News

Aedes Forecasting Challenge 2019

Posted on by Zach Gajewski

The Centers for Disease Control and Prevention (CDC) Division of Vector-Borne Diseases and the CDC Epidemic Prediction Initiative, in collaboration with the Council of State and Territorial Epidemiologists and the Centers of Excellence in Vector-Borne Diseases, are pleased to announce an open Aedes forecasting challenge for 2019.

Aedes aegypti and Ae. albopictus mosquitoes are the vectors of chikungunya, dengue, yellow fever, and Zika viruses, some of the most important arboviruses impacting human health globally. Because of their potential to transmit these viruses, these mosquitoes are targeted for surveillance and vector control in many areas of the United States. One of the challenges faced by agencies aiming to control these mosquitoes is that their seasonal and geographic range is not precisely known and may be changing.

The Aedes Forecasting Challenge focuses on predicting the seasonal presence of Ae. aegypti and Ae. albopictus in a subset of U.S. counties from multiple states across the country. At least two years of historical data (2017-2018) are provided for each county and forecasts will predict the collection and reporting of each species for each month of 2019, beginning in April*. The challenge is open to anyone and any methodological approach. Further details on how to participate can be found on the Epidemic Prediction Initiative website: https://predict.cdc.gov/.

Any questions can be directed to aedeschallenge@cdc.gov.

Thanks, Michael

Michael A. Johansson

CDC Division of Vector-Borne Diseases, San Juan, PR

Call for VecTraits Workshop participants at VBiTE2019

Posted on by Samraat Pawar

Dear RCN Members,

As part of the upcoming meeting, we will have a Working group on Vector Traits, with the goal of further improving the VecTraits database, which we are developing as a global resource for functional traits in disease vectors. To get an idea about where we (or at least some of us!) are coming from and how we envisage the role of vector Traits in VBD research, please see this preprint.

We are looking for 2-3 more members, who have experience with collecting, managing, or generally meddling around with vector traits, to join the VecTraits workshop team. If you are interested, please email me (s.pawar@imperial.ac.uk).

Exciting times ahead!

Best wishes

Samraat

New skills learned at VectorBite’s training workshop

Posted on by Johanna Ohm

Blog post by Rebecca Brown

This year’s VectorBiTE meeting was held at the Asilomar conference centre by the stunning bays of Monterey, California. In the days ahead of the working group sessions, post-doc and graduate students attended a three-day training workshop on quantitative tools for vector-borne diseases. Led by the charismatic Leah Johnson (Virginia Tech) and Samraat Pawar (Imperial College London), the workshop took the format of lectures followed by guided examples of analysis to gain practical experience, with assistance from instructors Fadoua El Moustaid (Virginia Tech), Marta Shocket (Stanford University) and Matt Watts (Imperial College London).

The training started off with data wrangling and an introduction to the R packages dyplr and tidyr, showing off their aesthetically pleasing summaries! The importance of minimizing editing your raw data file was highlighted (something I am guilty of) thus a key outcome was to record all steps used to process your data with an R script. We learned that models are not only useful to explain relationships in observed data, but models are key for revealing underlying mechanisms driving observed patterns. In the context of vector-borne diseases this is critical for predicting disease outbreaks or assessing the efficacy or suitability of interventions. Model fitting by least squares methods was taught and we worked through an example of fitting a non-linear least squared model to insect trait data. This was followed by teaching on the likelihood based methods: Maximum likelihood estimation and Bayesian analysis, which was new territory for me. We were taken through the steps to fit a model using maximum likelihood by creating a function to return the negative log likelihood to build the likelihood profile based on the data.

Participants of the 2018 VectorBiTE training workshop pose in front of the conference center.

On the final day, our new-learned skills were put to the test with a challenge! Our group tackled understanding mosquito development rate variation with temperature by maximum likelihood estimation. All groups came together at the end to share how they addressed their problem. The previous two days of intensive training paid off because there was a notable improvement in my understanding and ease of using the new techniques. I’m looking forward to applying these tools in my own analysis now. Thank-you VectorBiTE!

———-

Rebecca Brown is a PhD student at the Institute of Biodiversity, Animal Health and Comparative Medicine in Glasgow. She is interested in the impact of land-use change on the transmission of vector-borne diseases. Her current research is on the behaviour and ecology of Anopheles vectors of Plasmodium knowlesi malaria in Malaysian Borneo.

VectorBITE 2018: Meeting Recap

Posted on by Johanna Ohm

The VectorBite 2018 meeting just wrapped up a productive week of training and working group meetings at the Asilomar Conference Center near Monterey, CA. This year’s meeting was split into two parts: a three-day training session for post-docs and graduate students followed by two days of working group meetings.

The training covered an introduction to data management, visualization, and fitting models to data and then focused on specific topics in using data on vectors to fit trait data to mechanistic and statistical models and to fit population dynamics models to data taken from Vectorbyte‘s VecDyn database. The training materials are posted on GitHub.

The working group meetings started off with brief presentations from working group leaders to discuss plans and give an overview of the working group’s interests. Thursday and Friday were then spent hashing out ideas and in some cases, outlining papers to write or experiments to do with group members.

Working group topics included modeling how life history trade-offs in vector traits may impact transmission of vector-borne disease, creating a framework to understand how behavioral manipulation of vectors may similarly impact transmission, characterizing when and where rate summation breaks down for predicting thermal performance curves for different vector traits, discussion of tick questing behavior, whether we can use body size or other traits to create integral projection models for vector populations, and individual-based models for vector populations.

Two days go by fast, especially when we only get to meet once per year! The discussions were stimulating, groups outlined concrete goals and plans for how to complete tasks between now and next year, and we still made time for some walks or runs along the beach and drinks at the Asilomar pub. Here’s to another great #Vbite meeting!

 

Eco-informatics Working Group Meeting – VecDyn

Posted on by Matthew Watts

Post by Matt Watts

Dear All

As you know, I’ve been developing the VecDyn database & and accompanying WebApp. The database will cover vector population and presence/absence data. As part of our Eco-informatics working group meeting this year, we’ll work on finalizing the database. If any of you outside the working group is interested in this, please take a look at the ‘VecDyn Meeting Notes’ below. If you would like to provide any feedback, please do so using our GitHub issue tracker   https://github.com/vectorbite/VectorBiteDataPlatform/issues

VecDyn Meeting Notes

Here are some points that I’d like to cover during the meeting, please read through them carefully.

  1. Validate the final VecDyn data collection templates / backend.

You can access the information here on the GitHub development pages here https://github.com/vectorbite/VectorBiteDataPlatform/blob/master/static/Documentation/VecDyn/VecDynDocs.md

Go to the section ‘Data Collection Specifications’. This is based on the work we did last year, but with a few minor changes and additions.

  • Does this cover all possible scenarios i. e. specific types of study types and studies conducted at varying geographic levels?
  • Note that, we’ll standardise taxonomic and geographical information using the Catalogue of Life taxonomic database and the Global Administrative Unit Layers (GAUL) database (FAO, UN). So, we only require taxon name and a location description in the template.
  • Do you think we should standardise Environmental Descriptions too? See http://environmentontology.org/Browse-EnvO. Note that by standardising something in a database, it means that one can query a specific entity and all related entities

E.g. Terrestrial environment > forest > Temperate broadleaf and mixed forests.

This could be useful for many reasons e.g. tracking environmental changes coupled with population dynamics over time, however, most datasets supplied by governmental authorities do not supply this type of data, so it would probably be limited to academic studies.

  1. We would also like you to test and evaluate the web app and accompanying documentation. Special emphasis should be placed on the procedures and usability.
  • Try to download data, go to the website http://www.vectorbyte.org and try to download a data set, are you able to easily download data etc and are the instructions clear?
  • Look at the data submission instructions under the GitHub development pages under ‘Submitting data’. Are these easy to follow?
  • You can also test the data upload facility. This part of the site will only be accessible by curators, but it would be useful if you could check it.

In this next step we will use a test site, therefore go to

https://vectorbiteonlineplatform.pythonanywhere.com/VecDynTest/default/index

log on with:

Username: test@test.com

Password: test

Go to ‘Adding data to the database’ under the GitHub pages and follow the instructions.

Is this process easy to follow, any bugs?

  1. The next steps regarding VecDyn V1s development will be to improve the front end using the D3.js JavaScript data visualisation library, we will implement features to help users to evaluate and access data visually i.e. plots and maps. Are there any features you would like to see implemented?
  2. Any other comments?

New methods to detect infected mosquitoes

Posted on by Johanna Ohm

Blog post by Jo Ohm

The past year has seen a number of clever new methods to detect infection in mosquito vectors. These new methods which allow for improved detection and monitoring of the time course of infections inside mosquitoes will be powerful tools for exploring many questions central to the research of VectorBiters.  If inventions fuel science and science fuels invention, the future of vector-borne disease research has exciting findings to come from the use of these new tools. Below are some of the latest methods published in the literature which promise to improve our understanding of vector-borne disease transmission:

  1. Detection of virus in mosquitoes using Near Infrared Spectroscopy (NIRS) – NIRS has already been demonstrated to be useful in ageing mosquitoes and identifying between Anopheles species and a recent paper in Science Advances suggests it can be used to detect Zika-infected mosquitoes. Pluses: 18x faster and 110x cheaper than using RT-qPCR for Zika detection ; Minuses: destructive sampling, requires highly sensitive microspectrometer, unknown if it will work with field samples
  2. Malaria sporozoites measured through sugar feeding – A Nature Scientific Reports paper published earlier this month reports a nondestructive way to detect when malaria-infected mosquitoes become infectious by using PCR to detect parasites left behind in sugar-soaked cotton or FTA cards. This method is similar to methods already developed to detect dengue from mosquito sugar water. Pluses: Nondestructive sample, possible to use on individual mosquitoes (?) ; Minuses: Feeding on sugar through FTA cards reduces survival compared to feeding on sugar through cotton
  3. Identifying Aedes species and Wolbachia-infection status with a cellphone – Recently on bioRxiv, Bhadra et al report detection of Wolbachia-infected mosquitoes using an assay that fluoresces in response to the presence of Wolbachia-specific nucleic acids, which should be useful for surveillance purposes following Wolbachia-based mosquito field releases. Pluses: No DNA extractions required, likely to work in field settings ; Minuses: ?
  4. Track mosquitoes using rhodamine b – Mosquito mark-recapture experiments are notoriously difficult and marking with fluorescent dies can have fitness costs on the mosquitoes being marked. A new way to mark mosquitoes using rhodamine b fed through a honey solution was reported to have no detectable fitness costs on marked males. This should be a useful tool for capturing dispersal distance, mating patterns, and age of wild mosquito populations. Pluses: No fitness costs for marking mosquitoes for a mark-recapture experiment and the dye transfers to females through the seminal fluids of marked males ; Minuses: Only demonstrated in males so far, probably works for females (?)

New and exciting technologies have been developed to improve our approach to detecting and monitoring infectious mosquitoes. What other methods are out there? What methods don’t exist yet that would improve our understanding of vectors and vector-borne disease? Have any VectorBiters tried any of these methods yet?

Update from the “FutureBites” Working Group: What traits determine host and parasite range in bird malaria?

Posted on by Johanna Ohm

Blog post by Jenny Dunn

Pathogens infect a wide range of hosts: some are complete specialists, while others infect a diversity of species. Vector-borne diseases also range in the breadth of hosts that are involved in transmission cycles, but little is known about the traits that determine these host ranges. The VectorBite working group, FutureBites, has a subgroup focused on bird malaria. As  are using the avian malaria system, which has unrivaled diversity among parasites infecting vertebrates (~600 mitochondrial cytochrome b lineages of Plasmodium currently described), to identify host and pathogen traits associated with specialism and generalism in both pathogens and hosts.

Progress during the 2017 meeting at Imperial

Over the course of the meeting we spent time developing key questions to address, cleaning databases, and identifying methods to use in downstream analysis.

A main outcome for the meeting was discussing and deciding on three main objectives for the first set of analyses:

  1. Identify patterns of host-parasite-vector specificity through creation of matrices of malaria lineage/host specificity and malaria lineage/vector specificity
  2. Identify traits associated with specialist/generalist parasites, where specialism/generalism is defined either as host richness per se, or as phylogenetic host relatedness
  3. Identify traits associated with specialist/generalist host, where specialism/generalism is defined either as malaria parasite richness per se, or as phylogenetic parasite relatedness

To answer these questions we found and curated several datasets. These include two publicly available databases: MalAvi (which has data on malaria-bird host pairwise associations and malaria-vector pairwise associations) and avian host trait data (http://www.esapubs.org/archive/ecol/E088/096/metadata.htm). Bird host cell characteristics (curated by CF) and vector-host pairwise associations (curated by JD) were curated for this analysis. Phylogenies for bird and malaria species were constructed using maximum likelihood methods from sequence data publicly available.

We identified multiple possible definition of specialism and generalism, and defined both terms for our analyses. With AP’s expertise, we began analysing associations and writing code for further analyses.

Progress following the 2017 meeting

We are making steady progress despite time limitations, and have met over Skype since Imperial. We have been developing our thoughts around what further analyses might be possible with the datasets that already exist, and outlining the datasets along with their limitations before finalizing the analyses we want to address.

Future plans

We plan to continue and complete the analyses described above as time allows, and begin to draft a manuscript (led by CF and JD) for submission in 2018.

We plan to extend these analyses by using similar methods to examine vector-host and vector-parasite pairwise associations and associated traits, once vector trait data are available through the VecTrait database.

 

Group members: Jenny Dunn, Christina Faust, Andrew Park, Ana Rivero, Richard Hall, Sylvain Gandon

Update from the Vector Behavior and Co-infection goup: RCN year 2

Posted on by Fadoua El Moustaid

Blog post by Senay Yitbarek

What has the working group been doing?

The coinfection group is focused on incorporating vector behavior into multiple pathogen dynamics across plants, animals, and human systems. Our group has been working to identify relevant traits from the empirical literature that can help explain coinfection patterns in vector populations. The vector traits of interest have primarily focused on arthropod vectors including mosquitos, ticks, and aphids. For each vector group (~ 5 member/per group), we have appointed a group leader that is responsible for disseminating progress and updates to the general working group body. Furthermore, we have been working on a general theoretical framework that explores the consequences of vector traits for the epidemiology of vector-borne diseases. A separate working group is currently working on a vector borne model.

 

Any progress made?

The vector groups have recently completed a literature survey on relevant traits pertaining to coinfection dynamics. In the aphid group, seasonality and life stages have been found to play a key role in transmission events. For instance, the wingless-aphid morphs transmit at higher rates early in the season. Aphid preferences for infected and uninfected plants can also affect transmission efficiency of multiple viruses. In the tick group, we focused on two major species and found that ticks are likely to acquire pathogens at each life stage resulting in higher coinfection rates in adults. However, it takes ticks up to 3 years to complete a life cycle requiring hosts at each stage without which they die. Depending on the specific pathogen involved, seasonality generally increases transmission risk. However, transmission risk varies considerably with some pathogens showing annual stability while others peak during the summer months. In the mosquito group, we have examined the role of vector competence in transmitting arboviruses. While A. aegypti mosquitos are highly susceptible to multiple pathogens, vector competence shows preferential transmission to vertebrae hosts. For instance, A. aegypti mosquitos are highly permissive and competent for mono-infection and coinfection with Zika and Dengue, including co-transmission. However, Zika grows to higher titers and more efficiently infects hosts. Thus, vector competence in mosquitos is a critical component that needs to be accounted for in coinfection dynamics. With this in mind, the modeling group is developing a general coinfection model that incorporates vector traits. We are currently expanding on a classical vector-borne disease model by incorporating multiple pathogens and vector traits such as density, fecundity, searching efficiency, handling time, and life-stages. We will explore the effects of vector traits on the basic reproduction ratio of pathogens.

 

Future goals of this group?

We plan on submitting a manuscript in the form of a review paper that addresses our current knowledge and challenges in understanding the drivers of vector behavior and their consequences for coinfection dynamics. Several groups leaders from our working group will be attending the Vectorbite conference in Asilomar, California. As part of the workshop training, we hope to utilize the population dynamics database to fit some of the vector parameters to our coinfection model. Following the Vectorbite conference, we will reconvene a meeting on the UC Berkeley campus with several group members.