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This is a narrative review written by three experts in community medicine, disaster medicine and psychiatry reflecting the interdisciplinary approach in managing disasters. Selected important papers, personal published papers, PUBMED articles and media news related to the disaster management of the psychological effects of COVID-19 pandemic were collected over the last year, critically appraised and used in writing this manuscript.
The COVID-19 pandemic causes major emotional distress. Lack of effective treatments and availability of the current vaccines for this virus increases the fear of being infected and infecting others. Negative emotions are common and are related to adjustment but may progress in the long term to anxiety, depression, and post-traumatic stress syndrome. The COVID-19 pandemic has a major impact on mental health. The most common distress reactions include anxiety, insomnia, perception of insecurity, anger, fear of illness, and risky behaviors. Patients having mental disorders are vulnerable during the pandemic because of (1) somatic vulnerability, (2) cognitive and behavioral vulnerability, (3) psychosocial vulnerability, and (4) disruption to psychiatric care. Psychiatric wards, which are commonly separate from main hospitals, should be included in the disaster management plans. Acute care physicians carry the psychological and ethical impact of difficult triage decisions when ending the support of some patients to save others. A combination of fear and guilt may overcome normal human tolerance levels in vulnerable health workers. The moral injuries can be carried for a long time.
Addressing the psychological effects is an essential component of disaster management of infectious pandemics. This should be implemented through the whole spectrum of disaster management including preparedness, mitigation, response, and recovery.
Psychological impact has usually been ignored or has received only limited attention in disaster management plans. This review aims to address the early psychological impact of the COVID-19 pandemic, giving suggestions on how to mitigate these effects on the community, including health care providers, in the current COVID-19 pandemic as an essential component of disaster management.
The difficulties of educating psychiatric patients and making them adopt barrier measures and infectious isolation are particularly challenging. Psychiatric patients should be hospitalized if deemed necessary, for example if there was a risk to their life, or if they lack family support. It is important to note that in many countries psychiatric wards are remote from somatic medicine services and medical resuscitation units both geographically and professionally. This should be modified in disaster management plans.
Furthermore, sufficient resources should be available to support DV victims. Comprehensive DV guidelines that can be used during the response and recovery stages of disasters are already available . The effects of the COVID-19 pandemic on DV and the methods to address it should be an integral part of disaster management in all its stages, and should be included in future research on the effects of COVID-19 .
Addressing psychological effects is an essential component of the disaster management of infectious pandemics. These effects can be serious and can affect healthy subjects, patients, and health care providers. Appropriate measures should be implemented through the whole spectrum of disaster management including the preparedness, mitigation, response, and recovery.
All authors contributed to the idea. MS-H retrieved the literature on the public health and wrote the sections on it. FA-Z retrieved the literature on the economic impact, domestic violence, health care workers, and disaster management and wrote the sections on it. ES retrieved the literature on different aspects of the psychological impact and wrote the sections on it. All authors read and approved the last version of the paper.
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Specialised care is required only in a small group of population. Majority of the care occurs informally outside the medical settings by community level workers. Training these community level workers is highly essential ingredient of the disaster management. There is a need to de-medicalise the survivor's disaster response and also to de-professionalise the service delivery and focus on capacity building of the local community. By de-medicalising and de-professionalizing, gives us an opportunity to train the survivours, lay-public, local administration, community leaders, NGO's, faith healers, religious leaders, community level workers and significant others in providing care to the survivors during disaster.
Abstract:Undoubtedly, the age of big data has opened new options for natural disaster management, primarily because of the varied possibilities it provides in visualizing, analyzing, and predicting natural disasters. From this perspective, big data has radically changed the ways through which human societies adopt natural disaster management strategies to reduce human suffering and economic losses. In a world that is now heavily dependent on information technology, the prime objective of computer experts and policy makers is to make the best of big data by sourcing information from varied formats and storing it in ways that it can be effectively used during different stages of natural disaster management. This paper aimed at making a systematic review of the literature in analyzing the role of big data in natural disaster management and highlighting the present status of the technology in providing meaningful and effective solutions in natural disaster management. The paper has presented the findings of several researchers on varied scientific and technological perspectives that have a bearing on the efficacy of big data in facilitating natural disaster management. In this context, this paper reviews the major big data sources, the associated achievements in different disaster management phases, and emerging technological topics associated with leveraging this new ecosystem of Big Data to monitor and detect natural hazards, mitigate their effects, assist in relief efforts, and contribute to the recovery and reconstruction processes.Keywords: big data; disaster management; review
Once we have ensured that a dataset is not biased, we also need to decide how to integrate new distributed AI technologies within the data domain. Strategic modifications on the construction of space-based instruments like multiple small satellites3 and the introduction of edge computing (Nikos et al., 2018) have resulted in petabytes of data. Because AI relies on data transmission and computation of complex machine learning algorithms, centralized data processing and management can impose difficulties. On the one hand, real-time disaster applications require strong partnerships and data sharing between countries (recall the tsunami use case; Figure 4). On the other hand, ML algorithms are often operated in a centralized fashion, requiring training data to be fused in data servers. A centralized approach can also introduce additional challenges, such as privacy risks to personal and country-specific data. Furthermore, centralized data processing and management can limit transparency, which could lead to a lack of trust from end-users as well as difficulty in complying with regulations (e.g., GDPR).
Another important activity that can support the implementation of AI in DRR is standardization; that is, the creation of internationally recognized guidelines. Core standardization activities within the disaster management sphere are currently being undertaken by international standards developing organizations (SDOs), including the International Organization for Standardization (ISO), the International Electrotechnical Commission (IEC), and ITU. Other United Nations agencies, including WMO, UNEP, United Nations Office for Disaster Risk Reduction (UNDRR) and World Food Programme (WFP), are also contributing to the production of technical regulations, frameworks, recommended practices and de-facto standards within this field. 153554b96e