COVID-19 and the academy: opinions and experiences of university-based scientists in the U.S.

The COVID-19 pandemic has had profound effects on public health and the economy worldwide, with the United States experiencing a disproportionate burden. Reports indicate restricted access to university facilities and resources, reduced time spent on research, decreased international collaboration, diverted resources from other priorities, and potential compromises to peer review and scientific standards as efforts shifted toward COVID-19. Concerns have been raised that long-term impacts on scientific productivity may disproportionately affect women, people of color, early-career researchers, those with childcare responsibilities, and graduate students. Simultaneously, the pandemic spurred rapid monitoring, diagnostic, and vaccine research, raising debates about privacy risks associated with surveillance technologies and the public health implications of expedited governmental approval processes. This study reports findings from a probability-based sample survey of U.S. university-based biologists, biochemists, and civil and environmental engineers (n ≈ 362) on the impacts of COVID-19 on research productivity and differences by gender, academic rank, and hotspot status.

Prior literature, largely anecdotal or discipline-specific, documents widespread disruptions to academic research during COVID-19, including restricted access to on-campus facilities, declines in research time, reduced international collaborations, diversion of resources, and risks to peer review standards. Emerging evidence suggests disproportionate impacts on women, persons of color, early-career researchers, those with childcare responsibilities, and graduate students. Parallel discussions in public discourse and scholarship highlight tensions between the benefits of rapid deployment of surveillance technologies and diagnostics/vaccines and the associated risks to privacy and safety when regulatory processes are expedited. These strands motivate systematic, representative inquiry into how scientists have been affected and how they view policy trade-offs during the pandemic.

Survey Design: The author team developed a 67-item instrument in March 2020 covering impacts on research (39 items), participation in COVID-19 research (6 items), opinions about COVID-19 research and impacts (6 items), and personal exposure to COVID-19 (5 items). Average completion time was 21.1 minutes (SD = 2.4). Institutional Review Boards at Arizona State University and the University of Illinois at Chicago approved the study.

Sample Design: A one-stage cluster sample was constructed by identifying all R1 Carnegie research-intensive institutions (n = 131) and randomly selecting 20 universities proportionately across eight Carnegie regions, ensuring representation of multiple states per region. Faculty lists were compiled for biology, civil and environmental engineering, and biochemistry/genomics departments, including non-tenure track, tenure-track, and tenured faculty. These faculty constituted the survey sample frame.

Survey Administration: The online survey (Sawtooth Software) was fielded in May 2020 with personalized email invitations and reminders. Messages were sent in late April; the main invitation went out May 7 with three reminders, and data collection closed May 28. A stated administration reported 168 invited and 96 completes (AAPOR RR = 29.6%). The completed sample was weighted by gender and academic field. A conservative sampling error for full-sample estimates was ±25 percentage points.

Geographic Classification: Respondents’ employing institutions were classified by county COVID-19 “hotspot” status (CDC definition) during March 8–May 31, 2020. In this dataset, 56.6% of scientists were employed in hotspot counties.

Analytic Approach: Weighted descriptive statistics summarize results. Crosstabulations and chi-square tests (χ²) compare responses by gender, academic rank, and hotspot status. To adjust for multiple comparisons, only differences with p < 0.001 are reported as significant. A nonresponse bias analysis compared respondents (n = 362) to the full sample (n = 1,968), with weighting used to improve representativeness.

• Prevalence of impacts: Virtually all scientists (98%) reported some negative COVID-19 impacts; 93% reported at least one major negative impact. About half (52%) reported at least one positive impact, while 17% reported a major positive impact.
• Most common negative impact: University closures were cited by 93% of scientists as a negative impact (abstract). Reported major disruptions included lab work disruptions and closures, student employment disruptions (45%), and collaboration disruptions (40%). Minor negative impacts commonly included publishing/dissemination disruptions (43%).
• Gender differences: Women were significantly more likely than men to report difficulty concentrating on research during stay-at-home orders (χ² = 12.6, df = 1, p < 0.001). Approximately 50% of women reported severe disturbance to research time versus less than one-third of men.
• Rank differences: Assistant professors were significantly more likely to report unexpected childcare responsibilities (χ² = 23.62, df = 1, p < 0.001) and difficulties focusing on research (χ² = 13.9, df = 1, p < 0.001) as major impacts.
• Hotspot status: Scientists in hotspot counties generally did not report disproportionate impacts overall, though they were somewhat more likely to report major difficulties concentrating on research (e.g., 22%).
• Contributions to pandemic response: 21% contributed expertise to address the pandemic. About 18% contributed resources or collaboration to the scientific community (e.g., providing lab supplies, collaborating on experiments, reviewing findings). Thirteen percent engaged with the public (e.g., media responses, interpreting research). No significant differences by gender, rank, or hotspot at p < 0.001.
• Policy views on surveillance and FDA processes: 53% viewed surveillance technologies as necessary but in need of better regulation; 11% said use depends on the situation. A majority judged benefits to outweigh risks for suspending some FDA processes to expedite vaccine testing diagnostics (63%) and prior-infection diagnostics (54%). Opinions were more divided on expediting vaccine availability: 43% benefits outweigh risks vs 35% risks outweigh benefits. On the ethics of bypassing some approval processes to distribute a vaccine more quickly, 31% deemed it unethical, 29% ethical, and 40% said it depends on the situation.
• Nonresponse profile (selected): Respondents vs frame suggested modest over-representation of females and assistant professors and under-representation of associates/full professors; weighting aligned respondent distributions more closely with the frame.

The study documents widespread negative impacts of COVID-19 on academic scientists’ research, with more than 90% reporting at least one major disruption. Differences by gender and rank are pronounced: women more frequently reported difficulties concentrating on research, and assistant professors reported greater childcare burdens and problems focusing, consistent with concerns about disproportionate pandemic effects on women and early-career researchers. These disparities imply potential long-term consequences for research productivity, funding, and career progression, particularly for early-career women in STEM. Universities and funders may need to implement targeted supports (e.g., tenure clock extensions, dedicated funding for women and early-career researchers, childcare support, and workload monitoring) to mitigate inequities.

Despite pervasive disruptions, about half of scientists reported at least one positive impact, underscoring resilience and adaptability and the value of understanding both negative and positive effects across scientific fields. On regulatory and technology policy, the academic scientific community is not monolithic: while many support regulated use of surveillance technologies and selective suspension of FDA processes for diagnostics, opinions are more divided on accelerating vaccine availability and the ethics of bypassing approval steps. This diversity of views reflects the complexity of risk–benefit trade-offs during public health emergencies.

This probability-based survey of U.S. university-based biologists, biochemists, and civil and environmental engineers provides representative evidence that COVID-19 produced widespread negative impacts on academic research, with notable disparities by gender and academic rank. At the same time, many scientists experienced positive impacts, highlighting community resilience. Scientists’ policy views reveal support for regulated surveillance and expedited diagnostics approval, but divided opinions on accelerating vaccine availability and bypassing formal approval processes.

Institutions and funders should consider interventions to buffer vulnerable groups—particularly women and early-career faculty—through measures such as tenure and grant timeline flexibility, targeted funding opportunities, childcare support, and monitoring of service/teaching loads. Future research should expand beyond the studied disciplines to encompass broader fields, and examine intersections of race, gender, and caregiving responsibilities to better understand and address inequities intensified by the pandemic.

• Scope: The study focuses on biologists, biochemists, and civil and environmental engineers; findings may not generalize to all disciplines.
• Demographic measures: Race and ethnicity were not collected, preventing analyses of differential impacts across these groups.
• Response and sampling: Reported response rates and sample sizes vary across sections (e.g., 96 completes in one administration detail versus 362 respondents in nonresponse analysis). Although weighting by gender and field was applied, nonresponse bias may remain. A conservative sampling error of ±25 percentage points indicates wide confidence intervals for some estimates.
• Timing and context: Data were collected in May 2020 during early pandemic phases; impacts and perceptions may have evolved subsequently.
• Hotspot classification: County-level hotspot status may not capture within-county heterogeneity in exposure or institutional policies.