Defining Disaster-Related Health Risk: A Primer for Prevention

2018 ◽  
Vol 33 (3) ◽  
pp. 308-316 ◽  
Author(s):  
Mark Keim
Keyword(s):  
Public Health ◽  
Risk Management ◽  
Health Risk ◽  
Disaster Risk ◽  
International Standards ◽  
Disaster Risk Management ◽  
Health Determinants ◽  
Publication Type ◽  
Ongoing Research ◽  
Public Health Decision

AbstractEffective disaster risk management requires not only management of the immediate problem (disaster-related injuries and disease), but also of the patient’s risk factors and of the underlying health determinants. This requires an accurate and well-validated process for assessment of the determinants of disease.Ideally, disaster risk management is based on a prioritization process. Once hazards have been identified, they are assessed in terms of the probability and impact in terms of losses. The hazards associated with the greatest probability and impact loss are prioritized. In addition to prioritization, risk assessment also offers a process for ongoing research involving the interaction of health determinants, risk, and protective factors that may contribute to future adverse health outcomes.Recently, assessments of health risk have become an integral part of local, state, and national emergency preparedness programs. One of the strengths of these assessments is the convening of multi-sectoral input for public health decision making and plans. However, this diversity of input also creates challenges in development of a common nomenclature for assessing and communicating the characteristics of this risk. Definitions remain ambiguous for many of the key indicators of disaster risk, especially those applied to health risk.This report is intended as a primer for defining disaster-related health risk. This framework is discussed within a nomenclature that is consistent with international standards for risk management and public health prevention.KeimM. Defining disaster-related health risk: a primer for prevention. Prehosp Disaster Med. 2018;33(3):308-316.

scholarly journals Research in Health-Emergency and Disaster Risk Management and Its Potential Implications in the Post COVID-19 World

2021 ◽  
Vol 18 (5) ◽  
pp. 2520
Author(s):  
Emily Ying Yang Chan ◽  
Holly Ching Yu Lam
Keyword(s):  
Risk Management ◽  
Health Risk ◽  
Disaster Risk ◽  
Disaster Risk Management ◽  
Global Policy ◽  
Policy Shift ◽  
Health Risk Management ◽  
Research And Policy

Health-Emergency Disaster Risk Management (Health-EDRM) is one of the latest academic and global policy paradigms that capture knowledge, research and policy shift from response to preparedness and health risk management in non-emergency times [...]

scholarly journals DEVELOPMENT OF TIME-SERIES HUMAN SETTLEMENT MAPPING SYSTEM USING HISTORICAL LANDSAT ARCHIVE

2016 ◽  
Vol XLI-B8 ◽  
pp. 1385-1388
Author(s):  
H. Miyazaki ◽  
M. Nagai ◽  
R. Shibasaki
Keyword(s):  
Public Health ◽  
Time Series ◽  
Risk Management ◽  
Satellite Data ◽  
Disaster Risk ◽  
Disaster Risk Management ◽  
Training Data ◽  
Series Data ◽  
Landsat Data ◽  
Human Settlement

Methodology of automated human settlement mapping is highly needed for utilization of historical satellite data archives for urgent issues of urban growth in global scale, such as disaster risk management, public health, food security, and urban management. As development of global data with spatial resolution of 10-100 m was achieved by some initiatives using ASTER, Landsat, and TerraSAR-X, next goal has targeted to development of time-series data which can contribute to studies urban development with background context of socioeconomy, disaster risk management, public health, transport and other development issues. We developed an automated algorithm to detect human settlement by classification of built-up and non-built-up in time-series Landsat images. A machine learning algorithm, Local and Global Consistency (LLGC), was applied with improvements for remote sensing data. The algorithm enables to use MCD12Q1, a MODIS-based global land cover map with 500-m resolution, as training data so that any manual process is not required for preparation of training data. In addition, we designed the method to composite multiple results of LLGC into a single output to reduce uncertainty. The LLGC results has a confidence value ranging 0.0 to 1.0 representing probability of built-up and non-built-up. The median value of the confidence for a certain period around a target time was expected to be a robust output of confidence to identify built-up or non-built-up areas against uncertainties in satellite data quality, such as cloud and haze contamination. Four scenes of Landsat data for each target years, 1990, 2000, 2005, and 2010, were chosen among the Landsat archive data with cloud contamination less than 20%.We developed a system with the algorithms on the Data Integration and Analysis System (DIAS) in the University of Tokyo and processed 5200 scenes of Landsat data for cities with more than one million people worldwide.

scholarly journals DEVELOPMENT OF TIME-SERIES HUMAN SETTLEMENT MAPPING SYSTEM USING HISTORICAL LANDSAT ARCHIVE

2016 ◽  
Vol XLI-B8 ◽  
pp. 1385-1388 ◽  
Author(s):  
H. Miyazaki ◽  
M. Nagai ◽  
R. Shibasaki
Keyword(s):  
Public Health ◽  
Time Series ◽  
Risk Management ◽  
Satellite Data ◽  
Disaster Risk ◽  
Disaster Risk Management ◽  
Training Data ◽  
Series Data ◽  
Landsat Data ◽  
Human Settlement

Methodology of automated human settlement mapping is highly needed for utilization of historical satellite data archives for urgent issues of urban growth in global scale, such as disaster risk management, public health, food security, and urban management. As development of global data with spatial resolution of 10-100 m was achieved by some initiatives using ASTER, Landsat, and TerraSAR-X, next goal has targeted to development of time-series data which can contribute to studies urban development with background context of socioeconomy, disaster risk management, public health, transport and other development issues. We developed an automated algorithm to detect human settlement by classification of built-up and non-built-up in time-series Landsat images. A machine learning algorithm, Local and Global Consistency (LLGC), was applied with improvements for remote sensing data. The algorithm enables to use MCD12Q1, a MODIS-based global land cover map with 500-m resolution, as training data so that any manual process is not required for preparation of training data. In addition, we designed the method to composite multiple results of LLGC into a single output to reduce uncertainty. The LLGC results has a confidence value ranging 0.0 to 1.0 representing probability of built-up and non-built-up. The median value of the confidence for a certain period around a target time was expected to be a robust output of confidence to identify built-up or non-built-up areas against uncertainties in satellite data quality, such as cloud and haze contamination. Four scenes of Landsat data for each target years, 1990, 2000, 2005, and 2010, were chosen among the Landsat archive data with cloud contamination less than 20%.We developed a system with the algorithms on the Data Integration and Analysis System (DIAS) in the University of Tokyo and processed 5200 scenes of Landsat data for cities with more than one million people worldwide.

scholarly journals Sociodemographic Predictors of Health Risk Perception, Attitude and Behavior Practices Associated with Health-Emergency Disaster Risk Management for Biological Hazards: The Case of COVID-19 Pandemic in Hong Kong, SAR China

2020 ◽  
Vol 17 (11) ◽  
pp. 3869 ◽  
Author(s):  
Emily Ying Yang Chan ◽  
Zhe Huang ◽  
Eugene Siu Kai Lo ◽  
Kevin Kei Ching Hung ◽  
Eliza Lai Yi Wong ◽  
...  
Keyword(s):  
Risk Management ◽  
Hong Kong ◽  
Risk Perception ◽  
Health Risk ◽  
Well Being ◽  
Disaster Risk ◽  
Disaster Risk Management ◽  
Behavior Patterns ◽  
Cross Sectional ◽  
And Behavior

In addition to top-down Health-Emergency and Disaster Risk Management (Health-EDRM) efforts, bottom-up individual and household measures are crucial for prevention and emergency response of the COVID-19 pandemic, a Public Health Emergency of International Concern (PHEIC). There is limited scientific evidence of the knowledge, perception, attitude and behavior patterns of the urban population. A computerized randomized digital dialing, cross-sectional, population landline-based telephone survey was conducted from 22 March to 1 April 2020 in Hong Kong Special Administrative Region, China. Data were collected for socio-demographic characteristics, knowledge, attitude and risk perception, and various self-reported Health-EDRM behavior patterns associated with COVID-19. The final study sample was 765. Although the respondents thought that individuals (68.6%) had similar responsibilities as government (67.5%) in infection control, less than 50% had sufficient health risk management knowledge to safeguard health and well-being. Among the examined Health-EDRM measures, significant differences were found between attitude and practice in regards to washing hands with soap, ordering takeaways, wearing masks, avoidance of visiting public places or using public transport, and travel avoidance to COVID-19-confirmed regions. Logistic regression indicated that the elderly were less likely to worry about infection with COVID-19. Compared to personal and household hygiene practices, lower compliance was found for public social distancing.

scholarly journals Research Frontiers of Health Emergency and Disaster Risk Management: What Do We Know So Far?

2020 ◽  
Vol 17 (5) ◽  
pp. 1807
Author(s):  
Emily Ying Yang Chan ◽  
Holly Ching Yu Lam
Keyword(s):  
Risk Management ◽  
Health Risk ◽  
Paradigm Shift ◽  
Disaster Risk ◽  
Disaster Risk Management ◽  
Policy Paradigm ◽  
Health Risk Management ◽  
Research Frontiers ◽  
Research And Policy

Health-Emergency Disaster Risk Management (Health-EDRM) emerged as the latest knowledge, research and policy paradigm shift from response to preparedness and health risk management in non-emergency times [...]

Challenges and Strategies for Climate Change Adaptation Among Pacific Island Nations

2012 ◽  
Vol 6 (4) ◽  
pp. 415-423
Author(s):  
Mollie J. Mahany ◽  
Mark E. Keim
Keyword(s):  
Public Health ◽  
Climate Change ◽  
Risk Management ◽  
Climate Change Adaptation ◽  
Disaster Risk ◽  
Disaster Risk Management ◽  
Small Island ◽  
Pacific Island ◽  
Small Island Developing States ◽  
The Pacific

ABSTRACTFew regions of the world are at higher risk for environmental disasters than the Pacific Island countries and territories. During 2004 and 2005, the top public health leadership from 19 of 22 Pacific Island countries and territories convened 2 health summits with the goal of developing the world's first comprehensive regional strategy for sustainable disaster risk management as applied to public health emergencies. These summits followed on the objectives of the 1994 Barbados Plan of Action for the Sustainable Development of Small Island Developing States and those of the subsequent Yokohama Strategy and Plan of Action for a Safer World. The outputs of the 2004 and 2005 Pacific Health Summits for Sustainable Disaster Risk Management provide a detailed description of challenges and accomplishments of the Pacific Island health ministries, establish a Pacific plan of action based upon the principles of disaster risk management, and provide a locally derived, evidence-based approach for many climate change adaptation measures related to extreme weather events in the Pacific region. The declaration and outputs from these summits are offered here as a guide for developmental and humanitarian assistance in the region (and for other small-island developing states) and as a means for reducing the risk of adverse health effects resulting from climate change.(Disaster Med Public Health Preparedness. 2012;6:415-423)

scholarly journals CLOUD-BASED INTEGRATION AND STANDARDIZATION OF ADDRESS DATA FOR DISASTER MANAGEMENT – A SOUTH AFRICAN CASE STUDY

2020 ◽  
Vol XLIV-3/W1-2020 ◽  
pp. 145-150
Author(s):  
G. Tredrea ◽  
S. Coetzee ◽  
V. Rautenbach
Keyword(s):  
South Africa ◽  
Risk Management ◽  
South African ◽  
Disaster Risk ◽  
Political Support ◽  
International Standards ◽  
Disaster Risk Management ◽  
National Standard ◽  
Use Of Resources ◽  
Address Data

Abstract. Addresses are essential for disaster risk management and response because they are used to locate people affected by a disaster or at risk of being affected. South Africa is vulnerable to disasters, however, despite a legislative framework for supporting disaster risk management that meets international standards, implementation falls short due to underfunding, poor interdepartmental coordination and lack of political support. The importance of cross jurisdictional address data was highlighted by the COVID-19 pandemic of 2020 when the geocoding of positive cases was hindered due to the lack of such address data in South Africa. In this paper, we present first results about a cloud-based tool for integrating address data from multiple municipalities into a single address dataset that conforms to the South African National Standard, SANS 1883-2:2017, Geographic information – Addresses: Part 2: Address data exchange. We reviewed and evaluated three cloud platforms for the prototype implementation. The integrated dataset is maintained in the cloud and therefore readily accessible by relevant organizations. At the same time, processing in the cloud can handle changing volumes of data with elasticity, i.e. computing power can be increased or decreased at short notice, as necessary during a disaster response. Furthermore, processing can be automated, thereby mitigating the risk of reduced manpower due to a disaster. Overall, a properly maintained cloud-based tool can result in more efficient use of resources presenting a viable and interesting alternative for underfunded disaster risk management centres in South Africa and other parts of the world.

scholarly journals From Science to Policy and Practice: A Critical Assessment of Knowledge Management Before, During, and After Environmental Public Health Disasters

2019 ◽  
Vol 34 (s1) ◽  
pp. s73-s74
Author(s):  
Mélissa Généreux ◽  
Marc Lafontaine ◽  
Angela Eykelbosh
Keyword(s):  
Public Health ◽  
Risk Management ◽  
Knowledge Management ◽  
Participant Observation ◽  
Disaster Risk ◽  
Disaster Risk Management ◽  
World Health ◽  
Policy And Practice ◽  
Environmental Public Health ◽  
Wide Range

Introduction:Canada, like many countries, increasingly faces environmental public health (EPH) disasters. Such disasters often require both short- and long-term responses, necessitate evacuation and relocation, cause major environmental impacts, and generate the need for specific knowledge and expertise (chemistry, epidemiology, risk assessment, mental health, etc.).Aim:Given the importance of evidence-based, risk-informed decision making, we aimed to critically assess the integration of EPH expertise and research into each phase of disaster risk management in several Canadian and other jurisdictions.Methods:In-depth interviews were conducted with 23 leaders in disaster risk management from Canada, United States, United Kingdom, and Australia, and were complemented by other methods (i.e. participant observation, information gathered from participation in scientific events, and document review). Three criteria were explored: governance, knowledge creation and translation, and related needs and barriers. An interview guide was developed based on a standardized toolkit from the World Health Organization. Data were analyzed through a four-step content analysis.Results:Six cross-cutting themes emerged from the analysis. These themes are identified as critical factors in successful disaster knowledge management: 1) blending the best of traditional and modern approaches, 2) fostering community engagement; 3) cultivating relationships, 4) investing in preparedness and recovery, 5) putting knowledge into practice, and 6) ensuring sufficient human and financial resources. A wide range of promising knowledge-to-action strategies was also identified, including mentorship programs, communities of practice, advisory groups, systematized learning, and comprehensive repositories of tools and resources.Discussion:There is no single roadmap to incorporate EPH knowledge and expertise into disaster risk management. Our findings suggest that beyond structures and plans, it is necessary to cultivate relationships and share responsibility for ensuring the safety, health, and wellbeing of affected communities while respecting the local culture, capacity, and autonomy. Any such considerations should be incorporated into disaster risk management planning.

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