Background: Understanding participant attrition in longitudinal studies is essential for maintaining cohorts, establishing targeted interventions, and assessing potential biases introduced in study analyses. Yet, limited metrics, models, and long-term assessments exist for the evaluation of community-based cohorts in sub-Saharan Africa. Methods: We prospectively assessed participant attrition in the SchistoTrack cohort. A total of 2844 individuals aged 5-92 years were examined from 1445 randomly sampled households across three rural Ugandan districts. Baseline data on sociodemographics, medical history, spatial factors, and clinical examinations were collected in 2022, with annual and seasonal follow-ups analysed to 2024. Profiles of attriters and rejoiners were established with logistic regressions, while the timing of the first attrition event was analysed in multinomial models. Annual community engagement was conducted. Findings: Overall attrition rates were stable across the years ranging from 21-24.8%. Attriter profiles were established within the first year, with only borderline significant factors identified. Home ownership, compared to renting was negatively related to attrition (0.773; CI 0.599-0.998). And, each additional household member reduced the likelihood of attrition (0.923; CI 0.863-0.987). Higher education was positively associated with attrition (1.077; CI 1.047-1.108). Fishermen were not more likely than other individuals to have an attrition event, either overall or seasonally. 40.1% (240/598) of participants who dropped out from the first major follow-up rejoined the study at the following timepoint. Schistosome infection and the need for schistosomiasis-related medical referrals were not associated with later attrition when compared to uninfected individuals and individuals with referrals for ancillary causes or no needed referral. Communicating clinical findings and adjusting incentives across the years did not negatively impact study participation. Interpretation: By providing metrics and models for tracking attrition, our attrition analysis framework can guide the design and evaluation of community-based cohorts in rural sub- Saharan Africa.