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Introduction to Spatial Analysis in R

Overview
Coronavirus notice and FAQ - short course
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Coronavirus information

LSHTM is following the latest advice for the UK from Public Health England (PHE) on the coronavirus outbreak. Health and Safety of our students and staff is our top priority and, with that in mind, a decision not to deliver any face-to-face teaching until at least September 2020 has been taken.

Wherever possible, an alternative online provision is being developed and we will publish further information on our website as soon as it is available. Unfortunately, not all of our Short Courses can be delivered at a distance and will sadly be either cancelled or postponed. If this affects you directly, we will be in touch with options opened to you. 

Courses scheduled to run from September onwards are currently planned to be delivered as normal. However, the situation is developing rapidly, and you are therefore encouraged to regularly check the latest updates on the situation through reliable sources such as Public Health England. We would also strongly advise offer holders to book refundable tickets and accommodation as there is a chance that this may change. 

Overview - spatial analysis in R short course
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This short course has been cancelled. Candidates should still be able to register their interest for 2021.

Spatial analysis is becoming an increasingly useful tool throughout public health research with increasing amounts of spatial health data generated each year. Whether you’re a humanitarian aid worker looking to add map making to your growing rapid analysis skillset or an early stage PhD student who wants to learn the fundamentals before progressing to geostatistics, this short course will be well suited to your needs.

Our hands on, practical approach to teaching, with real-life examples, means you can progress from no previous experience with R to applying R to your own work with confidence. We also place a strong emphasis on enabling students to continue their learning independently allowing your skillset to continue growing beyond the end of the course.

Day 1

  • Introduction to the R computer programme, vocabulary and format of different datatypes
  • Using the “dplyr” and “ggplot2” packages to create numerical and visual summaries of structured data sets
  • Principles of tidy data
  • Practical session testing taught elements requiring a step by step approach to answer a real-world data analysis problem

Day 2

  • Introduction to spatial data types and spatial data concepts
  • Introduction to reading and visualising spatial data including interactive maps using “mapview”, “tmap”, and “sf” packages
  • Demonstration of basic and some advanced spatial manipulations such as buffering, spatial joins, and distance calculations
  • Visualisation of simple feature objects
  • Practical requires combining the skills into logical steps to answer a spatial analysis problem

Day 3

  • Revision of Generalised Linear Models and their extension as Generalised Linear Mixed Models and Generalised Additive Models
  • Including distance to features as covariates in GLMMs
  • Poisson point process models

Day 4

  • Discrete space spatial models with Markov random field smoothers
  • Principles of code review

Day 5

  • Continuous space spatial models with Gaussian process based smoothers
  • Reproducible reporting with R Markdown
  • Interactive spatial visualisation 

Who is this course for?

Practicing public health professionals and health researchers interested in adding expertise in spatial data analysis to their existing skillsets. Operational researchers and in particular those working in humanitarian crises / emergency deployments are particularly encouraged.

Teaching methods

The course is taught as a series of hands-on computer practicals using public health relevant examples from humanitarian crises. Background theory is presented by a lead tutor then students work independently or in small teams to solve a series of exercises with help available from in classroom teaching assistants. No prior experience with R is necessary for the course, but some basic knowledge and interest in epidemiological data analysis is highly desirable.

Funding
Funding - Introduction to Spatial Analysis in R
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Tuition fee waivers

Five tuition fee waivers are available for the 2020-intake of this programme funded by RECAP. Please note that the waivers do not cover travel, visa, accommodation or other incidental costs.

All fee waiver applicants must hold an offer of admission for the course. Preference will be given to applicants from low- and middle-income countries

If you wish to be considered for a fee waiver, please submit the following documents to Oliver Brady (oliver.brady@lshtm.ac.uk) no later than 5:00pm GMT on 31 March 2020: 

  • A letter of motivation (one page maximum) explaining how your existing training and experience has qualified you for this course. 
  • What you hope to gain from this course and how you will use these new skills in your current research or work. 
  • A letter of support or recommendation (one page maximum) from someone familiar with your work. This must from a professionally qualified person you know or a professional colleague stating: 
    • their role/position; 
    • how long they have known you and in what capacity; 
    • what they know of your current work; and 
    • why they think you are a good candidate for this course. 

A decision will be confirmed by 15 April 2020. 

How to apply
How to apply - spatial analysis short course
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Applying for this course

Please read LSHTM's Admissions policies prior to submitting your application.

Short courses - visas, accommodation, disclaimer
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Visas

The student is responsible for obtaining any visa or other permissions to attend the course, and is encouraged to start the application process as early as possible as obtaining a visa for the UK can sometimes take a long time. The Short Courses team can provide supporting documentation if requested.

Accommodation and meals

A list of hotels located in the vicinity of LSHTM, along with further resources for short term accommodation, can be found on our accommodation pages. Tea and coffee will be provided during breaks. Lunch vouchers for the LSHTM canteen will also be available.

Evening meals are not catered for at LSHTM, however there is a large choice of restaurants, cafés and shops nearby.

Important information

Please note:

  • If you have been offered a place on the course you will not be able to register without bringing formal ID (Passport) and without having obtained the correct visa if required.
  • It is essential that you read the current visa requirements for short course students.
  • LSHTM may cancel courses two weeks before the first day of the course if numbers prove insufficient.  In those circumstances, course fees will be refunded.
  • LSHTM cannot accept responsibility for accommodation, travel and other losses incurred as a result of the course being cancelled.