Understanding transmission and control of the pork tapeworm with CystiAgent: a spatially explicit agent-based model

Abstract

Background: The pork tapeworm, Taenia solium, is a serious public health problem in rural low-resource areas of Latin America, Africa and Asia, where the associated conditions of nuerocysticercosis (NCC) and porcine cysticercosis cause substantial health and economic harms. An accurate and validated transmission model for T. solium would serve as an important new tool for control and elimination, as it would allow for comparison of available intervention strategies, and prioritization of the most effective strategies for control and elimination efforts. Methods: We developed a spatially-explicit agent-based model (ABM) for T. solium ("CystiAgent") that differs from prior T. solium models by including a spatial framework and behavioral parameters such as pig roaming, open human defecation, and human travel. In this article, we introduce the structure and function of the model, describe the data sources used to parameterize the model, and apply sensitivity analyses (Latin hypercube sampling-partial rank correlation coefficient (LHS-PRCC)) to evaluate model parameters. Results: LHS-PRCC analysis of CystiAgent found that the parameters with the greatest impact on model uncertainty were the roaming range of pigs, the infectious duration of human taeniasis, use of latrines, and the set of "tuning" parameters defining the probabilities of infection in humans and pigs given exposure to T. solium. Conclusions: CystiAgent is a novel ABM that has the ability to model spatial and behavioral features of T. solium transmission not available in other models. There is a small set of impactful model parameters that contribute uncertainty to the model and may impact the accuracy of model projections. Field and laboratory studies to better understand these key components of transmission may help reduce uncertainty, while current applications of CystiAgent may consider calibration of these parameters to improve model performance. These results will ultimately allow for improved interpretation of model validation results, and usage of the model to compare available control and elimination strategies for T. solium.

Validation of a spatial agent-based model for Taenia solium transmission (“CystiAgent”) against a large prospective trial of control strategies in northern Peru

“…CystiAgent is a spatially explicit ABM developed in NetLogo 6.0.4 (Northwestern University, Evanston, IL), an open-access ABM software ideal for representing spatial processes in a graphical user interface. The full model code is available at http://modelingcommons.org/browse/one_model/6268 , and an in-depth model description with sensitivity analyses of model parameters was previously published by Pray et al [ 21 ].…”

“…Each of the above processes is defined mathematically by a probability distribution and corresponding parameter(s) ( Table 1 ). The majority of parameters were derived from observational studies conducted in northern Peru [ 21 , 32 ], but some were based on expert opinion and literature review. Model parameters, source data, and in-depth sensitivity analyses on model parameterization are described in detail in Pray et al [ 21 ].…”

“…To this end, six models of T. solium transmission have been published to date that attempt to fill this gap [16][17][18][19][20][21]. Despite preliminary use of these models to compare and contrast available control strategies, there are significant concerns about the validity of these models that must be addressed before reliable policy recommendations can be made.…”

“…In order to address the above limitations, we developed a novel agent-based model (ABM) called "CystiAgent" [21]. Notably, CystiAgent includes a spatial structure and open population, which allows it to represent key aspects of the T. solium life-cycle, and facilitates the evaluation of spatially targeted control interventions.…”

How modelling can help steer the course set by the World Health Organization 2021-2030 roadmap on neglected tropical diseases

“…Similarly for onchocerciasis, modelling shows that the rate at which interventions can be scaled down depend strongly on the spatial units of assessment 13,96 . Clustering of T. solium porcine cysticercosis around human taeniasis carriers, particularly evident in South American communities, demonstrates the need for spatially explicit models in certain settings 14,97 , such as the recently developed CystiAgent model for Peru 98 , capable of testing spatially structured interventions. From this it is evident that whilst spatial heterogeneity requires nuanced model structure, the leading challenge here is the paucity of data at the spatial level necessary to parameterise the models for spatially relevant insights.…”