Absenteeism has great advantages in promoting the early detection of epidemics. School absenteeism surveillance could timely detect the aggregations of absentees in time and space, so as to provide effective early warning and prevention and control of infectious diseases outbreaks in schools. Since April 1, 2012, an integrated syndromic surveillance system (ISSC) has been implemented in rural Hubei Province, China. With school absence data, finding the optimal model and related appropriate parameters for early warning of epidemics is necessary and practical.
Objective
To explore the optimal model and its related parameters via EWMA and CUSUM (C1, C2, C3) models in school absenteeism surveillance for early detection of infectious disease outbreaks in rural China.