Navigating hospitals safely through the COVID-19 epidemic tide: Predicting case load for adjusting bed capacity.

BACKGROUND: The pressures exerted by the coronavirus disease 2019 (COVID-19) pandemic pose an unprecedented demand on healthcare services. Hospitals become rapidly overwhelmed when patients requiring life-saving support outpace available capacities. OBJECTIVE: We describe methods used by a university hospital to forecast case loads and time to peak incidence. METHODS: We developed a set of models to forecast incidence among the hospital catchment population and to describe the COVID-19 patient hospital-care pathway. The first forecast utilized data from antecedent allopatric epidemics and parameterized the care-pathway model according to expert opinion (ie, the static model). Once sufficient local data were available, trends for the time-dependent effective reproduction number were fitted, and the care pathway was reparameterized using hazards for real patient admission, referrals, and discharge (ie, the dynamic model). RESULTS: The static model, deployed before the epidemic, exaggerated the bed occupancy for general wards (116 forecasted vs 66 observed), ICUs (47 forecasted vs 34 observed), and predicted the peak too late: general ward forecast April 9 and observed April 8 and ICU forecast April 19 and observed April 8. After April 5, the dynamic model could be run daily, and its precision improved with increasing availability of empirical local data. CONCLUSIONS: The models provided data-based guidance for the preparation and allocation of critical resources of a university hospital well in advance of the epidemic surge, despite overestimating the service demand. Overestimates should resolve when the population contact pattern before and during restrictions can be taken into account, but for now they may provide an acceptable safety margin for preparing during times of uncertainty.

[Subjective well-being and ability to work of hospital staff after SARS-CoV2 immunization with the mRNA vaccine BNT162b2]. / Subjektives Wohlbefinden und Arbeitsfähigkeit von Krankenhauspersonal nach SARS-CoV-2-Immunisierung mit dem mRNS-Impfstoff BNT162b2 ­ Ergebnisse einer anonymen Umfrage.

BACKGROUND: Since December 27, 2020, employees of the health system in Germany have been vaccinated against the SARS coronavirus-2 with the vaccine BNT162B2. Initial observations show that especially among younger vaccinated people side effects are common. In this study, using the example of clinic employees, the self-perceived well-being after the first and second dose of the vaccine was examined. METHODS: Anonymized online questionnaire to be filled out once by all employees after the second dose of BNT162B2 was offered. The severity of side effects was queried using an ordinal numerical rating scale with values between 0 and 10. Other key data points were age, gender, and occupational group. The ability to work in the days following the injections was recorded by self-reporting. RESULTS: Data from 555 respondents were evaluated. The mean age was 40.25 years (standard deviation 12.35). 56 % of the respondents were female, 44.3 % belonged to the medical service, 42.9 % to the nursing service and 12.8 % were assigned to other professional groups with COVID-19 patient contact. Around 2 % of all employees did not experience any side effects at all. The most common side effect was pain at the injection site. Fatigue, headaches and myalgia followed with decreasing frequency. After the first dose, ¾ of the respondents said they had tolerated the vaccination well overall, after the second dose it was only half. After the first dose, over 90 % of the respondents felt that they were able to work again on the following day, after the second dose one third stated that they were only able to work again on the second day. 2.2 % of all employees had to report that they were unable to work for at least one day after the first dose and 19.5 % after the second dose. CONCLUSIONS: Vaccination with BNT162B2 frequently leads to side effects, especially after the second dose. Perception of side effects resulted in 19 % of those questioned being sick after the second dose. Nevertheless, 95 % of all respondents would choose a coronavirus vaccination again.

Pandemic-Driven Development of a Medical-Grade, Economic and Decentralized Applicable Polyolefin Filament for Additive Fused Filament Fabrication.

A polyolefin with certified biocompatibility according to USP class VI was used by our group as feedstock for filament-based 3D printing to meet the highest medical standards in order to print personal protective equipment for our university hospital during the ongoing pandemic. Besides the chemical resistance and durability, as well as the ability to withstand steam sterilization, this polypropylene (PP) copolymer is characterized by its high purity, as achieved by highly efficient and selective catalytic polymerization. As the PP copolymer is suited to be printed with all common printers in fused filament fabrication (FFF), it offers an eco-friendly cost-benefit ratio, even for large-scale production. In addition, a digital workflow was established focusing on common desktop FFF printers in the medical sector. It comprises the simulation-based optimization of personalized print objects, considering the inherent material properties such as warping tendency, through to validation of the process chain by 3D scanning, sterilization, and biocompatibility analysis of the printed part. This combination of digital data processing and 3D printing with a sustainable and medically certified material showed great promise in establishing decentralized additive manufacturing in everyday hospital life to meet peaks in demand, supply bottlenecks, and enhanced personalized patient treatment.