The COVID-19 second wave badly affected India. This study assessed public preparedness and attitude towards a new lockdown in the state of West Bengal (WB) along with perception about the COVID pandemic situation.

An anonymous questionnaire was administered to all willing adult attendees of a COVID vaccination centre in Kolkata, capital city of WB. Logistic regression was applied to find the relationship between attitude towards lockdown and other selected independent variables.

Of the 839 persons analyzed, 72.0% were non-health workers; and 55.4% thought that available vaccines reduce COVID-19 risk. Among them, 54.4% wanted stricter guidelines imposed. For preparedness, 42.6% and 28.8% said they would stock additional food and medicines respectively. On multiple logistic regression, being female, having elderly family members, perceiving the second wave as worse, and favouring stricter restrictions, all had odds of favourable attitude towards the new, proposed lockdown.

A new lockdown was favoured by the majority. However, a well-planned and phased approach for this is needed in the light of many concerns about the previous lockdown. Mental health issues, financial security, medical help at hand, and ease of travel to workplaces are important issues that need to be addressed in case of future lockdown(s).

During the coronavirus disease 2019 (COVID-19), individuals’ compliance with protective behaviors was the most effective strategy to break the infection chain and prevent disease spread, even with vaccine availability and use. Understanding protective behaviors within the Jordanian context will shape health promotion campaigns and guide decision-makers to facilitate required resources and support Jordanian citizens. The objective of this study was to identify personal protective (preventive and avoidant) measures used by the Jordanian population during the COVID-19 pandemic to protect themselves from infection.

A cross-sectional study with an exploratory, descriptive design was used to collect data using an online self-reported questionnaire from Jordanian people. The survey included the Protection from Infection Scale and the Infection Avoidance Scale.

A total sample of 1053 Jordanian citizens was included in the study. The participants exhibited a moderate level of self-care behaviors and high levels of protective and infection avoidance behaviors. Their most common behaviors were getting enough sleep, wearing masks, washing hands, and avoiding travel to infected areas. Contrariwise, the least adopted behaviors were exercising, wearing gloves, and leaving their jobs or schools.

During pandemics, policy-makers must understand public concerns and protective behaviors, then provide them with tailored education through health promotion campaigns to enhance healthy behaviors.

This study explores the depressive symptoms in postpartum women during the coronavirus disease 2019 (COVID-19) crisis in Japan.

An online survey conducted from May 31 to June 6, 2020 resulted in 3073 responses obtained from mothers with infants < 12 mo.

The point prevalence of the Edinburgh Postnatal Depression Scale (EPDS) score of ≥ 9 was 28.66% for primipara and 25.83% for multipara. Logistic regression analysis indicated a negative association between the COVID-19 crisis and EPDS ≥ 9; specifically, decreased social support and financial concern were identified as risk factors. The COVID-19–related experiences significantly increased the score of each factor of EPDS, ie, anxiety, anhedonia, and depression.

During the COVID-19 crisis, the number of mothers who faced depreciation in social support and income had increased. Moreover, spending their perinatal period during the crisis increased the propensity of facing unexpected changes, such as changes of hospitals for delivery, or cancellation of parenting classes. These multiple factors were associated with an elevated risk of depression in postpartum women. In a prolonged crisis, postpartum mental health should be treated carefully with the prevention of infection.

Literature investigating the change in psychological problems of the health care workers (HCWs) throughout the coronavirus disease (COVID-19) pandemic is lacking. We aimed at comparing the psychological problems and attitudes toward work among HCWs over two waves of the COVID-19 pandemic in India.

A survey was conducted involving HCWs (n = 305, first wave, 2020; n = 325, second wave, 2021). Participants’ demographic and professional and psychological characteristics (using attitude toward COVID-19 questionnaire [ATCQ]; Depression, Anxiety, and Stress Scale – 21 Items and impact of event scale – 22) were recorded. The unpaired t-test/chi-squared test was used for comparison.

Significant improvements (χ2(1) = 7.3 to 45.6, P < 0.05) in level of depression (42.2% vs 9.6%), anxiety (41.3% vs 16.3%), stress (30.1% vs 6.7%), event-related stress symptoms (31.2% vs 27%), work-related stress (89.8% vs 76.8%), and stigma (25.9% vs 22.8, though marginally significant) were found among the participants of the second wave (vs first wave). However, on subgroup analysis, allied-HCWs (housekeeping staff and security personnel) reported lesser concerns over the domains of the ATCQ vis-a-viz frontline-HCWs (doctors and nurses).

This improvement could be attributed to greater awareness about the illness, better coping skills, vaccination, and so forth; however, more research is warranted to investigate these determinants.

To evaluate how key aspects of New York State Ventilator Allocation Guidelines (NYSVAG)—Sequential Organ Failure Assessment score criteria and ventilator time trials —might perform with respect to the frequency of ventilator reallocation and survival to hospital discharge in a simulated cohort of coronavirus disease (COVID-19) patients.

Single center retrospective observational and simulation cohort study of 884 critically ill COVID-19 patients undergoing ventilator allocation per NYSVAG.

In total, 742 patients (83.9%) would have had their ventilator reallocated during the 11-day observation period, 280 (37.7%) of whom would have otherwise survived to hospital discharge if provided with a ventilator. Only 65 (18.1%) of the observed surviving patients would have survived by NYSVAG. Extending ventilator time trials from 2 to 5 days resulted in a 49.2% increase in simulated survival to discharge.

In the setting of a protracted respiratory pandemic, implementation of NYSVAG or similar protocols could lead to a high degree of ventilator reallocation, including withdrawal from patients who might otherwise survive. Longer ventilator time trials might lead to improved survival for COVID-19 patients given their protracted respiratory failure. Further studies are needed to understand the survival of patients receiving reallocated ventilators to determine whether implementation of NYSVAG would improve overall survival.

The study objective was to determine the feasibility of training physicians in the principles of the National Incident Management System (NIMS) and Incident Command System (ICS) as applied to in-hospital rapid responses and to assess physicians’ attitudes regarding rapid responses.

This was an educational pilot study. Resident physicians completed a pre-survey, followed by online training in the principles of NIMS and ICS, a knowledge test, and a post-survey.

The number of residents who participated was 22. In the pre-survey, most (20/22) did not have a working understanding of NIMS/ICS. Participants (21/22) agreed that residents should have more training in resource organization. On the knowledge test, the median score was 9.5/10. In the post-survey, participants felt more comfortable clearing extra resources from the scene (P < 0.001) and that it would be easier to keep track of resources (P < 0.001). Most indicated that they had a working understanding of NIMS/ICS (P < 0.001) and felt more comfortable establishing command using NIMS/ICS (P < 0.001). All agreed that they would consider using an NIMS/ICS-based structure on their next rapid response.

Training physicians in the principles of NIMS/ICS as they pertain to rapid responses is feasible and appears to change residents’ attitudes about rapid responses.

The coronavirus disease (COVID-19) pandemic has presented unique challenges to pediatric emergency medicine (PEM) departments. The purpose of this study was to identify these challenges and ascertain how centers overcame barriers in creating solutions to continue to provide high-quality care and keep their workforce safe during the early pandemic.

This is a qualitative study based on semi-structured interviews with physicians in leadership positions who have disaster or emergency management experience. Participants were identified through purposive sampling. Interviews were recorded and transcribed electronically. Themes and codes were extracted from the transcripts by 2 independent coders. Constant comparison analysis was performed until thematic saturation was achieved. Member-checking was completed to ensure trustworthiness.

Fourteen PEM-trained physicians participated in this study. Communication, leadership and planning, clinical practice, and personal adaptations were the principal themes identified. Recommendations elicited include improving communication strategies; increasing emergency department (ED) representation within hospital-wide incident command; preparing for a surge and accepting adult patients; personal protective equipment supply and usage; developing testing strategies; and adaptations individuals made to their practice to keep themselves and their families safe.

By sharing COVID-19 experiences and offering solutions to commonly encountered problems, pediatric EDs may be better prepared for future pandemics.

To determine factors associated with increased response readiness to CBRN threats of paramedics in Ontario, Canada.

An internet-based survey was distributed via email and delivered at the start of each shift presentation during October, 2019. The target population was active-duty paramedics in the Ontario region of Canada. The survey was comprised of 6 sections pertaining to demographics, attitudinal components of risk perception, self-efficacy, deployment concerns, and resilience. Survey mean, univariate, and multivariate regression analyses were used to find the individual effect of each variable.

The univariate analysis indicated that higher response readiness was associated with additional training, education, CBRN, and family concerns, and incident experience. However, some variables were non-significant in the multivariate analysis. Increased response readiness was associated with CBRN concerns and training.

CBRN concerns and focused training regarding terrorism were both associated with increased response readiness. The information from the study can be used to build upon existing knowledge and support paramedics though training and preparation for CBRN specific disasters. The findings may also be used to improve current competency-based frameworks focused on response readiness.

A danger threatening hospitals is fire. The most important action following a fire is to urgently evacuate the hospital during the shortest time possible. The aim of this study was to predict the duration of emergency evacuation following hospital fire using machine-learning algorithms.

In this study, the real emergency evacuation duration of 190 patients admitted to a hospital was predicted in a simulation based on the following 8 factors: the number of hospital floors, patient preparation and transfer time, distance to the safe location, as well as patient’s weight, age, sex, and movement capability. To design and validate the model, we used statistical models of machine learning, including Support Vector Machines Random Forest, Naive Bayes Classifier, and Artificial Neural Network.

Data analysis showed that based on the Area Under the Curve, precision, and sensitivity values of 99.5%, 92.4%, and 92.1%, respectively, the Random Forest model showed a better performance compared to other models for predicting the duration of hospital emergency evacuation during fire.

Predicting evacuation duration can provide managers with accurate information and true analyses of these events. Therefore, health policy makers and managers can promote preparedness and responsiveness during fire by predicting evacuation duration and developing appropriate plans using machine learning models.

The transfer rate for patients from an Alternate Care Site (ACS) back to a hospital may serve as a metric of appropriate patient selection and the ability of an ACS to treat moderate to severely ill patients accepted from overwhelmed health-care systems. During the coronavirus infectious disease 2019 (COVID-19) pandemic, hospitals worldwide experienced acute surges of patients presenting with acute respiratory failure.

An ACS in Imperial County, California was re-established in November 2020 to help decompress 2 local hospitals experiencing surges of COVID-19 cases. The patients treated often had multiple comorbid illnesses and required a median supplemental oxygen of 3 L/min (LPM) on admission. Numerous interventions were initiated during a 2-wk period to improve clinical care delivery.

The objectives of this retrospective observational study are to evaluate the impact of these clinical and staff interventions at an ACS on the transfer rate and to provide issues to consider for future ACS sites managing COVID-19 patients.

The data suggest that continuous, real-time process-improvement interventions helped reduce the transfer rate back to hospitals from 36.7% to 14.5% and that an ACS is a viable option for managing symptomatic COVID-19 positive patients requiring hospital-level care when hospitals are overburdened.

The survival cox analysis is becoming more popular in time-to-event data analysis. When there are unobserved /unmeasured individual factors, then the results of this model may not be dependable. Hence, this study aimed to determine the factors associated with Covid-19 patients’ survival time with considering frailty factor.

This study was conducted at 1 of the hospitals in Iran, so that hospitalized patients with COVID-19 were included. Epidemiological, clinical, laboratory, and outcome data on admission were extracted from electronic medical records. Gamma-frailty Cox model was used to identify the effects of the risk factors.

A total of 360 patients with COVID-19 enrolled in the study. The median age was 74 years (IQR 61 – 83), 903 (57·7%) were men, and 661 (42·3%) were women; the mortality rate was 17%. The Cox frailty model showed that there is at least a latent factor in the model (P = 0.005). Age and platelet count were negatively associated with the length of stay, while red blood cell count was positively associated with the length of stay of patients.

The Cox frailty model indicates that in addition to age, the frailty factor is a useful predictor of survival in Covid-19 patients.

Obesity is a risk factor for various diseases and can affect the disease course. Studies have shown detrimental effects of obesity on patients affected with SARS-CoV-2 including increased hospitalization and more severe disease. This study aims to investigate the effects of obesity on symptom duration in patients with COVID-19, and also explore the possibility of using BMI as a predictor of symptom duration in outpatient settings.

Patients diagnosed with COVID-19 between June and October 2020, who had no other comorbidities, and were planned to receive treatment in the outpatient setting were enrolled in the study. Duration of the symptoms was determined based on participants’ self-report of their symptoms. Linear regression was used to create predictive models based on participants’ BMI, age, sex, disease presentation, and their self-reported symptom duration.

A total of 210 patients were included in the final analysis. Patients with higher BMI had significantly longer symptom duration. Linear regression models showed highest correlation between BMI and symptom duration compared to other covariates.

Low error in predictions and high coverage of data variability showed BMI can be used as a predictive factor for symptom duration in COVID-19 patients treated in outpatient settings.

The objectives of this study were to: validate current capacity estimates for radiological emergency response by collecting time motion observations from stations that would be used for screening and decontaminating populations, and use collected times to evaluate potential impact on current throughput calculations.

Time observations were collected at 11 functional radiation exercises across the country and aggregated for analysis for population monitoring activities, including contamination screening, decontamination, and registration. Collected times were compared to published estimates in current planning guidance, and evaluated to determine the suitability of using exercise observations to estimate throughput capacity.

2532-time observations were collected from 11 functional exercises. Of those, 2380 were validated and used for analysis. Contamination screening times varied greatly from current guidance, ranging from 19% below to 267% above existing estimates. Measurements indicate that capacity to perform contamination screening is significantly overestimated when using current estimates of service times and calculations when compared to observed aggregate service times.i

Aggregate service time data presented in this study can be used to yield a more realistic estimate of capacity to respond to a radiation event.

Research indicates that greater exposure to Hurricane Sandy is associated with increased mental health difficulties. This study examined whether Project Restoration, a program that linked adults into mental health care (L2C), was effective in reducing post-Sandy mental health difficulties as compared to a cohort of adults matched on mental health difficulties that were not linked into post-Sandy mental health care.

Project Restoration participants (n = 52) with elevated self-reported mental health difficulties had the option to enroll into L2C. Project LIGHT (n = 63) used similar methodologies but did not have a L2C component and served as the matched control group.

Multivariable modeling showed significant decreases in all mental health difficulties except for depression in the Project Restoration group, whereas there were no significant decreases in LIGHT. The decrease in anxiety from baseline to follow-up was significantly greater for Project Restoration as compared to LIGHT.

Findings confirm the powerful impact community outreach and treatment have on reducing mental health difficulties after a disaster.

Determining the health-care experiences, problems, and difficulties of nurses during a pandemic is important to shape the measures of nursing care management. This study aimed to better understand clinical nurses’ challenges and expectations surrounding coronavirus disease 2019 (COVID-19) pandemic.

A qualitative study with semi-structured interviews was conducted. The study sampling comprised of 48 clinical nurses who have worked in pandemic hospitals. Interviews were recorded, transcribed, and evaluated based on the content analysis method.

In this study, 6 main themes were determined as intrapersonal, interpersonal, institutional/organizational, community, policies and system challenges, and expectations. Based on the results, nurses’ perceived challenges were psychological distress, dilemma, safety and security issues, workload increased, disruption in family and social relationships, stigmatization encountered, and not making their voices heard enough due to the lack of nurses in the scientific advisory board. Nurses’ expectations were determined as improvement of their personal rights and institutional psychosocial support.

The results of this study can be used as a guide for action plans to support nurses, develop health-care protocols for safe patient care, and create family and pandemic support systems.