Evidence map›Paper›PMID 37941062›Full record

ArticleParasites & vectors2023

Spatial transferability of an agent-based model to simulate Taenia solium control interventions.

Francesco Pizzitutti, Gabrielle Bonnet, Eloy Gonzales-Gustavson, Sarah Gabriël, William K Pan, Armando E Gonzalez, Hector H Garcia, Seth E O'Neal, Cysticercosis Working Group in Peru

Open access · goldAbstract read
In one paragraph

Article in Parasites & vectors, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.8field-weighted citation impact, top 26% of its field
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

2 citing papers in PubMed, 3 citations in OpenAlex.

  1. Article
  2. 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 at 7 institutions in 5 countries.

Francesco PizzituttiGeography Department, San Francisco de Quito University, Quito, Ecuador. francesco.pizzitutti@gmail.com.
Gabrielle BonnetCentre for Mathematical Modelling of Infectious Disease (CMMID), Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK.
Eloy Gonzales-GustavsonTropical and Highlands Veterinary Research Institute, Universidad Nacional Mayor de San Marcos, Lima, Peru.
Sarah GabriëlDepartment of Veterinary Public Health and Food Safety, Ghent University, Ghent, Belgium.
William K PanNicholas School of Environment and Duke Global Health Institute, Duke University, Durham, USA.
Armando E GonzalezSchool of Veterinary Medicine, Universidad Nacional Mayor de San Marcos, Lima, Peru.
Hector H GarciaCenter for Global Health, Universidad Peruana Cayetano Heredia, Lima, Peru.
Seth E O'NealCenter for Global Health, Universidad Peruana Cayetano Heredia, Lima, Peru.
Cysticercosis Working Group in Peru
National University of San Marcos · PEDuke University · USGhent University · BEInstituto Nacional de Ciencias NeurológicasLondon School of Hygiene & Tropical Medicine · GBUniversidad Peruana Cayetano Heredia · PEUniversidad San Francisco de Quito · EC

Funding

Training in Parasitic Diseases and Central Nervous System Infections in Peru.D43TW001140 · FIC · UNIVERSIDAD PERUANA CAYETANO HEREDIA · PI GARCIA, HECTOR HUGO, GILMAN, ROBERT H · 1999 to 2025
$5.7M
Development and validation of an agent-based model to promote evidence-based control of Taenia solium cysticercosisR01AI141554 · NIAID · OREGON HEALTH & SCIENCE UNIVERSITY · PI O'NEAL, SETH E · 2019 to 2023
$3.3M
FIC NIH HHS D43 TW001140NIAID NIH HHS R01 AI141554NIH HHS NIH R01AI141554
6 · The paper itself

Abstract

backgroundModels can be used to study and predict the impact of interventions aimed at controlling the spread of infectious agents, such as Taenia solium, a zoonotic parasite whose larval stage causes epilepsy and economic loss in many rural areas of the developing nations. To enhance the credibility of model estimates, calibration against observed data is necessary. However, this process may lead to a paradoxical dependence of model parameters on location-specific data, thus limiting the model's geographic transferability.

methodsIn this study, we adopted a non-local model calibration approach to assess whether it can improve the spatial transferability of CystiAgent, our agent-based model of local-scale T. solium transmission. The calibration dataset for CystiAgent consisted of cross-sectional data on human taeniasis, pig cysticercosis and pig serology collected in eight villages in Northwest Peru. After calibration, the model was transferred to a second group of 21 destination villages in the same area without recalibrating its parameters. Model outputs were compared to pig serology data collected over a period of 2 years in the destination villages during a trial of T. solium control interventions, based on mass and spatially targeted human and pig treatments.

resultsConsidering the uncertainties associated with empirical data, the model produced simulated pre-intervention pig seroprevalences that were successfully validated against data collected in 81% of destination villages. Furthermore, the model outputs were able to reproduce validated pig seroincidence values in 76% of destination villages when compared to the data obtained after the interventions. The results demonstrate that the CystiAgent model, when calibrated using a non-local approach, can be successfully transferred without requiring additional calibration.

conclusionsThis feature allows the model to simulate both baseline pre-intervention transmission conditions and the outcomes of control interventions across villages that form geographically homogeneous regions, providing a basis for developing large-scale models representing T. solium transmission at a regional level.

Indexed as

CysticercosisSwine DiseasesTaeniasisTaenia soliumAnimalsCross-Sectional StudiesHumansSwineAgent-based modelingControl intervention simulationsHuman taeniasisInfectious diseases modelingModel calibrationModel transferabilityPig cysticercosisTaenia solium

Identifiers

PMID37941062
PMCPMC10634186
OpenAlexW4388488063

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.