Predicting the impact of COVID-19 interruptions on transmission of gambiense human African trypanosomiasis in two health zones of the Democratic Republic of Congo. (19th February 2021)

• Record Type: Journal Article
• Authors: Aliee, Maryam; Castaño, Soledad; Davis, Christopher N; Patel, Swati; Miaka, Erick Mwamba; Spencer, Simon E F; Keeling, Matt J; Chitnis, Nakul; Rock, Kat S
• Is Part Of: Transactions of the Royal Society of Tropical Medicine and Hygiene. Volume 115:Number 3(2021)
• Page Start: 245
• Page End: 252
• Publication Date: 2021-02-19
• Subjects: COVID-19 -- elimination of transmission -- gambiense human African trypanosomiasis (gHAT) -- mitigation -- modelling; Tropical medicine -- Periodicals; 616.9883
• DOI: 10.1093/trstmh/trab019
• Languages: English
• ISSNs: 0035-9203

Abstract

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.