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

Abstract

Background The pork tapeworm (Taenia solium) is a parasitic helminth that imposes a major health and economic burden on poor rural populations around the world. As recognized by the World Health Organization, a key barrier for achieving control of T. solium is the lack of an accurate and validated simulation model with which to study transmission and evaluate available control and elimination strategies. CystiAgent is a spatially-explicit agent based model for T. solium that is unique among T. solium models in its ability to represent key spatial and environmental features of transmission and simulate spatially targeted interventions, such as ring strategy. Methods/Principal findings We validated CystiAgent against results from the Ring Strategy Trial (RST)–a large cluster-randomized trial conducted in northern Peru that evaluated six unique interventions for T. solium control in 23 villages. For the validation, each intervention strategy was replicated in CystiAgent, and the simulated prevalences of human taeniasis, porcine cysticercosis, and porcine seroincidence were compared against prevalence estimates from the trial. Results showed that CystiAgent produced declines in transmission in response to each of the six intervention strategies, but overestimated the effect of interventions in the majority of villages; simulated prevalences for human taenasis and porcine cysticercosis at the end of the trial were a median of 0.53 and 5.0 percentages points less than prevalence observed at the end of the trial, respectively. Conclusions/Significance The validation of CystiAgent represented an important step towards developing an accurate and reliable T. solium transmission model that can be deployed to fill critical gaps in our understanding of T. solium transmission and control. To improve model accuracy, future versions would benefit from improved data on pig immunity and resistance, field effectiveness of anti-helminthic treatment, and factors driving spatial clustering of T. solium infections including dispersion and contact with T. solium eggs in the environment.

CystiHuman: A model of human neurocysticercosis

“…Eggs in the environment, originally represented as a number in [ 16 ], are now represented as a density. Information regarding adaptations to CystiAgent relevant to CystiHuman since the original paper [ 16 , 18 ] is provided in S1 Text .…”

Non-local validated parametrization of an agent-based model of local-scale Taenia solium transmission in North-West Peru

“…A detailed model description will be illustrated in the following sections. The model presented here is a development of a previously published model [ 5 , 6 ] and it designed to reproduce local-scale T . solium transmission dynamics in the simulated villages by replicating relevant conditions in the study area during the period of data collection.…”

“…Our group recently published CystiAgent, an ABM representing local-scale T . solium transmission in Peru that provides several important advances [ 5 , 6 ]. These include a spatially explicit framework to capture local transmission heterogeneity and to allow modelling of spatially targeted interventions, an open population structure to allow parasite influx into the modeled area, and measurement of model output accuracy against real-world longitudinal data collected during control interventions.…”

“…One of the main limitations with CystiAgent involves the approach that was proposed for the model calibration [ 5 , 6 ]. Calibration [ 7 ] is a standard procedure used to assign values to model parameters that represent complex sequences of unknown probabilities that cannot be measured empirically.…”

“…Typically, the possible parameter space is systematically sampled and corresponding model outputs are statistically evaluated to identify parameter values that provide best fit of model outputs to observed data [ 7 ]. The CystiAgent calibration approach presented in previously published studies [ 5 , 6 ] relies on six parameters, which promotes over-fitting and limits model credibility. This can be addressed by streamlining steps representing parasite transmission in the ABM, thereby capturing the unknown probabilities in fewer transmission parameters.…”