How Canadian researchers are fighting the spread of Syphilis with maths

Syphilis is among the most pernicious and damaging STIs. It’s caused by the bacterium Treponema pallidum, which spreads from person to person through vaginal, anal, and oral sex. The infection can also be transmitted by sharing infected needles or receiving an infected blood transfusion.

Syphilis was thought to be on the decline, but global cases have been rising in recent years, making controlling its spread essential. The infection is characterised by a distinctive chancre that appears on the initial site of infection. Flu-like symptoms like fever, body rashes, nausea, muscle aches, and headaches usually follow.

If left untreated, Syphilis will enter a latent state where it damages internal organs like the brain, nerves, eyes, heart, and blood vessels.

In 2022, the Kingston, Frontenac, Lennox & Addington Public Health region in Ontario experienced a sharp increase in confirmed Syphilis cases. The infection rates for the region in that year were double the provincial average. What was especially concerning was the rise in cases of congenital Syphilis, where the infection is passed from mother to child.

Researchers at Queen’s University in Kingston created a multidisciplinary study called Syphilis Point-of-care Rapid Testing and Immediate Treatment Evaluation (SPRITE) to investigate the phenomenon. The results of the study were published in Royal Society Open Science.

When researchers try to predict how a disease will behave within a population, they usually use mathematical models to simulate possible scenarios.

Traditional models used to predict the spread of Syphilis were based on Susceptible-Infectious Recovered (SIR) framework. This model assumes everyone within the population has the same chance of getting infected. But this doesn’t reflect the reality of how Syphilis is transmitted.

To understand what was really going on in the region, Queen’s University researchers developed a new mathematical framework called “edge-based network modelling”. This form of modelling accounts for how diseases spread through networks where the number of connections per individual is known.

By basing the model on the at-risk population’s reported number of sexual contacts, researchers were able to generate more accurate estimates of the outbreak’s scale. Researchers then calibrated the model with local case data, accounting for underreporting and risk factors.

The original SIR model fitted to the same data estimated that more than 15,000 people in the target population could become infected. But the network model projected around 1,700 cases.

The model predicted the outbreak’s magnitude and evaluated the potential benefits of enhancing point-of-care testing. The team discovered that a slight increase in testing by 5% could diminish the final epidemic size by more than 13%, offering compelling support for broadening rapid testing and treatment initiatives.

Accurate modelling enhances health outcomes and brings economic advantages. The network model offers a precise outbreak estimate, preventing excessive resource allocation and ensuring cost-efficient testing and intervention strategies.

The approach introduced in this study may also be more widely applied to analyse the transmission of other STIs, like Gonorrhoea, Chlamydia, and HIV.

Breakthroughs occur every day to help fight the spread of STIs. But these advances don’t completely prevent the spread.

If you think you may have been exposed to an STI, get in touch with Better2Know today to schedule an STI test at a sexual health clinic near you.