ABSTRACT
COVID-19 outbreaks in local communities can result in a drastic surge in demand for scarce resources such as mechanical ventilators. To deal with such demand surges, many hospitals (1) purchased large quantities of mechanical ventilators, and (2) canceled/postponed elective procedures to preserve care capacity for COVID-19 patients. These measures resulted in a substantial financial burden to the hospitals and poor outcomes for non-COVID-19 patients. Given that COVID-19 transmits at different rates across various regions, there is an opportunity to share portable healthcare resources to mitigate capacity shortages triggered by local outbreaks with fewer total resources. This paper develops a novel data-driven adaptive robust simulation-based optimization (DARSO) methodology for optimal allocation and relocation of mechanical ventilators over different states and regions. Our main methodological contributions lie in a new policy-guided approach and an efficient algorithmic framework that mitigates critical limitations of current robust and stochastic models and make resource-sharing decisions implementable in real-time. In collaboration with epidemiologists and infectious disease doctors, we give proof of concept for the DARSO methodology through a case study of sharing ventilators among regions in Ohio and Michigan. The results suggest that our optimal policy could satisfy ventilator demand during the first pandemic's peak in Ohio and Michigan with 14% (limited sharing) to 63% (full sharing) fewer ventilators compared to a no sharing strategy (status quo), thereby allowing hospitals to preserve more elective procedures. Furthermore, we demonstrate that sharing unused ventilators (rather than purchasing new machines) can result in 5% (limited sharing) to 44% (full sharing) lower expenditure, compared to no sharing, considering the transshipment and new ventilator costs.
ABSTRACT
Background: Despite special global considerations which have been made to prioritize vaccination of people with multiple sclerosis (MS), some are reluctant to get vaccinated. This study was aimed to evaluate the attitude toward coronavirus disease -2019 (COVID-19) vaccine and its probable correlations.Methods: Considering the study objectives, two valid questionnaires including Fear of COVID-19 Scale (FCV-19S) and attitude questionnaires were administered pre and post COVID-19 vaccination among people with MS.Results: The questionnaires were administered among 349 people with MS pre and post vaccination. The mean age of participants was 38.78 +/- 8.68 (range: 19 to 64) years. They all received the first dose of COVID-19 vaccine (Sinopharm). Although about 90% of participants felt satisfied after getting vaccinated and respected the preventive actions like social distancing and wearing face mask after vaccination, about 40% of them did not recommend vaccination to other patients. None of the demographic data was predictor of attitude score in COVID-19 vaccine and the only effective factor regarding fear of COVID-19 among people with MS was gender (P = 0.001).
ABSTRACT
Objective(s): Type 1 Interferons (IFNs) modulate the antiviral immune response and have been used for the treatment of coronaviruses. This study aimed to determine any possible effects and safety concerns of the two most promising exogenously administrable interferons (IFNbeta1a and IFNbeta1b) on the severity outcomes of COVID-19 in multiple sclerosis (MS) patients hospitalized with COVID-19. Material(s) and Method(s): Using the electronic health records systems;this is a cross-sectional study of two years of hospital admissions in terms of COVID-19 in Iran from March 2019 to August 2021. The severities of COVID-19 outcomes were admitted to ICU, hospitalization days, and in-hospital mortality. MS patients with positive results from PCR were included. The data included demographic information, admission, and discharge dates, initial and final diagnoses, hospital inpatient services, including all drugs, admitted wards, procedures, and hospital mortality. A questionnaire was filled out with information on their MS diagnosis, MS medications at the time of COVID-19 admission, history of other chronic illnesses, history of smoking, height and weight, co-morbidity, and MS course (MS type, EDSS, MS duration) and disease-modifying therapies (DMT) at the time of COVID-19 admission (Rituximab, Fingolimod, IFNs, Glatiramer acetate, Dimethyl fumarate, Teriflunomide, Tysabri, and Azathioprine). Result(s): A total of 993 hospitalized MS patients were included in the study. IFNs were used in 28.8% of patients for the treatment of SARS-CoV-2 infection;26% IFNbeta1a and 3.5% IFNbeta1b. Among studied patients, 5.6% did not receive any DMT before their hospital admission. Almost half of the patients were under Rituximab(50.3%). The data were classified based on consuming DMTs. Except for patients who received Rituximab;there was not any significant association between taking IFNs and reducing the severity of COVID-19 outcomes in each DMT sub-group. In patients who were under Rituximab;taking IFNbeta1a for COVID-19 treatment had a significant association with longer hospitalization than patients not receiving it (median (IQR);8(7) vs. 6(4) days, respectively, p=0.000). In the logistic regression model, after adjusting confounding factors, there was a constant association between receiving IFNbeta1a and the risk of longer hospitalization (adjusted OR=2.46 95%CI: 1.46, 4.13). Conclusion(s): The current data suggest that MS healthcare providers should consider specific risks of exogenously IFNbeta1a for the treatment of COVID-19 based on MS medication therapies.Copyright © 2022