This study aimed to evaluate a risk of flooding and landslides among home-care patients, to reveal an extent to which patients require support for evacuation, and to determine whether risk was accurately perceived among the patients.

This is a cross-sectional study targeting the patients who were actively treated at the home-care clinic in Fukui Prefecture, Japan. We collected data on the patients’ sociodemographic and clinical characteristics. Additionally, we collected data on their risk of flooding and landslides through hazard maps and distributed a questionnaire to these patients regarding their risk awareness of flooding and landslides.

Of the 199 eligible home-care patients, 84.9% (169 of 199) were at risk of flooding and/or landslides, and 58.6% (99 of 169) of them needs support during evacuation. Furthermore, of those who were at risk of flooding and/or landslides, 46.0% (45 of 99) had accurate risk assessments. Factors that resulted in inadequate risk awareness of flooding and landslides included: not placing importance on evacuation, not using medical equipment, and living on the first floor.

There was limited risk awareness of flooding and/or landslides among the home-care patients. The information of the risk factors regarding inadequate risk awareness of flooding and landslides should be used to sophisticate flooding and landslides evacuation strategy.

The present study aims to examine coronavirus disease 2019 (COVID-19) vaccination discussions on Twitter in Turkey and conduct sentiment analysis.

The current study performed sentiment analysis of Twitter data with the artificial intelligence (AI) Natural Language Processing (NLP) method. The tweets were retrieved retrospectively from March 10, 2020, when the first COVID-19 case was seen in Turkey, to April 18, 2022. A total of 10,308 tweets accessed. The data were filtered before analysis due to excessive noise. First, the text is tokenized. Many steps were applied in normalizing texts. Tweets about the COVID-19 vaccines were classified according to basic emotion categories using sentiment analysis. The resulting dataset was used for training and testing ML (ML) classifiers.

It was determined that 7.50% of the tweeters had positive, 0.59% negative, and 91.91% neutral opinions about the COVID-19 vaccination. When the accuracy values of the ML algorithms used in this study were examined, it was seen that the XGBoost (XGB) algorithm had higher scores.

Three of 4 tweets consist of negative and neutral emotions. The responsibility of professional chambers and the public is essential in transforming these neutral and negative feelings into positive ones.

This study aimed to investigate university students’ risk perception, protective measures, and general health during the coronavirus disease 2019 (COVID-19) pandemic in Turkey.

The research sample consisted of 1920 university students. The data were collected through an online questionnaire.

A total of 56.6% of the students considered their risk of being infected with the COVID-19. The number of measures taken by students was lower than expected. Students’ increased anxiety perceived individual risk level, insufficient social support perceptions, and their perceptions of the current pandemic more serious than previous epidemics affect the number of measures they take. Students had sleep and study problems, and suicidal thoughts in the social isolation period. Sex, studying in medicine, anxiety related to COVID-19, feeling unconfident in coping with the pandemic, social support, were determined to be risk factors regarding general health, sleep and study problems, and suicidal thoughts.

The results of the study showed that the measures taken by university students were insufficient and the precautions were affected by many factors. It was determined that their health was adversely affected by the pandemic. University administrations and decision-makers should consider the risk factors to improve the students’ experiences in such pandemics and emergencies.

The purpose of this study was to investigate the current situation and influencing factors of resilience, coping style, anxiety, and depression among rescue nurses on Emergency Medical Teams (EMTs) during the disaster preparedness stage, and to explore the relationship between resilience, coping style, anxiety, and depression.

A descriptive cross-sectional survey was used. The convenience sampling method was used to select rescue nurses from 4 national EMTs in Sichuan Province, China. CD-RISC, SCSQ, Zung SAS, and SDS were used as research tools.

A total of 197 valid questionnaires were returned, with a 98.5% response rate. The results of multiple regression analysis showed that average monthly income, depression level, and coping style were the main factors affecting nurses’ resilience. Resilience was significantly and positively correlated with coping style and negatively correlated with anxiety and depression. There were significant differences in SCSQ, Zung SAS, and SDS scores among Clusters.

In the disaster preparedness stage, rescue nurses on EMTs have a medium level of resilience and good coping styles, but their levels of anxiety and depression are high. It is suggested that more attention should be devoted to the target population to formulate effective intervention plans, reduce psychological pressures, and improve their capacity for coping with disasters.

Due to constraints in the dedicated health work force, outbreaks in peri-urban slums are often reported late. This study explores the feasibility of deploying Accredited Social Health Activists (ASHAs) in outbreak investigation and understand the extent to which this activity gives a balanced platform to fulfil their roles during public health emergencies to reduce its impact and improve mitigation measures.

Activities of ASHAs involved in the hepatitis E outbreak were reviewed from various registers maintained at the subcenter. Also, various challenges perceived by ASHAs were explored through focus group discussion (FGD). During March to May 2019, 13 ASHAs involved in the hepatitis outbreak investigation and control efforts in a peri-urban slum of Nagpur with population of around 9000. In total, 192 suspected hepatitis E cases reported.

During the outbreak, ASHAs performed multiple roles comprising house-to-house search of suspected cases, escorting suspects to confirm diagnosis and referral, community mobilization for out-reach investigation camps, risk communication to vulnerable, etc. During the activity, ASHAs faced challenges such as constraints in the logistics, compromise in other health-related activities, and challenges in sustaining behavior of the community.

It is feasible to implement the investigation of outbreaks through ASHAs. Despite challenges, they are willing to participate in these activities as it gave them an opportunity to fulfil the role as an activist, link worker, as well as a community interface.

This study assessed the prevalence and correlates of depression following the April 2020 flooding in Fort McMurray.

A cross-sectional study design. Questionnaires were self-administered through an anonymous, online survey. Data collected included sociodemographics, flooding-related variables, clinical information, and likely major depressive disorder (MDD) using PHQ-9 scoring. Data were analyzed using descriptive statistics, the chi-square test, and logistic regression at P = < 0.05.

Of the 186 respondents who completed the survey, 85.5% (159) of the respondents were females, 14.5% (27) were males, 52.7% (98) were above 40 years of age, and 94% (175) were employed. The prevalence of mild to severe depression among the respondents was 53.7% (75). Respondents who reported that they are unemployed are 12 times more likely to have a moderate to severe depression (OR = 12.16; 95% CI: 1.08–136.26). Respondents who had previously received a mental health diagnosis of MDD are five times more likely to have moderate to severe depression (OR = 5.306; 95% CI: 1.84–15.27).

This study suggests that flooding could impact the psychosocial and mental health of affected people. There is a need to reassess the existing guidelines on emergency planning for flooding to reduce its impacts on mental health and identify where research can support future evidence-based guidelines.

The aim of this study was to examine safety-related contamination threats and risks to health-care workers (HCWs) due to the reuse of personal protective equipment (PPE) among emergency department (ED) personnel.

We used a Participatory Design (PD) approach to conduct task analysis (TA) of PPE use and reuse. TA identified the steps, risks, and protective behaviors involved in PPE reuse. We used the Centers for Disease Control and Prevention (CDC) guidance for PPE donning and doffing specifying the recommended task order. Then, we convened subject matter experts (SMEs) with relevant backgrounds in Patient Safety, Human Factors and Emergency Medicine to iteratively identify and map the tasks, risks, and protective behaviors involved in the PPE use and reuse.

Two emerging threats were associated with behaviors in donning, doffing, and re-using PPE: (i) direct exposure to contaminant, and (ii) transmission/spread of contaminant. Protective behaviors included: hand hygiene, not touching the patient-facing surface of PPE, and ensuring a proper fit and closure of all PPE ties and materials.

TA was helpful revealed that the procedure for donning and doffing of re-used PPE does not protect ED personnel from contaminant spread and risk of exposure, even with protective behaviors present (e.g., hand hygiene, respirator use, etc.). Future work should make more apparent the underlying risks associated with PPE use and reuse.

Despite the implementation of various coronavirus disease 2019 (COVID-19) prevention and control strategies, the rate of COVID-19 is alarmingly increasing in Ethiopia as well as worldwide. The success of COVID-19 prevention measures is highly influenced by a lack of knowledge and misconceptions. This study aimed to assess misconceptions about COVID-19 and associated factors among residents of Dilla Town, southern Ethiopia.

A community-based cross-sectional study was conducted from December 1 to 30, 2020. Data were collected from 415 individuals using structured interviewer-based questionnaires. Logistic regression analyses were used to identify the relationship between the dependent and independent variables.

The proportion of respondents who have a high misconception about COVID-19 was 41.1%. Study participants who had poor knowledge were 2.1 (95% confidence interval [CI]: 1.1-3.8) times more likely to have a misconception about COVID-19 than their counterparts. Respondents who had access to information from more than 2 sources were 3.29 (with 95% CI: 1.2-9.2) times less likely to have a misconception about COVID-19 when compared with those who had access to 2 or fewer information sources.

A significant proportion of people have misconceptions about COVID-19 in the study area. To resolve these misconceptions, health sectors and stakeholders need to improve the residents’ knowledge by delivering COVID-19–related information from credible sources on a routine basis.

Emergency medical (EM) response systems require extensive coordination, particularly during mass casualty incidents (MCIs). The recognition of preparedness gaps and contextual priorities to MCI response capacity in low- and middle-income countries (LMICs) can be better understood through the components of EM reponse systems. This study aims to delineate essential components and provide a framework for effective emergency medical response to MCIs.

A scoping review was conducted using 4 databases. Title and abstract screening was followed by full-text review. Thematic analysis was conducted to identify themes pertaining to the essential components and integration of EM response systems.

Of 20,456 screened citations, 181 articles were included in the analysis. Seven major and 40 sub-themes emerged from the content analysis as the essential components and supportive elements of MCI medical response. The essential components of MCI response were integrated into a framework demonstrating interrelated connections between essential and supportive elements.

Definitions of essential components of EM response to MCIs vary considerably. Most literature pertaining to MCI response originates from high income countries with far fewer reports from LMICs. Integration of essential components is needed in different geopolitical and economic contexts to ensure an effective MCI emergency medical response.

The article seeks to assess the Brazilian health system ability to respond to the challenges imposed by the coronavirus disease 2019 (COVID-19) pandemic by measuring the capacity of Brazilian hospitals to care for COVID-19 cases in the 450 Health Regions of the country during the year 2020. Hospital capacity refers to the availability of hospital beds, equipment, and human resources.

We used longitudinal data from the National Register of Health Facilities (CNES) regarding the availability of resources necessary to care for patients with COVID-19 in inpatient facilities (public or private) from January to December 2020. Among the assessed resources are health professionals (certified nursing assistants, nurses, physical therapists, and doctors), hospital beds (clinical, intermediate care, and intensive care units), and medical equipment (computed tomography scanners, defibrillators, electrocardiograph monitors, ventilators, and resuscitators). In addition to conducting a descriptive analysis of absolute and relative data (per 10,000 users), a synthetic indicator named Installed Capacity Index (ICI) was calculated using the multivariate principal component analysis technique to assess hospital capacity. The indicator was further stratified into value ranges to understand its evolution.

There was an increase in all selected indicators between January and December 2020. It was possible to observe differences between the Northeast and North regions and the other regions of the country; most Health Regions presented low ICI. The ICI increased between the beginning and the end of 2020, but this evolution differed among Health Regions. The average increase in the ICI was more evident in the groups that already had considerably high baseline capacity in January 2020.

It was possible to identify inequalities in the hospital capacity to care for patients affected by COVID -19 in the Health Regions of Brazil, with a concentration of low index values in the Northeast and North of the country. As the indicator increased throughout the year 2020, inequalities were also observed. The information here provided may be used by health authorities, providers, and managers in planning and adjusting for future COVID-19 care and in dimensioning the adequate supply of hospital beds, health-care professionals, and devices in Health Regions to reduce associated morbidity and mortality. We recommend that the ICI continue to be calculated in the coming months of the pandemic to monitor the capacity in the country’s Health Regions.

We aimed to examine how public health policies influenced the dynamics of coronavirus disease 2019 (COVID-19) time-varying reproductive number (Rt) in South Carolina from February 26, 2020, to January 1, 2021.

COVID-19 case series (March 6, 2020, to January 10, 2021) were shifted by 9 d to approximate the infection date. We analyzed the effects of state and county policies on Rt using EpiEstim. We performed linear regression to evaluate if per-capita cumulative case count varies across counties with different population size.

Rt shifted from 2-3 in March to <1 during April and May. Rt rose over the summer and stayed between 1.4 and 0.7. The introduction of statewide mask mandates was associated with a decline in Rt (−15.3%; 95% CrI, −13.6%, −16.8%), and school re-opening, an increase by 12.3% (95% CrI, 10.1%, 14.4%). Less densely populated counties had higher attack rates (P < 0.0001).

The Rt dynamics over time indicated that public health interventions substantially slowed COVID-19 transmission in South Carolina, while their relaxation may have promoted further transmission. Policies encouraging people to stay home, such as closing nonessential businesses, were associated with Rt reduction, while policies that encouraged more movement, such as re-opening schools, were associated with Rt increase.

This study investigates the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission potential in North Dakota, South Dakota, Montana, Wyoming, and Idaho from March 2020 through January 2021.

Time-varying reproduction numbers, Rt, of a 7-d-sliding-window and of non-overlapping-windows between policy changes were estimated using the instantaneous reproduction number method. Linear regression was performed to evaluate if per-capita cumulative case-count varied across counties with different population size or density.

The median 7-d-sliding-window Rt estimates across the studied region varied between 1 and 1.25 during September through November 2020. Between November 13 and 18, Rt was reduced by 14.71% (95% credible interval, CrI, [14.41%, 14.99%]) in North Dakota following a mask mandate; Idaho saw a 1.93% (95% CrI [1.87%, 1.99%]) reduction and Montana saw a 9.63% (95% CrI [9.26%, 9.98%]) reduction following the tightening of restrictions. High-population and high-density counties had higher per-capita cumulative case-count in North Dakota on June 30, August 31, October 31, and December 31, 2020. In Idaho, North Dakota, South Dakota, and Wyoming, there were positive correlations between population size and per-capita weekly incident case-count, adjusted for calendar time and social vulnerability index variables.

Rt decreased after mask mandate during the region’s case-count spike suggested reduction in SARS-CoV-2 transmission.

Community-level social capital organizations are critical pre-existing resources that can be leveraged in a disaster.

The study aimed to test the hypothesis that communities with larger pre-disaster stocks of social capital organizations would maintain pre-disaster levels or experience growth.

An annual panel dataset of counties in the contiguous United States from 2000 to 2014 totaling 46620 county-years, including longitudinal data on disasters and social capital institutions was used to evaluate the effect of disaster on growth of social capital.

When a county experienced more months of disasters, social capital organizations increased a year later. These findings varied based on the baseline level of social capital organizations. For counties experiencing minor disaster impacts, growth in social capital organizations tends to occur in counties with more social capital organizations in 2000; this effect is a countervailing finding to that of major disasters, and effect sizes are larger.

Given the growing frequency of smaller-scale disasters and the considerable number of communities that experienced these disasters, the findings suggest that small scale events create the most common and potentially broadest impact opportunity for intervention to lessen disparities in organizational growth.

Most emergency preparedness planning seeks to identify vulnerable population subgroups; however, focusing on chronic conditions alone may ignore other important characteristics such as location and poverty. Social needs were examined as correlates of anticipated needs and desire for assistance during an emergency.

A retrospective, secondary analysis was conducted using assessments of 8280 adult Medicaid beneficiaries in Louisiana, linked with medical (n = 7936) and pharmacy claims (n = 7473).

The sample was 73% female; 47% Black; 34% White; mean age 41 y. Many had at least 1 chronic condition (75.9%), prescription (90.3%), and social need (45.2%). Across assessments, many reported food (40%), housing (34%), and transportation (33%) needs. However, far more people anticipated social needs during an emergency than in the next month. Having social needs increased the odds of anticipating any need (odds ratio [OR] = 1.5, 1.44-1.56) and desire for assistance during an emergency, even after controlling for significant covariates including older age, race, geographic region, Medicaid plan type, and prescriptions. Chronic conditions were significantly correlated with all anticipated needs in bivariate analyses, but only modestly associated (OR = 1.03, 1.01-1.06) with anticipated medication needs in multivariable analyses.

Identifying individuals with social needs, independent of their chronic disease status, will benefit emergency preparedness outreach efforts.