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Updated: Aug 30, 2026

A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data
Published on: December 9, 2015
Multiple sclerosis in Colombia: nationwide surveillance-based estimates and trends, 2016-2024
Carlos Alvarado-De la Hoz1, Silvia Angélica Andrade-Rondon1, Andrés Ricaurte-Fajardo1
1Pontificia Universidad Javeriana, Hospital Universitario San Ignacio, Bogotá, Colombia.
Background:
Updated national estimates of multiple sclerosis (MS) in Colombia remain limited. We aimed to describe the surveillance-based notified burden of confirmed MS in Colombia using the national orphan-disease notification registry.
Methods:
We conducted a retrospective nationwide observational study using de-identified individual-level Sivigila records of confirmed MS notifications from January 1, 2016, to December 31, 2024. Cumulative notified prevalence and diagnosis-date-based notified incidence were estimated using official population denominators. Department-, age-, and sex-specific estimates were calculated for 2024. Diagnosis-to-notification delay was used to assess reporting timeliness.
Results:
Overall, 5243 confirmed MS notifications were included. Median age at diagnosis was 35.5 years (IQR 27.3-45.3), and 70.2% were women. Cumulative notified prevalence reached 9.97 per 100,000 population in 2024. Diagnosis-date-based notified incidence peaked in 2022 at 0.80 per 100,000 and was 0.56 per 100,000 in 2024. The highest 2024 departmental estimates were observed in Bogotá, D.C. (27.10 per 100,000) and Antioquia (16.87 per 100,000). Age-specific estimates were highest among individuals diagnosed at 40-49 and 50-59 years. Median diagnosis-to-notification delay decreased from 2367 days in 2018 to 65 days in 2024 CONCLUSIONS: Colombia's orphan-disease surveillance system captures a higher notified MS burden than previously recognized. However, incomplete mortality ascertainment necessarily leads to overestimation of living prevalence, whereas incomplete and potentially selective notification may lead to underestimation; consequently, the net direction and magnitude of bias are uncertain. Temporal trends likely reflect registry maturation, retrospective notification, and reporting practices rather than abrupt epidemiological change.
