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Title: Causes and Consequences of Spatial Within-Host Viral Spread

Abstract

The spread of viral pathogens both between and within hosts is inherently a spatial process. While the spatial aspects of viral spread at the epidemiological level have been increasingly well characterized, the spatial aspects of viral spread within infected hosts are still understudied. Here, with a focus on influenza A viruses (IAVs), we first review experimental studies that have shed light on the mechanisms and spatial dynamics of viral spread within hosts. These studies provide strong empirical evidence for highly localized IAV spread within hosts. Since mathematical and computational within-host models have been increasingly used to gain a quantitative understanding of observed viral dynamic patterns, we then review the (relatively few) computational modeling studies that have shed light on possible factors that structure the dynamics of spatial within-host IAV spread. These factors include the dispersal distance of virions, the localization of the immune response, and heterogeneity in host cell phenotypes across the respiratory tract. While informative, we find in these studies a striking absence of theoretical expectations of how spatial dynamics may impact the dynamics of viral populations. To mitigate this, we turn to the extensive ecological and evolutionary literature on range expansions to provide informed theoretical expectations. We findmore » that factors such as the type of density dependence, the frequency of long-distance dispersal, specific life history characteristics, and the extent of spatial heterogeneity are critical factors affecting the speed of population spread and the genetic composition of spatially expanding populations. For each factor that we identified in the theoretical literature, we draw parallels to its analog in viral populations. We end by discussing current knowledge gaps related to the spatial component of within-host IAV spread and the potential for within-host spatial considerations to inform the development of disease control strategies.« less

Authors:
 [1];  [2];  [3];  [1]
  1. Emory Univ., Atlanta, GA (United States). Dept. of Biology
  2. Univ. of Illinois, Champaign, IL (United States). Dept. of Microbiology. Carl R. Woese Inst. for Genomic Biology
  3. Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
Publication Date:
Research Org.:
Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Emory Univ., Atlanta, GA (United States); Univ. of Illinois at Urbana-Champaign, IL (United States)
Sponsoring Org.:
USDOE; Defense Advanced Research Projects Agency (DARPA) (United States); National Inst. of Health (NIH) (United States)
OSTI Identifier:
1483551
Report Number(s):
LA-UR-18-29454
Journal ID: ISSN 1999-4915
Grant/Contract Number:  
89233218CNA000001; W911NF-17-2-0034; U54-GM111274
Resource Type:
Journal Article: Accepted Manuscript
Journal Name:
Viruses
Additional Journal Information:
Journal Volume: 10; Journal Issue: 11; Journal ID: ISSN 1999-4915
Publisher:
MDPI
Country of Publication:
United States
Language:
English
Subject:
60 APPLIED LIFE SCIENCES; influenza virus; within-host viral dynamics; spatial spread; within-host evolution

Citation Formats

Gallagher, Molly E., Brooke, Christopher B., Ke, Ruian, and Koelle, Katia. Causes and Consequences of Spatial Within-Host Viral Spread. United States: N. p., 2018. Web. doi:10.3390/v10110627.
Gallagher, Molly E., Brooke, Christopher B., Ke, Ruian, & Koelle, Katia. Causes and Consequences of Spatial Within-Host Viral Spread. United States. doi:10.3390/v10110627.
Gallagher, Molly E., Brooke, Christopher B., Ke, Ruian, and Koelle, Katia. Tue . "Causes and Consequences of Spatial Within-Host Viral Spread". United States. doi:10.3390/v10110627. https://www.osti.gov/servlets/purl/1483551.
@article{osti_1483551,
title = {Causes and Consequences of Spatial Within-Host Viral Spread},
author = {Gallagher, Molly E. and Brooke, Christopher B. and Ke, Ruian and Koelle, Katia},
abstractNote = {The spread of viral pathogens both between and within hosts is inherently a spatial process. While the spatial aspects of viral spread at the epidemiological level have been increasingly well characterized, the spatial aspects of viral spread within infected hosts are still understudied. Here, with a focus on influenza A viruses (IAVs), we first review experimental studies that have shed light on the mechanisms and spatial dynamics of viral spread within hosts. These studies provide strong empirical evidence for highly localized IAV spread within hosts. Since mathematical and computational within-host models have been increasingly used to gain a quantitative understanding of observed viral dynamic patterns, we then review the (relatively few) computational modeling studies that have shed light on possible factors that structure the dynamics of spatial within-host IAV spread. These factors include the dispersal distance of virions, the localization of the immune response, and heterogeneity in host cell phenotypes across the respiratory tract. While informative, we find in these studies a striking absence of theoretical expectations of how spatial dynamics may impact the dynamics of viral populations. To mitigate this, we turn to the extensive ecological and evolutionary literature on range expansions to provide informed theoretical expectations. We find that factors such as the type of density dependence, the frequency of long-distance dispersal, specific life history characteristics, and the extent of spatial heterogeneity are critical factors affecting the speed of population spread and the genetic composition of spatially expanding populations. For each factor that we identified in the theoretical literature, we draw parallels to its analog in viral populations. We end by discussing current knowledge gaps related to the spatial component of within-host IAV spread and the potential for within-host spatial considerations to inform the development of disease control strategies.},
doi = {10.3390/v10110627},
journal = {Viruses},
number = 11,
volume = 10,
place = {United States},
year = {Tue Nov 13 00:00:00 EST 2018},
month = {Tue Nov 13 00:00:00 EST 2018}
}

Journal Article:
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