Logistic regression analysis on risk factors associated with introduction of medical vectors by international navigation ships at Zhoushan port, Zhejiang

Objective To explore risk factors associated with introduction of medical vectors by international navigation ships. Methods Quarantine data for all ships arriving at Zhoushan port in 2016 were fitted with univariate and multivariate unconditional logistic regression model to identify the potential risk factors associated with introduction of medical vectors by international navigation ships. Results Medical vectors were captured in 213 of 1 272 ships arrived at Zhoushan port in 2016. The positive detection rate was 16.75%. Six risk factors identified by multivariate analysis were ship type (ORrefrigerated ship vs. container ship=7.591;ORcargo ship vs. container ship=1.956;ORother ship vs. container ship=3.658), arriving season (ORsummer vs.winter=3.677; ORspring vs.winter=3.333; ORautumn vs.winter=2.928), issuance port of ship sanitation control exemption certificate (SSCEC) (OR=1.689), cargo varieties (OR=1.651), coming from affected area (OR=1.596), ship age (OR=1.023). Conclusion Multivariate regression analysis on risk factors associated with introduction of medical vectors by international navigation ships can provide theoretic basis for the establishment of risk assessment and early warning system and guide quarantine practice through identifying ships with high risk of carrying medical vectors.