
POSTPONED
New date TBD

FIC MISMS workshop
Influenza epidemiology, digital surveillance and evolutionary dynamics
March 12-13, 2020
ANISE meeting, Livingstone, Zambia
Link for Registration
This training workshop is held in conjunction with the March 2020 meeting of the ANISE network in Zambia and follows scientific research sessions and training modules led by the GISAID and WHO teams earlier in the week.
Information on influenza epidemiology and evolutionary dynamics is particularly useful to guide intervention strategies, optimize surveillance, and vaccine design, but such studies remain scare in low-income settings. Digital surveillance uses novel data streams (Google searches, Twitter, data from participatory surveillance systems) to help monitor and forecast influenza activity in settings where traditional surveillance data may be lacking, sparse, or lag by several weeks. Phylogenetic analyses of influenza sequence data are important to shed light on the global, regional and local migration of influenza viruses, their evolution, and the match of circulating strains with available vaccines.
The objective of this two-day MISMS workshop is to train epidemiologists and virologists from Africa (particularly from countries with available data) on the use of the quantitative epidemiological methods for digital surveillance and forecasting, and on phylogenetic analyses for phylodynamics and phylogeography using the BEAST package.
This workshop will include two separate modules devoted to (i) epidemiology and (ii) phylogenetics. Both modules will include theory and practice sessions. Participants will be invited to work with their own data and with publicly available sample datasets.
Participants in the epidemiological module will be taught how to use different R packages for statistical analyses of influenza time series (lab-confirmed cases, ILI or SARI) and develop models using digital surveillance signals (Google, Twitter). They will learn how to use and analyse various Google tools, such as Google searches, Google correlates, and Google Trends. Short-term influenza forecasting models will also be presented. Participants will be walked through examples using sample datasets, and if time allows, a few hours will be devoted to the analysis of the participants’ own data. There will be a live demo of InfluenzaNet, an on-line platform for influenza participatory surveillance.
Participants in the phylogenetic module will learn how to prepare a sequence dataset, explored it using maximum likelihood phylogenies and use the BEAST platform to perform advanced phylogenetic analyses to understand the spatial and evolutionary dynamics of influenza viruses. 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 influenza 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:
Trevor Bedford, Fred Hutchinson Cancer Institute, WA, USA (TBC)
Daniela Paolotti, Institute for Scientific Interchange, Italy
Mauricio Santillana, Boston Children Hospital, MA, USA (TBC)
Kaiyuan Sun, NIH-Fogarty, Bethesda, MD, USA
Nídia Sequeira Trovão, NIH-Fogarty, Bethesda, MD, USA
Cécile Viboud, NIH-Fogarty, Bethesda, MD, USA
Excess Deaths from COVID-19
/in News /by Martha NelsonMISMS researcher Dr Cecile Viboud published a study in JAMA Internal Medicine estimating that the number of deaths due to any cause increased by approximately 122 000 from March 1 to May 30, 2020, which is 28% higher than the reported number of COVID-19 deaths.
How COVID took hold in North America and Europe
/in News /by Martha NelsonMISMS researchers Dr Martha Nelson and Dr Andrew Rambaut coauthored a study that tracked how the pandemic emanated from China and took hold in North America and Europe in early 2020.
Links:
Worobey et al, Science 2020 The emergence of SARS-CoV-2 in Europe and North America
Featured in NIH Director’s Blog
What can social networks tell us about the epidemiology of the 2019-2020 Coronavirus outbreak?
/in News /by Martha NelsonMISMS staff use social network data to study the epidemiology of the COVID-19 outbreak in China in a study published this week in Lancet Digital Health.
Need Help In Data Analysis?
/in Uncategorized /by Martha NelsonDIEPS staff collaborate globally to help researchers conduct phylogenetic analysis, time-series analysis, and/or mathematical modeling and publish co-authored studies in peer-reviewed journals. To begin a discussion about how DIEPS might be able to provide assistance in an analysis, please provide detailed information about the proposed project in the fields below.
Please note that DIEPS has limited staff and may not be able to accommodate all requests. We will try to get back to you within one week of your application.
Early childhood ‘imprinting’ influences infection with seasonal viruses
/in News /by Martha NelsonMISMS researchers show that birth year-specific differences in childhood immune imprinting explain why adults tend to be infected with H3N2 seasonal viruses while H1N1 mainly infects children in a study published in PLoS Pathogens: ‘Childhood immune imprinting to influenza A shapes birth year-specific risk during seasonal H1N1 and H3N2 epidemics‘.
MISMS MinION Workshop – Colombia
/in News, Uncategorized /by Martha NelsonTraining Workshop for the Implementation of MinION Sequencing for Influenza Viruses
February 6-8, 2020
Irotama Resort
Santa Marta, Colombia
Workshop Objective
This three-day workshop, held February 6-8th, 2020 in Santa Marta, Colombia, introduced new technologies and advanced informatics approaches that can be used for infectious disease genomic characterization in resource-limited settings. Using the portable, low-cost Oxford Nanopore MinION sequencing platform, we will introduce the essential laboratory and computational skills required to perform extensive genetic characterization of viral pathogens, using influenza A virus as a primary demonstration. Topics will include sample preparation, bioinformatics, and phylogenetic approaches to characterize newly sequenced sampled against publicly available data.
By the completion of the workshop, attendees were provided access and training to all essential bioinformatics tools required to establish real-time genetic characterization capabilities in their primary laboratories or at field sites using the low-cost Oxford Nanopore MinION sequencing platform. Best practices for implementing these new technologies in research, clinical, and public health laboratories were emphasized.
Instructors/staff:
Johns Hopkins University: Tom Mehoke, Peter Thielen
Fogarty International Center: Martha Nelson, Nidia Trovao
Workshop Agenda
Day 1 (Thursday Feb 6)
Introduction to Genomics Technologies and Oxford Nanopore Sequencing
Day 2 (Friday Feb 7):
Laboratory Considerations and Basic Bioinformatics
Revisit data from the earlier sequencing run
Recap of topics
Post-session evaluations
Day 3 (Saturday Feb 8):
Phylogenetics
MinION Workshop – Colombia
/in Uncategorized /by Martha NelsonMISMS Influenza Workshop – Zambia
/in News, Uncategorized /by Martha NelsonPOSTPONED
New date TBD
FIC MISMS workshop
Influenza epidemiology, digital surveillance and evolutionary dynamics
March 12-13, 2020
ANISE meeting, Livingstone, Zambia
Link for Registration
This training workshop is held in conjunction with the March 2020 meeting of the ANISE network in Zambia and follows scientific research sessions and training modules led by the GISAID and WHO teams earlier in the week.
Information on influenza epidemiology and evolutionary dynamics is particularly useful to guide intervention strategies, optimize surveillance, and vaccine design, but such studies remain scare in low-income settings. Digital surveillance uses novel data streams (Google searches, Twitter, data from participatory surveillance systems) to help monitor and forecast influenza activity in settings where traditional surveillance data may be lacking, sparse, or lag by several weeks. Phylogenetic analyses of influenza sequence data are important to shed light on the global, regional and local migration of influenza viruses, their evolution, and the match of circulating strains with available vaccines.
The objective of this two-day MISMS workshop is to train epidemiologists and virologists from Africa (particularly from countries with available data) on the use of the quantitative epidemiological methods for digital surveillance and forecasting, and on phylogenetic analyses for phylodynamics and phylogeography using the BEAST package.
This workshop will include two separate modules devoted to (i) epidemiology and (ii) phylogenetics. Both modules will include theory and practice sessions. Participants will be invited to work with their own data and with publicly available sample datasets.
Participants in the epidemiological module will be taught how to use different R packages for statistical analyses of influenza time series (lab-confirmed cases, ILI or SARI) and develop models using digital surveillance signals (Google, Twitter). They will learn how to use and analyse various Google tools, such as Google searches, Google correlates, and Google Trends. Short-term influenza forecasting models will also be presented. Participants will be walked through examples using sample datasets, and if time allows, a few hours will be devoted to the analysis of the participants’ own data. There will be a live demo of InfluenzaNet, an on-line platform for influenza participatory surveillance.
Participants in the phylogenetic module will learn how to prepare a sequence dataset, explored it using maximum likelihood phylogenies and use the BEAST platform to perform advanced phylogenetic analyses to understand the spatial and evolutionary dynamics of influenza viruses. 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 influenza 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:
Trevor Bedford, Fred Hutchinson Cancer Institute, WA, USA (TBC)
Daniela Paolotti, Institute for Scientific Interchange, Italy
Mauricio Santillana, Boston Children Hospital, MA, USA (TBC)
Kaiyuan Sun, NIH-Fogarty, Bethesda, MD, USA
Nídia Sequeira Trovão, NIH-Fogarty, Bethesda, MD, USA
Cécile Viboud, NIH-Fogarty, Bethesda, MD, USA
MISMS Workshop – Zambia
/in Uncategorized /by Martha NelsonShort-Term Visiting Fellows Program
/in News, Uncategorized /by Martha NelsonThe Division of International Epidemiology and Population Studies (DIEPS) has a long-standing tradition of hosting visiting international and US researchers for training in methods of analyzing infectious disease data and long-term collaboration and publication. Some of our past visitors are listed below:
Cheryl Cohen
Alice Fusaro
Magnus Gottfredsson
Jong-Won Kang
Aba Mahamat
Anthony Newall
Baltazar Nunes
Nesli Saglanmak
If you are interested in visiting us for an extended period of time, please complete the application below to describe your research interests. We typically accept 3-4 visiting researchers per year.