One paradox about antibiotics is that, broadly speaking, the more we use them, the less they continue to work. A team led by MIT scientists, including an HST faculty member and an HST PhD student, believes that this conundrum opens up an opportunity for a data-driven tool that could help doctors make safer, more customized decisions for patients.
Interventions limiting superspreading may be particularly effective at controlling the ongoing COVID-19 pandemic, according to an analysis of SARS-CoV and SARS-CoV-2 superspreading events.
Mathematical analysis of Covid-19 "super-spreading" events suggests that preventing large gatherings could significantly reduce Covid-19 infection rates.
Panelists discuss open problems in Covid-19 patient care and new opportunities for AI solutions. Left to right and top to bottom: Regina Barzilay, MIT; Gabriella Antici, Protea Institute; Rajesh Gandhi, MGH; Karen Wong, CDC; and Guillermo Torre, TEC Salud.