Please use this identifier to cite or link to this item:
https://doi.org/10.1186/1471-2334-12-336
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dc.title | Teacher led school-based surveillance can allow accurate tracking of emerging infectious diseases - evidence from serial cross-sectional surveys of febrile respiratory illness during the H1N1 2009 influenza pandemic in Singapore | |
dc.contributor.author | Soh, S.E. | |
dc.contributor.author | Cook, A.R. | |
dc.contributor.author | Chen, M.I.C. | |
dc.contributor.author | Lee, V.J. | |
dc.contributor.author | Cutter, J.L. | |
dc.contributor.author | Chow, V.T.K. | |
dc.contributor.author | Tee, N.W.S. | |
dc.contributor.author | Lin, R.T.P. | |
dc.contributor.author | Lim, W.-Y. | |
dc.contributor.author | Barr, I.G. | |
dc.contributor.author | Lin, C. | |
dc.contributor.author | Phoon, M.C. | |
dc.contributor.author | Ang, L.W. | |
dc.contributor.author | Sethi, S.K. | |
dc.contributor.author | Chong, C.Y. | |
dc.contributor.author | Goh, L.G. | |
dc.contributor.author | Goh, D.L.M. | |
dc.contributor.author | Tambyah, P.A. | |
dc.contributor.author | Thoon, K.C. | |
dc.contributor.author | Leo, Y.S. | |
dc.contributor.author | Saw, S.M. | |
dc.date.accessioned | 2014-11-26T02:13:09Z | |
dc.date.available | 2014-11-26T02:13:09Z | |
dc.date.issued | 2012-12-04 | |
dc.identifier.citation | Soh, S.E., Cook, A.R., Chen, M.I.C., Lee, V.J., Cutter, J.L., Chow, V.T.K., Tee, N.W.S., Lin, R.T.P., Lim, W.-Y., Barr, I.G., Lin, C., Phoon, M.C., Ang, L.W., Sethi, S.K., Chong, C.Y., Goh, L.G., Goh, D.L.M., Tambyah, P.A., Thoon, K.C., Leo, Y.S., Saw, S.M. (2012-12-04). Teacher led school-based surveillance can allow accurate tracking of emerging infectious diseases - evidence from serial cross-sectional surveys of febrile respiratory illness during the H1N1 2009 influenza pandemic in Singapore. BMC Infectious Diseases 12 : -. ScholarBank@NUS Repository. https://doi.org/10.1186/1471-2334-12-336 | |
dc.identifier.issn | 14712334 | |
dc.identifier.uri | http://scholarbank.nus.edu.sg/handle/10635/108810 | |
dc.description.abstract | Background: Schools are important foci of influenza transmission and potential targets for surveillance and interventions. We compared several school-based influenza monitoring systems with clinic-based influenza-like illness (ILI) surveillance, and assessed the variation in illness rates between and within schools.Methods: During the initial wave of pandemic H1N1 (pdmH1N1) infections from June to Sept 2009 in Singapore, we collected data on nation-wide laboratory confirmed cases (Sch-LCC) and daily temperature monitoring (Sch-DTM), and teacher-led febrile respiratory illness reporting in 6 sentinel schools (Sch-FRI). Comparisons were made against age-stratified clinic-based influenza-like illness (ILI) data from 23 primary care clinics (GP-ILI) and proportions of ILI testing positive for pdmH1N1 (Lab-ILI) by computing the fraction of cumulative incidence occurring by epidemiological week 30 (when GP-ILI incidence peaked); and cumulative incidence rates between school-based indicators and sero-epidemiological pdmH1N1 incidence (estimated from changes in prevalence of A/California/7/2009 H1N1 hemagglutination inhibition titers ≥ 40 between pre-epidemic and post-epidemic sera). Variation in Sch-FRI rates in the 6 schools was also investigated through a Bayesian hierarchical model.Results: By week 30, for primary and secondary school children respectively, 63% and 79% of incidence for Sch-LCC had occurred, compared with 50% and 52% for GP-ILI data, and 48% and 53% for Sch-FRI. There were 1,187 notified cases and 7,588 episodes in the Sch-LCC and Sch-DTM systems; given school enrollment of 485,723 children, this represented 0.24 cases and 1.6 episodes per 100 children respectively. Mean Sch-FRI rate was 28.8 per 100 children (95% CI: 27.7 to 29.9) in the 6 schools. We estimate from serology that 41.8% (95% CI: 30.2% to 55.9%) of primary and 43.2% (95% CI: 28.2% to 60.8%) of secondary school-aged children were infected. Sch-FRI rates were similar across the 6 schools (23 to 34 episodes per 100 children), but there was widespread variation by classrooms; in the hierarchical model, omitting age and school effects was inconsequential but neglecting classroom level effects led to highly significant reductions in goodness of fit.Conclusions: Epidemic curves from Sch-FRI were comparable to GP-ILI data, and Sch-FRI detected substantially more infections than Sch-LCC and Sch-DTM. Variability in classroom attack rates suggests localized class-room transmission. © 2012 Soh et al.; licensee BioMed Central Ltd. | |
dc.description.uri | http://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1186/1471-2334-12-336 | |
dc.source | Scopus | |
dc.subject | Respiratory tract infections | |
dc.subject | Serology | |
dc.subject | Vaccination | |
dc.type | Article | |
dc.contributor.department | SAW SWEE HOCK SCHOOL OF PUBLIC HEALTH | |
dc.contributor.department | DUKE-NUS GRADUATE MEDICAL SCHOOL S'PORE | |
dc.description.doi | 10.1186/1471-2334-12-336 | |
dc.description.sourcetitle | BMC Infectious Diseases | |
dc.description.volume | 12 | |
dc.description.page | - | |
dc.description.coden | BIDMB | |
dc.identifier.isiut | 000313524700001 | |
Appears in Collections: | Staff Publications Elements |
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