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1. Novel pathogen introduction triggers rapid evolution in animal social movement strategies

   https://doi.org/10.7554/eLife.81805  

   Gupte, Pratik Rajan; Albery, Gregory F; Gismann, Jakob; Sweeny, Amy; Weissing, Franz J (August 2023, eLife)

   Animal sociality emerges from individual decisions on how to balance the costs and benefits of being sociable. Novel pathogens introduced into wildlife populations should increase the costs of sociality, selecting against gregariousness. Using an individual-based model that captures essential features of pathogen transmission among social hosts, we show how novel pathogen introduction provokes the rapid evolutionary emergence and coexistence of distinct social movement strategies. These strategies differ in how they trade the benefits of social information against the risk of infection. Overall, pathogen-risk-adapted populations move more and have fewer associations with other individuals than their pathogen-risk-naive ancestors, reducing disease spread. Host evolution to be less social can be sufficient to cause a pathogen to be eliminated from a population, which is followed by a rapid recovery in social tendency. Our conceptual model is broadly applicable to a wide range of potential host–pathogen introductions and offers initial predictions for the eco-evolutionary consequences of wildlife pathogen spillover scenarios and a template for the development of theory in the ecology and evolution of animals’ movement decisions. 

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2. The tumour is in the detail: Local phylogenetic, population and epidemiological dynamics of a transmissible cancer in Tasmanian devils

   https://doi.org/10.1111/eva.13569  

   Hamede, Rodrigo; Fountain‐Jones, Nicholas M.; Arce, Fernando; Jones, Menna; Storfer, Andrew; Hohenlohe, Paul A.; McCallum, Hamish; Roche, Benjamin; Ujvari, Beata; Thomas, Frédéric (June 2023, Evolutionary Applications)

   Abstract Infectious diseases are a major threat for biodiversity conservation and can exert strong influence on wildlife population dynamics. Understanding the mechanisms driving infection rates and epidemic outcomes requires empirical data on the evolutionary trajectory of pathogens and host selective processes. Phylodynamics is a robust framework to understand the interaction of pathogen evolutionary processes with epidemiological dynamics, providing a powerful tool to evaluate disease control strategies. Tasmanian devils have been threatened by a fatal transmissible cancer, devil facial tumour disease (DFTD), for more than two decades. Here we employ a phylodynamic approach using tumour mitochondrial genomes to assess the role of tumour genetic diversity in epidemiological and population dynamics in a devil population subject to 12 years of intensive monitoring, since the beginning of the epidemic outbreak. DFTD molecular clock estimates of disease introduction mirrored observed estimates in the field, and DFTD genetic diversity was positively correlated with estimates of devil population size. However, prevalence and force of infection were the lowest when devil population size and tumour genetic diversity was the highest. This could be due to either differential virulence or transmissibility in tumour lineages or the development of host defence strategies against infection. Our results support the view that evolutionary processes and epidemiological trade‐offs can drive host‐pathogen coexistence, even when disease‐induced mortality is extremely high. We highlight the importance of integrating pathogen and population evolutionary interactions to better understand long‐term epidemic dynamics and evaluating disease control strategies. 

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3. Risk of death during acute infection is accelerating across diverse host-pathogen systems and consistent with multiple models of host-pathogen interaction

   https://doi.org/10.1128/msphere.00953-24  

   O'Sullivan, Tim; Karakoç, Canan; Wollein_Waldetoft, Kristofer; Brown, Sam P (May 2025, mSphere)

   Buchler, Nicolas E (Ed.)

   ABSTRACT Infectious diseases remain a major cause of global mortality, yet basic questions concerning the relationship between within-host processes governing pathogen burden (pathogen replication, immune responses) and population-scale (epidemiological) patterns of mortality remain obscure. We use a structured literature review to leverage the extensive biomedical data generated by controlled host infections to address the epidemiological question of whether infection-induced mortality is constant, accelerating, or follows some other pattern of change and to infer the within-host mechanistic basis of this pattern. We show that across diverse lethal infection models, the risk of death increases approximately exponentially in time since infection, in a manner phenomenologically similar to the dynamics of all-cause death. We further show that this pattern of accelerating risk is consistent with multiple alternate mechanisms of pathogen growth and host-pathogen interaction, underlining the limitations of current experimental approaches to connect within-host processes to epidemiological patterns. We review critical experimental questions that our work highlights, requiring additional non-invasive data on pathogen burden throughout the course of infection.IMPORTANCEHere, we ask a simple question: what are the dynamics of pathogen-induced death? Death is a central phenotype in both biomedical and epidemiological infectious disease biology, yet very little work has attempted to link the biomedical focus on pathogen dynamics within a host and the epidemiological focus on populations of infected hosts. To systematically characterize the dynamics of death in controlled animal infections, we analyzed 209 data sets spanning diverse lethal animal infection models. Across experimental models, we find robust support for an accelerating risk of death since the time of infection, contrasting with conventional epidemiological models that assume a constant elevated risk of death. Using math models, we show that multiple processes of growth and virulence are consistent with accelerating risk of death, and we end with a discussion of critical experiments to resolve how within-host biomedical processes map onto epidemiological patterns of disease. 

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4. Sin Nombre virus prevalence from 2014–2017 in wild deer mice, Peromyscus maniculatus , on five of the California Channel Islands

   https://doi.org/10.1111/zph.12855  

   Orrock, John L.; Connolly, Brian M.; Guiden, Peter W.; Chandler, Jennifer L.; Bron, Gebbiena M.; Drost, Charles A.; Garcelon, David K. (May 2021, Zoonoses and Public Health)

   Abstract Sin Nombre virus (SNV) is a zoonotic virus that is highly pathogenic to humans. The deer mouse,Peromyscus maniculatus, is the primary host of SNV, and SNV prevalence inP. maniculatusis an important indicator of human disease risk. Because the California Channel Islands contain permanent human settlements, receive hundreds of thousands of visitors each year, and can have extremely high densities ofP. maniculatus, surveillance for SNV in islandP. maniculatusis important for understanding the human risk of zoonotic disease. Despite the importance of surveillance on these heavily utilized islands, SNV prevalence (i.e. the proportion ofP. maniculatusthat test positive to antibodies to SNV) has not been examined in the last 13–27 years. We present data on 1,610 mice sampled for four consecutive years (2014–2017) on five of the California Channel Islands: East Anacapa, Santa Barbara, Santa Catalina, San Nicolas, and San Clemente. Despite historical data indicating SNV‐positive mice on San Clemente and Santa Catalina, we detected no SNV‐positive mice on these islands, suggesting very low prevalence or possible loss of SNV. Islands historically free of SNV (East Anacapa, Santa Barbara, and San Nicolas) remained free of SNV, suggesting that rates of pathogen introduction from other islands and/or the mainland are low. Although continued surveillance is warranted to determine whether SNV establishes on these islands, our work helps inform current human disease risk in these locations and suggests that SNV prevalence on these islands is currently very low. 

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5. Pathogens stabilize or destabilize depending on host stage structure

   https://doi.org/10.3934/mbe.2023901  

   Hite, Jessica L; de_Roos, André M (November 2023, Mathematical Biosciences and Engineering)

   A common assumption is that pathogens more readily destabilize their host populations, leading to an elevated risk of driving both the host and pathogen to extinction. This logic underlies many strategies in conservation biology and pest and disease management. Yet, the interplay between pathogens and population stability likely varies across contexts, depending on the environment and traits of both the hosts and pathogens. This context-dependence may be particularly important in natural consumer-host populations where size- and stage-structured competition for resources strongly modulates population stability. Few studies, however, have examined how the interplay between size and stage structure and infectious disease shapes the stability of host populations. Here, we extend previously developed size-dependent theory for consumer-resource interactions to examine how pathogens influence the stability of host populations across a range of contexts. Specifically, we integrate a size- and stage-structured consumer-resource model and a standard epidemiological model of a directly transmitted pathogen. The model reveals surprisingly rich dynamics, including sustained oscillations, multiple steady states, biomass overcompensation, and hydra effects. Moreover, these results highlight how the stage structure and density of host populations interact to either enhance or constrain disease outbreaks. Our results suggest that accounting for these cross-scale and bidirectional feedbacks can provide key insight into the structuring role of pathogens in natural ecosystems while also improving our ability to understand how interventions targeting one may impact the other. 

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