Abstract
BackgroundSentinel physician surveillance in communities has played an important role in detecting early signs of epidemics. The traditional approach is to let the primary care physician voluntarily and actively report diseases to the health department on a weekly basis. However, this is labor-intensive work, and the spatio-temporal resolution of the surveillance data is not precise at all. In this study, we built up a clinic-based enhanced sentinel surveillance system named “Sentinel plus” which was designed for sentinel clinics and community hospitals to monitor 23 kinds of syndromic groups in Taipei City, Taiwan. The definitions of those syndromic groups were based on ICD-10 diagnoses from physicians.MethodsDaily ICD-10 counts of two syndromic groups including ILI and EV-like syndromes in Taipei City were extracted from Sentinel plus. A negative binomial regression model was used to couple with lag structure functions to examine the short-term association between ICD counts and meteorological variables. After fitting the negative binomial regression model, residuals were further rescaled to Pearson residuals. We then monitored these daily standardized Pearson residuals for any aberrations from July 2018 to October 2019.ResultsThe results showed that daily average temperature was significantly negatively associated with numbers of ILI syndromes. The ozone and PM2.5 concentrations were significantly positively associated with ILI syndromes. In addition, daily minimum temperature, and the ozone and PM2.5 concentrations were significantly negatively associated with the EV-like syndromes. The aberrational signals detected from clinics for ILI and EV-like syndromes were earlier than the epidemic period based on outpatient surveillance defined by the Taiwan CDC.ConclusionsThis system not only provides warning signals to the local health department for managing the risks but also reminds medical practitioners to be vigilant toward susceptible patients. The near real-time surveillance can help decision makers evaluate their policy on a timely basis.
Highlights
Sentinel physician surveillance is a traditional and fundamental approach to monitor disease activity in communities
The results showed that daily average temperature was significantly negatively associated with numbers of influenza-like illness (ILI) syndromes
The ozone and PM2.5 concentrations were significantly positively associated with ILI syndromes
Summary
Sentinel physician surveillance is a traditional and fundamental approach to monitor disease activity in communities. Many countries such as France, Japan, and the United Kingdom have set up sentinel-based surveillance for a long time [1,2,3]. The data from sentinel surveillance can be used to compute the incidence of diseases or outpatient consultation rate [4]. In the United States, the feasibility of applying outpatient surveillance for ILI at the community level has been demonstrated, with a pattern consistent with syndromic and virological surveillance [9]. The advantages of syndromic surveillance and sentinel surveillance can be integrated to ensure community health quickly and precisely. The system has become an important component of the public health system for early warning and situational awareness
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