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Operational models for the prevention of blindness

Published online by Cambridge University Press:  04 August 2010

Valerie Isham
Affiliation:
University College London
Graham Medley
Affiliation:
University of Warwick
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Summary

Trachoma is the world's largest cause of preventable blindness. About 500 million people suffer from trachoma and about 7 million people are blind (Dawson et al. 1981). The aetiological agent is a bacterium, Chlamydia trachomatis, which causes progressive damage that can lead to blindness.

The prevalence and intensity of trachoma in a community is strongly associated with the degree of poverty and the resulting environmental conditions. The infection can be treated with antibiotics, but reinfection is common in heavily infected communities. At present, a vaccine is not available, although it is acknowledged that a suitable vaccine would be important for the control of trachoma, and research is actively pursuing such a vaccine. Trachoma could, like most other infectious diseases, be eradicated by a dramatic improvement in environmental conditions (especially clean water supply), public health and nutrition, but these are long-term goals. In the shorter term, control of trachoma can be acheived in varying degrees by combinations of strategies involving chemotherapy and other targeted medical interventions. Operational modelling work provides a practical tool for evaluating various strategies for the treatment and control of trachoma.

The main data used for developing and testing the models is from a series of longitudinal surveys carried out in the village of Jali, Gambia, West Africa, from 1984. In these surveys the villagers were examined clinically and microbiological samples were also obtained. Suitable demographic data was also used. The data collection, analysis, and the development of the models involves team work by medical doctors, microbiologists, statisticians, and operational researchers (Bailey et al. 1989, Ward et al. 1990, Shahani et al. 1992).

Type
Chapter
Information
Models for Infectious Human Diseases
Their Structure and Relation to Data
, pp. 402 - 404
Publisher: Cambridge University Press
Print publication year: 1996

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