What can social networks tell us about the epidemiology of the 2019-2020 Coronavirus outbreak?

MISMS 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.

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Need Help In in Data Analysis?

DIEPS 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

MISMS 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

Training 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

 

Time Event Presenter
9:00am Welcome and Introductions

  • Pre-session surveys
Peter Thielen
9:30am Low-Resource Genome Sequencing with Oxford Nanopore: Outbreak response and Influenza Applications  Peter Thielen
10:00am Data Analysis Objectives: Rapid Characterization and Consensus Sequence Generation Peter Thielen
11:00am BREAK
11:15am Rapid Talks: Single Slide Presentations from Attendees Attendees
12:00pm Lunch / Surveillance Meeting Field Trips

 

Day 2 (Friday Feb 7):

Laboratory Considerations and Basic Bioinformatics

 

Time Event Presenter
9:00am Practical Considerations: Establishing a Genomics Wet Laboratory

  • Efficient isolation of nucleic acids (DNA/RNA)
  • Targeted and untargeted sequencing approaches
  • Accurate quantification of DNA
  • Minimizing contamination
Peter Thielen
9:30am Concepts: Optimized Influenza A Virus Sample Preparation with Ligation reagents

  • Time- and reagent-optimizing considerations
  • Sequencing of influenza multi-segment PCR amplicons
Peter Thielen
10:00am BREAK
10:15am Hands on: Sequencing with the MinION Peter Thielen
11:45pm Data Manipulation and Exploratory Data Analysis

  • Complete consensus generation on generated data
Tom Mehoke
12:15pm Lunch
1:15pm Introduction to Phylogenetics Concepts

  • 101 talks on principles of phylogenetics
  • Common mistakes
Martha Nelson
2:15pm Using data produced by the MinION

  • Outline of general analysis workflow
  • Initial processing vs. in depth analysis
Tom Mehoke
2:45pm BREAK
3:00pm Hands-on: Processing data produced so far

  • Visualization of processed data
  • Introduction to folder hierarchy
  • Consensus sequence generation
Tom Mehoke
5:00pm Day 2 Review

Revisit data from the earlier sequencing run

Recap of topics

Post-session evaluations

 

Day 3 (Saturday Feb 8):

Phylogenetics

 

Time Event Presenter
9:00am Identifying Genomes and Building a Genetic Sequence Dataset

  • Genbank
Nídia Trovão
10:00am Multiple Sequence Alignment and Building a Phylogenetic Tree

  • AliView
  • MEGA
Nídia Trovão
11:00am BREAK
11:15am Post-processing of Phylogenetic Trees

  • FigTree
Martha Nelson
12:15pm Lunch
1:15pm How To: Interpret a Phylogenetic Tree Martha Nelson
2:15pm Final Recap

  • Open Discussion: Moving forward with resource development and applied research
  • Post-session evaluations
3:00pm BREAK
3:15pm Time to Work With Your Own Data All instructors available for questions

 

 

 

 

MinION Workshop – Colombia

MISMS Influenza Workshop – Zambia

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

MISMS Workshop – Zambia

Short-Term Visiting Fellows Program

The 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

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.

 

Hiring post-doctoral fellows

Post-doctoral fellowships · Infectious Disease

Fogarty International Center · Bethesda, MD

The Fogarty International Center (FIC), at the National Institutes of Health (NIH) in Bethesda, MD, is seeking post-doctoral fellows to study the epidemiology and evolutionary dynamics of human pathogens on a global scale. The position is within the Division of International Epidemiology and Population Studies (DIEPS), which has a long history of running computational projects and field studies, developing data-rich models, managing international collaborations and training programs, and translating research findings to policy, particularly in the area of influenza (see MISMS project). In addition to conducting primary research, the candidate(s) will have the opportunity to be an instructor at international training workshops. Successful candidates will work in the historic Stone House on the NIH Bethesda campus and enjoy fruitful interactions with the dynamic community of NIH intramural scientists. The candidate will participate in international research networks that generate data, for example NIAID’s Centers of Excellence in Influenza Research and Surveillance (CEIRS) and the RSV DIVERGE project. DIEPS has broad research interests that include disease modeling and forecasting, anti-microbial resistance, and pathogen evolution at the human-animal interface.

Successful candidate(s) will have a doctoral degree (PhD or equivalent) in computational or evolutionary biology, bioinformatics, or related quantitative fields. Strong quantitative and communications skills are required. The ability to critically evaluate data, publish scientific papers, work in interdisciplinary environments, and present at conferences is essential.

Interested candidates should contact Martha Nelson (nelsonma@mail.nih.gov) or Cécile Viboud (viboudc@mail.nih.gov). Applications should include a cover letter, a CV, a brief statement of research interests, and the names (and contact info) of three references. Salary will be commensurate with experience and NIH guidelines. US and non-US citizens are encouraged to apply.

 

Developing influenza vaccines for swine in Mexico

MISMS researchers characterized the high levels of genetic diversity of influenza viruses circulating in swine in Mexico, working closely with veterinarians in Mexico and with funding from a major animal vaccine manufacturer. The study is available online at Emerging Infectious Diseases and will be published in print next month. The study was a collaboration between the NIH, USDA, and University of Minnesota, which performed the genetic sequencing of the viruses. USDA performed antigenic cartography to visualize how the host immune system ‘sees’ virus lineages differently. MISMS staff performed the phylogenetic analysis, which showed that the viral diversity seen in Mexican swine comes primarily from humans (reverse zoonosis) and US exports of live hogs to Mexico. The direction of trade of live hogs between countries is critical in shaping where viruses are found globally.