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1. Modeling the Effects of Resource-Driven Immune Defense on Parasite Transmission in Heterogeneous Host Populations

   https://doi.org/10.1093/icb/icz074  

   Hall, Richard J. ( May 2019 , Integrative and Comparative Biology)

   Individuals experience heterogeneous environmental conditions that can affect within-host processes such as immune defense against parasite infection. Variation among individuals in parasite shedding can cause some hosts to contribute disproportionately to population-level transmission, but we currently lack mechanistic theory that predicts when environmental conditions can result in large disease outbreaks through the formation of immunocompromised superspreading individuals. Here, I present a within-host model of a microparasite’s interaction with the immune system that links an individual host’s resource intake to its infectious period. For environmental scenarios driving population-level heterogeneity in resource intake (resource scarcity and resource subsidy relative to baseline availability), I generate a distribution of infectious periods and simulate epidemics on these heterogeneous populations. I find that resource scarcity can result in large epidemics through creation of superspreading individuals, while resource subsidies can reduce or prevent transmission of parasites close to their invasion threshold by homogenizing resource allocation to immune defense. Importantly, failure to account for heterogeneity in competence can result in under-prediction of outbreak size, especially when parasites are close to their invasion threshold. More generally, this framework suggests that differences in conditions experienced by individual hosts can lead to superspreading via differences in resource allocation to immunemore »defense alone, even in the absence of other heterogeneites such as host contacts.

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2. Role of Multiple Infections on Immunological Variation in Wild Populations

   https://doi.org/10.1128/mSystems.00099-19  

   Tate, Ann T. ( June 2019 , mSystems)

   ABSTRACT A central challenge in the fields of evolutionary immunology and disease ecology is to understand the causes and consequences of natural variation in host susceptibility to infectious diseases. As hosts progress from birth to death in the wild, they are exposed to a wide variety of microorganisms that influence their physical condition, immune system maturation, and susceptibility to concurrent and future infection. Thus, multiple exposures to the same or different microbes can be important environmental drivers of host immunological variation and immune priming. In this perspective, I discuss parasite infracommunity interactions and their imprint on host immunity in space and time. I further consider feedbacks from parasite community dynamics within individual hosts on the transmission of disease at higher levels of biological organization and highlight the promise of systems biology approaches, using flour beetles as an example, for studying the role of multiple infections on immunological variation in wild populations.
3. Linking Bioenergetics and Parasite Transmission Models Suggests Mismatch Between Snail Host Density and Production of Human Schistosomes

   https://doi.org/10.1093/icb/icz058  

   Malishev, Matthew ; Civitello, David J. ( May 2019 , Integrative and Comparative Biology)

   The consequences of parasite infection for individual hosts depend on key features of host–parasite ecology underpinning parasite growth and immune defense, such as age, sex, resource supply, and environmental stressors. Scaling these features and their underlying mechanisms from the individual host is challenging but necessary, as they shape parasite transmission at the population level. Translating individual-level mechanisms across scales could inherently improve the way we think about feedbacks among parasitism, the mechanisms driving transmission, and the consequences of human impact and disease control efforts. Here, we use individual-based models (IBMs) based on general metabolic theory, Dynamic Energy Budget (DEB) theory, to scale explicit life-history features of individual hosts, such as growth, reproduction, parasite production, and death, to parasite transmission at the population level over a range of resource supplies focusing on the major human parasite, Schistosoma mansoni, and its intermediate host snail, Biomphalaria glabrata. At the individual level, infected hosts produce fewer parasites at lower resources as competition increases. At the population level, our DEB–IBM predicts brief, but intense parasite peaks early during the host growth season when resources are abundant and infected hosts are few. The timing of these peaks challenges the status quo that high densities ofmore »infected hosts produce the highest parasite densities. As expected, high resource supply boosts parasite output, but parasite output also peaks at modest to high host background mortality rates, which parallels overcompensation in stage-structured models. Our combined results reveal the crucial role of individual-level physiology in identifying how environmental conditions, time of the year, and key feedbacks within host–parasite ecology interact to define periods of elevated risk. The testable forecasts from this physiologically-explicit epidemiological model can inform disease management to reduce human risk of schistosome infection.

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4. Reactivation of latent infections with migration shapes population-level disease dynamics

   https://doi.org/10.1098/rspb.2020.1829  

   Becker, Daniel J. ; Ketterson, Ellen D. ; Hall, Richard J. ( September 2020 , Proceedings of the Royal Society B: Biological Sciences)

   Annual migration is common across animal taxa and can dramatically shape the spatial and temporal patterns of infectious disease. Although migration can decrease infection prevalence in some contexts, these energetically costly long-distance movements can also have immunosuppressive effects that may interact with transmission processes in complex ways. Here, we develop a mechanistic model for the reactivation of latent infections driven by physiological changes or energetic costs associated with migration (i.e. ‘migratory relapse’) and its effects on disease dynamics. We determine conditions under which migratory relapse can amplify or reduce infection prevalence across pathogen and host traits (e.g. infectious periods, virulence, overwinter survival, timing of relapse) and transmission phenologies. We show that relapse at either the start or end of migration can dramatically increase prevalence across the annual cycle and may be crucial for maintaining pathogens with low transmissibility and short infectious periods in migratory populations. Conversely, relapse at the start of migration can reduce the prevalence of highly virulent pathogens by amplifying culling of infected hosts during costly migration, especially for highly transmissible pathogens and those transmitted during migration or the breeding season. Our study provides a mechanistic foundation for understanding the spatio-temporal patterns of relapsing infections in migratory hosts,more »with implications for zoonotic surveillance and understanding how infection patterns will respond to shifts in migratory propensity associated with environmental change. Further, our work suggests incorporating within-host processes into population-level models of pathogen transmission may be crucial for reconciling the range of migration–infection relationships observed across migratory species.« less
5. Spatial heterogeneity can lead to substantial local variations in COVID-19 timing and severity

   https://doi.org/10.1073/pnas.2011656117  

   Thomas, Loring J. ; Huang, Peng ; Yin, Fan ; Luo, Xiaoshuang Iris ; Almquist, Zack W. ; Hipp, John R. ; Butts, Carter T. ( September 2020 , Proceedings of the National Academy of Sciences)

   Standard epidemiological models for COVID-19 employ variants of compartment (SIR or susceptible–infectious–recovered) models at local scales, implicitly assuming spatially uniform local mixing. Here, we examine the effect of employing more geographically detailed diffusion models based on known spatial features of interpersonal networks, most particularly the presence of a long-tailed but monotone decline in the probability of interaction with distance, on disease diffusion. Based on simulations of unrestricted COVID-19 diffusion in 19 US cities, we conclude that heterogeneity in population distribution can have large impacts on local pandemic timing and severity, even when aggregate behavior at larger scales mirrors a classic SIR-like pattern. Impacts observed include severe local outbreaks with long lag time relative to the aggregate infection curve, and the presence of numerous areas whose disease trajectories correlate poorly with those of neighboring areas. A simple catchment model for hospital demand illustrates potential implications for health care utilization, with substantial disparities in the timing and extremity of impacts even without distancing interventions. Likewise, analysis of social exposure to others who are morbid or deceased shows considerable variation in how the epidemic can appear to individuals on the ground, potentially affecting risk assessment and compliance with mitigation measures. These results demonstratemore »the potential for spatial network structure to generate highly nonuniform diffusion behavior even at the scale of cities, and suggest the importance of incorporating such structure when designing models to inform health care planning, predict community outcomes, or identify potential disparities.« less