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Fogarty International Center, NIH – National Institute for Communicable Diseases

Training Workshop on Infectious Diseases Dynamics and Evolution

December 3-5, 2018

Johannesburg, South Africa

 

Workshop outline:

A better understanding of the epidemiology and evolutionary dynamics of infectious diseases is particularly useful to guide intervention strategies, optimize surveillance, and vaccine design, but detailed studies remain scare in low- and middle-income settings.

The objective of this 3-day FIC-NICD workshop is to train epidemiologists, microbiologists, virologists and public health professionals, on the use of the computational methods in infectious diseases. Participants will learn how to use computational methods to characterize seasonality, disease burden, transmission dynamics, molecular analysis and phylodynamics of viral infections, with key focus on influenza and HIV.

Participants will be invited to work with their own data and with publicly available sample datasets. The workshop will include 2 parallel tracks on epidemiology and phylogenetics.

Participants to the epidemiology module will be taught how to use different R packages for statistical and mathematical analyses of epidemiological data, and other tools (such as EpiPoi) to visualize and define influenza seasonality and epidemic periods, estimate excess mortality or excess morbidity, infer time trends, estimate the reproduction number of epidemics, and fit simple mechanistic transmission models to data.

The phylodynamics/phylogeographic module will train participants in the use of the BEAST platform, to perform advanced phylogenetic analyses aimed at deciphering the spatial and evolutionary dynamics of viruses; influenza and HIV will be used as case studies. BEAST is a cross-platform program for Bayesian analysis of molecular sequences using Markov chain Monte Carlo (MCMC) algorithms. Outputs include rooted, time-measured phylogenies inferred using strict or relaxed molecular clock models. It can be used as a method of reconstructing phylogenies but is also a framework for testing evolutionary hypotheses without conditioning on a single tree topology. BEAST uses MCMC to average over tree space, so that each tree is weighted proportional to its posterior probability.

Participants will be provided a sample FASTA sequence datasets and walked through an example of BEAST analysis. An overview of the possible uses of BEAST will be discussed. If time allows, a few hours will be devoted to the analysis of the participants’ own data.

 

Faculty:

Philippe Lemey, University of Leuven, Belgium

Martha Nelson, Fogarty International Center, NIH

Amanda Perofsky, Fogarty International Center, NIH

Juliet Pulliam, SACEMA, South Africa

Andrew Rambaut, University of Edinburgh, Scotland

Nidia Trovao, Fogarty International Center, NIH

David Spiro, Fogarty International Center, NIH

Kaiyuan Sun, Fogarty International Center, NIH

Cecile Viboud, Fogarty International Center, NIH

 

Draft Agenda overview

 

Monday, December 3

Morning. Introductions and Research highlights (plenary; will include examples from influenza, HIV, animal-human interface and emerging infectious)

Afternoon: Break into phylogenetics and epidemiology groups

Start of 101 talks on principles of phylogenetics and disease modeling

Late afternoon: Software installation checks.

 

Tuesday December 4: 101 talks and software demonstrations

Epi track:

• Principles of time series analyses & wavelets.
• R estimation, SIR and TSIR models, network models
• Worked out example of time series/seasonality analyses in R**.
• Demonstration of EpiPoi, free software for visualization and analyses of spatio-temporal datasets
• Building models with increasing levels of complexity: HIV case study

Phylogenetics track:

• Principles of phylogenetics.
• Sequence alignments, maximum likelihood trees, detection of temporal signals.
• What you need to know before using BEAST + worked-out BEAST example
• Post-processing of BEAST trees

** For those who need more than a refresher in R, additional examples (and time) are available to become more familiar with R, in break-out groups.

Tuesday evening: Maria Giovani, NIAID programmes

 

Wednesday December 5: Presentations and hands-on practice with own data

Morning: Short presentations by participants (plenary or break-out groups, depending on size)

Remaining analytical topics to be covered

Afternoon: Work with your own data in small groups, facilitated by instructors.