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Evaluation of an Adjustable Epidemiologic Information System
BACKGROUND: In order to facilitate public health response and to achieve early control of infectious disease epidemics, an adjustable epidemiologic information system (AEIS) was established in the Taiwan public health network in February 2006. METHODOLOGY/PRINCIPAL FINDINGS: The performance of AEIS...
Autores principales: | , , , , , , |
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Formato: | Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2011
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3029279/ https://www.ncbi.nlm.nih.gov/pubmed/21298043 http://dx.doi.org/10.1371/journal.pone.0014596 |
Sumario: | BACKGROUND: In order to facilitate public health response and to achieve early control of infectious disease epidemics, an adjustable epidemiologic information system (AEIS) was established in the Taiwan public health network in February 2006. METHODOLOGY/PRINCIPAL FINDINGS: The performance of AEIS for the period 2006 through 2008 was evaluated based on a number of response times (RT) and the public health impact. After implementation of the system, the apparent overall shortened RT was mainly due to the shortening of personnel response time (PRT) and the time needed to draft a new questionnaire that incurred as personnel-system interface (PSI); PRT dropped from a fluctuating range of 9.8 ∼28.8 days in the first four months to <10 days in the following months and remained low till 2008 (0.88±1.52 days). The PSIs for newly emerged infectious diseases were 2.6 and 3.4 person-hours for H5N1 in 2007 and chikungunya in 2008, respectively, a much improvement from 1142.5 person-hours for SARS in 2003. The duration of each rubella epidemic cluster was evaluated as public health impact and showed a shortening trend (p = 0.019) that concurred with the shortening of PRT from 64.8±47.3 to 25.2±38.2 hours per cluster (p<0.0001). CONCLUSIONS/SIGNIFICANCE: The first evaluation of the novel instrument AEIS that had been used to assist Taiwan's multi-level government for infectious diseases control demonstrated that it was well integrated into the existing public health infrastructure. It provided flexible tools and computer algorithms with friendly interface for timely data collection, integration, and analysis; as a result, it shortened RTs, filled in gaps of personnel lacking sufficient experiences, created a more efficient flow of response, and identified asymptomatic/mild cases early to minimize further spreading. With further development, AEIS is anticipated to be useful in the application of other acute public health events needing immediate orchestrated data collection and public health actions. |
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