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.

Using data collected from a Community Assessment for Public Health Emergency Response (CASPER) conducted in Fairfax Health District, Virginia, in 2016, we sought to assess the relationship between household-level perceived preparedness and self-reported preparedness behaviors.

Weighted population estimates and 95% confidence intervals were reported, and Pearson’s chi-squared test was used to investigate differences by group.

Examining responses to how prepared respondents felt their household was to handle a large-scale emergency or disaster, an estimated 7.4% of respondents (95% CI: 4.3–12.3) reported that their household was “completely prepared,” 37.3% (95% CI: 31.4–43.7) were “moderately prepared,” 38.2% (95% CI: 31.6–45.2) were “somewhat prepared,” and 14.4% (95% CI: 10.2–20.0) were “unprepared.” A greater proportion of respondents who said that their household was “completely” or “moderately” prepared for an emergency reported engaging in several behaviors related to preparedness. However, for several preparedness behaviors, there were gaps between perceived preparedness and self-reported readiness.

Community assessments for public health preparedness can provide valuable data about groups who may be at risk during an emergency due to a lack of planning and practice, despite feeling prepared to handle a large-scale emergency or disaster.

The aim of this study is to describe the risk factors of injured children’s posttraumatic stress disorder (PTSD) in China and provide the scientific data for PTSD prevention and control in children.

Electronic databases, including Medline, Science Direct, Google Scholar, and CNKI (China National Knowledge Infrastructure), were searched for articles published on or before October 30, 2018, searching for the words, “PTSD,” “child”/“children,” “injury”/“injuries,” and “China”/“Chinese.” Forty-seven articles met the inclusion criteria and were meta-analyzed using random-effect models.

The total sample size in our meta-analysis was 65 298, and there were 13 402 children diagnosed with PTSD. The prevalence of PTSD after suffering from injury was 20.52% (95% CI = 17%–23%). PTSD occurrence was higher in girls than boys (24.61% vs 19.36%, P < 0.001). The PTSD rate for students was 51.82%, 37.12%, and 14.02% in senior, junior high school children, and primary school student, respectively. PTSD prevalence was 58.93% in rural children and higher than the urban children (57.36%). The prevalence of PTSD in ethnic minority children was significantly higher than that of Han Chinese children (35.38% vs 13.50%).

PTSD in injured children is significantly higher in girls, senior high school children, in rural areas, and in ethnic minority children. PTSD prevention and control should be focused on these 4 subgroups.

Syndromic surveillance has been useful for routine surveillance on a variety of health outcomes and for informing situational awareness during public health emergencies. Following the landfall of Hurricane Maria in 2017, the New York City (NYC) Department of Health and Mental Hygiene (DOHMH) implemented an enhanced syndromic surveillance system to characterize related emergency department (ED) visits.

ED visits with any mention of specific key words (“Puerto,” “Rico,” “hurricane,” “Maria”) in the ED chief complaint or Puerto Rico patient home Zip Code were identified from the DOHMH syndromic surveillance system in the 8-week window leading up to and following landfall. Visit volume comparisons pre- and post-Hurricane Maria were performed using Fisher’s exact test.

Analyses identified an overall increase in NYC ED utilization relating to Puerto Rico following Hurricane Maria landfall. In particular, there was a small but significant increase in visits involving a medication refill or essential medical equipment. Visits for other outcomes, such as mental illness, also increased, but the differences were not statistically significant.

Gaining this situational awareness of medical service use was informative following Hurricane Maria, and, following any natural disaster, the same surveillance methods could be easily established to aid an effective emergency response.

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.

Earthquakes, landslides, and floods are the most frequent natural disasters in Turkey. The country has also recently experienced an increased number of terrorist attacks. The purpose of this study is to understand the expectations and training of Turkish emergency medicine attending physicians in disaster medicine.

An online questionnaire was administered to the 937 members of the Emergency Medicine Association of Turkey, of which 191 completed the survey (20%).

Most participants (68%) worked at a Training and Research Hospital (TRH) or a University Hospital (UH), and 69% had practiced as an attending for 5 years or less. Mass immigration, refugee problems, and war/terror attacks were considered to be the highest perceived risk topics. Most (95%) agreed that disaster medicine trainings should occur during residency training. Regular disaster drills and exercises and weekly or monthly trainings were the most preferred educational modalities. Most respondents (85%) were interested in advanced training in disaster medicine, and this was highest for those working less than 5 years as an attending. UH and TRH residency training programs were not considered in themselves to be sufficient for learning disaster medicine.

Turkish emergency medicine residency training should include more disaster medicine education and training.

Hurricane Harvey left a path of destruction in its wake, resulting in over 100 deaths and damaging critical infrastructure. During a disaster, public health surveillance is necessary to track emerging illnesses and injuries, identify at-risk populations, and assess the effectiveness of response efforts. The Centers for Disease Control and Prevention (CDC) and American Red Cross collaborate on shelter surveillance to monitor the health of the sheltered population and help guide response efforts.

We analyzed data collected from 24 Red Cross shelters between August 25, 2017, and September 14, 2017. We described the aggregate morbidity data collected during Harvey compared with previous hurricanes (Gustav, Ike, and Sandy).

Over one-third (38%) of reasons for visit were for health care maintenance; 33% for acute illnesses, which includes respiratory conditions, gastrointestinal symptoms, and pain; 19% for exacerbation of chronic disease; 7% for mental health; and 4% for injury. The Red Cross treated 41% of clients within the shelters; however, reporting of disposition was often missed. These results are comparable to previous hurricanes.

The capacity of Red Cross shelter staff to address the acute health needs of shelter residents is a critical resource for local public health agencies overwhelmed by the disaster. However, there remains room for improvement because reporting remained inconsistent.

To determine the extent of service disruption among home health agencies impacted by Hurricane Harvey.

Structured interviews with optional open-ended questions were conducted with home health agencies in and around Houston, Texas. A random sample of 277 agencies was selected and contacted via telephone during the study period, from February to May of 2018.

Only 45% of 122 participating agencies indicated that their offices were open during Hurricane Harvey, and three-fourths reported that home visits were disrupted. The length of disruption varied: 7% reported a disruption of 1 day or less and 46% indicated a disruption of 1 week or longer. Disruption occurred even though nearly all (99%) of the agencies had—and close to all (92%) of them activated—an emergency preparedness plan.

Although most of the participating home health agencies activated their emergency preparedness plan, significant disruption in home health services occurred. While agencies are required to have clear, detailed plans in place, gaps in effective implementation of emergency preparedness plans remain.

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.

One method of monitoring public preparedness is through measuring public interest in preventive measures. The objective of this study was to analyze public interest in the coronavirus disease 2019 (COVID-19) preventive measures and to identify variables associated with timely stay-at-home (SAH) orders issued by governors.

State-level search volume was collected from Google Trends. Average preventive measure interest was calculated for the query terms “hand sanitizer,” “hand washing,” “social distancing,” and “COVID testing.” We then calculated the delay in statewide SAH orders from March 1, 2020, to the date of issuance and by-state presidential voting percentage. Bivariate correlations were computed to assess the relationship between interest in preventive measures and SAH order delay.

The correlation between average preventive measure interest and length of time before the SAH order was placed was −0.47. Average preventive measure interest was also inversely related to voting for a Republican presidential nominee in the 2016 election (R = −0.75), the latter of which was positively associated with longer delays in SAH orders (R = 0.48).

States with greater public interest in COVID-19 preventive measures were inversely related to governor issuance of timely SAH orders. Increasing public interest in preventive measures may slow the spread of the virus that causes COVID-19, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), by improving preparedness.

After-action reports analyze events and improve knowledge about how to prevent and react to unexpected situations. Anyway, there is no consensus among the templates developed for disaster events reporting, and there is not a specific model for reporting hospital disaster response.

The study was aimed to pilot the use of a new assessment tool for hospital response to natural disasters.

A data collection tool, focused on hospital disaster response to natural disasters, was created modifying the “Utstein-Style Template for Uniform Data Reporting of Acute Medical Response in Disasters” and tested the reaction of the nearest hospitals to the epicenter after the August 24, 2016, Central Italy earthquake.

Four hospitals were included. The completion rate of the tool was 97.10%. A total of 613 patients accessed the 4 emergency departments, most of them in Rieti Hospital (178; 29.04%). Three hundred thirty-six (54.81%) patients were classified as earthquake-related, most with trauma injuries (260; 77.38%).

This template seemed to be a valid instrument for hospital disaster management reporting and could be used for better comprehension of hospital disaster reaction, debriefing activities, and hospital disaster plan revisions.

Human stampedes (HS) may result in mass casualty incidents (MCI) that arise due to complex interactions between individuals, collective crowd, and space, which have yet to be described from a physics perspective. HS events were analyzed using basic physics principles to better understand the dynamic kinetic variables that give rise to HS.

A literature review was performed of medical and nonmedical sourced databases, Library of Congress databases, and online sources for the term human stampedes resulting in 25,123 references. Filters were applied to exclude nonhuman events. Retrieved references were reviewed for a predefined list of physics terms. Data collection involved recording frequency of each phrase and physics principle to give the final proportions of each predefined principle used a single-entry method for each of the 105 event reports analyzed. Data analysis was performed using the R statistics packages “tidyverse”, “psych”, “lubridate”, and “Hmisc” with descriptive statistics used to describe the frequency of each observed variable.

Of the 105 reports of HS resulting in injury or death reviewed, the following frequency of terms were found: density change in a limited capacity, 45%; XY-axis motion failure, 100%; loss of proxemics, 100%; deceleration with average velocity of zero, 90%; Z-axis displacement pathology (falls), 92%; associated structure with nozzle effect, 93%; and matched fluid dynamic of high pressure stagnation of mass gathering, 100%.

Description or reference to principles of physics was seen in differing frequency in 105 reports. These include XY-axis motion failure of deceleration that leads to loss of human to human proxemics, and high stagnation pressure resulting in the Z-axis displacement effect (falls) causing injury and death. Real-time video-analysis monitoring of high capacity events or those with known nozzle effects for loss of proxemics and Z-axis displacement pathology offers the opportunity to prevent mortality from human stampedes.