scholarly journals Parasite-induced shifts in host movement may explain the transient coexistence of high- and low-pathogenic disease strains

2019 ◽  
Author(s):  
Abdou Moutalab Fofana ◽  
Amy Hurford
Keyword(s):  
Rapid Evolution ◽  
Population Level ◽  
Disease Spread ◽  
Medical Interventions ◽  
Individual Host ◽  
High Virulence ◽  
Human Immunodeficiency Viruses ◽  
The Individual ◽  
Host Parasite ◽  
Host Movement

AbstractMany parasites induce decreased host movement, known as lethargy, which can impact disease spread and the evolution of virulence. Mathematical models have investigated virulence evolution when parasites cause host death, but disease-induced decreased host movement has received relatively less attention. Here, we consider a model where, due to the within-host parasite replication rate, an infected host can become lethargic and shift from a moving to a resting state, where it can die. We find that when the lethargy and disease-induced mortality costs to the parasites are not high, then evolutionary bistability can arise, and either moderate or high virulence can evolve depending on the initial virulence and the magnitude of mutation. These results suggest, firstly, the transient coexistence of strains with different virulence, which may explain the coexistence of low- and high-pathogenic strains of avian influenza and human immunodeficiency viruses, and secondly, that medical interventions to treat the symptoms of lethargy or prevent disease-induced host deaths can result in a large jump in virulence and the rapid evolution of high virulence. In complement to existing results that show bistability when hosts are heterogeneous at the population-level, we show that evolutionary bistability may arise due to transmission heterogeneity at the individual host-level.

scholarly journals Parasite-mediated anorexia increases or decreases virulence evolution, depending on dietary context

2018 ◽  
Author(s):  
J. L. Hite ◽  
C. E. Cressler
Keyword(s):  
Food Intake ◽  
Population Level ◽  
Parasite Development ◽  
Infection Prevalence ◽  
Individual Level ◽  
Physiological Processes ◽  
Gastrointestinal Conditions ◽  
The Individual ◽  
Spread Of Infection ◽  
Host Parasite

AbstractParasite-mediated anorexia is a ubiquitous, but poorly understood component of host-parasite interactions. These temporary but substantial reductions in food intake (range: 4-100%) limit exposure to parasites and alter within-host physiological processes that regulate parasite development, production, and survival, such as energy allocation, immune function, host-microbiota interactions, and gastrointestinal conditions. By altering the duration, severity, and spread of infection, anorexia could substantially alter ecological, evolutionary, and epidemiological dynamics. However, these higher-order implications are typically overlooked and remain poorly understood — even though medical (e.g., non-steroidal anti-inflammatory drugs, vaccines, targeted signaling pathways, calorie restriction) and husbandry practices (e.g., antibiotic and diet use for rapid growth, nutrient supplementation) often directly or indirectly alter host appetite and nutrient intake. Here, we develop theory that helps elucidate why reduced food intake (anorexia) can enhance or diminish disease severity and illustrates that the population-level outcomes often contrast with the individual-level outcomes: treatments that increase the intake of high quality nutrients (suppressing anorexia), can drive rapid individual-level recovery, but inadvertently increase infection prevalence and select for more virulent parasites. Such a theory-guided approach offers a tool to improve targeting host nutrition to manage disease in both human and livestock populations by revealing a means to predict how nutrient-driven feedbacks will affect both the host and parasite.

Optimality analysis of Th1/Th2 immune responses during microparasite-macroparasite co-infection, with epidemiological feedbacks

Parasitology ◽  
2008 ◽  
Vol 135 (7) ◽  
pp. 841-853 ◽  
Author(s):  
ANDY FENTON ◽  
TRACEY LAMB ◽  
ANDREA L. GRAHAM
Keyword(s):  
Immune Responses ◽  
Population Level ◽  
Parasite Abundance ◽  
Individual Level ◽  
Host Immune Responses ◽  
Individual Host ◽  
Diverse Community ◽  
The Individual ◽  
Optimality Models

SUMMARYIndividuals are typically co-infected by a diverse community of microparasites (e.g. viruses or protozoa) and macroparasites (e.g. helminths). Vertebrates respond to these parasites differently, typically mounting T helper type 1 (Th1) responses against microparasites and Th2 responses against macroparasites. These two responses may be antagonistic such that hosts face a ‘decision’ of how to allocate potentially limiting resources. Such decisions at the individual host level will influence parasite abundance at the population level which, in turn, will feed back upon the individual level. We take a first step towards a complete theoretical framework by placing an analysis of optimal immune responses under microparasite-macroparasite co-infection within an epidemiological framework. We show that the optimal immune allocation is quantitatively sensitive to the shape of the trade-off curve and qualitatively sensitive to life-history traits of the host, microparasite and macroparasite. This model represents an important first step in placing optimality models of the immune response to co-infection into an epidemiological framework. Ultimately, however, a more complete framework is needed to bring together the optimal strategy at the individual level and the population-level consequences of those responses, before we can truly understand the evolution of host immune responses under parasite co-infection.

scholarly journals Overcoming Reporting Delays Is Critical to Timely Epidemic Monitoring: The Case of COVID-19 in New York City

2020 ◽  
Author(s):  
Jeffrey E Harris
Keyword(s):  
New York ◽  
New York City ◽  
Statistical Method ◽  
York City ◽  
Population Level ◽  
Disease Spread ◽  
Individual Level ◽  
Specimen Processing ◽  
Reporting Delays ◽  
The Individual

During a fast-moving epidemic, timely monitoring of case counts and other key indicators of disease spread is critical to an effective public policy response. We describe a nonparametric statistical method - originally applied to the reporting of AIDS cases in the 1980s - to estimate the distribution of reporting delays of confirmed COVID-19 cases in New York City. During June 21 - August 1, 2020, the estimated mean delay in reporting was 5 days, with 15 percent of cases reported after 10 or more days. Relying upon the estimated reporting-delay distribution, we project COVID-19 incidence during the most recent three weeks as if each case had instead been reported on the same day that the underlying diagnostic test had been performed. The statistical method described here overcomes the problem of reporting delays only at the population level. The method does not eliminate reporting delays at the individual level. That will require improvements in diagnostic technology, test availability, and specimen processing.

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.

The Nature of Host–Pathogen Interactions

2021 ◽  
pp. 7-28
Author(s):  
Jennifer C. Owen ◽  
James S. Adelman ◽  
Amberleigh E. Henschen
Keyword(s):  
Infectious Disease ◽  
Disease Ecology ◽  
Population Level ◽  
Host Pathogen Interactions ◽  
Epidemiological Modeling ◽  
Individual Host ◽  
Host Pathogen ◽  
Multiple Meanings ◽  
The Individual ◽  
In The Beginning

The dynamics of infectious disease are driven by the fundamental processes that mediate host–pathogen interactions. A basic understanding of the mechanisms underlying these interactions is essential for disease ecologists regardless of their scale of inquiry. This chapter covers the terms and concepts commonly used in ecological studies of infectious disease across levels of organization and scales of inquiry, from the individual host organism to host populations and multispecies communities. When applicable, aspects that are unique to birds and their biology are highlighted. The between-host processes discussed in the beginning of the chapter arise from the within-host processes between the pathogen and the host’s immune system. These processes are then used as a framework to introduce the basics of epidemiological modeling and the population-level disease dynamics. The chapter is not meant to be exhaustive but, instead, to provide a common foundation for readers approaching this topic from unique backgrounds. Given the transdisciplinary nature of avian infectious disease ecology, many of the terms used have multiple meanings assigned to them that are taxon- or discipline-specific. Such variation in key terminology is, in large part, a consequence of the transdisciplinary and multiscaled approaches inherent in studying host–pathogen–vector–environment interactions.

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 Linking Bioenergetics and Parasite Transmission Models Suggests Mismatch Between Snail Host Density and Production of Human Schistosomes

2019 ◽  
Vol 59 (5) ◽  
pp. 1243-1252 ◽  
Author(s):  
Matthew Malishev ◽  
David J Civitello
Keyword(s):  
Host Density ◽  
Population Level ◽  
Immune Defense ◽  
Parasite Transmission ◽  
Host Snail ◽  
Individual Level ◽  
High Resource ◽  
Parasite Ecology ◽  
The Individual ◽  
Host Parasite

Abstract 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 of 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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