Rapid COVID-19 testing in Rural Areas
We believe that countries need accurate and immediate testing data from their rural areas to better contain the devastating effects of this pandemic. Armed with these results (which we can show on a daily basis) these countries will be able to make data-driven decisions around:
1. Outbreak policy and reactions (healthcare and resource deployment)
2. Economic policy (restrictions eased or increased, travel and trade decisions)
3. Workforce policy (immunity passes for essential workers that can assist rural communities)
Enveritas combines machine learning with field survey capability. Our platform allows randomized tests at scale in rural areas of developing countries with results received and analyzed the same day. Originally developed for sustainability auditing, this platform can be utilized to conduct antibody testing at scale (10,000 tests per week in each country) at low cost, high reliability, and rapid deployment speed. We could be operating in the targeted countries within 2 weeks.
Antibody tests permit detection up to several years after infection, can be administered at home, with results within 15 minutes. However, these tests have not been available until the past few weeks. There will be high demand for these tests as they come online with military forces, first responders and hospital staff likely to have first access, followed by consumers, public sector staff, and corporations with demand that might be expected to number in the tens of millions. If antibody testing could be done randomly at national scale on a weekly basis, this information would be invaluable in aiding difficult policy decisions. It would also overcome current biases of testing predominantly urban populations, those displaying symptoms, and those in known high risk groups. Nowhere is this more vital than rural areas of the developing world, where over a billion people live in 50 countries with fewer ICU beds combined than New York City. Deployable testing solutions, at scale, are needed in days rather than months.
The solution follows 4 steps (Rwanda example):
1. Estimate testing needs across the targeted countries, using our current AI satellite mapping tool. Large scale orders combined with the public service of supporting vulnerable populations may permit quick access to antibody tests as they come online at scale in the coming weeks.
2. Mobilize health workers and prepare all data collection tools within 14 days of program start date. We estimate a team of 100 full-time equivalent (FTE) health workers would be required in Rwanda, assuming health workers travel in teams of three and gather information from 32 individuals (5-7 households) per day. Enveritas will contribute tools we have developed for previous work that enabled us to cover 200,000+ rural households. 3. Sample and test 140,928 individuals during each 60-day phase of the program. This assumes a sample of at least 96 individuals from all 1,468 administrative cells across Rwanda. If the program has three phases, then this represents a total of than 422,784 individuals over a 180-day period. Enveritas will contribute tools that allow us to receive, analyse and share the data in real-time.
4. Build data sharing tools and dashboards for all relevant actors involved in coordinating the response
The Challenge's focus on how global communities can detect and respond to pandemics describes this project and solution perfectly. We are aligned with the Challenge and the global need right now to react quickly and effectively to solve this.
We firmly agree that increased detection and reliable, accurate and immediate data can assist countries to respond to this pandemic in the most cost-effective way.
- Pilot: An organization deploying a tested product, service, or business model in at least one community
- A new application of an existing technology
Enveritas has been developing and using innovative tools over the last few years that allow us to gather information from rural areas with a large focus on data quality and speed.
There has been a large amount of innovation to date in the development of these tools and since we were formed in 2016, we’ve built the largest coffee verification platform in the world. In the last three years, we completed over 200,000 farm interviews. (Fair Trade typically does several thousand interviews in a year.) Our innovation has been recognised across multiple partners including Google and Carto and Enveritas is a Y Combinator company, one of only a handful of non-profits selected.
Examples of our tools include:
- Our data collection app has been used by over 500 enumerators in 20 countries, mostly in regions with limited 3G coverage.
- We have developed AI models that predict rural villages and houses in Africa, Asia, and the Americas. We have a crop detection model that delivers 95% accuracy and a school detection model that delivers 90%+ accuracy.
- Our household detection tool mentioned above uses AI, in that it uses a machine-learning algorithm developed to identify rural households from satellite imagery.
- Our enumerators use our data-collection app (link above) that allows individual deployment to GPS points and assists in the navigation to them, particularly useful for rural areas.
- Our data is collected live through the above app and analysed in real time with Looker and other data analysis tools.
Enveritas is the first to develop these specific tools and have been doing so over the last 3 years. To date we have successfully conducted data collection on over 200,000 rural smallholder farms and households across 20+ low-resource countries.
We recently adapted the tools to survey schools across 100% of Cote D'Ivoire with the Ministry of Education.
We are about to launch this exact COVID testing project in Colombia, and are confident that our tools will work for this.
- Artificial Intelligence / Machine Learning
- GIS and Geospatial Technology
- Software and Mobile Applications
We believe that through rapid and rigorous testing, rural populations will be better served as countries respond to this pandemic.
- Rural
- Poor
- Low-Income
- Minorities & Previously Excluded Populations
- 1. No Poverty
- 3. Good Health and Well-Being
- 8. Decent Work and Economic Growth
- Brazil
- Burundi
- Colombia
- Costa Rica
- Ethiopia
- Guatemala
- Honduras
- Indonesia
- Côte d'Ivoire
- Kenya
- Nicaragua
- Papua New Guinea
- Philippines
- Rwanda
- Uganda
- Vietnam
- Brazil
- Burundi
- Colombia
- Costa Rica
- Ethiopia
- Guatemala
- Honduras
- Indonesia
- Côte d'Ivoire
- Kenya
- Nicaragua
- Papua New Guinea
- Philippines
- Rwanda
- Tanzania
- Uganda
- Vietnam
- Yemen, Rep.
To date we are working in Colombia and have secured funding from several large coffee companies (Nespresso, Smuckers, Tchibo) to reach rural areas. We currently have funding to statistically sample 1 million people (5% MoE and 95% CI) and are beginning operations this week. We welcome any funding to increase our reach in Colombia or scale this to high-risk areas in other countries.
This solution will address the current immediate need for COVID-19 testing and we do not expect it to continue past 1 year.
Enveritas has the network and capabilities to scale this across rural populations globally. The size of this coverage will depend on funding received to purchase tests.
Due to the urgent nature of the pandemic response our largest barrier is to secure funding to purchase the tests.
We are currently approaching several innovation funders like Solve as well as our larger clients and foundations.
- For-profit, including B-Corp or similar models
50 full-time staff members across our 20 countries.
1000+ part-time data-collectors.
Our Advisory Council includes Nobel Prize winner Michael Kremer, Rolls Royce Chairman and former McKinsey Global Managing Director Sir Ian Davis, Sir David Spiegelhalter, Head of Risk at Cambridge University and Professor Geoffrey Grimmett, Professor of Mathematical Statistics Cambridge University and Fellow, Royal Society.
The core team will consist of 7 members with expertise from in-country operations, data-science, and sustainability.
David B. - CEO and co-founder: David led the global coffee practice at Technoserve for 13 years and acts as sustainability counselor to several multinational firms.
Carl C. - COO and co-founder: Carl led work in over a dozen coffee countries over 10 years at Technoserve and founded a microfinance company in Tanzania. .
Karin R. - Operations: Karin previously worked at a public health NGO in Tanzania and in McKinsey in Joburg, South Africa. She holds a MSc in Global Health from the University of Sussex (UK).
Thomas V. - Operations: Thomas worked as an investment professional in Leverage Finance and Venture Capital. He holds a MSc in Management from HEC Paris.
Celine J. - Operations: Celine previously worked at McKinsey in Paris and as a Data Scientist at Groupama in Italy. She holds a MSc in Science and Executive Engineering from Mines Paristech.
Fernando I. - Data Scientist: Fernando worked for J-PAL Latin America and is an MPA from Harvard.
Grace G. - Computer Scientist. Grace’s last startup HoneyInsured was built on her Harvard-published research and cited in House and Senate testimonies. Grace has a BA from Harvard.
Enveritas has already received funding commitments from large coffee companies (including Nespresso and Folgers) and foundations for a rapid COVID-19 diagnostic testing of coffee areas in Colombia.
Our core revenue generation comes from large and specialty coffee and cocoa buyers. We supply data on the sustainability issues that their farmers face.
- Organizations (B2B)
We are able to sustain our operations through verification work, and expect to make a surplus by 2021 that we can reinvest into farmer livelihoods.
We understand that Solve is directing funding to innovative COVID response efforts and would welcome the partnership.
- Funding and revenue model
We hope to increase our partnerships and funding to scale to a larger population coverage in Colombia and also to include other low-resource countries.
We are currently approaching our larger client list, foundations and funds that are focused on rapid COVID relief efforts.
The enumerators and healthcare workers involved in testing during our project would qualify for this award as they leave the relative comfort of their families in urban areas to test their rural counterparts.