Prospective Assessment of Symptoms to Evaluate Asymptomatic SARS-CoV-2 Infections in a Cohort of Health Care Workers.

BACKGROUND: The frequency of asymptomatic severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections is unclear and may be influenced by how symptoms are evaluated. In this study, we sought to determine the frequency of asymptomatic SARS-CoV-2 infections in a prospective cohort of health care workers (HCWs). METHODS: A prospective cohort of HCWs, confirmed negative for SARS-CoV-2 exposure upon enrollment, were evaluated for SARS-CoV-2 infection by monthly analysis of SARS-CoV-2 antibodies as well as referral for polymerase chain reaction testing whenever they exhibited symptoms of coronavirus disease 2019 (COVID-19). Participants completed the standardized and validated FLU-PRO Plus symptom questionnaire scoring viral respiratory disease symptom intensity and frequency at least twice monthly during baseline periods of health and each day they had any symptoms that were different from their baseline. RESULTS: Two hundred sixty-three participants were enrolled between August 25 and December 31, 2020. Through February 28, 2021, 12 participants were diagnosed with SARS-CoV-2 infection. Symptom analysis demonstrated that all 12 had at least mild symptoms of COVID-19, compared with baseline health, near or at time of infection. CONCLUSIONS: These results suggest that asymptomatic SARS-CoV-2 infection in unvaccinated, immunocompetent adults is less common than previously reported. While infectious inoculum doses and patient factors may have played a role in the clinical manifestations of SARS-CoV-2 infections in this cohort, we suspect that the high rate of symptomatic disease was due primarily to participant attentiveness to symptoms and collection of symptoms in a standardized, prospective fashion. These results have implications for studies that estimate SARS-CoV-2 infection prevalence and for public health measures to control the spread of this virus.

Identifying Nontraditional Epidemic Disease Risk Factors Associated with Major Health Events from World Health Organization and World Bank Open Data.

Health events emerge from host, community, environment, and pathogen factors-forecasting epidemics is a complex task. We describe an exploratory analysis to identify economic risk factors that could aid epidemic risk assessment. A line list was constructed using the World Health Organization Disease Outbreak News (2016-2018) and economic indicators from the World Bank. Poisson regression employing forward imputations was used to establish relationships with the frequency with which countries reported public health events. Economic indicators demonstrated strong performance appropriate for further assessment in surveillance programming. In our analysis, three economic indicators were significantly associated to event reporting: how much the country's urban population changed, its average forest area, and a novel economic indicator we developed that assessed how much the gross domestic product changed per capita. Other economic indicators performed less well: changes in total, female, urban, and rural population sizes; population density; net migration; change in per cent forest area; total forest area; and another novel indicator, change in percent of trade as a fraction of the total economy. We then undertook a further analysis of the start of the current COVID-19 pandemic that revealed similar associations, but confounding by global disease burden is likely. Continued development of forecasting approaches capturing information relevant to whole-of-society factors (e.g., economic factors as assessed in our study) could improve the risk management process through earlier hazard identification and inform strategic decision processes in multisectoral strategies to preventing, detecting, and responding to pandemic-threat events.

Prospective Assessment of SARS-CoV-2 Seroconversion (PASS) study: an observational cohort study of SARS-CoV-2 infection and vaccination in healthcare workers.

BACKGROUND: SARS-CoV-2 is a recently emerged pandemic coronavirus (CoV) capable of causing severe respiratory illness. However, a significant number of infected people present as asymptomatic or pauci-symptomatic. In this prospective assessment of at-risk healthcare workers (HCWs) we seek to determine whether pre-existing antibody or T cell responses to previous seasonal human coronavirus (HCoV) infections affect immunological or clinical responses to SARS-CoV-2 infection or vaccination. METHODS: A cohort of 300 healthcare workers, confirmed negative for SARS-CoV-2 exposure upon study entry, will be followed for up to 1 year with monthly serology analysis of IgM and IgG antibodies against the spike proteins of SARS-CoV-2 and the four major seasonal human coronavirus - HCoV-OC43, HCoV-HKU1, HCoV-229E, and HCoV-NL63. Participants will complete monthly questionnaires that ask about Coronavirus Disease 2019 (COVID-19) exposure risks, and a standardized, validated symptom questionnaire (scoring viral respiratory disease symptoms, intensity and severity) at least twice monthly and any day when any symptoms manifest. SARS-CoV-2 PCR testing will be performed any time participants develop symptoms consistent with COVID-19. For those individuals that seroconvert and/or test positive by SARS-CoV-2 PCR, or receive the SARS-CoV-2 vaccine, additional studies of T cell activation and cytokine production in response to SARS-CoV-2 peptide pools and analysis of Natural Killer cell numbers and function will be conducted on that participant's cryopreserved baseline peripheral blood mononuclear cells (PBMCs). Following the first year of this study we will further analyze those participants having tested positive for COVID-19, and/or having received an authorized/licensed SARS-CoV-2 vaccine, quarterly (year 2) and semi-annually (years 3 and 4) to investigate immune response longevity. DISCUSSION: This study will determine the frequency of asymptomatic and pauci-symptomatic SARS-CoV-2 infection in a cohort of at-risk healthcare workers. Baseline and longitudinal assays will determine the frequency and magnitude of anti-spike glycoprotein antibodies to the seasonal HCoV-OC43, HCoV-HKU1, HCoV-229E, and HCoV-NL63, and may inform whether pre-existing antibodies to these human coronaviruses are associated with altered COVID-19 disease course. Finally, this study will evaluate whether pre-existing immune responses to seasonal HCoVs affect the magnitude and duration of antibody and T cell responses to SARS-CoV-2 vaccination, adjusting for demographic covariates.

Radiation exposure and cost influence physician medical image decision making: a randomized controlled trial.

BACKGROUND: It is estimated that 20%-40% of advanced medical imaging in the United States is unnecessary, resulting in patient overexposure to radiation and increasing the cost of care. Previous imaging utilization studies have focused on clinical appropriateness. An important contributor to excessive use of advanced imaging may be a physician "knowledge gap" regarding the safety and cost of the tests. OBJECTIVES: To determine whether safety and cost information will change physician medical image decision making. RESEARCH DESIGN: Double-blinded, randomized controlled trial. Following standardized case presentation, physicians made an initial imaging choice. This was followed by the presentation of guidelines, radiation exposure and health risk, and cost information. RESULTS: Approximately half (57 of 112, 50.9%) of participants initially selected computed tomography (CT). When presented with guideline recommendations, participants did not modify their initial imaging choice (P=0.197). A significant reduction (56.3%, P<0.001) in CT ordering occurred after presentation of radiation exposure/health risk information; ordering changed to magnetic resonance imaging or ultrasound (US). A significant reduction (48.3%, P<0.001) in CT and magnetic resonance imaging ordering occurred after presentation of Medicare reimbursement information; ordering changed to US. The majority of physicians (31 of 40, 77.5%) selecting US never modified their ordering. No significant relationship between physician demographics and decision making was observed. CONCLUSIONS: This study suggests that physician decision making can be influenced by safety and cost information and the order in which information is provided to physicians can affect their decisions.