Estimating the syphilis incidence and diagnosis rate in Japan: a mathematical modelling study

A network suspected infectious disease model for the development of syphilis transmission from 2015 to 2021 in Hubei province, China

AIMS

Understanding the transmission mode of syphilis is essential to prevent and predict its future prevalence and to develop effective control measures. This study aimed to develop a network suspected infectious disease model to simulate the syphilis transmission.

METHODS AND RESULTS

The number of syphilis cases in Wuhan's Fourth Hospital, Hubei province, China, from October 2015 to July 2021 was collected. The simulation was carried out by interpersonal network-SI (suspected infectious) model based on temporal exponential family random graph models. Late latent syphilis and tertiary syphilis are predicted by December 2025. The validity of simulated value and real data was tested, including determination coefficient (R2), root means square error (RMSE), and means relative error (MRE). Moreover, we developed an online app that can more easily predict the number of syphilis infections in different scenarios by setting different parameters. Results showed that R2, RMSE, and MRE were 0.995, 36.19, and 6.31, respectively. Speed from latent infection to primary syphilis, primary syphilis to secondary syphilis, and susceptible group to latent infection decreased rapidly. The speed of transformation from secondary syphilis to early incubation period and early latent to late latent experienced a process from increase to decreased. Late latent to tertiary syphilis patients increased steadily. The number of late latent patients, early latent, invisible infection, primary syphilis, and secondary syphilis all increased at first and turn to decreased. However, tertiary syphilis continuously kept rising in the whole process. To better make use of the transmission model, an online application was developed (https://alanwu.shinyapps.io/MD-shiny/).

CONCLUSIONS

Based on the simulation that late latent and tertiary syphilis were steadily increasing, the prevention and treatment for syphilis were imperative.

The effect of public health awareness and behaviors on the transmission dynamics of syphilis in Northwest China, 2006-2018, based on a multiple-stages mathematical model

Syphilis, a sexually transmitted infectious disease caused by the bacterium treponema pallidum, has re-emerged as a global public health issue with an estimated 12 million people infected each year. Understanding the impacts of health awareness and behaviors on transmission dynamics of syphilis can help to establish optimal control strategy in different regions. In this paper, we develop a multiple-stage SIRS epidemic model taking into account the public health awareness and behaviors of syphilis. First, the basic reproduction number R0 is obtained, which determines the global dynamics behaviors of the model. We derive the necessary conditions for implementing optimal control and the corresponding optimal solution for mitigation syphilis by using Pontryagin's Maximum Principle. Based on the data of syphilis in Ningxia from 2006 to 2018, the parameterizations and model calibration are carried out. The fitting results are in good agreement with the data. Moreover, sensitivity analysis shows that the public awareness induced protective behaviors C_e, compliance of condom-induced preventability ε and treatment for the primary syphilis m₁ play an important role in mitigating the risk of syphilis outbreaks. These results can help us gain insights into the epidemiology of syphilis and provide guidance for the public health authorities to implement health education programs.