Nurses are considered key members to respond to incidents and disasters. As many patients are hospitalized during the coronavirus disease (COVID-19) pandemic, and nurses are directly in contact with these patients; their preparedness enables them to respond to this situation more effectively and protects their health. Therefore, the present study aimed to design and validate a questionnaire to measure the nurses’ preparedness in response to COVID-19 in Iran in 2020.

This study was a mixed research aiming to develop and validate a psychometric research instrument in 2020. Based on the review of the literature regarding COVID-19 and other viral respiratory infections, the items were extracted, rewritten, and validated. In the quantitative phase, the validity of the questionnaire was evaluated in terms of face, content, and construct validity, and its reliability was evaluated based on internal consistency and stability (Cronbach’s alpha and Intra-class Correlation Coefficient [ICC]). To fill out the questionnaire, the nurses were selected by random sampling. Data analysis was done by the SPSS software, version 23 (IBM Corp, Armonk, NY).

The designed questionnaire included 9 dimensions and 50 items. The dimensions included (1) Incident Command System (ICS); (2) risk assessment and management; (3) information and communication management; (4) psychological approaches; (5) personal protective equipment; (6) prevention of contamination, isolation, and quarantine; (7) education and training; (8) patient management; and (9) features of the new coronavirus. The content and face validity of the questionnaire were approved by the specialists and experts of nursing and health in disasters and emergencies. The content validity ratio was > 0.7 for all items. The content validity index was also approved for all items. The Cronbach’s alpha coefficient and ICC were respectively 0.71 and 0.72 for the total questionnaire. The total score was determined based on 5 ranges, including 50–89 (very low preparedness), 90–129 (low preparedness), 130–170 (medium-level preparedness), 171–210 (high preparedness), and 211–250 (very high preparedness).

Nurses’ preparedness to respond to this pandemic requires multilateral measures. Measuring the nurses’ preparedness can clarify the challenges in hospital measures taken to respond to this crisis. Evaluating the nurses, determining the challenges and priorities, and finding solutions to resolve them can improve the nurses’ performance in providing health care services. Preparation of nurses during pandemics can reduce the damages to this group and maximize their efforts to protect the patients. Thus, health planners and policy-makers should try to promote the nurses’ awareness and preparedness.

Coronavirus disease (COVID-19) has emerged as a global pandemic for public health due to the large scale outbreak, therefore there is an urgent need to detect the infected cases quickly and isolate them in order to suppress the further spread of the disease. This study tries to identify a suitable pool testing method and algorithm for COVID-19.

This study tries to derive a general equation for the number of tests required for a pooled sample to detect every infected individual in the specific pool. The gain in pool testing over the normal procedure is quantified by the percentage of tests required compared to individual testing.

The percentage of tests required by the pool testing strategy varies according to the different splitting procedures, the size of the pooled sample, and the probability of an individual being infected in the population. If the probability of infection is 0.05, then for a pool size of 32, only 14 tests are sufficient to detect every infected individual.

The number of tests required to detect infected individuals by using the pooling method is much lower than individual testing. This may help us with increasing our testing capacity for COVID-19 by testing a large number of individuals in less time with limited resources.

The Japanese Association for Disaster Medicine developed a mass casualty life support (MCLS) course to improve cooperation among medical practitioners during a disaster, which is essential for reducing the rates of preventable disaster death. We investigated whether there was difference in first aid activity among members of the ambulance service during mass casualty training based on having taken the MCLS course.

Mass casualty training was held at the fire department of Numazu City. Twenty-one ambulance service parties participated in this training. They first evaluated the mass casualty situation, performed the appropriate services at the scene during the initial period, and then provided START triage for mock wounded patients. Throughout the training, 5 examiners evaluated their performance.

Regarding the difference in first aid activity based on MCLS course attendance among the ambulance service members, the cooperative management (scored on a scale of 1 to 5) among the members who had taken the MCLS course was significantly better than that among those who had not taken the course (median [interquartile range]: 5 [0.5] vs. 4 [1.75], P<0.05).

Attending an MCLS course may help to improve outcomes in the face of an actual mass casualty incident. (Disaster Med Public Health Preparedness. 2018;12:437–440)

Children are at increased risk for experiencing negative physical and mental health outcomes as a result of disasters. Millions of children spend their days in childcare centers or in residential family childcare settings. The purpose of this study was to describe childcare providers’ perceived levels of preparedness capabilities and to assess differences in levels of perceived preparedness between different types of childcare providers.

A national convenience sample of childcare center administrators and residential family childcare administrators completed a brief online survey about their preparedness efforts.

Overall, there were few differences in preparedness between childcare centers and residential family childcare providers. However, childcare centers were more likely to report that they had written plans (94.47%) than residential family childcare providers (83.73%) were (χ12=15.62; P<.001). Both types of providers were more likely to report being very prepared/prepared for fires (91.31%) than they were for any other type of emergency (flooding, active shooter, etc.; 45.08% to 79.34%).

Future work should assess how childcare providers respond to and recover from emergencies, as well as explore the types of resources childcare providers need in order to feel comfortable caring for children during such emergency situations. (Disaster Med Public Health Preparedness. 2019;13:704–708)

This study was intended to demonstrate the applicability of the hackathon in idea generation for managing emergencies and disasters with a particular focus on flash floods.

A 4-day hackathon event was held, having 60 students, 9 mentors and 6 judges gathered to explore different ideas, and to solve problems of Iran flooding from mid-March to April, 2019. Of these, 10 teams with 6 students were accordingly formed to brainstorm and discuss the idea, while 9 mentors offered advice and guided them to manage their ideas. Then, all teams focused on designing their business models. Finally, the hackathon teams finalized their lean canvas and presented their ideas to the judging panel and the other participants.

A total of 10 ideas were presented, and based on the knowledge and experience of the judges, 3 ideas that were more practical and useful were selected.

As participants in a hackathon identify and present real-world problems, while ensuring that the prototype solutions address the end-user’s needs, it could be used to drive innovation, generate ideas, promote change in emergencies and disasters, and can increase our preparedness for future events. It helps us to develop tools and applications to better respond to these events.

To identify key decisions along the continuum of care (conventional, contingency, and crisis) and the critical triggers and data elements used to inform those decisions concerning public health and health care response during an emergency.

A classic Delphi method, a consensus-building survey technique, was used with clinicians around Washington State to identify regional triggers and indicators. Additionally, using a modified Delphi method, we combined a workshop and single-round survey with panelists from public health (state and local) and health care coalitions to identify consensus state-level triggers and indicators.

In the clinical survey, 122 of 223 proposed triggers or indicators (43.7%) reached consensus and were deemed important in regional decision-making during a disaster. In the state-level survey, 110 of 140 proposed triggers or indicators (78.6%) reached consensus and were deemed important in state-level decision-making during a disaster.

The identification of consensus triggers and indicators for health care emergency response is crucial in supporting a comprehensive health care situational awareness process. This can inform the creation of standardized questions to ask health care, public health, and other partners to support decision-making during a response. (Disaster Med Public Health Preparedness. 2017;11:467–472)

The coronavirus disease 2019 (COVID-19) pandemic has led us to use virtual solutions and emerging technologies such as artificial intelligence (AI). Recent studies have clearly demonstrated the role of AI in health care and medical practice; however, a comprehensive review can identify potential yet not fulfilled functionalities of such technologies in pandemics. Therefore, this scoping review study aims at assessing AI functionalities in the COVID-19 pandemic in 2022.

A systematic search was carried out in PubMed, Cochran Library, Scopus, Science Direct, ProQuest, and Web of Science from 2019 to May 9, 2022. Researchers selected the articles according to the search keywords. Finally, the articles mentioning the functionalities of AI in the COVID-19 pandemic were evaluated. Two investigators performed this process.

Initial search resulted in 9123 articles. After reviewing the title, abstract, and full text of these articles, and applying the inclusion and exclusion criteria, 4 articles were selectd for the final analysis. All 4 were cross-sectional studies. Two studies (50%) were performed in the United States, 1 (25%) in Israel, and 1 (25%) in Saudi Arabia. They covered the functionalities of AI in the prediction, detection, and diagnosis of COVID-19.

To the extent of the researchers’ knowledge, this study is the first scoping review that assesses the AI functionalities in the COVID-19 pandemic. Health-care organizations need decision support technologies and evidence-based apparatuses that can perceive, think, and reason not dissimilar to human beings. Potential functionalities of such technologies can be used to predict mortality, detect, screen, and trace current and former patients, analyze health data, prioritize high-risk patients, and better allocate hospital resources in pandemics, and generally in health-care settings.

Healthcare and social organizations (HSOs) are first respondents after natural disasters. Hence, their preparedness and resilience are critical components for addressing future disasters. However, little is known about HSOs’ experiences prior to, during, and after hurricanes.

To describe preparedness, response, and recovery experiences from hurricanes Irma/ Maria among HSOs in Puerto Rico and the US Virgin Islands.

Using a convenience sample, semi-structured interviews were conducted with 52 key-informants. Content analysis for common and recurring themes and patterns was performed by HSO type.

Most HSOs (80.8%) had a preparedness plan and 55.8% responded providing emergency supplies. HSOs’ human resources (61.2%) was the main recovery facilitator/ enabler, while 36.5% identified the lack of economic resources and the lack of an integrated emergency plan as the top barriers. The main lesson learned include understanding the need to make improvements to their emergency preparedness plans (56.3%), and to establish an integrated/ centralized plan between relevant parties.

Lessons learned after hurricanes allowed HSOs to identify gaps and opportunities to become more resilient. Infrastructure capacity, human resources, communication systems, and economic support, as well as training, partnerships, and new policies should be defined, revised, and/ or integrated into the HSOs’ preparedness plans to mitigate the impact of future disasters.

Since December 2019, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been discovered in Wuhan and spread rapidly across China and worldwide. Characteristics of infected patients are needed to get insight into the full spectrum of the disease.

Epidemiological and clinical information of 1738 diagnosed patients during February 7-26, 2020 in Wuhan Dongxihu Fangcang Hospital were analyzed. A total of 709 patients were followed up on symptom, mental health, isolation site, and medication after discharge.

There were 852 males and 886 females in the cohort. The average age of the patients was 48.8 y. A total of 79.98% of the patients were from Wuhan, Hubei Province. The most common initial symptoms were fever, cough, and shortness of breath. Among all the patients, 1463 had complications, with respiratory distress as the most common complication. The average duration of hospitalization was 15.95 ± 14.69 d. The most common postdischarge symptom is cough. After discharge, most patients were full of energy and chose hotel as their self-isolation site. Coronavirus disease 2019 (COVID-19) Chinese medicine No.2 prescription is the medication used most commonly by the patients after discharge.

The population is generally susceptible to SARS-CoV-2. After receiving aggressive treatment of combined Chinese and Western medicine, most patients had a good prognosis and mental health after discharge.

Disasters of all varieties have been steadily increasing in frequency. Simultaneously, “big data” has seen explosive growth as a tool in business and private industries while opportunities for robust implementation in disaster management remain nascent. To more explicitly ascertain the current status of big data as applied to disaster recovery, we conducted an integrative literature review.

Eleven databases were searched using iteratively developed keywords to target big data in a disaster recovery context. All studies were dual-screened by title and abstract followed by dual full-text review to determine if they met inclusion criteria. Articles were included if they focused on big data in a disaster recovery setting and were published in the English-language peer-reviewed literature.

After removing duplicates, 25,417 articles were originally identified. Following dual title/abstract review and full-text review, 18 studies were included in the final analysis. Among those, 44% were United States-based and 39% focused on hurricane recovery. Qualitative themes emerged surrounding geographic information systems (GIS), social media, and mental health.

Big data is an evolving tool for recovery from disasters. More research, particularly in real-time applied disaster recovery settings, is needed to further expand the knowledge base for future applications.

Analyzing Hurricane Sandy emergency reports to assess the New York State (NYS) public health system response will help inform and improve future disaster preparedness and response.

Qualitative analysis of NYS Department of Health (NYSDOH) and Nassau and Suffolk County local health department (LHD) emergency reports was conducted. Three after-action reports and 48 situation reports were reviewed, grouped by key words and sorted into 16 Public Health Preparedness Capabilities. Within each capability, key words were labeled as strengths, challenges, or recommendations.

The NYSDOH capability most cited as a strength was successful emergency operations coordination, eg, interagency conference calls (27.4% of 1681 strengths). The most cited challenge was environmental health protection, eg, mold and oil spills (28% of 706 challenges). The LHD capability most cited both as a strength (46.7% of 30 strengths) and as a challenge (32.5% of 123 challenges) was emergency operations coordination. Strengths were exemplified by sharing local resources and challenges by insufficient memorandums of understanding for coordination.

Post-disaster emergency reports should be systematically reviewed to highlight both successes and areas for improvement. Future studies should prioritize collecting feedback from a wider spectrum of public health and service provider staff for planning of preparedness and response activities. (Disaster Med Public Health Preparedness. 2015;10:308–313)