BACKGROUND: By the middle of the 19th century, leprosy was a serious public health problem in Norway. By 1920, new cases only rarely occurred. This study aims to explain the disappearance of leprosy from Norway. METHODS: Data from the National Leprosy Registry of Norway and population censuses were used. The patient data include year of birth, onset of disease, registration, hospital admission, death, and emigration. The Norwegian data were analysed using epidemiological models of disease transmission and control. RESULTS: The time trend in leprosy new case detection in Norway can be reproduced adequately. The shift in new case detection towards older ages which occurred over time is accounted for by assuming that infected individuals may have a very long incubation period. The decline cannot be explained fully by the Norwegian policy of isolation of patients: an autonomous decrease in transmission, reflecting improvements in for instance living conditions, must also be assumed. The estimated contribution of the isolation policy to the decline in new case detection very much depends on assumptions made on build-up of contagiousness during the incubation period and waning of transmission opportunities due to rapid transmission to close contacts. CONCLUSION: The impact of isolation on interruption of transmission remains uncertain. This uncertainty also applies to contemporary leprosy control that mainly relies on chemotherapy treatment. Further research is needed to establish the impact of leprosy interventions on transmission.

*Computer Simulation, *Models, Statistical, *Registries, Adolescent, Adult, Aged, Child, Humans, Leprosy/*epidemiology/prevention & control/transmission, Middle aged, Norway/epidemiology, Patient Isolation, Research Support, Non-U.S. Gov't
hdl.handle.net/1765/10017
International Journal of Epidemiology
Erasmus MC: University Medical Center Rotterdam

Meima, A, Irgens, L.M, van Oortmarssen, G.J, Richardus, J.H, & Habbema, J.D.F. (2002). Disappearance of leprosy from Norway: an exploration of critical factors using an epidemiological modelling approach. International Journal of Epidemiology. Retrieved from http://hdl.handle.net/1765/10017