Comparison of stochastic and deterministic models for gambiense sleeping sickness at different spatial scales: A health area analysis in the DRC.

The intensification of intervention activities against the fatal vector-borne disease gambiense human African trypanosomiasis (gHAT, sleeping sickness) in the last two decades has led to a large decline in the number of annually reported cases. However, while we move closer to achieving the ambitious target of elimination of transmission (EoT) to humans, pockets of infection remain, and it becomes increasingly important to quantitatively assess if different regions are on track for elimination, and where intervention efforts should be focused. We present a previously developed stochastic mathematical model for gHAT in the Democratic Republic of Congo (DRC) and show that this same formulation is able to capture the dynamics of gHAT observed at the health area level (approximately 10,000 people). This analysis was the first time any stochastic gHAT model has been fitted directly to case data and allows us to better quantify the uncertainty in our results. The analysis focuses on utilising a particle filter Markov chain Monte Carlo (MCMC) methodology to fit the model to the data from 16 health areas of Mosango health zone in Kwilu province as a case study. The spatial heterogeneity in cases is reflected in modelling results, where we predict that under the current intervention strategies, the health area of Kinzamba II, which has approximately one third of the health zone's cases, will have the latest expected year for EoT. We find that fitting the analogous deterministic version of the gHAT model using MCMC has substantially faster computation times than fitting the stochastic model using pMCMC, but produces virtually indistinguishable posterior parameterisation. This suggests that expanding health area fitting, to cover more of the DRC, should be done with deterministic fits for efficiency, but with stochastic projections used to capture both the parameter and stochastic variation in case reporting and elimination year estimations.

Human African trypanosomiasis in the Democratic Republic of the Congo: disease distribution and risk.

BACKGROUND: For the past three decades, the Democratic Republic of the Congo (DRC) has been the country reporting the highest number of cases of human African trypanosomiasis (HAT). In 2012, DRC continued to bear the heaviest burden of gambiense HAT, accounting for 84 % of all cases reported at the continental level (i.e., 5,968/7,106). This paper reviews the status of sleeping sickness in DRC between 2000 and 2012, with a focus on spatio-temporal patterns. Epidemiological trends at the national and provincial level are presented. RESULTS: The number of HAT cases reported yearly from DRC decreased by 65 % from 2000 to 2012, i.e., from 16,951 to 5,968. At the provincial level a more complex picture emerges. Whilst HAT control in the Equateur province has had a spectacular impact on the number of cases (97 % reduction), the disease has proved more difficult to tackle in other provinces, most notably in Bandundu and Kasai, where, despite substantial progress, HAT remains entrenched. HAT prevalence presents its highest values in the northern part of the Province Orientale, where a number of constraints hinder surveillance and control. Significant coordinated efforts by the National Sleeping Sickness Control Programme and the World Health Organization in data collection, reporting, management and mapping, culminating in the Atlas of HAT, have enabled HAT distribution and risk in DRC to be known with more accuracy than ever before. Over 18,000 locations of epidemiological interest have been geo-referenced (average accuracy ≈ 1.7 km), corresponding to 93.6 % of reported cases (period 2000-2012). The population at risk of contracting sleeping sickness has been calculated for two five-year periods (2003-2007 and 2008-2012), resulting in estimates of 33 and 37 million people respectively. CONCLUSIONS: The progressive decrease in HAT cases reported since 2000 in DRC is likely to reflect a real decline in disease incidence. If this result is to be sustained, and if further progress is to be made towards the goal of HAT elimination, the ongoing integration of HAT control and surveillance into the health system is to be closely monitored and evaluated, and active case-finding activities are to be maintained, especially in those areas where the risk of infection remains high and where resurgence could occur.