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. 2008 Feb 8:8:16.
doi: 10.1186/1471-2334年8月16日.

Estimates of the duration of the early and late stage of gambiense sleeping sickness

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Estimates of the duration of the early and late stage of gambiense sleeping sickness

Francesco Checchi et al. BMC Infect Dis. .

Abstract

Background: The durations of untreated stage 1 (early stage, haemo-lymphatic) and stage 2 (late stage, meningo-encephalitic) human African trypanosomiasis (sleeping sickness) due to Trypanosoma brucei gambiense are poorly quantified, but key to predicting the impact of screening on transmission. Here, we outline a method to estimate these parameters.

Methods: We first model the duration of stage 1 through survival analysis of untreated serological suspects detected during Médecins Sans Frontières interventions in Uganda and Sudan. We then deduce the duration of stage 2 based on the stage 1 to stage 2 ratio observed during active case detection in villages within the same sites.

Results: Survival in stage 1 appears to decay exponentially (daily rate = 0.0019; mean stage 1 duration = 526 days [95%CI 357 to 833]), possibly explaining past reports of abnormally long duration. Assuming epidemiological equilibrium, we estimate a similar duration of stage 2 (500 days [95%CI 345 to 769]), for a total of nearly three years in the absence of treatment.

Conclusion: Robust estimates of these basic epidemiological parameters are essential to formulating a quantitative understanding of sleeping sickness dynamics, and will facilitate the evaluation of different possible control strategies.

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Figures

Figure 1
Figure 1
Simple model for the progression of untreated HAT.
Figure 2
Figure 2
Expected shapes of the observed distribution of survival times after detection. Shaded cells A1-C3 show the expected distribution of survival times after detection, given different scenarios for the true distribution of stage 1 survival (A, B and C) and incidence in the pre-detection period (1, 2 and 3). P = proportion of cases remaining in stage 1; t = time; * = exponential function P(t)=e(r1t), with mean stage 1 duration = 1/r1; ** = linear function P(t) = -r1t with fixed stage 1 duration = 1/r1.
Figure 3
Figure 3
Fitted interval-censored stage 1 survival models. For comparison purposes, the figure also superimposes a Kaplan-Meier survival curve (with Greenwood 95% confidence intervals) based on censoring progression events at the mid-point between the two visits between which the event is known to have occurred.
Figure 4
Figure 4
Timing of actual follow-up visits with respect to the scheduled date. Data are provided for visits at which progression to stage 2 was detected (n = 99), as well as all other visits (n = 4774).

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