SixtyNineMSM iPhone · Made for gay and bisexual men

Replace "probably" with a probability.

Between two STI tests, all you have is a feeling. SixtyNineMSM models what you actually did — encounter by encounter — into the probability of having acquired an infection since your last test, calibrated against UK surveillance data and computed entirely on your iPhone.

SixtyNineMSM home screen showing the cumulative probability of infection since the last test
The estimate

A calibrated probability, one per STI.

A test measures a single point in time; risk accumulates continuously between them, and individual encounters combine in ways that resist intuition. SixtyNineMSM reports one overall probability, a separate estimate for each of the four, and the uncertainty in every figure — never false precision.

  • Cumulative probability of having acquired any covered STI since your last test
  • Individual estimates for HIV, gonorrhoea, chlamydia and syphilis
  • A 95% credible interval from a Bayesian model on every number
Per-STI risk estimates over time with credible intervals
Attribution

See which encounters actually moved the number.

A single percentage is more useful when its components are visible. The estimate is decomposed by day, by encounter, and by STI — separating the events that materially changed your risk from those that didn't. A negative test result re-anchors the baseline, and the model starts accumulating from there.

Per-day and per-encounter contribution to cumulative risk
List of logged encounters, each with its per-STI risk estimates
Prevention, quantified

Each precaution, a risk modifier.

Condoms, PrEP, vaccination, and partner viral suppression each adjust the per-act transmission probability. SixtyNineMSM applies them to every encounter you record, so the effect of each intervention is measurable.

  • Condom use applied per relevant act
  • PrEP coverage inferred from Apple Health dose history
  • Partner HIV status, treatment, and viral suppression
  • Vaccination status (HepB, HPV, Mpox)
  • Unknowns handled with population prevalence, not worst-case guesses
What-if scenarios showing how condoms, PrEP and PEP change the estimate
Methodology

Grounded in surveillance data.

The model combines published per-act transmission probabilities with prevalence data from UK surveillance (UKHSA and ONS), adjusts them for the circumstances of each encounter, and propagates uncertainty through to the final estimate with a Bayesian model. Every assumption and source is documented inside the app.

Sources and methodology screen listing surveillance data and model inputs

No servers, ever

The app has no account and no backend, and never connects to the internet. There is nowhere for your data to be sent, so the developer and any third party simply never get it.

On-device & encrypted

Your data lives in an on-device database, encrypted at rest while your phone is locked and excluded from iCloud and device backups. Exports are password-protected and unlocked with Face ID.

Apple Health is optional

If you turn it on, the app reads your PrEP doses and can write encounters to Apple Health as "Sexual Activity". Anything in Apple Health is then managed by Apple and may sync via iCloud per your iOS settings. Leave it off and nothing is written there.

Not medical advice.

SixtyNineMSM provides statistical estimates for educational and informational purposes only. It is not medical advice, not a diagnosis, and cannot detect, confirm, or rule out any infection. Always consult a qualified healthcare professional and get tested.

Common questions

Where do the numbers come from?

Each encounter carries a per-act transmission probability drawn from published UK surveillance data. SixtyNineMSM aggregates these across every encounter since your last test, adjusts for the protection recorded, and uses a Bayesian model to fill gaps and quantify the uncertainty in the result.

Does it work outside the UK?

The baseline prevalence rates come from England (UKHSA and ONS data), so the estimates are calibrated for that population. You can record encounters anywhere, but the further your setting is from that epidemiological context, the less precise the estimates become.

What if I don't know a partner's status?

That is the expected case, and the model accounts for it. When serostatus, viral suppression or PrEP use is unknown, SixtyNineMSM applies the prevalence rates for that characteristic across the relevant population, rather than assuming best or worst case.

Which STIs does it cover?

HIV, gonorrhoea, chlamydia and syphilis. HepB, HPV and Mpox vaccination status is also recorded and factored in where it modifies the per-act transmission probability.

What about the Apple Health sync?

It is optional and off by default. When enabled, the app reads your PrEP dose history and writes encounters to Apple Health as "Sexual Activity" samples. Data in Apple Health is managed by Apple and may sync to your other devices via iCloud, depending on your iOS settings — outside the app's control. Leave it off and nothing is written to Health.

Does it replace testing?

No. It provides statistical estimates for informational purposes and cannot diagnose or exclude any infection. Continue testing on your scheduled interval and consult a healthcare professional with any concerns.

Almost here.

SixtyNineMSM is in open beta on TestFlight ahead of the App Store release.

On Beta in TestFlight