COVID-19 Infection and Symptoms Among Emergency Medicine Residents and Fellows in an Urban Academic Hospital Setting: Cross-sectional Questionnaire Study
Why this work is in the frame
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Bibliographic record
Abstract
Background COVID-19, an illness caused by the novel coronavirus SARS-CoV-2, affected many aspects of health care worldwide in 2020. From March to May 2020, New York City experienced a large surge of cases. Objective The aim of this study is to characterize the prevalence of illness and symptoms experienced by residents and fellows in 2 New York City hospitals during the period of March to May 2020. Methods An institutional review board–exempt survey was distributed to emergency medicine housestaff in May 2020, and submissions were accepted through August 2020. Results Out of 104 residents and fellows, 64 responded to our survey (a 61.5% response rate). Out of 64 responders, 27 (42%) tested positive for SARS-CoV-2 antibodies. Most residents experienced symptoms that are consistent with COVID-19; however, few received polymerase chain reaction testing. Out of 27 housestaff with SARS-CoV-2 antibodies, 18 (67%) experienced fever and chills, compared with 8 out of 34 housestaff (24%) without SARS-CoV-2 antibodies. Of the 27 housestaff with SARS-CoV-2 antibodies, 19 (70%) experienced loss of taste and smell, compared with 2 out of 34 housestaff (6%) without SARS-CoV-2 antibodies. Both fever and chills and loss of taste and smell were significantly more commonly experienced by antibody-positive compared to antibody-negative housestaff (P=.002 and <.001, respectively). All 13 housestaff who reported no symptoms during the study period tested negative for SARS-CoV-2 antibodies. Conclusions Our study demonstrated that in our hospitals, the rate of COVID-19 illness among emergency department housestaff was much higher than previously reported. Further studies are needed to characterize illness among medical staff in emergency departments across the nation. The high infection rate among emergency medicine trainees stresses the importance of supplying adequate personal protective equipment for health care professionals.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it