As part of the North American Observatory on Health Systems and Policies (NAO) Lecture Series we welcome Neil Seeman on Thursday, March 26, 2020 at 12:00 PM. This webinar is free of charge and open to anyone. Forward it to a friend who might be interested.
Please note this webinar is still scheduled to take place, despite the University of Toronto’s suspension of in-person events and classes.
Hearing from Quiet Voices to Improve Global Measurement and Understandings in Public Health: New Data Streams and New Technologies
What if we could more accurately, in real-time, and in all countries, assess the most effective public health messaging to contain disease outbreaks? What if we could reliably determine who are the most trusted public health messengers? What if we could understand what the majority believes to be true, rather than hear from outliers on social media, loud voices in the media, or from those who answer surveys for cash or rewards?
Neil will discuss examples from his data collection work in low-, middle-, and high-income nations, including:
- Monitoring trust in health officials in China during the COVID-19 outbreak and in other public health crises;
- Harvard research measuring expectations of healthcare quality in low- and middle-income countries; and
- How new models of data collection extend to measuring diverse ‘sensitive topics’ for which we have limited or flawed data in public health and policy, such as changing attitudes toward stigmatized populations.
The talk will engage audience members to explore what could now be possible to measure not only in Canada and the United States where the vast majority are online, but also in the rest of the world. What research and public health questions can we answer now in the era of Big Data that we couldn’t answer or answer as well before?
Neil Seeman is the Founder and Chief Executive Officer of RIWI Corp., a global trend-tracking, risk monitoring and prediction technology firm. His academic and commercial work seeks to collect a unique stream of individual, community-based, and country-wide sentiment data from more than 200 countries and territories in the world for organizations such as the UN World Food Programme, the Bill and Melinda Gates Foundation, the United States Agency for International Development, The World Bank, the US State Department and BofA Securities. For high-frequency, real-time public health sentiment data, Neil’s team works with leading research universities around the world, including Harvard University, Australian National University and the University of Toronto.
Neil’s pre-commercialization work in 2009-2010 involved tracking the efficacy of public health communications around the globe, and the measurement of online misinformation about vaccines. Neil invented RIWI’s intellectual property in machine-learning and Big Data, which first won attention for tracking the fall of Mubarak during the Egyptian Revolution of 2011. He is the author or co-author of hundreds of articles in major media around the world, and more than 30 peer-reviewed journal papers and several books and monographs. Prior to RIWI, he was Founder and Executive Director of the Innovation Cell, and led research initiatives at IBM and other data organizations to explore the opportunities and challenges of online data to improve patient-centred healthcare. He has taught at Ryerson University and the University of Toronto. Neil holds a bachelor’s degree from Queen’s University, a JD degree from the University of Toronto and a Master of Public Health from Harvard.
North American Observatory on Health Systems and Policies (NAO)
The North American Observatory on Health Systems and Policies (NAO) is a collaborative partnership of interested researchers, health organizations, and governments promoting evidence-informed health system policy decision-making. Due to the high degree of health system decentralization in the United States and Canada, the NAO is committed to focusing attention on comparing health systems and policies at the provincial and state level in federations.
Webinar Login Details via Zoom:
|Meeting ID||401 428 361|