Evidence map›Paper›PMID 33905480›Full record

ArticleClinical infectious diseases : an official publication of the Infectious Diseases Society of America2021

Modelling to Quantify the Likelihood that Local Elimination of Transmission has Occurred Using Routine Gambiense Human African Trypanosomiasis Surveillance Data.

Christopher N Davis, María Soledad Castaño, Maryam Aliee, Swati Patel, Erick Mwamba Miaka, Matt J Keeling, Simon E F Spencer, Nakul Chitnis, Kat S Rock

Abstract read
In one paragraph

Article in Clinical infectious diseases : an official publication of the Infectious Diseases Society of America, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

  1. Article
  2. Article
  3. Using Passive Surveillance to Maintain Elimination as a Public Health Problem for Neglected Tropical Diseases: A Model-Based Exploration.Clinical infectious diseases : an official publication of the Infectious Diseases Society of America · 2024
    Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. ModellingJournal of the Royal Society, Interface · 2021
    Article
  9. Article
  10. What Can Modeling Tell Us About Sustainable End Points for Neglected Tropical Diseases?Clinical infectious diseases : an official publication of the Infectious Diseases Society of America · 2021
    Article
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

9 authors.

Christopher N DavisMathematics Institute, University of Warwick, Coventry, United Kingdom.
María Soledad CastañoDepartment of Epidemiology and Public Health, Swiss Tropical and Public Health Institute, Basel, Switzerland.
Maryam AlieeMathematics Institute, University of Warwick, Coventry, United Kingdom.
Swati PatelZeeman Institute for Systems Biology and Infectious Disease Epidemiology Research (SBIDER), University of Warwick, Coventry, United Kingdom.
Erick Mwamba MiakaProgramme National de Lutte contre la Trypanosomiase Humaine Africaine, Kinshasa, the Democratic Republic of the Congo.
Matt J KeelingMathematics Institute, University of Warwick, Coventry, United Kingdom.
Simon E F SpencerZeeman Institute for Systems Biology and Infectious Disease Epidemiology Research (SBIDER), University of Warwick, Coventry, United Kingdom.
Nakul ChitnisDepartment of Epidemiology and Public Health, Swiss Tropical and Public Health Institute, Basel, Switzerland.
Kat S RockMathematics Institute, University of Warwick, Coventry, United Kingdom.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe gambiense human African trypanosomiasis (gHAT) elimination programme in the Democratic Republic of Congo (DRC) routinely collects case data through passive surveillance and active screening, with several regions reporting no cases for several years, despite being endemic in the early 2000s.

methodsWe use mathematical models fitted to longitudinal data to estimate the probability that selected administrative regions have already achieved elimination of transmission (EOT) of gHAT. We examine the impact of active screening coverage on the certainty of model estimates for transmission and therefore the role of screening in the measurement of EOT.

resultsIn 3 example health zones of Sud-Ubangi province, we find there is a moderate (>40%) probability that EOT has been achieved by 2018, based on 2000-2016 data. Budjala and Mbaya reported zero cases during 2017-18, and this further increases our respective estimates to 99.9% and 99.6% (model S) and to 87.3% and 92.1% (model W). Bominenge had recent case reporting, however, that if zero cases were found in 2021, it would substantially raise our certainty that EOT has been met there (99.0% for model S and 88.5% for model W); this could be higher with 50% coverage screening that year (99.1% for model S and 94.0% for model W).

conclusionsWe demonstrate how routine surveillance data coupled with mechanistic modeling can estimate the likelihood that EOT has already been achieved. Such quantitative assessment will become increasingly important for measuring local achievement of EOT as 2030 approaches.

Indexed as

Trypanosomiasis, AfricanAnimalsDemocratic Republic of the CongoHumansMass ScreeningProbabilityTrypanosoma brucei gambienseelimination of transmissiongambiense human African trypanosomiasis (gHAT)modelingsurveillance

Identifiers

PMID33905480
PMCPMC8201550

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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.