scholarly journals Spatial dynamics and genetics of infectious diseases on heterogeneous landscapes

2007 ◽  
Vol 4 (16) ◽  
pp. 935-948 ◽  
Author(s):  
Leslie A Real ◽  
Roman Biek
Keyword(s):  
Infectious Disease ◽  
Spatial Genetic Structure ◽  
Management Strategies ◽  
Spatial Dynamics ◽  
Disease Process ◽  
Disease Spread ◽  
Host Pathogen Interactions ◽  
Host Pathogen ◽  
Control And Management ◽  
And Control

Explicit spatial analysis of infectious disease processes recognizes that host–pathogen interactions occur in specific locations at specific times and that often the nature, direction, intensity and outcome of these interactions depend upon the particular location and identity of both host and pathogen. Spatial context and geographical landscape contribute to the probability of initial disease establishment, direction and velocity of disease spread, the genetic organization of resistance and susceptibility, and the design of appropriate control and management strategies. In this paper, we review the manner in which the physical organization of the landscape has been shown to influence the population dynamics and spatial genetic structure of host–pathogen interactions, and how we might incorporate landscape architecture into spatially explicit population models of the infectious disease process to increase our ability to predict patterns of disease occurrence and optimally design vaccination and control policies.

scholarly journals Next-generation technologies for studying host–pathogen interactions: a focus on dual transcriptomics, CRISPR/Cas9 screening and organs-on-chips

2019 ◽  
Vol 77 (6) ◽  
Author(s):  
Buket Baddal
Keyword(s):  
Infectious Disease ◽  
Drug Targets ◽  
Genome Mining ◽  
Three Dimensional ◽  
Local Environment ◽  
Rna Seq ◽  
Host Pathogen Interactions ◽  
Host Pathogen ◽  
On Chip ◽  
Organ Models

ABSTRACT Pathogens constantly interact with their hosts and the environment, and therefore have evolved unique virulence mechanisms to target and breach host defense barriers and manipulate host immune response to establish an infection. Advances in technologies that allow genome mining, gene editing such as CRISPR/Cas9, genomic, epigenomic and transcriptomic studies such as dual RNA-seq, coupled with bioinformatics, have accelerated the field of host–pathogen interactions within a broad range of infection models. Underpinning of the molecular changes that accompany invasion of eukaryotic cells with pathogenic microorganisms at the intersection of host, pathogen and their local environment has provided a better understanding of infectious disease mechanisms and antimicrobial strategies. The recent evolution of physiologically relevant three-dimensional (3-D) tissue/organ models and microfluidic organ-on-chip devices also provided a window to a more predictive framework of infectious disease processes. These approaches combined hold the potential to highly impact discovery of novel drug targets and vaccine candidates of the future. Here, we review three of the available and emerging technologies—dual RNA-seq, CRISPR/Cas9 screening and organs-on-chips, applicable to the high throughput study and deciphering of interaction networks between pathogens and their hosts that are critical for the development of novel therapeutics.

scholarly journals Mathematical models are a powerful method to understand and control the spread of Huanglongbing

2016 ◽  
Author(s):  
Rachel A Taylor ◽  
Erin Mordecai ◽  
Christopher A Gilligan ◽  
Jason R Rohr ◽  
Leah R Johnson
Keyword(s):  
Data Collection ◽  
Mathematical Models ◽  
Management Strategies ◽  
Intervention Strategy ◽  
Cost Effective ◽  
Plant Diseases ◽  
Disease Spread ◽  
Vector Borne ◽  
Almost All ◽  
And Control

Huanglongbing, or citrus greening, is a global citrus disease occurring in almost all citrus growing regions and causing substantial economic burdens to individual growers, citrus industries and governments. Successful management strategies to reduce disease burden are desperately needed but with so many possible interventions and combinations thereof, it is difficult to know which are worthwhile or cost-effective. We review how mathematical models have yielded useful insights into controlling disease spread for other vector-borne plant diseases, and the small number of mathematical models of Huanglongbing. We adapt a malaria model to Huanglongbing, by including temperature-dependent psyllid traits and economic costs, to show how models can be used to highlight which parameters require more data collection or which should be targeted for intervention. We analyze the most common intervention strategy, insecticide spraying, to determine the most cost-effective spraying strategy. We found that fecundity and feeding rate of the vector require more experimental data collection, for wider temperatures ranges. The best strategy for insecticide intervention was to spray for more days rather than pay extra for a more efficient spray. We conclude that mathematical models are able to provide useful recommendations for managing Huanglongbing spread.

scholarly journals Modeling Host-Pathogen Interactions in the Context of the Microenvironment: Three-Dimensional Cell Culture Comes of Age

2018 ◽  
Vol 86 (11) ◽  
Author(s):  
Jennifer Barrila ◽  
Aurélie Crabbé ◽  
Jiseon Yang ◽  
Karla Franco ◽  
Seth D. Nydam ◽  
...  
Keyword(s):  
Infectious Disease ◽  
Historical Context ◽  
Three Dimensional ◽  
Microbial Pathogens ◽  
Host Pathogen Interactions ◽  
Commensal Microbiota ◽  
Disease Mechanisms ◽  
Host Pathogen ◽  
Single Cell Type ◽  
Biomechanical Forces

ABSTRACTTissues and organs provide the structural and biochemical landscapes upon which microbial pathogens and commensals function to regulate health and disease. While flat two-dimensional (2-D) monolayers composed of a single cell type have provided important insight into understanding host-pathogen interactions and infectious disease mechanisms, these reductionist models lack many essential features present in the native host microenvironment that are known to regulate infection, including three-dimensional (3-D) architecture, multicellular complexity, commensal microbiota, gas exchange and nutrient gradients, and physiologically relevant biomechanical forces (e.g., fluid shear, stretch, compression). A major challenge in tissue engineering for infectious disease research is recreating this dynamic 3-D microenvironment (biological, chemical, and physical/mechanical) to more accurately model the initiation and progression of host-pathogen interactions in the laboratory. Here we review selected 3-D models of human intestinal mucosa, which represent a major portal of entry for infectious pathogens and an important niche for commensal microbiota. We highlight seminal studies that have used these models to interrogate host-pathogen interactions and infectious disease mechanisms, and we present this literature in the appropriate historical context. Models discussed include 3-D organotypic cultures engineered in the rotating wall vessel (RWV) bioreactor, extracellular matrix (ECM)-embedded/organoid models, and organ-on-a-chip (OAC) models. Collectively, these technologies provide a more physiologically relevant and predictive framework for investigating infectious disease mechanisms and antimicrobial therapies at the intersection of the host, microbe, and their local microenvironments.

scholarly journals Forecasting Unusual Trend of COVID-19 Progression in Pakistan

2020 ◽  
Author(s):  
SADAF ALI MALIK ◽  
Adnan Javed
Keyword(s):  
Infectious Disease ◽  
Disease Progression ◽  
Disease Spread ◽  
Major Fraction ◽  
Susceptible Population ◽  
Planning And Control ◽  
Trend Pattern ◽  
Spread Pattern ◽  
Mathematical Equations ◽  
And Control

The observed data of COVID-19 progression in Pakistan for first 50 days from the first patient been reported has shown quite an unusual trend which is in opposition to clear exponential spread pattern of any infectious disease. The data of positive cases of 50 days of disease progression has been collected from COVID-19 dashboard of Pakistan and analyzed to see the graphical trend and to forecast the behaviour of disease progression for next 30 days. Mathematical equations regarding exponential growth are used to analyse the disease progression and different possible trajectories are plotted to understand the approximate trend pattern. The possible projections estimated 20k-456k positive cases within 80 days of disease spread in Pakistan. Although, the disease progression pattern is not perfectly exponential, it is still threatening a major fraction of susceptible population and demands effective strategic planning and control.

scholarly journals Recent Advances in Immunotherapies Against Infectious Diseases

2020 ◽  
Author(s):  
Dharanidharan Ramamurthy ◽  
Trishana Nundalall ◽  
Sanele Cingo ◽  
Neelakshi Mungra ◽  
Maryam Karaan ◽  
...  
Keyword(s):  
Infectious Disease ◽  
Infectious Diseases ◽  
Management Strategies ◽  
Emerging Diseases ◽  
Checkpoint Inhibition ◽  
Widespread Implementation ◽  
Cytokine Levels ◽  
Recent Developments ◽  
And Control

Abstract Immunotherapies are disease management strategies that target or manipulate components of the immune system. Infectious diseases pose a significant threat to human health as evidenced by countries continuing to grapple with several emerging and re-emerging diseases, the most recent global health threat being the SARS-CoV2 pandemic. As such, various immunotherapeutic approaches are increasingly being investigated as alternative therapies for infectious diseases, resulting in significant advances towards the uncovering of pathogen-host immunity interactions. Novel and innovative therapeutic strategies are necessary to overcome the challenges typically faced by existing infectious disease prevention and control methods such as lack of adequate efficacy, drug toxicity and the emergence of drug resistance. As evidenced by recent developments and success of pharmaceuticals such as monoclonal antibodies, immunotherapies already show abundant promise to overcome such limitations while also advancing the frontiers of medicine. In this review we summarize some of the most notable inroads made to combat infectious disease, over mainly the last 5 years, through the use of immunotherapies such as vaccines, monoclonal antibody-based therapies, T-cell-based therapies, manipulation of cytokine levels and checkpoint inhibition. Whilst its most general applications are founded in cancer treatment, advances made towards the curative treatment of HIV, tuberculosis, malaria, zika virus and, most recently COVID-19, reinforce the role of immunotherapeutic strategies in the broader field of disease control. Ultimately, the comprehensive specificity, safety and cost of immunotherapeutics will impact its widespread implementation.

scholarly journals Applying optimal control theory to complex epidemiological models to inform real-world disease management

2019 ◽  
Vol 374 (1776) ◽  
pp. 20180284 ◽  
Author(s):  
E. H. Bussell ◽  
C. E. Dangerfield ◽  
C. A. Gilligan ◽  
N. J. Cunniffe
Keyword(s):  
Infectious Disease ◽  
Optimal Control ◽  
Disease Management ◽  
Control Theory ◽  
Optimal Control Theory ◽  
Management Strategies ◽  
Disease Outbreaks ◽  
Theme Issue ◽  
Infectious Disease Outbreaks ◽  
And Control

Mathematical models provide a rational basis to inform how, where and when to control disease. Assuming an accurate spatially explicit simulation model can be fitted to spread data, it is straightforward to use it to test the performance of a range of management strategies. However, the typical complexity of simulation models and the vast set of possible controls mean that only a small subset of all possible strategies can ever be tested. An alternative approach—optimal control theory—allows the best control to be identified unambiguously. However, the complexity of the underpinning mathematics means that disease models used to identify this optimum must be very simple. We highlight two frameworks for bridging the gap between detailed epidemic simulations and optimal control theory: open-loop and model predictive control. Both these frameworks approximate a simulation model with a simpler model more amenable to mathematical analysis. Using an illustrative example model, we show the benefits of using feedback control, in which the approximation and control are updated as the epidemic progresses. Our work illustrates a new methodology to allow the insights of optimal control theory to inform practical disease management strategies, with the potential for application to diseases of humans, animals and plants. This article is part of the theme issue ‘Modelling infectious disease outbreaks in humans, animals and plants: epidemic forecasting and control’. This theme issue is linked with the earlier issue ‘Modelling infectious disease outbreaks in humans, animals and plants: approaches and important themes’.

Dynamics of infectious disease

2007 ◽  
Author(s):  
Bryan Grenfell ◽  
Matthew Keeling
Keyword(s):  
Infectious Disease ◽  
Population Dynamics ◽  
Natural Enemy ◽  
Population Biology ◽  
Plant Pathogens ◽  
Disease Incidence ◽  
Host Pathogen Interactions ◽  
Incidence Data ◽  
Pathogen Dynamics ◽  
Host Pathogen

Host–pathogen associations continue to generate some of the most important applied problems in population biology. In addition, as foreshadowed in Chapter 5 of this volume, these systems give important insights into the dynamics of host– natural enemy interactions in general. The special place of pathogens in the study of host–natural enemy dynamics arises partly from excellent longterm disease-incidence data, reflecting the public health importance of many infections. However, we argue that host–pathogen dynamics are also distinctive because the intimate association between individual hosts and their pathogens is often reflected with particular clarity in the associated population dynamics. Throughout this chapter we focus in parallel on the population dynamics of host–pathogen interactions and the insights that host–pathogen dynamics can provide for population biology in general. Population-dynamic studies of infectious disease have a long history, which predates the modern foundations of ecology (Bernoulli, 1760). During the twentieth century, the preoccupation of population ecologists with the balance between extrinsic and intrinsic influences on population fluctuations and the role of nonlinearity and heterogeneity (Bjørnstad and Grenfell, 2001) find strong parallels in epidemiological studies of human diseases (Bartlett, 1956; Anderson and May, 1991). In terms of the ecological effects of parasitism, the traditional view held that ‘welladapted’ parasites would not have a consistent impact on the ecology of their hosts (Grenfell and Dobson, 1995). The 1970s saw a new departure, when Anderson and May pointed out the potential of infectious agents to exert nonlinear—regulatory or destabilizing—influences on the population dynamics of their hosts (Anderson and May, 1978, 1979; May and Anderson, 1978, 1979). There has since been an explosion of work on the population biology of human, animal, and plant pathogens. This work spans a huge range: from highly applied to basic theoretical work; from within-host to the metapopulation scale; from short-term population dynamics to long-term evolutionary processes. In this chapter we first outline the simple theory of epidemiological models; we then refine this picture to illustrate the potential impact of pathogens on the population dynamics of their hosts, as well as aspects of host–pathogen interactions which provide important insights into more general ecological 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.

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