BMC infectious diseases · 2026
Transmission and cost-effectiveness modelling to estimate the progress towards elimination and future strategy optimisation for gambiense human African trypanosomiasis in Uganda.
СтатьяНазвание и аннотация: Перевод в очереди
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Huang Ching-I, Antillon Marina, Crump Ronald E, Sutherland Samuel A, Bessell Paul R, Mugenyi Albert, Selby Richard, Brown Paul E, Hooley Brady, Hope Andrew, Dunkley Sophie, Sunnucks Rob, Torr Steve J, Tediosi Fabrizio, Ndung'u Joseph, Crowley Emily H, Kidega Eric, Wamboga Charles, Rock Kat S
Аннотация
BACKGROUND: Gambiense human African trypanosomiasis (gHAT) is a vector-borne disease with hundreds of thousands of people living at risk across Sub-Saharan Africa. Uganda, having reduced gHAT cases reported annually from 948 in 2000 to zero local cases since 2020, is a frontrunner to be verified by the World Health Organization (WHO) as having achieved elimination of transmission (EoT) of gHAT. It is now crucial to quantify the impact of the interventions deployed, quantify whether the last transmission event (LTE) and last case have already occurred, and determine the resources required to sustain the gains.
METHODS: We employed a suite of mechanistic compartmental gHAT models, fitted to data from seven districts (Adjumani, Amuru, Arua, Koboko, Maracha, Moyo, and Yumbe) in Uganda that reported gHAT cases during 2000-2022, to address these questions. By combining and weighting the evidence from each model variant, we captured the uncertainty of achieving different elimination metrics across Uganda. Additionally, we utilised the dynamic transmission model outputs to perform a health economic analysis, identifying the most cost-effective strategies to avert disease burden.
RESULTS: Predictions estimate that Uganda had the LTE in or before 2021 with high certainty (>95%). The model suggests that the local Ugandan case reported in 2019 may have been the last, but that there remains a 1.13% chance that cases could be reported after 2025. The cost-effectiveness analysis recommends that as transmission dynamics remain similarly low across all strategies, the Stop 2026 strategy, in which there is only passive screening from 2026 and subsequent reactive screening and vector control are only implemented if cases are detected, has the highest probability of being cost-effective and is predicted to have an economic cost of $193K ($161K-$220K) between 2026 and 2040.
CONCLUSIONS: To sustain Uganda's success whilst ensuring efficient resource use, this modelling analysis recommends implementing the Stop 2026 strategy in all seven analysed districts, which focuses on maintaining strong passive screening post-2026. This recommendation aligns with the current gHAT strategy in Uganda.
METHODS: We employed a suite of mechanistic compartmental gHAT models, fitted to data from seven districts (Adjumani, Amuru, Arua, Koboko, Maracha, Moyo, and Yumbe) in Uganda that reported gHAT cases during 2000-2022, to address these questions. By combining and weighting the evidence from each model variant, we captured the uncertainty of achieving different elimination metrics across Uganda. Additionally, we utilised the dynamic transmission model outputs to perform a health economic analysis, identifying the most cost-effective strategies to avert disease burden.
RESULTS: Predictions estimate that Uganda had the LTE in or before 2021 with high certainty (>95%). The model suggests that the local Ugandan case reported in 2019 may have been the last, but that there remains a 1.13% chance that cases could be reported after 2025. The cost-effectiveness analysis recommends that as transmission dynamics remain similarly low across all strategies, the Stop 2026 strategy, in which there is only passive screening from 2026 and subsequent reactive screening and vector control are only implemented if cases are detected, has the highest probability of being cost-effective and is predicted to have an economic cost of $193K ($161K-$220K) between 2026 and 2040.
CONCLUSIONS: To sustain Uganda's success whilst ensuring efficient resource use, this modelling analysis recommends implementing the Stop 2026 strategy in all seven analysed districts, which focuses on maintaining strong passive screening post-2026. This recommendation aligns with the current gHAT strategy in Uganda.