Algorithm effectively predicts transmission mode of syphilis in patients
A new algorithm designed to simulate and predict syphilis transmission in China has been found to effectively reflect the transmission mode of the disease in patients and could be used in a web app to help prevent and control the disease worldwide.
The results are revealed in a study by a team of researchers at Shanxi Medical University, ‘A network suspected infectious disease model for the development of syphilis transmission from 2015-2021 in Hubei Province, China’ which was published in the Journal of Applied Microbiology, an Applied Microbiology International publication.
They developed temporal exponential family random graph models (TERGMs) to simulate and predict the syphilis transmission in China, as corresponding author Dr Yue Zhang explained.
Syphilis was well controlled in China in the 1960s, but made a comeback in the 1980s, with a recent rapid increase in incidence, resulting in a major impact on human health and society.
“Given the disease burden of syphilis, and the need for significant impact interventions to reduce incidence and achieve long-term epidemic control, and the current limited models of transmission dynamics, we developed a mathematical model to investigate the time-series changes of syphilis transmission, improve and predict the simulation of syphilis transmission in China,” Dr Zhang said.
“This visual transmission dynamics model could provide scientific support to public health professionals and policy makers for targeted prevention measures and interventions.”
Predicting transmission mode
The researchers collected the number of syphilis cases in Wuhan’s fourth hospital, Hubei province, China from October 2015 to July 2021, and based on these data, found that TERGMs could effectively reflect the transmission mode of syphilis patients.
The late-stage latent syphilis and stage III syphilis cases are steadily increasing, making syphilis prevention and treatment imperative.
“The development of a web-app using this simulation algorithm could be easily used to predict syphilis under different scenes, which could help in the prevention and control of syphilis worldwide,” Dr Zhang said.
Difficult to recognise
Syphilis is a sexually and vertically transmitted disease and presents in a variety of forms that can be difficult to recognize, even for the most experienced clinician, and the natural history of both untreated and treated disease is unpredictable, which has led to substantial health losses in adults.
Economic growth, changes in sexual behavior, and improvement in syphilis screening are considered as factors for transmission of syphilis,” Dr Zhang said.
“TERGMS could make statistical inferences about local configurations that were associated with observed social networks. It can be seen that this model incorporates social networks into the model to simulate the real-world transmission of syphilis.
“In the future, we need to expand this network of calculators to allow the simulation of syphilis in different scenarios.”
The team thanked Wuhan Fourth Hospital for providing data support for the development of the model.
‘A network suspected infectious disease model for the development of syphilis transmission from 2015-2021 in Hubei Province, China’ was published in the Journal of Applied Microbiology, an Applied Microbiology International publication.