Evidence map›Paper›PMID 39123265›Full record

ArticleParasites & vectors2024

Modelling timelines to elimination of sleeping sickness in the Democratic Republic of Congo, accounting for possible cryptic human and animal transmission.

Ronald E Crump, Maryam Aliee, Samuel A Sutherland, Ching-I Huang, Emily H Crowley, Simon E F Spencer, Matt J Keeling, Chansy Shampa, Erick Mwamba Miaka, Kat S Rock

Abstract read
In one paragraph

Article in Parasites & vectors, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Ronald E Crump *Zeeman Institute for Systems Biology and Infectious Disease Epidemiology Research (SBIDER), University of Warwick, Academic Loop Road, CV4 7AL, Coventry, UK.ORCID http://orcid.org/0000-0002-9884-4900
Maryam Aliee *Zeeman Institute for Systems Biology and Infectious Disease Epidemiology Research (SBIDER), University of Warwick, Academic Loop Road, CV4 7AL, Coventry, UK.ORCID http://orcid.org/0000-0003-2268-2295
Samuel A SutherlandZeeman Institute for Systems Biology and Infectious Disease Epidemiology Research (SBIDER), University of Warwick, Academic Loop Road, CV4 7AL, Coventry, UK.ORCID http://orcid.org/0000-0003-1794-9813
Ching-I HuangZeeman Institute for Systems Biology and Infectious Disease Epidemiology Research (SBIDER), University of Warwick, Academic Loop Road, CV4 7AL, Coventry, UK.ORCID http://orcid.org/0000-0002-8329-8310
Emily H CrowleyZeeman Institute for Systems Biology and Infectious Disease Epidemiology Research (SBIDER), University of Warwick, Academic Loop Road, CV4 7AL, Coventry, UK.ORCID http://orcid.org/0000-0002-5121-4979
Simon E F SpencerZeeman Institute for Systems Biology and Infectious Disease Epidemiology Research (SBIDER), University of Warwick, Academic Loop Road, CV4 7AL, Coventry, UK.ORCID http://orcid.org/0000-0002-8375-5542
Matt J KeelingZeeman Institute for Systems Biology and Infectious Disease Epidemiology Research (SBIDER), University of Warwick, Academic Loop Road, CV4 7AL, Coventry, UK.ORCID http://orcid.org/0000-0003-4639-4765
Chansy ShampaProgramme National de Lutte Contre la Trypanosomiase Humaine Africaine (PNLTHA)-DRC, Kinshasa, Democratic Republic of Congo.
Erick Mwamba MiakaProgramme National de Lutte Contre la Trypanosomiase Humaine Africaine (PNLTHA)-DRC, Kinshasa, Democratic Republic of Congo.
Kat S RockZeeman Institute for Systems Biology and Infectious Disease Epidemiology Research (SBIDER), University of Warwick, Academic Loop Road, CV4 7AL, Coventry, UK. k.s.rock@warwick.ac.uk.ORCID http://orcid.org/0000-0001-8414-7648

Funding

Bill and Melinda Gates Foundation OPP1177824Bill and Melinda Gates Foundation OPP1184344Bill & Melinda Gates Foundation INV-005121
6 · The paper itself

Abstract

backgroundSleeping sickness (gambiense human African trypanosomiasis, gHAT) is a vector-borne disease targeted for global elimination of transmission (EoT) by 2030. There are, however, unknowns that have the potential to hinder the achievement and measurement of this goal. These include asymptomatic gHAT infections (inclusive of the potential to self-cure or harbour skin-only infections) and whether gHAT infection in animals can contribute to the transmission cycle in humans.

methodsUsing modelling, we explore how cryptic (undetected) transmission impacts the monitoring of progress towards and the achievement of the EoT goal. We have developed gHAT models that include either asymptomatic or animal transmission, and compare these to a baseline gHAT model without either of these transmission routes, to explore the potential role of cryptic infections on the EoT goal. Each model was independently calibrated to five different health zones in the Democratic Republic of the Congo (DRC) using available historical human case data for 2000-2020 (obtained from the World Health Organization's HAT Atlas). We applied a novel Bayesian sequential updating approach for the asymptomatic model to enable us to combine statistical information about this type of transmission from each health zone.

resultsOur results suggest that, when matched to past case data, we estimated similar numbers of new human infections between model variants, although human infections were slightly higher in the models with cryptic infections. We simulated the continuation of screen-confirm-and-treat interventions, and found that forward projections from the animal and asymptomatic transmission models produced lower probabilities of EoT than the baseline model; however, cryptic infections did not prevent EoT from being achieved eventually under this approach.

conclusionsThis study is the first to simulate an (as-yet-to-be available) screen-and-treat strategy and found that removing a parasitological confirmation step was predicted to have a more noticeable benefit to transmission reduction under the asymptomatic model compared with the others. Our simulations suggest vector control could greatly impact all transmission routes in all models, although this resource-intensive intervention should be carefully prioritised.

Indexed as

Disease EradicationTrypanosomiasis, AfricanAnimalsBayes TheoremDemocratic Republic of the CongoHumansTrypanosoma brucei gambienseTsetse FliesAnimalAsymptomaticEliminationGambiense human African trypanosomiasis (gHAT)Infection reservoirModel comparisonModellingTransmission

Identifiers

PMID39123265
PMCPMC11313002

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.