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About:
Application of WHO’s guideline for the selection of sentinel sites for hospital-based influenza surveillance in Indonesia
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wasabi.inria.fr
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Type:
Academic Article
research paper
schema:ScholarlyArticle
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type
Academic Article
research paper
schema:ScholarlyArticle
isDefinedBy
Covid-on-the-Web dataset
has title
Application of WHO’s guideline for the selection of sentinel sites for hospital-based influenza surveillance in Indonesia
Creator
Samaan, Gina
Apsari, Hana
Bratasena, Arie
Fandil, Ahmad
Hariyanto, Edy
Mangiri, Amalya
Mulyadi, Ester
Rusli, Roselinda
Sitorus, Martahan
Praptaningsih, Catharina
Sampurno, Ondri
Susilarini, Ni
Source
Medline; PMC
abstract
BACKGROUND: A sentinel hospital-based severe acute respiratory infection (SARI) surveillance system was established in Indonesia in 2013. Deciding on the number, geographic location and hospitals to be selected as sentinel sites was a challenge. Based on the recently published WHO guideline for influenza surveillance (2012), this study presents the process for hospital sentinel site selection. METHODS: From the 2,165 hospitals in Indonesia, the first step was to shortlist to hospitals that had previously participated in respiratory disease surveillance systems and had acceptable surveillance performance history. The second step involved categorizing the shortlist according to five regions in Indonesia to maximize geographic representativeness. A checklist was developed based on the WHO recommended attributes for sentinel site selection including stability, feasibility, representativeness and the availability of data to enable disease burden estimation. Eight hospitals, a maximum of two per geographic region, were visited for checklist administration. Checklist findings from the eight hospitals were analyzed and sentinel sites selected in the third step. RESULTS: Six hospitals could be selected based on resources available to ensure system stability over a three-year period. For feasibility, all eight hospitals visited had mechanisms for specimen shipment and the capacity to report surveillance data, but two had limited motivation for system participation. For representativeness, the eight hospitals were geographically dispersed around Indonesia, and all could capture cases in all age and socio-economic groups. All eight hospitals had prerequisite population data to enable disease burden estimation. The two hospitals with low motivation were excluded and the remaining six were selected as sentinel sites. CONCLUSIONS: The multi-step process enabled sentinel site selection based on the WHO recommended attributes that emphasize right-sizing the surveillance system to ensure its stability and maximizing its geographic representativeness. This experience may guide other countries interested in adopting WHO’s influenza surveillance standards for sentinel site selection.
has issue date
2014-09-23
(
xsd:dateTime
)
bibo:doi
10.1186/1472-6963-14-424
bibo:pmid
25248619
has license
cc-by
sha1sum (hex)
4f25223579f443edc058800f30c4fe8847a6ab57
schema:url
https://doi.org/10.1186/1472-6963-14-424
resource representing a document's title
Application of WHO’s guideline for the selection of sentinel sites for hospital-based influenza surveillance in Indonesia
has PubMed Central identifier
PMC4179842
has PubMed identifier
25248619
schema:publication
BMC Health Serv Res
resource representing a document's body
covid:4f25223579f443edc058800f30c4fe8847a6ab57#body_text
is
schema:about
of
named entity 'location'
named entity 'hospitals'
named entity 'sentinel'
covid:arg/4f25223579f443edc058800f30c4fe8847a6ab57
named entity 'Indonesia'
named entity 'severe acute respiratory infection'
named entity 'SARI'
named entity 'hospital-based'
named entity 'WHO'
named entity 'Indonesia'
named entity 'pneumonia'
named entity 'epidemiological'
named entity 'SARI'
named entity 'MOH'
named entity 'epidemiological'
named entity 'West Nusa Tenggara'
named entity 'sentinel surveillance'
named entity 'MOH'
named entity 'North Sulawesi'
named entity 'World Health Organization'
named entity 'sentinel surveillance'
named entity 'WHO'
named entity 'incidence rate'
named entity 'avian influenza'
named entity 'modem'
named entity 'WHO'
named entity 'influenza'
named entity 'Java'
named entity 'influenza viruses'
named entity 'socioeconomic'
named entity 'population density'
named entity 'population demographics'
named entity 'public hospitals'
named entity 'SIBI'
named entity 'influenza'
named entity 'diagnostic testing'
named entity 'influenza pandemic'
named entity 'WHO'
named entity 'influenza'
named entity 'socioeconomic'
named entity 'disease burden'
named entity 'WHO'
named entity 'Indonesia'
named entity 'influenza'
named entity 'influenza'
named entity 'coronavirus infections'
named entity 'influenza'
named entity 'x-rays'
named entity 'SIBI'
named entity 'SARI'
named entity 'long term'
named entity 'disease control'
named entity 'virological'
named entity 'long term'
named entity 'dengue'
named entity 'epidemiological'
named entity 'Kalimantan'
named entity 'influenza'
named entity 'epidemiological'
named entity 'SIBI'
named entity 'epidemiological'
named entity 'SIBI'
named entity 'MOH'
named entity 'H5N1'
named entity 'pneumonia'
named entity 'Indonesia'
named entity 'CDC'
named entity 'influenza'
named entity 'SARI'
named entity 'epidemiological'
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