Answer once, get 7 risk estimates
This panel runs seven independent machine-learning models in a single form. Each model was trained on nationally representative NHANES serology data (2005–2016, up to 44,500 participants per model) and estimates the probability that a person with your demographic profile has antibodies for a given infection. Fill in the form below and receive personalized risk estimates for:
HSV-1
Oral herpes
HSV-2
Genital herpes
Hepatitis B
Core antibody
Hepatitis C
Antibody
HPV-16
High-risk type
HPV-6
Low-risk type
HPV 16/18
Combined high-risk
Before you begin:
Are you currently experiencing symptoms or have you recently been in contact with someone who tested positive?
This tool estimates risk based on demographic and lifestyle factors for people without known symptoms or exposure. It is not designed to assess the likelihood of infection after a specific exposure or to evaluate active symptoms.
If you have symptoms or known exposure, lab testing is the appropriate next step. A healthcare provider can order the right tests and interpret the results for your situation.
Each of the seven models is a gradient-boosted classifier trained on individual-level serology results from the CDC's National Health and Nutrition Examination Survey (NHANES). NHANES is a nationally representative, cross-sectional survey that collects both interview data and laboratory specimens from thousands of US residents every two-year cycle.
When you submit the form, each model receives the subset of your answers relevant to that infection and returns a calibrated probability. The models share many input features (age, sex, race, sexual history) but each was trained independently on its own serological outcome and may use additional disease-specific predictors.
Each percentage represents the estimated probability that a person with your profile has antibodies for that infection, based on patterns observed in the NHANES population. A higher number means a higher statistical likelihood of past or current infection, not a certainty.
Results are compared against the US population average (shown as a red threshold line on each gauge). Being above the average does not mean you are infected, and being below it does not mean you are not. Individual variation is wide, and only laboratory testing can determine actual infection status.
Herpes simplex virus type 1 is one of the most common infections worldwide. The WHO estimates 3.7 billion people under 50 carry HSV-1. Most infections are oral, acquired in childhood through non-sexual contact. HSV-1 can also cause genital herpes through oral-genital contact. Many carriers are asymptomatic and unaware of their status. US seroprevalence is approximately 48%.
Herpes simplex virus type 2 is the primary cause of genital herpes. Transmission occurs through sexual contact, including during asymptomatic viral shedding. US seroprevalence is approximately 12%. Risk factors include number of lifetime sexual partners, biological sex (higher in women), and race/ethnicity. Antiviral medications can reduce outbreak frequency and transmission risk.
Hepatitis C is a blood-borne virus that can cause chronic liver disease, cirrhosis, and liver cancer. The strongest risk factor is injection drug use. The CDC recommends one-time screening for all adults and for anyone born between 1945–1965 (the "baby boomer" cohort). Modern direct-acting antivirals cure HCV in over 95% of cases. US antibody prevalence is approximately 1.5%.
Hepatitis B is transmitted through blood and bodily fluids and can cause chronic liver infection. An effective vaccine has been available since 1982. This calculator estimates natural infection (core antibody positive), which is distinct from vaccine-derived immunity. Key risk factors include being born outside the US, race/ethnicity (highest prevalence among Asian and Black populations), and age. US core antibody prevalence is approximately 5.4%.
HPV is the most common sexually transmitted infection. Most sexually active people will acquire HPV at some point. This panel estimates serum antibody positivity for three categories:
Vaccination with Gardasil 9 protects against HPV types 6, 11, 16, 18, and five additional high-risk types. The HPV models are based on pre-vaccination-era data (2007–2010) and estimate natural infection only.
All seven models are trained on individual-level data from the CDC's National Health and Nutrition Examination Survey (NHANES). NHANES collects interview responses, physical measurements, and laboratory specimens from a nationally representative sample of US residents every two years. Our models use between 7,600 and 44,500 participants depending on the infection, spanning NHANES cycles from 2005 through 2016.
No. This panel provides statistical estimates based on demographic patterns. It cannot diagnose any infection. Diagnosis requires laboratory testing: type-specific IgG blood tests or PCR swabs for herpes, antibody and RNA tests for hepatitis, and HPV DNA testing or Pap smears for HPV. If you have symptoms or believe you have been exposed, see a healthcare provider for proper testing.
No. Your responses are processed on our server to generate results and are stored only in a temporary session that expires when you close your browser. We do not save your answers to a database, share them with third parties, or use them for any purpose beyond generating your results. No account or sign-up is required. See our Privacy Policy for full details.
The seven models use between 15 and 25 input features each. Because many features overlap (age, sex, race, sexual history), you answer a single unified form rather than filling out seven separate forms. Some questions, like household composition or depression score, may seem unrelated but were statistically significant predictors in the NHANES training data. Including them improves model accuracy.
A higher percentage means that among people in the NHANES survey who shared your demographic profile, a larger proportion tested positive for antibodies to that infection. It is a statistical likelihood, not a certainty. For example, an estimate of 30% means that roughly 3 in 10 people with similar characteristics had antibodies — it does not mean you have a 30% chance of catching something today.
The red line represents the overall US population average seroprevalence for that infection based on NHANES data. If your estimate is below the line, your profile is associated with lower-than-average prevalence. If above, higher-than-average. The line provides context, not a clinical threshold.
Yes. After results appear, click any of the risk estimate boxes to open that infection's individual calculator page in a new tab. The page will display your results along with additional charts: age-trend analysis, factor sensitivity, population percentile, and more. Your answers are carried over automatically.
The models estimate natural infection based on pre-vaccination-era patterns and do not account for vaccination status. If you are vaccinated, your actual risk of infection is likely lower than what the calculator estimates. The HBV model specifically uses core antibody (anti-HBc) as its outcome, which distinguishes natural infection from vaccine-derived immunity (anti-HBs).
Each model was evaluated on held-out test data using the Area Under the ROC Curve (AUC) metric. AUC values range from 0.73 (HPV-6) to 0.87 (HCV), indicating good discriminative ability. All models were calibrated using isotonic regression to ensure predicted probabilities are well-aligned with observed rates. Full validation details are on our Methodology page.
You should see a healthcare provider if you have active symptoms (sores, rashes, jaundice, fatigue), if you know you have been exposed to someone with an STD, if you are pregnant, or if you need an actual test result for any reason. This tool is for education and risk context only. It is not a substitute for clinical evaluation or laboratory testing. STDCheck.com offers a 10-Test Panel that covers all major STDs with confidential results in 1-2 days.
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View Testing Options →For full technical details on model training, feature engineering, calibration, and validation, see our Methodology page. Questions about our editorial standards are addressed in our Editorial Policy.