Background The Bacillus Calmette–Guérin (BCG) vaccine may confer cross‐protection against viral diseases in adults. This study evaluated BCG vaccine cross‐protection in adults with convalescent coronavirus disease 2019 (COVID‐19). Method This was a multicenter, prospective, randomized, placebo‐controlled, double‐blind phase III study (ClinicalTrials.gov: NCT04369794). Setting: University Community Health Center and Municipal Outpatient Center in South America. Patients: a total of 378 adult patients with convalescent COVID‐19 were included. Intervention: single intradermal BCG vaccine ( n = 183) and placebo ( n = 195). Measurements: the primary outcome was clinical evolution. Other outcomes included adverse events and humoral immune responses for up to 6 months. Results A significantly higher proportion of BCG patients with anosmia and ageusia recovered at the 6‐week follow‐up visit than placebo (anosmia: 83.1% vs. 68.7% healed, p = 0.043, number needed to treat [NNT] = 6.9; ageusia: 81.2% vs. 63.4% healed, p = 0.032, NNT = 5.6). BCG also prevented the appearance of ageusia in the following weeks: seven in 113 (6.2%) BCG recipients versus 19 in 126 (15.1%) placebos, p = 0.036, NNT = 11.2. BCG did not induce any severe or systemic adverse effects. The most common and expected adverse effects were local vaccine lesions, erythema ( n = 152; 86.4%), and papules ( n = 111; 63.1%). Anti–severe acute respiratory syndrome coronavirus 2 humoral response measured by N protein immunoglobulin G titer and seroneutralization by interacting with the angiotensin‐converting enzyme 2 receptor suggest that the serum of BCG‐injected patients may neutralize the virus at lower specificity; however, the results were not statistically significant. Conclusion BCG vaccine is safe and offers cross‐protection against COVID‐19 with potential humoral response modulation. Limitations: No severely ill patients were included.

No abstract

Introduction: Heath care workers with direct (HCW-D) or indirect (HCW-A) patient contact represent 4.2% to 17.8% of COVID-19 cases. We evaluate the temporal COVID-19 infection behavior among HCW-D, HCW-A, and non-HCW. Methods: From February 2020 to April 2021, trained nurses recorded age, gender, occupation, and symptoms in a COVID-19 testing outpatient health center. We allocated data into weekly time fractals and calculated the proportion of COVID-19 positive among HCW vs. non-HCW and incorporated an ARFIMA model (traditionally used in weather forecast) to predict future cases of COVID-19. Results: Among 8,998 COVID-19 RT-PCR tests, 3,462 (42%) patients were HCW-D, and 933 (11%) were HCW-A. Overall, 1,914 (21.3%) returned positive, representing 27%, 25% and 19% of HCW-D, HCW-A and non-HCW, respectively. HCW-D or HCW-A were significantly more likely to test positive for COVID-19 than non-HCW (OR=1.5, p<0.0001). The percentage of positive to negative test results remained steady over time. In the positive cases, the percentage of HCW to non-HCW declined significantly over time (Mann-Kendal trend test: tau=-0.58, p<0.0001). Our ARFIMA model showed a long-memory infection pattern in the occurrence of new COVID-19 cases lasting for months. Average error was 1.9 cases per week comparing predicted to actual values three months later (May-July 2021). Conclusion: HCW have a sustained 50% higher risk of COVID-19 positivity in the pandemic. Time-series analysis showed a long-memory infection pattern with virus spread mainly among HCWs before the general population. The tool http://wdchealth.covid-map.com/shiny/covid-map/ will be updated according to population previous infection and vaccination impact.

Purpose: To develop a reliable tool that predicts which patients are most likely to be COVID-19 positive and which ones have an increased risk of hospitalization. Methods: From February 2020 to April 2021, trained nurses recorded age, gender, and symptoms in an outpatient COVID-19 testing center. All positive patients were followed up by phone for 14 days or until symptom-free. We calculated the symptoms odds ratio for positive results and hospitalization and proposed a random forest machine-learning model to predict positive testing. Results: A total of 8,998 patients over 16 years old underwent COVID-19 RT-PCR, with 1,914 (21.3%) positives. Fifty patients needed hospitalization (2.6% of positives), and three died (0.15%). Most common symptoms were: cough, headache, sore throat, coryza, fever, myalgia (57%, 51%, 44%, 36%, 35%, 27%, respectively). Cough, fever, and myalgia predicted positive COVID-19 test, while others behaved as protective factors. The best predictors of positivity were fever plus anosmia/ageusia (OR=6.31), and cough plus anosmia/ageusia (OR=5.82), both p<0.0001. Our random forest model had an ROC-AUC of 0.72 (specificity=0.70, sensitivity=0.61, PPV=0.38, NPV=0.86). Having steady fever during the first days of infection and persistent dyspnea increased the risk of hospitalization (OR=6.66, p<0.0001 and OR=3.13, p=0.003, respectively), while anosmia-ageusia (OR=0.36, p=0.009) and coryza (OR=0.31, p=0.014) were protective. Conclusion: Present study and algorithm may help identify patients at higher risk of having SARS-COV-2 (online calculator http://wdchealth.covid-map.com/shiny/calculator/), and also disease severity and hospitalization based on symptoms presence, pattern, and duration, which can help physicians and health care providers.

Aim: We previously published results of the BATTLE trial, showing that patients recently infected with SARS-CoV-2 can benefit from receiving Bacillus Calmette-Guérin (BCG) with minimal adverse effects. The study incorporated two strains of this vaccine. In this study, patient outcomes were compared based on the strain of BCG because different strains have been shown to have different immunogenicity. Methods: BATTLE was a double-blind controlled trial of COVID-19 convalescent patients; symptom progression, injection-site lesion characteristics and adverse effects were compared between recipients of placebo, Russian BCG strain or Brazilian BCG strains. Results: There was no statistically significant difference between the two BCG strains in terms of symptom progression, lesion-size or type. Conclusion: The two strains have similar clinical outcomes in COVID-19 convalescent patients.