Human African trypanosomiasis : current status and eradication efforts

Epidemics of human African trypanosomiasis (HAT) in the 20th century led to millions of deaths. However, since the start of the twenty-first century, there is been a continued decline in the number of reported cases, due to increased investment and prioritisation of control efforts. Systematic screening of at-risk areas and widespread access to increasingly advanced diagnostics and treatments, along with much improved vector control, have all helped to make disease elimination achievable in the near future. Despite the progress, the danger of disease resurgence is well-known for HAT and continued surveillance and treatment availability is essential. Additionally, many uncertainties regarding HAT transmission remain and combine to make potential disease eradication a complete unknown

Screening strategies for a sustainable endpoint for Gambiense sleeping sickness

Background. Gambiense human African trypanosomiasis (gHAT, sleeping sickness) is a vector-borne disease typically fatal without treatment. Intensified, mainly medical-based, interventions in endemic areas have reduced the occurrence of gHAT to historically low levels. However, persistent regions, mainly in the Democratic Republic of Congo (DRC), remain a challenge to achieving the World Health Organization global elimination of transmission (EOT) target. Methods. Stochastic models of gHAT transmission fitted to DRC case data explored patterns of regional reporting and extinction. The time to EOT at a health zone scale (∼100,000 people) and how an absence of reported cases informs about EOT was quantified. Results. Regional epidemiology and level of active screening (AS) both influenced the predicted time to EOT. Different AS cessation criteria had similar expected infection dynamics and recrudescence of infection was unlikely. However, whether EOT has been achieved when AS ends, is critically dependent on the stopping criteria. Two or three consecutive years of no detected cases provided greater confidence of EOT compared to a single year (66-75% and 82-84% probability of EOT respectively compared to 31-51%). Conclusion. Multiple years of AS without case detections is a valuable measure to assess the likelihood that the EOT target has been met locally

Predicting the impact of intervention strategies for sleeping sickness in two high-endemicity health zones of the Democratic Republic of Congo

Two goals have been set for Gambian human African trypanosomiasis (HAT), the first is to achieve elimination as a public health problem in 90% of foci by 2020, and the second is to achieve zero transmission globally by 2030. It remains unclear if certain HAT hotspots could achieve elimination as a public health problem by 2020 and, of greater concern, it appears that current interventions to control HAT in these areas may not be sufficient to achieve zero transmission by 2030. A mathematical model of disease dynamics was used to assess the potential impact of changing the intervention strategy in two high-endemicity health zones of Kwilu province, Democratic Republic of Congo. Six key strategies and twelve variations were considered which covered a range of recruitment strategies for screening and vector control. It was found that effectiveness of HAT screening could be improved by increasing effort to recruit high-risk groups for screening. Furthermore, seven proposed strategies which included vector control were predicted to be sufficient to achieve an incidence of less than 1 reported case per 10,000 people by 2020 in the study region. All vector control strategies simulated reduced transmission enough to meet the 2030 goal, even if vector control was only moderately effective (60% tsetse population reduction). At this level of control the full elimination threshold was expected to be met within six years following the start of the change in strategy and over 6000 additional cases would be averted between 2017 and 2030 compared to current screening alone. It is recommended that a two-pronged strategy including both enhanced active screening and tsetse control is implemented in this region and in other persistent HAT foci to ensure the success of the control programme and meet the 2030 elimination goal for HAT

Village-scale persistence and elimination of gambiense human African trypanosomiasis

Gambiense human African trypanosomiasis (gHAT) is one of several neglected tropical diseases that is targeted for elimination by the World Health Organization. Recent years have seen a substantial decline in the number of globally reported cases, largely driven by an intensive process of screening and treatment. However, this infection is highly focal, continuing to persist at low prevalence even in small populations. Regional elimination, and ultimately global eradication, rests on understanding the dynamics and persistence of this infection at the local population scale. Here we develop a stochastic model of gHAT dynamics, which is underpinned by screening and reporting data from one of the highest gHAT incidence regions, Kwilu Province, in the Democratic Republic of Congo. We use this model to explore the persistence of gHAT in villages of different population sizes and subject to different patterns of screening. Our models demonstrate that infection is expected to persist for long periods even in relatively small isolated populations. We further use the model to assess the risk of recrudescence following local elimination and consider how failing to detect cases during active screening events informs the probability of elimination. These quantitative results provide insights for public health policy in the region, particularly highlighting the difficulties in achieving and measuring the 2030 elimination goal

Estimating the distribution of time to extinction of infectious diseases in mean-field approaches

A key challenge for many infectious diseases is to predict the time to extinction under specific interventions. In general, this question requires the use of stochastic models which recognize the inherent individual-based, chance-driven nature of the dynamics; yet stochastic models are inherently computationally expensive, especially when parameter uncertainty also needs to be incorporated. Deterministic models are often used for prediction as they are more tractable; however, their inability to precisely reach zero infections makes forecasting extinction times problematic. Here, we study the extinction problem in deterministic models with the help of an effective ‘birth–death’ description of infection and recovery processes. We present a practical method to estimate the distribution, and therefore robust means and prediction intervals, of extinction times by calculating their different moments within the birth–death framework. We show that these predictions agree very well with the results of stochastic models by analysing the simplified susceptible–infected–susceptible (SIS) dynamics as well as studying an example of more complex and realistic dynamics accounting for the infection and control of African sleeping sickness (Trypanosoma brucei gambiense)

Modelling gambiense human African trypanosomiasis infection in villages of the Democratic Republic of Congo using Kolmogorov forward equations

Stochastic methods for modelling disease dynamics enables the direct computation of the probability of elimination of transmission (EOT). For the low-prevalence disease of human African trypanosomiasis (gHAT), we develop a new mechanistic model for gHAT infection that determines the full probability distribution of the gHAT infection using Kolmogorov forward equations. The methodology allows the analytical investigation of the probabilities of gHAT elimination in the spatially-connected villages of different prevalence health zones of the Democratic Republic of Congo, and captures the uncertainty using exact methods. Our method provides a more realistic approach to scaling the probability of elimination of infection between single villages and much larger regions, and provides results comparable to established models without the requirement of detailed infection structure. The novel flexibility allows the interventions in the model to be implemented specific to each village, and this introduces the framework to consider the possible future strategies of test-and-treat or direct treatment of individuals living in villages where cases have been found, using a new drug

Brief of Corporate Law Professors as Amici Curie in Support of Respondents

The Supreme Court has looked to the rights of corporate shareholders in determining the rights of union members and non-members to control political spending, and vice versa. The Court sometimes assumes that if shareholders disapprove of corporate political expression, they can easily sell their shares or exercise control over corporate spending. This assumption is mistaken. Because of how capital is saved and invested, most individual shareholders cannot obtain full information about corporate political activities, even after the fact, nor can they prevent their savings from being used to speak in ways with which they disagree. Individual shareholders have no “opt out” rights or practical ability to avoid subsidizing corporate political expression with which they disagree. Nor do individuals have the practical option to refrain from putting their savings into equity investments, as doing so would impose damaging economic penalties and ignore conventional financial guidance for individual investors

Cost-effectiveness modelling to optimise active screening strategy for gambiense human African trypanosomiasis in endemic areas of the Democratic Republic of Congo

Background: Gambiense human African trypanosomiasis (gHAT) has been brought under control recently with village-based active screening playing a major role in case reduction. In the approach to elimination, we investigate how to optimise active screening in villages in the Democratic Republic of Congo, such that the expenses of screening programmes can be efficiently allocated whilst continuing to avert morbidity and mortality. Methods: We implement a cost-effectiveness analysis using a stochastic gHAT infection model for a range of active screening strategies and, in conjunction with a cost model, we calculate the net monetary benefit (NMB) of each strategy. We focus on the high-endemicity health zone of Kwamouth in the Democratic Republic of Congo. Results: High-coverage active screening strategies, occurring approximately annually, attain the highest NMB. For realistic screening at 55% coverage, annual screening is cost-effective at very low willingness-to-pay thresholds (20.4 per disability adjusted life year (DALY) averted), only marginally higher than biennial screening (14.6 per DALY averted). We find that, for strategies stopping after 1, 2 or 3 years of zero case reporting, the expected cost-benefits are very similar. Conclusions: We highlight the current recommended strategy—annual screening with three years of zero case reporting before stopping active screening—is likely cost-effective, in addition to providing valuable information on whether transmission has been interrupted