To identify error-prone operational steps and key sites of self-contamination during donning and doffing of personal protective equipment (PPE).

A total of 56 health care workers including 37 nurses and 19 physicians, were recruited to don and doff the PPE recommended by the Chinese Center for Disease Control and Prevention. Operational errors and sites of self-contamination were recorded using UV-fluorescent labeling and video surveillance.

Three main errors during donning were identified: choosing a loose-fitting coverall that was difficult to handle; ignoring to inspect the seal of N95 respirator or gloves; and forgetting to pull up the zipper completely. Four main errors during doffing were identified: removing the N95 respirator in a wrong way; touching the scrubs with contaminated hands and elbows; touching contaminated external surfaces of the goggles; and performing insufficient hand hygiene. Key sites that were easily contaminated during the doffing of PPE included left hand and wrist, left lower leg, chest, and left abdomen.

Identifying the steps prone to errors and key sites of self-contamination in the process of PPE donning and doffing can facilitate the training of PPE use and provide detailed evidence for optimizing standardized protocols to reduce contamination.

Community responses are important for the management of early-phase outbreaks of coronavirus disease 2019 (COVID-19). Perceived susceptibility and severity are considered key elements that motivate people to adopt non-pharmaceutical interventions. This study aimed to i) explore perceived susceptibility and severity of the COVID-19 pandemic, ii) examine the practice of non-pharmaceutical interventions, and iii) assess the potential association of perceived COVID-19 susceptibility and severity with the practice of non-pharmaceutical interventions among people living in Afghanistan.

A cross-sectional design was employed, using online surveys disseminated from April to May 2020. Convenience sampling was used to recruit the participants of this study. The previously developed scales were used to assess the participants’ demographic information, perceived risk of SARS-CoV-2 infection, and perceived severity of COVID-19. Multivariate analyses were conducted to assess the potential association of perceived COVID-19 susceptibility and severity with the practice of non-pharmaceutical interventions.

The internet was the main source for obtaining COVID-19 information among participants in this study. While 45.8% of the participants believed it was “very unlikely” for them to get infected with COVID-19, 76.7% perceived COVID-19 as a severe disease. Similarly, 37.5% believed the chance of being cured if infected with COVID-19 is “unlikely/very unlikely”. The majority of participants (95.6%) perceived their health to be in “good” and “very good” status. Overall, 74.2% mentioned that they stopped visiting public places, 49.7% started using gloves, and 70.4% started wearing a mask. Participants who believed they have a low probability of survival if infected with COVID-19 were more likely to wear masks and practice hand washing.

It appears that communities’ psychological and behavioral responses were affected by the early phase of the COVID-19 pandemic in Afghanistan, especially among young internet users. The findings gained from a timely behavioral assessment of the community might be useful to develop interventions and risk communication strategies in epidemics within and beyond COVID-19.

This study compared the prognostic performances of the Brescia-COVID Respiratory Severity Scale (BCRSS) and the Quick COVID-19 Severity Index (qCSI) scores in hospitalized patients diagnosed with COVID-19.

The data of all adult patients (over 18 years of age) who were admitted into a state hospital with confirmed COVID-19 between May 1, 2020 and October 31, 2020 were retrospectively examined. The area under the receiver operating characteristic (ROC) curve, known as the area under the curve (AUC), was used to assess the BCRSS prediction rule and the qCSI score to assess the discriminatory power in predicting in-hospital mortality and intensive care unit (ICU) admission.

There were 341 patients included in this study. The mean age of the patients was 58.2 ± 17.2, of which 165 were men and 176 were women, and 61.3% of patients had at least one comorbidity. The most common comorbidity was hypertension. The predictive power scores of BCRSS and qCSI were found as very good in terms of in-hospital mortality (AUC 0.804 and 0.847, respectively) and likewise in terms of ICU admission (AUC 0.842 and 0.851, respectively).

Both BCRSS and qCSI scoring systems were found to be successful in predicting in-hospital mortality and ICU admission in our patient population.

This study aimed to determine whether COVID-19 is associated with a different presenting clinical picture or a more severe course of illness in people with a past history of chemical war injury.

This is a multicenter retrospective study in Fars province, Iran, from 22 August to 4 October 2020. People with a past history of chemical war injury and COVID-19 were studied. Two age- and sex-matched control groups, double the size of the patient group each, from the same database of patients with COVID-19 who were hospitalized at the same time [i.e., healthy controls and pseudocontrols].

46 people with a past history of chemical war injury, 92 healthy controls, and 92 pseudocontrols were studied. People with COVID-19 and a past history of chemical war injury had a significantly higher rate of chest pain compared to others. There were no other clinical differences between the groups. Mortality rate was 17.39%, 15.21%, and 27.17% in people with a past history of chemical war injury, the control group, and the pseudocontrol group, respectively.

A past history of a chemical war injury does not add to the risk of COVID-19 and does not significantly modify its clinical picture either.

To evaluate the mortality rates of 566,602 patients with coronavirus disease (COVID-19) based on sex, age, and the presence or absence of underlying diseases and determine whether the underlying disease provides prognostic information specifically related to death.

The mortality rate was evaluated using conditional probability to identify the significant factors, and adjusted odds ratios (ORs) using a multivariable logistic regression analysis were estimated.

The mortality rate of patients with underlying health conditions was 12%, which was 4 times higher than that of patients without underlying health conditions. Furthermore, the mortality rates of women and men with underlying health conditions were 5.5 and 3.4 times higher than the mortality rates of patients without underlying health conditions, respectively. In a multivariable logistic regression analysis including sex, age, and underlying health conditions, male sex (OR: 1.83), age ≥ 41 years (ORs > 2.70), and underlying health conditions (OR: 2.20) were confirmed as risk factors for death.

More attention should be paid to older patients with underlying diseases and male patients with underlying diseases as the probability of death in this population was significantly high.

The aim of this study was to test the appearance of negative dominance in COVID-19 vaccine-related information and activity online. We hypothesized that if negative dominance appeared, it would be a reflection of peaks in adverse events related to the vaccine, that negative content would attract more engagement on social media than other vaccine-related posts, and posts referencing adverse events related to COVID-19 vaccination would have a higher average toxicity score.

We collected data using Google Trends for search behavior, CrowdTangle for social media data, and Media Cloud for media stories, and compared them against the dates of key adverse events related to COVID-19. We used Communalytic to analyze the toxicity of social media posts by platform and topic.

While our first hypothesis was partially supported, with peaks in search behavior for image and YouTube videos driven by adverse events, we did not find negative dominance in other types of searches or patterns of attention by news media or on social media.

We did not find evidence in our data to prove the negative dominance of adverse events related to COVID-19 vaccination on social media. Future studies should corroborate these findings and, if consistent, focus on explaining why this may be the case.

The COVID-19 pandemic and associated social distancing increased stressors related to risk for domestic conflict but increases in domestic conflict early in the pandemic have yet to be studied in community samples.

Increase in domestic conflict (verbal or physical fights) since the beginning of the pandemic was assessed in 1196 partnered and cohabitating respondents, drawn from a nationally representative sample, in May 2020. Chi-square tests and logistic regression analyses were used to estimate associations of demographic characteristics and financial worry with domestic conflict.

An increase in domestic conflict was reported by 10.6% (95% CI 7.7-13.4) of the sample. Domestic conflict increase was significantly associated with younger age, lower education, and financial worry.

Increases in domestic conflict were seen in certain vulnerable groups and in those who report financial worry. Policies ensuring financial stability, particularly early in the disaster conditions, could reduce domestic conflict during continued COVID-19 conditions or other disasters.

In the wake of the SARS-CoV-2 pandemic, rapid identification of pediatric mental health risk is extremely important. The Western Regional Alliance for Pediatric Emergency Management held an integrated, interdisciplinary national tabletop exercise to familiarize mental health and non-mental health professionals with Psychological Simple Triage and Rapid Treatment (PsySTART), an evidence-based triage and incident management system used to evaluate new mental health risk impacts following exposure to traumatic events such as COVID-19.

Participants were exposed to three practice cases that reflected a combination of “all hazards” scenarios and were asked to triage each case using PsySTART. Participants were asked to interpret results both at an individual site and aggregate county and/or state level.

The exercise had a total of 115 participants with a total of 156 discrete triage encounters. A user-defined operating picture was created with graphs of aggregate mental health risk data, generating cross-regional, real-time situational awareness. After the exercise, vast majority of the participants reported confidence in their ability to use PsySTART in their practices.

Participants are now better equipped with tools to perform mental health triage for early intervention during COVID-19 and other disasters and understand risk on a population level.

To assess the hospital beds and intensive care unit (ICU) beds with a ventilator surge capacity of the health system in Kingdom of Saudi Arabia (KSA) during COVID-19 pandemic.

This study used relevant data from the National Health Emergency Operation Center to estimate general hospital and ICU beds surge capacity and tipping points under three distinct transmission scenarios.

The study results reveal that hospitals in the KSA need to be supplied with additional 4,372 hospital beds to care for COVID-19 positive cases if the pandemic continues over six months period. At the same time, it requires additional 2,192 or 1,461 hospital beds if the pandemic persists over a 12- or 18-months period, respectively, to manage hospitalized COVID-19 overloads. The health system surge capacity would suffer from a shortage of 1,600, 797, and 540 ICU beds under the three transmission scenarios to absorb critical and intensive care COVID-19 cases.

Our findings highlight the urgent need for additional hospital and ICU beds in the face of critical COVID-19 cases in KSA. The study recommends further assessment measures to the health system surge capacity to keep the Saudi health system prepared during the COVID-19 pandemic.