Real-time Geospatial Mapping and Outbreak Prediction Platform

We are developing handheld devices to perform on-site rapid pathogen detection and provide real-time test-data aggregation for outbreak surveillance 

Dr. Katherine Clayton, Co-founder & CEO, OmniVis Inc.

Existing pathogen detection solutions heavily rely on polymerase chain reaction (PCR) based approaches, aptly described as the “gold-standard”, due to their ability to detect the genetic information of the pathogens, even in extremely small quantities. 

However, several days can elapse between requesting a test, receiving a result, and acting on the diagnosis, leaving a window in which infection may spread. In an outbreak or health emergency that warrants quick large-scale testing, PCR based tests can be too slow to contain the spread. 

Recent experiences from COVID-19 outbreak (2020-2021) and earlier cholera outbreaks in Yemen (2016-2021), Mozambique (2019), and Haiti (2010) suggest that in addition to reliable rapid-detection, faster dissemination of the test information is equally important to better identify, and respond, to global health emergencies.

At OmniVis, we provide a solution that addresses both these challenges simultaneously. We are developing handheld devices to perform on-site, rapid-pathogen-testing (under 30 minutes), and provide real-time aggregation of the test-results (over-the-web) for outbreak surveillance. 

We believe that our solution will enable public health professionals and government agencies to take a proactive, rather than reactive, approach for detecting environmental pathogens, and designing an evidence-driven response plan. 

OmniVis performs user-centered design with diverse members to co-create their rapid detection technology. Everything we design includes user feedback to make a product that is easily adopted into their existing workflows by being intuitive.

OmniVis’ customers are humanitarian aid organizations, principal investigators within water testing facilities, and community leaders in regions where cholera is present. Our data generation not only enables aid organizations to respond more quickly to the presence of cholera, but also provides quantitative information for performance and budget justification.  

The users of our device are the field workers who would test a water source for cholera. Upon receiving a result, a field worker would notify the community affected by cholera through warning signage and grassroots approaches. Local organizations, once notified, would provide water filters, chlorine treatments, or warn the community to boil their water. The end beneficiaries of the OmniVis technology are the community members that may be affected by or vulnerable to cholera.

For COVID-19 we are addressing healthcare workers in mobile clinics who focus on agricultural areas and to be spun out for further use in lower infrastructure settings.

Development of a comprehensive database for cholera 

Unlike COVID-19, a comprehensive point-in-time surveillance data for cholera (that can shed light on the seasonal nature of the outbreak) is not easily available to epidemiologist and data-scientists. Further, extraction/collection of data requires text-mining publicly-available weekly epidemiological reports, which are published in Portable Document Format (PDF). Also, data reporting frequency, accessibility and content differ from one-source to another. WHO reports cholera data on a yearly basis, which is very coarse to build models that can incorporate seasonal nature of the cholera outbreaks. ProMED, which is a collection of articles submitted by different sources, and contains more granular information, does not have a consistent structure.  

We will develop a data pipeline to collect, clean and combine cholera data from different sources (WHO, ProMED, WorldBank, weekly epidemiological reports, etc.,) and build a comprehensive database that can be used to build data-driven models for forecasting cholera outbreaks. 

The database will be made available publicly, including the option to download in multiple easy-to-consume formats.

OmniVis initially focused on tailoring our device to be used by community health workers, NGO field workers, and water testing laboratories. Diseases like cholera currently take a week to detect in water, using laboratory techniques that require infrastructure and years of training. We made a portable device for a user to take to the water source to detect cholera in water in under 30 minutes.

Additionally, OmniVis translated the device for healthcare workers to detect COVID-19 in patient samples. With an affordable price point, portability, and rapid results, we can let patients know about COVID-19 in a single appointment time. We believe with our model that we will allow for more COVID-19 testing to be conducted, allowing patients to know about their results earlier and lower cases. 

Links for COVID-19 testing: 

https://www.nationalgeographic...

https://abcnews.go.com/Politic...

OmniVis views scaling impact in four major ways:

1. Provide more tests to organizations to diagnose more patients than they current can.
2. Reach more countries and communities with more devices and testing.
3. Enter new disease markets to diagnose more diseases early, particularly with diseases that exacerbate inequity (tuberculosis, cholera, COVID-19, malaria, HIV).
4. Use data driven approaches to begin predicting outbreaks.

In the next 1 year:

With (1), providing more tests, OmniVis looks to lock in further funding from grants and venture capital to increase our manufacturing pipeline to maintain a low cost, competitive platform while providing enough tests to users. With more capital, we can scale manufacturing and provide cost competitive options. With (2) we are starting in the USA, Kenya, Bangladesh, and Haiti in the next 1 year. With (3) we are starting with detection of cholera and COVID-19. With (4) we are building out a predictive model for cholera and COVID-19 and working with mobile network operators to disseminate outbreak data to communities.

In 3 years:

We plan to have our HIV and malaria solutions on the market (3) with corresponding outbreak prediction platforms (4). We will also be reaching new countries for cholera testing (1 & 2).

OmniVis wants to change the way that cholera detection was performed to make progress toward disease eradication. We believe that by detecting a case of cholera in a water source can impact numerous lives, from those who directly access the water source and the families that also use the same water (# of persons accessing safe water)

We are also considering the impact of detecting cholera and COVID-19, early (total # of lives improved for COVID-19 and cholera). 

Additionally, we use a log frame indicator for all of our field testing to measure solution progress and impact that align with our Theory of Change. For "outcomes" we measure:

• Increased number of sources tested per month
• Improved access of safe water
• Improved communication between field workers/testing organizations and communities
• Improved approaches to outbreak response

For "outputs" we measure:

• Development of a usable testing platform that field workers can use
• Improve testing science to be more accurate than current portable testing approaches
• Increased speed of testing that can be performed in a community
• Accurate recording of all relevant outbreak information at positive sample site (GPS, time, etc.)

As a company, the two barriers we need to overcome in the next year (and next 3 years) are in manufacturing and international trade. Though experienced in prototyping devices, we are exploring solutions and forming strategy for scaling manufacturing to larger quantities. We have reached out to several product development consultancies to better understand the manufacturing challenges we face, and which manufacturing option is our best option at each stage of growth. Without team members physically located in our target regions which have variable and sometime volatile political and economic conditions, we expect that international trade will pose a steep learning curve. To prepare ourselves for these challenges, we are looking for advisors and board members with experiences in these fields to join our team and carefully select local partnerships that have the clout and reputation to pave the way for us. 

• Purdue University: We have a sub award grant for a collaboration with Purdue for HIV viral load testing and cholera testing.
• icddr,b: We worked previously with icddr,b for field testing on 2 occasions and have a grant to work with the organization for further field testing.
• Code for Africa: We have a grant to work with the organization for further field testing.

Before the COVID-19 pandemic, OmniVis was building a cholera detection solution with a data-driven approach to eliminate outbreaks by early detection. When the pandemic hit, we translated our technology to tackle COVID-19. The Trinity Challenge encompasses the same vision that OmniVis has, that collaboration in the early identification and response of infectious diseases can lead to more rapid recovery. With the alignment of our company goals with this Challenge, we can provide the diagnostic device, data, and prediction models as one of the many elements needed to overcome outbreaks. 

• ProMED: OmniVis would like to partner with ProMED to utilize their reporting system for 1) disseminating our diagnostic-test driven insights and outbreak forecasts around the world as quickly as possible and 2) consuming the latest news/information/data for improving our models.  
• Johns Hopkins University and their COVID-19 dashboard: We believe that OmniVis and JHU could partner and learn from one another to use current data to predict future outbreaks.
• CDC: OmniVis would like to work with a major player like the CDC to understand and work together on rapid outbreak response after collecting any diagnostic data.
• Higher Life Foundation - We would like to partner with Higher Life Foundation with their focus on Cholera Response/Roadmap to elimination. We believe that our collaborative strengths can help strengthen cholera prediction models toward disease elimination.