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1.
Public Health Rep ; 137(5): 820-825, 2022.
Artigo em Inglês | MEDLINE | ID: mdl-35658738

RESUMO

Upon request from tribal nations, and as part of the Centers for Disease Control and Prevention's (CDC's) emergency response, CDC staff provided both remote and on-site assistance to tribes to plan, prepare, and respond to the COVID-19 pandemic. From April 2, 2020, through June 11, 2021, CDC deployed a total of 275 staff to assist 29 tribal nations. CDC staff typically collaborated in multiple work areas including epidemiology and surveillance (86%), contact tracing (76%), infection prevention control (72%), community mitigation (72%), health communication (66%), incident command structure (55%), emergency preparedness (38%), and worker safety (31%). We describe the activities of CDC staff in collaboration with 4 tribal nations, Northern Cheyenne, Hoopa Valley, Shoshone-Bannock, and Oglala Sioux Tribe, to combat COVID-19 and lessons learned from the engagement.


Assuntos
COVID-19 , Defesa Civil , COVID-19/epidemiologia , COVID-19/prevenção & controle , Centers for Disease Control and Prevention, U.S. , Humanos , Pandemias/prevenção & controle , Estados Unidos/epidemiologia
2.
J Public Health Manag Pract ; 22(3): E29-38, 2016.
Artigo em Inglês | MEDLINE | ID: mdl-23263628

RESUMO

OBJECTIVE: The main objective of this study is to review information within the situation reports (SITREPs) and incident notices (INs) prepared by the Division of Bioterrorism Preparedness and Response/Epidemiology Surveillance and Response Branch, (DBPR/ESRB), Centers for Disease Control and Prevention (CDC). The secondary objective is to evaluate accuracy and completeness of the information provided in these documents. METHODS: The authors reviewed all SITREPs/INs prepared by DBPR/ESRB from January 2007 to June 2009. Data were abstracted for variables related to the type of incidents, the type of CDC assistance requested, the geographic origin of the calls, and the organization reporting the event or requesting CDC assistance or both. In addition, variables were also created to assess the accuracy and completeness of reports for quality improvement analysis. RESULTS: The DBPR/ESRB prepared 77 SITREPs and 22 INs. Most of them were related to unknown white powders/suspicious packages or BioWatch Actionable Reports (78%). Most calls (79%), requesting CDC assistance or not, were domestic. Almost all calls requesting CDC assistance were for clinical and/or laboratory consultation and/or request for analysis of samples. Most of the calls requesting CDC assistance came from city, county, state, or federal government agencies and military organizations (82%). However, 14 of the analyzed documents (14.4%) were misclassified, that is, a SITREP was written when it should have been an IN or vice versa. The authors also noted the absence of some relevant information among some of the documents, for example, date/time of update. CONCLUSIONS: All of the issues/incidents reported in this article to which DBPR/ESRB responded were cause for legitimate concern. However, significant improvement can be made in the preparation of these reports by CDC staff to ensure efficient and effective response from CDC and its partners. Finally, local entities may wish to develop a similar documentation and reporting process to help manage significant incidents.


Assuntos
Bioterrorismo/estatística & dados numéricos , Centers for Disease Control and Prevention, U.S./estatística & dados numéricos , Planejamento em Desastres/estatística & dados numéricos , Vigilância da População/métodos , Órgãos Governamentais/organização & administração , Humanos , Estados Unidos
3.
Lancet Infect Dis ; 12(2): 150-6, 2012 Feb.
Artigo em Inglês | MEDLINE | ID: mdl-22252150

RESUMO

Crowds are a feature of large cities, occurring not only at mass gatherings but also at routine events such as the journey to work. To address extreme crowding, various computer models for crowd movement have been developed in the past decade, and we review these and show how they can be used to identify health and safety issues. State-of-the-art models that simulate the spread of epidemics operate on a population level, but the collection of fine-scale data might enable the development of models for epidemics that operate on a microscopic scale, similar to models for crowd movement. We provide an example of such simulations, showing how an individual-based crowd model can mirror aggregate susceptible-infected-recovered models that have been the main models for epidemics so far.


Assuntos
Aglomeração , Comportamento de Massa , Modelos Teóricos , Simulação por Computador , Humanos
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