Risk factors for the evolutionary emergence of pathogens

We use a multitype continuous time Markov branching process model to describe the dynamics of the spread of parasites of two types that can mutate into each other in a common host population. While most mathematical models for the virulence of infectious diseases focus on the interplay between the dynamics of host populations and the optimal characteristics for the success of the pathogen, our model focuses on how pathogen characteristics may change at the start of an epidemic, before the density of susceptible hosts decline. We envisage animal husbandry situations where hosts are at very high density and epidemics are curtailed before host densities are much reduced. The use of three pathogen characteristics: lethality, transmissibility and mutability allows us to investigate the interplay of these in relation to host density. We provide some numerical illustrations and discuss the effects of the size of the enclosure containing the host population on the encounter rate in our model that plays the key role in determining what pathogen type will eventually prevail. We also present a multistage extension of the model to situations where there are several populations and parasites can be transmitted from one of them to another. We conclude that animal husbandry situations with high stock densities will lead to very rapid increases in virulence, where virulent strains are either more transmissible or favoured by mutation. Further the process is affected by the nature of the farm enclosures.

Infectious disease dynamics result from the complex interplay of epidemiological, ecological and evolutionary (epi-eco-evo) processes. Accurately modelling these coupled processes is crucial for understanding pathogen spread and informing public health strategies. However, existing genomic epidemiology simulators typically assume conditional independence among these processes: generating transmission trees independently of pathogen evolution, and then superimposing neutral mutations onto fixed genealogies without ecological feedback. This simplification fails to capture how pathogen evolution dynamically reshapes epidemic trajectories.We introduce e3SIM, an open-source, agent-based, forward-time simulator for macOS and Linux that explicitly integrates pathogen transmission dynamics, molecular evolution and environmental factors. e3SIM incorporates configurable compartmental models, user-defined host contact networks, customizable pathogen genetic architectures and optional eco-evolutionary features (e.g. within-host dynamics, multi-strain infections). This integration enables realistic modelling of pathogen spread and evolution. Key features include modularity, flexible epidemiological and population-genetic modelling, time-varying environmental factors and a user-friendly graphical interface.We demonstrated e3SIM’s capabilities by simulating SARS-CoV-2 and Mycobacterium tuberculosis outbreaks. e3SIM captured the emergence and spread of drug-resistant variants under sequential treatments, highlighting how pathogen evolution and environmental variations dynamically reshape epidemic trajectories. We also illustrated how interactions between pathogen transmissibility and host population structures, particularly those involving socially active “superspreaders”, strongly influence pathogen lineage expansion and transmission clusters. Runtime profiling demonstrated computational efficiency and scalability.e3SIM provides a powerful tool for simulating infectious disease dynamics through the explicit integration of epi-eco-evo processes, substantially enhancing realism and predictive accuracy in genomic epidemiology. Its modular, user-friendly design supports broad applications across diverse host-pathogen systems, enabling rigorous exploration of scenarios critical to public health.

e12532 Background: Genetic testing has not been widely performed in Japan. It is not known whether BRCA mutation-carrier model is useful for selecting eligible person of genetic testing. We studied the validation of BRCAPRO in Japanese. Methods: Twenty-six hundred sixty-five people visited to our hospital between 2011 and 2012.They were surveyed family history as a risk factor of inheriting breast cancer according to NCCN guideline. Among them, those who have a number of family history of breast cancer, ovarian cancer, pancreatic cancer, prostate cancer were selected and in addition, genetic counselor constructed family tree. We also calculated BRCA1/2 mutation probability by BRCAPRO.Those who had more than 10% mutation probability and early onset breast cancer, triple negative breast cancer were received genetic counseling and genetic testing for applicants. We also calculated sensitivity, specificity and predictive value at 10% estimated probability. Results: One hundred five people (3.9%) were selected as a risk of inheriting breast cancer, of which sixty-three people (2.3%) were constructed family tree.The number of people who had more than 10% and 30% mutation probability by BRCAPRO was seven (0.26%) and three (0.11%).Nine people performed BRCA1/2 genetic testing (proband : eight, relative: one)Four people carried a deleterious BRCA mutation (BRCA1: three, BRCA2: one).In the cases which had more than 30% mutation probability, all of them carried a deleterious BRCA mutation. Most of their mutation site was L63X which was most frequent in Japan. Using a 10% cut-off, sensitivity was 75%, specificity was 80%,positive predictive value was 75%. When it comes to the cases which had more than 30% mutation probability, Sensitivity, specificity, positive predictive value were all 100%. Conclusions: Our findings suggest BRCAPRO is useful in Japanese, especially those who have more than 30% mutation probability.

With an increasing body of evidence that SARS-CoV-2 is an airborne pathogen, droplet character formed during speech, coughs, and sneezes are important. Larger droplets tend to fall faster and are less prone to drive the airborne transmission pathway. Alternatively, small droplets (aerosols) can remain suspended for long time periods. The small size of SARS-CoV-2 enables it to be encapsulated in these aerosols, thereby increasing the pathogen’s ability to be transmitted via airborne paths. Droplet formation during human respiratory events relates to airspeed (speech, cough, sneeze), fluid properties of the saliva/mucus, and the fluid content itself. In this work, we study the fluidic drivers (fluid properties and content) and their influence on factors relating to transmissibility. We explore the relationship between saliva fluid properties and droplet airborne transmission paths. Interestingly, the natural human response appears to potentially work with these drivers to mitigate pathogen transmission. In this work, the saliva is varied using two approaches: (1) modifying the saliva with colloids that increase the viscosity/surface tension, and (2) stimulating the saliva content to increased/decreased levels. Through modern experimental and numerical flow diagnostic methods, the character, content, and exposure to droplets and aerosols are all evaluated. The results indicate that altering the saliva properties can significantly impact the droplet size distribution, the formation of aerosols, the trajectory of the bulk of the droplet plume, and the exposure (or transmissibility) to droplets. High-fidelity numerical methods used and verify that increased droplet size character enhances droplet fallout. In the context of natural saliva response, we find previous studies indicating natural human responses of increased saliva viscosity from stress and reduced saliva content from either stress or illness. These responses both favorably correspond to reduced transmissibility. Such a finding also relates to potential control methods, hence, we compared results to a surgical mask. In general, we find that saliva alteration can produce fewer and larger droplets with less content and aerosols. Such results indicate a novel approach to alter SARS-CoV-2’s transmission path and may act as a way to control the COVID-19 pandemic, as well as influenza and the common cold.

The specific processes that facilitate pathogen transmission are poorly understood, particularly for wild animal populations. A major impediment for investigating transmission pathways is the need for simultaneous information on host contacts and pathogen transfer. In this study, we used commensal Escherichia coli strains as a model system for gastrointestinal pathogens. We combined strain-sharing information with detailed host contact data to investigate transmission routes in mountain brushtail possums. Despite E. coli being transmitted via the faecal-oral route, we revealed that, strain-sharing among possums was better explained by host contacts than spatial proximity. Furthermore, and unexpectedly, strain-sharing was more strongly associated with the duration of brief nocturnal associations than day-long den-sharing. Thus, the most cryptic and difficult associations to measure were the most relevant connections for the transmission of this symbiont. We predict that future studies that employ similar approaches will reveal the importance of previously overlooked associations as key transmission pathways.

BackgroundBecause of complex interactions of climate variables at the levels of the pathogen, vector, and host, the potential influence of climate change on vector-borne and zoonotic diseases (VBZDs) is poorly understood and difficult to predict. Climate effects on the nonvector-borne zoonotic diseases are especially obscure and have received scant treatment.ObjectiveWe described known and potential effects of climate change on VBZDs and proposed specific studies to increase our understanding of these effects. The nonvector-borne zoonotic diseases have received scant treatment and are emphasized in this paper.Data sources and synthesisWe used a review of the existing literature and extrapolations from observations of short-term climate variation to suggest potential impacts of climate change on VBZDs. Using public health priorities on climate change, published by the Centers for Disease Control and Prevention, we developed six specific goals for increasing understanding of the interaction between climate and VBZDs and for improving capacity for predicting climate change effects on incidence and distribution of VBZDs.ConclusionsClimate change may affect the incidence of VBZDs through its effect on four principal characteristics of host and vector populations that relate to pathogen transmission to humans: geographic distribution, population density, prevalence of infection by zoonotic pathogens, and the pathogen load in individual hosts and vectors. These mechanisms may interact with each other and with other factors such as anthropogenic disturbance to produce varying effects on pathogen transmission within host and vector populations and to humans. Because climate change effects on most VBZDs act through wildlife hosts and vectors, understanding these effects will require multidisciplinary teams to conduct and interpret ecosystem-based studies of VBZD pathogens in host and vector populations and to identify the hosts, vectors, and pathogens with the greatest potential to affect human populations under climate change scenarios.

Genetic variation for disease resistance within host populations can strongly impact the spread of endemic pathogens. In plants, recent work has shown that within-population variation in resistance can also affect the transmission of foreign spillover pathogens if that resistance is general. However, most hosts also possess specific resistance mechanisms that provide strong defenses against coevolved endemic pathogens. Here we use a modeling approach to ask how antagonistic coevolution between hosts and their endemic pathogen at the specific resistance locus can affect the frequency of general resistance, and therefore a host's vulnerability to foreign pathogens. We develop a two-locus model with variable recombination that incorporates both general resistance (effective against all pathogens) and specific resistance (effective against endemic pathogens only). With coevolution, when pathogens can evolve to evade specific resistance, we find that the regions where general resistance can evolve are greatly expanded, decreasing the risk of foreign pathogen invasion. Furthermore, coevolution greatly expands the conditions that maintain polymorphisms at both resistance loci, thereby driving greater genetic diversity within host populations. This genetic diversity often leads to positive correlations between host resistance to foreign and endemic pathogens, similar to those observed in natural populations. However, if resistance loci become linked, the resistance correlations can shift to negative. If we include a third linkage-modifying locus in our model, we find that selection often favors complete linkage. Our model demonstrates how coevolutionary dynamics with an endemic pathogen can mold the resistance structure of host populations in ways that affect its susceptibility to foreign pathogen spillovers, and that the nature of these outcomes depends on resistance costs, as well as the degree of linkage between resistance genes.

Many eukaryotes host mutualistic, maternally transmitted prokaryotic symbionts. Two kinds of evolution within symbiont genomes threaten to erode the benefits of these associations. First, because symbionts reproduce asexually, are sequestered within hosts, and undergo bottlenecks at infection, they are subject to the long‐term accumulation of deleterious mutations through Muller’s ratchet. Second, “selfish” mutations, benefiting symbionts at host expense, could cause the ultimate decline of both host and symbionts. We performed simulations to assess how the fate of each mutation type is affected by host population size, numbers of symbionts transmitted to progeny, selection within and between hosts, and mutation rate. Fixation rate always increases with decreasing host population size. However, fixation rates for uniformly deleterious and selfish mutations are oppositely affected by varying transmission numbers, with increased numbers slowing accumulation of strictly deleterious mutations, especially for effects concentrated within hosts, but speeding fixation of “selfish” mutations. In aphid symbionts, most genes underlie basic cellular processes and are probably selected at both levels, but a substantial minority of genes contribute only to host fitness. No inoculum size is optimal for minimizing deleterious evolution for both categories of gene.

Event Abstract Back to Event Spatial dynamics of transmission and persistence of African swine fever in wild boar populations: insight for control Kim M. Pepin1* 1 National Wildlife Research Center, Animal and Plant Health Inspection Service, United States ASF is a devastating disease for swine producers that is hypothesized to persist in wild boar populations in Eastern Europe through contact with contaminated carcasses and/or continual re-introductions, depending on host density and spatial ecology. However, the role of different transmission and persistence mechanisms remain poorly understood despite their importance for planning allocation of surveillance and control resources across space. We predicted that carcass-based transmission would be important for persistence, especially in low-density host populations because carcasses can increase transmission probability when contact rates are low. We also predicted that host density and social structure would be important for predicting the amount of environmental transmission. We developed a spatially-explicit model of African swine fever (ASF) in wild boar, and fit the model to surveillance data from Eastern Poland (2014-16) using Approximate Bayesian Computation. A total of 4625 wild boar samples were collected through hunters and 271 samples were through reports of dead carcasses. Thus, hunter harvests made up most of the surveillance samples (94.5%). We estimated new introduction rates, and daily probabilities of direct and carcass-based transmission that best explained the data. Our prior distributions were vague such that new introduction rates ranged from a single event to 60 introductions per year (i.e., continuous spillover at the border). Likewise for transmission probabilities by both mechanisms, we considered prior distributions where the probabilities ranged from no transmission to transmission to all neighbors daily. This design allowed us to quantify the relative role of these three persistence mechanisms at explaining the data. We also evaluated three different spatial models of contact structure, a process that is poorly understood, to identify which spatial processes are important for prediction and to account for their uncertainty. Using estimated parameters we derived the relative number of direct and carcass-based transmission events that most likely occurred to generate the observed data. To understand the potential role of carcass-based transmission beyond this particular outbreak, we conducted sensitivity analyses on the three parameters that affect persistence: introduction frequency, direct transmission probability, and carcass-based transmission probability; over a range of host population densities. The purpose of this latter analysis was to understand how host density drives mechanisms of persistence. We inferred that between 50-68% of transmission events occurred through contact with a contaminated carcass, depending on host density and contact structure. Carcass-based transmission was higher at low host density and when social grouping was considered in the contact structure. Carcass-based transmission was necessary for autonomous persistence under realistic parameters for this system. Autonomous persistence by direct transmission alone required higher host densities. Persistence also became possible with direct transmission alone when re-introductions occurred more than once per year and direct transmission probabilities were moderately high. We showed how the relative role of different persistence mechanisms can differ based on small changes in host population density and assumptions about spatial contact processes. Social structure was an important consideration to capture along with standard spatial spreading processes in order to best explain the data, and thus infer of the role of different transmission mechanisms. Management policies should emphasize removal of carcasses and consider how reductions in host densities may affect carcass-based transmission. Understanding the ecological conditions that determine the frequency of different transmission mechanisms is important for choosing optimal management strategies across different ecological contexts. Acknowledgements KMP was funded by the USDA-APHIS National Feral Swine Damage Management Program. TP was supported by the National Science Centre, Poland (grant number 2014/15/B/NZ9/01933). We thank M. Łyjak, A. Kowalczyk, K. Śmietanka, and G. Woźniakowski from Department of Swine Diseases, National Veterinary Research Institute in Pulawy, Poland, for surveillance data. N. Selva provided valuable information on carcass persistence time. Keywords: African Swine Fever, wild boar, Approximate Bayesian Computation, Spatially-explicit transmission model, Contact structure, environmental transmission, Disease persistence Conference: GeoVet 2019. Novel spatio-temporal approaches in the era of Big Data, Davis, United States, 8 Oct - 10 Oct, 2019. Presentation Type: Regular oral presentation Topic: Special topic on African Swine Fever (ASF) Citation: Pepin KM (2019). Spatial dynamics of transmission and persistence of African swine fever in wild boar populations: insight for control. Front. Vet. Sci. Conference Abstract: GeoVet 2019. Novel spatio-temporal approaches in the era of Big Data. doi: 10.3389/conf.fvets.2019.05.00009 Copyright: The abstracts in this collection have not been subject to any Frontiers peer review or checks, and are not endorsed by Frontiers. They are made available through the Frontiers publishing platform as a service to conference organizers and presenters. The copyright in the individual abstracts is owned by the author of each abstract or his/her employer unless otherwise stated. Each abstract, as well as the collection of abstracts, are published under a Creative Commons CC-BY 4.0 (attribution) licence (https://creativecommons.org/licenses/by/4.0/) and may thus be reproduced, translated, adapted and be the subject of derivative works provided the authors and Frontiers are attributed. For Frontiers’ terms and conditions please see https://www.frontiersin.org/legal/terms-and-conditions. Received: 20 Jun 2019; Published Online: 27 Sep 2019. * Correspondence: Mx. Kim M Pepin, National Wildlife Research Center, Animal and Plant Health Inspection Service, Fort Collins, United States, kim.m.pepin@usda.gov Login Required This action requires you to be registered with Frontiers and logged in. To register or login click here. Abstract Info Abstract The Authors in Frontiers Kim M Pepin Google Kim M Pepin Google Scholar Kim M Pepin PubMed Kim M Pepin Related Article in Frontiers Google Scholar PubMed Abstract Close Back to top Javascript is disabled. Please enable Javascript in your browser settings in order to see all the content on this page.

While disease is widely recognized as affecting host population size, it has rarely been considered to play a role in determining host range limits. Many diseases may not be able to persist near the range limit if host population density falls below the critical threshold level for pathogen invasion. However, in vector‐ and sexually transmitted diseases, pathogen transmission may be largely independent of host density and theory demonstrates that diseases with frequency‐dependent transmission may persist in small populations near the range limit. Empirical studies of disease at species range limits have lagged behind the theory, and to date, no previous study has tested the hypothesis that vector or sexually transmitted diseases can be maintained at host range limits. We studied the distribution of anther‐smut disease, a sterilizing pollinator‐transmitted disease, on four alpine plant species to determine whether disease was present at the host range limits. We found that host abundance declined towards the elevational range limits, and disease extended to the most extreme elevational range limits in three of the four host species. Maximum likelihood estimation of the magnitude of the disease‐free halo showed that it was small or nonexistent for all host species. Moreover, disease prevalence within populations was often higher nearer the host's range limit than in the range centre and was independent of host density. Synthesis. Our results show that diseases where transmission is frequency‐dependent have the potential to affect host distributions not just in theory, but also in real world populations.

Impacts of deer management practices on the spatial dynamics of the tick Ixodes ricinus: A scenario analysis

BRCAPRO and Myriad II are widely used models for predicting BRCA1/2 mutation probability before genetic testing. However, the accuracy of these models in Koreans is not known. This study was performed to evaluate the accuracy of the BRCAPRO and Myriad II models. Two hundred thirty-six women with breast cancer who underwent comprehensive BRCA1/2 genetic testing at our hospital between 2003 and 2010 were included in this study. We evaluated the performance of each model by comparing the numbers of observed versus predicted mutation carriers. We calculated sensitivity, specificity, and predictive values at 10 % estimated probability. Forty-six individuals were identified to carry a deleterious BRCA mutation. The prevalence of BRCA mutation (19.5 %) was significantly higher than that predicted by BRCAPRO (9.0 %, p = 0.001) and Myriad (5.6 %, p < 0.001). In familial breast cancer patients, BRCA mutation rate (observed 22.7 %) was underestimated by both BRCAPRO (expected 11.4 %, p = 0.006) and Myriad II (expected 6.4 %, p < 0.001). Subgroup analyses showed that both models underestimated the risk of BRCA mutation in patients with a family history of breast cancer (probands' age at breast cancer diagnosis >50 years), with only one relative with breast cancer, and with non-familial early-onset breast cancer or bilateral breast cancer. Using a 10 % cut-off, the sensitivities were 47.8 % (BRCAPRO) and 50.0 % (Myriad), and positive predictive values were 44.9 % (BRCAPRO) and 43.4 % (Myriad). Both BRCAPRO and Myriad II underestimated the risk of BRCA1/2 mutation in Koreans. Our findings suggest that these models are less sensitive in Korean women, and therefore a new BRCA mutation prediction model based on Korean data is needed for proper genetic counseling.

Preventing pathogenic viral and bacterial transmission in the human environment is critical, especially in potential outbreaks that may be caused by the release of ancient bacteria currently trapped in the permafrost. Existing commercial disinfectants present issues such as a high carbon footprint. This study proposes a sustainable alternative, a bioliquid derived from biomass prepared by hydrothermal liquefaction. Results indicate a high inactivation rate of pathogenic virus and bacteria by the as-prepared bioliquid, such as up to 99.99% for H1N1, H5N1, H7N9 influenza A virus, and Bacillus subtilis var. niger spores and 99.49% for Bacillus anthracis. Inactivation of Escherichia coli and Staphylococcus epidermidis confirmed that low-molecular-weight and low-polarity compounds in bioliquid are potential antibacterial components. High temperatures promoted the production of antibacterial substances via depolymerization and dehydration reactions. Moreover, bioliquid was innoxious as confirmed by the rabbit skin test, and the cost per kilogram of the bioliquid was $0.04427, which is notably lower than that of commercial disinfectants. This study demonstrates the potential of biomass to support our biosafety with greater environmental sustainability.

Avian influenza (AI) H5N1 virus consider a potential threat to the poultry industry with sever zoonotic effect associated with a high risk on human being associated with the poultry production. The disease become endemic in Egypt and cause more than 359 confirmed human infection cases in the last few years. Samples (serum and tissues) collected from 160 poultry farms that suspected to be infected with H5N1. Samples were collected from 75 broiler chicken farms, 55 broiler duck farms and 30 layer duck farms. As well as 115 human samples (serum and throat swabs) collected from persons suffering from respiratory manifestations and have a history of contact with infected birds. Samples were examined using Haemagglutination inhibition (HI) test and Reverse Transcription Real Time PCR (RT- qPCR) for detection of avian influenza H5N1 virus. HI test detect H5N1 antibodies in 71 poultry samples out of 160 (44.4%). While, RT- qPCR detect H5N1 in 13 out of 160 samples (8.1%). On the other hand, HI test detect H5N1 antibodies in six human sample out of 115 human cases (5.2%) while, RT- qPCR detect H5N1 in two human samples out of 115 human cases (1.7%). There was an increase in rate of highly pathogenic avian influenza transmission from poultry-to-human. Adaption of AI virus was increased to duck flocks with higher percentage of vaccinal escape. Thus, there is a need to give more attention to the vaccination programs and increasing the usage of the vaccines prepared from Egyptian H5N1 virus or update the current vaccines with the isolates representing the circulating virus in the Egyptian market. All these measures will increase the protection level in poultry farms and intern decrease the risk of human infection rates.

1. The hypothesis that habitat fragmentation (biotic or abiotic) alters the transmission of disease within a population is explored using field data from a well-studied amphibian-pathogen system. 2. We used the Ambystoma tigrinum-A. tigrinum virus (ATV) model system to show how habitat fragmentation as a result of emergent vegetation and habitat management affects disease transmission dynamics in ponds across a landscape. 3. We quantified variation in ATV infection over time and across the landscape. ATV infection was significantly higher in ponds modified for livestock use (P = 0.032). Disease incidence decreased with increased amounts of emergent vegetation (P < 0.001). These factors appear to control disease transmission by altering the host contact rate and with it disease transmission. 4. A field experiment to test the effect of emergent vegetation on the distribution of larvae in ponds demonstrated a behavioural change in larvae found in sparsely vegetated ponds. Microhabitat choices resulted in larvae being concentrated at the pond edge resulting in a 'halo effect' in sparsely vegetated ponds, whereas larvae in heavily vegetated ponds were distributed more evenly throughout. Microhabitat choice affects the effective density that larvae experience. This 'halo effect' increases contact rates in the shallows of sparsely vegetated ponds and increases the transmission of a directly transmitted pathogen. 5. Despite recurrent epidemics of a lethal Ranavirus in tiger salamanders on the Kaibab Plateau, Arizona, USA, these populations persist. We discuss the implications of our results in the context of density-dependent transmission and homogeneous mixing, two increases key assumptions of epidemiological theory.