Free Content Quantifying the level of under-detection of Trypanosoma brucei rhodesiense sleeping sickness cases

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Abstract:

Summary

To formally quantify the level of under-detection of Trypanosoma brucei rhodesiense sleeping sickness (SS) during an epidemic in Uganda, a decision tree (under-detection) model was developed; concurrently, to quantify the subset of undetected cases that sought health care but were not diagnosed, a deterministic (subset) model was developed. The values of the under-detection model parameters were estimated from previously published records of the duration of symptoms prior to presentation and the ratio of early to late stage cases in 760 SS patients presenting at LIRI hospital, Tororo, Uganda during the 1988–1990 epidemic of SS. For the observed early to late stage ratio of 0.47, we estimate that the proportion of under-detection in the catchment area of LIRI hospital was 0.39 (95% CI 0.37–0.41) i.e. 39% of cases are not reported. Based on this value, it is calculated that for every one reported death of SS, 12.0 (95% CI 11.0–13.0) deaths went undetected in the LIRI hospital catchment area – i.e. 92% of deaths are not reported. The deterministic (subset) model structured on the possible routes of a SS infection to either diagnosis or death through the health system or out of it, showed that of a total of 73 undetected deaths, 62 (CI 60–64) (85%) entered the healthcare system but were not diagnosed, and 11 (CI 11–12) died without seeking health care from a recognized health unit. The measure of early to late stage presentation provides a tractable measure to determine the level of rhodesiense SS under-detection and to gauge the effects of interventions aimed at increasing treatment coverage.

Keywords: Uganda; disease burden; rhodesiense sleeping sickness; under-detection

Document Type: Research Article

DOI: http://dx.doi.org/10.1111/j.1365-3156.2005.01470.x

Affiliations: 1: London School of Hygiene and Tropical Medicine, London, UK 2: Centre for Tropical Veterinary Medicine, Edinburgh, UK 3: International Livestock Research Institute, Nairobi, Kenya

Publication date: September 1, 2005

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