Statistics without Borders and Lisa 2020: Support For/Capacity in Global Science

This talk provides an overview of two organizations, Statistics Without Borders and LISA 2020, in which statisticians lead global engagement in science by supporting projects to become more scientific and building capacity for science globally.

Statistics Without Borders (SWB) provides pro-bono statistical, data science, and data analysis services to organizations that don't have resources to pay for statistical help. It has helped a wide variety of organizations with many different types of projects since its founding in 2008. Organizations include small non-governmental organizations (NGOs) in Africa, large international NGOs, United Nations affiliated groups, and animal-related NGOs. SWB does work to improve health and education in developing countries, improve international response to natural disasters like earthquakes, and on human rights issues, among other things. Statistics Without Borders has grown to about 1900 members and works on at least 25 projects per year.

LISA 2020 is a program to build statistics capacity and research infrastructure in developing countries. It has similar goals as SWB – to increase the impact of statistics worldwide by facilitating more statisticians working on projects to improve human health, development, research, and better decision-making through statistics and data science. LISA 2020 trains statisticians from developing countries to effectively communicate and collaborate with non-statisticians to apply statistics and data science to solve real-world problems and make better decisions. The LISA 2020 program helps these newly trained collaborative statisticians create statistical collaboration laboratories in their home universities or institutions. Currently there are five new statistical collaboration laboratories in the LISA 2020 Network in Nigeria (2), Tanzania, Ethiopia, and Brazil. Each lab trains statistics students to become effective collaborative statisticians who can use statistics and data science to solve problems; enables and accelerates scientific and other research projects, including collaborations with local businesses, NGOs, and governmental agencies; and engages in statistical outreach activities to improve the statistical skills and literacy of their local communities. With a strong mentoring network, just one statistician trained to communicate and collaborate with non-statisticians can enable 20 or more scientific projects per year. Each project can impact hundreds or thousands of people.