Fairness and COVID: Conducting research during the crisis.

The COVID-19 pandemic forced Principal Investigators (PIs) to make rapid and unprecedented decisions about ongoing research projects and research teams. Confronted with vague or shifting guidance from institutional administrators and public health officials, PIs nonetheless had to decide whether their projects were "essential," who could conduct on-site "essential" research, how to continue research activities by remote means if possible, and how to safely and effectively manage personnel during the crisis. Based on both narrative comments from a federally sponsored survey of over a thousand NIH- and NSF-funded PIs and their personnel, as well as follow-up interviews with over 60 survey participants, this study examines various ways PI and institutional decisions raised issues of procedural and distributive fairness. These fairness issues include the challenge of treating research personnel fairly in light of their disparate personal circumstances and inconsistent enforcement of COVID-19-related directives. Our findings highlight aspects of fairness and equitability that all PIs and research administrators should keep in mind for when future research disruptions occur.

Principal Investigators' Priorities and Perceived Barriers and Facilitators When Making Decisions About Conducting Essential Research in the COVID-19 Pandemic.

At the onset of the COVID-19 pandemic in the United States, stay-at-home orders disrupted normal research operations. Principal investigators (PIs) had to make decisions about conducting and staffing essential research under unprecedented, rapidly changing conditions. These decisions also had to be made amid other substantial work and life stressors, like pressures to be productive and staying healthy. Using survey methods, we asked PIs funded by the National Institutes of Health and the National Science Foundation (N = 930) to rate how they prioritized different considerations, such as personal risks, risks to research personnel, and career consequences, when making decisions. They also reported how difficult they found these choices and associated symptoms of stress. Using a checklist, PIs indicated those factors in their research environments that made their decisions easier (i.e., facilitators) or more difficult (i.e., barriers) to make. Finally, PIs also indicated how satisfied they were with their decisions and management of research during the disruption. Descriptive statistics summarize PIs' responses and inferential tests explore whether responses varied by academic rank or gender. PIs overall reported prioritizing the well-being and perspectives of research personnel, and they perceived more facilitators than barriers. Early-career faculty, however, rated concerns about their careers and productivity as higher priorities compared to their senior counterparts. Early-career faculty also perceived greater difficulty and stress, more barriers, fewer facilitators, and had less satisfaction with their decisions. Women rated several interpersonal concerns about their research personnel more highly than men and reported greater stress. The experience and perceptions of researchers during the COVID-19 pandemic can inform policies and practices when planning for future crises and recovering from the pandemic.

Enabling Hotspot Detection and Public Health Response to the COVID-19 Pandemic.

INTRODUCTION: Public-facing maps of COVID-19 cases, hospital admissions, and deaths are commonly displayed at the state, county, and zip code levels, and low case counts are suppressed to protect confidentiality. Public health authorities are tasked with case identification, contact tracing, and canvasing for educational purposes during a pandemic. Given limited resources, authorities would benefit from the ability to tailor their efforts to a particular neighborhood or congregate living facility. METHODS: We describe the methods of building a real-time visualization of patients with COVID-19-positive tests, which facilitates timely public health response to the pandemic. We developed an interactive street-level visualization that shows new cases developing over time and resolving after 14 days of infection. Our source data included patient demographics (ie, age, race and ethnicity, and sex), street address of residence, respiratory test results, and date of test. RESULTS: We used colored dots to represent infections. The resulting animation shows where new cases developed in the region and how patterns changed over the course of the pandemic. Users can enlarge specific areas of the map and see street-level detail on residential location of each case and can select from demographic overlays and contour mapping options to see high-level patterns and associations with demographics and chronic disease prevalence as they emerge. CONCLUSIONS: Before the development of this tool, local public health departments in our region did not have a means to map cases of disease to the street level and gain real-time insights into the underlying population where hotspots had developed. For privacy reasons, this tool is password-protected and not available to the public. We expect this tool to prove useful to public health departments as they navigate not only COVID-19 pandemic outcomes but also other public health threats, including chronic diseases and communicable disease outbreaks.