Contact Heterogeneity, Rather Than Transmission Efficiency, Limits the Emergence and Spread of Canine Influenza Virus
Influenza virus infects a range of vertebrate hosts, including domesticated animals as well as humans. Some of the most serious influenza pandemics in humans have involved host range shifts, when an influenza virus jumps from one host species to another. Importantly, however, host range shifts do not always cause pandemics. Rather, epidemiological patterns tend to be unpredictable in new host species, causing disease patterns that change over space and time. In this paper, we analyze epidemiological and evolutionary dynamics of canine influenza virus (CIV), which jumped to dogs in the late 1990s from an equine strain (EIV) prevalent in horses. We show that the epidemiology and evolution of CIV is strongly influenced by heterogeneous patterns of infectious contact among dogs in the US. A few large populations in metropolitan animal shelters serve as reservoirs for CIV, but the virus cannot be maintained for long in smaller facilities or in the companion dog population without input from the larger shelters, which represent disease hotspots. These hotspot dynamics give a clear picture of what can happen in the time between the beginning of a host range shift and the onset of a possible pandemic, allowing more targeted strategies for control and eradication.
Vyšlo v časopise:
Contact Heterogeneity, Rather Than Transmission Efficiency, Limits the Emergence and Spread of Canine Influenza Virus. PLoS Pathog 10(10): e32767. doi:10.1371/journal.ppat.1004455
Kategorie:
Research Article
prolekare.web.journal.doi_sk:
https://doi.org/10.1371/journal.ppat.1004455
Souhrn
Influenza virus infects a range of vertebrate hosts, including domesticated animals as well as humans. Some of the most serious influenza pandemics in humans have involved host range shifts, when an influenza virus jumps from one host species to another. Importantly, however, host range shifts do not always cause pandemics. Rather, epidemiological patterns tend to be unpredictable in new host species, causing disease patterns that change over space and time. In this paper, we analyze epidemiological and evolutionary dynamics of canine influenza virus (CIV), which jumped to dogs in the late 1990s from an equine strain (EIV) prevalent in horses. We show that the epidemiology and evolution of CIV is strongly influenced by heterogeneous patterns of infectious contact among dogs in the US. A few large populations in metropolitan animal shelters serve as reservoirs for CIV, but the virus cannot be maintained for long in smaller facilities or in the companion dog population without input from the larger shelters, which represent disease hotspots. These hotspot dynamics give a clear picture of what can happen in the time between the beginning of a host range shift and the onset of a possible pandemic, allowing more targeted strategies for control and eradication.
Zdroje
1. ParrishCR, KawaokaY (2005) The origins of new pandemic viruses: the acquisition of new host ranges by canine parvovirus and influenza A viruses. Annu Rev Microbiol 59: 553–586 doi:10.1146/annurev.micro.59.030804.121059
2. WoolhouseMEJ, HaydonDT, AntiaR (2005) Emerging pathogens: the epidemiology and evolution of species jumps. Trends Ecol Evol 20: 238–244 doi:10.1016/j.tree.2005.02.009
3. WolfeND, DunavanCP, DiamondJ (2007) Origins of major human infectious diseases. Nature 447: 279–283 doi:10.1038/nature05775
4. GortazarC, ReperantLA, KuikenT, la Fuente deJ, BoadellaM, et al. (2014) Crossing the Interspecies Barrier: Opening the Door to Zoonotic Pathogens. PLoS Pathog 10: e1004129 doi:10.1371/journal.ppat.1004129
5. GuanY, ZhengBJ, HeYQ, LiuXL, ZhuangZX, et al. (2003) Isolation and characterization of viruses related to the SARS coronavirus from animals in southern China. Science 302: 276–278 doi:10.1126/science.1087139
6. SmithGJD, VijaykrishnaD, BahlJ, LycettSJ, WorobeyM, et al. (2009) Origins and evolutionary genomics of the 2009 swine-origin H1N1 influenza A epidemic. Nature 459: 1122–1125.
7. ColemanCM, FriemanMB (2013) Emergence of the Middle East Respiratory Syndrome Coronavirus. PLoS Pathog 9 doi:10.1371/journal.ppat.1003595
8. MorseSS, MazetJAK, WoolhouseMEJ, ParrishCR, CarrolD, et al. (2012) Prediction and prevention of the next pandemic zoonosis. The Lancet 380: 1956–1965 doi:10.1016/S0140-6736(12)61684-5
9. MayRM, GuptaS, McLeanAR (2001) Infectious disease dynamics: what characterizes a successful invader? Phil Trans R Soc Lond B 356: 901–910 doi:10.1098/rstb.2001.0866
10. AntiaR, RegoesRR, KoellaJC, BergstromCT (2003) The role of evolution in the emergence of infectious diseases. Nature 426: 658–661 doi:10.1038/nature02104
11. Lloyd-SmithJO, GeorgeD, PepinKM, PitzerVE, PulliamJRC, et al. (2009) Epidemic dynamics at the human-animal interface. Science 326: 1362–1367 doi:10.1126/science.1177345
12. ArinaminpathyN, McLeanAR (2009) Evolution and emergence of novel human infections. Proc R Soc B 276: 3937–3943 doi:10.1098/rspb.2009.1059
13. NewmanMEJ (2002) Spread of epidemic disease on networks. Phys Rev E Stat Nonlin Soft Matter Phys 66: 016128.
14. MeyersLA, PourbohloulB, NewmanM, SkowronskiDM, BrunhamRC (2005) Network theory and SARS: predicting outbreak diversity. J Theor Biol 232: 71–81.
15. StadlerT, KühnertD, BonhoefferS, DrummondAJ (2013) Birth–death skyline plot reveals temporal changes of epidemic spread in HIV and hepatitis C virus (HCV). PNAS 110: 228–233 doi:10.1073/pnas.1207965110/-/DCSupplemental
16. CrawfordPC, DuboviEJ, CastlemanWL, StephensonI, GibbsEPJ, et al. (2005) Transmission of equine influenza virus to dogs. Science 310: 482–485 doi:10.1126/science.1117950
17. HaywardJJ, DuboviEJ, ScarlettJM, JaneczkoS, HolmesEC, et al. (2010) Microevolution of canine influenza virus in shelters and its molecular epidemiology in the United States. J Virol 84: 12636–12645 doi:10.1128/JVI.01350-10
18. AndersonTC, BromfieldCR, CrawfordPC, DoddsWJ, GibbsEPJ, et al. (2012) Serological evidence of H3N8 canine influenza-like virus circulation in USA dogs prior to 2004. Vet J 191: 312–316 doi:10.1016/j.tvjl.2011.11.010
19. KruegerWS, HeilGL, YoonK-J, GrayGC (2014) No evidence for zoonotic transmission of H3N8 canine influenza virus among US adults occupationally exposed to dogs. Influenza and Other Respiratory Viruses 8: 99–106 doi:10.1111/irv.12208
20. RivaillerP, PerryIA, JangY, DavisCT, ChenL-M, et al. (2010) Evolution of canine and equine influenza (H3N8) viruses co-circulating between 2005 and 2008. Virology 408: 71–79 doi:10.1016/j.virol.2010.08.022
21. DuboviEJ, NjaaBL (2008) Canine Influenza. Veterinary Clinics of North America: Small Animal Practice 38: 827–835 doi:10.1016/j.cvsm.2008.03.004
22. BarrellEA, PecoraroHL, Torres-HendersonC, MorleyPS, LunnKF, et al. (2010) Seroprevalence and risk factors for canine H3N8 influenza virus exposure in household dogs in Colorado. J Vet Intern Med 24: 1524–1527 Available: http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?dbfrom=pubmed&id=21155162&retmode=ref&cmd=prlinks.
23. JirjisFF, DeshpandeMS, TubbsAL, JayappaH, LakshmananN, et al. (2010) Transmission of canine influenza virus (H3N8) among susceptible dogs. Vet Microbiol 144: 303–309 doi:10.1016/j.vetmic.2010.02.029
24. SerraVF, StanzaniG, SmithG, OttoCM (2011) Point seroprevalence of canine influenza virus H3N8 in dogs participating in a flyball tournament in Pennsylvania. J Am Vet Med Assoc 238: 726–730 doi:10.2460/javma.238.6.726
25. HoltDE, MoverMR, BrownDC (2010) Serologic prevalence of antibodies against canine influenza virus (H3N8) in dogs in a metropolitan animal shelter. J Am Vet Med Assoc 237: 71–73 doi:10.2460/javma.237.1.71
26. PecoraroHL, BennettS, HuyvaertKP, SpindelME, LandoltGA (2014) Epidemiology and Ecology of H3N8 Canine Influenza Viruses in US Shelter Dogs. J Vet Intern Med 28: 311–318 doi:10.1111/jvim.12301
27. WaddellGH, TeiglandMB, SigelMM (1963) A new influenza virus associated with equine respiratory disease. J Am Vet Med Assoc 143: 587–590.
28. DalyJM, MacRaeS, NewtonJR, WattrangE, EltonDM (2011) Equine influenza: a review of an unpredictable virus. Vet J 189: 7–14 doi:10.1016/j.tvjl.2010.06.026
29. VirmaniN, BeraBC, SinghBK, ShanmugasundaramK, GulatiBR, et al. (2010) Equine influenza outbreak in India (2008–09): virus isolation, sero-epidemiology and phylogenetic analysis of HA gene. Vet Microbiol 143: 224–237 doi:10.1016/j.vetmic.2009.12.007
30. WeiG, Xue-FengL, YanY, Ying-YuanW, Ling-LiD, et al. (2010) Equine influenza viruses isolated during outbreaks in China in 2007 and 2008. Vet Rec 167: 382–383 doi:10.1136/vr.c3805
31. BountouriM, FragkiadakiE, NtafisV, KanellosT, XylouriE (2011) Phylogenetic and molecular characterization of equine H3N8 influenza viruses from Greece (2003 and 2007): evidence for reassortment between evolutionary lineages. Virol J 8: 350 doi:10.1186/1743-422X-8-350
32. CowledB, WardMP, HamiltonS, GarnerG (2009) The equine influenza epidemic in Australia: Spatial and temporal descriptive analyses of a large propagating epidemic. Prev Vet Med 92: 60–70 doi:10.1016/j.prevetmed.2009.08.006
33. HughesJ, AllenRC, BaguelinM, HampsonK, BaillieGJ, et al. (2012) Transmission of Equine Influenza Virus during an Outbreak Is Characterized by Frequent Mixed Infections and Loose Transmission Bottlenecks. PLoS Pathog 8: e1003081 doi:10.1371/journal.ppat.1003081.s015
34. DalyJM, LaiACK, BinnsMM, ChambersTM, BarrandeguyM, et al. (1996) Antigenic and genetic evolution of equine H3N8 influenza A viruses. Journal of General Virology 77: 661–671 doi:10.1099/0022-1317-77-4-661
35. MurciaPR, BaillieGJ, StackJC, JervisC, EltonD, et al. (2013) Evolution of equine influenza virus in vaccinated horses. J Virol 87: 4768–4771 doi:10.1128/JVI.03379-12
36. ParkerJ, RambautA, PybusOG (2008) Correlating viral phenotypes with phylogeny: Accounting for phylogenetic uncertainty. Infection, Genetics and Evolution 8: 239–246 doi:10.1016/j.meegid.2007.08.001
37. GillespieDT (1977) Exact stochastic simulation of coupled chemical reactions. J Phys Chem 81: 2340–2361 doi:10.1021/j100540a008
38. Anderson RM, May RM (1992) Infectious diseases of humans: dynamics and control. Oxford University Press, USA.
39. BarriaMI, GarridoJL, SteinC, ScherE, GeY, et al. (2012) Localized Mucosal Response to Intranasal Live Attenuated Influenza Vaccine in Adults. The Journal of infectious diseases 207: 115–124 doi:10.1093/infdis/jis641
40. MorensDM, TaubenbergerJK (2010) Historical thoughts on influenza viral ecosystems, or behold a pale horse, dead dogs, failing fowl, and sick swine. Influenza and Other Respiratory Viruses 4: 327–337 doi:10.1111/j.1750-2659.2010.00148.x
41. LiebermanE, HauertC, NowakMA (2005) Evolutionary dynamics on graphs. Nature 433: 312–316.
42. GlassK, WoodJLN, MumfordJA, JessetD, GrenfellBT (2002) Modelling equine influenza 1: a stochastic model of within-yard epidemics. Epidemiol Infect 128: 491–502.
43. MillsCE, RobinsJM, LipsitchM (2004) Transmissibility of 1918 pandemic influenza. Nature 432: 904–906 doi:10.1038/nature03063
44. WallingaJ, LipsitchM (2007) How generation intervals shape the relationship between growth rates and reproductive numbers. Proc R Soc B 274: 599–604 doi:10.1371/journal.pmed.0020174
45. FraserC, DonnellyCA, CauchemezS, HanageWP, Van KerkhoveMD, et al. (2009) Pandemic potential of a strain of influenza A (H1N1): early findings. Science 324: 1557.
46. Holmes EC (2009) The evolution and emergence of RNA viruses. Oxford University Press, USA.
47. DalzielBD, PourbohloulB, EllnerSP (2013) Human mobility patterns predict divergent epidemic dynamics among cities. Proc R Soc B 280: 20130763–20130763 doi:10.1371/journal.pcbi.1002425
48. McCallumH, BarlowN, HoneJ (2001) How should pathogen transmission be modelled? Trends Ecol Evol 16: 295–300.
49. Gilks WR, Richardson S, Spiegelhalter D (1995) Markov Chain Monte Carlo in Practice. CRC Press.
50. Nowak MA, May RM (2000) Virus dynamics. Oxford University Press.
51. EdgarRC (2004) MUSCLE: a multiple sequence alignment method with reduced time and space complexity. BMC Bioinformatics 5: 113 doi:10.1186/1471-2105-5-113
52. GuindonS, DufayardJ-F, LefortV, AnisimovaM, HordijkW, et al. (2010) New algorithms and methods to estimate maximum-likelihood phylogenies: assessing the performance of PhyML 3.0. Syst Biol 59: 307–321 doi:10.1093/sysbio/syq010
53. StadlerT, KouyosR, Wyl vonV, YerlyS, BöniJ, et al. (2012) Estimating the basic reproductive number from viral sequence data. Molecular Biology and Evolution 29: 347–357 doi:10.1093/molbev/msr217
54. DrummondAJ, RambautA (2007) BEAST: Bayesian evolutionary analysis by sampling trees. BMC Evolutionary Biology 7: 214.
55. Bouckaert R, Kuhnert D, Vaughan TG, Wu CH, Xie D, et al. (2013) BEAST2: A software platform for Bayesian evolutionary analysis. available at http://beast2.cs.auckland.ac.nz. Available: http://www.beast2.org/wiki/index.php/Main_Page#FAQ.
Štítky
Hygiena a epidemiológia Infekčné lekárstvo LaboratóriumČlánok vyšiel v časopise
PLOS Pathogens
2014 Číslo 10
- Očkování proti virové hemoragické horečce Ebola experimentální vakcínou rVSVDG-ZEBOV-GP
- Parazitičtí červi v terapii Crohnovy choroby a dalších zánětlivých autoimunitních onemocnění
- Koronavirus hýbe světem: Víte jak se chránit a jak postupovat v případě podezření?
Najčítanejšie v tomto čísle
- Novel Cyclic di-GMP Effectors of the YajQ Protein Family Control Bacterial Virulence
- MicroRNAs Suppress NB Domain Genes in Tomato That Confer Resistance to
- CD4 Depletion in SIV-Infected Macaques Results in Macrophage and Microglia Infection with Rapid Turnover of Infected Cells
- Theory and Empiricism in Virulence Evolution