Modeling and analysis of seasonal transmission patterns of syphilis, HIV, and gonorrhea

Seasonality is an important factor affecting the spread of infectious diseases. The driving factors behind the seasonal characteristics of infectious diseases vary. In this study, we use mathematical models to analyze the factors contributing to the seasonal patterns of syphilis, HIV, and gonorrhea epidemics. The results of fitting the model using reported data show that seasonal variations in contact rates and diagnosis rates are the driving factors behind the seasonal patterns of syphilis, HIV, and gonorrhea epidemics. In addition, the estimated values of the basic reproduction numbers from 2012 to 2015 indicate that HIV poses a higher transmission risk compared to syphilis and gonorrhea, and the spread of all three infectious diseases among high-risk populations remained inadequately controlled. These results provide mathematical insights for public health authorities to formulate strategies aimed at mitigating the spread of syphilis, HIV, and gonorrhea.