Host heterogeneity in susceptibility and disease dynamics: tests of a mathematical model

Caterpillar movement mediates spatially local interactions and determines the relationship between population density and contact

BACKGROUND

While interactions in nature are inherently local, ecological models often assume homogeneity across space, allowing for generalization across systems and greater mathematical tractability. Density-dependent disease models are a prominent example of models that assume homogeneous interactions, leading to the prediction that disease transmission will scale linearly with population density. In this study, we examined how the scale of larval butterfly movement interacts with the resource landscape to influence the relationship between larval contact and population density in the Baltimore checkerspot (Euphydryas phaeton). Our study was inspired by the recent discovery of a viral pathogen that is transmitted horizontally among Baltimore checkerspot larvae.

METHODS

We used multi-year larvae location data across six Baltimore checkerspot populations in the eastern U.S. to test whether larval nests are spatially clustered. We then integrated these spatial data with larval movement data in different resource contexts to investigate whether heterogeneity in spatially local interactions alters the assumed linear relationship between larval nest density and contact. We used Correlated Random Walk (CRW) models and field observations of larval movement behavior to construct Probability Distribution Functions (PDFs) of larval dispersal, and calculated the overlap in these PDFs to estimate conspecific contact within each population.

RESULTS

We found that all populations exhibited significant spatial clustering in their habitat use. Subsequent larval movement rates were influenced by encounters with host plants and larval age, and under many movement scenarios, the scale of predicted larval movement was not sufficient to allow for the "homogeneous mixing" assumed in density dependent disease models. Therefore, relationships between population density and larval contact were typically non-linear. We also found that observed use of available habitat patches led to significantly greater contact than would occur if habitat use were spatially random.

CONCLUSIONS

These findings strongly suggest that incorporating larval movement and spatial variation in larval interactions is critical to modeling disease outcomes in E. phaeton. Epidemiological models that assume a linear relationship between population density and larval contact have the potential to underestimate transmission rates, especially in small populations that are already vulnerable to extinction.

Prior exposure to pathogens augments host heterogeneity in susceptibility and has key epidemiological consequences

Pathogen epidemics are key threats to human and wildlife health. Across systems, host protection from pathogens following initial exposure is often incomplete, resulting in recurrent epidemics through partially-immune hosts. Variation in population-level protection has important consequences for epidemic dynamics, but whether acquired protection influences host heterogeneity in susceptibility and its epidemiological consequences remains unexplored. We experimentally investigated whether prior exposure (none, low-dose, or high-dose) to a bacterial pathogen alters host heterogeneity in susceptibility among songbirds. Hosts with no prior pathogen exposure had little variation in protection, but heterogeneity in susceptibility was significantly augmented by prior pathogen exposure, with the highest variability detected in hosts given high-dose prior exposure. An epidemiological model parameterized with experimental data found that heterogeneity in susceptibility from prior exposure more than halved epidemic sizes compared with a homogeneous population with identical mean protection. However, because infection-induced mortality was also greatly reduced in hosts with prior pathogen exposure, reductions in epidemic size were smaller than expected in hosts with prior exposure. These results highlight the importance of variable protection from prior exposure and/or vaccination in driving host heterogeneity and epidemiological dynamics.

Parasite transmission in size-structured populations

Host heterogeneity can affect parasite transmission, but determining underlying traits and incorporating them into transmission models remains challenging. Body size is easily measured and affects numerous ecological interactions, including transmission. In the snail-schistosome system, larger snails have a higher exposure to parasites but lower susceptibility to infection per parasite. We quantified the effect of size-based heterogeneity on population-level transmission by conducting transmission trials in differently size-structured snail populations and competing size-dependent transmission models. Populations with greater proportions of large snails had lower prevalence, and small snails were shielded from infection by co-occurring large conspecifics. Furthermore, a fully dependent transmission model that incorporated body size in both exposure and susceptibility outperformed other candidate models considered. Incorporating traits such as body size, which are affected by and directly affect host ecology, into transmission models could yield insights into natural dynamics and disease mitigation in many systems.

Is there a sicker sex? Dose relationships modify male-female differences in infection prevalence

Throughout the animal kingdom, there are striking differences in the propensity of one sex or the other to become infected. However, precisely when we should expect males or females to be the sicker sex remains unclear. A major barrier to answering this question is that very few studies have considered how the susceptibility of males and females changes across the full range of pathogen doses encountered in nature. Without quantifying this 'dose-susceptibility' relationship, we have likely underestimated the scope for sex differences to arise. Here, we use the Daphnia magnia-Pasteuria ramosa system to reveal that sex differences in susceptibility are entirely dose-dependent, with pathogens having a higher probability of successfully establishing an infection in mature males at low doses, but mature females at high doses. The scope for male-female differences to emerge is therefore much greater than previously appreciated-extending to sex differences in the upper limits to infection success, per-propagule infectivity risks and density-dependent pathogen behaviour. Applying this expanded scope across the animal kingdom will help us understand when and why a sicker sex emerges, and the implications for diseases in nature-where sex ratios, age structure and pathogen densities vary drastically.

Spatiotemporal-social association predicts immunological similarity in rewilded mice

Environmental influences on immune phenotypes are well-documented, but our understanding of which elements of the environment affect immune systems, and how, remains vague. Behaviors, including socializing with others, are central to an individual's interaction with its environment. We therefore tracked behavior of rewilded laboratory mice of three inbred strains in outdoor enclosures and examined contributions of behavior, including associations measured from spatiotemporal co-occurrences, to immune phenotypes. We found extensive variation in individual and social behavior among and within mouse strains upon rewilding. In addition, we found that the more associated two individuals were, the more similar their immune phenotypes were. Spatiotemporal association was particularly predictive of similar memory T and B cell profiles and was more influential than sibling relationships or shared infection status. These results highlight the importance of shared spatiotemporal activity patterns and/or social networks for immune phenotype and suggest potential immunological correlates of social life.

Quantifying individual-level heterogeneity in infectiousness and susceptibility through household studies

The spread of SARS-CoV-2, like that of many other pathogens, is governed by heterogeneity. "Superspreading," or "over-dispersion," is an important factor in transmission, yet it is hard to quantify. Estimates from contact tracing data are prone to potential biases due to the increased likelihood of detecting large clusters of cases, and may reflect variation in contact behavior more than biological heterogeneity. In contrast, the average number of secondary infections per contact is routinely estimated from household surveys, and these studies can minimize biases by testing all members of a household. However, the models used to analyze household transmission data typically assume that infectiousness and susceptibility are the same for all individuals or vary only with predetermined traits such as age. Here we develop and apply a combined forward simulation and inference method to quantify the degree of inter-individual variation in both infectiousness and susceptibility from observations of the distribution of infections in household surveys. First, analyzing simulated data, we show our method can reliably ascertain the presence, type, and amount of these heterogeneities given data from a sufficiently large sample of households. We then analyze a collection of household studies of COVID-19 from diverse settings around the world, and find strong evidence for large heterogeneity in both the infectiousness and susceptibility of individuals. Our results also provide a framework to improve the design of studies to evaluate household interventions in the presence of realistic heterogeneity between individuals.

House Sparrows Vary Seasonally in Their Ability to Transmit West Nile Virus

AbstractSeasonality in infectious disease prevalence is predominantly attributed to changes in exogenous risk factors. For vectored pathogens, high abundance, activity, and/or diversity of vectors can exacerbate disease risk for hosts. Conversely, many host defenses, particularly immune responses, are seasonally variable. Seasonality in host defenses has been attributed, in part, to the proximate (i.e., metabolic) and ultimate (i.e., reproductive fitness) costs of defense. In this study, our goal was to discern whether any seasonality is observable in how a common avian host, the house sparrow (Passer domesticus), copes with a common zoonotic arbovirus, the West Nile virus (WNV), when hosts are studied under controlled conditions. We hypothesized that if host biorhythms play a role in vector-borne disease seasonality, birds would be most vulnerable to WNV when breeding and/or molting (i.e., when other costly physiological activities are underway) and thus most transmissive of WNV at these times of year (unless birds died from infection). Overall, the results only partly supported our hypothesis. Birds were most transmissive of WNV in fall (after their molt is complete and when WNV is most prevalent in the environment), but WNV resistance, WNV tolerance, and WNV-dependent mortality did not vary among seasons. These results collectively imply that natural arboviral cycles could be partially underpinned by endogenous physiological changes in hosts. However, other disease systems warrant study, as this result could be specific to the nonnative and highly commensal nature of the house sparrow or a consequence of the relative recency of the arrival of WNV to the United States.

Unhealthy herds and the predator–spreader: Understanding when predation increases disease incidence and prevalence

Disease ecologists now recognize the limitation behind examining host–parasite interactions in isolation: community members—especially predators—dramatically affect host–parasite dynamics. Although the initial paradigm was that predation should reduce disease in prey populations (“healthy herds hypothesis”), researchers have realized that predators sometimes increase disease in their prey. These “predator–spreaders” are now recognized as critical to disease dynamics, but empirical research on the topic remains fragmented. In a narrow sense, a “predator–spreader” would be defined as a predator that mechanically spreads parasites via feeding. However, predators affect their prey and, subsequently, disease transmission in many other ways such as altering prey population structure, behavior, and physiology. We review the existing evidence for these mechanisms and provide heuristics that incorporate features of the host, predator, parasite, and environment to understand whether or not a predator is likely to be a predator–spreader. We also provide guidance for targeted study of each mechanism and quantifying the effects of predators on parasitism in a way that yields more general insights into the factors that promote predator spreading. We aim to offer a better understanding of this important and underappreciated interaction and a path toward being able to predict how changes in predation will influence parasite dynamics.

Social association predicts immunological similarity in rewilded mice

Environmental influences on immune phenotypes are well-documented, but our understanding of which elements of the environment affect immune systems, and how, remains vague. Behaviors, including socializing with others, are central to an individual's interaction with its environment. We tracked behavior of rewilded laboratory mice of three inbred strains in outdoor enclosures and examined contributions of behavior, including social associations, to immune phenotypes. We found that the more associated two individuals were, the more similar their immune phenotypes were. Social association was particularly predictive of similar memory T and B cell profiles and was more influential than sibling relationships or worm infection status. These results highlight the importance of social networks for immune phenotype and reveal important immunological correlates of social life.

Meta-Analysis of the Effects of Insect Pathogens: Implications for Plant Reproduction

Despite extensive work on both insect disease and plant reproduction, there is little research on the intersection of the two. Insect-infecting pathogens could disrupt the pollination process by affecting pollinator population density or traits. Pathogens may also infect insect herbivores and change herbivory, potentially altering resource allocation to plant reproduction. We conducted a meta-analysis to (1) summarize the literature on the effects of pathogens on insect pollinators and herbivores and (2) quantify the extent to which pathogens affect insect traits, with potential repercussions for plant reproduction. We found 39 articles that fit our criteria for inclusion, extracting 218 measures of insect traits for 21 different insect species exposed to 25 different pathogens. We detected a negative effect of pathogen exposure on insect traits, which varied by host function: pathogens had a significant negative effect on insects that were herbivores or carried multiple functions but not on insects that solely functioned as pollinators. Particular pathogen types were heavily studied in certain insect orders, with 7 of 11 viral pathogen studies conducted in Lepidoptera and 5 of 9 fungal pathogen studies conducted in Hymenoptera. Our results suggest that most studies have focused on a small set of host-pathogen pairs. To understand the implications for plant reproduction, future work is needed to directly measure the effects of pathogens on pollinator effectiveness.

Viral transmission and infection prevalence in a cannibalistic host-pathogen system

Cannibalism, while prevalent in the natural world, is often viewed as detrimental to a cannibal's health, especially when they consume pathogen-infected conspecifics. The argument stems from the idea that cannibalizing infected individuals increases the chance of coming into contact with a pathogen and subsequently becoming infected. Using an insect pest, the fall armyworm (Spodoptera frugiperda), that readily cannibalizes at the larval stage and its lethal pathogen, we experimentally examined how cannibalism affects viral transmission at both an individual and population level. Prior to death, the pathogen in the system stops the larval host from growing, resulting in infected individuals being smaller than healthy individuals. This leads to size-structured cannibalism of infected individuals with the larger healthy larvae consuming the smaller infected larvae, which is commonly observed. At the individual level, we show that the probability of cannibalism is relatively high for both infected and uninfected individuals especially when the cannibal is larger than the victim. However, the probability of the cannibal becoming infected given that a pathogen-infected individual has been cannibalized is relatively low. On a population level, when cannibalism is allowed to occur transmission rates decline. Additionally, by cannibalizing infected larvae, cannibals lower the infection risk for non-cannibals. Thus, cannibalism can decrease infection prevalence and, therefore, may not be as deleterious as once thought. Under certain circumstances, cannibalizing infected individuals, from the uninfected host's perspective, may even be advantageous, as one obtains a meal and decreases competition for resources with little chance of becoming infected.

Quantifying individual-level heterogeneity in infectiousness and susceptibility through household studies

The spread of SARS-CoV-2, like that of many other pathogens, is governed by heterogeneity. "Superspreading," or "over-dispersion," is an important factor in transmission, yet it is hard to quantify. Estimates from contact tracing data are prone to potential biases due to the increased likelihood of detecting large clusters of cases, and may reflect variation in contact behavior more than biological heterogeneity. In contrast, the average number of secondary infections per contact is routinely estimated from household surveys, and these studies can minimize biases by testing all members of a household. However, the models used to analyze household transmission data typically assume that infectiousness and susceptibility are the same for all individuals or vary only with predetermined traits such as age. Here we develop and apply a combined forward simulation and inference method to quantify the degree of inter-individual variation in both infectiousness and susceptibility from observations of the distribution of infections in household surveys. First, analyzing simulated data, we show our method can reliably ascertain the presence, type, and amount of these heterogeneities with data from a sufficiently large sample of households. We then analyze a collection of household studies of COVID-19 from diverse settings around the world, and find strong evidence for large heterogeneity in both the infectiousness and susceptibility of individuals. Our results also provide a framework to improve the design of studies to evaluate household interventions in the presence of realistic heterogeneity between individuals.

High prevalence does not necessarily equal maintenance species: Avoiding biased claims of disease reservoirs when using surveillance data

1. Many pathogens of public health and conservation concern persist in host communities. Identifying candidate maintenance and reservoir species is therefore a central component of disease management. The term maintenance species implies that if all species but the putative maintenance species were removed, then the pathogen would still persist. In the absence of field manipulations, this statement inherently requires a causal or mechanistic model to assess. 2. However, we lack a systematic understanding of i) how often conclusions are made about maintenance and reservoir species without reference to mechanistic models ii) what types of biases may be associated with these conclusions and iii) how explicitly invoking causal or mechanistic modeling can help ameliorate these biases. Filling these knowledge gaps is critical for robust inference on pathogen persistence and spillover in multihost parasite systems, with clear implications for human and wildlife health. 3. To address these gaps, we performed a literature review on the evidence previous studies have used to make claims regarding maintenance or reservoir species. We then developed a multihost-parasite model to explore and demonstrate common biases that could arise when inferring maintenance potential from observational prevalence data. Finally, we developed new theory to show how model-driven inference of maintenance species can minimize and eliminate emergent biases. 4. In our review, we found that 83% of studies used some form of observational prevalence data to draw conclusions on maintenance potential and only 6% of these studies combined observational data with mechanistic modeling. Using our model, we demonstrate how the community, spatial, and temporal context of observational data can lead to substantial biases in inferences of maintenance potential. Importantly, our theory identifies that model-driven inference of maintenance species elucidates other streams of observational data that can be leveraged to correct these biases. 5. Model-driven inference is an essential, yet underused, component of multidisciplinary studies that make inference on host reservoir and maintenance species. Better integration of wildlife disease surveillance and mechanistic models is necessary to improve the robustness and reproducibility of our conclusions regarding maintenance and reservoir species.

Individual variation in susceptibility or exposure to SARS-CoV-2 lowers the herd immunity threshold

Individual variation in susceptibility and exposure is subject to selection by natural infection, accelerating the acquisition of immunity, and reducing herd immunity thresholds and epidemic final sizes. This is a manifestation of a wider population phenomenon known as "frailty variation". Despite theoretical understanding, public health policies continue to be guided by mathematical models that leave out considerable variation and as a result inflate projected disease burdens and overestimate the impact of interventions. Here we focus on trajectories of the coronavirus disease (COVID-19) pandemic in England and Scotland until November 2021. We fit models to series of daily deaths and infer relevant epidemiological parameters, including coefficients of variation and effects of non-pharmaceutical interventions which we find in agreement with independent empirical estimates based on contact surveys. Our estimates are robust to whether the analysed data series encompass one or two pandemic waves and enable projections compatible with subsequent dynamics. We conclude that vaccination programmes may have contributed modestly to the acquisition of herd immunity in populations with high levels of pre-existing naturally acquired immunity, while being crucial to protect vulnerable individuals from severe outcomes as the virus becomes endemic.

A model for leveraging animal movement to understand spatio-temporal disease dynamics

The ongoing explosion of fine-resolution movement data in animal systems provides a unique opportunity to empirically quantify spatial, temporal and individual variation in transmission risk and improve our ability to forecast disease outbreaks. However, we lack a generalizable model that can leverage movement data to quantify transmission risk and how it affects pathogen invasion and persistence on heterogeneous landscapes. We developed a flexible model 'Movement-driven modelling of spatio-temporal infection risk' (MoveSTIR) that leverages diverse data on animal movement to derive metrics of direct and indirect contact by decomposing transmission into constituent processes of contact formation and duration and pathogen deposition and acquisition. We use MoveSTIR to demonstrate that ignoring fine-scale animal movements on actual landscapes can mis-characterize transmission risk and epidemiological dynamics. MoveSTIR unifies previous work on epidemiological contact networks and can address applied and theoretical questions at the nexus of movement and disease ecology.

Individual variation in susceptibility or exposure to SARS-CoV-2 lowers the herd immunity threshold

Individual variation in susceptibility and exposure is subject to selection by natural infection, accelerating the acquisition of immunity, and reducing herd immunity thresholds and epidemic final sizes. This is a manifestation of a wider population phenomenon known as "frailty variation". Despite theoretical understanding, public health policies continue to be guided by mathematical models that leave out considerable variation and as a result inflate projected disease burdens and overestimate the impact of interventions. Here we focus on trajectories of the coronavirus disease (COVID-19) pandemic in England and Scotland until November 2021. We fit models to series of daily deaths and infer relevant epidemiological parameters, including coefficients of variation and effects of non-pharmaceutical interventions which we find in agreement with independent empirical estimates based on contact surveys. Our estimates are robust to whether the analysed data series encompass one or two pandemic waves and enable projections compatible with subsequent dynamics. We conclude that vaccination programmes may have contributed modestly to the acquisition of herd immunity in populations with high levels of pre-existing naturally acquired immunity, while being critical to protect vulnerable individuals from severe outcomes as the virus becomes endemic.

Plant neighbours can make or break the disease transmission chain of a fungal root pathogen

Biodiversity can reduce or increase disease transmission. These divergent effects suggest that community composition rather than diversity per se determines disease transmission. In natural plant communities, little is known about the functional roles of neighbouring plant species in belowground disease transmission. Here, we experimentally investigated disease transmission of a fungal root pathogen (Rhizoctonia solani) in two focal plant species in combinations with four neighbour species of two ages. We developed stochastic models to test the relative importance of two transmission-modifying mechanisms: (1) infected hosts serve as nutrient supply to increase hyphal growth, so that successful disease transmission is self-reinforcing; and (2) plant resistance increases during plant development. Neighbouring plants either reduced or increased disease transmission in the focal plants. These effects depended on neighbour age, but could not be explained by a simple dichotomy between hosts and nonhost neighbours. Model selection revealed that both transmission-modifying mechanisms are relevant and that focal host-neighbour interactions changed which mechanisms steered disease transmission rate. Our work shows that neighbour-induced shifts in the importance of these mechanisms across root networks either make or break disease transmission chains. Understanding how diversity affects disease transmission thus requires integrating interactions between focal and neighbour species and their pathogens.

Dilution effects in disease ecology

For decades, people have reduced the transmission of pathogens by adding low‐quality hosts to managed environments like agricultural fields. More recently, there has been interest in whether similar ‘dilution effects’ occur in natural disease systems, and whether these effects are eroded as diversity declines. For some pathogens of plants, humans and other animals, the highest‐quality hosts persist when diversity is lost, so that high‐quality hosts dominate low‐diversity communities, resulting in greater pathogen transmission. Meta‐analyses reveal that these natural dilution effects are common. However, studying them remains challenging due to limitations on the ability of researchers to manipulate many disease systems experimentally, difficulties of acquiring data on host quality and confusion about what should and should not be considered a dilution effect. Because dilution effects are widely used in managed disease systems and have been documented in a variety of natural disease systems, their existence should not be considered controversial. Important questions remain about how frequently they occur and under what conditions to expect them. There is also ongoing confusion about their relationships to both pathogen spillover and general biogeographical correlations between diversity and disease, which has resulted in an inconsistent and confusing literature. Progress will require rigorous and creative research.

Heterogeneity in susceptibility dictates the order of epidemic models

The fundamental models of epidemiology describe the progression of an infectious disease through a population using compartmentalized differential equations, but typically do not incorporate population-level heterogeneity in infection susceptibility. Here we combine a generalized analytical framework of contagion with computational models of epidemic dynamics to show that variation strongly influences the rate of infection, while the infection process simultaneously sculpts the susceptibility distribution. These joint dynamics influence the force of infection and are, in turn, influenced by the shape of the initial variability. We find that certain susceptibility distributions (the exponential and the gamma) are unchanged through the course of the outbreak, and lead naturally to power-law behavior in the force of infection; other distributions are often sculpted towards these "eigen-distributions" through the process of contagion. The power-law behavior fundamentally alters predictions of the long-term infection rate, and suggests that first-order epidemic models that are parameterized in the exponential-like phase may systematically and significantly over-estimate the final severity of the outbreak. In summary, our study suggests the need to examine the shape of susceptibility in natural populations as part of efforts to improve prediction models and to prioritize interventions that leverage heterogeneity to mitigate against spread.

Host genotype and genetic diversity shape the evolution of a novel bacterial infection

Pathogens continue to emerge from increased contact with novel host species. Whilst these hosts can represent distinct environments for pathogens, the impacts of host genetic background on how a pathogen evolves post-emergence are unclear. In a novel interaction, we experimentally evolved a pathogen (Staphylococcus aureus) in populations of wild nematodes (Caenorhabditis elegans) to test whether host genotype and genetic diversity affect pathogen evolution. After ten rounds of selection, we found that pathogen virulence evolved to vary across host genotypes, with differences in host metal ion acquisition detected as a possible driver of increased host exploitation. Diverse host populations selected for the highest levels of pathogen virulence, but infectivity was constrained, unlike in host monocultures. We hypothesise that population heterogeneity might pool together individuals that contribute disproportionately to the spread of infection or to enhanced virulence. The genomes of evolved populations were sequenced, and it was revealed that pathogens selected in distantly-related host genotypes diverged more than those in closely-related host genotypes. S. aureus nevertheless maintained a broad host range. Our study provides unique empirical insight into the evolutionary dynamics that could occur in other novel infections of wildlife and humans.

Evolutionary rescue in host-pathogen systems

Natural populations encounter a variety of threats that can increase their risk of extinction. Populations can avoid extinction through evolutionary rescue (ER), which occurs when an adaptive, genetic response to selection allows a population to recover from an environmental change that would otherwise cause extinction. While the traditional framework for ER was developed with abiotic risk factors in mind, ER may also occur in response to a biotic source of demographic change, such as the introduction of a novel pathogen. We first describe how ER in response to a pathogen differs from the traditional ER framework; density-dependent transmission, pathogen evolution, and pathogen extinction can change the strength of selection imposed by a pathogen and make host population persistence more likely. We also discuss several variables that affect traditional ER (abundance, genetic diversity, population connectivity, and community composition) that also directly affect disease risk resulting in diverse outcomes for ER in host-pathogen systems. Thus, generalizations developed in studies of traditional ER may not be relevant for ER in response to the introduction of a pathogen. Incorporating pathogens into the framework of ER will lead to a better understanding of how and when populations can avoid extinction in response to novel pathogens.

Host traits, identity, and ecological conditions predict consistent flea abundance and prevalence on free-living California ground squirrels

Understanding why some individuals are more prone to carry parasites and spread diseases than others is a key question in biology. Although epidemiologists and disease ecologists increasingly recognize that individuals of the same species can vary tremendously in their relative contributions to the emergence of diseases, very few empirical studies systematically assess consistent individual differences in parasite loads within populations over time. Two species of fleas (Oropsylla montana and Hoplopsyllus anomalous) and their hosts, California ground squirrels (Otospermophilus beecheyi), form a major complex for amplifying epizootic plague in the western United States. Understanding its biology is primarily of major ecological importance and is also relevant to public health. Here, we capitalize on a long-term data set to explain flea incidence on California ground squirrels at Briones Regional Park in Contra Costa County, USA. In a 7 year study, we detected 42,358 fleas from 2,759 live trapping events involving 803 unique squirrels from two free-living populations that differed in the amount of human disturbance in those areas. In general, fleas were most abundant and prevalent on adult males, on heavy squirrels, and at the pristine site, but flea distributions varied among years, with seasonal conditions (e.g., temperature, rainfall, humidity), temporally within summers, and between flea species. Although on-host abundances of the two flea species were positively correlated, each flea species occupied a distinctive ecological niche. The common flea (O. montana) occurred primarily on adults in cool, moist conditions in early summer whereas the rare flea (H. anomalous) was mainly on juveniles in hot, dry conditions in late summer. Beyond this, we uncovered significantly repeatable and persistent effects of host individual identity on flea loads, finding consistent individual differences among hosts in all parasite measures. Taken together, we reveal multiple determinants of parasites on free-living mammals, including the underappreciated potential for host heterogeneity - within populations - to structure the emergence of zoonotic diseases such as bubonic plague.

Uncovering drivers of dose-dependence and individual variation in malaria infection outcomes

To understand why some hosts get sicker than others from the same type of infection, it is essential to explain how key processes, such as host responses to infection and parasite growth, are influenced by various biotic and abiotic factors. In many disease systems, the initial infection dose impacts host morbidity and mortality. To explore drivers of dose-dependence and individual variation in infection outcomes, we devised a mathematical model of malaria infection that allowed host and parasite traits to be linear functions (reaction norms) of the initial dose. We fitted the model, using a hierarchical Bayesian approach, to experimental time-series data of acute Plasmodium chabaudi infection across doses spanning seven orders of magnitude. We found evidence for both dose-dependent facilitation and debilitation of host responses. Most importantly, increasing dose reduced the strength of activation of indiscriminate host clearance of red blood cells while increasing the half-life of that response, leading to the maximal response at an intermediate dose. We also explored the causes of diverse infection outcomes across replicate mice receiving the same dose. Besides random noise in the injected dose, we found variation in peak parasite load was due to unobserved individual variation in host responses to clear infected cells. Individual variation in anaemia was likely driven by random variation in parasite burst size, which is linked to the rate of host cells lost to malaria infection. General host vigour in the absence of infection was also correlated with host health during malaria infection. Our work demonstrates that the reaction norm approach provides a useful quantitative framework for examining the impact of a continuous external factor on within-host infection processes.

Metacercariae of Austrodiplostomum compactum (Trematoda, Diplostomidae) in non-native fish species in Brazil: a possible explanation for the high rate of parasitic infection

Metacercariae of Diplostomidae are widely distributed in America and may cause diplostomiasis, an ocular disease in fishes. The aim of this study is to report the occurrence of metacercariae of Austrodiplostomum compactum in Plagioscion squamosissimus (non-native fish species) from Nova Avanhandava Reservoir, Tietê River, Brazil and an explanation for the high infection rates with this parasite in the Paraná River Basin is proposed. Eyes of 70 hosts were examined, the metacercariae were preserved and identified. The prevalence (P), mean intensity of infection (MII) ± standard deviation, mean abundance (MA) ± standard deviation, were calculated and a bibliographic review was performed. There was no difference in parasitism between male and female hosts. The values of P = 80%, MII = 21.55 ± 3.25 and MA = 17.24 ± 2.91 were high, as in most studies in areas where P. squamosissimus were introduced, while these values were low in areas of natural occurrence. This may be explained by the genetic susceptibility of the host to the parasite. The entire population of P. squamosissimus from the Upper Paraná has been founded by a few specimens, resulting in very low genetic variability. Consequently, the population may be highly susceptible to A. compactum.

Dynamics of a predator-prey model with generalized Holling type functional response and mutual interference

Mutual interference and prey refuge are important drivers of predator-prey dynamics. The "exponent" or degree of mutual interference has been under much debate in theoretical ecology. In the present work, we investigate the interplay of the mutual interference exponent, and prey refuge, on the behavior of a predator-prey model with a generalized Holling type functional response - considering in particular the "non-smooth" case. This model can also be used to model an infectious disease where a susceptible population, moves to an infected class, after being infected by the disease. We investigate dynamical properties of the system and derive conditions for the occurrence of saddle-node, transcritical and Hopf-bifurcations. A sufficient condition for finite time extinction of the prey species has also been derived. In addition, we investigate the effect of a prey refuge on the population dynamics of the model and derive conditions such that the prey refuge would yield persistence of the population. We provide additional verification of our analytical results via numerical simulations. Our findings are in accordance with classical experimental results in ecology (Gause, 1934), that show that extinction of predator and prey populations is possible in a finite time period - but that bringing in refuge can effectively yield persistence.

Intraguild predation decreases predator fitness with potentially varying effects on pathogen transmission in a herbivore host

Predators and pathogens often regulate the population dynamics of their prey or hosts. When species interact with both their predators and their pathogens, understanding each interaction in isolation may not capture the system's dynamics. For instance, predators can influence pathogen transmission via consumptive effects, such as feeding on infected prey, or non-consumptive effects, such as changing the prey's susceptibility to infection. A prey species' infection status can, in turn, influence predator's choice of prey and have negative fitness consequences for the predator. To test how intraguild predation (IGP), when predator and pathogen share the same prey/host, affects pathogen transmission, predator preference, and predator fitness, we conducted a series of experiments using a crop pest (Pseudoplusia includens), a generalist predator (Podisus maculiventris), and a generalist pathogen (Autographa californica multicapsid nuclear polyhedrovirus, AcMNPV). Using a field experiment, we quantified the effects of consumptive and non-consumptive predators on pathogen transmission. We found that a number of models provided similar fits to the data. These models included null models showing no effects of predation and models that included a predation effect. We also found that predators consumed infected prey more often when choosing between live infected or live healthy prey. Infected prey also reduced predator fitness. Developmental times of predators fed infected prey increased by 20% and longevity decreased by 45%, compared with those that consumed an equivalent number of non-infected prey. While this research shows an effect of the pathogen on intraguild predator fitness, we found no support that predators affected pathogen transmission.

A note on species richness and the variance of epidemic severity

The commonly observed negative correlation between the number of species in an ecological community and disease risk, typically referred to as "the dilution effect", has received a substantial amount of attention over the past decade. Attempts to test this relationship experimentally have revealed that, in addition to the mean disease risk decreasing with species number, so too does the variance of disease risk. This is referred to as the "variance reduction effect", and has received relatively little attention in the disease-diversity literature. Here, we set out to clarify and quantify some of these relationships in an idealized model of a randomly assembled multi-species community undergoing an epidemic. We specifically investigate the variance of the community disease reproductive ratio, a multi-species extension of the basic reproductive ratio [Formula: see text], for a family of random-parameter community SIR models, and show how the variance of community [Formula: see text] varies depending on whether transmission is density or frequency-dependent. We finally outline areas of further research on how changes in variance affect transmission dynamics in other systems.

Inter- and intraspecific variation of spider mite susceptibility to fungal infections: Implications for the long-term success of biological control

Spider mites are severe pests of several annual and perennial crops worldwide, often causing important economic damages. As rapid evolution of pesticide resistance in this group hampers the efficiency of chemical control, alternative control strategies, such as the use of entomopathogenic fungi, are being developed. However, while several studies have focused on the evaluation of the control potential of different fungal species and/or isolates as well as their compatibility with other control methods (e.g., predators or chemical pesticides), knowledge on the extent of inter- and intraspecific variation in spider mite susceptibility to fungal infection is as yet incipient. Here, we measured the mortality induced by two generalist fungi, Beauveria bassiana and Metarhizium brunneum, in 12 spider mite populations belonging to different Tetranychus species: T. evansi, T. ludeni, and T. urticae (green and red form), within a full factorial experiment. We found that spider mite species differed in their susceptibility to infection by both fungal species. Moreover, we also found important intraspecific variation for this trait. These results draw caution on the development of single strains as biocontrol agents. Indeed, the high level of intraspecific variation suggests that (a) the one-size-fits-all strategy may fail to control spider mite populations and (b) hosts resistance to infection may evolve at a rapid pace. Finally, we propose future directions to better understand this system and improve the long-term success of spider mite control strategies based on entomopathogenic fungi.

An Empirical Test of the Role of Small-Scale Transmission in Large-Scale Disease Dynamics

A key assumption of epidemiological models is that population-scale disease spread is driven by close contact between hosts and pathogens. At larger scales, however, mechanisms such as spatial structure in host and pathogen populations and environmental heterogeneity could alter disease spread. The assumption that small-scale transmission mechanisms are sufficient to explain large-scale infection rates, however, is rarely tested. Here, we provide a rigorous test using an insect-baculovirus system. We fit a mathematical model to data from forest-wide epizootics while constraining the model parameters with data from branch-scale experiments, a difference in spatial scale of four orders of magnitude. This experimentally constrained model fits the epizootic data well, supporting the role of small-scale transmission, but variability is high. We then compare this model's performance to an unconstrained model that ignores the experimental data, which serves as a proxy for models with additional mechanisms. The unconstrained model has a superior fit, revealing a higher transmission rate across forests compared with branch-scale estimates. Our study suggests that small-scale transmission is insufficient to explain baculovirus epizootics. Further research is needed to identify the mechanisms that contribute to disease spread across large spatial scales, and synthesizing models and multiscale data are key to understanding these dynamics.

Modelling the epidemiology of residual Plasmodium vivax malaria in a heterogeneous host population: A case study in the Amazon Basin

The overall malaria burden in the Americas has decreased dramatically over the past two decades, but residual transmission pockets persist across the Amazon Basin, where Plasmodium vivax is the predominant infecting species. Current elimination efforts require a better quantitative understanding of malaria transmission dynamics for planning, monitoring, and evaluating interventions at the community level. This can be achieved with mathematical models that properly account for risk heterogeneity in communities approaching elimination, where few individuals disproportionately contribute to overall malaria prevalence, morbidity, and onwards transmission. Here we analyse demographic information combined with routinely collected malaria morbidity data from the town of Mâncio Lima, the main urban transmission hotspot of Brazil. We estimate the proportion of high-risk subjects in the host population by fitting compartmental susceptible-infected-susceptible (SIS) transmission models simultaneously to age-stratified vivax malaria incidence densities and the frequency distribution of P. vivax malaria attacks experienced by each individual over 12 months. Simulations with the best-fitting SIS model indicate that 20% of the hosts contribute 86% of the overall vivax malaria burden. Despite the low overall force of infection typically found in the Amazon, about one order of magnitude lower than that in rural Africa, high-risk individuals gradually develop clinical immunity following repeated infections and eventually constitute a substantial infectious reservoir comprised of asymptomatic parasite carriers that is overlooked by routine surveillance but likely fuels onwards malaria transmission. High-risk individuals therefore represent a priority target for more intensive and effective interventions that may not be readily delivered to the entire community.

Metacommunity theory for transmission of heritable symbionts within insect communities

Microbial organisms are ubiquitous in nature and often form communities closely associated with their host, referred to as the microbiome. The microbiome has strong influence on species interactions, but microbiome studies rarely take interactions between hosts into account, and network interaction studies rarely consider microbiomes. Here, we propose to use metacommunity theory as a framework to unify research on microbiomes and host communities by considering host insects and their microbes as discretely defined "communities of communities" linked by dispersal (transmission) through biotic interactions. We provide an overview of the effects of heritable symbiotic bacteria on their insect hosts and how those effects subsequently influence host interactions, thereby altering the host community. We suggest multiple scenarios for integrating the microbiome into metacommunity ecology and demonstrate ways in which to employ and parameterize models of symbiont transmission to quantitatively assess metacommunity processes in host-associated microbial systems. Successfully incorporating microbiota into community-level studies is a crucial step for understanding the importance of the microbiome to host species and their interactions.

Understanding the Evolutionary Ecology of host--pathogen Interactions Provides Insights into the Outcomes of Insect Pest Biocontrol

The use of viral pathogens to control thepopulation size of pest insects has produced both successful and unsuccessful outcomes. Here, we investigate whether those biocontrol successes and failures can be explained by key ecological and evolutionary processes between hosts and pathogens. Specifically, we examine how heterogeneity inpathogen transmission, ecological and evolutionary tradeoffs, andpathogen diversity affect insect population density and thus successful control. Wefirst review theexisting literature and then use numerical simulations of mathematical models to further explore these processes. Our results show that thecontrol of insect densities using viruses depends strongly on theheterogeneity of virus transmission among insects. Overall, increased heterogeneity of transmission reduces theeffect of viruses on insect densities and increases thelong-term stability of insect populations. Lower equilibrium insect densities occur when transmission is heritable and when there is atradeoff between mean transmission and insect fecundity compared to when theheterogeneity of transmission arises from non-genetic sources. Thus, theheterogeneity of transmission is akey parameter that regulates thelong-term population dynamics of insects and their pathogens. Wealso show that both heterogeneity of transmission and life-history tradeoffs modulate characteristics of population dynamics such as thefrequency and intensity of ``boom--bust" population cycles. Furthermore, we show that because of life-history tradeoffs affecting thetransmission rate, theuse of multiple pathogen strains is more effective than theuse of asingle strain to control insect densities only when thepathogen strains differ considerably intheir transmission characteristics. By quantifying theeffects of ecology and evolution on population densities, we are able to offer recommendations to assess thelong-term effects of classical biocontrol.

Modelling evolution of virulence in populations with a distributed parasite load

Modelling evolution of virulence in host-parasite systems is an actively developing area of research with ever-growing literature. However, most of the existing studies overlook the fact that individuals within an infected population may have a variable infection load, i.e. infected populations are naturally structured with respect to the parasite burden. Empirical data suggests that the mortality and infectiousness of individuals can strongly depend on their infection load; moreover, the shape of distribution of infection load may vary on ecological and evolutionary time scales. Here we show that distributed infection load may have important consequences for the eventual evolution of virulence as compared to a similar model without structuring. Mathematically, we consider an SI model, where the dynamics of the infected subpopulation is described by a von Förster-type equation, in which the infection load plays the role of age. We implement the adaptive dynamics framework to predict evolutionary outcomes in this model. We demonstrate that for simple trade-off functions between virulence, disease transmission and parasite growth rates, multiple evolutionary attractors are possible. Interestingly, unlike in the case of unstructured models, achieving an evolutionary stable strategy becomes possible even for a variation of a single ecological parameter (the parasite growth rate) and keeping the other parameters constant. We conclude that evolution in disease-structured populations is strongly mediated by alterations in the overall shape of the parasite load distribution.

Development and characterization of white spot disease linked microsatellite DNA markers in Penaeus monodon, and their application to determine the population diversity, cluster and structure

Pathogens that are introduced suddenly to natural populations can potentially cause quick changes to the genetics and diversity of the host. In the past three decades, white spot syndrome virus (WSSV) has caused damaging epizootics in Penaeus monodon populations. In this study, we developed WSSV resistance- or susceptibility-linked microsatellite DNA markers, and their effectiveness was validated experimentally. WSSV-resistant marker linked retroelements and genes that may have an important role in WSSV-resistance phenomena were partially identified. Allelic data of 1,694 samples from nine distinct geographic locations in India were revealed that populations from Digha and Kochi were highly dispersed, and also showed higher genetic diversity, higher population diversity, and lower prevalence of disease resistance. A very high level of gene flow was observed within all populations and a very high level of genetic variation was present within populations. Two genetically admixture population clusters were estimated in nature. WSSV-resistance has a significant link with genetic diversity, population cluster and population diversity. Microsatellite marker analysis characterized genetic divergence, diversity and structure among wild populations.

The effects of individual nonheritable variation on fitness estimation and coexistence

Demographic theory and data have emphasized that nonheritable variation in individual frailty enables selection within cohorts, affecting the dynamics of a population while being invisible to its evolution. Here, we include the component of individual variation in longevity or viability which is nonheritable in simple bacterial growth models and explore its ecological and evolutionary impacts. First, we find that this variation produces consistent trends in longevity differences between bacterial genotypes when measured across stress gradients. Given that direct measurements of longevity are inevitably biased due to the presence of this variation and ongoing selection, we propose the use of the trend itself for obtaining more exact inferences of genotypic fitness. Second, we show how species or strain coexistence can be enabled by nonheritable variation in longevity or viability. These general conclusions are likely to extend beyond bacterial systems.

Method for serial passage of infectious hematopoietic necrosis virus (IHNV) in rainbow trout

Transmission is a fundamental component of pathogen fitness. A better understanding of pathogen transmission can greatly improve disease management. In particular, controlled studies of multiple rounds of natural transmission (i.e. serial passage) can provide powerful epidemiological and evolutionary inferences. However, such studies are possible in only a few systems because of the challenges in successfully initiating and maintaining transmission in the laboratory. Here we developed an efficient and reproducible cohabitation method for conducting controlled experiments investigating the effects of serial passage on infectious hematopoietic necrosis virus (IHNV) in rainbow trout. This method was used to investigate the transmission efficiency and kinetics of viral shedding of IHNV over 3 serial passages. Transmission efficiency decreased from 100 to 62.5% over the passage steps and was associated with a decrease in virus shedding into water. A shift in the peak of viral shedding was also observed, from Day 2 post immersion for passage 0 to at least 24 h later for all subsequent passages. Finally, the characterization of viruses after 1 round of transmission and propagation on cells showed no change in glycoprotein (G gene) sequences or viral virulence compared to the ancestral virus stock. The methods developed provide valuable tools for reproducible population-level studies of IHNV epidemiology and evolution.

Optimal foraging in seasonal environments: implications for residency of Australian flying foxes in food-subsidized urban landscapes

Bats provide important ecosystem services such as pollination of native forests; they are also a source of zoonotic pathogens for humans and domestic animals. Human-induced changes to native habitats may have created more opportunities for bats to reside in urban settings, thus decreasing pollination services to native forests and increasing opportunities for zoonotic transmission. In Australia, fruit bats (Pteropus spp. flying foxes) are increasingly inhabiting urban areas where they feed on anthropogenic food sources with nutritional characteristics and phenology that differ from native habitats. We use optimal foraging theory to investigate the relationship between bat residence time in a patch, the time it takes to search for a new patch (simulating loss of native habitat) and seasonal resource production. We show that it can be beneficial to reside in a patch, even when food productivity is low, as long as foraging intensity is low and the expected searching time is high. A small increase in the expected patch searching time greatly increases the residence time, suggesting nonlinear associations between patch residence and loss of seasonal native resources. We also found that sudden increases in resource consumption due to an influx of new bats has complex effects on patch departure times that again depend on expected searching times and seasonality. Our results suggest that the increased use of urban landscapes by bats may be a response to new spatial and temporal configurations of foraging opportunities. Given that bats are reservoir hosts of zoonotic diseases, our results provide a framework to study the effects of foraging ecology on disease dynamics.One contribution of 14 to a theme isssue 'Anthropogenic resource subsidies and host-parasite dynamics in wildlife'.

Bottom-up trait-mediated indirect effects decrease pathogen transmission in a tritrophic system

A plant's induction of secondary defenses helps to decrease herbivore damage by changing resource quality. While these chemical or physical defenses may directly decrease herbivory, they can also have indirect consequences. In a tritrophic system consisting of a plant, an insect herbivore, and an insect pathogen, plant based trait-mediated indirect effects (TMIEs) can alter host-pathogen interactions and, thereby, indirectly affect disease transmission. In a series of field experiments, individual soybean plants (Glycine max) were sprayed with either a jasmonic acid (JA) solution to trigger induction of plant defenses or a similar control compound. Fall armyworm (Spodoptera frugiperda) larvae along with varying amounts of a lethal baculovirus were placed on the plants to measure transmission. Induction of plant defenses decreased viral transmission due to increased population heterogeneity arising from changes in individual susceptibility. The change in susceptibility via TMIEs was driven by a decrease in feeding rates and an increase viral dose needed to infect larvae. While the induction against herbivore attack may decrease herbivory, it can also decrease the efficacy of the herbivore's pathogen potentially to the plant's detriment. While TMIEs have been well-recognized for being driven by top-down forces, bottom-up interactions can dictate community dynamics and, here, epizootic severity.

Manipulating host resistance structure reveals impact of pathogen dispersal and environmental heterogeneity on epidemics

Understanding how variation in hosts, parasites, and the environment shapes patterns of disease is key to predicting ecological and evolutionary outcomes of epidemics. Yet in spatially structured populations, variation in host resistance may be spatially confounded with variation in parasite dispersal and environmental factors that affect disease processes. To tease apart these disease drivers, we paired surveys of natural epidemics with experiments manipulating spatial variation in host susceptibility to infection. We mapped epidemics of the wind-dispersed powdery mildew pathogen Podosphaera plantaginis in five populations of its plant host, Plantago lanceolata. At 15 replicate sites within each population, we deployed groups of healthy potted 'sentinel' plants from five allopatric host lines. By tracking which sentinels became infected in the field and measuring pathogen connectivity and microclimate at those sites, we could test how variation in these factors affected disease when spatial variation in host resistance and soil conditions was minimized. We found that the prevalence and severity of sentinel infection varied over small spatial scales in the field populations, largely due to heterogeneity in pathogen prevalence on wild plants and unmeasured environmental factors. Microclimate was critical for disease spread only at the onset of epidemics, where humidity increased infection risk. Sentinels were more likely to become infected than initially healthy wild plants at a given field site. However, in a follow-up laboratory inoculation study we detected no significant differences between wild and sentinel plant lines in their qualitative susceptibility to pathogen isolates from the field populations, suggesting that primarily non-genetic differences between sentinel and wild hosts drove their differential infection rates in the field. Our study leverages a multi-faceted experimental approach to disentangle important biotic and abiotic drivers of disease patterns within wild populations.

Quantitative analysis of the dose-response of white spot syndrome virus in shrimp

White spot syndrome virus (WSSV) is an important cause of mortality and economic losses in shrimp farming. Although WSSV-induced mortality is virus dose dependent and WSSV infection does not necessarily lead to mortality, the relationships between virus-particle dose, infection and mortality have not been analysed quantitatively. Here, we explored WSSV dose-response by a combination of experiments, modelling and meta-analysis. We performed dose-response experiments in Penaeus vannamei postlarvae, recorded host mortality and detected WSSV infection. When we fitted infection models to these data, two models-differing in whether they incorporated heterogeneous host susceptibility to the virus or not-were supported for two independent experiments. To determine the generality of these results, we reanalysed published data sets and then performed a meta-analysis. We found that WSSV dose-response kinetics is indeed variable over experiments. We could not clearly identify which specific infection model has the most support by meta-analysis, but we argue that these results also are most concordant with a model incorporating varying levels of heterogeneous host susceptibility to WSSV. We have identified suitable models for analysing WSSV dose-response, which can elucidate the most basic virus-host interactions and help to avoid underestimating WSSV infection at low virus doses.

The epidemiology and evolution of parasite transmission through cannibalism

Cannibalism is a widespread behavior, and evidence is abundant for transmission from infected victims to susceptible cannibals in many parasite-host systems. Current theory suggests that cannibalism generally impedes disease spread, because each victim is usually consumed by a single cannibal. Thus, cannibalism merely transfers pathogens from one individual to another without spreading infections to additional hosts. This assumes that cannibalism is the only mode of transmission and that the host population is homogenous. However, host developmental stages are a key determinant of both cannibal-victim and host-pathogen interactions. We suggest that multiple modes of pathogen transmission can interact through host stage structure. We show theoretically that cannibalism can enhance disease spread by consistently transferring infections from low quality to high quality hosts that are more infectious via horizontal transmission. We review empirical evidence for the generality of key conditions required for this process, and analyze the implications for the evolution of transmission through cannibalism. More generally, our theory promotes the consideration of multiple transmission pathways when studying parasite-host systems, and advances a useful intuition for assessing whether or not such pathways may be mutually augmentative.

Effects of multiple sources of genetic drift on pathogen variation within hosts

Changes in pathogen genetic variation within hosts alter the severity and spread of infectious diseases, with important implications for clinical disease and public health. Genetic drift may play a strong role in shaping pathogen variation, but analyses of drift in pathogens have oversimplified pathogen population dynamics, either by considering dynamics only at a single scale-such as within hosts or between hosts-or by making drastic simplifying assumptions, for example, that host immune systems can be ignored or that transmission bottlenecks are complete. Moreover, previous studies have used genetic data to infer the strength of genetic drift, whereas we test whether the genetic drift imposed by pathogen population processes can be used to explain genetic data. We first constructed and parameterized a mathematical model of gypsy moth baculovirus dynamics that allows genetic drift to act within and between hosts. We then quantified the genome-wide diversity of baculovirus populations within each of 143 field-collected gypsy moth larvae using Illumina sequencing. Finally, we determined whether the genetic drift imposed by host-pathogen population dynamics in our model explains the levels of pathogen diversity in our data. We found that when the model allows drift to act at multiple scales-including within hosts, between hosts, and between years-it can accurately reproduce the data, but when the effects of drift are simplified by neglecting transmission bottlenecks and stochastic variation in virus replication within hosts, the model fails. A de novo mutation model and a purifying selection model similarly fail to explain the data. Our results show that genetic drift can play a strong role in determining pathogen variation and that mathematical models that account for pathogen population growth at multiple scales of biological organization can be used to explain this variation.