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

Abstract 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 (<DOLLAR/>20.4 per disability adjusted life year (DALY) averted), only marginally higher than biennial screening (<DOLLAR/>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.

Download Full-text

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

10.1101/2020.08.03.20167296 ◽

2020 ◽

Cited By ~ 1

Author(s):

Christopher N Davis ◽

Kat S Rock ◽

Marina Antillon ◽

Erick Mwamba Miaka ◽

Matt J Keeling

Keyword(s):

Cost Effectiveness ◽

Human African Trypanosomiasis ◽

Democratic Republic ◽

Democratic Republic Of Congo ◽

Infection Model ◽

African Trypanosomiasis ◽

High Coverage ◽

Republic Of Congo ◽

Active Screening ◽

Screening Strategies

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 eve of 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 while continuing to avert morbidity and mortality. We implement a cost-effectiveness analysis using a stochastic gHAT infection model for a range of active screening strategies and we calculate the net monetary benefit (NMB) of each strategy. High-coverage active screening strategies, occurring approximately annually, attain the highest NMB. We find that, for strategies stopping after one to three years of zero case reporting, the expected cost-benefits are very similar and we highlight the current recommended strategy (three years before stopping) is likely cost-effective, in addition to providing valuable information on whether transmission has been interrupted.

Download Full-text

Predicting the impact of COVID-19 interruptions on transmission of gambiense human African trypanosomiasis in two health zones of the Democratic Republic of Congo

Transactions of the Royal Society of Tropical Medicine and Hygiene ◽

10.1093/trstmh/trab019 ◽

2021 ◽

Author(s):

Maryam Aliee ◽

Soledad Castaño ◽

Christopher N Davis ◽

Swati Patel ◽

Erick Mwamba Miaka ◽

...

Keyword(s):

Human African Trypanosomiasis ◽

Democratic Republic ◽

Democratic Republic Of Congo ◽

Neglected Tropical Diseases ◽

Passive Surveillance ◽

African Trypanosomiasis ◽

Republic Of Congo ◽

Active Screening ◽

Control Programmes ◽

The Impact

Abstract Many control programmes against neglected tropical diseases have been interrupted due to the coronavirus disease 2019 (COVID-19) pandemic, including those that rely on active case finding. In this study we focus on gambiense human African trypanosomiasis (gHAT), where active screening was suspended in the Democratic Republic of Congo (DRC) due to the pandemic. We use two independent mathematical models to predict the impact of COVID-19 interruptions on transmission and reporting and achievement of the 2030 elimination of transmission (EOT) goal for gHAT in two moderate-risk regions of the DRC. We consider different interruption scenarios, including reduced passive surveillance in fixed health facilities, and whether this suspension lasts until the end of 2020 or 2021. Our models predict an increase in the number of new infections in the interruption period only if both active screening and passive surveillance were suspended, and with a slowed reduction—but no increase—if passive surveillance remains fully functional. In all scenarios, the EOT may be slightly pushed back if no mitigation, such as increased screening coverage, is put in place. However, we emphasise that the biggest challenge will remain in the higher-prevalence regions where EOT is already predicted to be behind schedule without interruptions unless interventions are bolstered.

Download Full-text

Predicting the impact of COVID-19 interruptions on transmission of gambiense human African trypanosomiasis in two health zones of the Democratic Republic of Congo

10.1101/2020.10.26.20219485 ◽

2020 ◽

Author(s):

Maryam Aliee ◽

Soledad Castaño ◽

Christopher N Davis ◽

Swati Patel ◽

Erick Mwamba Miaka ◽

...

Keyword(s):

Human African Trypanosomiasis ◽

Democratic Republic ◽

Democratic Republic Of Congo ◽

Neglected Tropical Diseases ◽

Passive Surveillance ◽

African Trypanosomiasis ◽

Republic Of Congo ◽

Active Screening ◽

Control Programmes ◽

The Impact

AbstractMany control programmes against neglected tropical diseases have been interrupted due to COVID-19 pandemic, including those that rely on active case finding. In this study we focus on gambiense human African trypanosomiasis (gHAT), where active screening was suspended in the Democratic Republic of Congo (DRC) due to the pandemic. We use two independent mathematical models to predict the impact of COVID-19 interruptions on transmission and reporting, and the achievement of 2030 elimination of transmission (EOT) goal for gHAT in two moderate-risk regions of DRC. We consider different interruption scenarios, including reduced passive surveillance in fixed health facilities, and whether this suspension lasts until the end of 2020 or 2021. Our models predict an increase in the number of new infections in the interruption period only if both active screening and passive surveillance were suspended, and with slowed reduction - but no increase - if passive surveillance remains fully functional. In all scenarios, the EOT may be slightly pushed back if no mitigation such as increased screening coverage is put in place. However, we emphasise that the biggest challenge will remain in the higher prevalence regions where EOT is already predicted to be behind schedule without interruptions unless interventions are bolstered.

Download Full-text

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

10.1101/2021.05.24.21257532 ◽

2021 ◽

Author(s):

Christopher N Davis ◽

Matt J Keeling ◽

Kat S Rock

Keyword(s):

Human African Trypanosomiasis ◽

Democratic Republic ◽

Democratic Republic Of Congo ◽

Mechanistic Model ◽

Stochastic Methods ◽

African Trypanosomiasis ◽

Exact Methods ◽

Republic Of Congo ◽

Forward Equations ◽

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 the Kwamouth and Mosango health zones of the Democratic Republic of Congo, and captures the uncertainty using exact methods. We predict that, if current active and passive screening continue at current levels, local elimination of infection will occur in 2029 for Mosango and after 2040 in Kwamouth, respectively. 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.

Download Full-text

Characteristics, behaviors and association between Human African Trypanosomiasis and HIV seropositivity among volunteer blood donors in a semi-rural area: A survey from Kikwit, the Democratic Republic of Congo

Acta Parasitologica ◽

10.1515/ap-2016-0096 ◽

2016 ◽

Vol 61 (4) ◽

Author(s):

Lefils Kasiama Ndilu ◽

Mathilde Bothale Ekila ◽

Donald Fundji Mayuma ◽

Alain Musaka ◽

Roger Wumba ◽

...

Keyword(s):

Alcohol Intake ◽

Blood Donors ◽

Human African Trypanosomiasis ◽

Democratic Republic ◽

Democratic Republic Of Congo ◽

Casual Sex ◽

Unprotected Sex ◽

African Trypanosomiasis ◽

Republic Of Congo ◽

Hiv Test

AbstractBlood safety is a major element in the strategy to control the HIV epidemic. The aim of this study was to determine the prevalence and the associated factors of a positive HIV test among blood donors and its association between Human African Trypanosomiasis in Kikwit, the Democratic Republic of Congo. A cross-sectional study was conducted between November 2012 and May 2013. An anonymous questionnaire was designed to extract relevant data. The average mean age of participants was 30 years. The majority were man (67.8%). The overall prevalence of HIV, syphilis, hepatitis B, hepatitis C and human African trypanosomiasis was respectively 3.2%, 1.9%, 1.6%, 1.3% and 1.3%. Alcohol intake, casual unprotected sex, not using condoms during casual sex, sex after alcohol intake and seroprevalence of human African trypanosomiasis were significantly associated with a positive HIV test result ( p<0.05). In this study, sexual risk behaviors were the major risk factors associated with positive HIV tests in blood donors living in Kikwit. It is important to raise awareness about HIV and voluntary blood donation in response to some observations noted in this study such as the low educational level of the blood donors, the low level of knowledge of HIV prevention methods.

Download Full-text

Quantitative evaluation of the strategy to eliminate human African trypanosomiasis in the Democratic Republic of Congo

Parasites & Vectors ◽

10.1186/s13071-015-1131-8 ◽

2015 ◽

Vol 8 (1) ◽

Cited By ~ 40

Author(s):

Kat S. Rock ◽

Steve J. Torr ◽

Crispin Lumbala ◽

Matt J. Keeling

Keyword(s):

Quantitative Evaluation ◽

Human African Trypanosomiasis ◽

Democratic Republic ◽

Democratic Republic Of Congo ◽

African Trypanosomiasis ◽

Republic Of Congo

Download Full-text

Quantifying epidemiological drivers of gambiense human African Trypanosomiasis across the Democratic Republic of Congo

10.1101/2020.06.23.20138065 ◽

2020 ◽

Cited By ~ 4

Author(s):

Ronald E Crump ◽

Ching-I Huang ◽

Ed Knock ◽

Simon E F Spencer ◽

Paul Brown ◽

...

Keyword(s):

Human African Trypanosomiasis ◽

Democratic Republic ◽

Democratic Republic Of Congo ◽

Model Fitting ◽

Case Finding ◽

World Health ◽

Model Parameters ◽

African Trypanosomiasis ◽

Republic Of Congo ◽

Case Data

AbstractGambiense human African trypanosomiasis (gHAT) is a virulent disease declining in burden but still endemic in West and Central Africa. Although it is targeted for elimination of transmission by 2030, there remain numerous questions about the drivers of infection and how these vary geographically.In this study we focus on the Democratic Republic of Congo (DRC), which accounted for 84% of the global case burden in 2016, to explore changes in transmission across the country and elucidate factors which may have contributed to the persistence of disease or success of interventions in different regions. We present a Bayesian fitting methodology, applied to 168 endemic health zones (∼ 100,000 population size), which allows for calibration of mechanistic gHAT model to case data (from the World Health Organization HAT Atlas) in an adaptive and automated framework.It was found that the model needed to capture improvements in passive detection to match observed trends in the data within former Bandundu and Bas Congo provinces indicating these regions have substantially reduced time to detection. Health zones in these provinces generally had longer burn-in periods during fitting due to additional model parameters.Posterior probability distributions were found for a range of fitted parameters in each health zone; these included the basic reproduction number estimates for pre-1998 (R0) which was inferred to be between 1 and 1.19, in line with previous gHAT estimates, with higher median values typically in health zones with more case reporting in the 2000s.Previously, it was not clear whether a fall in active case finding in the period contributed to the declining case numbers. The modelling here accounts for variable screening and suggests that underlying transmission has also reduced greatly – on average 96% in former Equateur, 93% in former Bas Congo and 89% in former Bandundu – Equateur and Bandundu having had the highest case burdens in 2000. This analysis also sets out a framework to enable future predictions for the country.Author summaryGambiense human African trypanosomiasis (gHAT; sleeping sickness) is a deadly disease targeted for elimination by 2030, however there are still several unknowns about what factors influence continued transmission and how this changes with geographic location.In this study we focus on the Democratic Republic of Congo (DRC), which reported 84% of the global cases in 2016 to try and explain why some regions of the country have had more success than others in bringing down case burden. To achieve this we used a state-of-the-art statistical framework to match a mathematical gHAT model to reported case data for 168 regions with some case reporting during 2000–2016.The analysis indicates that two former provinces, Bandundu and Bas Congo had substantial improvements to case detection in fixed health facilities in the time period. Overall, all provinces were estimated to have reductions in (unobservable) transmission including ∼ 96% in former Equateur. This is reassuring as case finding effort has decreased in that region.The model fitting presented here will allow predictions of gHAT under future strategies to be performed in the future.

Download Full-text

Quantifying epidemiological drivers of gambiense human African Trypanosomiasis across the Democratic Republic of Congo

PLoS Computational Biology ◽

10.1371/journal.pcbi.1008532 ◽

2021 ◽

Vol 17 (1) ◽

pp. e1008532

Author(s):

Ronald E. Crump ◽

Ching-I Huang ◽

Edward S. Knock ◽

Simon E. F. Spencer ◽

Paul E. Brown ◽

...

Keyword(s):

Human African Trypanosomiasis ◽

Democratic Republic ◽

Democratic Republic Of Congo ◽

Probability Distributions ◽

Central Africa ◽

World Health ◽

Model Parameters ◽

African Trypanosomiasis ◽

Republic Of Congo ◽

Variable Screening

Gambiense human African trypanosomiasis (gHAT) is a virulent disease declining in burden but still endemic in West and Central Africa. Although it is targeted for elimination of transmission by 2030, there remain numerous questions about the drivers of infection and how these vary geographically. In this study we focus on the Democratic Republic of Congo (DRC), which accounted for 84% of the global case burden in 2016, to explore changes in transmission across the country and elucidate factors which may have contributed to the persistence of disease or success of interventions in different regions. We present a Bayesian fitting methodology, applied to 168 endemic health zones (∼100,000 population size), which allows for calibration of a mechanistic gHAT model to case data (from the World Health Organization HAT Atlas) in an adaptive and automated framework. It was found that the model needed to capture improvements in passive detection to match observed trends in the data within former Bandundu and Bas Congo provinces indicating these regions have substantially reduced time to detection. Health zones in these provinces generally had longer burn-in periods during fitting due to additional model parameters. Posterior probability distributions were found for a range of fitted parameters in each health zone; these included the basic reproduction number estimates for pre-1998 (R0) which was inferred to be between 1 and 1.14, in line with previous gHAT estimates, with higher median values typically in health zones with more case reporting in the 2000s. Previously, it was not clear whether a fall in active case finding in the period contributed to the declining case numbers. The modelling here accounts for variable screening and suggests that underlying transmission has also reduced greatly—on average 96% in former Equateur, 93% in former Bas Congo and 89% in former Bandundu—Equateur and Bandundu having had the highest case burdens in 2000. This analysis also sets out a framework to enable future predictions for the country.

Download Full-text

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

Journal of The Royal Society Interface ◽

10.1098/rsif.2021.0419 ◽

2021 ◽

Vol 18 (183) ◽

Author(s):

Christopher N. Davis ◽

Matt J. Keeling ◽

Kat S. Rock

Keyword(s):

Human African Trypanosomiasis ◽

Democratic Republic ◽

Democratic Republic Of Congo ◽

Mechanistic Model ◽

Stochastic Methods ◽

African Trypanosomiasis ◽

Exact Methods ◽

Republic Of Congo ◽

Forward Equations ◽

Kolmogorov Forward Equations

Stochastic methods for modelling disease dynamics enable the direct computation of the probability of elimination of transmission. 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.

Download Full-text