This research aims to provide guidance on means to bolster safe and effective emergency response. Safe and effective performance among firefighters is key to protecting firefighters, to ensure mission completion, and to protect the public during emergency response situations. Although some studies have shown the impact of safety climate on firefighter performance, few studies have explored the impact of safety climate on affective organizational commitment and safety behaviors among firefighters, which are critical to more effective emergency response.

Data collected from 349 career firefighters in the southern United States were analyzed by means of structural equation modeling to assess posited relationships in the proposed model.

This study confirmed a model that describes the relationships between safety climate, affective organizational commitment, and safety behaviors. Safety climate significantly predicted affective organizational commitment (P < 0.001) and affective organizational commitment was positively associated with both safety compliance (P < 0.001) and safety participation (P < 0.001).

This study has implications for researchers and practitioners. Firefighters exhibit positive affective organizational commitment as a result of positive safety climate perceptions. This commitment is then associated with positive safety behavior outcomes, which bolsters personal safety and enhances the likelihood of safe and effective mission completion to protect the public.

Civil–military relationships are necessary in humanitarian emergencies but, if poorly managed, may be detrimental to the efforts of humanitarian organizations. Awareness of guidelines and understanding of risks relating to the relationship among deployed military personnel have not been evaluated.

Fifty-five military and 12 humanitarian healthcare workers in South Sudan completed questionnaires covering experience, training and role, agreement with statements about the deployment, and free text comments.

Both cohorts were equally aware of current guidance. Eight themes defined the relationship. There was disagreement about the benefit to the South Sudanese people of the military deployment, and whether military service was compatible with beneficial health impacts. Two key obstacles to the relationship and 3 areas the relationship could be developed were identified.

This study shows that United Kingdom military personnel are effectively trained and understand the constraints on the civil–military relationship. Seven themes in common between the groups describe the relationship. Current guidance could be adapted to allow a different relationship for healthcare workers.

To provide scientific, theoretical support for the improvement of medical disaster training, we systematically analyzed the National Disaster Life Support (NDLS) Course and established a training curriculum with feedback based on the current status of disaster medicine in China.

The gray prediction model is applied to long-term forecast research on course effect. In line with the hypothesis, the NDLS course with feedback capability is more scientific and standardized.

The current training NDLS course system is suitable for Chinese medical disasters. After accepting the course training, audiences’ capabilities were enhanced. In the constructed GM (1,1) model prediction, the developing coefficients of the pretest and the posttest are 0.04 and 0.057, respectively. In light of the coefficient, the model is appropriate for the long-term prediction. The predicted results can be used as the basis for constructing training closed-loop optimization feedback. It can indicate that the course system has a good effect as well.

According to the constructed GM model, the NDLS course system is scientific, practical, and operational. The research results can provide reference for relevant departments and be used for the construction of similar training course systems.

We analyzed characteristics of tornado-related injuries and medical impact on a county-level hospital in China in June 23, 2016. The objective of this study was to describe and analyze local government rescue responses following the tornado.

County hospital medical records of 288 tornado-related injury patients were collected. Descriptive analyses to study injury characteristics and associated risk factors were performed.

Of the studied population, 84% of the wounded were older than 45 years. Only 30 (10.4%) people were sent to the hospital for treatment within 3 hours following the disaster. Heavy objects or collapsing houses accounted for 191 (66.3%) of the documented injuries. The proportion of people with resulting brain injuries was 46.2% of the entire injured population, and the incidence of lower extremity injuries was 27.8%. A total of 89.6% of the wounded had skin and soft tissue injuries. Multiple injuries were found in 129 (44.8%) people and 156 had a single injury (54.2%), and 3 cases with acute stress disorder were admitted to the hospital.

Preparation plans, including tornado warnings, prevention, and rescue, are a basic requirement for the mitigation of tornado-related injuries. Protection awareness of tornado disasters is also critical to ensure injury prevention.

To study injury patterns and medical rescue operations related to tornadoes that occur in rural areas, this study investigated the data pertaining to the 2017 Chifeng tornado (China).

Medical records of 52 tornado-related patients were investigated. Data were collected from 3 local hospitals that received all the tornado victims.

A total of 148 injuries were diagnosed. Tornado-related injuries were mainly caused by collapsed houses (51.9%) and direct physical trauma caused by the tornado (38.5%). Most injuries occurred outdoors (63.5%). The head (20.3%) and thorax (14.8%) were most 2 frequent anatomical injury sites. Soft-tissue injuries (43.9%) and contusions and lacerations (37.3%) were the 2 most common injury types. On evaluating the Abbreviated Injury Scale scores, a score of 1 was the most common (66.2%), and a score of 6 was not recorded.

A trailing phenomenon in the distribution of time to admission among the victims of a particular tornado in China was observed. The delivery is timely compared with nondisaster situation. There was a statistically significant difference of injury causes between outdoor and indoor patients. Helmets should be used by potential tornado victims. Basement units capable of functioning as shelters should be built in villages.

This study describes the epidemiologic features of an outbreak of the coronavirus disease (COVID-19) in Tianjin caused by a novel coronavirus and provides the scientific basis for prevention and control measures.

Data from COVID-19 cases were collected from daily notifications given to the National Health Commission of the People’s Republic of China and Tianjin Health Committee. All of the data were analyzed with SPSS, version 24.0 software (IBM Corp, Armonk, NY).

As of February 24, 2020, there have been 135 confirmed cases, 3 deaths, and 87 recoveries in Tianjin, China. The incidence of COVID-19 was 8.65/1 000 000 with a 2.22% case fatality rate. Regarding geographic distribution, the incidence was 8.82 per 1 000 000 in urban areas and 8.00 per 1 000 000 in suburbs. During the early stage of the epidemic, most cases came from urban areas and in patients with a history of sojourning in Hubei Province. The majority of patients were 31–70 years old (75.97%). A familial clustering was the most important characteristic of COVID-19 (accounting for 74.81%).

Current information suggests that people are generally susceptible to COVID-19, which has shown a familial clustering in Tianjin.

The purpose of this study was to assess the readability of information on the Internet posted about coronavirus disease 2019 (COVID-19) to determine how closely these materials are written to the recommended reading levels.

Using the search term “coronavirus,” information posted on the first 100 English language websites was identified. Using an online readability calculator, multiple readability tests were conducted to ensure a comprehensive representation would result.

The mean readability scores ranged between grade levels 6.2 and 17.8 (graduate school level). Four of the 5 measures (GFI, CLI, SMOG, FRE) found that readability exceeded the 10th grade reading level indicating that the text of these websites would be difficult for the average American to read. The mean reading level for nearly all noncommercial and commercial websites was at or above the 10th grade reading level.

Messages about COVID-19 must be readable at an “easy” level, and must contain clear guidelines for behavior. The degree to which individuals seek information in response to risk messages is positively related to the expectation that the information will resolve uncertainty. However, if the information is too complex to interpret and it fails to lead to disambiguation, this can contribute to feelings of panic.

Italy has been one of the first countries to implement mitigation measures to curb the coronavirus disease 2019 (COVID-19) pandemic. There is currently a debate on when and how such measures should be loosened. To forecast the demand for hospital intensive care unit (ICU) and non-ICU beds for COVID-19 patients from May to September, we developed 2 models, assuming a gradual easing of restrictions or an intermittent lockdown.

We used a compartmental model to evaluate 2 scenarios: (A) an intermittent lockdown; (B) a gradual relaxation of the lockdown. Predicted ICU and non-ICU demand was compared with the peak in hospital bed use observed in April 2020.

Under scenario A, while ICU demand will remain below the peak, the number of non-ICU will substantially rise and will exceed it (133%; 95% confidence interval [CI]: 94-171). Under scenario B, a rise in ICU and non-ICU demand will start in July and will progressively increase over the summer 2020, reaching 95% (95% CI: 71-121) and 237% (95% CI: 191-282) of the April peak.

Italian hospital demand is likely to remain high in the next months. If restrictions are reduced, planning for the next several months should consider an increase in health-care resources to maintain surge capacity across the country.

As an emerging infectious disease, COVID-19 has involved many countries and regions. With the further development of the epidemic, the proportion of clusters has increased.

In our study, we collected information on COVID-19 clusters in Qingdao City. The epidemiological characteristics and clinical manifestations were analyzed.

Eleven clusters of COVID-19 were reported in Qingdao City between January 29, and February 23, 2020, involving 44 confirmed cases, which accounted for 73.33% of all confirmed cases. From January 19 to February 2, 2020, the cases mainly concentrated in the district that had many designated hospitals. Patients aged 20-59 y old accounted for the largest proportion (68.18%) of cases; the male-to-female sex ratio was 0.52:1. Three cases were infected from exposure to confirmed cases. The average incubation period was 6.28 d. The median number of cases per cluster was 4, and the median duration time was 6 d. The median cumulative number of exposed persons was 53.

More attention should be paid to the epidemic of clusters in prevention and control of COVID-19. In addition to isolating patients, it is essential to track, screen, and isolate those who have come in close contact with patients. Self-isolation is the key especially for healthy people in the epidemic area.

To document the lived experience of Italian pediatric emergency physicians during the coronavirus disease 2019 (COVID-19) pandemic.

We developed a structured interview to collect the lived experience of the staff of the pediatric emergency department (PED) of a tertiary referral university hospital in Northern Italy. The open-ended questions were draft according to the suggestions of Canadian colleagues and administered by 1 interviewer, who was part of the PED staff, at the end of March 2020. All the PED staff was interviewed, on a voluntary basis, using purposive sampling.

Most respondents declared to be afraid of becoming infected and of infecting their families. The number of patients seen in the PED has decreased, and the cases tend to be more severe. A shift in the clinical approach to the ill child has occurred, the physical examination is problem-oriented, aiming to avoid un-necessary maneuvers and to minimize the number of practitioners involved. The most challenging aspects reported are: (1) performing a physical examination in personal protective equipment (PPE), (2) being updated with rapidly evolving guidelines, and (3) staying focused on the possible COVID-19 clinical presentation without failing in differential diagnosis.

During the COVID-19 pandemic, it seems that pediatric emergency physicians are radically changing their clinical practice, aiming at prioritizing essential interventions and maneuvers and self-protection.

More than 80% of coronavirus disease 2019 (COVID-19) cases are mild or moderate. In this study, a risk model was developed for predicting rehabilitation duration (the time from hospital admission to discharge) of the mild-moderate COVID-19 cases and was used to conduct refined risk management for different risk populations.

A total of 90 consecutive patients with mild-moderate COVID-19 were enrolled. Large-scale datasets were extracted from clinical practices. Through the multivariable linear regression analysis, the model was based on significant risk factors and was developed for predicting the rehabilitation duration of mild-moderate cases of COVID-19. To assess the local epidemic situation, risk management was conducted by weighing the risk of populations at different risk.

Ten risk factors from 44 high-dimensional clinical datasets were significantly correlated to rehabilitation duration (P < 0.05). Among these factors, 5 risk predictors were incorporated into a risk model. Individual rehabilitation durations were effectively calculated. Weighing the local epidemic situation, threshold probability was classified for low risk, intermediate risk, and high risk. Using this classification, risk management was based on a treatment flowchart tailored for clinical decision-making.

The proposed novel model is a useful tool for individualized risk management of mild-moderate COVID-19 cases, and it may readily facilitate dynamic clinical decision-making for different risk populations.