How the Broad community is responding to COVID-19
As the COVID-19 pandemic presents increasing public health challenges, scientists from around the world have responded with openness and unprecedented speed, studying the SARS-CoV-2 virus and working to develop new diagnostic technologies, treatments, and tools for researchers. Scientists at the Broad Institute of MIT and Harvard are contributing to this global effort in a variety of ways.
Learn more about how Broad scientists are helping understand and track the virus's spread.
Epidemiology & Surveillance
The Broad Institute is sequencing the genetic code of SARS-CoV-2 viruses to monitor for known and emerging variants of concern, to support public health response to COVID-19. We strive to generate data in real time and share the findings with state public health officials and the CDC. We also share the genomic data immediately in public databases for the scientific community to access.
December 22, 2021
An outbreak of more than 1,000 COVID-19 cases in Provincetown last July raised many early questions about infection and transmission among vaccinated individuals. Broad's Viral Genomics group and SARS-CoV-2 sequencing team in the Genomics Platform, with contributions from across Broad and the MA Department of Public Health, analyzed genomic and epidemiological data from 467 people associated with the outbreak and found evidence supporting extensive transmission of the Delta variant from and between fully vaccinated persons. However, the outbreak contributed little to the broader surge of Delta cases in the US, likely due to high vaccination rates and the robust public health response.
December 20, 2021
New data suggest the Omicron variant is spreading as a new wave of COVID-19 infections continues in Massachusetts.
December 14, 2021
While the team launched new COVID-19 diagnostic and pathogen surveillance capabilities, they also analyzed more than 120,000 human genomes in 2021, with no slowdown in sight.
September 24, 2021
The partnership will facilitate the use of Terra — an open-source platform for biomedical data storage, analysis, and collaboration — in public health labs for genomic surveillance of SARS-CoV-2 and future outbreaks.
April 9, 2021
In partnership with the CDC, Broad scientists are analyzing SARS-CoV-2 genomes to look for known variants of concern, detect emerging ones, and support public health needs.
August 17, 2021 update: See Broad's COVID-19 Genomic Surveillance dashboard, which is updated weekly.
March 16, 2021
Amplicon-based sequencing is commonly used in SARS-CoV-2 genomic surveillance but has a high risk of contamination. Kim Lagerborg, Erica Normandin, Matthew Bauer, Steven Reilly, Katherine Siddle and colleagues have devised a new approach that uses synthetic DNA spike-ins (SDSIs) to track samples and detect inter-sample contamination. The team devised best practices for Illumina-based sequencing and ways to increase sensitivity for low-viral load samples incorporating SDSIs. The authors demonstrate the method in the real-time investigation of a suspected hospital cluster of SARS-CoV-2 cases.
March 14, 2021
Eric Alm and colleagues describe a nationwide campaign to monitor SARS-CoV-2 in the wastewater of 159 counties in 40 U.S. states, covering 13 percent of the U.S. population from February 18 to June 2, 2020. Wastewater viral titers were consistent with, and appeared to precede, clinical COVID-19 surveillance indicators, including daily new cases. The authors conclude that a national wastewater-based approach to disease surveillance may be feasible and effective.
August 26, 2020
William Allen, core institute member Feng Zhang, associate member Xihong Lin, and colleagues present an analysis of self-reported health, behavioral, exposure, and demographic information collected through How We Feel, a mobile- and web-based survey application. Their findings, based on responses from more than half a million users, provide a unique window into many aspects of users' experiences related to COVID-19, including risk factors, symptom history, and motivations for testing.
August 25, 2020
Jacob Lemieux, Katherine Siddle, and Bronwyn MacInnis of the lab of institute member Pardis Sabeti of Broad's Infectious Disease and Microbiome Program (IDMP) and Genomic Center for Infectious Diseases (GCID), and many colleagues used genomic epidemiology to track the introduction and spread of SARS-CoV-2 across the first wave of the epidemic in the Boston area. The team estimates that the virus entered the region at least 80 separate times, mostly from elsewhere in the US and from Europe. One of those introductions was linked to a superspreading event that led to massive community transmission across the city and to other states and countries. The team also investigated superspreading in other settings, including a single viral introduction into a nursing home that led to widespread transmission amongst residents and staff. A visual narrative summary of this work is available on nextstrain.org, and blog posts from the Sabeti lab’s research associates and volunteer project managers from Stanley Center for Psychiatric Research about their contributions to the work.
August 25, 2020
Colin Worby from Broad's IDMP and GCID and collaborator Hsiao-Han Chang (National Tsing Hua University, Taiwan) used epidemic models to examine the role of face masks in mitigating the spread of COVID-19 in the general population. They found that face masks, even with a limited protective effect, can reduce infections and deaths, and delay the peak time of the epidemic. Learn more in the NIH Director's Blog.
August 4, 2020
Andres Colubri, Pardis Sabeti, and collaborators at Harvard University and Brown University modeled the impact of university-level responses to past mumps outbreaks at Harvard in 2016 and at Ohio State University in 2014, and used the resulting insights to determine which control interventions are most effective. Their results suggest that universities should design more aggressive diagnostic procedures and stricter quarantine policies to reduce infectious disease incidence on their campuses.
July 27, 2020
Between April 9th and June 9th, 2020, the Broad Institute’s COVID-19 diagnostic laboratory worked in partnership with the Massachusetts Department of Public Health to test 32,480 residents and staff from 366 skilled nursing facilities, nursing homes, and assisted living facilities across the state, regardless of whether these individuals showed any symptoms.
In addition to forming a critical part of the state’s effort to combat the spread of disease among vulnerable populations, this effort generated a large dataset worth exploring — nearly 33,000 tests, all processed at a single lab using the same standards, connected to data about the presence of symptoms and demographics. Initial findings were shared in this blog post, including that individuals with and without symptoms at the time of testing have similar viral loads, suggesting significant transmission regardless of current symptom status.
July 6, 2020
Initial reports suggest that COVID-19 disproportionately afflicts historically disadvantaged populations. Associate member Amit Khera of the Program in Medical and Population Genetics, Aniruddh Patel, Manish Paranjpe, and colleagues, investigated associations between race, socioeconomic factors, and COVID-19 hospitalizations among 418,794 participants of the UK Biobank, 549 of whom had been hospitalized. The team found that both Black and Asian participants had an increased risk of COVID-19 hospitalization compared to white participants. Measures of socioeconomic deprivation and household income tracked with risk as well, but accounting for such measures only modestly attenuated risks in Black participants. The researchers write that whether this increased risk relates to differences in biologic factors such as host genetics, pre-existing comorbidities, testing or hospitalization patterns, or additional disparities in social determinants of health warrants further study.
June 4, 2020
Genomic data are a powerful new source of information about how viruses move through communities, and can help inform public health decisions. New data from the Broad’s viral genomics group — led by Jacob Lemieux and Bronwyn MacInnis, working in close partnership with colleagues from Massachusetts General Hospital and the Massachusetts Department of Public Health — provide insights into how SARS-CoV-2 entered and spread through the Boston area. The data suggest there were at least 30 independent introductions into the region from several international and domestic sources. It also sheds light on early superspreading events, including rapid and extensive transmission within a congregate living facility, and introduction and spread from an international conference that shaped the ongoing outbreak in Massachusetts.
May 6, 2020
Group testing, which involves combining samples from multiple individuals and testing as a single pool, may help expand diagnostic testing capacities. Broad Fellow Brian Cleary, associate member Michael Mina, core institute member Aviv Regev, and colleagues explored the effectiveness of group testing for SARS-CoV-2 using mathematical models of epidemic spread and viral kinetics. They identified designs that substantially increase the identification rate of infected individuals in resource-limited settings and accurately estimate overall prevalence with up to 400 times less testing, and confirmed their framework experimentally.
April 7, 2020
Testing wastewater for pathogens can complement estimates of an outbreak’s intensity and provide data for epidemiologic modeling. Core institute member Eric Alm and colleagues sampled wastewater from a Greater Boston-area treatment plant and found higher levels of SARS-CoV-2 RNA than would be expected based on confirmed COVID-19 case counts.
Update: June 23, 2020
In a longitudinal analysis led by Alm, the presence of SARS-CoV-2 RNA in wastewater from a Massachusetts facility increased exponentially from mid-March to mid-April 2020 and then declined, preceding a peak in clinical cases by 4-10 days. Monitoring wastewater may help identify early trends in disease transmission, and may shed light on infection characteristics that are difficult to capture in clinical investigations, such as early viral shedding dynamics.