Lessons Learned in Public Health Emergency Management: Personal Reflections

2000 ◽  
Vol 15 (4) ◽  
pp. 83-88 ◽  
Author(s):  
Kenneth W. Kizer

AbstractMultiple environmental, ecological, and socio-political forces are converging to increase the occurrence of both natural and technological disasters. Ten forces are of most concern in this regard. These are: 1) global warming, with its consequent weather extremes and climate changes; 2) continued rapid human population growth and concomitant increased urbanization; 3) decreased bio-diversity and consequent ecological fragility; 4) deforestation and loss of natural habitat for animal species, with resultant greater overlap of human and animal habitats, human exposure to animal pathogens, and other ecological perturbations; 5) increased technological development throughout the world (especially in developing countries with their typically immature safety programs) 6) globalization and increased population mobility; 7) sub-national religious and ethnic conflicts, and their potential for conflict escalation and large scale displacement of populations; 8) the collapse of several major countries and consequent unraveling of national identity and social order; 9) the rise of terrorism; and 10) dramatic advances in the science and technology of computing, communications, biotechnology, and genomics.This paper describes 10 lessons learned relative to the public health aspects of emergency management, especially as they pertain to disasters. 1) Planning pays; 2) A bad situation can be made worse by inappropriate responses; 3) Most life saving interventions will occur before the disaster happens and immediately afterwards by local action; 4) Public health emergency management is not a democratic process; 5) Psychological impacts are usually greater than anticipated; 6) Communications and information management are vital, but often are the weak link in the response chain; 7) Collaboration and partnerships are essential; 8) Unsolicited volunteers and aid are inevitable and must be planned for and managed; 9) Never assume anything, and always expect the unexpected; and 10) Post-event evaluation is important, and must be coordinated.The paramount lesson learned from past emergencies is that the untoward impact of these events can be anticipated and significantly ameliorated by appropriate planning and preparation. On the other hand, preparation for emergency events has deteriorated because of health-care financial constraints, and resources to support planning and needed infrastructure have diminished. Given these realities, the major unresolved challenge is how to ensure that planning for the common good is supported and, in fact, gets done.

SIMULATION ◽  
2017 ◽  
Vol 94 (5) ◽  
pp. 401-419
Author(s):  
Bin Chen ◽  
Peng Zhang

Epidemic transmission is a common type of public health emergency that is difficult to forecast and often causes substantial harm. Artificial societal models provide a novel approach to the study of public health problems. However, public health emergency management (PHEM) always involves multi-disciplinary and multi-hierarchical models that complicate the work of modeling. Models are also made more complex by the consideration of new requirements and interactions. Therefore, we propose a domain-specific methodology to guide the modeling process in PHEM. By analyzing domain characteristics and modeling requirements, a meta-modeling framework can be constructed, containing the basic elements with which to construct an artificial society to study epidemic transmission. In this paper, the designs of meta-models are discussed in detail, and domain models are implemented by code generation, which enables the support of large-scale, agent-based computational experiments on the KD-ACP platform. Case studies of Ebola are outlined, emergency scenarios are reconstructed based on pre-designed meta-models, and “scenario-response” experiments are presented. This study provides a valuable framework and methodology with which to study complex social problems in PHEM. The proposed method has been verified effectively and efficiently.


2009 ◽  
Vol 109 (7) ◽  
pp. 976-992 ◽  
Author(s):  
Jiaxiang Hu ◽  
Amy Z. Zeng ◽  
Lindu Zhao

2017 ◽  
Vol 15 (3) ◽  
pp. 244-252 ◽  
Author(s):  
Anita Patel ◽  
Maryann M. D'Alessandro ◽  
Karen J. Ireland ◽  
W. Greg Burel ◽  
Elaine B. Wencil ◽  
...  

2020 ◽  
Vol 16 (2) ◽  
pp. 179
Author(s):  
Lise D. Martel ◽  
Michael Phipps ◽  
Amadou Traore ◽  
Claire J. Standley ◽  
Mohamed L. Soumah ◽  
...  

2018 ◽  
Vol 30 (3) ◽  
pp. 207-216 ◽  
Author(s):  
Kyungwoo Kim ◽  
Kyujin Jung

We investigated public health emergency management networks during the recent outbreak of Middle East respiratory syndrome coronavirus that affected more than 17 000 people in South Korea. We administered a survey to 169 organizations in order to map the pattern of communication and response networks during the Middle East respiratory syndrome outbreak. We also conducted 11 semistructured interviews with national, regional, and local government officials to comprehend inhibiting and facilitating factors in risk communication and response to the system. National ministries or agencies play central roles in coordinating and supporting the overall response, and local and regional governments or agencies interact with other governments and agencies. Governmental agencies coordinating and/or supporting the outbreak response had difficulties in communicating with other agencies because of the ambiguity of the nature of the infectious disease, slow information disclosure, differences in the organizational priorities, different information standards, and the limitations of the information system. To better respond to a virus outbreak, government agencies need to improve hierarchical communication among different levels of governments, horizontal communication and cooperation between same types or different types of agencies, and information systems.


2013 ◽  
Vol 43 (5) ◽  
pp. 1028-1041 ◽  
Author(s):  
Wei Duan ◽  
Zhidong Cao ◽  
Youzhong Wang ◽  
Bin Zhu ◽  
Daniel Zeng ◽  
...  

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