Evidence map›Paper›PMID 36682395›Full record

ArticleActa tropica2023

Does a One Health approach to human African trypanosomiasis control hasten elimination? A stochastic compartmental modeling approach.

Julianne Meisner, Agapitus Kato, Marshall M Lemerani, Erick M Miaka, Acaga T Ismail, Jonathan Wakefield, Ali Rowhani-Rahbar, David Pigott, Jonathan D Mayer, Christopher Lorton and 1 more

Abstract read
In one paragraph

Article in Acta tropica, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
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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

11 authors.

Julianne MeisnerDepartment of Global Health, University of Washington, Seattle, WA, USA. Electronic address: meisnerj@uw.edu.
Agapitus KatoUganda Virus Research Institute, Entebbe, Uganda.
Marshall M LemeraniTrypanosomiasis Control Programme, Malawi Ministry of Health, Lilongwe, Malawi.
Erick M MiakaTrypanosomiasis Control Programme, Malawi Ministry of Health, Lilongwe, Malawi.
Acaga T IsmailProgramme National de Lutte contre la Trypanosomiase Humaine Africaine, Kinshasa, DRC.
Jonathan WakefieldDepartment of Statistics, University of Washington, Seattle, WA, USA; Department of Biostatistics, University of Washington, Seattle, WA, USA.
Ali Rowhani-RahbarDepartment of Epidemiology, University of Washington, Seattle, WA, USA.
David PigottDepartment of Health Metrics Sciences, University of Washington, Seattle, WA, USA.
Jonathan D MayerDepartment of Epidemiology, University of Washington, Seattle, WA, USA; Department of Geography, University of Washington, Seattle, WA, USA.
Christopher LortonInstitute for Disease Modeling, Seattle, WA, USA.
Peter M RabinowitzDepartment of Environmental and Occupational Health Sciences, Seattle, WA, USA.

Funding

Biostatistics, Epidemiologic & Bioinformatic Training in Environmental HealthT32ES015459 · NIEHS · UNIVERSITY OF WASHINGTON · PI June T. Spector · 2009 to 2026
$10.6M
NIEHS NIH HHS T32 ES015459
6 · The paper itself

Abstract

background. In response to large strides in the control of human African trypanosomiasis (HAT), in the early 2000s the WHO set targets for elimination of both the gambiense (gHAT) and rhodesiense (rHAT) forms as a public health (EPHP) problem by 2020, and elimination of gHAT transmisson (EOT) by 2030. While global EPHP targets have been met, and EOT appears within reach, current control strategies may fail to achieve gHAT EOT in the presence of animal reservoirs, the role of which is currently uncertain. Furthermore, rHAT is not targeted for EOT due to the known importance of animal reservoirs for this form.

methods. To evaluate the utility of a One Health approach to gHAT and rHAT EOT, we built and parameterized a compartmental stochastic model, using the Institute for Disease Modeling's Compartmental Modeling Software, to six HAT epidemics: the national rHAT epidemics in Uganda and Malawi, the national gHAT epidemics in Uganda and South Sudan, and two separate gHAT epidemics in Democratic Republic of Congo distinguished by dominant vector species. In rHAT foci the reservoir animal sub-model was stratified on four species groups, while in gHAT foci domestic swine were assumed to be the only competent reservoir. The modeled time horizon was 2005-2045, with calibration performed using HAT surveillance data and Optuna. Interventions included insecticide and trypanocide treatment of domestic animal reservoirs at varying coverage levels.

results. Validation against HAT surveillance data indicates favorable performance overall, with the possible exception of DRC. EOT was not observed in any modeled scenarios for rHAT, however insecticide treatment consistently performed better than trypanocide treatment in terms of rHAT control. EOT was not observed for gHAT at 0% coverage of domestic reservoirs with trypanocides or insecticides, but was observed by 2030 in all test scenarios; again, insecticides demonstrated superior performance to trypanocides.

conclusionsEOT likely cannot be achieved for rHAT without control of wildlife reservoirs, however insecticide treatment of domestic animals holds promise for improved control. In the presence of domestic animal reservoirs, gHAT EOT may not be achieved under current control strategies.

Indexed as

InsecticidesOne HealthTrypanocidal AgentsTrypanosomiasis, AfricanAnimalsAnimals, DomesticHumansSwineInsecticidesTrypanocidal AgentsHATHuman African trypanosomiasisOne HealthStochastic compartmental modelsZoonoses

Identifiers

PMID36682395
PMCPMC9992224

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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.