Global health disasters are on the rise and can occur at any time with little advance warning, necessitating preparation. The authors created a comprehensive evidence-based Emergency Preparedness Training Program focused on long-term retention and sustained learner engagement.

A prospective observational study was conducted of a simulation-based mass casualty event training program designed using an outcomes-based logic model. A total of 25 frontline healthcare workers from multiple hospital sites in the New York metropolitan area participated in an 8-hour immersive workshop. Data was collected from assessments, and surveys provided to participants 3 weeks prior to the workshop, immediately following the workshop, and 3 months after completion of the workshop.

The mean percentage of total knowledge scores improved across pre-workshop, post-workshop and retention (3 months post-workshop) assessments (53.2% vs. 64.8% vs. 67.6%, P < 0.05). Average comfort scores in the core MCI competencies increased across pre-workshop, post-workshop and retention self-assessments (P < 0.01). Of the participants assessed at 3 months retention (n = 14, 56%), 50.0% (n = 7) assisted in updating their hospital’s emergency operations plan and 50.0% (n = 7) pursued further self-directed learning in disaster preparedness medicine.

The use of the logic model provided a transparent framework for the design, implementation, and evaluation of a competency-based EPT program at a single academic center.

There has been a reported increase in cases of domestic violence during the coronavirus disease 2019 (COVID-19) pandemic; however, systematic research data are still unavailable. This study was conducted to find out domestic violence prevalence and coping strategies among married adults during lockdown due to COVID-19 in India.

A cross-sectional study was conducted among married men and women in the month of April 2020. Data regarding socio-demographic profile, domestic violence, and coping strategies used during lockdown were collected thorough Google Forms. A total of 97.9% of the forms were completely filled by the respondents. A descriptive analysis was done.

Of 94 study participants, approximately 7.4% (n = 7) had faced domestic violence during lockdown. Of these 7 participants, approximately 85.7% (n = 6) reported increased frequency of domestic violence during lockdown. Approximately half of the victims chose to ignore it (57.1%; n = 4) or used yoga/meditation (42.9%; n = 3) to cope.

With approximately 7.4% study participants facing domestic violence during lockdown, it is necessary to study its detailed epidemiology in pandemics so that interventions like helpline numbers, screening of patients during tele-consultation, etc., which can be delivered even during lockdown with the help of health-care and frontline workers could be devised to address this problem.

The purpose of the research was to investigate and identify the impact of COVID-19 lockdown on fine particulate matter (PM2.5) pollution in Dhaka, Bangladesh by using ground-based observation data.

The research assessed air quality during the COVID-19 pandemic for PM2.5 from January 1, 2017 to August 1, 2020. The research considered pollution in pre-COVID-19 (January 1 to March 23), during COVID-19 (March 24 to May 30), and post-COVID-19 (May 31 to August 1) lockdown periods with current (2020) and historical (2017-2019) data.

PM2.5 pollution followed a similar yearly trend in year 2017-2020. The average concentration for PM2.5 was found 87.47 μg/m 3 in the study period. Significant PM2.5 declines were observed in the current COVID-19 lockdown period compared with historical data: 11.31% reduction with an absolute decrease of 7.15 μg/m 3.

The findings of the research provide an overview of how the COVID-19 pandemic affects air pollution. The results will provide initial evidence regarding human behavioral changes and emission controls. This research will also suggest avenues for further study to link the findings with health outcomes.

Bottlenecks in the personal protective equipment (PPE) supply chain have contributed to shortages of PPE during the coronavirus disease 2019 (COVID-19) pandemic, resulting in fractures in the functionality of health-care systems. This study was conducted with the aim of determining the effectiveness of retrofitted commercial snorkel masks as an alternative respirator for health-care workers during infectious disease outbreaks.

A retrospective analysis was performed, analyzing qualitative and quantitative fit test results of the retrofitted Aria Ocean Reef® full-face snorkeling mask on health-care workers at the McGill University Health Centre between April and June 2020. Historical fit test results, using medical-grade respirators, for health-care workers, were also analyzed.

During the study period, 71 participants volunteered for fit testing, 60.6% of which were nurses. The overall fit test passing rate using the snorkel mask was 83.1%. Of the participants who did not previously pass fit testing with medical-grade respirators, 80% achieved a passing fit test with the snorkel respirator.

The results suggest that this novel respirator may be an effective and feasible alternative solution to address PPE shortages, while still providing health-care workers with ample protection. Additional robust testing will be required to ensure that respirator fit is maintained, after numerous rounds of disinfection.

The objective of this study is to assess the impact that natural disaster response has on local health departments’ (LHD) ability to continue to provide essential public health services.

A web-based survey was sent to all North Carolina Local Health Directors. The survey asked respondents to report on LHD functioning following Hurricanes Florence (2018) and Dorian (2019).

After Hurricane Florence, the positions who most frequently had regular duties postponed or interrupted were leadership (15 of 48; 31.3%), and professional staff (e.g., nursing and epidemiology: 11 of 48; 22.9%). Staffing shelters for all phases – from disaster response through long-term recovery – was identified as a burden by LHDs, particularly for nursing staff. Approximately 66.6% of LHD jurisdictions opened an Emergency Operations Center (EOC) or activated Incident Command System in response to both hurricanes. If an EOC was activated, the LHD was statistically, significantly more likely to report that normal duties had been interrupted across every domain assessed.

The ability of LHDs to perform regular activities and provide essential public health services is impacted by their obligations to support disaster response. Better metrics are needed to measure the impacts to estimate indirect public health impacts of disasters.

Mass casualty incidents (MCIs) have gained increasing attention in recent years due multiple high-profile events. MCI preparedness improves the outcomes of trauma victims, both in the hospital and prehospital settings. Yet most MCI protocols are designed for high-income countries, even though the burden of mass casualty incidents is greater in low-resource settings.

Hôpital Universitaire de Mirebalais (HUM), a 300-bed academic teaching hospital in central Haiti, developed MCI protocols in an iterative process after a large MCI in 2014. Frequent MCIs from road traffic collisions allowed protocol refinement over time. HUM’s protocols outline communication plans, triage, schematics for reorganization of the emergency department, clear delineation of human resources, patient identification systems, supply chain solutions, and security measures for MCIs. Given limited resources, protocol components are all low-cost or cost-neutral. Unique adaptations include the use of 1) social messaging for communication, 2) mass casualty carts for rapid deployment of supplies, and 3) stickers for patient identification, templated orders, and communication between providers.

These low-cost solutions facilitate a systematic response to MCIs in a resource-limited environment and help providers focus on patient care. These interventions were well received by staff and are a potential model for other hospitals in similar settings.

To characterize and compare early coverage of coronavirus disease 2019 (COVID-19) in newspapers, television, and social media, and discuss implications for public health communication strategies that are relevant to an initial pandemic response.

Latent Dirichlet allocation (LDA), an unsupervised topic modeling technique, analysis of 3271 newspaper articles, 40 cable news shows transcripts, 96,000 Twitter posts, and 1000 Reddit posts during March 4-12, 2020, a period chronologically early in the timeframe of the COVID-19 pandemic.

Coverage of COVID-19 clustered on topics such as epidemic, politics, and the economy, and these varied across media sources. Topics dominating news were not predominantly health-related, suggesting a limited presence of public health in news coverage in traditional and social media. Examples of misinformation were identified, particularly in social media.

Public health entities should use communication specialists to create engaging informational content to be shared on social media sites. Public health officials should be attuned to their target audience to anticipate and prevent spread of common myths likely to exist within a population. This may help control misinformation in early stages of pandemics.

Chengannur, a town in the south Indian state of Kerala, was 1 of the worst affected towns during the floods of 2018. Post-flood, Kerala state was under the threat of many infectious diseases including leptospirosis, but did not report any leptospirosis infections.

This study was conducted with the following objectives: (1) Assess the knowledge, attitude and practices regarding the prevention of leptospirosis among the flood affected population and Accredited Social Health Activists (ASHAs) of Chengannur; and (2) Analyze the factors responsible for and contributing to leptospirosis control in the area post flood.

A cross-sectional questionnaire based observational study was conducted among 2 groups: the flood affected population, and ASHA. The questionnaire was divided into 3 parts. Part A contained the socio-demographic information. Part B contained questions on assessment of knowledge, attitude, and practices regarding the prevention, and control of leptospirosis. Part C was only for the ASHA involved.

The final sample size was 331 (244 from the general population and 87 ASHAs). With respect to knowledge, attitude, and practice, the responses were dichotomized into correct and wrong responses. The mean knowledge score was 9.01 ± 1.08 (maximum score of 10), mean attitude score was of 3.61 ± 0.55 (maximum score of 4) and the mean practice score was 4.12 ± 1.05 (maximum score of 5).

Knowledge and attitude scores did not significantly differ between the general population and ASHA, but the practice score showed a higher score among the ASHA, all of which could have probably contributed to the prevention of a leptospirosis outbreak in the region.

The role of medical students in the current coronavirus disease 2019 (COVID-19) pandemic is rapidly evolving. The aim of this review is to explore the involvement of medical students in past global health emergencies, to help inform current and future scenarios.

A rapid systematic review was undertaken, including articles from online databases discussing the roles, willingness and appropriateness of medical student involvement in global health emergencies. Data were extracted, appraised and written up as a narrative synthesis. This study was registered with PROSPERO (CRD42020177231).

Twenty-eight articles were included. Medical students played a wide variety of clinical and nonclinical roles including education and logistics, although medical assistance was the most commonly reported role. Challenges included a lack of preparedness and negative mental health impacts. A total of 91.7% of included articles about willingness found medical students were more willing to be involved than not.

This review shows medical students are capable and willing to be involved in global health emergencies. However, there should be clear protocols for the roles that they play, taking into account the appropriateness. As a rapid review, there were study limitations and more research is required regarding the impact of these roles on medical students and the system.

To compare actual patient presentation rates from Belgium’s largest public open-air cultural festival with predictions provided by existing models and the Belgian Plan Risk Manifestations model.

Retrospectively, actual patient presentation rates gathered from the Ghent Festivities (Belgium) during 2013–2019 were compared to predicted patient presentation rates by the Arbon, Hartman, and PRIMA models.

During 7 editions, 8673000 people visited the Ghent Festivities; 9146 sought medical assistance resulting in a mean patient presentation rate (PPR) of 1.05. The PRIMA model overestimated the number of patient encounters for each occasion. The other models had a high rate of underprediction. When comparing deviations in predictions between the PRIMA model to the other models, there is a significant difference in the mean deviation (Arbon: T = 0.000, P < 0.0001, r = −0.8701; Hartman: T = 0.000, P < 0.0001, r = −0.869).

Despite the differences between the predictions of all 3 models, our results suggest that the PRIMA model is a valid tool to predict patient presentations to IEHS during public cultural MG. However, to substantiate the PRIMA model even further, more research is needed to further validate the model for a broad range of MG.

Several aspects of the coronavirus disease 2019 (COVID-19) pandemic remain ambiguous, including its transmission, severity, geographic, and racial differences in mortality. These variations merit elaboration of local patterns to inform wider national policies.

In a retrospective analysis, data of patients treated at a dedicated COVID hospital with moderate and severe illness during 8 wk of the pandemic were reviewed with attention to mortality in a competing risks framework.

A total of 1147 patients were hospitalized, and 312 (27.2%) died in hospital. Those who died were older (56.5 vs 47.6 y; P < 0.0001). Of these, 885 (77.2%) had tested positive on reverse transcriptase polymerase chain reaction (RT-PCR), with 219 (24.2%) deaths (incidence rate, 1.9 per 100 person-days). Median time from onset of symptoms to death was 11 days. A competing risks analysis for in-hospital death revealed an adjusted cause-specific hazard ratio of 1.4 for each decade increase in age.

This retrospective analysis provides broad patterns of disease presentation and mortality. Even COVID test-negative patients will receive treatment at dedicated facilities, and 33% presenting cases may die within the first 72 h, most with comorbid illness. This should be considered while planning distribution of services for effective health-care delivery

The aim of this study is to investigate the accuracy of shock index (SI) and modified shock index (mSI) in predicting the intensive care unit (ICU) requirement and in-hospital mortality among coronavirus disease (COVID-19) patients who are admitted to the emergency department (ED). Likewise, the effects of patients’ conditions such as age, gender, and comorbidity on prognosis will be analyzed.

The files were retrospectively scanned for all COVID-19 patients over the age of 18 years who were admitted to the ED and hospitalized between January 1, 2021, and March 15, 2021. The area under the receiver operating characteristic curve and the area under the curve (AUC) were used to assess each scoring system discriminatory for predicting in-hospital mortality and ICU admission.

There were 464 patients included in this study. The mean age of the patients was 62.4 ± 16.7, of which 245 were men and 219 were women. The most common comorbidity in patients was hypertension (200; 43.1%), followed by chronic obstructive pulmonary disease (174; 37.5%), and coronary artery disease (154; 33.2%). In terms of in-hospital mortality, the AUC of SI, and mSI were 0.719 and 0.739, respectively. In terms of an ICU requirement, the AUC of SI, and mSI were 0.704 and 0.729, respectively.

In this study, it was concluded that SI and mSI are useful in predicting in-hospital mortality and ICU requirement in COVID-19 patients. In addition, another important result of the study is that advanced age, male gender, and hypertension may be associated with a poor prognosis.

The coronavirus disease (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.

Stakeholders are responsible for managing the risks of disasters. Hence, appropriate, collaborative, timely interactions of involved organizations, and having a collective view of these interactions, have an important influence on the operation of the whole system. This study was aimed at social network analysis (SNA) for the implementation of the Sendai framework for disaster risk reduction in Iran.

SNA was used in this study. A review of literature on disaster risk management (DRM) plus snowball sampling technique identified a list of 85 stakeholders. Delphi method among purposefully selected experts was used to score the relationship between the stakeholders. Louvain method, along with the modularity optimization method, was applied to identify groups of stakeholders with greater interactions. Centrality measurements were used to define organizations with key-roles in the network.

The density of this network was 0.75, which showed that not all the stakeholders were connected. The National Disaster Management Organization and Civil Defense Organization showed higher influences considering their responsibilities. A total of 3 clusters of stakeholders with specific duties that mostly interact with each other and have some interaction with other groups were recognized.

Understanding the pre-disaster interaction of the network and the strengths and weaknesses of the interactions among stakeholders could help improve DRM.

People with NCDs are particularly vulnerable to disasters. This research systematically reviewed reports describing studies on the status of patients with NCDs before, during and after disasters.

Relevant articles published from 1997 to 2019 were collected by searching the Scopus, PubMed, and Science Direct databases. We specifically examined reports describing NCDs and including the key words ‘Non-Communicable Disease and Disasters.’ NCDs include cardiovascular, respiratory, diabetes and cancer diseases.

The review identified 42 relevant articles. Most of the included studies were found to have described the conditions of patients with NCDs after disasters - 14 (13.3%), during disasters – 11 (26.2%), before disasters – 6 (14.3%), within all stages of disasters: before, during and after – 6 (14.3%), only during and after disasters – 4 (9.5%), and includes before and during disasters – 1 (2.4%).

NCDs pose major health issues in disasters. Development of strong counter measures against the interruption of treatment, as well as surveillance systems to ascertain medical needs for NCDs are necessary as preparation for future disasters.