Researchers at institutions including Johns Hopkins University and the University of Pennsylvania used computer modeling to determine that eviction bans during the COVID-19 pandemic lowered infection rates, shielding entire communities from the virus.
The scientists said they used simulations to predict additional virus infections in major U.S. cities if bans were not authorized in fall 2020.
The team initially calibrated its model to reproduce the most common epidemic patterns observed in major cities last year, accounting for infection-rate changes due to public health measures.
Another iteration factored in the lifting of eviction bans, determining that people who are evicted or who live in a household that hosts evictees are 1.5 to 2.5 times more likely to become infected than with such bans in place.
From Johns Hopkins Medicine Newsroom
View Full Article
From "Managing Multicore Memory"
MIT News (09/13/13) Larry Hardesty
View Full Article
No entries found