News

Funded Research Exchanges

We are pleased to announce funding for research exchanges for those working on behavioral and ecological aspects of vector borne diseases. The aim of these awards is to allow VectorBiTE network members the opportunity to spend time working intensively away from their home institutions, within a group with complementary expertise, to pursue VBiTE related research. 

In the spirit of the RCN, example exchanges could include learning about a different vector system, exchange between a theoretically and empirically based group, or a gathering of researchers to identify data standards or consolidate data for use. Exchanges must be completed before December 15, 2022. 

To apply please send your CV, Letter of support from host, a <2000 word description of the research, requirement for exchange (why can’t you do this virtually?), timeline and specific activities associated with the exchange, and a budget. 

The total budget should be no more than $5,000 USD and can cover economy travel, lodging, and subsistence. Due to the nature of the funding we can only support travel for US-based persons (of any nationality), usually to travel within the United States, although in some cases we may be able to fund limited international travel. 

Please send application materials to vectorbitercn@gmail.com. Applications for funding are rolling and will be reviewed as they come in. The last review will take place in November 2022, if funds are still available. Note that the total number of awards will be based on funding availability and demand, so we recommend applying early.

Board Meeting and Updated Operating Principles and Procedures

The VectorBiTE Network Steering Committee and Advisory Board had it’s first meeting from 3-4 August 2022. During the meeting we began formulating long term plans for the Network and updated our OPP document. We are posting the OPP and soliciting feedback before the next meeting of the Steering Committee, scheduled for mid-September. If you have comments or feedback on the OPP document, please submit those through the VectorBiTE gmail account OR e-mail one of the steering committee members (see below).

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Current Steering Committee

  • Leah Johnson (Chair)
  • Lauren Cator (Chair Elect)
  • Nicole Gottdenker
  • Peter Hudson
  • Cynthia Lord
  • Samraat Pawar
  • Catherine Lippi (trainee representative)

Current Advisory Board

  • Mike Boots
  • Shannon LaDeau
  • Sunny Power
  • Sadie Ryan
  • Sam Rund
  • Matt Thomas

New VectorBiTE Operating Principals and Procedures

The current VBiTE board and steering committee have developed and adopted new operating principles and procedures (OPP) for the network. This document will be used to guide the transition of the RCN into the future VBiTE network. Please take a moment and read the OPP document, attached below. Once you read over the document and still want to receive email updates from VBiTE and participate in the community please fill out the following surveyPlease note that only those that fill out the survey and agree to adhere to the OPP will continue to get emails from VBiTE.

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VectorBiTE 2021

Hello VectorBiTE members,

We are planning to hold virtual events this summer. These will include a symposium focusing on VectorBiTE related research topics and a training workshop. We are holding the symposium on July 8-9th and training on July 28-30th. Please apply on google forms for the symposium and for the training.

Similar to previous years we will be providing training in:

  1. Introduction VectorByte databases
  2. Data Wrangling
  3. Model Fitting Introduction
  4. Time Series
  5. Likelihoods
  6. Bayesian on Traits 
  7. Bayesian on Time Series

We hope you are all well and we look forward to seeing you again!

Best,

VectorBiTE Team

VBiTE 2020 Update

Due to the current circumstances of COVID-19, we will not be meeting before this year’s Ecological Society of America meeting. We will postpone an in-person meet up until spring 2021. We will provide more details when we have them. In the meantime, we are looking into providing some small virtual meetings. We will be sending out an email soon about what these meetings will entail.

VectorBiTE 2019 Survey

Please remember to take the VectorBiTE 2019 Survey. This survey is for all VectorBiTE members, whether you participated in the last meeting or not. We are looking for feedback from members about how VectorBiTE should move forward. The survey should only take 5-10 minutes to fill out and would help us figure out the future of VectorBiTE.

The survey can be found here.

VectorBiTE 2019: Meeting Recap

VectorBiTE 2019 just finished at Fondazione Edmund Mach in Trento, Italy! Just like last year, the meeting was split into two parts; training and then a general working group meeting. The first three days were the training session where graduate students and postdocs came to advance their data management and statistical skill set. The last two and half days were set aside for working groups to meet and continue making progress on their research projects.

The training session started off with general linear and non-linear models and moved on to time series and eventually fitting Bayesian models. The trainees worked extremely hard during the first two days to learn a bunch of new skills and then on the third day they applied what they had learned to a group project on either their own data sets and data from Vectorbyte’s VecDyn or VecTraits database. The training material can be found here.

On Thursday morning, all the VectorBiTE 2019 participants met up and the training participants shared what they had been working on. The working group leaders then gave a brief overview of what each working group has been doing and what they hope to accomplish at the meeting. Trainees were able to join working groups and apply their new skill sets to help the working groups. Check out the working group one page summaries to find out about what each group accomplished in this year’s meeting!

During the working group portion of the meeting, we also got a video presentation from E-STAR, on mosquito prevention in Italy. The group showed us one of their videos that they use in their elementary school outreach events. The video focused on Ms. Mosquito and an elementary school child learning about how to prevent Ms. Mosquito from permanently moving to Trento, Italy. The video shared mosquito prevention methods that students can use and teach their parents.

This year’s meeting was at a stunning location filled with great scientific discussions. We are looking forward to seeing the outcomes of each working group from this year’s meeting!

The cost of a vector borne disease

Post by: Eli Fenichel

What is the cost of a vector borne disease? It is not simply the sum of medical bills from treatment. People incur costs to avoid getting sick. Economic theory says that on the margin people are expected to equalize there incremental expenditures or forgone benefits on avoidance with their expected incremental costs of illness. In a 2018 study, published in Environmental and Resource Economics, we estimate the behavioral risk avoidance response to Lyme Disease in the Northeast United States, and use that to estimate the avoidance costs. We find that the average individual in the average Northeast US county spends nearly nine and half fewer hours outdoors per year. For reference the average outdoor activity lasts 73 minutes. This amounts to the average individual taking nearly 8 fewer trips outside per year or just over one billion lost trips. These trips can be valued at between $2.74 to $4.91 per trip – these are largely trips to things like local parks. All told this means that the cost of defensive actions to avoid Lyme Disease are on the order of $2.8 billion to $5.0 billion a year (we used 2006 dollars for our analysis). This suggests that if Lyme could be eradicated permanently and with perfect certainty, then that would merit an expenditure of up to $40 billion, using the US Office and Management’s 7% discount rate.

There are challenges to doing a study like this. First, there is getting the data. Second, is addressing bias, because behavior itself likely effects Lyme cases. We use two primary sources of data, supplemented with a few others. The core behavioral data comes from the American Time Use Survey (ATUS), which is collected and made public by the US Bureau of Labor Statistics. The ATUS asks a stratified random sample of the Current Population Survey to keep a minute-by-minute diary of all activities and locations of activities for a 24 hour period. The survey has been run every day since January 1, 2003. However, in our study we only use the first decade of observations. The survey tracks nearly 400 activity codes and 25 location codes (types of locations not exact coordinates). The data can be aggregated to the county level, though in many locations the data are more granular. We merge these data with year-by-county Lyme Disease case reports from the CDC. Additionally, we use some weather data and geographic data.

There are potential concerns with the data and with the process of simply regressing time spent outside on Lyme Disease cases. First, there could be challenges with the ATUS data, but BLS puts a lot of effort into the randomization and recruiting process, and these data are used in the context of many important economic and policy decisions. Second, there is concern that reporting of Lyme Disease may go down as Lyme becomes endemic. If this is the case, then the behavioral response we measure should be a lower bound and underestimate the cost. Regressing Lyme Disease cases on time spent outside using an ordinary least squares regression is likely biased because time spent outside is an important input into contracting Lyme. This sort of feedback problem is common in economic statistics, and economists and econometricians have developed a number of regression techniques to address these problems. Standard ordinary least squares regressions finds no effect of Lyme Disease cases on time spent outdoors, our econometric regression that accounts for the feedback (an Arellano-Bond estimator) finds a strong significant reduction in time spent outdoors that attenuates with increasing Lyme Disease cases in a county. Our estimates condition on population, minimum humidity, minimum temperature, precipitation, percent wilderness, percent city parks, maximum humidity, and maximum temperature. Overall, the estimate of the marginal effect of Lyme Disease cases on time spent outdoors is highly robust to model specification.

We believe that most researchers studying vector borne disease do so because they are concerned about social outcomes and public health. We are too. Yet, public health is not an end to itself, it is an important input into broader wellbeing. Quantifying the tradeoffs people make around avoiding getting sick can provide a credible lower bound to the cost of a vector borne disease and help policy makers better assess the tradeoffs involved in reducing vector borne infections. Increasingly, available data on human behavior makes these analyses possible. We encourage vector disease scientists to work with economists to further place the important science of vector borne pathogens in a social context.