Identify risk-based behavioral segments
The pandemic is causing monumental shifts in daily routines. Identify behavior-based user segments based on common risk factors, such as Essential Workers, Inter-city Travelers, Super Spreaders, Hospital Workers, Delivery Workers, Stay-at-Home Users, and more. By identifying these user segments, we can make smarter decisions about the allocation of scarce resources, and predict new outbreaks before they occur.
Segments and Audience
Neura’s ML algorithms provide smart analytics to help organizations understand high risk situations and areas.
Differentiate populations and neighborhoods based on risk factors and make well-informed predictions about the safety and infection status of populations and towns.
Super-SpreadersIdentify anonymized individuals who meet more than 15 different people per day - high risk for virus spreading.
Inter-City TravelerSee individuals who travel between cities thus increasing the rate of virus spread.
Social-SpreaderDetermine individuals who have multiple friend groups, attend gatherings, and meet new people.
Essential WorkforceIdentify movement and mobility patterns essential workers commuting to their workplaces.
Household SupplierPeople visiting stores as the sole buyer of goods for each household.
Returning ResidentDetermine the residents returning from abroad journeys and are at higher risk of infection.
Retail Business Case Study
Restart the economy safely while ensuring proper COVID-19 risk mitigation measures are in place.
Neura deployed a real-time economy restart insights platform, including micro-segmentations in order to stay in compliance with changing guidelines. We equip businesses with predictive analytics and visibility into areas, businesses, and populations with risk of future outbreaks.
Data-driven decision making for controlled business reopening as well as information for social distancing compliance according to geographies in order to communicate reliable and critical information to populations.Read More >
Municipality Case Study
Our social distancing index was used as a predictor of COVID-19 outbreaks.
Neura deployed a system to help the government predict cities with an increased risk of COVID-19 outbreaks, providing a social-distancing index that has taken into account millions of anonymized data points building a behavioral model of population density and migrations.
During the peak of COVID-19, a high correlation was proven between Neura's index and the percentage of COVID-19 cases in 3 distinct cities. The scores were shared with health authorities enabling data driven COVID-19 policy decisions.Read More >
Health Organization Case Study
Enabled one of the world's largest HMO's to effectively deploy COVID-19 screening tests.
Neura's technology generated metrics such as social distancing index, human encounter rates, personal mobility patterns and behavioral segmentation, Neura was able to accurately map and calculate the infection rate potential for members of the Health Maintenance Organization.
Through the merging of our machine learning behavioral segmentation with the HMO's epidemiological data base, our client was able to optimally utilize scarce screening tests on patients where it would be most impactful.Read More >