Surgo Insights Translated into State of Uttar Pradesh’s Behavior Change Communication Strategy and Roadmap

The Government of Uttar Pradesh recently developed a new behavior change communication strategy for 2018-2021. Research funded by the Surgo Foundation formed the foundation for this strategy including the cross cutting strategic elements as well as behavior- specific approaches for RMNCH behaviors. This strategy outlines the state government’s behavior change communication priorities and is a roadmap for partners to help plan their investments in behavior change communications. The Government of Uttar Pradesh will begin implementing the strategy this year. 

Surgo Foundation and the Clinton Health Access Initiative Team Up for Strategic Partnership

What if we could make major strides against global epidemics such as HIV and TB by combining expertise in healthcare delivery models in low-resource settings with a deep understanding of what drives behavior?  What if we could dramatically reduce the number of children who die from diarrhea by nudging families and caregivers towards correct care-seeking behavior while also strengthening access to needed drugs? These are some of the big questions that drove us - the Surgo Foundation and the Clinton Health Access Initiative (CHAI) - to set up a long-term, strategic partnership.

In 2017, we launched the first project based on this partnership in Chennai, India, as part of the city’s initiative to eliminate TB.

Surgo Foundation was founded with a key belief that people with limited resources have choices and need to be treated as active customers rather than passive beneficiaries. Surgo’s mission is to catalyze the global development community by developing solutions and tools that put customers at the center of programs. Surgo connects across disciplines and utilizes diverse techniques adapted from fields such as behavioral sciences, market research, data science, and machine learning, to bring a fresh perspective to some of the most stubborn development problems. Bringing its funds, tools, and solutions, Surgo partners with other organizations and governments to help them maximize their success.

CHAI is committed to strengthening integrated health systems and expanding access to care and treatment in the developing world. CHAI’s approach focuses on improving market dynamics for medicines and diagnostics; lowering prices for treatment; accelerating access to lifesaving technologies; and helping governments build the capacity required for high-quality care and treatment programs.

Both of our organizations have similar end goals – help governments save lives, reduce morbidity and mortality, and achieve the Sustainable Development Goals – but bring a different perspective, approach and expertise. We decided to collaborate for two main reasons: complementary strengths and the ability to bring new, comprehensive approaches to governments we partner with around the world.

1. Complementary strengths: With its global footprint, CHAI works at scale to support governments in solving some of the biggest problems across the public health sector, especially related to access and health systems challenges. Surgo brings strong customer- and systems-centric approaches that help to design more effective programs at lower costs. Surgo will contribute to this partnership by applying its tools and methodologies on the behavior and systems side. CHAI will work in areas of supply, policy and management. Both will work towards achieving the same goal – impact at scale.

2. Bring new approaches to country governments: CHAI plays a key role in helping governments build the capacity of their health systems and is a trusted partner to ministries of health (or equivalent). Both Surgo and CHAI saw tremendous potential to leverage CHAI’s experience working with governments in order to bring Surgo’s expertise, solutions and tools directly to them. Surgo’s tools and approaches can help governments to develop programs that shift behaviors in key areas.

We saw value in moving away from a project-based funding relationship to a longer-term collaboration. It allows both Surgo and CHAI to dynamically adapt to what we learn together on the ground, rather than enter into a contract or grant with set activities identified at the beginning. We recognize that global development takes time and the long term perspective is critical.

Chennai, India represents the first site for the two organizations’ collaboration. As part of the TB Free Chennai Initiative (TFCI), we are helping the local government and its partners to reduce the burden of this million-year old disease which, globally, claims more victims than any other infectious disease. In Chennai, there are approximately 23,000 TB cases that develop annually, of which less than 10,000 are reported to the local government. Unreported cases are either patients receiving care in the private sector, where TB care is unregulated and the quality varies, or are patients who have yet to seek care or were not properly diagnosed.  First, we are examining how to get patients to seek care sooner; currently, it often takes patients 4 to 6 weeks after developing symptoms of TB. During this time, they are contagious and may infect others around them. Surgo is leading cutting-edge research to better understand patient and provider behaviors and uncover key points of influence to get patients in the door of health facilities and treated sooner. Once they are in the door, CHAI, and the consortium of partners under the TFCI umbrella, are helping doctors to make diagnoses faster and more accurate by training them to recognize the signs of and test for TB as well as improving access to best-in-class diagnostics.

This is just the first of many programs that Surgo and CHAI hope to work on together. We are actively looking at other global challenges where our combined expertise can drive impact.

Surgo Foundation Launches its Machine Learning Initiative for Precision Public Health

Washington, DC -- Surgo Foundation is launching the Surgo Machine Learning Initiative for Precision Public Health (ML4PxP) to explore the feasibility of applying causal machine learning methods to international development data. Machine learning presents an opportunity to examine an exponentially growing body of data with a fresh perspective beyond the confines of traditional statistics.

“There has been a lot of buzz surrounding machine learning in the international development industry, yet we actually know very little about how it can be applied and where it can add value,” says Sema Sgaier, co-founder and executive director of Surgo Foundation. A tremendous amount of effort has been focused on improving global health and development outcomes by scaling specific interventions. Yet, little is known about the causal chain of factors that drive outcomes. Machine learning can help us reconstruct this story line and find the key intervention points. “We aim to answer two fundamental questions: Is causal machine learning a reliable and scalable complement to traditional statistical analysis?  And can machine learning uncover new insights from previously unconnected data sets?”

Machine learning is a subfield of artificial intelligence that allows systems to learn from data and even predict outcomes without explicit rule-based programming.  Today’s machine learning technology can devise learning algorithms that discover relationships between data points with minimal subjective assumptions. In other words, machine learning doesn’t require researchers to start with a hypothesis.

In the international development sector, most analyses are done using traditional statistics, examining vertical data sets and testing an established hypothesis. This method often misses the opportunity to look at the whole system. By linking large, unconnected data sets without a preconceived hypothesis, machine learning has the potential to uncover a fuller set of relationships between data points.  

Surgo has formed a strong and diverse consortium of partners across the private and non-profit sectors including the Bill and Melinda Gates Foundation (BMGF), GNS Healthcare, the University of Sussex, and the University of Manitoba.  In its first proof-of-concept project, ML4PxP will begin by testing several potential causal machine learning approaches on reproductive, maternal, and child health data sets from Uttar Pradesh, India. Together, the consortium is innovating to determine whether and how such models can be applied to help solve big international development questions. This initiative is part of a larger partnership between Surgo Foundation and BMGF to advance cutting-edge research and the uptake of evidence for decision-making.

About Surgo Foundation: A privately funded Action Tank whose mission is to catalyze the global development sector to meet their promise by developing solutions and tools that put customers at the center. As with this machine learning initiative, Surgo incubates, tests, and scales solutions so others don’t have to.

About the Bill & Melinda Gates Foundation: Guided by the belief that every life has equal value, the Bill & Melinda Gates Foundation works to help all people lead healthy, productive lives. In developing countries, it focuses on improving people's health and giving them the chance to lift themselves out of hunger and extreme poverty.

About GNS Healthcare: Solves healthcare’s matching problem by transforming massive and diverse data streams to precisely match therapeutics, procedures, and interventions to individuals to improve health outcomes and lower costs. Their causal learning and simulation platform, REFS, accelerates the discovery of what works for whom and why.

About University of Manitoba: One of Canada’s largest and research intensive universities offering over 100 academic programs, including professional disciplines such as medicine, law and engineering. University of Manitoba leads the Uttar Pradesh Technical Support Unit (TSU) project, which is funded by The Bill & Melinda Gates Foundation. 

About University of Sussex: A leading research-intensive university near Brighton, England with over 15,000 students and strong research credentials in machine learning and artificial intelligence.