Individual-based Model Research Articles

Assessing the impact of multi-year droughts on German forests in the context of increased tree mortality

Forests play a crucial role in climate regulation and societal well-being. Despite their significance, the increasing frequency of droughts poses a severe threat to forest ecosystems, impacting carbon sequestration and forest stability. In Germany, the unprecedented 2018–2020 drought resulted in extensive tree mortality and damaged wood volume, with lasting effects observed in subsequent years. As climate models project a continuation of such droughts, understanding the impact of droughts on forests becomes imperative. However, it is unclear how forests will evolve in the future if the drought duration continues to increase.This study employs a forest model to analyze the impact of droughts across various German forest types, focusing on the duration of drought periods and their influence on forest productivity. By utilizing an individual-based forest growth model and national forest inventories, the study addresses critical knowledge gaps regarding the effects of multi-year droughts on biomass and productivity across various forest types, including monocultures and mixed forests. The simulations consider a drought-induced large increase in tree mortality caused by factors such as pest infestations and diseases across Germany.Our simulation results reveal a declining aboveground biomass and gross primary production (GPP) for all simulated drought scenarios, including the three- and six-year drought. GPP is reduced by 46 % in the 3-year drought scenario and by 58 % in the 6-year drought scenario. Notably, prolonged droughts lead to cumulative losses, with a saturation effect in drought scenarios exceeding eight years. Forest stand composition influences these impacts, with greater GPP losses in low-biomass stands. Furthermore, different forest types exhibit varying responses. Monocultures and even-sized forests (mostly planted and managed forests) are more sensitive to drought than mixed and uneven-sized forests.The results provide valuable insights into forest resilience and ecosystem responses to increasingly frequent and prolonged droughts, highlighting the importance of understanding the effects of drought on monocultures and mixed forests to inform future forest management strategies. Modelling the influence of biotic factors on forest dynamics in a process-based manner remains a challenge that requires future research.

Adaptive Ensemble of Multi-Kernel Gaussian Process Regressions Based on Heuristic Model Screening for Nonparametric Modeling of Ship Maneuvering Motion

Abstract Gaussian process regression (GPR) is a commonly used approach for establishing the nonparametric models of ship maneuvering motion, and its performance depends on the selection of the kernel function. However, no single kernel function can be universally applied to all nonparametric models of ship maneuvering motion, which may compromise the robustness of GPR. To address this issue, an adaptive ensemble of multi-kernel GPRs based on heuristic model screening (AEGPR-HMS) is proposed in this paper. In the proposed method, four kernel functions are involved in constructing the ensemble model. The HMS method is introduced to determine the weights of individual-based GPR models, which can be adaptively assigned according to the baseline GPR model. To determine the hyper-parameters of these kernel functions, the genetic algorithm is also employed to compute the optimal values. The KVLCC2 tanker provided by the SIMMAN 2008 workshop is used to validate the performance of the proposed method. The results demonstrate that the AEGPR-HMS is an efficient and robust method for nonparametric modeling of ship maneuvering motion.

Understanding dynamics and overlapping epidemiologies of HIV, HSV-2, chlamydia, gonorrhea, and syphilis in sexual networks of men who have sex with men.

We aimed to investigate the overlapping epidemiologies of human immunodeficiency virus (HIV), herpes simplex virus type 2 (HSV-2), chlamydia, gonorrhea, and syphilis in sexual networks of men who have sex with men (MSM), and to explore to what extent the epidemiology of one sexually transmitted infection (STI) relates to or differs from that of another STI. An individual-based Monte Carlo simulation model was employed to simulate the concurrent transmission of STIs within diverse sexual networks of MSM. The model simulated sexual partnering, birth, death, and STI transmission within each specific sexual network. The model parameters were chosen based on the current knowledge and understanding of the natural history, transmission, and epidemiology of each considered STI. Associations were measured using the Spearman's rank correlation coefficient (SRCC) and maximal information coefficient (MIC). A total of 500 sexual networks were simulated by varying the mean and variance of the number of partners for both short-term and all partnerships, degree correlation, and clustering coefficient. HSV-2 had the highest current infection prevalence across the simulations, followed by HIV, chlamydia, syphilis, and gonorrhea. Threshold and saturation effects emerged in the relationship between STIs across the simulated networks, and all STIs demonstrated moderate to strong associations. The strongest current infection prevalence association was between HIV and gonorrhea, with an SRCC of 0.84 (95% CI: 0.80-0.87) and an MIC of 0.81 (95% CI: 0.74-0.88). The weakest association was between HSV-2 and syphilis, with an SRCC of 0.54 (95% CI: 0.48-0.59) and an MIC of 0.57 (95% CI, 0.49-0.65). Gonorrhea exhibited the strongest associations with the other STIs while syphilis had the weakest associations. Across the simulated networks, proportions of the population with zero, one, two, three, four, and five concurrent STI infections were 48.6, 37.7, 11.1, 2.4, 0.3, and < 0.1%, respectively. For lifetime exposure to these infections, these proportions were 13.6, 21.0, 22.9, 24.3, 13.4, and 4.8%, respectively. STI epidemiologies demonstrate substantial overlap and associations, alongside nuanced differences that shape a unique pattern for each STI. Gonorrhea exhibits an "intermediate STI epidemiology," reflected by the highest average correlation coefficient with other STIs.

Density-dependent species interactions modulate alpine treelineshifts.

Species interactions such as facilitation and competition play a crucial role in driving species range shifts. However, density dependence as a key feature of these processes has received little attention in both empirical and modelling studies. Herein, we used a novel, individual-based treeline model informed by rich insitu observations to quantify the contribution of density-dependent species interactions to alpine treeline dynamics, an iconic biome boundary recognized as an indicator of global warming. We found that competition and facilitation dominate in dense versus sparse vegetation scenarios respectively. The optimal balance between these two effects was identified at an intermediate vegetation thickness where the treeline elevation was the highest. Furthermore, treeline shift rates decreased sharply with vegetation thickness and the associated transition from positive to negative species interactions. We thus postulate that vegetation density must be considered when modelling species range dynamics to avoid inadequate predictions of its responses to climate warming.

Sex ratio distorting microbes exacerbate arthropod extinction risk in variable environments.

Maternally-inherited sex ratio distorting microbes (SRDMs) are common among arthropod species. Typically, these microbes cause female-biased sex ratios in host broods, either by; killing male offspring, feminising male offspring, or inducing parthenogenesis. As a result, infected populations can experience drastic ecological and evolutionary change. The mechanism by which SRDMs operate is likely to alter their impact on host evolutionary ecology; despite this, the current literature is heavily biased towards a single mechanism of sex ratio distortion, male-killing. Furthermore, amidst the growing concerns surrounding the loss of arthropod diversity, research into the impact of SRDMs on the viability of arthropod populations is generally lacking. In this study, using a theoretical approach, we model the epidemiology of an understudied mechanism of microbially-induced sex ratio distortion-feminisation-to ask an understudied question-how do SRDMs impact extinction risk in a changing environment? We constructed an individual-based model and measured host population extinction risk under various environmental and epidemiological scenarios. We also used our model to identify the precise mechanism modulating extinction. We find that the presence of feminisers increases host population extinction risk, an effect that is exacerbated in highly variable environments. We also identified transmission rate as the dominant epidemiological trait responsible for driving extinction. Finally, our model shows that sex ratio skew is the mechanism driving extinction. We highlight feminisers and, more broadly, SRDMs as important determinants of the resilience of arthropod populations to environmental change.

An individual-based model for direct and indirect transmission of chronic wasting disease in free-ranging white-tailed deer

Chronic wasting disease (CWD) is an infectious prion disease that infects members of the Cervidae family (i.e., deer) resulting in widespread ecological, economic, and recreational ramifications. We introduce a spatially explicit individual-based model (IBM) that integrates individual deer movement and behavior with population and disease dynamics to forecast CWD in populations of free-ranging white-tailed deer (Odocoileus virginianus). We use a Susceptible-Exposed-Infectious-Dead (S-E-I-D) epidemiological framework to explore spatiotemporal dynamics of CWD within an agriculturally dominated area in Michigan, USA. The IBM results closely mimicked documented short- and long-term dynamics of white-tailed deer populations and CWD in the Midwestern, USA. We applied pattern-oriented modeling using annual apparent CWD prevalence rates reported by Midwestern state wildlife agencies to validate the disease model. The introduction of a single infected deer to the modeled landscape (93 km2) led to an outbreak of CWD in 100 out of 350 model simulations (29 %); prevalence never exceeded 1.47 % for repetitions where the outbreak ended. For the 100 simulations where disease persisted, the deer population declined by 87 % by year 50 following initial introduction of CWD. Mean (±SD) prevalence after 5, 10, 25, and 50 years was 1.1 % (±1.0 %), 3.4 % (±3.3 %), 46.5 % (±18.8 %), and 51.8 % (±18.1 %), respectively, which highly correlated (r = 0.99) with annual CWD prevalence reported in Wisconsin white-tailed deer populations for years 1–21 post initial detection. Combined with a global sensitivity analysis, the IBM indicated that prevalence of CWD at year 20 was most sensitive to harvest rate of yearling and adult female deer and least sensitive to prion shedding rate, prion half-life, and deer group numbers, indicating that deer population parameters were more influential than disease parameters on CWD dynamics. Our IBM serves as a tool to explore and better understand indirect and direct transmission of CWD within free-ranging cervid populations. Users of this model can adjust parameter values to explore how interactions among individual deer and between deer and their environment affect CWD dynamics. This IBM also serves as a framework for applying and assessing spatially and temporally explicit management scenarios.

Economic Cycles and Entry into Parenthood: Is the Association Changing and Does it Affect Macro-Level Trends? Micro-Level Hazard and Simulation Models of Belgian Fertility Trends, 1960–2010

The association between economic cycles—typically measured in terms of GDP growth or swings in unemployment—and macro-level fertility trends has received ample attention in the literature. Compared to studies that consider macro-level fertility, individual-based models can address the association between economic cycles and specific stages of family formation (e.g. entry into parenthood) more precisely while allowing for structural factors that contribute to fertility postponement. Using population-wide longitudinal microdata from the Belgian censuses we combine discrete-time hazard models of entry into parenthood for the period 1960 to 2010 with microsimulation models to assess whether economic cycles in tandem with educational expansion can account for year-to-year variation in the proportion of women entering parenthood and variation in the pace of fertility postponement at the macro-level. Results indicate that educational expansion has been a structural driver of fertility postponement, whereas the procyclical effect of economic cycles accounts for accelerations and decelerations of fertility postponement throughout the period considered. Microsimulation of macro-level fertility trends indicates that individual-based models predict the annual proportion of women entering parenthood and the mean age at first birth with average errors of prediction below 1 per cent and 3 months, respectively, while also showing strong correlations between first differences of observed and simulated time-series. Because the extended observation window encompasses several severe recessions, we test whether the association between economic cycles and entry into parenthood has changed over time and how this affected macro-level trends, discussing several mechanisms that may account for such temporal variation.

Population Consequences of Parent-Offspring Competition: An Individual-Based Model

The article compares different versions of individual-based models of single population dynamics with overlapping generations with results of the model of population with non-overlapping generations. In all models, various versions of global competition for common resources and their unequal partitioning between competing individuals are analysed, i.e., when juveniles and adult individuals compete for the same resources, when juveniles and adult individuals use different resources, and a case called mother’s care. The article analyses the relationship between individual variability and population persistence measured by the time of population extinction. Persistence of a population is increased by all forms of competition between individuals not weakened by any environmental factors (e.g. diversification of resources of competing individuals) or factors arising from evolutionary history of the species (e.g. mother’s care) and related in an appropriate way to the mechanism shaping individual variability in the population. Any form of weakening competition leading to decreasing individual variability will adversely affect the persistence of the population. However, differences between versions of the model are not very big.

The multi-dimensional challenges of controlling respiratory virus transmission in indoor spaces: Insights from the linkage of a microscopic pedestrian simulation and SARS-CoV-2 transmission model.

SARS-CoV-2 transmission in indoor spaces, where most infection events occur, depends on the types and duration of human interactions, among others. Understanding how these human behaviours interface with virus characteristics to drive pathogen transmission and dictate the outcomes of non-pharmaceutical interventions is important for the informed and safe use of indoor spaces. To better understand these complex interactions, we developed the Pedestrian Dynamics-Virus Spread model (PeDViS), an individual-based model that combines pedestrian behaviour models with virus spread models incorporating direct and indirect transmission routes. We explored the relationships between virus exposure and the duration, distance, respiratory behaviour, and environment in which interactions between infected and uninfected individuals took place and compared this to benchmark 'at risk' interactions (1.5 metres for 15 minutes). When considering aerosol transmission, individuals adhering to distancing measures may be at risk due to the buildup of airborne virus in the environment when infected individuals spend prolonged time indoors. In our restaurant case, guests seated at tables near infected individuals were at limited risk of infection but could, particularly in poorly ventilated places, experience risks that surpass that of benchmark interactions. Combining interventions that target different transmission routes can aid in accumulating impact, for instance by combining ventilation with face masks. The impact of such combined interventions depends on the relative importance of transmission routes, which is hard to disentangle and highly context dependent. This uncertainty should be considered when assessing transmission risks upon different types of human interactions in indoor spaces. We illustrated the multi-dimensionality of indoor SARS-CoV-2 transmission that emerges from the interplay of human behaviour and the spread of respiratory viruses. A modelling strategy that incorporates this in risk assessments can help inform policy makers and citizens on the safe use of indoor spaces with varying inter-human interactions.

Performance of Outbreak Management Plans for Emerging Plant Diseases: The Case of Almond Leaf Scorch Caused by Xylella fastidiosa in Mainland Spain.

Outbreak response to quarantine pathogens and pests in the European Union (EU) is regulated by the EU Plant Health Law, but the performance of outbreak management plans in terms of their effectiveness and efficiency has been quantified only to a limited extent. As a case study, the disease dynamics of almond leaf scorch, caused by Xylella fastidiosa, in the affected area of Alicante, Spain, were approximated using an individual-based spatial epidemiological model. The emergence of this outbreak was dated based on phylogenetic studies, and official surveys were used to delimit the current extent of the disease. Different survey strategies and disease control measures were compared to determine their effectiveness and efficiency for outbreak management in relation to a baseline scenario without interventions. One-step and two-step survey approaches were compared with different confidence levels, buffer zone sizes, and eradication radii, including those set by the EU legislation for X. fastidiosa. The effect of disease control interventions was also considered by decreasing the transmission rate in the buffer zone. All outbreak management plans reduced the number of infected trees (effectiveness), but large differences were observed in the number of susceptible trees not eradicated (efficiency). The two-step survey approach, high confidence level, and the reduction in the transmission rate increased the efficiency. Only the outbreak management plans with the two-step survey approach removed infected trees completely, but they required greater survey efforts. Although control measures reduced disease spread, surveillance was the key factor in the effectiveness and efficiency of the outbreak management plans. [Formula: see text] Copyright © 2024 The Author(s). This is an open access article distributed under the CC BY 4.0 International license.

Evolution of individual variation in a competitive trait: a theoretical analysis.

When competitive traits are costly, negative frequency dependence can maintain genetic variance. Most theoretical studies examining this problem assume binary polymorphisms, yet most trait variation in wild populations is continuous. We propose that continuous trait variation can result from continuous variation in resource quality and that, specifically, the shape of the resource distribution determines trait maintenance. We used an individual-based model to test which conditions favour the stable maintenance of variation and which cause temporal fluctuations in trait values. This approach, inspired by contrasting outcomes of previous studies regarding variance and fluctuations in trait values, clearly showed a decisive role played by the shape of resource distributions. Under extreme conditions, e.g., the absence of resource variation or with very scarce resources for weak competitors, traits evolved to a single non-competitive or highly competitive strategy, respectively. Most other distributions led to strong temporal fluctuations on trait values or the maintenance of stable, standing variation. Our results thus explain the contradicting outcomes of previous theoretical studies and, at the same time, provide hypotheses to explain the maintenance of genetic variation and individual differences. We suggest ways to empirically test the proposed effects of resource variation on trait maintenance.

Alternative vegetation trajectories through passive habitat rewilding: opposite effects for animal conservation

ContextPassive habitat rewilding after rural abandonment can affect wildlife differently depending on the type of habitats that it generates.ObjectiveEvaluate and compare the effects of two alternative vegetation trajectories that occur through passive habitat rewilding in Mediterranean ecotone areas (crop-scrub and crop-pine forest transitions) on the long-term population dynamics of animal species.MethodsWe used the spur-thighed tortoise (Testudo graeca), a characteristic long-lived species of cultural landscapes, as study species. We applied a spatially explicit and individual-based model (STEPLAND) to simulate the movement and demographic processes in a long-term period, by comparing an “impact scenario” (i.e., historical land-use changes) to a “control scenario” (no land-use changes).ResultsThe two landscape scenarios resulted in different population trends. In the crop-scrub scenarios (control and impact), population densities increased similarly over time. However, the crop-pine forest scenario negatively affected population density throughout the simulation period, and showed a time-lag response of three decades. The extinction risk was 55% with a time-lag response of approximately 110 years.ConclusionsOur study highlights the need to analyse the legacy effects on long-lived ectotherms, using them as a proxy to understand the future effects of dynamic landscapes created by “passive habitat rewilding”. Our results showed how traditional agriculture in Mediterranean ecotone areas may generate “ecotone effects” (i.e. increase in demographical parameters), but also population extinction on long-lived ectotherms. Therefore, we consider it relevant to maintain traditional agricultural areas in Mediterranean landscapes, especially in ecotone areas associated with pine forests (generating mosaics with open habitats).

Balancing Ethics and Culture: A Scoping Review of Ethico-Cultural and Implementation Challenges of the Individual-Based Consent Model in African Research.

Objective: This review explores the ethico-cultural and implementation challenges associated with the individual-based informed consent (IC) model in the relatively collectivistic African context and examines suggested approaches to manage them. Methods: We searched four databases for peer-reviewed studies published in English between 2000 to 2023 that examined the ethico-cultural and implementation challenges associated with the IC model in Africa. Results: Findings suggest that the individual-based IC model largely misaligns with certain African social values and ethos and subverts the authority and functions of community gatekeepers. Three recommendations were proffered to manage these challenges, that researchers should: adopt a multi-step approach to IC, conduct a rapid ethical assessment, and generate an African-centered IC model. Conclusions: A pluriversal, context-specific, multi-step IC model that critically harmonizes the cultural values of the local population and the general principles of IC can minimize ethics dumping, safeguard the integrity of the research process, and promote respectful engagement.

Alternative reproductive tactics and evolutionary rescue.

Almost all life on earth is facing environmental change, and understanding how populations will respond to these changes is of urgent importance. One factor that is known to affect the speed by which a population can evolve when faced with changes in the environment is strong sexual selection. This increases the adaptive capacity of a population by increasing reproductive skew toward well-adapted (usually) males who will, on average, be best able to compete for matings. This effect could potentially be disrupted when males pursue alternative reproductive tactics (ARTs), whereby males within a species exhibit qualitatively different behaviors in their pursuit of matings. ARTs are diverse, but one common class is those expressed through condition-dependent polyphenism such that high-quality, well-adapted males compete aggressively for mates and low-quality, poorly adapted males attempt to acquire matings via other, nonaggressive behaviors. Here, using an individual-based modeling approach, we consider the possible impacts of ARTs on adaptation and evolutionary rescue. When the ART is simultaneous, meaning that low-quality males not only engage in contests but also pursue other tactics, adaptive capacity is reduced and evolutionary rescue, where a population avoids extinction by adapting to a changing environment, becomes less likely. This is because the use of the ART allows low-quality males to contribute more maladaptive genes to the population than would happen otherwise. When the ART is fixed, however, such that low-quality males will only use the alternative tactic and do not engage in contests, we find the opposite: adaptation happens more quickly and evolutionary rescue when the environment changes is more likely. This surprising effect is caused by an increase in the mating success of the highest quality males who face many fewer competitors in this scenario-counterintuitively, the presence of males pursuing the ART increases reproductive skew toward those males in the best condition.

Lessons from the calibration and sensitivity analysis of a fish larval transport model

Numerous fish populations show strong year-to-year variations in recruitment. The early life stages play a crucial role in determining recruitment and dispersal patterns. A helpful tool to understand recruitment and dispersal involves simulations with a Lagrangian transport model, which results from the coupling between a hydrodynamic model and an individual-based model. Larval transport models require sound knowledge of the biological processes governing larval dispersal, and they may be highly sensitive to the parameters selected. Various assumptions about larval traits, behaviour and other model parameters can be tested by comparing simulation results with field data to identify the most sensitive parameters and to improve model calibration. This study shows that biological parameterization is more important than inter-annual variability in explaining the year-to-year differences in larval recruitment of common sole in the North Sea and the eastern English Channel. In contrast, year-to-year variability of connectivity leads to higher variability than changes in the biological parameters. The most influential parameters are pelagic larval duration, spawning period and mortality. Calibration over a 12 yr recruitment survey shows that a scenario with low mortality associated with a long larval duration and behaviour involving nycthemeral and tidal migration best reproduces the observations. This research provides insights into factors influencing fish dispersal and recruitment, suggesting a strategy for enhancing the accuracy of models in upcoming studies. The study supports the improvement of larval dispersal modelling by incorporating an easily applicable sensitivity analysis for both calibration and validation. Incorporating sensitivity analyses enhances larval dispersal models, providing performing tools that can contribute to informed fisheries management and understanding of recruitment variability.

Phytoplankton retention mechanisms in estuaries: a case study of the Elbe estuary

Abstract. Due to their role as primary producers, phytoplankton are essential to the productivity of estuarine ecosystems. However, it is important to understand how these nearly passive organisms are able to persist within estuaries when river inflow results in a net outflow to the ocean. Estuaries also represent challenging habitats due to a strong salinity gradient. Little is known about how phytoplankton are able to be retained within estuaries. We present a new individual-based Lagrangian model of the Elbe estuary which examines possible retention mechanisms for phytoplankton. Specifically, we investigated how reproduction, sinking and rising, and diel vertical migration may allow populations to persist within the estuary. We find that vertical migration, especially rising, favors retention, while fast sinking does not. We further provide first estimates of outwashing losses. Our simulations illustrate that riverbanks and tidal flats are essential for the long-term survival of phytoplankton populations, as they provide refuges from strong downstream currents. These results contribute to the understanding needed to advance the ecosystem-based management of estuaries.

The decline of the 2022 Italian mpox epidemic: Role of behavior changes and control strategies

In 2022, a global outbreak of mpox occurred, predominantly impacting men who have sex with men (MSM). The rapid decline of this epidemic is yet to be fully understood. We investigated the Italian outbreak by means of an individual-based mathematical model calibrated to surveillance data. The model accounts for transmission within the MSM sexual contact network, in recreational and sex clubs attended by MSM, and in households. We indicate a strong spontaneous reduction in sexual transmission (61-87%) in affected MSM communities as the possible driving factor for the rapid decline in cases. The MSM sexual contact network was the main responsible for transmission (about 80%), with clubs and households contributing residually. Contact tracing prevented about half of the potential cases, and a higher success rate in tracing contacts could significantly amplify its effectiveness. Notably, immunizing the 23% of MSM with the highest sexual activity (10 or more partners per year) could completely prevent new mpox resurgences. This research underscores the importance of augmenting contact tracing, targeted immunization campaigns of high-risk groups, and fostering reactive behavioral changes as key strategies to manage and prevent the spread of emerging sexually transmitted pathogens like mpox within the MSM community.

A multi-rate dynamic analysis method of individual-based district heating system

The new generation of the district heating system (DHS) has attracted much attention due to its high efficiency. A precise and fast dynamic simulation is the foundation of the optimization and control strategy of a DHS. As a type of heterogeneous system, the DHS has internal components with multiple time scales, which limits accuracy of simulations. However, current studies have either chosen pseudo-dynamic models or have not considered the effect of the internal time scale on the simulation. To solve above problems, a dynamic multi-rate simulation method based on the individual-based model (IBM) is proposed in this paper. According to IBM, a complex system is decoupled into individuals, who interact with each other to form the whole system from bottom-up. During the process of modeling, equations of individuals indicating their dynamic behaviors are all converted into a system of ordinary differential equations (ODEs). And then the ODEs are solved from system level using multi-rate simulation methods. The case study illustrates that the proposed method takes 36.59 s for the 72 h long-term simulation of the DHS containing three components commonly involved and a district heating network, which provides good decision-making information for the optimal control of the system.

Predicting consequences of COVID-19 control measure de-escalation on nosocomial transmission and mortality: a modelling study in a French rehabilitation hospital

Infection control measures are effective for nosocomial COVID-19 prevention but bear substantial health-economic costs, motivating their "de-escalation" in settings at low risk of SARS-CoV-2 transmission. Yet consequences of de-escalation are difficult to predict, particularly in light of novel variants and heterogeneous population immunity. To estimate how infection control measure de-escalation influences nosocomial COVID-19 risk. An individual-based transmission model was used to simulate SARS-CoV-2 outbreaks and control measure de-escalation in a French long-term care hospital with multi-modal control measures in place (testing and isolation, universal masking, single-occupant rooms). Estimates of COVID-19 case fatality rates (CFRs) from reported outbreaks were used to quantify excess COVID-19 mortality due to de-escalation. In a population fully susceptible to infection, de-escalating both universal masking and single rooms resulted in hospital-wide outbreaks of 114 (95% CI: 103-125) excess infections, compared with five (three to seven) excess infections when de-escalating only universal masking or 15 (11-18) when de-escalating only single rooms. When de-escalating both measures and applying CFRs from the first wave of COVID-19, excess patient mortality ranged from 1.57 (1.41-1.71) to 9.66 (8.73-10.57) excess deaths/1000 patient-days. By contrast, when applying CFRs from subsequent pandemic waves and assuming susceptibility to infection among 40-60% of individuals, excess mortality ranged from 0 (0-0) to 0.92 (0.77-1.07) excess deaths/1000 patient-days. The de-escalation of bundled COVID-19 control measures may facilitate widespread nosocomial SARS-CoV-2 transmission. However, excess mortality is probably limited in populations at least moderately immune to infection and given CFRs resembling those estimated during the 'post-vaccine' era.

Sustaining high-value salmonid populations in regulated rivers: Insights from individual-based modelling of brown trout and Atlantic salmon

To combat climate change, societal pressure to develop fossil-free hydroelectricity is growing. There is a great need, however, for environmental assessment tools that can predict the effects of streamflow regulation on biodiversity in hydropower-regulated rivers. Ecological modelling lets practitioners: 1) set broad bounds on population-level responses of key species and 2) identify knowledge gaps and prioritize research needs. Individual-based models (IBMs) are powerful tools for assessing relative benefits of alternative management actions, and therefore help to develop more sustainable hydropower solutions. We applied the inSALMO 7.3-SD IBM for populations of brown trout (Salmo trutta) and Atlantic salmon (S. salar) in the lower Gullspång River, Sweden. We simulated the effects of various minimum hydropeaking flow releases (from 9 to 21 m3/s) on outmigration production. We found that the number of age-1 outmigrants of both species decreased with increasing minimum flow release of the hydropeaking scenarios. The number of age-2 trout outmigrants did not change considerably with increasing the minimum release, but decreased sharply at the highest flow. The most age-2 salmon outmigrants were produced by flow scenarios with minimum releases of 15 and 18 m3/s. The model predicts, therefore, varying species- and life stage-specific effects of flow regulation. Moreover, increased flow caused juveniles to stay in the river longer and outmigrate at larger size, which exposes them to simulated predation longer but could increase post-outmigration survival. By providing insights into mechanisms driving population dynamics, IBMs can help promote the sustainability of high-conservation-value fish species.