Presented with
Evaluating Solutions

The Trinity Challenge on Antimicrobial Resistance

How can data and analytics reduce the impact of antimicrobial resistance and bacterial infections in low- and middle-income communities?

Submissions are Closed


Dr. Mark Dybul

Professor of Medicine, Chief Strategy Officer, Center for Global Health Practice and Impact, Georgetown University Medical Center

Dr. Divleen Jeji

India Lead, Google Health


Dr. Metuge Alain

Head of Health Department, Reach Out Cameroon

Dr. Yewande Alimi

One Health Unit Lead, Africa CDC

James Anderson

Executive Director, Global Health, IFPMA

United Kingdom

Elizabeth Ashley

Director, Lao-Oxford-Mahosot Hospital-Wellcome Trust Research Unit

Akhil Bansal

Founder, AMR Funding Circle

Karen Bett

Senior Policy Manager, Data Equity & Inclusion, Global Partnership for Sustainable Development Data

Prof Chris Butler

Clinical Director, Primary Care Clinical Trials Unit, University of Oxford, Nuffield Department of Primary Care Health Sciences, University of Oxford

United Kingdom

Dr. Mark Dybul

Professor of Medicine, Chief Strategy Officer, Center for Global Health Practice and Impact, Georgetown University Medical Center

Kat Esser

Principal, Health Equity Strategy & Innovation, Amazon

United States

Glenda Gray

President and CEO, South African Medical Research Council

Aqil Jeenah

Management Consultant | Veterinarian, McKinsey & Company

Dr. Divleen Jeji

India Lead, Google Health

Dr. Toby Leslie

Global Technical Lead, The Fleming Fund / Mott MacDonald

United Kingdom

Lesley-Anne Long

CEO, Wonderfuture

Prof. Mirfin Mpundu DrPH

Executive Director, ReAct Africa


Dr. Sumi Robson

Senior Research Manager, Wellcome Trust

Patipat Susumpow

Managing Director, Opendream


Erick Venant

Founder, Roll Back Antimicrobial Resistance Initiative (RBA Initiative)

Prof. Timothy Walsh

Microbiologist, Ineos Oxford Institute

Dr. Peiling Yap

Chief Scientist, HealthAI - The Global Agency for Responsible AI in Health


Judging Criteria

Solve’s unique selection methodology is a multi-phase process that includes screening, review, and judging. Expert panels of judges utilize evaluation criteria to assign quantitative scores to each solution. These scores, coupled with qualitative deliberation discussion, determine the selection of winning teams. 

Solve’s standard scoring rubric uses the below criteria to assess the solutions: 

  1. Challenge Alignment: The solution uses data, digital tools and/or analytics to address one or more Challenge objectives

  2. Potential for Impact: The planned solution implementation has the potential to impact the intended population

  3. Feasibility: The team has a realistic, practical plan for implementing the solution, it is feasible in the given context, and the team has a reasonable plan for operational sustainability and measurable results that can be proven to work

  4. Innovative Approach: The solution includes a new technology, a new application of data, digital tools and/or analytics, a new policy model, or a new process for solving the Challenge

  5. Inclusive Human-Centered Design: Inclusive and equitable outcomes are considered in the design, implementation, and internal operations of the solution

  6. Scalability: The solution has a plan for equitable viability and the potential to be scaled to affect the lives of more people in low- and middle-income countries

  7. Proximate Leadership: The solution is led by a visionary entrepreneur, innovator, or team who has deep understanding of the communities they serve and the problem they are trying to solve, expertise to develop and implement solutions, and the ability to adapt and respond to feedback, along with the necessary skills and track record to improve, expand, or replicate their solution

  8. Technical Feasibility: If the digital tools and/or analytics are novel, the applicant has provided convincing evidence that it has been built and functions as they claim it does even if only proof-of-concept

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