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PLOS Disease Forecasting & Surveillance Channel – Meet the Editors

Don Olson, Nick Reich, Elaine Nsoesie, Cécile Viboud and Michael Johansson announce the launch of the PLOS Disease Forecasting & Surveillance Channel.


Today sees the launch of the PLOS Disease Forecasting & Surveillance Channel. Channels are resources for research communities: a single destination to discover and explore content from PLOS journals as well as the broader literature, supplemented by commentary, blogs, news and more to keep readers up to date with the latest research in their field.

The goal of modern electronic disease surveillance is to provide access to data on population public health trends, with a focus on increasing both the amount of data and the speed with which the data are disseminated and analysed. This in turn provides the opportunity for rapid detection, characterization, and forecasting of disease threats or conditions that can be used to support public health decision making.

The PLOS Disease Forecasting & Surveillance Channel will include research papers and online commentary related to new methods, findings, or datasets in the fields of disease forecasting and electronic disease surveillance, with a specific focus on work that has relevance to public health policy.

The new channel will highlight current research that meets some or all of the following criteria:

  • Describes or uses a novel data source to inform disease surveillance or forecasting activities
  • Integrates multiple distinct data sources to inform disease surveillance or forecasting activities
  • Develops new surveillance or forecasting methodology
  • Evaluates surveillance or forecasting methodologies on real or simulated data, with a focus on robust, out-of-sample validation
  • Presents original research using surveillance data whose findings have direct implications for public health policy
  • Contributes to the rapid detection, characterization, and forecasting of disease threats

The PLOS Disease Forecasting & Surveillance Channel was developed with the Channel Editors, who will be responsible for curating the content that goes into the Channel.

Meet the Editors

Don Olson*:  I am an epidemiologist and research scientist who has worked on the development and implementation of disease surveillance systems with the New York City Department of Health and Mental Hygiene and the International Society for Disease Surveillance since 2004. My research interests range from the study of past pandemics to the creation of next generation electronic disease surveillance systems, with a particular interest in the development of health monitoring systems that can inform forecasting and modeling efforts.

 

 

Nick Reich: I am an Associate Professor of Biostatistics at the UMass-Amherst School of Public Health and Health Sciences. My research focuses on developing statistical methods for time-series forecasting, with a particular focus on ensemble methods and applications in infectious disease. I work collaboratively with public health officials from across the world, including the Ministry of Public Health in Thailand, the US Centers for Disease Control and Prevention, and the New York City Department of Health and Mental Hygiene.

 

 

 

Elaine Nsoesie: I am an Assistant Professor at the Institute for Health Metrics and Evaluation and the Department of Global Health at the University of Washington in Seattle, USA.  I am also an Adjunct Assistant Professor in the Department of Biomedical Informatics and Medical Education. My work is primarily in the field of digital epidemiology and global health. I evaluate the use of digital data and technology for disease surveillance and forecasting. Specifically, my research has focused on the surveillance of influenza-like illnesses, foodborne outbreaks and vector-borne diseases such as, chikungunya and Zika. Currently, I am developing methods that combine recent advances in machine learning algorithms with digital data for global health applications. I also write journalistic articles about the use of digital data for public health. You can find me on Twitter @ensoesie.

 

Michael Johansson^: I am a Biologist at the Centers for Disease Control and Prevention Dengue Branch in San Juan, Puerto Rico. My focuses on applying statistical and mathematical modeling to improve surveillance, prevention, and control of arboviral diseases including chikungunya, dengue, yellow fever, and Zika. I also work on broader initiatives with academic and governmental partners to improve the use of quantitative models to support decision making related to infectious disease outbreaks. I am also a founder of the nonprofit Outbreak Science, a Deputy Editor of PLOS Neglected Tropical Diseases, and a member of the International Health Regulations Roster of Experts.

 

 

Cécile Viboud+: I am an epidemiologist based at the Fogarty International Center of the  US National Institutes of Health in Bethesda MD. I research the transmission dynamics of acute viral infections, working at the interface of public health and computational modeling, and influenza is my favorite disease system. I’ve also recently became interested in the transmission dynamics of zoonotic infections, and the potential use of Big Data for infectious disease surveillance and forecast.

 

 

 


Check out the PLOS Disease Forecasting and Surveillance Channel – channels.plos.org/dfs

* Donald Olson is serving as a Channel Editor in a personal capacity. The views expressed are his own and do not necessarily represent the views of the New York City Department of Health and Mental Hygiene.

^ Michael Johansson is serving as a Channel Editor in a personal capacity. The views expressed are his own and do not necessarily represent the views of the Centers for Disease Control and Prevention or the United States Government.

+ Cécile Viboud is serving as a Channel Editor in a personal capacity. The views expressed are her own and do not necessarily represent the views of the US National Institutes of Health or the United States Government.


Image Credit: a composite image created by PLOS using an image created by Martin Grandjean http://www.martingrandjean.ch/connected-world-air-traffic-network/ CC BY

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