Risk perception plays an important role in testing behaviour for sexually transmitted infections, but is rarely included in mathematical models exploring the impact of testing. We explored the impact of incorporating sexual behaviour (SB), risk perception (RP) and differential testing uptake in SB–RP groups on prevalence, using chlamydia as an example. We developed a pair model with a susceptible–infected–susceptible structure representing heterosexuals aged 16–26 years. The effect of testing on chlamydia prevalence was compared between a model with only SB (SB model) and a model with SB and RP (SB–RP model). In the SB–RP model, a scenario without differential testing uptake in SB–RP groups was compared to scenarios with differential testing uptake in SB–RP groups. Introducing testing into the SB–RP model resulted in a slightly smaller reduction in chlamydia prevalence (−38.0%) as compared to the SB model (−40.4%). In the SB–RP model, the scenario without differential testing uptake in SB–RP groups overestimated the reduction in chlamydia prevalence (with 4.8%), especially in the group with high SB and low RP (19.8%). We conclude that mathematical models incorporating RP and differential testing uptake in SB–RP groups improve the impact assessment of testing and treatment on chlamydia prevalence.