Sociality and disease transmission: Difference between revisions
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| ⚫ | Studies have generated very mixed results regarding pathogen risk and prevalence in animal communities. One of the earliest measurements we have regarding a correlation between pathogen prevalence and animal social groups is with prairie dog wards |
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“I would imagine the most important damage from social behavior to be the spread of communicable disease”- George C. Williams |
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| ⚫ | Studies have generated very mixed results regarding pathogen risk and prevalence in animal communities. One of the earliest measurements we have regarding a correlation between pathogen prevalence and animal social groups is with prairie dog wards<ref>{{cite journal|last1=Hoogland|first1=John L.|title=Aggression, Ectoparasitism, and Other Possible Costs of Prairie Dog (Sciuridae, Cynomys Spp.) Coloniality|journal=Behaviour|date=1 January 1979|volume=69|issue=1|pages=1–34|doi=10.1163/156853979X00377}}</ref>. Hoogland, 1979, found in his study that as the size of the ward increased, the abundance of parasites in the burrow also increased. Several studies that followed in years since have also supported this finding that an increase in community size and density produces an increase of risk and prevalence of pathogenic infection <ref>{{cite journal|last1=Wilkinson|first1=G.S.|title=The Social Organization of the Common Vampire Bat|journal=Behavioral Ecology and Sociobiology|date=1985|volume=17|issue=2|doi=10.1007/BF00299244}}</ref>, <ref>{{cite journal|last1=Shields|first1=William M.|last2=Crook|first2=Janice R.|title=Barn Swallow Coloniality: A Net Cost for Group Breeding in the Adirondacks?|journal=Ecology|date=October 1987|volume=68|issue=5|pages=1373–1386|doi=10.2307/1939221}}</ref>, <ref name=":0">{{cite journal|last1=Møller|first1=Anders Pape|last2=Dufva|first2=Reija|last3=Allander|first3=Klas|title=Parasites and the Evolution of Host Social Behavior|journal=Advances in the study of Behavior|date=1993|volume=22}}</ref>, <ref name=":1">{{cite journal|last1=Altizer|first1=Sonia|last2=Nunn|first2=Charles L.|last3=Thrall|first3=Peter H.|last4=Gittleman|first4=John L.|last5=Antonovics|first5=Janis|last6=Cunningham|first6=Andrew A.|last7=Cunnningham|first7=Andrew A.|last8=Dobson|first8=Andrew P.|last9=Ezenwa|first9=Vanessa|last10=Jones|first10=Kate E.|last11=Pedersen|first11=Amy B.|last12=Poss|first12=Mary|last13=Pulliam|first13=Juliet R. C.|title=Social Organization and Parasite Risk in Mammals: Integrating Theory and Empirical Studies|journal=Annual Review of Ecology, Evolution, and Systematics|date=1 January 2003|volume=34|pages=517–547|url=http://www.jstor.org/stable/30033785}}</ref>. Vector-born parasites as well as parasites transmitted by direct social contact appeared to correlate positively in number with the density of a population<ref name=":0" />,<ref name=":1" />. In a recent meta-analysis of the data, Patterson and Ruckstahl (2013) confirmed that “parasite intensity and prevalence both increased positively with group size…” with the caveat of mobile parasites, which displayed a negative correlation between group size and infection intensity. Møller et al. (1993) speculate, however, that animals have evolved behaviors to mitigate the pathogenic risk of living in social groups. This includes grooming, rotating roost sites, mate selection, and aggressive behavior that is thought to reveal the presence of a depressed immune system in an individual. |
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Not all research has supported this connection between pathogens and sociality, however. In fact, an abundance of information on social mammals as well as avian groups has drawn the exact opposite conclusion<ref name="Griffin Nunn">{{cite journal|last1=Griffin|first1=Randi H.|last2=Nunn|first2=Charles L.|title=Community structure and the spread of infectious disease in primate social networks|journal=Evolutionary Ecology|date=21 September 2011|volume=26|issue=4|pages=779–800|doi=10.1007/s10682-011-9526-2}}</ref>, <ref name="Snaith">{{cite journal|last1=Snaith|first1=Tamaini V.|last2=Chapman|first2=Colin A.|last3=Rothman|first3=Jessica M.|last4=Wasserman|first4=Michael D.|title=Bigger groups have fewer parasites and similar cortisol levels: a multi-group analysis in red colobus monkeys|journal=American Journal of Primatology|date=November 2008|volume=70|issue=11|pages=1072–1080|doi=10.1002/ajp.20601}}</ref>, <ref name="Wilson">{{cite journal|last1=Wilson|first1=Kenneth|last2=Knell|first2=Robert|last3=Boots|first3=Michael|last4=Koch-Osborne|first4=Jane|title=Group living and investment in immune defence: an interspecific analysis|journal=Journal of Animal Ecology|date=January 2003|volume=72|issue=1|pages=133–143|doi=10.1046/j.1365-2656.2003.00680.x}}</ref>, <ref name="huang li">{{cite journal|last1=Huang|first1=Wei|last2=Li|first2=Chunguang|title=Epidemic spreading in scale-free networks with community structure|journal=Journal of Statistical Mechanics: Theory and Experiment|date=1 January 2007|volume=2007|issue=01|pages=P01014|doi=10.1088/1742-5468/2007/01/P01014|url=http://iopscience.iop.org/article/10.1088/1742-5468/2007/01/P01014/pdf|language=en|issn=1742-5468}}</ref>, <ref name="Salathe">{{cite journal|last1=Salathé|first1=Marcel|last2=Jones|first2=James H.|title=Dynamics and Control of Diseases in Networks with Community Structure|journal=PLOS Computational Biology|date=8 April 2010|volume=6|issue=4|pages=e1000736|doi=10.1371/journal.pcbi.1000736|url=http://dx.doi.org/10.1371/journal.pcbi.1000736|issn=1553-7358}}</ref>, <ref name="wey 2008">{{cite journal|last1=Wey|first1=Tina|last2=Blumstein|first2=Daniel T.|last3=Shen|first3=Weiwei|last4=Jordán|first4=Ferenc|title=Social network analysis of animal behaviour: a promising tool for the study of sociality|journal=Animal Behaviour|date=1 February 2008|volume=75|issue=2|pages=333–344|doi=10.1016/j.anbehav.2007.06.020|url=http://dx.doi.org/10.1016/j.anbehav.2007.06.020}}</ref>, <ref>{{cite journal|last1=Arnold|first1=Walter|last2=Anja|first2=V. Lichtenstein|title=Ectoparasite loads decrease the fitness of alpine marmots but are not a cost of sociality|journal=Behavioral Ecology|date=1993|volume=4|issue=1|pages=36–39|doi=10.1093/beheco/4.1.36}}</ref>. Higher hemocyte and phenoloxidase levels were measured in solitary species than in socially organized ones in one study<ref name="Wilson" />. This study is uniquely informative because it removes the potentially confounding factors of host-parasite coevolution and phylogenetic similarities that come from measuring only the presence of pathogens, rather than the activity of the immune system. Similarly, Snaith et al. (2008) found that large social groups had even fewer parasites and they also measured lower levels of cortisol, a stress hormone that reduces immune function. Viral presence in scale-free networks without communities is higher, and in fact, the stronger the community structure of the animals is, the less likely a new outbreak will occur <ref name="huang li" />This information has stimulated inquiry into the various social structures that characterize animals. |
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A few reasons for the contrary findings have been speculated. Due to the complex nature of social groups, studies that sample pathogen presence frequently fail to account for the fission-fusion nature that characterizes them: conflicts occur, new social bonds are made or die out, births and deaths of individuals occur, groups or individuals may migrate, networks may overlap or else be quite far apart from one another. Social groups are far from being stagnant and single measurements of pathogen presence can easily have misleading results <ref name="Salathe" />.Wilson et al., 2003 also highlight the importance of accounting for shared ancestry among animals, which includes recent genetic relation as well as phylogenetic relationships. Parasite-host co-evolution is also important to consider, which may lead to an endemic presence of a pathogen in a group, or conversely, an immunity <ref name="Wilson" />. Many other factors confound the dynamics of social groups and pathogen spread that will be examined in the "Challenges" section. |
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Community Structures of Social Animals and Implications for Contagious Infections |
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Griffin and Nunn’s (2012) article on community structure simulated the introduction of a pathogen into various group structures and communities. Ultimately, “increased modularity mediates the elevated risk of parasitism associated with living in larger groups” <ref name="Griffin Nunn" />. Such structures are composed of nodes that may represent an individual or a unit of individuals in a group who have ties to other nodes. If the community structure is strong, the eigenvector (here represented as a pathogen) will experience a dying-out effect <ref name="huang li" />, <ref name="Griffin Nunn" />, <ref name="wey 2008" />.In geometrical structures of communities, a point represents a node, and a line between two nodes represents a social tie or interaction. In certain structures, the eigenvector may pass from one group to another, but the chances are limited. If a node is said to represent an individual, we can imagine that three potential outcomes will occur once that node has been infected. The individual may die, may become immune to future infection by the pathogen, or may live with the disease chronically until it is shed. In the first two outcomes, the pathogen will begin to experience a dying-out effect and transmission will begin to weaken. Wey et al. (2008) note that not all nodes are equal in weight within the community’s structure, and therefore their level of risk for both reception and transmission may vary heavily. Furthermore, this “weight” of an individual can have interesting implications for transmission if a “key individual” is removed from the structure <ref name="wey 2008" />. An extreme consequence of the removal of a key individual could be the collapse of the structure, but also may mean the loss of a “super-spreader”, which is an individual with many ties inside a community as well as ties to other communities <ref name="Griffin Nunn" />. Super-spreaders may be measured by their high levels of in-degree and out-degree numbers. In-degree is a reflection of the susceptibility of a node because it is a measurement of all the social ties a node is the recipient of, whereas out-degree is a reflection of the contagiousness of a node because it is a measurement of all the social ties generating from that node<ref name="wey 2008" />. |
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Challenges |
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In addition to the natural factors that make measuring true pathogen risk and prevalence difficult (mentioned above) are behaviors like mate selection, stress-hormone levels, degree of promiscuity in a group, and diet <ref name="Wilson" />, |
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==References== |
==References== |
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Revision as of 04:04, 20 December 2016
Template:New unreviewed article
Definition:
The degree to which social behavior among animals influences the transmission of infectious disease. Furthermore, the degree to which social grouping strategies may promote or block the transmission of infectious diseases.
“I would imagine the most important damage from social behavior to be the spread of communicable disease”- George C. Williams
Non-human Social Groups and Disease Transmission Studies have generated very mixed results regarding pathogen risk and prevalence in animal communities. One of the earliest measurements we have regarding a correlation between pathogen prevalence and animal social groups is with prairie dog wards[1]. Hoogland, 1979, found in his study that as the size of the ward increased, the abundance of parasites in the burrow also increased. Several studies that followed in years since have also supported this finding that an increase in community size and density produces an increase of risk and prevalence of pathogenic infection [2], [3], [4], [5]. Vector-born parasites as well as parasites transmitted by direct social contact appeared to correlate positively in number with the density of a population[4],[5]. In a recent meta-analysis of the data, Patterson and Ruckstahl (2013) confirmed that “parasite intensity and prevalence both increased positively with group size…” with the caveat of mobile parasites, which displayed a negative correlation between group size and infection intensity. Møller et al. (1993) speculate, however, that animals have evolved behaviors to mitigate the pathogenic risk of living in social groups. This includes grooming, rotating roost sites, mate selection, and aggressive behavior that is thought to reveal the presence of a depressed immune system in an individual.
Not all research has supported this connection between pathogens and sociality, however. In fact, an abundance of information on social mammals as well as avian groups has drawn the exact opposite conclusion[6], [7], [8], [9], [10], [11], [12]. Higher hemocyte and phenoloxidase levels were measured in solitary species than in socially organized ones in one study[8]. This study is uniquely informative because it removes the potentially confounding factors of host-parasite coevolution and phylogenetic similarities that come from measuring only the presence of pathogens, rather than the activity of the immune system. Similarly, Snaith et al. (2008) found that large social groups had even fewer parasites and they also measured lower levels of cortisol, a stress hormone that reduces immune function. Viral presence in scale-free networks without communities is higher, and in fact, the stronger the community structure of the animals is, the less likely a new outbreak will occur [9]This information has stimulated inquiry into the various social structures that characterize animals. A few reasons for the contrary findings have been speculated. Due to the complex nature of social groups, studies that sample pathogen presence frequently fail to account for the fission-fusion nature that characterizes them: conflicts occur, new social bonds are made or die out, births and deaths of individuals occur, groups or individuals may migrate, networks may overlap or else be quite far apart from one another. Social groups are far from being stagnant and single measurements of pathogen presence can easily have misleading results [10].Wilson et al., 2003 also highlight the importance of accounting for shared ancestry among animals, which includes recent genetic relation as well as phylogenetic relationships. Parasite-host co-evolution is also important to consider, which may lead to an endemic presence of a pathogen in a group, or conversely, an immunity [8]. Many other factors confound the dynamics of social groups and pathogen spread that will be examined in the "Challenges" section. Community Structures of Social Animals and Implications for Contagious Infections Griffin and Nunn’s (2012) article on community structure simulated the introduction of a pathogen into various group structures and communities. Ultimately, “increased modularity mediates the elevated risk of parasitism associated with living in larger groups” [6]. Such structures are composed of nodes that may represent an individual or a unit of individuals in a group who have ties to other nodes. If the community structure is strong, the eigenvector (here represented as a pathogen) will experience a dying-out effect [9], [6], [11].In geometrical structures of communities, a point represents a node, and a line between two nodes represents a social tie or interaction. In certain structures, the eigenvector may pass from one group to another, but the chances are limited. If a node is said to represent an individual, we can imagine that three potential outcomes will occur once that node has been infected. The individual may die, may become immune to future infection by the pathogen, or may live with the disease chronically until it is shed. In the first two outcomes, the pathogen will begin to experience a dying-out effect and transmission will begin to weaken. Wey et al. (2008) note that not all nodes are equal in weight within the community’s structure, and therefore their level of risk for both reception and transmission may vary heavily. Furthermore, this “weight” of an individual can have interesting implications for transmission if a “key individual” is removed from the structure [11]. An extreme consequence of the removal of a key individual could be the collapse of the structure, but also may mean the loss of a “super-spreader”, which is an individual with many ties inside a community as well as ties to other communities [6]. Super-spreaders may be measured by their high levels of in-degree and out-degree numbers. In-degree is a reflection of the susceptibility of a node because it is a measurement of all the social ties a node is the recipient of, whereas out-degree is a reflection of the contagiousness of a node because it is a measurement of all the social ties generating from that node[11]. Challenges In addition to the natural factors that make measuring true pathogen risk and prevalence difficult (mentioned above) are behaviors like mate selection, stress-hormone levels, degree of promiscuity in a group, and diet [8],
References
- ^ Hoogland, John L. (1 January 1979). "Aggression, Ectoparasitism, and Other Possible Costs of Prairie Dog (Sciuridae, Cynomys Spp.) Coloniality". Behaviour. 69 (1): 1–34. doi:10.1163/156853979X00377.
- ^ Wilkinson, G.S. (1985). "The Social Organization of the Common Vampire Bat". Behavioral Ecology and Sociobiology. 17 (2). doi:10.1007/BF00299244.
- ^ Shields, William M.; Crook, Janice R. (October 1987). "Barn Swallow Coloniality: A Net Cost for Group Breeding in the Adirondacks?". Ecology. 68 (5): 1373–1386. doi:10.2307/1939221.
- ^ a b Møller, Anders Pape; Dufva, Reija; Allander, Klas (1993). "Parasites and the Evolution of Host Social Behavior". Advances in the study of Behavior. 22.
- ^ a b Altizer, Sonia; Nunn, Charles L.; Thrall, Peter H.; Gittleman, John L.; Antonovics, Janis; Cunningham, Andrew A.; Cunnningham, Andrew A.; Dobson, Andrew P.; Ezenwa, Vanessa; Jones, Kate E.; Pedersen, Amy B.; Poss, Mary; Pulliam, Juliet R. C. (1 January 2003). "Social Organization and Parasite Risk in Mammals: Integrating Theory and Empirical Studies". Annual Review of Ecology, Evolution, and Systematics. 34: 517–547.
- ^ a b c d Griffin, Randi H.; Nunn, Charles L. (21 September 2011). "Community structure and the spread of infectious disease in primate social networks". Evolutionary Ecology. 26 (4): 779–800. doi:10.1007/s10682-011-9526-2.
- ^ Snaith, Tamaini V.; Chapman, Colin A.; Rothman, Jessica M.; Wasserman, Michael D. (November 2008). "Bigger groups have fewer parasites and similar cortisol levels: a multi-group analysis in red colobus monkeys". American Journal of Primatology. 70 (11): 1072–1080. doi:10.1002/ajp.20601.
- ^ a b c d Wilson, Kenneth; Knell, Robert; Boots, Michael; Koch-Osborne, Jane (January 2003). "Group living and investment in immune defence: an interspecific analysis". Journal of Animal Ecology. 72 (1): 133–143. doi:10.1046/j.1365-2656.2003.00680.x.
- ^ a b c Huang, Wei; Li, Chunguang (1 January 2007). "Epidemic spreading in scale-free networks with community structure". Journal of Statistical Mechanics: Theory and Experiment. 2007 (01): P01014. doi:10.1088/1742-5468/2007/01/P01014. ISSN 1742-5468.
- ^ a b Salathé, Marcel; Jones, James H. (8 April 2010). "Dynamics and Control of Diseases in Networks with Community Structure". PLOS Computational Biology. 6 (4): e1000736. doi:10.1371/journal.pcbi.1000736. ISSN 1553-7358.
{{cite journal}}: CS1 maint: unflagged free DOI (link) - ^ a b c d Wey, Tina; Blumstein, Daniel T.; Shen, Weiwei; Jordán, Ferenc (1 February 2008). "Social network analysis of animal behaviour: a promising tool for the study of sociality". Animal Behaviour. 75 (2): 333–344. doi:10.1016/j.anbehav.2007.06.020.
- ^ Arnold, Walter; Anja, V. Lichtenstein (1993). "Ectoparasite loads decrease the fitness of alpine marmots but are not a cost of sociality". Behavioral Ecology. 4 (1): 36–39. doi:10.1093/beheco/4.1.36.
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