Francesco Pizzitutti

Background: Models 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. Methods: In 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. Results: Considering 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. Conclusions: This 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. Graphical

The widespread dispersion of pigs infected with cysticercosis across endemic villages, low cyst burden among infected pigs, and low prevalence of taeniasis all suggest that pig ingestion of human feces is not the only mode of transmission for Taenia solium. Our objective was to evaluate the risk of porcine cysticercosis associated with exposure to human feces, dung beetles, and flies in an endemic community setting. We used a cluster-randomized cohort design to compare the risk of developing antibodies and infection among 120 piglets raised in either free-roaming (FR), standard corral (SC), or netted corral environments (NC). We collected monthly blood samples to detect serum antibodies and necropsied all pigs after 10 months to identify cysts. A total of 66 piglets developed antibodies with the relative risk of seropositivity in FR vs. all corralled pigs increasing significantly after 18 weeks. Of 108 necropsied pigs, 15 had T. solium cysts, all belonging to the FR group. Corrals were protective against infection but less so against seropositivity. NC, which did not completely exclude insects, did not provide added protection against seropositivity as compared to SC. The results of this study suggest that dung beetles and flies do not play an important role in infection.

The pork tapeworm, Taenia solium, is the cause of a preventable zoonotic disease, cysticercosis, affecting both pigs and humans. Continued endemic transmission of T. solium is a major contributor of epilepsy and other neurologic morbidity, and the source of important economic losses, in many rural areas of developing countries. Simulation modelling can play an important role in aiding the design and evaluation of strategies to control or even eliminate transmission of the parasite. In this paper, we present a new agent based model of local-scale T. solium transmission and a new, non-local, approach to the model calibration to fit model outputs to observed human taeniasis and pig cysticercosis prevalence simultaneously for several endemic villages. The model fully describes all relevant aspects of T. solium transmission, including the processes of pig and human infection, the spatial distribution of human and pig populations, the production of pork for human consumption, and the movement of humans and pigs in and out in several endemic villages of the northwest of Peru. Despite the high level of uncertainty associated with the empirical measurements of epidemiological data associated with T. solium, the non-local calibrated model parametrization reproduces the observed prevalences with an acceptable precision. It does so not only for the villages used to calibrate the model, but also for villages not included in the calibration process. This important finding demonstrates that the model, including its calibrated parametrization, can be successfully transferred within an endemic region. This will enable future studies to inform the design and optimization of T. solium control interventions in villages where the calibration may be prevented by the limited amount of empirical data, expanding the possible applications to a wider range of settings compared to previous models.

Introduction: The Taenia solium tapeworm is responsible for cysticercosis, a neglected tropical disease presenting as larvae in the body of a host following taenia egg ingestion. Neurocysticercosis (NCC), the name of the disease when it affects the human central nervous system, is a major cause of epilepsy in developing countries, and can also cause intracranial hypertension, hydrocephalus and death. Simulation models can help identify the most cost-effective interventions before their implementation. Modelling NCC should enable the comparison of a broad range of interventions, from treatment of human taeniasis (presence of an adult taenia worm in the human intestine) to NCC mitigation. It also allows a focus on the actual impact of the disease, rather than using proxies as is the case for other models. Methods: This agent-based model is the first model that simulates human NCC and associated pathologies. It uses the output of another model, CystiAgent, which simulates the evolution of pig cysticercosis and human taeniasis, adding human and cyst agents, including a model of cyst location and stage, human symptoms, and treatment. CystiHuman also accounts for delays in the appearance of NCC-related symptoms. It comprises three modules detailing cyst development, seizure probability and timing, and intracranial hypertension/hydrocephalus, respectively. It has been implemented in Java MASON and calibrated in three endemic villages in Peru, then applied to another village (Rica Playa) to compare simulation results with field data in that village. Results and discussion: Despite limitations in available field data, parameter values found through calibration are plausible and simulated outcomes in Rica Playa are close to actual values for NCC prevalence and the way it increases with age and cases with single lesions. Initial simulations further suggest that short-term interventions followed by a rapid increase in taeniasis prevalence back to original levels may have limited impacts on NCC prevalence.

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.

Though malaria control initiatives have markedly reduced malaria prevalence in recent decades, global eradication is far from actuality. Recent studies show that environmental and social heterogeneities in low-transmission settings have an increased weight in shaping malaria micro-epidemiology. New integrated and more localized control strategies should be developed and tested. Here we present a set of agent-based models designed to study the influence of local scale human movements on local scale malaria transmission in a typical Amazon environment, where malaria is transmission is low and strongly connected with seasonal riverine flooding. The agent-based simulations show that the overall malaria incidence is essentially not influenced by local scale human movements. In contrast, the locations of malaria high risk spatial hotspots heavily depend on human movements because simulated malaria hotspots are mainly centered on farms, were laborers work during the day. The agent-based models are then used to test the effectiveness of two different malaria control strategies both designed to reduce local scale malaria incidence by targeting hotspots. The first control scenario consists in treat against mosquito bites people that, during the simulation, enter at least once inside hotspots revealed considering the actual sites where human individuals were infected. The second scenario involves the treatment of people entering in hotspots calculated assuming that the infection sites of every infected individual is located in the household where the individual lives. Simulations show that both considered scenarios perform better in controlling malaria than a randomized treatment, although targeting household hotspots shows slightly better performance.

This paper presents a decision-support system based on a system dynamics model designed to examine tourism management in the Galapagos Islands. A participatory approach was used to integrate the views of multiple stakeholders in the Galapagos Islands and to build an understandable, graphical representation of the impacts of tourism and residential population growth. Each subsystem is examined through hypotheses involving three scenarios of tourism growth that are associated with different residential population expansions. A number of integrative and linked social-ecological effects in our model have been shown to severely shock the natural environment of the Galapagos and saturate the capacity of several socio-economic subsystems. Major concerns of the expanding human dimension in the Galapagos are represented by (1) the growing number of introduced species that threaten the Islands’ unique natural environment, and (2) the rapid saturation of the Galapagos National Park's tourism reception capacity. The model relies upon real data to specify rules, relationships, and rates of exchange that are derived through statistical functions and/or functions specified in theory or practice. The presented decision-support system is a quantitative scenario-planning tool that can be used by policy-makers to achieve an enhanced understanding of the Galapagos Islands as a coupled human–natural system.

The Amazon environment has been exposed in the last decades to radical changes that have been accompanied by a remarkable rise of both Plasmodium falciparum and Plasmodium vivax malaria. The malaria transmission process is highly influenced by factors such as spatial and temporal heterogeneities of the environment and individual-based characteristics of mosquitoes and humans populations. All these determinant factors can be simulated effectively trough agent-based models. This paper presents a validated agent-based model of local-scale malaria transmission. The model reproduces the environment of a typical riverine village in the northern Peruvian Amazon, where the malaria transmission is highly seasonal and apparently associated with flooding of large areas caused by the neighbouring river. Agents representing humans, mosquitoes and the two species of Plasmodium (P. falciparum and P. vivax) are simulated in a spatially explicit representation of the environment around the village. The model environment includes: climate, people houses positions and elevation. A representation of changes in the mosquito breeding areas extension caused by the river flooding is also included in the simulation environment. A calibration process was carried out to reproduce the variations of the malaria monthly incidence over a period of 3 years. The calibrated model is also able to reproduce the spatial heterogeneities of local scale malaria transmission. A “what if” eradication strategy scenario is proposed: if the mosquito breeding sites are eliminated through mosquito larva habitat management in a buffer area extended at least 200 m around the village, the malaria transmission is eradicated from the village. The use of agent-based models can reproduce effectively the spatiotemporal variations of the malaria transmission in a low endemicity environment dominated by river floodings like in the Amazon.

Currently tourism is the main driver of change in the Galapagos Islands, affecting the social, terrestrial, and marine sub-systems. Tourism also has direct and indirect consequences for the unique archipelago's natural habitats and for the human well-being. Describing the mechanisms that drive and affect most the tourism development in Galapagos is a preliminary condition to developing a better understanding of the interaction structure of factors that shape the Galapagos archipelago as a social-ecological complex system. In this paper, we present a first attempt to represent the touristic market in Galapagos trough an Agent Based Model (ABM) of touristic activity, focusing on touristic offers, reservations, and touristic activities. The model is based on an individual-based representation of tourists' consumption preferences and touristic accommodation offers in the Galapagos Islands. Tourist agents are created to mimic the real world by assigning average characteristics of individuals who visit the Galapagos Archipelago of Ecuador. The accommodation offers (i.e., hotels and cruises) are generated in accordance with actual conditions derived from data collected through field surveys. The model includes a market agent that can change the prices, create and delete accommodation offers following an evolutionary algorithm. We carried out preliminary simulations that show a close agreement between real world data and model outputs. Furthermore we used the model to generate three 'what if' scenarios in order to study how emergent patterns in the touristic market in Galapagos are affected by changes in the archipelago environment. In this way we illustrate how the model can be used as a useful tool to help public policy makers to explore the consequences of their decisions.