Respiratory viral infections, including severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), are among the most common illnesses and a leading cause of morbidity and mortality worldwide. Due to the severe effects on health, the need of new tools to study the pathogenesis of respiratory viruses as well as to test for new antiviral drugs and vaccines is urgent. In vitro culture model systems, such as three-dimensional (3D) cultures, are emerging as a desirable approach to understand the virus host interactions and to identify novel therapeutic agents. In the first part of the article, we address the various scaffold-free and scaffold-based 3D culture models such as hydrogels, bioreactors, spheroids and 3D bioprinting as well as present their properties and advantages over conventional 2D methods. Then, we review the 3D models that have been used to study the most common respiratory viruses including influenza, parainfluenza, respiratory syncytial virus (RSV) and coronaviruses. Herein, we also explain how 3D models have been applied to understand the novel SARS-CoV-2 infectivity and to develop potential therapies.

Background: Little has been published on predictors of prolonged sick leaves during the COVID-19 pandemic. This study aims to determine the rate of COVID-19 infections among healthcare workers (HCWs) and to identify the predictors of longer sick leave days. Methods: We identified predictors of longer sick leave using linear regression analysis in a cross-sectional study design. Results: Thirty-three percent of the total workforce contracted COVID-19. On average, HCWs took 12.5 sick leave days after COVID-19 infection. The regression analysis revealed that older employees, nurses, and those who caught COVID-19 earlier in the pandemic were more likely to take longer sick leave. Conclusions: Age, job position, and month of infection predicted sick leave duration among HCWs in our sample. Results imply that transmission was most likely community-based. Public health interventions should consider these factors when planning for future pandemics.

Background: The COVID-19 pandemic strained healthcare systems around the world. This study aims to understand the preparedness of private remote hospitals in Lebanon to respond to the pandemic and evaluate the impact of inter-hospital collaborations on the hospitals’ readiness. Methods: A multi-centered study was conducted between August 2020 and June 2021 in ten Lebanese private remote hospitals based on a mixed-methods embedded approach where the quantitative supported the qualitative. Through the AUB-USAID (American University of Beirut-United States Agency for International Development) COVID-19 project, these hospitals received personal protective equipment and medical equipment in addition to COVID-19-related training using the Train-the-Trainer model. The quantitative part used knowledge and evaluation questionnaires and a pre–post-intervention hospital preparedness checklist. The qualitative approach adopted semi-structured interviews with a purposive sample from key hospital personnel. Quantitative data were analyzed using SPSS version 27, and a p-value of <0.05 was considered to be statistically significant. For the qualitative data, a thematic analysis was performed by adopting the six-phase process described by Braun and Clarke. Results: Of the 393 healthcare workers who attended the training and completed the evaluation questionnaire, 326 completed the pre- and post-training knowledge questionnaire. A significant improvement was observed in mean knowledge scores following training for infection control, nursing, and polymerase chain reaction sampling staff (p-value < 0.001, p-value < 0.001, and p-value = 0.006, respectively), but not for housekeeping staff. More than 93% of the participants showed high trainer and content evaluation scores. As for the hospitals’ preparedness assessments, there was a clear improvement in the pre- and post-assessment scores for each hospital, and there was a significant difference in the mean of the total scores of partner hospitals pre- and post-USAID-AUB project (p-value = 0.005). These findings were supported by the qualitative analysis, where nine hospitals expressed the positive impact of the USAID-AUB intervention in improving their preparedness to respond to the COVID-19 pandemic at a critical time when it was highly needed. Despite the intervention, persistent challenges remained. Conclusions: A timely and proactive collaborative program between academic/tertiary care centers and remote community hospitals that includes sharing supplies and expertise is feasible and highly effective during public health emergencies.