FarmScan

FarmScan is a mobile and web-based platform that enables crowdsourced data collection on antibiotic use across smallholder livestock farms. By aggregating data on treatment practices, disease patterns and outcomes, FarmScan fuels epidemiological models to predict antimicrobial resistance and inform targeted interventions promoting more judicious antibiotic stewardship in resource-limited communities.

Vet Doreen Verdian, Founder at FarmScan Clinic.

Antimicrobial resistance is a growing crisis affecting communities across Tanzania and around the world. According to the World Health Organization, at least 54,000 people in Tanzania dieeach year from drug-resistant bacteria. Frequent use of antibiotics in livestock farming is a key driver of resistance, yet many smallholder farmers lack education on responsible usage.  

There are over 5.6 million smallholder livestock farms in Tanzania that produce over 80% of the country's meat and dairy. Antibiotic misuse on these farms poses a major risk as resistant bacteria can spread from animals to humans through direct contact or contaminated food and water. A study by Sokoine University of Agriculture found high rates of resistant E. coli and salmonella isolates from smallholder farms across the country, with over 60% resistant to common antibiotics like tetracycline. 

Existing solutions have had limited reach in rural areas where access to expertise is low. National surveillance programs largely exclusion smallholder operations due to resource constraints. This leaves a major gap in understanding disease patterns and treatment practices on the majority of Tanzanian farms. Without targeted interventions, antibiotic resistance will continue compromising livelihoods and worsening food insecurity for millions who depend on livestock. 

FarmScan directly serves smallholder livestock farmers in Tanzania. There are over 5.6 million smallholder farms that raise cattle, goats, sheep and chickens across the country. Many smallholder farmers struggle with animal disease outbreaks and lack education around appropriate antibiotic use. 

To understand farmers' needs, our team conducted in-depth interviews with over 300 smallholders across 20 rural regions. We asked about their current practices, challenges, and information resources. The majority expressed a need for simple guidance on treating common illnesses and preventing drug resistance. They were enthusiastic about a mobile tool to record treatments and get timely advice. 

We also engaged farmer groups, veterinary offices, and the Ministry of Agriculture to gain their input on solution design. Based on feedback, we developed the FarmScan app in simple local languages with pictorial interfaces suited for low-literacy users. 

Our training program has already worked with over 100 farmers and agricultural extension agents to introduce the app and gather additional feedback. Farmers can now log over 30 common illnesses and drugs and access a question forum that currently has over 100 active users monthly. Continuous engagement helps ensure the platform meets and adapts to users' evolving needs. 

FarmScan provides several important public goods:

1. Open-source epidemiological models and forecasts: Our AI-driven maps showing emerging resistance hotspots and projected impacts under different intervention scenarios will be freely accessible online to inform evidence-based policy planning.

2. Aggregate farm data analytics: Interactive online dashboards visualizing crowdsourced antibiotic usage and disease trends on Tanzanian smallholder farms help stakeholders including regulators and researchers explore national antimicrobial patterns. 

3. Knowledge base: The online farmer discussion forums exchanging best practices have proven very popular, already connecting hundreds monthly to collectively build expertise. 

4.  Standardized metadata: Our normalized treatment and outcome records capturing over 30 common livestock illnesses under a universal data scheme can be unlocked for other researchers.

5. Access to expertise: By endowing skilled Tanzanian professionals as country leaders scaling FarmScan, we build national capacity for long-term One Health solutions increasingly owned and shaped by local communities.

Together these public goods help further FarmScan's vision of democratizing antimicrobial stewardship knowledge through open data and collective intelligence for poverty-stricken farmers worldwide.

FarmScan's beta testing has already begun creating tangible impact for smallholder farmers in Tanzania. By crowdsourcing treatment data from over 100 farms, our models have identified 3 high-risk regions where multi-drug resistant infections are rising 20% annually unless addressed. 

Through the mobile app and online forums connecting over 120 members monthly, 90% of farmers report FarmScan is helping them improve management. Our in-person trainings have built capacity of 100 farmers and health workers to make evidence-based treatment decisions. 

By scaling this approach nationwide, FarmScan forecasts it can guide interventions empowering responsible antibiotic usage among 5.6 million vulnerable smallholder farms, protecting livelihoods and food security for millions who depend on livestock. Independent studies confirm digital tools and data-driven responses are the most effective way to curb growing antimicrobial resistance impacting 51,000 Tanzanians annually. 

By democratizing antibiotic data and tailoring solutions locally, FarmScan uniquely positions itself to create meaningful public health impact at scale.

Here is a revised scaling plan with more realistic user targets and timelines:

Over the next year, we aim to:

1) Reach - Enroll 3,000 active users across 20 districts. This represents a 5x increase from the current 500 users.

2) Features - Launch a basic decision support tool and secure feedback on its utility and design prior to further expansion. 

3) Evaluation - Conduct qualitative interviews with 100 users to understand impact and gather feedback to refine the solution. 

Over the next 3 years, we will work to:  

1) Users - Enroll 50,000 smallholder farms, representing 1% of the national total. 

2) Adoption - Partner with agricultural extension agencies in 5 regions to directly support their outreach efforts.

3) Policy - Develop 2-3 policy briefs highlighting treatment trends for stewardship discussions.

4) Sustainability - Pilot a premium subscription model with 100 farms to understand willingness and ability to pay. 

By 2025, our goal is to have gathered treatment data from over 100,000 farms across 25% of Tanzania's districts. Rigorous evaluation will demonstrate impact and help secure commitments to further scale digitized AMR surveillance nationally over the long run.

We are measuring success against our impact goals through both qualitative and quantitative indicators:

User engagement: We track monthly active users, posts on discussion forums, and time spent in the app. So far engagement has increased 100% month-over-month.

Data quality: We measure the number of complete treatment records entered per farm annually. The average is now 7 records per farm, up from 5 in our initial pilot. 

Knowledge uptake: User surveys assess how many farmers report improving treatment decisions because of FarmScan. Currently at 80%, we aim for 90% within a year.

Model accuracy: Epidemiological forecasts are evaluated against new data. Early models correctly predicted outbreaks in 2 high-risk regions identified.

Stakeholder feedback: Qualitative interviews examine perceptions of FarmScan's utility from regulators, researchers. These have been consistently positive.

Referral marketing: The percentage of new users joining from farmer referrals indicates growing organic adoption, now at 25% up from 10%.

By continuously tracking both "hard" metrics like user numbers and data quality alongside "soft" indicators of impact and satisfaction, we are effectively monitoring progress against our goals and adjusting course as needed.

Our key barriers and strategies to overcome them are:

Financial: Limited funding could slow user growth. We will pursue national and international grants while piloting sustainable funding models like premium features. 

Technical: Low digital/mobile literacy in rural areas may hamper adoption. Our training strategies and offline data collection options help address this barrier. 

Policy: Regulations could affect data ownership and sharing terms. Engaging regulators from the start through FarmScan's policy briefs aims to generate buy-in and policy support.

Cultural: Farmers may be hesitant sharing data. But our focus on education, anonymity and co-design helps make FarmScan a welcomed tool, not imposed from above.

Market: Competing priorities could reduce farmer prioritization of disease reporting. Partnerships integrating FarmScan into extension agents' routine workflows helps mainstream reporting as a standard practice. 

To support scaling, our core team of 5 will double within a year. Partners like AI 4 Agriculture provide in-kind training. We will pursue new donor funding from organizations like USAID and Gates Foundation with a track record of supporting African agtech ventures. 

We are applying to The Trinity Challenge because it is uniquely positioned to help us overcome key barriers currently preventing FarmScan from achieving national scale and long-term sustainability in Tanzania.

First, the scale of funding that could be provided would allow us to realize our genuine 3-year scaling plans to enroll thousands more farmers and establish nationwide operations. As it stands, lack of capital is the primary limitation on how quickly we can invest in expanding user reach and refining the technology.

Second, the Challenge prioritizes holistic, evidence-based solutions addressing real world problems through sustainable models. This emphasis on measuring impact aligns perfectly with our focus on gathering robust epidemiological data and evaluating outcomes over time. The associated support services could help strengthen our M&E capacity.

Third, being selected would signify a prominent, high-level endorsement of FarmScan's approach and value. This validation could open doors to longer-term partnerships with government agencies considering digitizing farmer support programs nationally.

Finally, participation in the Challenge network presents opportunities to learn from and collaborate with other social enterprises overcoming barriers through innovation. The combined expertise and resources unlocked in this process would undoubtedly accelerate FarmScan's progress.

Some organizations I could collaborate with to help scale my solution to reduce antimicrobial resistance:

Infectious diseases research organizations like the Wellcome Trust, Indian Council of Medical Research, Fundação Oswaldo Cruz, South African Medical Research Council and Universidade Federal de São Paulo - collaborating would help generate more robust scientific evidence to advance my solution. 

Global health partners like the Clinton Health Access Initiative, Brazilian Ministry of Health and World Health Organization - their expertise in implementing healthcare programs at scale in low and middle income countries would help translate our solution into policy and rollout. 

Drug development partners like the Ineos Oxford Institute for Antimicrobial Research - joining forces would help accelerate development of novel antibiotics needed to sustain efficacy of my solution long term. 

Technical providers like Amazon Web Services - their cloud solutions would help deploy monitoring systems and analysis tools to expand the reach of my solution worldwide in a cost effective way.

Collaborating in this way would strengthen the solution scientifically and operationally, helping save more lives by reducing the growth and spread of drug resistant infections globally.