Writing for STAT, Prof. Kevin Esvelt explores how we can stop the spread of the B-117, a variant of SARS-CoV-2. Going forward, Esvelt and his co-author argue that “over the next few years we must build a genomic monitoring system to detect evolutionary changes in viral, bacterial, and other pathogens that could require new measures to protect public health, and that could detect new pandemic pathogens of any provenance early enough to intervene.”
In a new white paper, senior lecturer Steve Spear examines how the U.S. can prepare to better handle the next pandemic, reports Carey Goldberg for WBUR. Spear and his co-author are “calling for a system that would be better at amplifying pandemic lessons learned locally, to be sure the best known methods are shared and scaled up.”
Marc Zissman, associate division head at Lincoln Lab, speaks with New York Times reporter Jennifer Valentino-DeVries about the challenges associated with encouraging people to use coronavirus tracing apps.
MIT researchers have developed a model that could help people estimate the risks of contracting Covid-19 in different scenarios, reports Emily Czachor for Newsweek. The tool “provides calculations which estimate how many people can remain within an enclosed space, and for how long, before they are theoretically exposed to the virus.”
Writing for WBUR, Prof. Kate Kellogg and alumna Noa Ghersin outline how to help prevent outbreaks of Covid-19 at long-term care facilities. “Nursing homes lack the resources of other institutions,” they write. “They aren’t states, they aren’t cities, they aren’t major hospital systems.”
MIT researchers have developed a new model that could be used to help determine “how long you will be safe in a room with someone who is positive for COVID-19 based on room type, size and even the ventilation and filtration system,” reports Boston 25 News.
Fast Company reporter Mark Sullivan writes that Prof. John Bush and Prof. Martin Z. Bazant have developed a mathematical model that “simulates the fluid dynamics of virus-loaded respiratory droplets in any space, from a cozy kitchen to a gigantic concert hall.”
A new study by MIT researchers finds that “changes in coronavirus levels in wastewater preceded rises and falls in positive test results by four to 10 days,” reports Kim Tingley for The New York Times. The findings suggest that “sewage surveillance could play an important role in helping contain the pandemic.”
Fast Company reporter Adele Peters spotlights Particles for Humanity, an MIT spinoff that is developing a new technology that makes it possible to deliver multiple doses of a vaccine in one shot. “The new technology works like traditional drug delivery,” writes Peters, “but with the addition of tiny time-release capsules filled with antigens, the part of the vaccine that stimulates the immune system so that it can later respond to a virus.”
Prof. Eric Alm speaks with New York Times Magazine reporter Kim Tingley about how studying wastewater can provide public health officials with advance warning of an uptick in coronavirus cases. “If you want to really understand what’s going on in a city on a basic chemical, biological level, you should be looking at the wastewater," says Alm.
Reporting for WCVB-TV, Katie Thompson highlights a new study by MIT researchers that examines the role of super-spreading events in the Covid-19 pandemic. "The main idea is that most people generate zero or one cases, but it's the people generating hundreds of cases that we should perhaps be worried about," says postdoc Felix Wong said.
Visiting Professor Susan Blumenthal writes for CNN about the need for face mask standards to help stem the spread of Covid-19. “Developing a national certification and labeling system for mask effectiveness, educating about their power for preventing infection, and mandating their use are essential components of protecting individuals and communities from viral spread in America's battle against this pandemic,” writes Blumenthal and her co-author.
A new study by MIT researchers finds that super-spreading events are larger drivers of the Covid-19 pandemic than originally thought, reports Carey Goldberg for WBUR. “We found in our study that super-spreading events can indeed be a major driver of the current pandemic,” says postdoc Felix Wong. “Most people generate zero or one cases, but it's the people generating hundreds of cases that we really should be worried about.”
A new algorithm developed by MIT researchers could be used to help detect people with Covid-19 by listening to the sound of their coughs, reports Zoe Kleinman for BBC News. “In tests, it achieved a 98.5% success rate among people who had received an official positive coronavirus test result, rising to 100% in those who had no other symptoms,” writes Kleinman.
Mashable reporter Rachel Kraus writes that a new system developed by MIT researchers could be used to help identify patients with Covid-19. Kraus writes that the algorithm can “differentiate the forced coughs of asymptomatic people who have Covid from those of healthy people.”