Location: Arthropod-borne Animal Diseases Research
Project Number: 3020-32000-018-010-R
Project Type: Reimbursable Cooperative Agreement
Start Date: Jul 1, 2019
End Date: Jun 30, 2022
Biting arthropods (mosquitoes, biting flies, and ticks) at best, harm morale and at worst, may transmit harmful pathogens. Protective and preventive equipment or products are only useful if deployed and used correctly. PICTUREE will use historical and current data to create a risk profile picture that can inform planners of what equipment will be needed to fight specific vector-borne risks during deployment. This is proactive treatment and planning rather than the current reactive methods. The output can then be incorporated with other programs or apps created by the DWFP to help planners get the necessary materials to soldiers that need it the most. PICTUREE will summarize diverse data sets (past human and zoonotic case reports, disease vector species or genera distributions, current weather and historic seasonal trends, real-time social media reports, etc.) and turn that information into actionable data. This decision support platform fills an unmet need by summarizing all the resources in one location and outputting it into operational information. Currently, the approach to vector-borne disease is reactionary and retroactive. With the help of PICTUREE, the DoD can move towards a proactive approach to preventing vector-borne diseases before they become of public health importance. Furthermore, this platform will be flexible to accommodate new information sources on the front end, as well as, accommodating the outputs to fit to be developed apps or tools for planners pre-operation, on the ground soldiers in-country, or doctors post-operations.
All current practices are reactionary and follow a retroactive approach to vector-borne diseases and human health protection, but PICTUREE can allow for a more proactive and adaptive approach to PREVENTING those same pathogens from ever becoming of public health interest. PICTUREE will significantly improve pest management for all branches of the Armed Forces and Homeland Security by creating a single up to date snapshot of risk from arthropod-borne pathogens rather than having to sort through various streams of data. The results of this work will ultimately result in the adoption of a new decisions support system open to the public with inputs from local mosquito abatement districts as well as possible inputs from local health departments. Current risk will be evaluated based on three factors: (1) Vector arthropod species distribution (Genus level vector distribution records and niche modeling to infer vector distribution in poorly sampled areas). Species distributions will be mapped based on published records and linked to habitat characteristics. The habitat characteristics can then be used for niche habitat analysis to infer the distributions in un-surveyed areas. Therefore, an area can be classified as reported presence, predicted presence, and unsuitable. These shape files will be updated as new records become available. (2) Past cases based on health records and crowdsourcing (social media). Historical records of past pathogen circulation in the human and animal reservoirs can be used to determine which pathogens may be present in an area. However, vector species distributions can change, along with the pathogens they carry. To account for this variability, crowdsourced data will also be used to update the species and pathogen distribution maps. Current suspected cases, but not confirmed, pathogen transmission based on social media posts and search terms can be used to detect pathogen emergence, re-emergence, or ongoing outbreaks. (3) Estimated vector abundance based on weather (rainfall and temperature) and seasonal data. Abundance and distribution of disease vectors are driven by weather conditions. Monitoring current weather and comparing it to past weather patterns during outbreaks will help signal elevated risk. This reduces the need to survey for disease vectors year-round, which may not be possible in some locations globally. The model will be validated and updated when arthropod survey data is available. The innovation of PICTUREE is the risk estimation which comes from the combined use of multiple data streams to estimate current pathogen transmission. Filtering methods are needed to reduce noise from the various data sources such as social media reports or to weight certain sources of data stronger than others based on the confidence of accurate reporting. Similarly, the model smoothing methods will fill gaps in incomplete data sets by interpolating geographic and temporal gaps in disparate data sources. Ultimately, the output of the cleaned data will result in three levels of risk: high, medium, and low for a given pathogen in a geographic area.