Density-dependent Transmission Research Articles

The effect of diversity on disease reverses from dilution to amplification in a 22-year biodiversity × N × CO2 experiment

Plant disease often increases with N, decreases with CO2, and increases as biodiversity is lost (i.e., the dilution effect). Additionally, all these factors can indirectly alter disease by changing host biomass and hence density-dependent disease transmission. Yet over long periods of time as communities undergo compositional changes, these biomass-mediated pathways might fade, intensify, or even reverse in direction. Using a field experiment that has manipulated N, CO2, and species richness for over 20 years, we compared severity of a specialist rust fungus (Puccinia andropogonis) on its grass host (Andropogon gerardii) shortly after the experiment began (1999) and twenty years later (2019). Between these two sampling periods, two decades apart, we found that disease severity consistently increased with N and decreased with CO2. However, the relationship between diversity and disease reversed from a dilution effect in 1999 (more severe disease in monocultures) to an amplification effect in 2019 (more severe disease in mixtures). The best explanation for this reversal centered on host density (i.e., aboveground biomass), which was initially highest in monoculture, but became highest in mixtures two decades later. Thus, the diversity-disease pattern reversed, but disease consistently increased with host biomass. These results highlight the consistency of N and CO2 as drivers of plant disease in the Anthropocene and emphasize the critical role of host biomass—despite potentially variable effects of diversity—for relationships between biodiversity and disease.

Co-feeding transmission leads to bi-stability of tick-borne disease spread dynamics

Considering that co-feeding transmission depends on the loads of infected ticks on each host, we develop a tick-borne disease dynamics model with co-feeding transmission probability peaking at an intermediate level of infected tick loads. We stratify tick and host population by their infection status and divide the vector population in terms of infection status and post-egg stages (larvae, nymphs and adults). We use the tick population dynamics and disease spread basic reproduction numbers and co-feeding transmission characteristics to describe the disease endemic structure, and show, for the first time, that density-dependent co-feeding transmission provides a novel mechanism for bi-stability. Numerical simulations based on parameters from laboratory and fields data confirm the possibility of bi-stability in biologically realistic settings, and sensitivity analyses show that the nymphal tick load value at which the co-feeding transmission probability reaches the maximum impacts most significantly on the stable endemic equilibrium value.

Reconciling contrasting effects of nitrogen on host immunity and pathogen transmission using stoichiometric models.

Hosts rely on the availability of nutrients for growth, and for defense against pathogens. At the same time, changes in host nutrition can alter the dynamics of pathogens that rely on their host for reproduction. For primary producer hosts, enhanced nutrient loads may increase host biomass or pathogen reproduction, promoting faster density-dependent pathogen transmission. However, the effect of elevated nutrients may be reduced if hosts allocate a growth-limiting nutrient to pathogen defense. In canonical disease models, transmission is not a function of nutrient availability. Yet, including nutrient availability is necessary to mechanistically understand the response of infection to changes in the environment. Here, we explore the implications of nutrient-mediated pathogen infectivity and host immunity on infection outcomes. We developed a stoichiometric disease model that explicitly integrates the contrasting dependencies of pathogen infectivity and host immunity on nitrogen (N) and parameterized it for an algal-host system. Our findings reveal dynamic shifts in host biomass build-up, pathogen prevalence, and the force of infection along N supply gradients with N-mediated host infectivity and immunity, compared with a model in which the transmission rate was fixed. We show contrasting responses in pathogen performance with increasing N supply between N-mediated infectivity and N-mediated immunity, revealing an optimum for pathogen transmission at intermediate N supply. This was caused by N limitation of the pathogen at a low N supply and by pathogen suppression via enhanced host immunity at a high N supply. By integrating both nutrient-mediated pathogen infectivity and host immunity into a stoichiometric model, we provide a theoretical framework that is a first step in reconciling the contrasting role nutrients can have on host-pathogen dynamics.

Small mammal community composition impacts bank vole (Clethrionomys glareolus) population dynamics and associated seroprevalence of Puumala orthohantavirus.

Rodents are important reservoirs for zoonotic pathogens that cause diseases in humans. Biodiversity is hypothesized to be closely related to pathogen prevalence through multiple direct and indirect pathways. For example, the presence of non-host species can reduce contact rates of the main reservoir host and thus reduce the risk of transmission ("dilution effect"). In addition, an overlap in ecological niches between two species could lead to increased interspecific competition, potentially limiting host densities and reducing density-dependent pathogen transmission processes. In this study, we investigated the relative impact of population-level regulation of direct and indirect drivers of the prevalence of Puumala orthohantavirus (PUUV) in bank voles (Clethrionomys glareolus) during years with high abundance. We compiled data on small mammal community composition from four regions in Germany between 2010 and 2013. Structural equation modeling revealed a strong seasonality in PUUV control mechanisms in bank voles. The abundance of shrews tended to have a negative relationship with host abundance, and host abundance positively influenced PUUV seroprevalence, while at the same time increasing the abundance of competing non-hosts like the wood mouse (Apodemus sylvaticus) and the yellow-necked field mouse (Apodemus flavicollis) were associated with reduced PUUV seroprevalence in the host. These results indicate that for PUUV in bank voles, dilution is associated with increased interspecific competition. Anthropogenic pressures leading to the decline of Apodemus spp. in a specific habitat could lead to the amplification of mechanisms promoting PUUV transmission within the host populations.

Mumps epidemic dynamics in the United States before vaccination (1923–1932)

Mumps is a vaccine-preventable, reemerging, and highly transmissible infectious disease. Widespread vaccination dramatically reduced cases; however, case counts have been increasing over the past 20 years. To provide a quantitative overview of historical mumps dynamics that can act as baseline information to help identify causes of mumps reemergence, we analyzed timeseries of cases reported from 1923 to 1932 in the United States. During that time, 239,230 mumps cases were reported in 70 cities. Larger cities reported annual epidemics and smaller cities reported intermittent, sporadic outbreaks. The critical community size above which transmission continuously occurred was likely between 365,583 and 781,188 individuals but could range as high as 3,376,438 individuals. Mumps cases increased as city size increased, suggesting density-dependent transmission. Using a density-dependent SEIR model, we calculated a mean effective reproductive number (Re) of 1.2. Re varied by city and over time, with periodic high values that could characterize short periods of very high transmission known as superspreading events. Case counts most often peaked in March, with higher-than-average transmission from December through April and showed a correlation with weekly births. While certain city pairs in Midwestern states had synchronous outbreaks, most outbreaks were less synchronous and not driven by distance between cities. This work demonstrates the importance of long-term infectious disease surveillance data and will inform future studies on mumps reemergence and control.

Transmission dynamics of lyssavirus in Myotis myotis: mechanistic modelling study based on longitudinal seroprevalence data.

We investigated the transmission dynamics of lyssavirus in Myotis myotis and Myotis blythii, using serological, virological, demographic and ecological data collected between 2015 and 2022 from two maternity colonies in northern Italian churches. Despite no lyssavirus detection in 556 bats sampled over 11 events by reverse transcription-polymerase chain reaction (RT-PCR), 36.3% of 837 bats sampled over 27 events showed neutralizing antibodies to European bat lyssavirus 1, with a significant increase in summers. By fitting sets of mechanistic models to seroprevalence data, we investigated factors that influenced lyssavirus transmission within and between years. Five models were selected as a group of final models: in one model, a proportion of exposed bats (median model estimate: 5.8%) became infectious and died while the other exposed bats recovered with immunity without becoming infectious; in the other four models, all exposed bats became infectious and recovered with immunity. The final models supported that the two colonies experienced seasonal outbreaks driven by: (i) immunity loss particularly during hibernation, (ii) density-dependent transmission, and (iii) a high transmission rate after synchronous birthing. These findings highlight the importance of understanding ecological factors, including colony size and synchronous birthing timing, and potential infection heterogeneities to enable more robust assessments of lyssavirus spillover risk.

Effects of culling vampire bats on the spatial spread and spillover of rabies virus.

Controlling pathogen circulation in wildlife reservoirs is notoriously challenging. In Latin America, vampire bats have been culled for decades in hopes of mitigating lethal rabies infections in humans and livestock. Whether culls reduce or exacerbate rabies transmission remains controversial. Using Bayesian state-space models, we show that a 2-year, spatially extensive bat cull in an area of exceptional rabies incidence in Peru failed to reduce spillover to livestock, despite reducing bat population density. Viral whole genome sequencing and phylogeographic analyses further demonstrated that culling before virus arrival slowed viral spatial spread, but reactive culling accelerated spread, suggesting that culling-induced changes in bat dispersal promoted viral invasions. Our findings question the core assumptions of density-dependent transmission and localized viral maintenance that underlie culling bats as a rabies prevention strategy and provide an epidemiological and evolutionary framework to understand the outcomes of interventions in complex wildlife disease systems.

Multimodal pathogen transmission as a limiting factor in host distribution.

Theoretical models suggest that infectious diseases could play a substantial role in determining the spatial extent of host species, but few studies have collected the empirical data required to test this hypothesis. Pathogens that sterilize their hosts or spread through frequency-dependent transmission could have especially strong effects on the limits of species' distributions because diseased hosts that are sterilized but not killed may continue to produce infectious stages and frequency-dependent transmission mechanisms are effective even at very low population densities. We collected spatial pathogen prevalence data and population abundance data for alpine carnations infected by the sterilizing pathogen Microbotryum dianthorum, a parasite that is spread through both frequency-dependent (vector-borne) and density-dependent (aerial spore transmission) mechanisms. Our 13-year study reveals rapid declines in population abundance without a compensatory decrease in pathogen prevalence. We apply a stochastic, spatial model of parasite spread that accommodates spatial habitat heterogeneity to investigate how the population dynamics depend on multimodal (frequency-dependent and density-dependent) transmission. We found that the observed rate of population decline could plausibly be explained by multimodal transmission, but is unlikely to be explained by either frequency-dependent or density-dependent mechanisms alone. Multimodal pathogen transmission rates high enough to explain the observed decline predicted that eventual local extinction of the host species is highly likely. Our results add to a growing body of literature showing how multimodal transmission can constrain species distributions in nature.

From trees to fleas: masting indirectly affects flea abundance on a rodent host.

Mast seeding causes strong fluctuations in populations of forest animals. Thus, this phenomenon can be used as a natural experiment to examine how variation in host abundance affects parasite loads. We investigated fleas infesting yellow-necked mice in beech forest after 2 mast and 2 non-mast years. We tested 2 mutually exclusive scenarios: (1) as predicted by classical models of density-dependent transmission, an increase in host density will cause an increase in ectoparasite abundance (defined as the number of parasites per host), versus (2) an increase in host density will cause a decline in flea abundance ("dilution," which is thought to occur when parasite population growth is slower than that of the host). In addition, we assessed whether masting alters the relationship between host traits (sex and body mass) and flea abundance. We found a hump-shaped relationship between host and flea abundance. Thus, the most basic predictions are too simple to describe ectoparasite dynamics in this system. In addition, masting modified seasonal dynamics of flea abundance, but did not affect the relationship between host traits and flea abundance (individuals with the highest body mass hosted the most fleas; after controlling for body mass, parasite abundance did not vary between sexes). Our results demonstrate that pulses of tree reproduction can indirectly, through changes in host densities, drive patterns of ectoparasite infestation.

Timescale reverses the relationship between host density and infection risk.

Host density shapes infection risk through two opposing phenomena. First, when infective stages are subdivided among multiple hosts, greater host densities decrease infection risk through 'safety in numbers'. Hosts, however, represent resources for parasites, and greater host availability also fuels parasite reproduction. Hence, host density increases infection risk through 'density-dependent transmission'. Theory proposes that these phenomena are not disparate outcomes but occur over different timescales. That is, higher host densities may reduce short-term infection risk, but because they support parasite reproduction, may increase long-term risk. We tested this theory in a zooplankton-disease system with laboratory experiments and field observations. Supporting theory, we found that negative density-risk relationships (safety in numbers) sometimes emerged over short timescales, but these relationships reversed to 'density-dependent transmission' within two generations. By allowing parasite numerical responses to play out, time can shift the consequences of host density, from reduced immediate risk to amplified future risk.

Modeling scenarios for mitigating outbreaks in congregate settings.

The explosive outbreaks of COVID-19 seen in congregate settings such as prisons and nursing homes, has highlighted a critical need for effective outbreak prevention and mitigation strategies for these settings. Here we consider how different types of control interventions impact the expected number of symptomatic infections due to outbreaks. Introduction of disease into the resident population from the community is modeled as a stochastic point process coupled to a branching process, while spread between residents is modeled via a deterministic compartmental model that accounts for depletion of susceptible individuals. Control is modeled as a proportional decrease in the number of susceptible residents, the reproduction number, and/or the proportion of symptomatic infections. This permits a range of assumptions about the density dependence of transmission and modes of protection by vaccination, depopulation and other types of control. We find that vaccination or depopulation can have a greater than linear effect on the expected number of cases. For example, assuming a reproduction number of 3.0 with density-dependent transmission, we find that preemptively reducing the size of the susceptible population by 20% reduced overall disease burden by 47%. In some circumstances, it may be possible to reduce the risk and burden of disease outbreaks by optimizing the way a group of residents are apportioned into distinct residential units. The optimal apportionment may be different depending on whether the goal is to reduce the probability of an outbreak occurring, or the expected number of cases from outbreak dynamics. In other circumstances there may be an opportunity to implement reactive disease control measures in which the number of susceptible individuals is rapidly reduced once an outbreak has been detected to occur. Reactive control is most effective when the reproduction number is not too high, and there is minimal delay in implementing control. We highlight the California state prison system as an example for how these findings provide a quantitative framework for understanding disease transmission in congregate settings. Our approach and accompanying interactive website (https://phoebelu.shinyapps.io/DepopulationModels/) provides a quantitative framework to evaluate the potential impact of policy decisions governing infection control in outbreak settings.

Factors influencing the presence of parasitic trombiculids on red-backed voles (Myodes gapperi) in a temperate archipelago

Parasites can influence host population health and dynamics and are often an overlooked aspect of the ecology of ecosystems. Understanding the impacts of ecological interactions between parasites and small mammals can provide insights into ecosystem dynamics. We live trapped small mammals within the Apostle Islands archipelago (2017–2020) and assessed factors influencing the presence of mites from the Trombiculidae family. Archipelagos provide unique research opportunities because in small mammal–parasitic trombiculid systems, they are essentially closed systems. We detected trombiculids on 47% of red-backed vole ( Myodes gapperi (Vigors, 1830)) individuals but rarely detected trombiculids on other species. We developed and ranked a set of a priori logistic regression models of trombiculid presence relative to habitat quality, host abundance, body condition, sex, and sexual maturity to identify factors significant in predicting trombiculid infection for M. gapperi. Parasitic trombiculids were more likely when M. gapperi abundance was high and body condition was poor; however, it is unknown whether trombiculids affect condition or if trombiculids are more likely to parasitize hosts in poor condition. The significance of host abundance may indicate density-dependent transmission. Our work suggests that host density and body condition are important factors influencing parasitism by trombiculids in M. gapperi populations.

How Multiple Interaction Types Affect Disease Spread and Dilution in Ecological Networks

Ecological communities are composed of different functional guilds that are engaging in multiple types of biotic interactions. We explore how ecological networks fare when confronting infectious diseases according to density-dependent (DD) and frequency-dependent (FD) transmission modes. Our model shows that network compositions can dictate both disease spreading and the relationship between disease and community diversity (including species richness and Shannon’s diversity) as depicted in the dilution effect. The disease becomes more prevalent within communities harboring more mutualistic interactions, generating a positive relationship between disease prevalence and community diversity (i.e., an amplification effect). By contrast, in communities with a fixed proportion of mutualistic interactions, higher diversity from the balance of competition and predation can impede disease prevalence (i.e., the dilution effect). Within-species disease prevalence increases linearly with a species’ degree centrality. These patterns of disease transmission and the diversity-disease relationship hold for both transmission modes. Our analyses highlight the complex effects of interaction compositions in ecological networks on infectious disease dynamics and further advance the debate on the dilution effect of host diversity on disease prevalence.

Population growth of Gyrodactylus kobayashii in goldfish (Carassius auratus) associated with host density.

Host density is a key regulatory factor in parasite transmission. The goldfish (Carassius auratus)-Gyrodactylus kobayashii model was used to investigate effects of host density on population growth of gyrodactylids. A donor fish infected by five gravid gyrodactylids was mixed with 11 parasite-free goldfish at five host densities. There was a significant positive correlation between host density and mean abundance of G. kobayashii throughout the 58-day experiment. During early infection (days 15–24), mean abundance in medium high (0.5 fish L−1) and high host density groups (1 and 2 fish L−1) was significantly higher than that in the low host density groups (0.125 and 0.25 fish L−1). At high host density, prevalence increased more rapidly, and the peak prevalence was higher. Fitting of an exponential growth model showed that the population growth rate of the parasite increased with host density. A hypothesis was proposed that higher host density contributed to increased reinfection of detached gyrodactylids. A reinfection experiment was designed to test this hypothesis. Both mean abundance and prevalence at a host density of 1 fish L−1 were significantly higher than those at 0.25 fish L−1 on days 1 and 3, which suggested that more reinfections of G. kobyashii occurred at the higher host density. Density-dependent transmission during the early infection was an important contributor of population growth of G. kobayashii, as well as density-dependent reinfection of the detached gyrodactylids.

Stability and Hopf bifurcation of an SIR epidemic model with density-dependent transmission and Allee effect.

In this paper, an SIR model with a strong Allee effect and density-dependent transmission is proposed, and its characteristic dynamics are investigated. The elementary mathematical characteristic of the model is studied, including positivity, boundedness and the existence of equilibrium. The local asymptotic stability of the equilibrium points is analyzed using linear stability analysis. Our results indicate that the asymptotic dynamics of the model are not only determined using the basic reproduction number ${R_0}$. If ${R_0} < 1$, there are three disease-free equilibrium points, and a disease-free equilibrium is always stable. At the same time, the conditions for other disease-free equilibrium points to be bistable were determined. If ${R_0} > 1$ and in certain conditions, either an endemic equilibrium emerges and is locally asymptotically stable, or the endemic equilibrium becomes unstable. What must be emphasized is that there is a locally asymptotically stable limit cycle when the latter happens. The Hopf bifurcation of the model is also discussed using topological normal forms. The stable limit cycle can be interpreted in a biological significance as a recurrence of the disease. Numerical simulations are used to verify the theoretical analysis. Taking into account both density-dependent transmission of infectious diseases and the Allee effect, the dynamic behavior becomes more interesting than when considering only one of them in the model. The Allee effect makes the SIR epidemic model bistable, which also makes the disappearance of diseases possible, since the disease-free equilibrium in the model is locally asymptotically stable. At the same time, persistent oscillations due to the synergistic effect of density-dependent transmission and the Allee effect may explain the recurrence and disappearance of disease.

Dilution of Epidemic Potential of Environmentally Transmitted Infectious Diseases for Species with Partially Overlapping Habitats.

AbstractSpecies diversity may play an important role in the modulation of pathogen transmission through the dilution effect. Infectious disease models can help elucidate mechanisms that may underlie this effect. While many modeling studies have assumed direct host-to-host transmission, many pathogens are transmitted through the environment. We present a mathematical modeling analysis exploring conditions under which we observe the dilution effect in systems with environmental transmission where host species interact through fully or partially overlapping habitats. We measure the strength of the dilution effect by the relative decrease in the basic reproduction number of two-species assemblages compared with that of a focal host species. We find that a dilution effect is most likely when the pathogen is environmentally persistent (frequency-dependent-like transmission). The magnitude of this effect is strongest when the species with the greater epidemic potential is relatively slow to pick up pathogens in the environment (density-dependent transmission) and the species with the lesser epidemic potential is efficient at picking up pathogens (frequency-dependent transmission). These findings suggest that measurable factors, including pathogen persistence and the host's relative efficiency of pathogen pickup, can guide predictions of when biodiversity might lead to a dilution effect and may thus give concrete direction to future ecological work.

Social fluidity mobilizes contagion in human and animal populations.

Humans and other group-living animals tend to distribute their social effort disproportionately. Individuals predominantly interact with a small number of close companions while maintaining weaker social bonds with less familiar group members. By incorporating this behavior into a mathematical model, we find that a single parameter, which we refer to as social fluidity, controls the rate of social mixing within the group. Large values of social fluidity correspond to gregarious behavior, whereas small values signify the existence of persistent bonds between individuals. We compare the social fluidity of 13 species by applying the model to empirical human and animal social interaction data. To investigate how social behavior influences the likelihood of an epidemic outbreak, we derive an analytical expression of the relationship between social fluidity and the basic reproductive number of an infectious disease. For species that form more stable social bonds, the model describes frequency-dependent transmission that is sensitive to changes in social fluidity. As social fluidity increases, animal-disease systems become increasingly density-dependent. Finally, we demonstrate that social fluidity is a stronger predictor of disease outcomes than both group size and connectivity, and it provides an integrated framework for both density-dependent and frequency-dependent transmission.

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.

Using sensitivity analysis to identify factors promoting higher versus lower infection prevalence in multi-host communities

Relationships between host species richness and levels of disease in a focal host are likely to be context-dependent, depending on the characteristics of which particular host species are present in a community. I use a multi-host epidemiological model with environmental transmission to explore how the characteristics of the host species (e.g., competence and competitive ability), host density, and the pathogen transmission mechanism affect the proportion of infected individuals (i.e., infection prevalence) in a focal host. My sensitivity-based approach identifies the indirect pathways through which specific ecological and epidemiological processes affect focal host infection prevalence. This in turn yields predictions about the context-dependent rules governing whether increased host species richness increases (amplifies) or decreases (dilutes) infection prevalence in a focal host. For example, in many cases, amplification and dilution are predicted to occur when added host species are sources or sinks of infectious propagules, respectively. However, if the added host species have strong and asymmetric competitive effects on resident host species, then amplification and dilution are predicted to occur when the added host species have stronger competitive effects on resident host species that are sources or sinks of infectious propagules, respectively. My results also predict that greater dilution and less amplification is more likely to occur under frequency-dependent direct transmission than density-dependent direct transmission when (i) the added hosts have lower competence than resident host species and (ii) interspecific competition between the added host species and resident host species is lower; the opposite conditions promote greater amplification and less dilution under frequency-dependent direct transmission. This work helps identify and explain the mechanisms shaping the context-dependent relationships between host species richness and disease in multi-host communities.

The Context-Dependent Effects of Host Competence, Competition, and Pathogen Transmission Mode on Disease Prevalence.

AbstractBiodiversity in communities is changing globally, including the gain and loss of host species in host-pathogen communities. Increased host diversity can cause infection prevalence in a focal host to increase (amplification) or decrease (dilution). However, it is unclear what general rules govern the context-dependent effects, in part because theories for pathogens with different transmission modes have developed largely independently. Using a two-host model, we explore how the pathogen transmission mode and characteristics of a second host (disease competence and competitive ability) influence disease prevalence in a focal host. Our work shows how the theories for pathogens with environmental transmission, density-dependent direct transmission, and frequency-dependent direct transmission can be unified. Our work also identifies general rules about how host and pathogen characteristics affect amplification/dilution. For example, higher-competence hosts promote amplification, unless they are strong interspecific competitors; strong interspecific competitors promote dilution, unless they are large sources of new infections; and dilution occurs under frequency-dependent direct transmission more than density-dependent direct transmission, unless interspecific host competition is sufficiently strong. Our work helps explain how the characteristics of the pathogen and a second host affect disease prevalence in a focal host.