At the beginning of the year, I mapped out several of the key topics that I wanted to cover in this blog series – I wanted to highlight some of the innovative analytics projects civic analytics leaders were conducting and how it may benefit and inspire the private sector. Last month, I shared the successes San Francisco experienced with upskilling its workforce to become more data fluent by designing and running its own Data Academy. March had been earmarked to research the various ways cities and states utilize analytics and technology when it comes to managing natural disasters and/or infectious diseases.
The timing (unfortunately) aligned with the WHO officially declaring COVID-19 a global pandemic on March 11, 2020. Health officials and civic leaders had already been utilizing a variety of analytics tools, data, and techniques to identify outbreak clusters to try and quell the spread of the virus. From identifying and mapping cluster areas to detecting and managing those infected, advanced analytics has been playing a significant role and below is a brief overview of some of the activities taking place.
Geographic Information Systems (GIS) Data
GIS data has played a critical role in understanding the spread of this virus so that communities and first responders have some idea of how it’s behaving. Tracking can help leaders prepare by issuing directives like shelter in place, preparing health care workers with expected patient headcount, and focusing efforts in locations such as New Rochelle, New York where more than 50 cases were attributed to one individual.
Utilizing GIS data, interactive maps depicting where the disease is occurring and the number of cases by date of report can easily be viewed and tracked on the WHO Novel Coronavirus (COVID-19) Situation dashboard; Johns Hopkins University has also created a resource center with its own dashboard to track global cases and the University of Washington's IHME COVID-19 Projections dashboard has gained a lot of attention with its state by state breakdown of peak dates while the COVID-19 Healthcare Coalition dashboard focuses on vulnerable populations by region. Esri’s ArcGIS is the platform being used to power many of these publicly available dashboards.
Natural Language Processing (NLP)
BlueDot is a Canadian start-up that detects and tracks the spread of diseases around the world by using “natural language processing and machine learning to cull data from hundreds of thousands of sources, including statements from official public health organizations, digital media, global airline ticketing data, livestock health reports and population demographics. It’s able to rapidly process tons of information every 15 minutes, 24 hours a day.” In the case of COVID-19, airline ticketing information helped inform which cities the disease was likely to spread to from Wuhan.
Drones and Facial Recognition
When China began issuing shelter in place rules, drones were used to monitor and track individuals venturing outside. Many of the drones were also equipped with a loudspeaker so that directives could be shared with the individual; if someone was breaking a specific rule, facial recognition technology could identify that individual and fines would be issued accordingly.
AI Temperature Sensors
Firetinas is one of the solutions being used to test mass crowds and “quickly differentiate high body temperature individuals from general public.” Firetinas touts an A.I. algorithm and chips that “calculates 3 trillion times per second for body detection of up to 100 individuals. The A.I. algorithm is crucial in forehead temperature measurement which will improve the efficiency by 15 times.” This is important since testing for COVID-19 has proven difficult in many areas (e.g., limited availability of test kits, prioritizing demand, etc.) but detecting a high fever can quickly identify an individual that may require priority testing and quarantine to protect the larger community.
In an effort to limit human exposure to COVID-19 and other bacteria, robots are being used to clean hospital rooms. UVD Robots and XAG Robot are roaming hospital hallways in China and using UV light and/or spraying disinfectant to better protect staff and patients.
As this all unfolds, it will be interesting to see the lasting impact of these technologies. Will we be safer and more resilient in the future? What lessons will we have learned to better manage a virus at this scale? Looking at the financial crisis from 2008, FinTech certainly experienced stricter regulations and deeper scrutiny of algorithms and models but what will this mean for the travel, hospitality, retail, and healthcare industries? Time will tell... In the meantime, be safe, be well, and do your best to take care of your community as we are all in this together.
(updated April 7, 2020 to include additional links to publicly available dashboards)
Lise Massey is the Program Manager for IIA’s Analytics Leadership Consortium (ALC) and has been with IIA for six years. The ALC is a closed network of senior analytics executives from diverse industries who meet to share and discuss best practices, as well as discover and develop analytics innovation, all for the purpose of improving the business impact of analytics at their firms. Prior to IIA, Lise spent over 10 years designing, managing, and leading media analytics programs for a diverse portfolio of clients and has experience in many aspects of program and project management, account management, strategic and tactical planning, business development, and training. Lise is a graduate from the University of Oregon.
You can view more posts by Lise here.