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Introduction: Healthcare patterns change during disease outbreaks and pandemics. Identification of modified patterns is important for future preparedness and response. Emergency department (ED) crowding can occur because of the volume of patients waiting to be seen, which results in delays in patient assessment or treatment and impediments to leaving the ED once treatment is complete. Therefore, ED crowding has become a growing problem worldwide and represents a serious barrier to healthcare operations. Methods: This observational study was based on a retrospective review of the epidemiologic and clinical records of patients who presented to the Foundation IRCCS Policlinic San Matteo in Pavia, Italy, during the coronavirus disease 2019 (COVID-19) outbreak (February 21–May 1, 2020, pandemic group). The methods involved an estimation of the changes in epidemiologic and clinical data from the annual baseline data after the start of the COVID-19 pandemic. Results: We identified reduced ED visits (180 per day in the control period vs 96 per day in the pandemic period; P < 0.001) during the COVID-19 pandemic, irrespective of age and gender, especially for low-acuity conditions. However, patients who did present to the ED were more likely to be hemodynamically unstable, exhibit abnormal vital signs, and more frequently required high-intensity care and hospitalization. During the pandemic, ED crowding dramatically increased primarily because of an increased number of visits by patients with high-acuity conditions, changes in patient management that prolonged length of stay, and increased rates of boarding, which led to the inability of patients to gain access to appropriate hospital beds within a reasonable amount of time. During the pandemic, all crowding output indices increased, especially the rates of boarding (36% vs 57%; P < 0.001), “access block” (24% vs 47%; P < 0.001), mean boarding time (640 vs 1,150 minutes [min]; P 0.001), mean “access block” time (718 vs 1,223 min; P < 0.001), and “access block” total time (650,379 vs 1,359,172 min; P < 0.001). Conclusion: Crowding in the ED during the COVID-19 pandemic was due to the inability to access hospital beds. Therefore, solutions to this lack of access are required to prevent a recurrence of crowding due to a new viral wave or epidemic.

The geriatric population constitutes a large slice of the population of Western countries and a class of fragile patients, with greater deaths due to COVID-19. The patterns of healthcare utilization change during pandemic disease outbreaks. Identifying the patterns of changes of this particular fragile subpopulation is important for future preparedness and response. Overcrowding in the emergency department (ED) can occur because of the volume of patients waiting to be seen, delays in patient assessment or treatment in the ED, or impediments to leaving the ED once the treatment has been completed. Overcrowding has become a serious and growing issue globally, which represents a serious impediment to healthcare utilization. To estimate the rate of ED visits attributable to the outbreak and guide the planning of strategies for managing ED access or after the outbreak of transmittable respiratory diseases. This observational study was based on a retrospective review of the epidemiological and clinical records of patients aged > 75 years who visited the Foundation IRCCS Policlinic San Matteo during the first wave of COVID-19 outbreak (February 21 to May 1, 2020; pandemic group). The analysis methods included estimation of the changes in the epidemiological and clinical data from the annual baseline data after the start of the COVID-19 pandemic. Outcome measures and analysis: Primary objective is the evaluation of ED admission rate change and ED overcrowding. Secondary objectives are the evaluation of modes of ED access by reason and triage code, access types, clinical outcomes (such as admission and mortality rates). During the pandemic, ED crowding increased dramatically, although the overall number of patients decreased, in the face of a percentage increase in those with high-acuity conditions, because of changes in patient management that have prolonged length of stay (LOS) and increased rates of access block. Overcrowding during the COVID-19 pandemic can be attributed to the Access Block. Access Block solutions are hence required to prevent a recurrence of crowding to any new viral wave or new epidemic in the future. Supplementary Information The online version contains supplementary material available at 10.1007/s11739-021-02732-w.

Background During the COVID-19 pandemic, the health care workers (HCWs) at the frontline have been largely exposed to infected patients, running a high risk of being infected by the SARS-CoV-2 virus. Since limiting transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in health care setting is crucial to avoid the community spread of SARS-CoV-2, we want to share our experience as an early hit hospital where standard infection control practices have been conscientiously applied and effective. We believe that our example, as first and hardest hit country, might be a warning and aid not only for those who have been hit later, but also for a second fearful wave of contagion. In addition, we want to offer an insight on modifiable risk factors for HWs-related infection. Methods Demographic, lifestyle, work-related and comorbidities data of 1447 HCWs, which underwent a nasopharyngeal swab for SARS-CoV-2, were retrospectively collected. For the 164 HCWs positive for SARS-CoV-2, data about safety in the workplace, symptoms and clinical course of COVID-19 were also collected. Cumulative incidence of SARS-CoV-2 infection was estimated. Risk factors for SARS-CoV-2 infection were assessed using a multivariable Poisson regression. Results The cumulative incidence of SARS-CoV-2 infection among the screened HCWs was 11.33% (9.72–13.21). Working in a COVID-19 ward, being a former smoker (versus being a person who never smoked) and BMI was positively associated with SARS-CoV-2 infection, whereas being a current smoker was negatively associated with this variable. Conclusions Assuming an equal accessibility and proper use of personal protective equipment of all the HCWs of our Hospital, the great and more prolonged contact with COVID-19 patients remains the crucial risk factor for SARS-CoV-2. Therefore, increased and particular care needs to be focused specifically on the most exposed HCWs groups, which should be safeguarded. Furthermore, in order to limit the risk of asymptomatic spread of SARS-CoV-2 infection, the HCWs mild symptoms of COVID-19 should be considered when evaluating the potential benefits of universal staff testing.

Introduction The sudden increase in the number of critically ill patients following a disaster can be overwhelming. Study objective The main objective of this study was to assess the real number of available and readily freeable beds ("bed surge capacity") and the availability of emergency operating rooms (OR) in a maximum emergency using a theoretical simulation. Patients and methods The proportion of dismissible patients in four areas (Medical Area, Surgical Area, Sub-intensive Care Units, Intensive Care Units) and three emergency OR was assessed at 2 and 24 hours after a simulated maximum emergency. Four scenarios were modeled. Hospitalization and surgical capacities were assessed on weekdays and holidays. The creation of new beds was presumed by the possibility of moving patients to a lower level of care than that provided at the time of detection, of dislocation of patients to a discharge room, with care transferred to lower-intensity hospitals, rehabilitation, or discharge facilities. The Phase 1 table-top simulations were conducted during the weekday morning hours. In particular, the 24-hour table-top simulations of a hypothetical event lasted about 150 minutes compared to those conducted at 2 hours, which were found to be longer (about 195 minutes). Phase 2 was conducted on two public holidays and a quick response time was observed within the first 40 minutes of the start of the test (about 45% of departments). Results The availability of simulated beds was greater than that indicated in the maximum emergency plans (which was based solely on the census of beds). Patients admitted to Intensive Care and The Sub-Intensive Area may be more difficult to move than those in low-intensity care. The availability of emergency OR was not problematic. Age influenced the possibility of remitting/transferring patients. Conclusion Simulation in advance of a maximum emergency is helpful in designing an efficient response plan.

Vaccine breakthrough SARS-CoV-2 infection has been monitored in 3720 healthcare workers receiving 2 doses of BNT162b2. SARS-CoV-2 infection is detected in 33 subjects, with a 100-day cumulative incidence of 0.93%. Vaccine protection against acquisition of SARS-CoV-2 infection is 83% (95%CI: 58–93%) in the overall population and 93% (95%CI: 69-99%) in SARS-CoV-2-experienced subjects, when compared with a non-vaccinated control group from the same Institution, in which SARS-CoV-2 infection occurs in 20/346 subjects (100-day cumulative incidence: 5.78%). The infection is symptomatic in 16 (48%) vaccinated subjects vs 17 (85%) controls (p = 0.01). All analyzed patients, in whom the amount of viral RNA was sufficient for genome sequencing, results infected by the alpha variant. Antibody and T-cell responses are not reduced in subjects with breakthrough infection. Evidence of virus transmission, determined by contact tracing, is observed in two (6.1%) cases. This real-world data support the protective effect of BNT162b2 vaccine. A triple antigenic exposure, such as two-dose vaccine schedule in experienced subjects, may confer a higher protection., Several COVID-19 vaccines have shown good efficacy in clinical trials. Here, the authors provide real world effectiveness data in a group of BNT162b2 vaccinated health care workers and find that breakthrough infections are asymptomatic or mild.

Objective: The protection from SARS-CoV-2 infection induced by SARS-CoV-2 anti-S1 and anti-S2 IgG antibody positivity resulting from natural infection was evaluated. Methods: The frequency of SARS-CoV-2 infection (as determined by virus RNA detection) was evaluated in a group of 1,460 seropositive and a control group of 8,150 seronegative healthcare workers in three Centres of Northern Italy in the period June-November 2020. Neutralizing serum titers were analyzed in seropositive subjects with or without secondary SARS-CoV-2 infection. Results: During the 6-month survey, 1.78% seropositive subjects developed secondary SARS-CoV-2 infection while 6.63% seronegative controls developed primary infection (odds ratio: 0.26; 95% confidence interval: 0.17-0.38). Secondary infection was associated with low or absent serum neutralizing titer (p

Purpose: During the COVID-19 pandemic, the health care workers (HCWs) at the frontline have been largely exposed to infected patients, running an high risk of being infected by the SARS-CoV-2 virus. This study investigates the epidemiological, clinical and lifestyles characteristics that might play roles in the susceptibility of HCWs to COVID-19 in a hit Italian hospital. Methods:Demographic, lifestyle, work-related and comorbidities data of 1447 HCWs which underwent a nasopharyngeal swab for SARS-CoV-2 were retrospectively collected. For the 164 HCWs positive for SARS-CoV-2, data about safety in the workplace, symptoms and clinical course of COVID-19 were also collected. Cumulative incidence of SARS-CoV-2 infection was estimated. Risk factors for SARS-CoV-2 infection were assessed using a multivariable Poisson regression. Results: The cumulative incidence of SARS-CoV-2 infection among the screened HCWs was 11.33 (9.72-13.21). Working in a COVID-19 ward, being a former smoker (vs being a person who never smoked) and BMI were positively associated with SARS-CoV-2 infection, whereas being a current smoker was negatively associated with this variable. Conclusions: Assuming an equal accessibility and proper use of PPE of all the HCWs of our Hospital, the great and more prolonged contact with COVID-19 patients remains the crucial risk factor for SARS-CoV-2. Therefore, increased and particular care needs to be focused specifically on the most exposed HCWs groups, which should be safeguarded. Furthermore, in order to limit the risk of asymptomatic spread of SARS-CoV-2 infection, the HCWs mild symptoms of COVID-19 should be considered when evaluating the potential benefits of universal staff testing

Italy is one of the most exposed countries worldwide to COVID-19, and Lombardy is the most affected region in Italy. In this context, Fondazione IRCCS Policlinico San Matteo in Pavia, one of the largest University hospitals in the region, has been involved in the management of the outbreak since its inception. Immediately after the communication of the first Italian COVID-19+ patient, the Pediatric Unit has been completely reorganized to face the approaching outbreak. The optimization of the Pediatric Unit resources for COVID-19 emergency is reported as an example to safely preserve health activity during the pandemic.(www.actabiomedica.it)

Introduction The sudden increase in the number of critically ill patients following a disaster can be overwhelming. Study Objective The main objective of this study was to assess the real number of available and readily freeable beds (“bed surge capacity”) and the availability of emergency operating rooms (OR) in a maximum emergency using a theoretical simulation. Patients and Methods The proportion of dismissible patients in four areas (Medical Area, Surgical Area, Sub-intensive Care Units, Intensive Care Units) and three emergency OR was assessed at 2 and 24 hours after a simulated maximum emergency. Four scenarios were modeled. Hospitalization and surgical capacities were assessed on weekdays and holidays. The creation of new beds was presumed by the possibility of moving patients to a lower level of care than that provided at the time of detection, of dislocation of patients to a discharge room, with care transferred to lower-intensity hospitals, rehabilitation, or discharge facilities. The Phase 1 table-top simulations were conducted during the weekday morning hours. In particular, the 24-hour table-top simulations of a hypothetical event lasted about 150 minutes compared to those conducted at 2 hours, which were found to be longer (about 195 minutes). Phase 2 was conducted on two public holidays and a quick response time was observed within the first 40 minutes of the start of the test (about 45% of departments). Results The availability of simulated beds was greater than that indicated in the maximum emergency plans (which was based solely on the census of beds). Patients admitted to Intensive Care and The Sub-Intensive Area may be more difficult to move than those in low-intensity care. The availability of emergency OR was not problematic. Age influenced the possibility of remitting/transferring patients. Conclusion Simulation in advance of a maximum emergency is helpful in designing an efficient response plan.