Effects of Different Absenteeism Statistical Methods on Influenza Surveillance

Abstract

<i>Background</i> The existing absenteeism surveillance systems in China rely heavily on school doctors to collect data manually, but the low prevalence rate of school doctors makes it difficult to popularize this mode. The method of absenteeism statistics requires new breakthroughs. <i>Objective</i> The purpose of this study was to evaluate the feasibility of an established absenteeism surveillance system based on face recognition, and to explore the appropriate surveillance index for this system. <i>Methods</i> A primary school of about 1900 students was selected. Absenteeisms reported by school doctors and this system from March 1, 2021 (week 9) to January 14, 2022 (week 2) were collected, as well as weekly positive rate of influenza virus (WPRIV) released by China National Influenza Center. Eight weekly absenteeism rate indicators were calculated: all-cause absenteeism rate reported by system (WAR1), all-cause absenteeism rate reported by school doctors (WAR2), sickness absenteeism rate reported by school doctors (WAR3), and the rate of students absent one time (WAR4), two times (WAR5), three to four times (WAR6), one to two times (WAR7) and two to four times (WAR8) a week reported by the system. Pearson correlation coefficients of eight indicators and WPRIV were analyzed, and the change trend of their time series diagram was investigated. <i>Results</i> During week 9-42, WAR1 (r=0.614, p=0.001), WAR4 (r=0.631, p<0.001), WAR5 (r=0.651, p<0.001), WAR6 (r=0.541, p<0.001), WAR7 (r=0.654, p<0.001) and WAR8 (r=0.644, p<0.001) were significantly correlated with WPRIV, while WAR2 (r=0.262, p>0.05) and WAR3 (r=0.239, p>0.05) were not. Throughout the surveillance period, WAR1 (r=0.671, p<0.001), WAR2 (r=0.638, p<0.001), WAR3 (r=0.752, p<0.001), WAR5 (r=0.682, p<0.001), WAR6 (r=0.535, p<0.001) and WAR8 (r=0.683, p<0.001) were significantly correlated with WPRIV, while WAR4 (r=0.086, p>0.05) and WAR7 (r=0.242, p>0.05) were not. <i>Conclusions</i> Absenteeism reported by the system was more effective for influenza surveillance than absenteeism reported by school doctors, especially when the influenza activity level was low. When WAR1, WAR5 and WAR8 were combined together, the epidemic situation of influenza could be more comprehensively aware.