How to avoid a local epidemic becoming a global pandemic.

Here, we combine international air travel passenger data with a standard epidemiological model of the initial 3 mo of the COVID-19 pandemic (January through March 2020; toward the end of which the entire world locked down). Using the information available during this initial phase of the pandemic, our model accurately describes the main features of the actual global development of the pandemic demonstrated by the high degree of coherence between the model and global data. The validated model allows for an exploration of alternative policy efficacies (reducing air travel and/or introducing different degrees of compulsory immigration quarantine upon arrival to a country) in delaying the global spread of SARS-CoV-2 and thus is suggestive of similar efficacy in anticipating the spread of future global disease outbreaks. We show that a lesson from the recent pandemic is that reducing air travel globally is more effective in reducing the global spread than adopting immigration quarantine. Reducing air travel out of a source country has the most important effect regarding the spreading of the disease to the rest of the world. Based upon our results, we propose a digital twin as a further developed tool to inform future pandemic decision-making to inform measures intended to control the spread of disease agents of potential future pandemics. We discuss the design criteria for such a digital twin model as well as the feasibility of obtaining access to the necessary online data on international air travel.

Species Diversity and Habitat Fragmentation Per Se: The Influence of Local Extinctions and Species Clustering.

AbstractAnthropogenic fragmentation of habitat is considered to be a critical factor contributing to the decline of species. However, a general consensus on the degree to which habitat loss and what has been called "habitat fragmentation per se" contribute to the loss of species diversity has not yet emerged. For empirical and theoretical reasons the topic has recently attracted renewed attention, thus reviving the "single large or several small" (SLOSS) debate. To study the effect of fragmentation per se, we use a spatially explicit and continuous, competitively neutral simulation model with immigration from a regional pool. The model accounts for the influence of ecological drift and intrafragment species clustering (due to limited dispersal) on local (plot) and global (landscape) diversity. We find that fragmentation increases global diversity but decreases local diversity, prominently so if fragments become more isolated. Cluster formation is a key mechanism reducing local diversity. By adding external disturbance events that lead to the occasional extinction of entire communities in habitat fragments, we show that the combined effect of such extinctions and cluster formation can create nonlinear interactive effects of fragmentation and fragment isolation on diversity patterns. We conclude that while in most cases fragmentation will decrease local and increase landscape diversity, universal predictions concerning the SLOSS debate should be taken with care.

Modeling health outcomes associated with BRCA testing and treatment strategies for patients with metastatic pancreatic cancer.

BACKGROUND: Germline BRCA mutations (gBRCAm) occur in 4%-8% patients with metastatic pancreatic cancer (mPC); guidelines recommend platinum-based chemotherapies and olaparib maintenance in this population. We evaluated, through modeling, the role of treatments and gBRCA testing on health outcomes of mPC patients. METHODS: A decision tree/partitioned survival model was developed to assess lifetime health outcomes for four strategies: 1) no testing; 2) early testing/no olaparib maintenance; 3) early testing (i.e., before 1L treatment)/olaparib maintenance; and 4) late testing/olaparib maintenance. Treatment patterns were assumed to follow current practice in the United States. Overall survival and progression-free survival curves were extrapolated from pivotal trials, including POLO trial for outcomes from olaparib maintenance after at least 16 weeks of platinum-based chemotherapy. RESULTS: Among patients with gBRCAm, almost twice as many patients received platinum-based regimens in strategies involving early testing compared to when early testing was not employed (78.7 % vs 40.2 %). Health outcomes were highest in the strategy with early testing and available olaparib treatment whether considering progression-free life years (PF LYs, 1.27 vs 0.55-0.87), LYs (1.82 vs 0.95-1.27) or quality adjusted life years (QALYs, 1.15 vs 0.73-0.92 for others). Consistent patterns of results were observed in the overall cohort of mPC patients (i.e., irrespective of gBRCAm). CONCLUSION: Patients with mPC achieved longest health outcomes (as measured by mean PF LYs, LYs and QALYs) with a scenario of early gBRCA testing and availability of olaparib maintenance. The results were primarily driven by improved health outcomes associated with higher efficacy of platinum-based chemotherapies and olaparib used in gBRCAm patients.

Preservation of pulsatility with universal ventricular assist device: In vitro assessment for biventricular support.

BACKGROUND: The objective of this study was to assess the pulsatility preservation capability of the universal ventricular assist device (UVAD) when used as a biventricular assist device (BVAD). This evaluation was conducted through an in vitro experiment, utilizing a pulsatile biventricular circulatory mock loop. METHODS: Two UVAD pumps were tested in a dual setup (BVAD) in the circulatory model with the simulated conditions of left heart failure (HF), right HF, and moderate/severe biventricular HF (BHF). The total flow, aortic pulse pressure, the pulse augmentation factor (PAF), the energy-equivalent pressure (EEP), and the surplus hemodynamic energy (SHE) were observed at various pump speeds to evaluate the pulsatility. RESULTS: The aortic pulse pressure increased from the baseline (without pump) in all simulated hemodynamic conditions. The PAF ranged from 17%-35% in healthy, left HF, right HF, and mild BHF conditions, with the highest PAF of 90% being observed in the severe BHF condition. The EEP correlated with LVAD flow in all groups (R2 = 0.87-0.97) and increased from the baseline in all cases. The SHE peaked at approximately 5-6 L/min of LVAD support and was likely to decrease at higher LVAD pump flow. The largest decrease in SHE from the baseline, 53%, was observed in the mild BHF conditions with the highest LVAD and RVAD support. CONCLUSIONS: The UVAD successfully demonstrated the ability to preserve pulsatility in vitro, and to optimize the cardiac output, as an isolated circulatory support device option (RVAD or LVAD) and when used for BVAD support.

Social network analysis reveals the failure of between-farm movement restrictions to reduce Salmonella transmission.

An increasing number of countries are investigating options to stop the spread of the emerging zoonotic infection Salmonella Dublin (S. Dublin), which mainly spreads among bovines and with cattle manure. Detailed surveillance and cattle movement data from an 11-yr period in Denmark provided an opportunity to gain new knowledge for mitigation options through a combined social network and simulation modeling approach. The analysis revealed similar network trends for noninfected and infected cattle farms despite stringent cattle movement restrictions imposed on infected farms in the national control program. The strongest predictive factor for farms becoming infected was their cattle movement activities in the previous month, with twice the effect of local transmission. The simulation model indicated an endemic S. Dublin occurrence, with peaks in outbreak probabilities and sizes around observed cattle movement activities. Therefore, pre- and postmovement measures within a 1-mo time window may help reduce S. Dublin spread.

Projecting COVID-19 intensive care admissions for policy advice, the Netherlands, February 2020 to January 2021.

BackgroundModel projections of coronavirus disease 2019 (COVID-19) incidence help policymakers about decisions to implement or lift control measures. During the pandemic, policymakers in the Netherlands were informed on a weekly basis with short-term projections of COVID-19 intensive care unit (ICU) admissions.AimWe aimed at developing a model on ICU admissions and updating a procedure for informing policymakers.MethodThe projections were produced using an age-structured transmission model. A consistent, incremental update procedure integrating all new surveillance and hospital data was conducted weekly. First, up-to-date estimates for most parameter values were obtained through re-analysis of all data sources. Then, estimates were made for changes in the age-specific contact rates in response to policy changes. Finally, a piecewise constant transmission rate was estimated by fitting the model to reported daily ICU admissions, with a changepoint analysis guided by Akaike's Information Criterion.ResultsThe model and update procedure allowed us to make weekly projections. Most 3-week prediction intervals were accurate in covering the later observed numbers of ICU admissions. When projections were too high in March and August 2020 or too low in November 2020, the estimated effectiveness of the policy changes was adequately adapted in the changepoint analysis based on the natural accumulation of incoming data.ConclusionThe model incorporates basic epidemiological principles and most model parameters were estimated per data source. Therefore, it had potential to be adapted to a more complex epidemiological situation with the rise of new variants and the start of vaccination.

Simulation and training for pediatric colorectal surgery and anorectal malformation: a scoping review.

PURPOSE: To study the published literature for various models used for simulation and training in the field of pediatric colorectal surgery. METHOD: A PubMed search was conducted for studies of simulation models in anorectal malformation on 24 March 2024 with the search words 'simulation pediatric colorectal surgery' followed by another search on 'simulation AND anorectal malformation' that gave 22 and 14 results, respectively (total 36). After removing 4 duplicate publications, 12 were found relevant to simulation and training in colorectal diseases. One publication relevant to the topic was added from literature, thirteen articles were studied. RESULTS: Of these, 5; 1; 4; and 3 were on inanimate models; animate model; 3D reconstructions; and training, respectively. Simulation models are available for posterior sagittal anorectoplasty. The same inanimate model was used in five articles. The animate model was based on a chicken cadaver. 3D models have been made for personalized preoperative assessment and to understand the imaging in anorectal malformation. One 3D model was made by regeneration of organoid epithelium. Training modules were made to evaluate surgical dissection, standardize surgical techniques, and improve proficiency. CONCLUSION: Simulation models are an important tool for teaching the steps of surgery and discussing the nuances of operative complications among mentors and peers. With advances in this field, the development of high-fidelity models, more training modules, and consensus on surgical techniques will benefit surgical training.

Simulations of Transients in a Four-Pole Magnetic Bearing with Permanent Magnets.

This paper presents the design of and transient time simulations for a four-pole magnetic bearing with permanent magnets. The usage of permanent magnets reduces the consumption of electric energy in comparison to a traditional active magnetic bearing. Permanent magnets are installed in the yoke of the stator core to limit the cross-coupling of the magnetic flux generated by the windings. The first part of this paper presents the design of the magnetic bearing and its finite-element model, while the second part describes the field-circuit indirectly coupled finite-element model for the transient time simulation. The presented simulation model was used to calculate the transient response for the rotor lifting from the starting position, the step change in the rotor position and the change in the rotor position under an external impact force applied along the y-axis.

[Simulation model of tumor-treating fields].

Tumor-treating fields (TTFields) is a novel treatment modality for malignant solid tumors, often employing electric field simulations to analyze the distribution of electric fields on the tumor under different parameters of TTFields. Due to the present difficulties and high costs associated with reproducing or implementing the simulation model construction techniques, this study used readily available open-source software tools to construct a highly accurate, easily implementable finite element simulation model for TTFields. The accuracy of the model is at a level of 1 mm 3. Using this simulation model, the study carried out analyses of different factors, such as tissue electrical parameters and electrode configurations. The results show that factors influncing the distribution of the internal electric field of the tumor include changes in scalp and skull conductivity (with a maximum variation of 21.0% in the treatment field of the tumor), changes in tumor conductivity (with a maximum variation of 157.8% in the treatment field of the tumor), and different electrode positions and combinations (with a maximum variation of 74.2% in the treatment field of the tumor). In summary, the results of this study validate the feasibility and effectiveness of the proposed modeling method, which can provide an important reference for future simulation analyses of TTFields and clinical applications.

The Testing Imperative: Why the US Ending the Human Immunodeficiency Virus (HIV) Epidemic Program Needs to Renew Efforts to Expand HIV Testing in Clinical and Community-Based Settings.

Data from several modeling studies demonstrate that large-scale increases in human immunodeficiency virus (HIV) testing across settings with a high burden of HIV may produce the largest incidence reductions to support the US Ending the HIV Epidemic (EHE) initiative's goal of reducing new HIV infections 90% by 2030. Despite US Centers for Disease Control and Prevention's recommendations for routine HIV screening within clinical settings and at least yearly screening for individuals most at risk of acquiring HIV, fewer than half of US adults report ever receiving an HIV test. Furthermore, total domestic funding for HIV prevention has remained unchanged between 2013 and 2019. The authors describe the evidence supporting the value of expanded HIV testing, identify challenges in implementation, and present recommendations to address these barriers through approaches at local and federal levels to reach EHE targets.

Inter-annual facilitation via pollinator support arises with species-specific germination rates in a model of plant-pollinator communities.

Facilitation is likely important for understanding community diversity dynamics, but its myriad potential mechanisms are under-investigated. Studies of pollinator-mediated facilitation in plants, for example, are typically focused on how co-flowering species facilitate each other's pollination within a season. However, pollinator-mediated facilitation could also arise in the form of inter-annual pollination support, where co-occurring plant populations mutually facilitate each other by providing dynamic stability to support a pollinator population through time. In this work, I test this hypothesis with simulation models of annual flowering plant and bee pollinator populations to determine if and how inter-annual pollination support affects the persistence and/or stability of simulated communities. Two-species plant communities persisted at higher rates than single-species communities, and facilitation was strongest in communities with low mean germination rates and highly species-specific responses to environmental variation. Single-species communities were often more stable than their counterparts, likely because of survivorship-persistent single-species communities were necessarily more stable through time to support pollinators. This work shows that competition and facilitation can simultaneously affect plant population dynamics. It also importantly identifies key features of annual plant communities that might exhibit inter-annual pollination support- those with low germination rates and species-specific responses to variation.

Simulating carbon accumulation and loss in the central Congo peatlands.

Peatlands of the central Congo Basin have accumulated carbon over millennia. They currently store some 29 billion tonnes of carbon in peat. However, our understanding of the controls on peat carbon accumulation and loss and the vulnerability of this stored carbon to climate change is in its infancy. Here we present a new model of tropical peatland development, DigiBog_Congo, that we use to simulate peat carbon accumulation and loss in a rain-fed interfluvial peatland that began forming ~20,000 calendar years Before Present (cal. yr BP, where 'present' is 1950 CE). Overall, the simulated age-depth curve is in good agreement with palaeoenvironmental reconstructions derived from a peat core at the same location as our model simulation. We find two key controls on long-term peat accumulation: water at the peat surface (surface wetness) and the very slow anoxic decay of recalcitrant material. Our main simulation shows that between the Late Glacial and early Holocene there were several multidecadal periods where net peat and carbon gain alternated with net loss. Later, a climatic dry phase beginning ~5200 cal. yr BP caused the peatland to become a long-term carbon source from ~3975 to 900 cal. yr BP. Peat as old as ~7000 cal. yr BP was decomposed before the peatland's surface became wetter again, suggesting that changes in rainfall alone were sufficient to cause a catastrophic loss of peat carbon lasting thousands of years. During this time, 6.4 m of the column of peat was lost, resulting in 57% of the simulated carbon stock being released. Our study provides an approach to understanding the future impact of climate change and potential land-use change on this vulnerable store of carbon.

Why do Hymenopteran workers drift to non-natal groups? Generalized reciprocity and the maximization of group and parental success.

Eusocial Hymenoptera are often characterized by having facultatively or obligately sterile worker castes. However, findings across an increasing number of species are that some workers are non-natal-they have 'drifted' away from where they were born and raised. Moreover, drifters are often indistinguishable from natal workers in the work and benefits provided to joined groups. This seems an evolutionary paradox of providing benefits to potentially unrelated individuals over close kin. Rather than being mistakes, drifting is proposed to be adaptive if joiners either gain inclusive fitness by preferentially moving to other kin groups or through generalized reciprocity in which exchanging workers across groups raises group-level genetic diversity and creates social heterosis. It is unclear, however, if reciprocity is unlikely because of a susceptibility to cheating. In resolving this question, a series of evolutionary simulations show: (1) Reciprocity can persist under a range of genetic assumptions and scenarios of cheating, (2) cheating almost always evolves, but can be expressed in a variety of ways that are not always predictable, (3) the inclusive fitness hypothesis is equally or more susceptible to cheating. Moreover, existing data in Hymenoptera (although not extensive) are more consistent with generalized reciprocity. This supports a hypothesis that drifting, as a phenomenon, may more often reflect maximization of group and parental fitness rather than fitness gains for the individual drifters.

Pollen carryover, pollinator movement, and spatial context impact the delivery of pollination services in apple orchards.

Assessing the relative contributions of different pollinator taxa to pollination services is a central task in both basic eco-evolutionary research and applied conservation and agriculture. To that end, many studies have quantified single-visit pollen deposition and visitation frequency, which together determine a pollinator species' rate of conspecific pollen delivery. However, for plant species that require or benefit from outcrossing, pollination service quality further depends upon the ratio of outcross to self-pollen deposited, which is determined by two additional pollinator traits: pollen carryover and movement patterns among genetically compatible plant individuals. Here, we compare the pollination capacities of managed honey bees, native bumble bees, and native mining bees in apple-a varietally self-incompatible commercial crop-when pollen carryover and pollinator movement patterns are considered. We constructed simulation models of outcross pollen deposition parameterized using empirically measured single-visit pollen deposition, visitation frequency, and probabilities of intertree movement exhibited by each pollinator type, as well as pollen carryover patterns simulated based on parameters reported in the literature. In these models, we also explicitly specified the spatial relationships among cross-compatible trees based on field-realistic orchard layout schemes. We found that estimated pollination service delivery was considerably reduced for all pollinator types when pollen carryover and pollinator movement patterns were considered, as compared to when only single-visit pollen deposition and visitation frequency were considered. We also found that the performance of different pollinator types varied greatly across simulated orchard layout schemes and pollen carryover scenarios, including one instance where bumble and mining bees reversed their relative rankings. In all simulations, native bumble and mining bees outperformed managed honey bees in terms of both outcross pollen delivery per unit time and per flower visited, with disparities being greatest under scenarios of low pollen carryover. We demonstrate the degree to which pollination studies may reach inaccurate conclusions regarding pollination service delivery when pollen carryover and pollinator movement patterns are ignored. Our finding of the strong context dependence of pollination efficiency, even within a single plant-pollinator taxon pair, cautions that future studies in both basic and applied pollination biology should explicitly consider the ecological context in which pollination interactions take place.

Evolutionary potential mitigates extinction risk under climate change in the endangered southwestern willow flycatcher.

The complexity of global anthropogenic change makes forecasting species responses and planning effective conservation actions challenging. Additionally, important components of a species' adaptive capacity, such as evolutionary potential, are often not included in quantitative risk assessments due to lack of data. While genomic proxies for evolutionary potential in at-risk species are increasingly available, they have not yet been included in extinction risk assessments at a species-wide scale. In this study, we used an individual-based, spatially explicit, dynamic eco-evolutionary simulation model to evaluate the extinction risk of an endangered desert songbird, the southwestern willow flycatcher (Empidonax traillii extimus), in response to climate change. Using data from long-term demographic and habitat studies in conjunction with genome-wide ecological genomics research, we parameterized simulations that include 418 sites across the breeding range, genomic data from 225 individuals, and climate change forecasts spanning 3 generalized circulation models and 3 emissions scenarios. We evaluated how evolutionary potential, and the lack of it, impacted population trajectories in response to climate change. We then investigated the compounding impact of drought and warming temperatures on extinction risk through the mechanism of increased nest failure. Finally, we evaluated how rapid action to reverse greenhouse gas emissions would influence population responses and species extinction risk. Our results illustrate the value of incorporating evolutionary, demographic, and dispersal processes in a spatially explicit framework to more comprehensively evaluate the extinction risk of threatened and endangered species and conservation actions to promote their recovery.

Cost-utility analysis of the UPRIGHT intervention promoting resilience in adolescents.

BACKGROUND: As mental health in adulthood is related to mental status during adolescence, school-based interventions have been proposed to improve resilience. The objective of this study was to build a simulation model representing the natural history of mental disorders in childhood, adolescence and youth to estimate the cost-effectiveness of the UPRIGHT school-based intervention in promoting resilience and mental health in adolescence. METHODS: We built a discrete event simulation model fed with real-world data (cumulative incidence disaggregated into eight clusters) from the Basque Health Service database (609,381 individuals) to calculate utilities (quality-adjusted life years [QALYs]) and costs for the general population in two scenarios (base case and intervention). The model translated changes in the wellbeing of adolescents into different risks of mental illnesses for a time horizon of 30 years. RESULTS: The number of cases of anxiety was estimated to fall by 5,125 or 9,592 and those of depression by 1,269 and 2,165 if the effect of the intervention lasted 2 or 5 years respectively. From a healthcare system perspective, the intervention was cost-effective for all cases considered with incremental cost-utility ratios always lower than €10,000/QALY and dominant for some subgroups. The intervention was always dominant when including indirect and non-medical costs (societal perspective). CONCLUSIONS: Although the primary analysis of the trial did not did not detect significant differences, the UPRIGHT intervention promoting positive mental health was dominant in the economic evaluation from the societal perspective. Promoting resilience was more cost-effective in the most deprived group. Despite a lack of information about the spillover effect in some sectors, the economic evaluation framework developed principally for pharmacoeconomics can be applied to interventions to promote resilience in adolescents. As prevention of mental health disorders is even more necessary in the post-coronavirus disease-19 era, such evaluation is essential to assess whether investment in mental health promotion would be good value for money by avoiding costs for healthcare providers and other stakeholders.

Plant Disease Models and Forecasting: Changes in Principles and Applications over the Last 50 Years.

This review gives a perspective of selected advances made since the middle of the 20th century in plant disease modeling, and the associated increase in the number of models published during that time frame. This progress can be mainly attributed to advances in (i) sensors and automatic environmental data collection technology, (ii) instrumentation and methods for studying botanical epidemiology, and (iii) data analytics and computer science. We review the evolution of techniques for developing data-based (empirical) models and process-based (mechanistic) models using the wheat rusts as a case study. We also describe the increased importance of knowledge about biological processes for plant disease modeling by using apple scab as a second case study. For both wheat rusts and apple scab, we describe how the models have evolved over the last 50 years by considering certain milestones that have been achieved in disease modeling. Finally, we describe how plant disease models are used as part of a multi-modeling approach to develop decision-making tools in the application of integrated pest management.

Modeling of cryopreservation pathway operation at an aquatic biomedical stock center for zebrafish.

Aquatic biomedical model organisms play a substantial role in advancing our understanding of human health, however, comparably little work has been directed towards developing dependable, high-throughput storage programs for valuable genetic resources. The Zebrafish International Resource Center (ZIRC) has developed a standardized cryopreservation pathway and stored thousands of genetic lines in their repository for use by the biomedical research community. This has yet to be replicated in other facilities, and an overall repository-level pathway has never been analyzed for aquatic species. To encourage repository development for other biomedical models and to improve the ZIRC storage process and system, this study used discrete-event simulation modeling to systematically analyze the cryopreservation pathway for efficiency, and to identify improvements. The models reflected "real-world" working conditions and were used to simulate key outputs, such as production capacity over time (throughput) and steps in the process that limit production (bottlenecks). With these models, recommendations were identified to eliminate waiting times and increase efficiency. These included following proper husbandry protocols because male quality significantly affected production time, and the use of part-time operators to assist with steps that had longer Waiting Times (i.e., time samples spent in a queue) to increase production capacity. Simulation process modeling is a powerful tool that can improve the operations of existing repositories. It can also support repository development at other biomedical stock centers, and at other facilities devoted to aquatic species such as research, conservation, and aquaculture production hatcheries.

Fine-grained mathematical modeling for cost-effectiveness evaluation of public health policies for cervical cancer, with application to a Colombian case study.

BACKGROUND: Cervical cancer (CC) is globally ranked fourth in terms of incidence and mortality among women. Vaccination against Human Papillomavirus (HPV) and screening programs can significantly reduce CC mortality rates. Hence, executing cost-effective public health policies for prevention and surveillance is crucial. However, defining policies that make the best use of the available resources is not easy, as it requires predicting the long-term costs and results of interventions on a changing population. Since the simpler task of predicting the results of public health policies is difficult, devising those that make the best usage of available resources is an arduous challenge for decision-makers. METHODS: This paper proposes a fine-grained epidemiological simulation model based on differential equations, to effectively predict the costs and effectiveness of CC public health policies that include vaccination and screening. The model represents population dynamics, HPV transmission within the population, likelihood of infection clearance, virus-induced appearance of precancerous lesions and eventually CC, as well as immunity gained with vaccination and early detection with screening. RESULTS: We offer a compartmentalized modeling approach that separates population, epidemics, and intervention concerns. We instantiate models with actual data from a Colombian case study and analyze their results to show how our modeling approach can support CEA studies. Moreover, we implement models in an open-source software tool to simultaneously define and evaluate multiple policies. With the support of the tool, we analyze 54 policies within a 30-year time horizon and use as a comparator the CC policy that has been used until recently. We identify 8 dominant policies, the best one with an ICER of 6.3 million COP (Colombian Pesos) per averted DALY. We also validate the modeling approach against the available population and HPV epidemic data. The effects of uncertainty in the values of key parameters (discount rate, sensitivity of screening tests) is evaluated through one-way sensitivity analysis. CONCLUSIONS: Our modeling approach can provide valuable support for healthcare decision-makers. The implementation into an automated tool allows customizing the analysis with country-specific data, flexibly defining public health policies to be evaluated, and conducting disaggregate analyses of their cost and effectiveness.

Biological control of the stink bug Nezara viridula (Heteroptera: Pentatomidae) by two parasitoids and their interaction in non-crop habitats: a simulation model.

Non-cultivated areas are resting, overwintering, feeding, and/or reproducing habitats for insects, and also places from where crop areas are colonized; thus, they are essential for understanding the biological control programs in agroecosystems. We developed a simulation model for a non-cultivated area of Buenos Aires province (Argentina), and we analyzed the control of Nezara viridula achieved by the action of two parasitoids: the oophagous Trissolcus basalis and the tachinid Trichopoda giacomellii, which attack older nymphs and adults. The model is a discrete time, deterministic, phenomenological, spatially homogeneous with a 1-week time interval simulation model, based on the age-structure and/or stage-structure of N. viridula and its two parasitoids. The host-parasitoid interactions were combined with a degree-day model affecting development times of T. giacomellii pupae and T. basalis pre-imaginal stages. The simultaneous attack of both parasitoid species enables the persistence of the system at low host densities, mediated by the functional response of the parasitoids, identified as population regulation factors. However, if only one parasitoid exists (i.e., only T. basalis or only T. giacomellii) the interaction N. viridula-parasitoid persisted but at higher density of N. viridula. These results explain the successful biological control of N. viridula after the introduction of T. basalis in the 1980s, when T. giacomellii was the only parasitoid present, unable to control N. viridula. Our model shows an indirect competition when both parasitoids are present: the attack of one of them diminished the potential number of hosts available to the other parasitoid species. In the field this interaction is obscured by the hibernation period which acted as a reset mechanism affecting the density and age/stage structure of all three populations. Our model was supported by field observations, and never exhibited the extinction of any of the parasitoids from the interaction.