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Tropical Diseases Modelling Network (TDModNet)

July 27, 2011 in Uncategorized

Tropical Diseases Modelling Network (TDModNet)

TDModNet is a new network for mathematical modellers and their collaborators based in the tropics and working on tropical infectious diseases. There are members with a range of research experience (from graduate student to professor) and expertise (mathematicians, biologists, epidemiologists, malariologists, policy makers, geneticists, bioinformaticists, clinicians). The aim is to provide a forum to build mathematical modelling capacity in the developing world in a self-sufficient way by exploiting the pre-existing structure of the network members.

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Postdoctoral Positions at Penn State – Malaria Modeling

February 10, 2017 in Job, postdoc

Penn State University – Jobs

The Boni Lab in the Department of Biology at The Pennsylvania State University is recruiting highly-motivated postdoctoral scholars to work on several key public health questions using large-scale individual-based malaria simulations. Our lab’s research interests can be seen here and here Positions can begin anytime in 2017. Our lab is based at the Center for Infectious Disease Dynamics at the Pennsylvania State University (University Park Campus), and we collaborate with partners based in Ho Chi Minh City, Vietnam at the Oxford University Clinical Research Unit. The postdoctoral scholar(s) will be funded by the Bill and Melinda Gates Foundation’s Malaria Modeling Consortium (MMC), and the research will be integrated into MMC activities that currently include five institutions: Penn State, Institute for Disease Modeling, Oxford, Swiss Tropical Institute, and Imperial College. The first malaria questions to be investigated will be whether (a) the deployment of multiple first-line antimalarial therapies delays the onset of drug resistance, and (b) whether delaying drug resistance benefits other malaria control strategies. The background for aim (a) is described in these two papers and The analysis for aim (b) is still to be developed. Software development for the malaria microsimulation began in 2010 and the current version of the C++ source code can be found here The main goals of this project will be to continue development and validation of the malaria microsimulation, in order to (1) add detailed geographic structure and create scenarios where the simulation can be run as a ‘country model’, with the first countries of interest being Cambodia, Zambia, and Uganda; (2) add more detailed pharmacokinetic and pharmacodynamics models that are more representative of the true action of drugs on parasites; (3) determine how best to prepare for an event where artemisinin-resistant malaria parasites are introduced into Africa, where hundreds of millions of people rely on life-saving artemisinin drugs; (4) optmize the future introduction of antimalarial drugs that will be available after 2020. Candidates are encouraged to apply if they are interested in these questions and interested in developing their own new directions in the computational epidemiology of malaria. The position requires strong knowledge of the C++ programming language. The position requires a PhD in one of Ecology, Evolution, Computational Epidemiology, Mathematical Modeling, Population Genetics, Bioinformatics, Applied Mathematics, or a related field. The ideal candidate will have experience in one or more mathematical modeling methods. Complementary expertise in epidemiology, ecology, or immunology may also be helpful but is not required. Excellent communication skills, including writing, are required, as is a strong publication record. Applications must be submitted electronically. A complete application should include a cover letter detailing experience and research interests, a current CV, and contact information for three professional references. Review of applications will begin immediately and be ongoing in 2017.

Lab website:

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Building research networks for integrating infectious disease modeling into national control programs

January 26, 2017 in News, workshop

Building research networks for integrating infectious disease modeling into national control programs


A Wellcome Trust funded workshop at Harvard University for junior scientists working at the interface of policy and research in low and middle income settings.


Organizers: Caroline Buckee (Harvard), Jessica Metcalf (Princeton)

Dates: May 10th-12th 2017

Location: Harvard University, USA

Participant limit: 15

Funding: participant travel and accommodation are covered by the workshop.


There remains a disheartening lag between the rapid advances in quantitative methods and data streams available to scientists, and the integration of the promising new approaches they afford into national control programs in low and middle-income settings. In order to take advantage of methods in genomics, mathematical modeling, remote sensing, and big data, for example, national control programs must not only partner with researchers and corporations gathering such data, but importantly, they must build internal capacity to make use of them, in order to translate research into concrete actions. For young researchers embedded in national control programs or at local universities, the lack of support from peers and mentors with appropriate expertise is often a major hurdle to achieving this goal.


We have been developing new approaches for targeting resources (spatially and temporally) for control programs of infectious diseases such as malaria, rubella, measles, and dengue fever, using new data sources and cutting edge quantitative methods. We will conduct a 3 day long workshop at Harvard University that is specifically targeted at approximately 15 junior researchers from low and middle income countries who are working at the interface of infectious disease research and policy, providing their travel and accommodation.


The main aims of this workshop are twofold:


  1. To introduce participants to key developments in infectious disease modeling and data analysis, including risk mapping, epidemiological modeling, forecasting, and new data streams (principally genomics, satellite data, and mobile phone data). Here, we will concentrate on how to use and interpret models, how to implement them, how to deal with uncertainty, as well as on specific diseases relevant to the participants.
  2. To build a network of researchers from different low and middle-income regions who may work on different diseases in different countries, but who have similar academic expertise and can support each other as a peer group. We hope that these alumni will help us to organize similar meetings in endemic settings, and result in a co-authored publication.



Day 1:

  • Introductions and short lectures (Metcalf, Buckee, Tatem, Maude)
  • Focus on data streams and hands on modeling sessions.
  • Break-out sessions: learning from each other – what are the main challenges the participants face, and why? What do they feel are the most important gaps in the control program/research area they work in? Participants will be grouped by region (Southern Africa, SE Asia, W Africa, for example) for group projects.



Day 2:

  • Full day workshop at Harvard Center for Geographical Analysis on the use of ArcGIS and mapping software for surveillance and spatial risk analysis for disease control. Participants will be encouraged ahead of time to bring data sets from their country of origin.


Day 3:

  • Breakout sessions: groups present their projects on the main challenges from their region, and general discussion.
  • Discussion: contraints of new approaches and the limits of translatability of research.
  • Review article development with input from all participants: we aim to write a review article outlining the main challenges and opportunities for national control programs with respect to the translation of new approaches to policy. Participants will bring their own experiences to bear on the feasibility for implementing state of the art techniques within programs in their respective countries. Each participant will be a co-author on a resulting publication.



Caroline Buckee (Harvard): modeling, malaria, mobile phone data

Jessica Metcalf (Princeton): modeling, rubella/measles, vaccination policy

Andrew Tatem (Southampton): geography, satellite data and remote sensing, mobile phone data

Richard Maude (Mahidol-Oxford Research Unit/Harvard): clinical epi, modeling, malaria policy

Harvard Center for Geographical Analysis: ArcGIS mapping tools



Applicants should have a Masters or a PhD in a relevant field, and be working directly with infectious disease epidemiological data, and have policy-relevant focus or experience. Ideally, applicants should be directly involved with control programs. A quantitative background is not required, but is strongly advised, and strong computer skills are essential.

To Apply :

Please send an email to Caroline Buckee ( or Jessica Metcalf ( and include a CV and a very brief description of your work and why you might be interested in and suitable for the workshop, as well as the name and email of a more senior colleague who we could reach out to for a reference.

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Wellcome Advance courses and Scientific conferences 2017

January 18, 2017 in News, workshop


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January 18, 2017 in News, workshop


26–30 June 2017

Wellcome Genome Campus, Hinxton, Cambridge, UK

Applications Invited


We welcome applications for this bioinformatics summer school, run jointly with EMBL-EBI. This course will provide an introduction to the use of bioinformatics in biological research, theory and practice, and hands-on experience on using publicly available data resources and tools.

Participants will take part in a group project to conduct bioinformatics based research and explore biological questions. The programme includes discussions on the applications of bioinformatics in biological research and practical examples on how to browse, search, and retrieve biological data from public repositories. The course will culminate in a group presentation session involving all participants, giving an opportunity for wider discussions on the benefits and challenges of working with biological data.

The course is aimed at individuals working across biological sciences who have little or no experience in bioinformatics. A limited number of registration bursaries are available to attend this course, visit the website for further details.

Learning outcomes:
Following course completion participants should be able to:

  • Discuss applications of bioinformatics in biological research
  • Browse, search, and retrieve biological data from public repositories
  • Use appropriate bioinformatics tools to explore biological data
  • Explore how biological data can be stored, organised and interconverted

Group projects available:

  • Structural biology and functional prediction
  • De novo assembly and annotation
  • Networks and pathways
  • Phylogenetics
  • Metabolomics
  • Genomic variation project
  • Chemogenomics

Lead instructors
Melissa Burke
European Bioinformatics Institute, Hinxton, UK
Laura Emery European Bioinformatics Institute, Hinxton, UK
Sarah Morgan European Bioinformatics Institute, Hinxton, UK
Bill Pearson University of Virginia, Virginia, USA

Dates for your diary

Bursary deadline: 7 March

Application deadline 14 March

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Epidemiological evaluation of vaccines: efficacy, safety and policy

January 10, 2017 in News, workshop


Epidemiological evaluation of vaccines: efficacy, safety and policy

Course dates: 3 – 14 July 2017

The Epidemiology of a Vaccine

Epidemiological research has become an important tool in assessing vaccine protection. Although there are several courses specialising in vaccinology, there remains a gap in teaching about advanced epidemiological tools for vaccine evaluation. This course fills that gap, providing an in-depth training on current methods used in the evaluation of vaccine efficiency, safety and policy. It aims to address immunisation issues in high, middle and low income countries.

Who should apply?

The course is relevant to public health professionals and field researchers with a strong interest in vaccine efficacy, safety and policy impact. Although this course focuses on human diseases the same concepts apply to animal diseases. The course is intensive and a good command of the English language is essential. A knowledge of computers and a basic knowledge of Word for Windows and Excel is also essential. Participants will be expected to have completed a basic post-graduate epidemiology module or equivalent. They should have an understanding of epidemiological measures of disease frequency (incidence, prevalence), measures of effect (odds ratios, risk ratios), the merits of different study designs (cross-sectional, cohort, case-control, intervention studies) and key concepts and implications of sampling error, bias and confounding.

Course fee

The course fee for 2017 is £2,850.00.

Participants employed by academic/governmental institutions or NGOs from a LMIC (World Bank definition) are offered a 50% reduction on the course fee. This offer is applicable to a maximum of 10 participants on a first come first serve basis based on receipt of payment. Fees will and cover participation in the course, training materials, and incidental tea/coffee and reception, but does not cover travel costs, accommodation and meals. If the course fee is to be paid on the applicant’s behalf, please send a letter from the sponsor to confirm this as soon as possible. Otherwise, the applicant will be held personally responsible for payment.


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