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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.
Disasters of all varieties have been steadily increasing in frequency. Simultaneously, “big data” has seen explosive growth as a tool in business and private industries while opportunities for robust implementation in disaster management remain nascent. To more explicitly ascertain the current status of big data as applied to disaster recovery, we conducted an integrative literature review.
Eleven databases were searched using iteratively developed keywords to target big data in a disaster recovery context. All studies were dual-screened by title and abstract followed by dual full-text review to determine if they met inclusion criteria. Articles were included if they focused on big data in a disaster recovery setting and were published in the English-language peer-reviewed literature.
After removing duplicates, 25,417 articles were originally identified. Following dual title/abstract review and full-text review, 18 studies were included in the final analysis. Among those, 44% were United States-based and 39% focused on hurricane recovery. Qualitative themes emerged surrounding geographic information systems (GIS), social media, and mental health.
Big data is an evolving tool for recovery from disasters. More research, particularly in real-time applied disaster recovery settings, is needed to further expand the knowledge base for future applications.
Modern digital strategies, including Internet of Things, machine learning, and mobile applications, have revolutionized situational awareness during disaster management. Despite their importance, no review of digital strategies to support emergency food security efforts has been conducted. This scoping review fills that gap.
Keywords were defined within the concepts of food assistance, digital technology, and disasters. After the database searches, PRISMA guidelines were followed to perform a partnered, 2-round scoping literature review.
The search identified 3201 articles, and 26 articles met criteria and were included in the analysis. The data types used to describe the tools were text/opinion (42.3%), qualitative (23.1%), system architecture (19.2%), quantitative and qualitative (11.5 %), and quantitative (3.8%). The tools’ main functions were Resource Allocation (41.7%), Data Collection and Management (33%), Interagency Communications (15.4 %), Beneficiary Communications (11.5%), and Fundraising (7.7%). The platforms used to achieve these goals were Mobile Application (36%), Internet of Things (20%), Website (20%), and Mobile Survey (8%); 92% covered the disaster response phase.
Digital tools for planning, situational awareness, client choice, and recovery are needed to support emergency food assistance, but there is a lack of these tools and research on their effectiveness across all disaster phases.
Influenza vaccination remains the most effective primary prevention strategy for seasonal influenza. This research explores the percentage of emergency medical services (EMS) clinicians who received the seasonal flu vaccine in a given year, along with their reasons for vaccine acceptance and potential barriers.
A survey was distributed to all EMS clinicians in Virginia during the 2018-2019 influenza season. The primary outcome was vaccination status. Secondary outcomes were attitudes and perceptions toward influenza vaccination, along with patient care behaviors when treating an influenza patient.
Ultimately, 2796 EMS clinicians throughout Virginia completed the survey sufficiently for analysis. Participants were mean 43.5 y old, 60.7% male, and included the full range of certifications. Overall, 79.4% of surveyed EMS clinicians received a seasonal flu vaccine, 74% had previously had the flu, and 18% subjectively reported previous side effects from the flu vaccine. Overall, 54% of respondents believed their agency has influenza or respiratory specific plans or procedures.
In a large, state-wide survey of EMS clinicians, overall influenza vaccination coverage was 79.4%. Understanding the underlying beliefs of EMS clinicians remains a critical priority for protecting these frontline clinicians. Agencies should consider practical policies, such as on-duty vaccination, to increase uptake.
The national response to the coronavirus disease 2019 (COVID-19) pandemic has highlighted critical weaknesses in domestic health care and public health emergency preparedness, despite nearly 2 decades of federal funding for multiple programs designed to encourage cross-cutting collaboration in emergency response. Health-care coalitions (HCCs), which are funded through the Hospital Preparedness Program, were first piloted in 2007 and have been continuously funded nationwide since 2012 to support broad collaborations across public health, emergency management, emergency medical services, and the emergency response arms of the health-care system within a geographical area. This commentary provides a SWOT (strengths, weaknesses, opportunities, and threats) analysis to summarize the strengths, weaknesses, opportunities, and threats related to the current HCC model against the backdrop of COVID-19. We close with concrete recommendations for better leveraging the HCC model for improved health-care system readiness. These include better evaluating the role of HCCs and their members (including the responsibility of the HCC to better communicate and align with other sectors), reconsidering the existing framework for HCC administration, increasing incentives for meaningful community participation in HCC preparedness, and supporting next-generation development of health-care preparedness systems for future pandemics.
Since its 1960s origins, the Haddon matrix has served as a tool to understand and prevent diverse mechanisms of injuries and promote safety. Potential remains for broadened application and innovation of the matrix for disaster preparedness. Hospital functionality and efficiency are particularly important components of community vulnerability in developed and developing nations alike. Given the Haddon matrixʼs user-friendly approach to integrating current engineering concepts, behavioral sciences, and policy dimensions, we seek to apply it in the context of hospital earthquake preparedness and response. The matrixʼs framework lends itself to interdisciplinary planning and collaboration between social and physical sciences, paving the way for a systems-oriented reduction in vulnerabilities. Here, using an associative approach to integrate seemingly disparate social and physical science disciplines yields innovative insights about hospital disaster preparedness for earthquakes. We illustrate detailed examples of pre-event, event, and post-event engineering, behavioral science, and policy factors that hospital planners should evaluate given the complex nature, rapid onset, and broad variation in impact and outcomes of earthquakes. This novel contextual examination of the Haddon matrix can enhance critical infrastructure disaster preparedness across the epidemiologic triad, by integrating essential principles of behavioral sciences, policy, law, and engineering to earthquake preparedness.
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