title: Early detection for cases of enterovirus- and influenza-like illness through a newly established school-based syndromic surveillance system in Taipei, January 2010 ~ August 2011.
abstract: School children may transmit pathogens with cluster cases occurring on campuses and in families. In response to the 2009 influenza A (H1N1) pandemic, Taipei City Government officials developed a School-based Infectious Disease Syndromic Surveillance System (SID-SSS). Teachers and nurses from preschools to universities in all 12 districts within Taipei are required to daily report cases of symptomatic children or sick leave requests through the SID-SSS. The pre-diagnosis at schools is submitted firstly as common pediatric disease syndrome-groups and re-submitted after confirmation by physicians. We retrieved these data from January 2010 to August 2011 for spatio-temporal analysis and evaluated the temporal trends with cases obtained from both the Emergency Department-based Syndromic Surveillance System (ED-SSS) and the Longitudinal Health Insurance Database 2005 (LHID2005). Through the SID-SSS, enterovirus-like illness (EVI) and influenza-like illness (ILI) were the two most reported syndrome groups (77.6% and 15.8% among a total of 19,334 cases, respectively). The pre-diagnosis judgments made by school teachers and nurses showed high consistency with physicians' clinical diagnoses for EVI (97.8%) and ILI (98.9%). Most importantly, the SID-SSS had better timeliness with earlier peaks of EVI and ILI than those in the ED-SSS. Furthermore, both of the syndrome groups in these two surveillance systems had the best correlation reaching 0.98 and 0.95, respectively (p<0.01). Spatio-temporal analysis observed the patterns of EVI and ILI both diffuse from the northern suburban districts to central Taipei, with ILI spreading faster. This novel system can identify early suspected cases of two important pediatric infections occurring at schools, and clusters from schools/families. It was also cost-effective (95.5% of the operation cost reduced and 59.7% processing time saved). The timely surveillance of mild EVI and ILI cases integrated with spatial analysis may help public health decision-makers with where to target for enhancing surveillance and prevention measures to minimize severe cases.
authors: Department of Medicine, College of Medicine, National Taiwan University (NTU), Taipei, Taiwan, Republic of China.
authors: Ting Chia
authors: TC
authors: Weng
authors: Research Center for Humanities and Social Sciences, Academia Sinica, Taipei, Taiwan, R.O.C.
authors: Ta Chien
authors: TC
authors: Chan
authors: Department of Health, Taipei City Government, Taipei, Taiwan, R.O.C.
authors: Hsien Tang
authors: HT
authors: Lin
authors: Institute of Epidemiology and Preventive Medicine, College of Public Health, NTU, Taipei, Taiwan, R.O.C.
authors: Chia Kun Jasper
authors: CK
authors: Chang
authors: Institute of Epidemiology and Preventive Medicine, College of Public Health, NTU, Taipei, Taiwan, R.O.C.
authors: Wen Wen
authors: WW
authors: Wang
authors: Institute of Epidemiology and Preventive Medicine, College of Public Health, NTU, Taipei, Taiwan, R.O.C.
authors: Zheng Rong Tiger
authors: ZR
authors: Li
authors: Department of Pediatrics, NTU Hospital, Taipei, Taiwan, R.O.C.
authors: Hao-Yuan
authors: HY
authors: Cheng
authors: Department of Health, Taipei City Government, Taipei, Taiwan, R.O.C.
authors: Yu-Roo
authors: YR
authors: Chu
authors: Taipei City Hospital, Department of Health, Taipei City Government, Taipei, Taiwan, R.O.C; School of Medicine, National Yang-Ming University, Taipei, Taiwan, R.O.C.
authors: Allen Wen-Hsiang
authors: AW
authors: Chiu
authors: Taipei City Hospital, Department of Health, Taipei City Government, Taipei, Taiwan, R.O.C; School of Medicine, National Yang-Ming University, Taipei, Taiwan, R.O.C.
authors: Muh-Yong
authors: MY
authors: Yen
authors: Institute of Epidemiology and Preventive Medicine, College of Public Health, NTU, Taipei, Taiwan, R.O.C.
authors: Chwan-Chuen
authors: CC
authors: King
mesh_terms: D003362:Cost-Benefit Analysis; D003967:Diarrhea / Q000175:diagnosis / Q000453:epidemiology; D004196:Disease Outbreaks / Q000191:economics / Q000517:prevention & control; D042241:Early Diagnosis; D004770:Enterovirus / Q000502:physiology; D004769:Enterovirus Infections / Q000175:diagnosis* / Q000453:epidemiology / Q000821:virology; D005178:Faculty / Q000706:statistics & numerical data; D005843:Geography; D054884:Host-Pathogen Interactions; D006801:Humans; D015994:Incidence; D053118:Influenza A Virus, H1N1 Subtype / Q000502:physiology; D007251:Influenza, Human / Q000175:diagnosis* / Q000453:epidemiology / Q000821:virology; D009726:Nurses / Q000706:statistics & numerical data; D011159:Population Surveillance / Q000379:methods*; D012574:Schools / Q000706:statistics & numerical data; D012621:Seasons; D062211:Spatio-Temporal Analysis; D013577:Syndrome; D013624:Taiwan / Q000453:epidemiology; D014495:Universities / Q000706:statistics & numerical data