidemiology.

• Public health as well as epidemiology GIS Database creation

• Data Types as well as Data Sources in public health and Epidemiology

• Working with GIS Data

• Working with information from various sources (databases, and shapefiles spreadsheets)

• Facilitated Practical workouts in dealing with GIS Data

• Styling and symbolization

Module four

Spatial Visualization and mapping in Public health and Epidemiology

• Mapping Project activities

• GIS mapping of main concern public health issues (HIV & Malaria, AIDS Tuberculosis)

• GIS mapping of Most Vulnerable Populations (MARPS)

• GIS Mapping of wellness services and health resources

Module five

A GIS for checking in public health and Epidemiology

• GIS in Progression and disease transmission mapping

• GIS as a choice Support System for Public Health Management (What, when, where, why and how analysis - case studies)

• Use of GIS found Health and Epidemiology Related Disaster Management (practical) or case studies

• GIS in Public health and environmental management (functional) or case studies

Module six

• Participatory GIS to come down with public health

• Use of movable GIS in health surveillance as well as assessments

 • Integrating GIS in Electronic Medical Records (practical?) or case studies

Module seven

Essential statistical data evaluation for Public health and Epidemiology

• Introduction to Excel

• Preparing information for analysis

• Creating a list

• Manipulating information with formulas

• Sorting and outlining data

• Entering Data: Data Forms

• Finding Records Using Criteria

• Filtering Data

• Data Auditing

• Data validation

Module eight

Graphs, Line and Charts Graphs

• Bar Charts

• Statistical Data Analysis with Excel Presentation utilizing Pivot charts

• Descriptive Statistics

• Pivot tables

• Probability Distribution

• Hypothesis tests

Module nine

• Analyses of Variance

• Measures of Precision

• Single Factor Experiments

• Factorial Experiments

• Regression Analysis

Module ten

• Data Quality reporting