The Boston Health Care for the Homeless program has discovered a large cluster of positive coronavirus cases at a specific homeless shelter in the city.
According to WBUR, the program was testing homeless people with symptoms of the coronavirus, but then discovered that some of the positive cases were clustering around the Pine Street Inn, a local homeless shelter.
After noticing the cluster, the program decided to test everyone at the Pine Street Inn and discovered that 36% of the 397 homeless people staying at the shelter were positive for the coronavirus, reports the news agency. But even more shocking, none of them were exhibiting symptoms.
According to Fox-30, the Center for Disease Control is now “actively” investigating the program’s findings and the people who tested positive have since been moved elsewhere and placed in isolation.
Dr. Jim O’Connell, the president of Boston Health Care for the Homeless, has called the results surprising, particularly for the potential implications on future coronavirus screenings.
“It was like a double knockout punch. The number of positives was shocking, but the fact that 100 percent of the positives had no symptoms was equally shocking,” said Dr. O’Connell, reports the news agency. “How much of the COVID virus is being passed by people who don’t even know they have it?”
The program’s testing results could also raise questions about the pervasiveness of covert transmission and the overall infection rate among the population as compared to the confirmed case rate.
In addition to the Boston Health Care for the Homeless test findings, a preliminary study out of Stanford University suggests that the coronavirus fatality rate could be lower than previously believed.
The study, which was conducted in Santa Clara County, California, over the course of two days in early April, found that the presence of coronavirus antibodies among test subjects implies that infection within the county is “much more widespread than indicated by the number of confirmed cases.”
An abstract for the study indicates that between 41,000 and 80,000 people in Santa Clara County may have been infected with the virus as of early April, which would mean between “50-85-fold more than the number of confirmed cases.” Santa Clara County has nearly 2 million people.
The study used a sample of 3,300 people from the county, and the authors concede that the study has several limitations, particularly among the demographics of the participants, which they sought to partially address through statistical weighting.
“Our sampling strategy selected for members of Santa Clara County with access to Facebook and a car to attend drive-through testing sites,” said the authors. “This resulted in an overrepresentation of white women between the ages of 19 and 64, and an under-representation of Hispanic and Asian populations, relative to our community.”
“Other biases, such as bias favoring individuals in good health capable of attending our testing sites, or bias favoring those with prior COVID-like illnesses seeking antibody confirmation are also possible. The overall effect of such biases is hard to ascertain,” said the authors.