This project aims to evaluate the long-term impact of SARS-CoV-2 infection on male and female fertility using nationwide Swedish electronic health record (EHR) and register data from 2021–2026. The study will assess incident infertility diagnoses (ICD-10: N97 for female infertility; N46 for male infertility and subcategories) among individuals with documented COVID-19 compared to matched non-infected controls. Using linked data from the National Patient Register, Prescribed Drug Register, Medical Birth Register, Cause of Death Register, and regional laboratory databases, we will construct population-based cohorts and apply causal inference methods (target trial emulation, time-to-event analyses, inverse probability weighting) to estimate the risk of new infertility diagnoses following COVID-19 infection. Severity stratification (non-hospitalized, hospitalized, ICU) and vaccination status will be incorporated as time-varying exposures. Machine learning models (e.g., gradient boosting, penalized regression) will be used to identify high-risk phenotypes and interaction patterns between infection severity, comorbidities, endocrine disorders, and reproductive outcomes. Key knowledge gaps include: Long-term (>3–5 years) fertility outcomes after COVID-19. Sex-specific differences in post-infectious reproductive risk. The role of repeated infections and vaccination. Healthcare-seeking bias versus true biological impairment. Sweden’s comprehensive register linkage enables robust longitudinal follow-up and target trial emulation comparable to large-scale US and UK EHR studies. This project will generate population-level, causally informed evidence on whether COVID-19 contributes to incident infertility and inform reproductive health policy and clinical guidelines.