The Centers for Disease Control and Prevention recently released a report showing that diseases from vectors, such as mosquitoes, ticks, and fleas, have tripled since 2004 in the U.S.

The World Health Organization is also tracking the global spread and increase of vector-borne diseases. Clearly, there is a need for researchers to connect and develop tools to address this problem.

Leah R. Johnson, a Virginia Tech researcher, in collaboration with colleagues at Imperial College London, Stanford, and Penn State, created the Vector Behavior in Transmission Ecology Research Coordination Network, or VectorBiTE RCN, to bring together scientists studying vector-borne infections with diverse perspectives from all over the globe. The VectorBiTE network encourages the collection and consolidation of key data and the development of analytical tools to better understand the impact of behavior of vectors, such as mosquitoes and ticks, on disease transmission.

“We are bringing together specialists in vector behavioral ecology, epidemiology, theoretical ecology, mathematics, and statistics to promote an open exchange of ideas, data, and tools to tackle this problem,” said Johnson, an assistant professor of statistics in the College of Science at Virginia Tech. Johnson’s interests are in statistical and mathematical biology, ecology, and epidemiology,  and she is an affiliate of computational modeling and data analytics, the Department of Biological Sciences,  and the Global Change Center, housed in the  Fralin Life Science Institute.

VectorBiTE RCN is a collaboration created in 2015 and led by Leah Johnson and Lauren Cator, a behavioral ecologist at Imperial College London. The RCN is jointly funded by a National Institutes of Health grant in the United States and a Biotechnology and Biological Sciences Resource Council grant in the United Kingdom. The leadership team also includes Samraat Pawar, a senior lecturer at Imperial College London; Erin Mordecai, an assistant professor in biology at Stanford University; and Peter Hudson, an ecologist and biologist at Penn State University.

VectorBiTE RCN currently has more than 300 members from around the globe. The network facilitates the development of new models and their integration with empirical data using quantitative methods to better understand the processes that drive transmission patterns in vector-borne diseases.

One of the goals of the VectorBiTE network is to train young researchers to apply these new tools and models as they are developed. Fadoua El Moustaid and Zach Gajewski, two graduate students in the Department of Biological Sciences and Interfaces of Global Change Fellows in Johnson’s lab, are helping to facilitate this training by organizing annual meetings, maintaining the VectorBiTE website, keeping members updated through social media, and participating in working groups and virtual meetings throughout the year.

To this end, the third annual VectorBiTE meeting wrapped up a week of training and working group meetings at the Asilomar Conference Center near Monterey, California, in June. This year’s meeting was split into two parts: a three-day training session for post-docs and graduate students on mathematical and statistical methods as well as an introduction to the Vectorbyte Population Dynamics database, followed by two days of working group meetings.

“We brought in graduate students and post-docs from all over the world. We had students from Australia, Africa, the U.S., and the U.K. participate in the training, and VectorBiTE RCN provided the funding for these individuals to participate,” said El Moustaid, who taught a workshop on statistical modeling.   

Researchers at meetings
Training sessions at the third annual VectorBiTE meeting near Monterey, California.

Training covered an introduction to data management, visualization, and fitting models to data. It then focused on specific topics in using data on traits of insect vectors to fit  mechanistic and statistical trait models and to fit population dynamics models to data taken from Vectorbyte’s VecDyn database.

Working group topics included modeling how life history trade-offs in vector traits may impact transmission of vector-borne disease, creating a framework for understanding how behavioral manipulation of vectors may similarly impact transmission, discussion of tick questing behavior, and individual-based models for vector populations.

“What’s impressed me the most is how VectorBiTE has brought empiricists and theoretical researchers together. They think in such different ways, so an exchange of ideas is powerful. In the past, however, there hasn’t been enough communication between these different groups,” said Gajewski.

The goal of the VectorBiTE RCN is to create this collaborative network of researchers to address and tackle the spread of vector-borne diseases. Through this network, some working groups have already published papers, researchers are collaborating on new projects, and students have found graduate student and post-doctoral positions. Researchers can get involved in the VectorBiTE RCN by applying through the VectorBiTE website

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