scholarly journals Population-Level Disease Dynamics Reflect Individual Heterogeneities in Transmission

2019 ◽  
Author(s):  
Jonathon A. Siva-Jothy ◽  
Lauren A. White ◽  
Meggan E. Craft ◽  
Pedro F. Vale
Keyword(s):  
Social Network ◽  
Disease Transmission ◽  
Network Connectivity ◽  
Population Level ◽  
Disease Dynamics ◽  
Virus Shedding ◽  
Transmission Potential ◽  
Social Aggregation ◽  
Individual Host ◽  
Host Heterogeneity

AbstractHost heterogeneity in disease transmission is widespread and presents a major hurdle to predicting and minimizing pathogen spread. Using the Drosophila melanogaster model system infected with Drosophila C virus, we integrate experimental measurements of individual host heterogeneity in social aggregation, virus shedding, and disease-induced mortality into an epidemiological framework that simulates outbreaks of infectious disease. We use these simulations to calculate individual variation in disease transmission and apportion this variation to specific components of transmission: social network degree distribution, infectiousness, and infection duration. The experimentally-observed variation produces substantial differences in individual transmission potential, providing evidence for genetic and sex-specific effects on disease dynamics at a population level. Manipulating variation in social network connectivity, infectiousness, and infection duration in simulated populations reveals that these components affect disease transmission in clear and distinct ways. We consider the implications of this genetic and sex-specific variation in disease transmission and discuss implications for appropriate control methods given the relative contributions made by social aggregation, virus shedding, and infection duration to transmission in other host-pathogen systems.

scholarly journals Genotype and sex-based host variation in behaviour and susceptibility drives population disease dynamics

2020 ◽  
Vol 287 (1938) ◽  
pp. 20201653
Author(s):  
Lauren A. White ◽  
Jonathon A. Siva-Jothy ◽  
Meggan E. Craft ◽  
Pedro F. Vale
Keyword(s):  
Disease Outbreaks ◽  
Population Level ◽  
Population Diversity ◽  
Pathogen Transmission ◽  
Disease Dynamics ◽  
Susceptible Population ◽  
Virus Shedding ◽  
Social Aggregation ◽  
Modelling Framework ◽  
Host Heterogeneity

Host heterogeneity in pathogen transmission is widespread and presents a major hurdle to predicting and minimizing disease outbreaks. Using Drosophila melanogaster infected with Drosophila C virus as a model system, we integrated experimental measurements of social aggregation, virus shedding, and disease-induced mortality from different genetic lines and sexes into a disease modelling framework. The experimentally measured host heterogeneity produced substantial differences in simulated disease outbreaks, providing evidence for genetic and sex-specific effects on disease dynamics at a population level. While this was true for homogeneous populations of single sex/genetic line, the genetic background or sex of the index case did not alter outbreak dynamics in simulated, heterogeneous populations. Finally, to explore the relative effects of social aggregation, viral shedding and mortality, we compared simulations where we allowed these traits to vary, as measured experimentally, to simulations where we constrained variation in these traits to the population mean. In this context, variation in infectiousness, followed by social aggregation, was the most influential component of transmission. Overall, we show that host heterogeneity in three host traits dramatically affects population-level transmission, but the relative impact of this variation depends on both the susceptible population diversity and the distribution of population-level variation.

scholarly journals Dissecting genetic and sex-specific sources of host heterogeneity in pathogen shedding and spread

2021 ◽  
Vol 17 (1) ◽  
pp. e1009196
Author(s):  
Jonathon A. Siva-Jothy ◽  
Pedro F. Vale
Keyword(s):  
Viral Load ◽  
Individual Variation ◽  
Disease Transmission ◽  
Genetic Background ◽  
Pathogen Transmission ◽  
Published Data ◽  
Virus Shedding ◽  
Transmission Potential ◽  
Sources Of Variation ◽  
Host Heterogeneity

Host heterogeneity in disease transmission is widespread but precisely how different host traits drive this heterogeneity remains poorly understood. Part of the difficulty in linking individual variation to population-scale outcomes is that individual hosts can differ on multiple behavioral, physiological and immunological axes, which will together impact their transmission potential. Moreover, we lack well-characterized, empirical systems that enable the quantification of individual variation in key host traits, while also characterizing genetic or sex-based sources of such variation. Here we used Drosophila melanogaster and Drosophila C Virus as a host-pathogen model system to dissect the genetic and sex-specific sources of variation in multiple host traits that are central to pathogen transmission. Our findings show complex interactions between genetic background, sex, and female mating status accounting for a substantial proportion of variance in lifespan following infection, viral load, virus shedding, and viral load at death. Two notable findings include the interaction between genetic background and sex accounting for nearly 20% of the variance in viral load, and genetic background alone accounting for ~10% of the variance in viral shedding and in lifespan following infection. To understand how variation in these traits could generate heterogeneity in individual pathogen transmission potential, we combined measures of lifespan following infection, virus shedding, and previously published data on fly social aggregation. We found that the interaction between genetic background and sex explained ~12% of the variance in individual transmission potential. Our results highlight the importance of characterising the sources of variation in multiple host traits to understand the drivers of heterogeneity in disease transmission.

scholarly journals Deposition of pathogenic Mycoplasma gallisepticum onto bird feeders: host pathology is more important than temperature-driven increases in food intake

2013 ◽  
Vol 9 (5) ◽  
pp. 20130594 ◽  
Author(s):  
James S. Adelman ◽  
Amanda W. Carter ◽  
William A. Hopkins ◽  
Dana M. Hawley
Keyword(s):  
Food Intake ◽  
Ambient Temperature ◽  
Disease Transmission ◽  
Population Level ◽  
Mycoplasma Gallisepticum ◽  
Pathogen Transmission ◽  
Disease Dynamics ◽  
Transmission Potential ◽  
Thermoneutral Zone ◽  
Bird Feeders

Although ambient temperature has diverse effects on disease dynamics, few studies have examined how temperature alters pathogen transmission by changing host physiology or behaviour. Here, we test whether reducing ambient temperature alters host foraging, pathology and the potential for fomite transmission of the bacterial pathogen Mycoplasma gallisepticum (MG), which causes seasonal outbreaks of severe conjunctivitis in house finches ( Haemorhous mexicanus ). We housed finches at temperatures within or below the thermoneutral zone to manipulate food intake by altering energetic requirements of thermoregulation. We predicted that pathogen deposition on bird feeders would increase with temperature-driven increases in food intake and with conjunctival pathology. As expected, housing birds below the thermoneutral zone increased food consumption. Despite this difference, pathogen deposition on feeders did not vary across temperature treatments. However, pathogen deposition increased with conjunctival pathology, independently of temperature and pathogen load, suggesting that MG could enhance its transmission by increasing virulence. Our results suggest that in this system, host physiological responses are more important for transmission potential than temperature-dependent alterations in feeding. Understanding such behavioural and physiological contributions to disease transmission is critical to linking individual responses to climate with population-level disease dynamics.

scholarly journals Comparing transmission potential networks based on social network surveys, close contacts and environmental overlap in rural Madagascar

2022 ◽  
Vol 19 (186) ◽  
Author(s):  
Kayla Kauffman ◽  
Courtney S. Werner ◽  
Georgia Titcomb ◽  
Michelle Pender ◽  
Jean Yves Rabezara ◽  
...  
Keyword(s):  
Social Network ◽  
Spatial Data ◽  
Disease Transmission ◽  
Close Contact ◽  
Pathogen Transmission ◽  
Centrality Measures ◽  
Data Types ◽  
Transmission Potential ◽  
Spatial Network Analysis ◽  
Transmission Pathways

Social and spatial network analysis is an important approach for investigating infectious disease transmission, especially for pathogens transmitted directly between individuals or via environmental reservoirs. Given the diversity of ways to construct networks, however, it remains unclear how well networks constructed from different data types effectively capture transmission potential. We used empirical networks from a population in rural Madagascar to compare social network survey and spatial data-based networks of the same individuals. Close contact and environmental pathogen transmission pathways were modelled with the spatial data. We found that naming social partners during the surveys predicted higher close-contact rates and the proportion of environmental overlap on the spatial data-based networks. The spatial networks captured many strong and weak connections that were missed using social network surveys alone. Across networks, we found weak correlations among centrality measures (a proxy for superspreading potential). We conclude that social network surveys provide important scaffolding for understanding disease transmission pathways but miss contact-specific heterogeneities revealed by spatial data. Our analyses also highlight that the superspreading potential of individuals may vary across transmission modes. We provide detailed methods to construct networks for close-contact transmission pathogens when not all individuals simultaneously wear GPS trackers.

scholarly journals Dissecting genetic and sex-specific host heterogeneity in pathogen transmission potential

2019 ◽  
Author(s):  
Jonathon A. Siva-Jothy ◽  
Pedro F. Vale
Keyword(s):  
Viral Load ◽  
Disease Transmission ◽  
Genetic Background ◽  
Pathogen Transmission ◽  
Virus Shedding ◽  
Transmission Potential ◽  
Individual Level ◽  
Sources Of Variation ◽  
Specific Variation ◽  
The Individual

AbstractHeterogeneity in disease transmission is widespread and, when not accounted for, can produce unpredictable outbreaks of infectious disease. Despite this, precisely how different sources of variation in host traits drive heterogeneity in disease transmission is poorly understood. Here we dissected the sources of variation in pathogen transmission using Drosophila melanogaster and Drosophila C Virus as a host-pathogen model system. We found that infected lifespan, viral growth, virus shedding, and viral load at death were all significantly influenced by fly genetic background, sex and female mating status. To understand how variation in each of these traits may generate heterogeneity in disease transmission, we estimated individual transmission potential by integrating data on virus shedding and lifespan alongside previously collected data on social aggregation. We found that ∼15% of between-individual heterogeneity in disease transmission was explained by a significant interaction between genetic and sex-specific variation. We also characterised the amount of variation in viral load, virus shedding, and lifespan following infection that could be explained by genetic background and sex. Amongst the determinants of individual variation in disease transmission these sources of host variation play roles of varying importance, with genetic background generally playing the largest role. Our results highlight the importance of characterising sources of variation in multiple host traits when studying disease transmission at the individual-level.

scholarly journals Behavioural ecology and infectious disease: implications for conservation of biodiversity

2019 ◽  
Vol 374 (1781) ◽  
pp. 20180054 ◽  
Author(s):  
James Herrera ◽  
Charles L. Nunn
Keyword(s):  
Infectious Disease ◽  
Disease Transmission ◽  
Disease Ecology ◽  
Scale Up ◽  
Species Conservation ◽  
Population Level ◽  
Behavioural Ecology ◽  
Parasite Transmission ◽  
Transmission Potential ◽  
Increased Risk

Behaviour underpins interactions among conspecifics and between species, with consequences for the transmission of disease-causing parasites. Because many parasites lead to declines in population size and increased risk of extinction for threatened species, understanding the link between host behaviour and disease transmission is particularly important for conservation management. Here, we consider the intersection of behaviour, ecology and parasite transmission, broadly encompassing micro- and macroparasites. We focus on behaviours that have direct impacts on transmission, as well as the behaviours that result from infection. Given the important role of parasites in host survival and reproduction, the effects of behaviour on parasitism can scale up to population-level processes, thus affecting species conservation. Understanding how conservation and infectious disease control strategies actually affect transmission potential can therefore often only be understood through a behavioural lens. We highlight how behavioural perspectives of disease ecology apply to conservation by reviewing the different ways that behavioural ecology influences parasite transmission and conservation goals. This article is part of the theme issue ‘Linking behaviour to dynamics of populations and communities: application of novel approaches in behavioural ecology to conservation’.

A multi-scale cholera model linking between-host and within-host dynamics

2018 ◽  
Vol 11 (03) ◽  
pp. 1850034
Author(s):  
Chayu Yang ◽  
Drew Posny ◽  
Feng Bao ◽  
Jin Wang
Keyword(s):  
Human Body ◽  
Population Level ◽  
Sir Model ◽  
Disease Dynamics ◽  
Modeling Framework ◽  
Multi Scale ◽  
Scale Modeling ◽  
Individual Host ◽  
Multi Scale Modeling ◽  
The Individual

We propose a multi-scale modeling framework to investigate the transmission dynamics of cholera. At the population level, we employ a SIR model for the between-host transmission of the disease. At the individual host level, we describe the evolution of the pathogen within the human body. The between-host and within-host dynamics are connected through an environmental equation that characterizes the growth of the pathogen and its interaction with the hosts outside the human body. We put a special emphasis on the within-host dynamics by making a distinction for each individual host. We conduct both mathematical analysis and numerical simulation for our model in order to explore various scenarios associated with cholera transmission and to better understand the complex, multi-scale disease dynamics.

scholarly journals Transient disease dynamics across ecological scales

2021 ◽  
Author(s):  
Yun Tao ◽  
Jessica L. Hite ◽  
Kevin D. Lafferty ◽  
David J. D. Earn ◽  
Nita Bharti
Keyword(s):  
Disease Transmission ◽  
Movement Ecology ◽  
Pathogen Transmission ◽  
Disease Spread ◽  
Transient Dynamics ◽  
Transmission Potential ◽  
Movement Dynamics ◽  
Individual Host ◽  
Ecological Hierarchy ◽  
The Individual

AbstractAnalyses of transient dynamics are critical to understanding infectious disease transmission and persistence. Identifying and predicting transients across scales, from within-host to community-level patterns, plays an important role in combating ongoing epidemics and mitigating the risk of future outbreaks. Moreover, greater emphases on non-asymptotic processes will enable timely evaluations of wildlife and human diseases and lead to improved surveillance efforts, preventive responses, and intervention strategies. Here, we explore the contributions of transient analyses in recent models spanning the fields of epidemiology, movement ecology, and parasitology. In addition to their roles in predicting epidemic patterns and endemic outbreaks, we explore transients in the contexts of pathogen transmission, resistance, and avoidance at various scales of the ecological hierarchy. Examples illustrate how (i) transient movement dynamics at the individual host level can modify opportunities for transmission events over time; (ii) within-host energetic processes often lead to transient dynamics in immunity, pathogen load, and transmission potential; (iii) transient connectivity between discrete populations in response to environmental factors and outbreak dynamics can affect disease spread across spatial networks; and (iv) increasing species richness in a community can provide transient protection to individuals against infection. Ultimately, we suggest that transient analyses offer deeper insights and raise new, interdisciplinary questions for disease research, consequently broadening the applications of dynamical models for outbreak preparedness and management.

scholarly journals Livestock movement informs the risk of disease spread in traditional production systems in East Africa

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Divine Ekwem ◽  
Thomas A. Morrison ◽  
Richard Reeve ◽  
Jessica Enright ◽  
Joram Buza ◽  
...  
Keyword(s):  
Disease Transmission ◽  
Production Systems ◽  
Control Strategies ◽  
Herd Size ◽  
Transmission Risk ◽  
Disease Spread ◽  
Transmission Potential ◽  
Spatial And Temporal Scales ◽  
Transmission Distance ◽  
Risk Of Disease

AbstractIn Africa, livestock are important to local and national economies, but their productivity is constrained by infectious diseases. Comprehensive information on livestock movements and contacts is required to devise appropriate disease control strategies; yet, understanding contact risk in systems where herds mix extensively, and where different pathogens can be transmitted at different spatial and temporal scales, remains a major challenge. We deployed Global Positioning System collars on cattle in 52 herds in a traditional agropastoral system in western Serengeti, Tanzania, to understand fine-scale movements and between-herd contacts, and to identify locations of greatest interaction between herds. We examined contact across spatiotemporal scales relevant to different disease transmission scenarios. Daily cattle movements increased with herd size and rainfall. Generally, contact between herds was greatest away from households, during periods with low rainfall and in locations close to dipping points. We demonstrate how movements and contacts affect the risk of disease spread. For example, transmission risk is relatively sensitive to the survival time of different pathogens in the environment, and less sensitive to transmission distance, at least over the range of the spatiotemporal definitions of contacts that we explored. We identify times and locations of greatest disease transmission potential and that could be targeted through tailored control strategies.

scholarly journals PDE limits of stochastic SIS epidemics on networks

2020 ◽  
Vol 8 (4) ◽  
Author(s):  
F Di Lauro ◽  
J-C Croix ◽  
L Berthouze ◽  
I Z Kiss
Keyword(s):  
Network Inference ◽  
Mean Field ◽  
Population Level ◽  
Death Process ◽  
Disease Dynamics ◽  
Epidemic Outbreak ◽  
Numerical Tests ◽  
Mean Field Models ◽  
Stochastic Epidemic ◽  
Fokker Planck Equations

Abstract Stochastic epidemic models on networks are inherently high-dimensional and the resulting exact models are intractable numerically even for modest network sizes. Mean-field models provide an alternative but can only capture average quantities, thus offering little or no information about variability in the outcome of the exact process. In this article, we conjecture and numerically demonstrate that it is possible to construct partial differential equation (PDE)-limits of the exact stochastic susceptible-infected-susceptible epidemics on Regular, Erdős–Rényi, Barabási–Albert networks and lattices. To do this, we first approximate the exact stochastic process at population level by a Birth-and-Death process (BD) (with a state space of $O(N)$ rather than $O(2^N)$) whose coefficients are determined numerically from Gillespie simulations of the exact epidemic on explicit networks. We numerically demonstrate that the coefficients of the resulting BD process are density-dependent, a crucial condition for the existence of a PDE limit. Extensive numerical tests for Regular, Erdős–Rényi, Barabási–Albert networks and lattices show excellent agreement between the outcome of simulations and the numerical solution of the Fokker–Planck equations. Apart from a significant reduction in dimensionality, the PDE also provides the means to derive the epidemic outbreak threshold linking network and disease dynamics parameters, albeit in an implicit way. Perhaps more importantly, it enables the formulation and numerical evaluation of likelihoods for epidemic and network inference as illustrated in a fully worked out example.

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