Dalla Lana School of Public Health, University of Toronto, Toronto, Canada

Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, Canada

Department of Medicine, University of Toronto, Toronto, Canada

Division of Infectious Diseases, St. Michael’s Hospital, University of Toronto, Rm. 4-179, 30 Bond Street, Toronto M5B 1W8, Canada

Department of Infectious Disease Epidemiology, School of Public Health, Imperial College, London, UK

Abstract

Background

Syphilis incidence among men who have sex with men (MSM) continues to rise despite attempts to increase screening and treatment uptake. We examined the marginal effect of increased frequency versus increased coverage of screening on syphilis incidence in Toronto, Canada.

Methods

We developed an agent-based, network model of syphilis transmission, representing a core population of 2,000 high-risk MSM. Epidemiological and biological parameters were drawn from regional surveillance data and literature-derived estimates. The pre-intervention period of the model was calibrated using surveillance data to identify 1000 credible simulations per strategy. Evaluated strategies included: annual syphilis screening at baseline coverage, increased screening frequency at baseline coverage, and increased coverage of annual screening. Intervention impact was measured as annual prevalence of detected infectious cases and syphilis incidence per year over 10 years.

Results

Of the strategies evaluated, increasing the frequency of syphilis screening to every three months was most effective in reducing reported and incident syphilis infections. Increasing the fraction of individuals tested, without increasing test frequency, resulted a smaller decline in incidence, because reductions in infectious syphilis via treatment were counterbalanced by increased incident syphilis among individuals with prior latent syphilis. For an equivalent number of additional tests performed annually, increased test frequency was consistently more effective than improved coverage.

Conclusions

Strategies that focus on higher frequency of testing in smaller fractions of the population were more effective in reducing syphilis incidence in a simulated MSM population. The findings highlight how treatment-induced loss of immunity can create unexpected results in screening-based control strategies.

Background

Urban centres in high-income countries have witnessed a re-emergence of syphilis in recent years, with the epidemic concentrated among men who have sex with men (MSM) and HIV-infected individuals

Challenges that make syphilis difficult to control include: the development of vague or no symptoms during early infection, such that infected individuals may not seek treatment

Clinical studies have shown that the adoption of more frequent syphilis screening among high-risk groups is feasible and increases the detection of asymptomatic infectious syphilis

Given the burden of syphilis in MSM and the clear need for more impactful interventions to reduce incidence and achieve long-term epidemic control, we created a mathematical model of syphilis transmission dynamics in Toronto, Canada to estimate the potential effectiveness of different syphilis screening strategies. Specifically, we evaluated whether expanding population coverage or increasing test frequency among individuals already undergoing routine syphilis screening would be more effective in a population of high-risk MSM.

Methods

Transmission model overview

We modeled the dynamics of syphilis in MSM in Toronto, Canada, using an agent-based approach. We modeled Toronto because it is one of the cities most affected by the recent syphilis resurgence in the MSM population

The model represented a population of 2,000 high-risk MSM, with individuals forming a network of sexual contacts along which the transmission of syphilis occurred. Based on local HIV prevalence estimates in MSM, 20% of the population was assumed to be HIV positive

**Parameter**

**Details**

**Value**

**Distribution**

**Source**

**Type**

*Not infectious.

**Population characteristics**

Population size

2,000

Time spent in model (years) (min, max, mode)

1, 34, 17

Triangular

Proportion of MSM who are HIV positive

0.2

**Syphilis natural history**

Probability of transmission (per act) (min, max, mode)

Penile-anal/Penile-oral

0.01, 0.05, 0.014

Triangular

Incubation period (days)

21-28

Uniform discrete

Infection/infectious period (days)

Primary

45-60

Uniform discrete

Secondary

100-140

Uniform discrete

Early latent*

365

Recurrent

90

Late Latent*

Until end of life in model

Probability of recurrent syphilis

0.25

Duration of protective immunity following

treatment (years)

Primary or secondary syphilis

0

Latent syphilis

5

**Partnership characteristics**

Number of partners in past 6 months (proportion of population in each category)

1

0.28

2-9

0.48

10-29

0.15

30-75

0.09

Maximum number of partnersin past 6 months (by partner number category) (min, max, mode)

1

1

Assumption

2-9

2,9,8

Triangular

10-29

10,29,25

Triangular

30-75

30,75,50

Triangular

Duration of partnership (days) (min, max, mode)

Casual

1,2,1

Triangular

Regular

7,3000,365

Triangular

**Behavioural characteristics**

Frequency of anal sex (per day)

Casual partnership

0.7

Regular partnership

0.3

Frequency of oral sex (per day)

Casual partnership

1

Regular partnership

0.3

Probability of condom use (anal sex)

HIV-concordant

0.5

HIV-discordant

0.8

Condom efficacy

Assume condom use for anal intercourse only

0.9

**Test and Treatment characteristics**

Probability of seeking medical care for symptoms

Primary

0.25

Secondary

0.60

Time to treat (days)

Primary

3-56

Uniform

Secondary

1-57

Uniform

Proportionof population screened routinely for

syphilis

assumption

HIV positive

0.5

HIV negative

0.2

Test sensitivity

Treponemal-specific screening test

0.95

Probability of partner notification

Assumption

Casual partner

0.1

Regular partner

0.6

Trace-back period for partner notification

(months)

Primary

3

Secondary

6

Early latent

12

Time from index case identification to screening of named partner(s) (days)

3-21

Assumption

Infection transmission component

The infection transmission component of the model (Figure

Schematic of the infection transmission component of the model

**Schematic of the infection transmission component of the model.** Each box represents a discrete health state for an individual, with transition times between health states defined in Table

Men were tested for syphilis if they sought medical care for symptoms or accepted screening, with a likelihood of correct diagnosis dependent on test sensitivity

Partnership component

The partnership component described an individual’s sexual network and was based on Toronto-specific data from the Lambda survey

In the model, each individual was assigned a number of desired partners per six-month period, and formed partnerships with other partner-seeking individuals in the simulated population. Partnerships could be concurrent or serial. Casual and regular partnerships differed by frequency of sexual contact and partnership duration. We differentiated between casual and regular partnerships for the sake of applying contact tracing (i.e., we assumed different probabilities of identification and treatment of regular versus casual partners) and for the application of different behavioral characteristics, such as condom use and frequency of sexual contact. Condom use was assumed to be nil during oral sex

Model calibration

Each stochastic model realization represents one result out of many possible epidemic trajectories. We selected and analyzed simulated epidemics that reproduced the annual case detection rate of primary, secondary, and early latent syphilis among high-risk MSM in Toronto between 2006 and 2010. We used the reported number of cases of infectious syphilis among males in Toronto during this time period divided by the estimated size of the Toronto MSM population

Control strategies and analysis

We evaluated the impact of increasing either the coverage or frequency of syphilis screening in high-risk MSM (Table

**Intervention**

**Description**

**Details**

*Note that there are 80 extra tests required annually for the screen every 3 months strategy, compared to the equivalent number of tests strategy with 100% annual coverage.

(A) Base case

Screen every 12 months

• 20% of HIV-negative individuals screened

• 50% of HIV-positive individuals screened

• 60% of regular and 10% of casual partners of infectious index cases treated

• 520 tests performed annually

(B) Increase coverage of screening

Increase coverage by 10%

Same as (A), but:

• 30% of HIV-negative individuals screened

• 60% of HIV-positive individuals screened

• 720 tests performed annually

(C) Increase frequency of screening

Screen every 6 or every 3 months

Same as (A), but

• Frequency of screening in population is increased to every 6 (1040 tests annually) or 3 (2080 tests annually) months*

(D) Equivalent number of tests

Screen a proportion of the population every 12 months such that the total number tests performedis equivalent to (C)

To equal every 6 months:

• 100% of HIV-positive individuals screened and 40% of HIV-negative individuals screened (1040 tests annually)

To equal every 3 months:

• 100% of the population screened (2000 tests annually)*

All interventions were initiated in 2011, with immediate scale-up, and were sustained over a 10-year period. Intervention impact was measured as the prevalence of detected infectious (primary, secondary, and early latent) cases per year over the intervention period. We also estimated the annual incidence of syphilis. To characterize the uncertainty around these estimates, we constructed 95% bootstrap confidence intervals with 1000 replications, using sampling with replacement from the 1000 runs conducted for each model scenario.

Results

In total, approximately 2500 simulations were required to produce 1000 “credible” epidemics for each scenario. Of the discarded simulations, 37% fell below the lower limit and 63% produced detected cases above the upper limit. None of the credible epidemics achieved local elimination over the subsequent 10 years.

Using model realizations that produced reported case counts within our target calibration range for the time period between 2006 and 2010, we examined the effect of increasing the frequency or coverage of screening in the model population for a 10-year period beginning in 2011. All strategies were projected to reduce the number of reported infectious syphilis cases, compared to the base case scenario of continuing to screen a fixed proportion of the population annually (Figure

Model-projected annual rates of reported infectious syphilis

**Model-projected annual rates of reported infectious syphilis.** Results are based on 1000 realizations of each intervention scenario and are presented as mean values with corresponding 95% uncertainty bounds. Prior to 2011, all scenarios included annual screening only, with the specified interventions implemented at the start of 2011 (indicated by a dashed line).

Comparing strategies that required approximately the same annual number of tests, more frequent testing in men already accessing screening was projected to be more effective than expanding the proportion of the population that received annual testing (Figure

Model-projected annual rates of reported infectious syphilis under equivalent test volume strategies

**Model-projected annual rates of reported infectious syphilis under equivalent test volume strategies.** Results are based on 1000 realizations of each intervention scenario and are presented as mean values with corresponding 95% uncertainty bounds. Prior to 2011, all scenarios included annual screening only, with the specified interventions implemented at the start of 2011 (indicated by a dashed line). 3-monthly and 100% annual screening (black lines) required approximately the same number of screening tests annually, as did the 6-monthly and 52% annual screening (grey lines).

Expected reduction in infectious syphilis cases following implementation of different intervention strategies

**Expected reduction in infectious syphilis cases following implementation of different intervention strategies.** The proportion of cases averted was calculated relative to the expected number of cases in the base case scenario (no increase in frequency or coverage of screening). Proportion of cases averted is presented for both diagnosed cases and incident cases (reported and unreported), and is calculated using the mean value of 1000 realizations for each intervention scenario. Error bars represent 95% uncertainty bounds. Strategies requiring the same number of annual tests are indicated.

Discussion

Using a dynamical model of syphilis transmission in a core group of MSM that was parameterized with the best available data on the epidemiology of the current epidemic and disease natural history, we evaluated plausible screening strategies that might be employed for epidemic control. We found that increasing test frequency in at-risk MSM who already access screening, rather than expanding outreach to provide screening to under-screened individuals, would be the optimal means of reducing syphilis incidence.

While the finding may appear counterintuitive, it is consistent both with the observed rebound in syphilis rates that occurred in Vancouver in the context of dramatic expansion of empirical treatment efforts

By incorporating sexual network data and capturing the indirect effects of interventions, such as the downstream prevention of cases following treatment of a single individual, we are able to evaluate the potential impact of changes in syphilis screening on disease dynamics. Previous modeling studies of syphilis transmission have provided important qualitative and quantitative insights for epidemic control by exploring the influence of key parameters on syphilis rebound

To our knowledge, only one previous study has performed a similar examination using an agent-based model of syphilis in Australian MSM, and demonstrated the potential impact of more frequent screening in MSM, compared to increasing the proportion of MSM screened

Our model is subject to limitations, including uncertainty in model parameters. When the appropriate data were available, parameters were drawn from distributions to account for this uncertainty. Although we included results from a large number of model realizations for each strategy, we did not explicitly evaluate the impact of stochastic uncertainty on model results within each parameter set. However, the impact of stochasticity on the results appears to be small, likely due to the reasonably large number of simulations performed. The partnership component of the model was parameterized using data from a cross-sectional study, and thus may not capture changes in behaviour over time, and their consequent impact on the syphilis epidemic in Toronto’s MSM population. Although our model included HIV status, we did not attempt to evaluate the synergistic impact of syphilis testing and treatment on syphilis-HIV co-infection. An important next step is to incorporate costs and evaluate the cost-effectiveness of these strategies.

Conclusions

In summary, a model that incorporates the best available data on syphilis transmission in MSM core groups in a large urban centre suggests that syphilis screening campaigns will be most successful if they focus on reducing the interval between tests in high-risk MSM, rather than focusing on outreach to increase the proportion of the population screened.

Competing interests

The authors declare that they have no competing interests.

Authors’ contributions

All authors were involved in the study conception and design, analysis and interpretation of data, and drafting of the manuscript. AT built the model and analyzed output data. SM and DF assisted with data acquisition and the critical revision of the manuscript for important intellectual content. All authors read and approved the final manuscript.

Acknowledgements

This research was supported in part by the Ontario AIDS Bureau in partnership with the Hassel Free Clinic. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

The authors thank Frank McGee and James Murray (Ontario AIDS Bureau), Robert Remis and Dionne Gesnick (University of Toronto), Rita Shahin and Dana Al-Bargash (Toronto Public Health), Dara Friedman and Jacqueline Willmore (Ottawa Public Health) and Leo Mitterni (Hassle Free Clinic) for providing valuable input and data.

Pre-publication history

The pre-publication history for this paper can be accessed here: