A Modeling Study on the Effect of Interstate Mobility Restrictions on the SARS-CoV-2 Pandemic.

Mobility is a crucial element in comprehending the possible expansion of the transmission chain in an epidemic. In the initial phases, strategies for containing cases can be directly linked to population mobility restrictions, especially when only non-pharmaceutical measures are available. During the pandemic of COVID-19 in Brazil, mobility limitation measures were strongly opposed by a large portion of the population. Hypothetically, if the population had supported such measures, the sharp rise in the number of cases could have been suppressed. In this context, computational modeling offers systematic methods for analyzing scenarios about the development of the epidemiological situation taking into account specific conditions. In this study, we examine the impacts of interstate mobility in Brazil. To do so, we develop a metapopulational model that considers both intra and intercompartmental dynamics, utilizing graph theory. We use a parameter estimation technique that allows us to infer the effective reproduction number in each state and estimate the time-varying transmission rate. This makes it possible to investigate scenarios related to mobility and quantify the effect of people moving between states and how certain measures to limit movement might reduce the impact of the pandemic. Our results demonstrate a clear association between the number of cases and mobility, which is heightened when states are closer to each other. This serves as a proof of concept and shows how reducing mobility in more heavily trafficked areas can be more effective.

Centrality to the metapopulation is more important for population genetic diversity than habitat area or fragmentation.

Drift and gene flow affect genetic diversity. Given that the strength of genetic drift increases as population size decreases, management activities have focused on increasing population size through preserving habitats to preserve genetic diversity. Few studies have empirically evaluated the impacts of drift and gene flow on genetic diversity. Kryptolebias marmoratus, henceforth 'rivulus', is a small killifish restricted to fragmented New World mangrove forests with gene flow primarily associated with ocean currents. Rivulus form distinct populations across patches, making them a well-suited system to test the extent to which habitat area, fragmentation and connectivity are associated with genetic diversity. Using over 1000 individuals genotyped at 32 microsatellite loci, high-resolution landcover data and oceanographic simulations with graph theory, we demonstrate that centrality (connectivity) to the metapopulation is more strongly associated with genetic diversity than habitat area or fragmentation. By comparing models with and without centrality standardized by the source population's genetic diversity, our results suggest that metapopulation centrality is critical to genetic diversity regardless of the diversity of adjacent populations. While we find evidence that habitat area and fragmentation are related to genetic diversity, centrality is always a significant predictor with a larger effect than any measure of habitat configuration.

Inference on spatiotemporal dynamics for coupled biological populations.

Mathematical models in ecology and epidemiology must be consistent with observed data in order to generate reliable knowledge and evidence-based policy. Metapopulation systems, which consist of a network of connected sub-populations, pose technical challenges in statistical inference owing to nonlinear, stochastic interactions. Numerical difficulties encountered in conducting inference can obstruct the core scientific questions concerning the link between the mathematical models and the data. Recently, an algorithm has been proposed that enables computationally tractable likelihood-based inference for high-dimensional partially observed stochastic dynamic models of metapopulation systems. We use this algorithm to build a statistically principled data analysis workflow for metapopulation systems. Via a case study of COVID-19, we show how this workflow addresses the limitations of previous approaches. The COVID-19 pandemic provides a situation where mathematical models and their policy implications are widely visible, and we revisit an influential metapopulation model used to inform basic epidemiological understanding early in the pandemic. Our methods support self-critical data analysis, enabling us to identify and address model weaknesses, leading to a new model with substantially improved statistical fit and parameter identifiability. Our results suggest that the lockdown initiated on 23 January 2020 in China was more effective than previously thought.

The challenging biogeography of the Juan Fernández Islands and Coast Range of central Chile explained by new models of East Pacific tectonics.

Biogeographers have often been puzzled by several unusual features in the Juan Fernández Islands (JFI) biota. These include the very high endemism density, multiple endemics that are older than the current islands, close biogeographic affinities with the central and West Pacific, and affinities with the diverse Coast Range of central Chile. We review aspects of biogeography in the JFI and the Coast Range in light of recent geological studies. These have examined the mantle below the East Pacific and South America, and have produced radical, new ideas on tectonic history. A long-lived, intraoceanic archipelago ~9000 km long is now thought to have existed in the East Pacific (passing between the JFI hotspot and mainland Chile) until the mid-Cretaceous. At this time, South America, which was moving westward with the opening of the Atlantic, collided with the archipelago. The assumption that the JFI biota is no older than its current islands is questionable, as taxa would have survived on prior islands produced at the JFI hotspot. We propose a new interpretation of evolution in the region based on tectonics rather than on island age and incorporating the following factors: the newly described East Pacific Archipelago; a long history for the JFI hotspot; metapopulation dynamics, including metapopulation vicariance; and formation of the Humboldt Current in the Cretaceous. The model accounts for many distinctive features of the JFI and Coast Range biota.

COVID-19 in Scottish care homes: A metapopulation model of spread among residents and staff.

The movement of populations between locations and activities can result in complex transmission dynamics, posing significant challenges in controlling infectious diseases like COVID-19. Notably, networks of care homes create an ecosystem where staff and visitor movement acts as a vector for disease transmission, contributing to the heightened risk for their vulnerable communities. Care homes in the UK were disproportionately affected by the first wave of the COVID-19 pandemic, accounting for almost half of COVID-19 deaths during the period of 6th March - 15th June 2020 and so there is a pressing need to explore modelling approaches suitable for such systems. We develop a generic compartmental Susceptible - Exposed - Infectious - Recovered - Dead (SEIRD) metapopulation model, with care home residents, care home workers, and the general population modelled as subpopulations, interacting on a network describing their mixing habits. We illustrate the model application by analysing the spread of COVID-19 over the first wave of the COVID-19 pandemic in the NHS Lothian health board, Scotland. We explicitly model the outbreak's reproduction rate and care home visitation level over time for each subpopulation and execute a data fit and sensitivity analysis, focusing on parameters responsible for inter-subpopulation mixing: staff-sharing, staff shift patterns and visitation. The results from our sensitivity analysis show that restricting staff sharing between homes and staff interaction with the general public would significantly mitigate the disease burden. Our findings indicate that protecting care home staff from disease, coupled with reductions in staff-sharing across care homes and expedient cancellations of visitations, can significantly reduce the size of outbreaks in care home settings.

STOCHASTICITY, SCALE, AND REFRACTION: DETERMINANTS OF POPULATION SYNCHRONY IN PARASITES OF CENTRARCHIDS IN J. STROM THURMOND LAKE, SOUTH CAROLINA.

Among-deme asynchrony has the potential to influence community richness and diversity by increasing the likelihood of regional persistence for a species. Parasites of Lepomis spp. collected from 4 localities at J. Strom Thurmond Lake, South Carolina over a 1-yr period were used to evaluate patterns of parasite population synchrony. Localities were separated by approximately 5 km to increase the likelihood that the parasites sampled represented different demes. Tylodelphys scheuringi and Crinicleidus longus, exhibited negative covariation between synchrony and among-locality distances. The degree of synchrony exhibited by Neoechinorhynchus cylindratis, Crepidostomum cornutum, and Clavunculus bifurcatus was associated with the degree of similarity in habitat structure between localities. Patterns of synchrony for Posthodiplostomum minimum and Spinitectus sp. were not associated with any of the habitat variables examined. The influence of habitat structure on parasite population synchrony, possibly through the refraction of large-scale environmental drivers, has the potential to produce asynchronous dynamics that are independent of the distance between demes, thereby promoting regional persistence by increasing the likelihood of rescue effects.

Habitat requirements of deadwood-dependent invertebrates that occupy tree hollows.

Tree hollows support a specialised species-rich fauna. We review the habitat requirements of saproxylic (= deadwood dependent) invertebrates which occupy tree hollows. We focus on studies quantifying relationships between species occurrence patterns and characteristics of tree hollows, hollow trees, and the surrounding landscape. We also explore the processes influencing species occurrence patterns by reviewing studies on the spatio-temporal dynamics of populations, including their dispersal and genetic structure. Our literature search in the database Scopus identified 52 relevant publications, all of which were studies from Europe. The dominant taxonomic group studied was beetles. Invertebrates in hollow trees were often more likely to be recorded in trees with characteristics reflecting a large amount of resources or a stable and warm microclimate, such as a large diameter, large amounts of wood mould (= loose material accumulated in the hollows mainly consisting of decaying wood), a high level of sun exposure, and with entrance holes that are large and either at a low or high height, and in dry hollows, with entrances not directed upwards. A stable microclimate is probably a key factor why some species of saproxylic invertebrates are confined to tree hollows. Other factors that are different in comparison to downed dead wood is the fact that hollows at a given height from the ground provide shelter from ground-living predators, that hollows persist for longer, and that the content of nutrients might be enhanced by the accumulation of dead leaves, insect frass, and remains from dead insects. Several studies have identified a positive relationship between species occupancy per tree and the amount of habitat in the surrounding landscape, with a variation in the spatial scale at which characteristics of the surrounding landscape had the strongest effect over spatial scales from 200 to 3000 m. We found empirical support for the extinction threshold hypothesis, which predicts that the frequency of species presence per tree is greater if a certain number of trees are aggregated into a few large clusters of hollow trees rather than distributed among many small clusters. Observed thresholds in species occurrence patterns can be explained by colonisation-extinction dynamics, with species occupancy per tree influenced by variation in rates of immigration. Consistent with this assumption, field studies suggest that dispersal rate and range can be low for invertebrates occupying tree hollows, although higher in a warmer climate. For one species in which population dynamics has been studied over 25 years (Osmoderma eremita), the observed population dynamics have characteristics of a "habitat-tracking metapopulation", as local extinctions from trees occur possibly because those trees become unsuitable as well as due to stochastic processes in small populations. The persistence of invertebrate fauna confined to tree hollows may be improved by prolonging the standing life of existing hollow trees. It is also important to recruit new generations of hollow trees, preferably close to existing larger groups of hollow trees. Thus, the spatio-temporal dynamics of hollow trees is crucial for the invertebrate fauna that rely upon them.

Genome-Wide Allele Frequency Changes Reveal That Dynamic Metapopulations Evolve Differently.

Two important characteristics of metapopulations are extinction-(re)colonization dynamics and gene flow between subpopulations. These processes can cause strong shifts in genome-wide allele frequencies that are generally not observed in "classical" (large, stable, and panmictic) populations. Subpopulations founded by one or a few individuals, the so-called propagule model, are initially expected to show intermediate allele frequencies at polymorphic sites until natural selection and genetic drift drive allele frequencies toward a mutation-selection-drift equilibrium characterized by a negative exponential-like distribution of the site frequency spectrum. We followed changes in site frequency spectrum distribution in a natural metapopulation of the cyclically parthenogenetic pond-dwelling microcrustacean Daphnia magna using biannual pool-seq samples collected over a 5-yr period from 118 ponds occupied by subpopulations of known age. As expected under the propagule model, site frequency spectra in newly founded subpopulations trended toward intermediate allele frequencies and shifted toward right-skewed distributions as the populations aged. Immigration and subsequent hybrid vigor altered this dynamic. We show that the analysis of site frequency spectrum dynamics is a powerful approach to understand evolution in metapopulations. It allowed us to disentangle evolutionary processes occurring in a natural metapopulation, where many subpopulations evolve in parallel. Thereby, stochastic processes like founder and immigration events lead to a pattern of subpopulation divergence, while genetic drift leads to converging site frequency spectrum distributions in the persisting subpopulations. The observed processes are well explained by the propagule model and highlight that metapopulations evolve differently from classical populations.

52,000 years of woolly rhinoceros population dynamics reveal extinction mechanisms.

The extinction of the woolly rhinoceros (Coelodonta antiquitatis) at the onset of the Holocene remains an enigma, with conflicting evidence regarding its cause and spatiotemporal dynamics. This partly reflects challenges in determining demographic responses of late Quaternary megafauna to climatic and anthropogenic causal drivers with available genetic and paleontological techniques. Here, we show that elucidating mechanisms of ancient extinctions can benefit from a detailed understanding of fine-scale metapopulation dynamics, operating over many millennia. Using an abundant fossil record, ancient DNA, and high-resolution simulation models, we untangle the ecological mechanisms and causal drivers that are likely to have been integral in the decline and later extinction of the woolly rhinoceros. Our 52,000-y reconstruction of distribution-wide metapopulation dynamics supports a pathway to extinction that began long before the Holocene, when the combination of cooling temperatures and low but sustained hunting by humans trapped woolly rhinoceroses in suboptimal habitats along the southern edge of their range. Modeling indicates that this ecological trap intensified after the end of the last ice age, preventing colonization of newly formed suitable habitats, weakening stabilizing metapopulation processes, triggering the extinction of the woolly rhinoceros in the early Holocene. Our findings suggest that fragmentation and resultant metapopulation dynamics should be explicitly considered in explanations of late Quaternary megafauna extinctions, sending a clarion call to the fragility of the remaining large-bodied grazers restricted to disjunct fragments of poor-quality habitat due to anthropogenic environmental change.

Evolutionary ecology of dispersal in biodiverse spatially structured systems: what is old and what is new?

Dispersal is a well-recognized driver of ecological and evolutionary dynamics, and simultaneously an evolving trait. Dispersal evolution has traditionally been studied in single-species metapopulations so that it remains unclear how dispersal evolves in metacommunities and metafoodwebs, which are characterized by a multitude of species interactions. Since most natural systems are both species-rich and spatially structured, this knowledge gap should be bridged. Here, we discuss whether knowledge from dispersal evolutionary ecology established in single-species systems holds in metacommunities and metafoodwebs and we highlight generally valid and fundamental principles. Most biotic interactions form the backdrop to the ecological theatre for the evolutionary dispersal play because interactions mediate patterns of fitness expectations across space and time. While this allows for a simple transposition of certain known principles to a multispecies context, other drivers may require more complex transpositions, or might not be transferred. We discuss an important quantitative modulator of dispersal evolution-increased trait dimensionality of biodiverse meta-systems-and an additional driver: co-dispersal. We speculate that scale and selection pressure mismatches owing to co-dispersal, together with increased trait dimensionality, may lead to a slower and more 'diffuse' evolution in biodiverse meta-systems. Open questions and potential consequences in both ecological and evolutionary terms call for more investigation. This article is part of the theme issue 'Diversity-dependence of dispersal: interspecific interactions determine spatial dynamics'.

Stability analysis of a metapopulation model for the dynamics of malaria's spread including climatic factors.

Eradicating malaria remains a big challenge for computer scientists, mathematicians, epidemiologists, entomologists, physicians and many others. Their approaches range from recovering patients to eradicating the disease. However, collaboration, not always efficient between all these scientists, leads to the implementation of incomplete prototypes or to an under-exploitation of their results. Environmental and climatic factors are part of these elements that are usually omitted by computer scientists and mathematicians in the modelling of the malaria spread dynamic. Tropical countries, most affected by the disease are also mostly underdeveloped or developing countries, and therefore, statistical data are often lacking or difficult to access. Populations are constantly in motion over ecosystems with different environmental and climatic conditions, from a region to another. In this paper, we analyse the global asymptotic stability at the disease-free equilibrium of a metapopulation model including climatic factors.

Greenhouses represent an important evolutionary niche for Alternaria alternata.

Alternaria alternata is a ubiquitous soil-borne fungus capable of causing diseases in a variety of plants and occasionally in humans. While populations of A. alternata from infected plants have received significant attention, relatively little is known about its soil populations, including its population genetic structure and antifungal susceptibilities. In addition, over the last two decades, greenhouses have become increasingly important for food and ornamental plant production throughout the world, but how greenhouses might impact microbial pathogens such as A. alternata populations remains largely unknown. Different from open crop fields, greenhouses are often more intensively cultivated, with each greenhouse being a relatively small and isolated space where temperature and humidity are higher than surrounding environments. Previous studies have shown that greenhouse populations of two common molds, Aspergillus fumigatus and A. alternata, within a small community in southwestern China were variably differentiated. However, the relative contribution of physical separation among local greenhouses to the large-scale population structure remains unknown. Here, we isolated strains of A. alternata from seven greenhouses in Shijiazhuang, northeast China. Their genetic diversity and triazole susceptibilities were analyzed and compared with each other and with 242 isolates from nine greenhouses in Kunming, southwest China. Results showed that the isolation of greenhouses located <1 km from each other locally contributed similarly to the overall genetic variation as that between the two distant geographic regions. In addition, our results indicate that greenhouses could be significant sources of triazole resistance, with greenhouses often differing in their frequencies of resistant strains to different triazoles. IMPORTANCE: Greenhouses have become increasingly important for food production and food security. However, our understanding of how greenhouses may contribute to genetic variations in soil microbial populations is very limited. In this study, we obtained and analyzed soil populations of the cosmopolitan fungal pathogen Alternaria alternata in seven greenhouses in Shijiazhuang, northeast China. Our analyses revealed high proportions of isolates being resistant to agricultural triazole fungicides and medical triazole drugs, including cross-resistance to both groups of triazoles. In addition, we found that greenhouse populations of A. alternata located within a few kilometers showed similar levels of genetic differentiation as those separated by over 2,000 km between northeast and southwest China. Our study suggests that greenhouse populations of this and potentially other fungal pathogens represent an important ecological niche and an emerging threat to food security and human health.

Golden lion tamarin metapopulation dynamics five years after heavy losses to yellow fever.

The golden lion tamarin (GLT) is an Endangered primate endemic to Brazil's lowland Atlantic Forest. After centuries of deforestation and capture for the pet trade, only a few hundred individuals survived, all in isolated forest fragments 85 km from Rio de Janeiro city. Intensive conservation actions, including reintroduction of zoo-born tamarins, increased numbers to about 3700 in 2014. The most severe yellow fever epidemic/epizootic in Brazil in 80 years reduced two of the largest GLT populations by over 90%. Herein we report the results of a 2023 survey of GLTs designed to examine the dynamics of population recovery following yellow fever. Results indicate that populations hard hit by yellow fever are recovering due in part to immigration from adjacent forest fragments. No local extirpations were observed. About 4800 GLTs live in the survey area. This represents a 31% increase since the baseline survey completed in 2014. Two factors explain most of the increase: four large areas that had no GLTs or very low-density populations in 2014 are now at moderate density (three areas) or low density (one area), explaining 71% of overall increase since 2014. Increase in forest area within our survey area may explain up to 16% of the increase in GLT numbers since 2014. Results of computer simulations suggest that strengthening forest connectivity will facilitate metapopulation resilience in the face of mortality factors such as yellow fever.

Building pondscapes for amphibian metapopulations.

The success of ponds constructed to restore ecological infrastructure for pond-breeding amphibians and benefit aquatic biodiversity depends on where and how they are built. We studied effects of pond and landscape characteristics, including connectivity, on metapopulation dynamics of 12 amphibian species in Switzerland. To understand the determinants of long-term occupancy (here summarized as incidence), environmental effects on both colonization and persistence should be considered. We fitted dynamic occupancy models to 20 years of monitoring data on a pond construction program to quantify effects of pond and landscape characteristics and different connectivity metrics on colonization and persistence probabilities in constructed ponds. Connectivity to existing populations explained dynamics better than structural connectivity metrics, and simple metrics (distance to the nearest neighbor population, population density) were useful surrogates for dispersal kernel-weighted metrics commonly used in metapopulation theory. Population connectivity mediated the persistence of conservation target species in new ponds, suggesting source-sink dynamics in newly established populations. Population density captured this effect well and could be used by practitioners for site selection. Ponds created where there were 2-4 occupied ponds within a radius of ∼0.5 km had >3.5 times higher incidence of target species (median) than isolated ponds. Species had individual preferences regarding pond characteristics, but breeding sites with larger (≥100 m2) total water surface area, that temporarily dried, and that were in surroundings with maximally 50% forest benefitted multiple target species. Pond diversity will foster amphibian diversity at the landscape scale.

Construcción de estanques para meta poblaciones de anfibios Resumen El éxito de los estanques construidos para restaurar la infraestructura ecológica para los anfibios que allí se reproducen y para beneficiar la biodiversidad acuática depende de en dónde y cómo se construyen. Estudiamos los efectos de las características de los estanques y el paisaje, incluida la conectividad, sobre la dinámica de las meta poblaciones de 12 especies de anfibios en Suiza. Se deben considerar los efectos ambientales sobre la colonización y la persistencia para entender las determinantes de la ocupación a largo plazo (resumida aquí como incidencia). Ajustamos los modelos dinámicos de ocupación a datos de 20 años de monitoreo de un programa de construcción de estanques para cuantificar los efectos de las características del estanque y el paisaje y las diferentes medidas de conectividad para las probabilidades de colonización y persistencia en los estanques construidos. La conectividad con las poblaciones existentes explicó mejor la dinámica que las medidas de conectividad estructural, mientras que las medidas simples (distancia a la población vecina más cercana, densidad poblacional) fueron sustitutos útiles para las medidas de dispersión ponderadas al núcleo que se usan con frecuencia en la teoría de meta poblaciones. La conectividad poblacional medió la persistencia de las especies a conservar en los estanques nuevos, lo que sugiere que hay dinámicas fuente­sumidero en las poblaciones recién establecidas. La densidad poblacional capturó muy bien este efecto y podría usarse para que los practicantes seleccionen sitios. Los estanques construidos en un radio de ≈0.5 km de dos a cuatro estanques ocupados tuvieron >3.5 más incidencia de las especies a conservar (mediana) que los estanques aislados. Las especies tuvieron preferencias individuales con respecto a las características de los estanques, aunque los sitios de reproducción con una mayor superficie total de agua (≥100 m2), que se secaban temporalmente y que estaban rodeados con un máximo de 50% de bosque beneficiaron a muchas especies a conservar. Por esto, la diversidad de estanques promoverá la diversidad de anfibios a escala de paisaje.

Epidemicity indices and reproduction numbers from infectious disease data in connected human populations.

We focus on distinctive data-driven measures of the fate of ongoing epidemics. The relevance of our pursuit is suggested by recent results proving that the short-term temporal evolution of infection spread is described by an epidemicity index related to the maximum instantaneous growth rate of new infections, echoing concepts and tools developed to study the reactivity of ecosystems. Suitable epidemicity indices can showcase the dynamics of infections, together with commonly employed effective reproduction numbers, especially when the latter assume values less than 1. In particular, epidemicity evaluates the short-term reactivity to perturbations of a disease-free equilibrium. Here, we show that sufficient epidemicity thresholds to prevent transient epidemic outbreaks in a spatially connected setting can be estimated by generalizing existing analogues derived when spatial effects are neglected. We specifically account for the discrete nature, in both space and time, of surveillance data of the type typically employed to estimate effective reproduction numbers that formed the bulk of the communication of the state of the COVID-19 pandemic and its controls. After analyzing the effects of spatial heterogeneity on the considered prognostic indicators, we perform a short- and long-term analysis on the COVID-19 pandemic in Italy, showing that endemic conditions were maintained throughout the duration of our simulation despite stringent control measures. Our method provides a portfolio of prognostic indices that are essential to pinpoint the ongoing pandemic in both a qualitative and quantitative manner, as our results demonstrate. We base our conclusions on extended investigations of the effects of spatial fragmentation of communities of different sizes owing to connectivity by human mobility and contact scenarios, within real geographic contexts and synthetic setups designed to test our framework.

Landscape fragmentation overturns classical metapopulation thinking.

Habitat loss and isolation caused by landscape fragmentation represent a growing threat to global biodiversity. Existing theory suggests that the process will lead to a decline in metapopulation viability. However, since most metapopulation models are restricted to simple networks of discrete habitat patches, the effects of real landscape fragmentation, particularly in stochastic environments, are not well understood. To close this major gap in ecological theory, we developed a spatially explicit, individual-based model applicable to realistic landscape structures, bridging metapopulation ecology and landscape ecology. This model reproduced classical metapopulation dynamics under conventional model assumptions, but on fragmented landscapes, it uncovered general dynamics that are in stark contradiction to the prevailing views in the ecological and conservation literature. Notably, fragmentation can give rise to a series of dualities: a) positive and negative responses to environmental noise, b) relative slowdown and acceleration in density decline, and c) synchronization and desynchronization of local population dynamics. Furthermore, counter to common intuition, species that interact locally ("residents") were often more resilient to fragmentation than long-ranging "migrants." This set of findings signals a need to fundamentally reconsider our approach to ecosystem management in a noisy and fragmented world.

Enhancing seasonal influenza projections: A mechanistic metapopulation model for long-term scenario planning.

In temperate regions, annual preparation by public health officials for seasonal influenza requires early-season long-term projections. These projections are different from short-term (e.g., 1-4 weeks ahead) forecasts that are typically updated weekly. Whereas short-term forecasts estimate what "will" likely happen in the near term, the goal of scenario projections is to guide long-term decision-making using "what if" scenarios. We developed a mechanistic metapopulation model and used it to provide long-term influenza projections to the Flu Scenario Modeling Hub. The scenarios differed in their assumptions about influenza vaccine effectiveness and prior immunity. The parameters of the model were inferred from early season hospitalization data and then simulated forward in time until June 3, 2023. We submitted two rounds of projections (mid-November and early December), with the second round being a repeat of the first with three more weeks of data (and consequently different model parameters). In this study, we describe the model, its calibration, and projections targets. The scenario projection outcomes for two rounds are compared with each other at state and national level reported daily hospitalizations. We show that although Rounds 2 and 3 were identical in definition, the addition of three weeks of data produced an improvement to model fits. These changes resulted in earlier projections for peak incidence, lower projections for peak magnitude and relatively small changes to cumulative projections. In both rounds, all four scenarios presented conceivable outcomes, with some scenarios agreeing well with observations. We discuss how to interpret this agreement, emphasizing that this does not imply that one scenario or another provides the ground truth. Our model's performance suggests that its underlying assumptions provided plausible bounds for what could happen during an influenza season following two seasons of low circulation. We suggest that such projections would provide actionable estimates for public health officials.

Limits to species' range: the tension between local and global adaptation.

We know that heritable variation is abundant, and that selection causes all but the smallest populations to rapidly shift beyond their original trait distribution. So then, what limits the range of a species? There are physical constraints and also population genetic limits to the effectiveness of selection, ultimately set by population size. Global adaptation, where the same genotype is favoured over the whole range, is most efficient when based on a multitude of weakly selected alleles and is effective even when local demes are small, provided that there is some gene flow. In contrast, local adaptation is sensitive to gene flow and may require alleles with substantial effect. How can populations combine the advantages of large effective size with the ability to specialise into local niches? To what extent does reproductive isolation help resolve this tension? I address these questions using eco-evolutionary models of polygenic adaptation, contrasting discrete demes with continuousspace.

Integrating dynamical modeling and phylogeographic inference to characterize global influenza circulation.

Global seasonal influenza circulation involves a complex interplay between local (seasonality, demography, host immunity) and global factors (international mobility) shaping recurrent epidemic patterns. No studies so far have reconciled the two spatial levels, evaluating the coupling between national epidemics, considering heterogeneous coverage of epidemiological and virological data, integrating different data sources. We propose a novel combined approach based on a dynamical model of global influenza spread (GLEAM), integrating high-resolution demographic and mobility data, and a generalized linear model of phylogeographic diffusion that accounts for time-varying migration rates. Seasonal migration fluxes across global macro-regions simulated with GLEAM are tested as phylogeographic predictors to provide model validation and calibration based on genetic data. Seasonal fluxes obtained with a specific transmissibility peak time and recurrent travel outperformed the raw air-transportation predictor, previously considered as optimal indicator of global influenza migration. Influenza A subtypes supported autumn-winter reproductive number as high as 2.25 and an average immunity duration of 2 years. Similar dynamics were preferred by influenza B lineages, with a lower autumn-winter reproductive number. Comparing simulated epidemic profiles against FluNet data offered comparatively limited resolution power. The multiscale approach enables model selection yielding a novel computational framework for describing global influenza dynamics at different scales - local transmission and national epidemics vs. international coupling through mobility and imported cases. Our findings have important implications to improve preparedness against seasonal influenza epidemics. The approach can be generalized to other epidemic contexts, such as emerging disease outbreaks to improve the flexibility and predictive power of modeling.

A compartment and metapopulation model of Rocky Mountain spotted fever in southwestern United States and northern Mexico.

Rocky Mountain spotted fever (RMSF) is a fatal tick-borne zoonotic disease that has emerged as an epidemic in western North America since the turn of the 21st century. Along the US south-western border and across northern Mexico, the brown dog tick, Rhipicephalus sanguineus, is responsible for spreading the disease between dogs and humans. The widespread nature of the disease and the ongoing epidemics contrast with historically sporadic patterns of the disease. Because dogs are amplifying hosts for the Rickettsia rickettsii bacteria, transmission dynamics between dogs and ticks are critical for understanding the epidemic. In this paper, we developed a compartment metapopulation model and used it to explore the dynamics and drivers of RMSF in dogs and brown dog ticks in a theoretical region in western North America. We discovered that there is an extended lag-as much as two years-between introduction of the pathogen to a naïve population and epidemic-level transmission, suggesting that infected ticks could disseminate extensively before disease is detected. A single large city-size population of dogs was sufficient to maintain the disease over a decade and serve as a source for disease in surrounding smaller towns. This model is a novel tool that can be used to identify high risk areas and key intervention points for epidemic RMSF spread by brown dog ticks.