Four projects focused on describing the clinical predictors, characteristics, and consequences of SARS-CoV-2 infection (Chan, Dougan, Moorman, Morrow). Most of these were conducted among health care workers at local hospitals, although one involved a 6-hospital consortium (Morrow) and one was population-based (Chan). Together, these studies provided early clinical descriptions of the disease, pinpointing anosmia as a distinguishing symptom and identifying racial/ethnic minorities and cancer patients as among those most at risk. Other findings included the lack of association between COPD and asthma and increased Covid risk, the protective effects of masking, and the safety of non-steroidal anti-inflammatory drugs for Covid patients. The Morrow group documented the very high risk of new onset acute heart failure (10%) among Covid patients admitted to ICUs and the association of a set of circulating proteins associated with inflammation/apoptosis and angiogenesis. Several of these studies led to collaborations both within and outside the investigators’ institutions that have resulted in subsequent projects and funding. Final results of some of these projects, particularly those that require collaboration with basic science laboratories, are still being processed.
Four of the funded projects developed innovative methods and platforms for Covid surveillance and monitoring. These included the development of Global.health (Brownstein), a centralized open resource of verified Covid case-level data from around the world that currently includes detailed data on over 100 million Covid patients from over 100 countries. The investigators built new tools to enable access to the dataset to partners and to provide country-level data visualizations. Similar tools are currently being built for monkeypox. Another team (Erickson) modified a tool that had been created to monitor opioids in wastewater to detect the presence and quantity of Covid in urban wastewater in order to provide an anonymized and rapid way to follow local epidemic trends. This tool has now been widely used throughout the world as an early warning system to detect viral transmission and is considered to be a more reliable of local infection burden than more conventional case counting approaches. A third team (Chan) developed a digital tool through which to conduct large population-based cohort studies, thus contributing both to the early description of Covid related symptoms and outcomes as well as innovative methods for large, real-time epidemiologic studies. Lastly, one group (Reich) developed a novel visualization pipeline to track the global and regional prevalence of Covid-19 mutations; this tool identifies mutations and presents the timeline on which they arise on various geographical scales, thereby allowing researchers to identify potential candidate variants that should be monitored closely. Each of these surveillance tools has the potential to be deployed for surveillance of other potential pandemic pathogens and several are already being modified to address new pandemic threats.
Two studies focused on the mental health and behavioral aspects of lockdown and pandemic fear during the pandemic. One of these (Patel) focused on survey data from Harvard University students and found that graduate students were at particularly high risk of negative mental health consequences of the pandemic. The second (Zheng) took a very different approach by developing tools to quantify and analyze global social media posts to assess trends in affective states or “expressed sentiment.” This project showed that while the early pandemic led to steep declines in expressed sentiment, these did not directly correlate with lockdowns.
One study developed a model to quantify US hospital capacity (ICU surge, hospital beds, and ventilators) for Covid, which has resulted in several publications as well as a publicly accessible dashboard (the COVID-19 Risk-Level Dashboard) that has played a role in informing local communities about their Covid risk and local medical capacity. Finally, one study (Murray) developed an approach to studying re-purposed vaccines (BCG) for Covid and other potential pathogens and built clinical trials networks in nursing homes in the US and Asia.
Many of these projects would not have happened without MassCPR support. This was especially true for well-established research groups whose focus was not previously in infectious disease epidemiology but which pivoted to work on Covid in the context of the pandemic. These projects often resulted in new collaborations – both locally within the Massachusetts research community and globally, within national and global research networks. For example, the Chan group partnered with an international consortium that collected data from participants in the US, UK, and Sweden, and the Erickson project developed a robust national network that allowed the team to roll out waste water testing as routine surveillance in the US. While many of these projects went on to obtain further funding for these efforts from US and international research funders, the MassCPR awards occurred early enough to kickstart many of these projects.
