Operation based exercises represent simulation activities, which are of great importance for emergency preparedness, as they simulate real experiences in a guided manner. Whereas their primary purpose is to address the organizational emergency preparedness, little is known about the personal benefits of involved participants and whether these positive changes endure over time.

Immediate and medium term assessment of the effectiveness on individual preparedness and benefits of participants, based on self-perception, after participating in a set of 4 interdisciplinary field exercises organized as part of the MSc in Global Health-Disaster Medicine of the Medical School of the National and Kapodistrian University of Athens, Greece. The field exercises were carried out yearly, from 2016 to 2019. Data were collected via questionnaires pre- and post-exercise (1 week and 10 months after participation). The sample size was 228 trainees, with a response rate of 88%.

The majority (95%) stated that Mass Casualty Incident (MCI) exercises are appropriate for disaster management training in terms of comprehending theory, and for team-building training. In the case of a real MCI, 22% of the participants declared themselves to be ready to respond prior to MCI exercises. Upon completion, the overall perception of readiness among the participants increased to 77%. Trainee feedback indicated enhancement of both technical and non-technical skills (87%), which were persistent over time, and revealed a high level of satisfaction with the training.

This study shows a positive immediate and medium-term impact of operation-based exercises on technical, non-technical skills, and self-perception of participants.

To assess Liberian health care workers’ feelings around safety in returning to work in the setting of the Ebola virus disease outbreak of 2014–2015 after receiving infection prevention and control (IPC) training.

Academic Consortium Combating Ebola in Liberia (ACCEL) training surveys were done at 21 public, Liberian hospitals to understand health care workers’ attitudes surrounding Ebola and whether they felt safe while at work based on multiple factors. Logistic regression was used for analysis.

We found that health care workers feeling safe at work during the Ebola outbreak was primarily predicted by the number of IPC/Ebola trainings received pre-ACCEL interventions. Health care workers felt increasingly safer and motivated to return to work as trainings approached 3 (OR 8, p-value < 0.001); however, more than 3 trainings resulted in decreased safety and motivation. In addition, health care workers who reported washing their hands before and after patient contact were 3.4 times more likely to understand how to protect themselves from Ebola.

These results help to better understand the utility of repeated trainings on health care worker practice attitudes and the importance of IPC policies within hospitals, such as hand hygiene promotion and education, when coordinating humanitarian efforts.

This article investigates how perceived vulnerability to the coronavirus disease 2019 (COVID-19) pandemic at its early stages is associated with people’s perception of their health, the need for health-care services, and expenses related to addressing the COVID-19 impact on their health.

The results are based on the analysis of surveys that were distributed among members of 26 random Facebook groups in April-May, 2020. Perceived COVID-19 pandemic related stress and health concerns were examined by using the analysis of variance (ANOVA) test.

Among 315 respondents, 64% have experienced COVID-19 related stress and identified anxiety, headache, insomnia, and weight gain as their primary health concerns. The ANOVA test revealed that females are more impacted by the COVID-19 stress than males. Around 40% of respondents believed that the COVID-19 would lead to an increase in the cost of health services, and 20% of respondents anticipated that the COVID-19 pandemic would increase their need for health services.

Learning about how people perceive the COVID-19 pandemic impact on their health, particularly in the pandemic’s early stages can allow health professionals to develop targeted interventions that can influence pandemic preventative behaviors among different population groups. This study can help understand use patterns and mitigate financial barriers that could interfere with patients’ care-seeking behavior.

The objective of this study is to map vulnerability of Asian countries to the COVID-19 pandemic.

According to the Intergovernmental Panel on Climate Change (IPCC) 2007 framework for natural hazards, vulnerability is a function of exposure, sensitivity, and adaptive capacity. From an extensive literature review, we identified 16 socioeconomic, meteorological, environmental, and health factors that influence coronavirus disease 2019 (COVID-19) cases and deaths. The underlying factors of vulnerability were identified using principal component analysis.

Our findings indicate that the percentage of the urban population, obesity rate, air connectivity, and the population aged 65 and over, diabetes prevalence, and PM2.5 levels all contributed significantly to COVID-19 sensitivity. Subsequently, governance effectiveness, human development index (HDI), vaccination rate, and life expectancy at birth, and gross domestic product (GDP) all had a positive effect on adaptive capacity. The estimated vulnerability was corroborated by a Pearson correlation of 0.615 between death per million population and vulnerability.

This study demonstrates the application of universal indicators for assessing pandemic vulnerability for informed policy interventions such as the COVAX vaccine roll-out priority. Despite data limitations and a lack of spatiotemporal analysis, this study’s methodological framework allows for ample data incorporation and replication.

The aim of this study was to review the articles dealing with the mutual impacts of the coronavirus disease 2019 (COVID-19) pandemic and the recent earthquakes to elicit the various scopes of the lessons learned including the challenges, the successful measures, and the recommendations.

To detect the relevant studies published between February 1, 2020, and June 9, 2021, PubMed, Web of Science, Scopus, and Google Scholar were searched. Having considered specific inclusion/exclusion criteria, 18 studies were included.

Seven major earthquakes have occurred concurrently or before the pandemic era in Albania, Croatia, Haiti, Great East Japan, Mexico, Nepal, and Utah. Thematic analysis revealed 5 themes for the “challenges” (management inefficiency, increased life-threatening, economic, socially related, and dual psychological challenges); 4 themes for the “efficient response measures” (health-care services measures, government measures, community-based cooperative activities, and disaster management response); and 3 major themes with 7 sub-themes for the “recommendations” including “the mitigation phase” (identifying probable natural disasters), “the preparedness phase” (preparing necessary equipment), and “the response phase” (mental care response measures, health-care-related COVID-19 measures, economic improvement measures, recognizing community-based capabilities, and government-related boosting measures).

It is suggested that these scopes of the mutual impacts of the COVID-19 pandemic and the earthquakes be studied in systematic reviews.

This study sought to understand factors related to weather-related disaster survivors’ health information and mental health-care–seeking behaviors.

In November 2017, we conducted a quantitative survey of 170 Gulf Coast residents who experienced weather-related disasters. The survey assessed how individual and psychosocial factors affect health-care–seeking behavior.

Nearly 66% of participants reported a high frequency of depression and/or anxiety symptoms, yet only 39% saw a medical professional. Of participants who visited a medical professional, 76% sought information from nonmedical sources. Seeking medical care was strongly correlated with seeking information from nonmedical sources and previous healthcare experiences, but not with fear and stigma.

Positive communication and strong support systems have the potential to mitigate the reluctance people have in seeking help for mental health problems. Although it is discouraging that few people seek professional care, it is promising that participants were not avoiding care due to fear of being stigmatized. Less opposition to mental health care by survivors offers opportunity for mental health professionals to treat the psychological problems survivors experience. Providing necessary information may make headway to mental health care where it is greatly needed.

The objective of this research is to identify sociodemographic predictors of depression for a rural population in the US during the COVID-19 pandemic to enhance mental health disaster preparedness.

This study uses t-tests to differentiate between gender and ethnicity groups regarding depression status; binary logistic regression to identify socio-demographic characteristics that predict depression status; and t-test to differentiate between average depression scores, measured by the PHQ-9, pre-COVID-19 pandemic (2019) and after it’s start (2020).

Results indicate that men were less likely than women to report depression. Clients who identified as Latinx/Hispanic were 2.8 times more likely than non-Hispanics to report depression and clients who did not reside in public housing were 19.9% less likely to report depression. There was a statistically significant difference between mean PHQ-9 scores pre- and post-pandemic, with pre-pandemic scores lower on average, with a small effect size.

Building on findings from this study, we propose ways to increase rural access to mental health services, through equitable access to telemedicine, to meet the needs of rural clients to increase disaster preparedness.

To explore the health impacts of Hurricane Maria (HM) on HIV care outcomes among people living with HIV who use drugs.

Using data from an ongoing cohort study in San Juan, Puerto Rico (Proyecto PACTo), we measured differences in HIV care outcomes (viral load, viral suppression, and CD4 counts) before and after HM using assessments conducted at 6-month intervals. Generalized estimating equations were used to assess factors associated with HIV care outcomes.

All HIV care outcomes showed a deterioration from pre-HM values to post-HM values (mean viral load increased, CD4 counts decreased, and rate of viral suppression decreased) after controlling for pre-HM sociodemographic and health characteristics. In addition to HM, age (aIRR = 1·01), being homeless (aIRR = 0·78) and having health insurance (aIRR = 1·6) were independently associated with viral suppression.

219 participants completed follow-up visits between April 2017 and January 2018, before and after HM.

People living with HIV who use drugs in Puerto Rico experienced poorer HIV outcomes following HM. Socio-environmental factors contributing to these outcomes is discussed in the context of disaster response, recovery, and program planning.

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.

Food security during public health emergencies relies on situational awareness of needs and resources. Artificial intelligence (AI) has revolutionized situational awareness during crises, allowing the allocation of resources to needs through machine learning algorithms. Limited research exists monitoring Twitter for changes in the food security-related public discourse during the COVID-19 pandemic. We aim to address that gap with AI by classifying food security topics on Twitter and showing topic frequency per day.

Tweets were scraped from Twitter from January 2020 through December 2021 using food security keywords. Latent Dirichlet Allocation (LDA) topic modeling was performed, followed by time-series analyses on topic frequency per day.

237,107 tweets were scraped and classified into topics, including food needs and resources, emergency preparedness and response, and mental/physical health. After the WHO’s pandemic declaration, there were relative increases in topic density per day regarding food pantries, food banks, economic and food security crises, essential services, and emergency preparedness advice. Threats to food security in Tigray emerged in 2021.

AI is a powerful yet underused tool to monitor food insecurity on social media. Machine learning tools to improve emergency response should be prioritized, along with measurement of impact. Further food insecurity word patterns testing, as generated by this research, with supervised machine learning models can accelerate the uptake of these tools by policymakers and aid organizations.