Objective  To explore the application of the three Early Aberration Reporting System (EARS) cusum algorithms (C1, C2 and C3) (EARS-3Cs) model in the monitoring and early warning of infectious respiratory diseases in port cities in China and to provide a reference for improving early warning capacity for infectious respiratory diseases in port cities and controlling the risk of infectious respiratory disease epidemics.

  Methods  Major indicators of early warning for infectious respiratory disease epidemic were selected based on a multi-source data early warning index system constructed by our previous studies and 8 core indicators were screened out with expert group discussions. From reports of Center for Disease Control and Prevention of Zhuhai city – a port city in Guangdong province from April 15 to May 15, 2021, we extracted daily monitoring data on the 8 core indicators for early warming of coronavirus disease 2019 (COVID19) epidemic in the 5 districts of the city and daily district-specific values of C1, C2 and C3 of EARS model were calculated with SPSS 21.0 for making early wearing of the epidemic.

  Results  According to the calculated values of C1, C2 and C3, the number of days with the warning of infectious respiratory disease are 1 – 2 days, 3 days and 5 – 9 days for the city during the epidemic period. The sensitivity of the C1, C2 and C3 for early warning increases sequentially. Indicated by the EARS-3Cs model- derived early warning, the period with moderate risk of COVID19 epidemic could be from April 30 to May 7 for the 5 districts of the city and the period was characterized by a sudden increase in the population mobility in Zhuhai city.

  Conclusion  The EARS-3Cs model is of certain scientificity and rationality when applied in monitoring and early warning of infectious respiratory diseases for port cities in China.