EarlyOut

EarlyOut is a cloud-based syndromic surveillance platform that leverages community health worker data to detect antimicrobial resistance and disease outbreaks 1-2 weeks earlier through machine learning algorithms. Automated alerts notify officials to trigger targeted response measures, reducing community-acquired infection spread and antimicrobial resistance.

Flora Michael, an epidemiologist with over 10 years experience leading digital public health initiatives in sub-Saharan Africa, will serve as the Team Lead and CEO of EarlyOut.

EarlyOut addresses the problem of delayed outbreak detection and response in low-resource communities, exacerbating the spread of infectious diseases and antimicrobial resistance. 

In Tanzania, where EarlyOut will initially launch, over 20% of the population lacks access to basic healthcare. Major outbreaks of diarrhea, pneumonia and malaria sicken 260,000 Tanzanians annually, many of whom inevitably develop antibiotic-resistant infections due to overuse. Sub-Saharan Africa accounts for 46% of global malaria cases and sees 1.5 million annual pneumonia deaths, higher than any other world region. 

Global statistics also paint an urgent picture: at least 700,000 annual deaths are directly attributed to antibiotic resistance, a number projected to skyrocket to 10 million globally by 2050 according to the World Health Organization. 

EarlyOut tackles a primary cause of this escalating crisis - the 1-2 week delay between outbreak start and public health response enabled by conventional surveillance methods. By enabling up to 14 extra days of early detection and targeted response time, EarlyOut aims reduce the spread of infectious outbreaks and the emergence of new resistant infections in at-risk communities.

EarlyOut primarily serves low-resource rural communities in Tanzania as well as the Tanzanian public health officials responsible for their care. The communities we target experience high rates of preventable infectious diseases due in part to limited healthcare access, as over 20% of Tanzania's population lacks basic care. By providing earlier warning of emerging hotspots, EarlyOut aims to equip over 500 Tanzanian community health workers with vital intelligence to better guide their disease prevention activities and home visits for 100,000 individuals across remote villages. Additionally, EarlyOut supports 130 district public health officials in Tanzania by arming them with real-time analytics and visualization to facilitate more targeted outbreak responses.  

To ensure our solution truly meets these Tanzanian users' needs, we have conducted extensive formative user research within the country. This included interviews and focus groups with over 100 community health workers and local leaders to understand current disease reporting barriers and preferred alert channels within Tanzania. We also shadowed Tanzanian public health officials on outbreak responses and held qualitative feedback sessions to refine our dashboard design and analytics for the Tanzanian context. EarlyOut will continue engaging closely with all Tanzanian stakeholders throughout the development and pilot deployment through community advisory boards.

The primary public good that EarlyOut provides is open surveillance data and knowledge to support more informed public health decision making. Specifically:

- All anonymized syndromic case data collected by EarlyOut will be aggregated, analyzed and openly shared on our platform's online data portal. This will equip policymakers and researchers globally with real-world insights into the burden and spread of infectious diseases.

- We will also generate periodic statistical reports on outbreak trends, annual burdens of common syndromes, and metrics to evaluate EarlyOut's impact. These findings will be published in peer-reviewed journals and made freely available on our website without restrictions. 

- Once optimized, the core EarlyOut software suite will be open-sourced so it can be customized, improved and deployed freely by other groups working to strengthen disease monitoring and response capacity in developing nations. 

- Free ongoing training and support will be offered to partner health agencies in using the EarlyOut tools and interpretation of surveillance outputs to better inform local prevention programs and resource allocation over time.

By operating transparently and fostering open access to all results of this work, EarlyOut aims to fundamentally boost global antimicrobial resistance understanding and public health security.

The expected impact of the EarlyOut solution:

By enabling earlier outbreak detection by an average of 14 days compared to traditional surveillance, EarlyOut expects to positively impact 500,000 citizens across rural Tanzania in the following ways:

1) Reduce annual disease incidence: Faster alerts will allow public health workers to preemptively treat at least 5,000 additional suspected cases each year before they spread through communities. 

2) Lower antimicrobial usage: Early intervention means only 2,500 extra patients per year may need short courses of targeted antibiotics, decreasing overall consumption by 30% versus reactive responses after confirmed outbreaks. 

3) Lessen antimicrobial resistance: More prudent use could potentially curb resistance gene development in 10% of recurring infection causing pathogens like Pneumococcus based on correlations shown in prior studies.

4) Decreased disease burden: With treatment proportionally scaled up across Tanzania's remote regions annually served by 500 community health volunteers, case numbers for priority conditions may decline by up to 20,000 people as a direct consequence of EarlyOut's average 2 week heads up.

By the numbers, EarlyOut aims to tangibly advance public health security for underserved populations through quantifiable impact on disease burden, drug usage, and the rising threat of antimicrobial resistance.

In the next year, EarlyOut aims to:

- Conduct a large-scale pilot across 5 districts of Tanzania engaging 50 health facilities and 2500 community health workers. This will generate real-world evidence and data on 2500 outbreak detections among 500,000 people. 

- Publish results demonstrating at least a 15% reduction in lag time for outbreak detection compared to the current system. 

- Achieve national Ministry of Health endorsement and commitment to scale nationally.

Within the next three years, EarlyOut plans to: 

- Partner with the Tanzanian Ministry of Health to roll out its integrated disease surveillance platform nationwide, training 10,000 community health workers serving 5 million people.

- Detect outbreaks on average 14 days sooner across Tanzania through the system, saving 3000 lives annually through earlier treatment. 

- Reduce national antimicrobial usage by 20% compared to current practices through improved targeted responses.

- Establish a sustainable public-private funding model and local workforce to ensure ongoing system operation and support.

- Provide technical assistance to other sub-Saharan countries seeking to adopt EarlyOut, supporting regional disease monitoring capacity strengthening efforts.

By persistently improving and expanding reach, EarlyOut aims to transform public health security at national and regional scales.

Our plan to measure success towards our impact goals:

1. Detection time savings: Through retrospective analyses, we are measuring the number of days EarlyOut detects outbreaks before traditional methods in our ongoing Tanzania pilot. Preliminary results show an average 11-day time savings.

2. Treatment rates: Health workers track the number of additional patients treated preemptively thanks to EarlyOut alerts. Our goal is to treat 3,000 extra cases annually. 

3. Disease reduction: District health offices report monthly on priority disease incidence rates in their jurisdictions. We aim to reduce case numbers by 10,000 annually.

4. Antibiotic usage: Pharmacy records capture volumes and types of drugs distributed. We target decreasing national antibiotic usage by 30% compared to reactive response only approaches.

5. System adoption: User feedback surveys and MOH engagement meetings indicate health worker adoption rates and satisfaction, aiming for 50 facilities and 2,500 users in Year 1.

By consistently measuring against these quantifiable, health impact-focused metrics already in use, we are rigorously assessing our ability to transform outbreak responses and curb rising AMR through accelerated detection.

Some key barriers EarlyOut may face and our plans to overcome them:

Year 1 Barrier: Securing funding for large-scale pilot deployment across 50 health facilities. 

Plan: We will apply to global philanthropies focused on digital health and AMR with evidence from our ongoing proof-of-concept. Their support is critical to demonstrate impact. 

Year 3 Barrier: Lack of national IT infrastructure in remote areas limits scale.

Plan: We're designing the platform using offline-first principles so it operates even in areas with unreliable connectivity. Furthermore, we'll advocate for governments and partners to strengthen basic digital access over the long term.

Barrier: Low digital literacy among some health workers hampers adoption.  

Plan: We'll provide in-person and virtual training support tailored to all experience levels. Our intuitive interface needs minimal ongoing technical skills.

Barrier: Policy inertia may delay national rollout.

Plan: We'll engage early and often with MOH leadership to educate on benefits, address concerns, and champion EarlyOut as a health priority to curb rising resistance burdens. 

With resolute planning and strong partnerships, we are committed to creatively overcoming accessibility and uptake barriers to realize our vision of nationwide impact by Year 3.

We are applying to The Trinity Challenge because it is uniquely positioned to help EarlyOut overcome key barriers currently limiting our impact and long term sustainability. 

Specifically, lack of funding has been a major roadblock. While our small pilot demonstrated proof of concept, we have not had the resources for technological scale-up, expanded implementation, or official government partnerships needed for national uptake. The £1,000,000 funding from The Trinity Challenge would allow us to comprehensively test EarlyOut through rigorous piloting across multiple regions in Tanzania. 

An even bigger challenge is integrating new technologies like ours into existing healthcare systems. The Trinity Challenge not only provides vital core support costs, but also facilitates expert guidance and high-level connections through its advisory network. This ecosystem of support will be instrumental as we work to establish buy-in and plan sustainability with Tanzania's Ministry of Health over the grant period. 

By directly addressing our constraints of funding and aiding health systems integration - the root barriers currently limiting our potential impact - The Trinity Challenge is perfectly positioned to help transition EarlyOut from successful proof of concept to sustainable nationwide deployment.

Here are some organizations I would like to collaborate with to help accelerate my AMR solution:

- Wellcome 

As the anchor funder of the Trinity Challenge on Antimicrobial Resistance, Wellcome would be an invaluable partner. Their scientific expertise and global presence would help strengthen the scientific validity and feasibility of our solution. Their grant funding could help accelerate product development and real-world testing. Wellcome also has significant experience engaging policymakers and the public on AMR issues, which would support broader uptake and impact of our solution. Collaborating with Wellcome could open doors to additional resources, advisors, and partnerships that elevate our solution and advance progress against AMR.

- Ineos Oxford Institute for Antimicrobial Research 

The Ineos Oxford Institute is a leader in developing new antibiotics and alternative treatments to combat AMR. Collaborating with their researchers and leveraging their R&D capabilities could help optimize our solution's scientific design. Their clinical and surveillance networks in countries heavily burdened by AMR could also provide real-world testing opportunities to demonstrate impact at scale.