Task
Coastal cities are at an increased risk of waterborne and vector-borne disease following natural hazards such as typhoons and hurricanes, which are expected to increase in both frequency and severity due to climate change. Assessing the environmental drivers of risk in near real-time presents a critical monitoring challenge in a resource-limited context. Our solution is a tip-and-cue system that utilizes drones to validate satellite-based detection of water-based indicators of infectious disease following natural disasters. If scaled globally, our core technology can fundamentally change the way that cities prioritize resources in post-disaster settings. Our integrated remote monitoring system will quickly identify high priority sites for testing and mitigation of waterborne and vector-borne infectious diseases, reducing the risk of large outbreaks that can last beyond the initial hazard event.
Cities in coastal regions are increasingly vulnerable to natural hazards such as typhoons, hurricanes and tropical storms, which are predicted to become both more severe and more frequent due to climate change. These storms bring flooding and destruction to already vulnerable communities causing crowding and disrupting health systems, increasing the risk of both waterborne and vector-borne disease outbreaks. After Hurricane Maria Puerto Rico experienced a spike in cases of Leptospirosis, Zika, Chikungunya and Dengue. In resource constrained post-disaster circumstances, real-time surveillance of the environmental drivers of such diseases is nearly impossible using existing methods. Responders cannot make efficient decisions about the best ways to deploy their resources and prevent further suffering without the information that such surveillance would provide. Task solves that problem. We seek to reduce the time and cost to survey broad regions for water-based indicators of infectious disease in real time following natural hazard events.
We are currently prototyping with hardware and software integration in our home base of Columbus, Ohio. However, we are in contact with partner organizations in San Juan, Puerto Rico and plan a pilot project starting in the fall. We are implementing the lean innovation methodology with a targeted group of stakeholders across government to understand their needs and utilize user input to tailor our solution. We believe that improved resource targeting can (1) reduce direct disease burden for urban populations in coastal communities; (2) reduce burden on healthcare system; (3) improve long-term health stability by reducing the likelihood that a natural disaster will initiate endemicity of infectious diseases.
Task is a platform that enables automated validation of satellite-based indicators of infectious disease risk with unmanned aerial systems (UAS).
Satellite-based monitoring of post-disaster settings can identify critical indicators of waterborne and vector-borne disease reservoirs. Monitoring with moderate resolution satellite systems facilitates broad spatial and temporal coverage of post-disaster areas at low cost. However, this information must be validated by higher resolution systems to be actionable in the public health setting. To do this, we have created TASK, a platform for the automated validation of satellite-based indicators of infectious disease risk with unmanned aerial systems (UAS). TASK dispatches UAS to sites that are positively identified by satellite-based change detection algorithms, and then either confirms or rejects these alerts based on higher resolution samples. This increases confidence in remote monitoring of post-disaster locations, and decreases the number of high priority sites for testing and mitigation.
This platform supports existing surveillance systems in limited resource urban environments and reduces the time and cost associated with identifying risk sites of highest priority.
- Prevent infectious disease outbreaks and vector-borne illnesses
- Enable equitable access to affordable and effective health services
- Prototype
- New technology
Remote monitoring of environmental drivers of infectious diseases, particularly in post-disaster settings, has shown significant promise due to its low cost and high geographic coverage. However, existing programs are only able to validate their findings on an ad hoc basis, if at all. Our solution integrates two scales of remote monitoring (satellite and drone) in a seamless validation process to provide both the broad coverage of space-based assets and the accuracy of UAS. This presents an opportunity to fundamentally change the way risk is assessed in the short-term following a natural hazard event in coastal cities like San Juan. Task presents alerts in a contextualized, user-friendly application interface that is intended for use in the decision-making environment of post-disaster situations.
The core technology of our solution is an automated tasking process that integrates satellite-based change detection models with drone validation. Thus, we utilize both space-based and drone imagery to characterize waterborne and vector-borne disease indicators in near real-time. Using satellite-based systems to automatically task drone systems for follow-up monitoring is a novel concept and our key technical advancement is the smooth integration of these systems into a single decision-support platform.
- Machine Learning
- Internet of Things
In post-disaster settings, coastal cities must prioritize the deployment of limited resources to highest priority areas. However, the risk of waterborne and vector-borne disease is dynamic and dependent upon environmental conditions that can change rapidly. Remote monitoring of well-established indicators of infectious disease with a satellite-based system offers broad coverage at a low cost. We integrate this system with a higher resolution drone-based validation process to increase confidence in alerts and to support actionable mitigation targeting.
- Peri-Urban Residents
- Urban Residents
- Very Poor/Poor
- Low-Income
- Minorities/Previously Excluded Populations
- United States
- United States
We are currently prototyping with hardware and software integration at the Aerospace Research Center in our home base of Columbus, Ohio. We plan to pilot in San Juan in the upcoming year, and within five years offer a functionally operational platform in multiple coastal cities that face the threat of natural hazards.
In the next year, our goal is to transition from prototype testing to deployment in the context of San Juan. We also plan to use the SOLVE opportunity to identify additional cities that could benefit from our technology, as well as to identify complementary technologies in the health surveillance space. In five years, we intend to be implementing our platform in multiple cities, reducing the time and cost associated with post-disaster health monitoring for local and regional governments that collectively affect millions of lives.
The UAV regulatory environment differs country to country. Currently, the United States has among the most strict regulatory environment, meaning that drones cannot be operated beyond the line of sight of a human operator or spotter. We have been in contact with organizations such as Direct Relief that have already been navigating this regulatory environment for applications in the health space in the context of Puerto Rico, and we are confident we can find both short-term and long-term solutions to implement our technology.
In the United States and its territories, we plan to implement pilot projects with a small team of spotters to circumnavigate beyond line-of-sight regulations. This proof of concept will serve as the foundation of our application to the FAA for a use-case exemption to the beyond line-of-sight regulation, the process of which we have already begun. Depending on the country of deployment, similar processes may be required, though beginning in the strict regulatory environment of the United States will pave the way for deployment in more flexible environments moving forward.
- Other e.g. part of a larger organization (please explain below)
Task is a project of the Battelle Center for Science, Engineering and Public Policy at the Ohio State University.
The mission of Battelle Center for Science, Engineering and Public Policy is to create a translational bridge between the technology development community and the public policy arena. The Battelle Center is housed in the John Glenn College of Public Affairs, which provides consistent, direct contact with a breadth of government and state agencies.
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We bring a breadth of experience to this project across the full spectrum of our technology landscape, including health surveillance, aerospace engineering and drone technology, and computer science and automation. This includes multiple faculty members at Ohio State University. We are also proud of the local context of our team's geodesist, who has spent most of his life living and working in Puerto Rico. In addition, we offer as team members both an alumnus and an instructor of the DoD-sponsored Hacking for Defense course at Ohio State, which teaches the lean innovation methodology in the national security context.
At Ohio State, we are working with the the John Glenn College of Public Affairs, the College of Engineering, the Aerospace Research Center and the College of Food, Agricultural and Environmental Sciences. We have validated our technology and problem statement with multiple US government agencies and a breadth of nonprofit organizations. We are currently navigating the local government landscape in Puerto Rico to best understand how to implement our pilot project.
Our key beneficiaries are the local and regional government organizations responsible for deployment of resources in post-disaster settings. The current framework for these organizational relationships is the Incident Management System, a standardized mechanism for strategic decision-making in emergency situations. In the United States, an Emergency Operations Center (EOC) is established in the wake of a natural hazard, which provides a single, temporary point of command for resource deployment. The EOC houses all relevant agencies, which for us include the state health department and the US CDC. These organizations frequently collaborate with nonprofit organizations such as Direct Relief and the Red Cross, which are also seeking to optimize resource deployment in post-disaster settings. We plan for our technology platform to be adopted in the Emergency Operations Center as a risk prioritization and decision-making tool, and from here it will benefit governmental health organizations that take action based on this information, saving them time and money. We plan to implement a subscription model, in which government organizations and aid organizations pay a flat fee for our end-to-end management of the technology platform. In limited resource governments, we believe that aid organizations will pay the majority of the fee, with use agreements for the service to be offered to local governments.
Ultimately, we will positively affect local communities that can receive testing and mitigation of waterborne disease in areas of greatest risk much faster than offered by the current paradigm.
We are beginning with limited startup capital from Battelle Center, and plan to continue in pilot development with philanthropic fundraising. In the long run, we plan to sustain our activities by selling a subscription model to government and aid organizations.
We are applying to Solve to (1) champion our project, socializing it with a broad network of potential end-users and complementary technology providers; (2) receive feedback and improvement from a community of like-minded peers; (3) obtain the interest of potential funders who can support us through pilot implementation.
- Business model
- Distribution
- Funding and revenue model
- Legal
- Monitoring and evaluation
We have found great benefit from our early conversations with organizations such as Direct Relief, and we hope to continue to learn about how we can improve our technology from the front-line organizations that will be implementing it.
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Research scientist
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Graduate Research Associate
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Graduate Research Associate