Timelines of infection and transmission dynamics of H1N1pdm09 in swine

Autoři: Laetitia Canini aff001;  Barbara Holzer aff002;  Sophie Morgan aff002;  Johanneke Dinie Hemmink aff002;  Becky Clark aff002;  ;  Mark E. J. Woolhouse aff001;  Elma Tchilian aff002;  Bryan Charleston aff003
Působiště autorů: Usher Institute, The University of Edinburgh, Edinburgh, United Kingdom aff001;  Mucosal immunology, Pirbright Institute, Woking, United Kingdom aff002;  Viral immunology, Pirbright Institute, Woking, United Kingdom aff003
Vyšlo v časopise: Timelines of infection and transmission dynamics of H1N1pdm09 in swine. PLoS Pathog 16(7): e32767. doi:10.1371/journal.ppat.1008628
Kategorie: Research Article
doi: 10.1371/journal.ppat.1008628


Influenza is a major cause of mortality and morbidity worldwide. Despite numerous studies of the pathogenesis of influenza in humans and animal models the dynamics of infection and transmission in individual hosts remain poorly characterized. In this study, we experimentally modelled transmission using the H1N1pdm09 influenza A virus in pigs, which are considered a good model for influenza infection in humans. Using an experimental design that allowed us to observe individual transmission events occurring within an 18-hr period, we quantified the relationships between infectiousness, shed virus titre and antibody titre. Transmission events was observed on 60% of occasions when virus was detected in donor pig nasal swabs and transmission was more likely when donor pigs shed more virus. This led to the true infectious period (mean 3.9 days) being slightly shorter than that predicted by detection of virus (mean 4.5 days). The generation time of infection (which determines the rate of epidemic spread) was estimated for the first time in pigs at a mean of 4.6 days. We also found that the latent period of the contact pig was longer when they had been exposed to smaller amount of shed virus. Our study provides quantitative information on the time lines of infection and the dynamics of transmission that are key parts of the evidence base needed to understand the spread of influenza viruses though animal populations and, potentially, in humans.

Klíčová slova:

Antibodies – Influenza – Influenza A virus – Influenza viruses – Natural history of disease – Pig models – Swine – Viral replication


1. Gray GC, McCarthy T, Capuano AW, Setterquist SF, Olsen CW, Alavanja MC, et al. Swine Workers and Swine Influenza Virus Infections. Emerg Infect Dis. 2007;13: 1871–1878. doi: 10.3201/eid1312.061323 18258038

2. Myers KP, Setterquist SF, Capuano AW, Gray GC. Infection Due to 3 Avian Influenza Subtypes in United States Veterinarians. Clin Infect Dis. 2007;45: 4–9. doi: 10.1086/518579 17554693

3. Fragaszy E, Ishola DA, Brown IH, Enstone J, Nguyen‐Van‐Tam JS, Simons R, et al. Increased risk of A(H1N1)pdm09 influenza infection in UK pig industry workers compared to a general population cohort. Influenza Other Respir Viruses. 2016;10: 291–300. doi: 10.1111/irv.12364 26611769

4. Vincent AL, Ma W, Lager KM, Janke BH, Richt JA. Chapter 3 Swine Influenza Viruses: A North American Perspective. Advances in Virus Research. Academic Press; 2008. pp. 127–154. doi: 10.1016/S0065-3527(08)00403-X

5. Opriessnig T, Giménez-Lirola LG, Halbur PG. Polymicrobial respiratory disease in pigs. Anim Health Res Rev. 2011;12: 133–148. doi: 10.1017/S1466252311000120 22152290

6. Schmidt C, Cibulski SP, Andrade CP, Teixeira TF, Varela APM, Scheffer CM, et al. Swine Influenza Virus and Association with the Porcine Respiratory Disease Complex in Pig Farms in Southern Brazil. Zoonoses Public Health. 2016;63: 234–240. doi: 10.1111/zph.12223 26302164

7. Myers KP, Olsen CW, Gray GC. Cases of Swine Influenza in Humans: A Review of the Literature. Clin Infect Dis Off Publ Infect Dis Soc Am. 2007;44: 1084–1088. doi: 10.1086/512813 17366454

8. Simon G, Larsen LE, Dürrwald R, Foni E, Harder T, Van Reeth K, et al. European Surveillance Network for Influenza in Pigs: Surveillance Programs, Diagnostic Tools and Swine Influenza Virus Subtypes Identified in 14 European Countries from 2010 to 2013. Vijaykrishna D, editor. PLoS ONE. 2014;9: e115815. doi: 10.1371/journal.pone.0115815 25542013

9. Suzuki Y, Ito T, Suzuki T, Holland RE, Chambers TM, Kiso M, et al. Sialic Acid Species as a Determinant of the Host Range of Influenza A Viruses. J Virol. 2000;74: 11825–11831. doi: 10.1128/jvi.74.24.11825-11831.2000 11090182

10. Ito T, Castrucci MR, Donatelli I, Kida H, Paulson JC, Webster RG, et al. Molecular Basis for the Generation in Pigs of Influenza A Viruses with Pandemic Potential. J VIROL. 1998;72: 7.

11. Meurens F, Summerfield A, Nauwynck H, Saif L, Gerdts V. The pig: a model for human infectious diseases. Trends Microbiol. 2012;20: 50–57. doi: 10.1016/j.tim.2011.11.002 22153753

12. Canini L, Carrat F. Population Modeling of Influenza A/H1N1 Virus Kinetics and Symptom Dynamics. J Virol. 2011;85: 2764–2770. doi: 10.1128/JVI.01318-10 21191031

13. Hemmink JD, Morgan SB, Aramouni M, Everett H, Salguero FJ, Canini L, et al. Distinct immune responses and virus shedding in pigs following aerosol, intra-nasal and contact infection with pandemic swine influenza A virus, A(H1N1)09. Vet Res. 2016;47. doi: 10.1186/s13567-016-0390-5 27765064

14. Janke BH. Influenza A Virus Infections in Swine: Pathogenesis and Diagnosis. Vet Pathol. 2014;51: 410–426. doi: 10.1177/0300985813513043 24363301

15. Rajao DS, Vincent AL. Swine as a Model for Influenza A Virus Infection and Immunity. ILAR J. 2015;56: 44–52. doi: 10.1093/ilar/ilv002 25991697

16. Baccam P, Beauchemin C, Macken CA, Hayden FG, Perelson AS. Kinetics of Influenza A Virus Infection in Humans. J Virol. 2006;80: 7590–7599. doi: 10.1128/JVI.01623-05 16840338

17. Pawelek KA, Huynh GT, Quinlivan M, Cullinane A, Rong L, Perelson AS. Modeling Within-Host Dynamics of Influenza Virus Infection Including Immune Responses. PLOS Comput Biol. 2012;8: e1002588. doi: 10.1371/journal.pcbi.1002588 22761567

18. Miao H, Hollenbaugh JA, Zand MS, Holden-Wiltse J, Mosmann TR, Perelson AS, et al. Quantifying the Early Immune Response and Adaptive Immune Response Kinetics in Mice Infected with Influenza A Virus. J Virol. 2010;84: 6687–6698. doi: 10.1128/JVI.00266-10 20410284

19. Porta M. A Dictionary of Epidemiology. Oxford University Press; 2014.

20. Rose N, Hervé S, Eveno E, Barbier N, Eono F, Dorenlor V, et al. Dynamics of influenza A virus infections in permanently infected pig farms: evidence of recurrent infections, circulation of several swine influenza viruses and reassortment events. Vet Res. 2013;44: 72. doi: 10.1186/1297-9716-44-72 24007505

21. Carrat F, Vergu E, Ferguson NM, Lemaitre M, Cauchemez S, Leach S, et al. Time Lines of Infection and Disease in Human Influenza: A Review of Volunteer Challenge Studies. Am J Epidemiol. 2008;167: 775–785. doi: 10.1093/aje/kwm375 18230677

22. Hayden FG, Fritz R, Lobo MC, Alvord W, Strober W, Straus SE. Local and systemic cytokine responses during experimental human influenza A virus infection. Relation to symptom formation and host defense. 1998 [cited 16 Jul 2018]. doi: 10.1172/JCI1355 9449698

23. Fritz RS, Hayden FG, Calfee DP, Cass LM, Peng AW, Alvord WG, et al. Nasal cytokine and chemokine responses in experimental influenza A virus infection: results of a placebo-controlled trial of intravenous zanamivir treatment. J Infect Dis. 1999;180: 586–593. doi: 10.1086/314938 10438343

24. Romagosa A, Allerson M, Gramer M, Joo H, Deen J, Detmer S, et al. Vaccination of influenza a virus decreases transmission rates in pigs. Vet Res. 2011;42: 120. doi: 10.1186/1297-9716-42-120 22185601

25. Cador C, Hervé S, Andraud M, Gorin S, Paboeuf F, Barbier N, et al. Maternally-derived antibodies do not prevent transmission of swine influenza A virus between pigs. Vet Res. 2016;47. doi: 10.1186/s13567-016-0365-6 27530456

26. Grassly NC, Fraser C. Mathematical models of infectious disease transmission. Nat Rev Microbiol. 2008;6: 477–487. doi: 10.1038/nrmicro1845 18533288

27. Neira V, Rabinowitz P, Rendahl A, Paccha B, Gibbs SG, Torremorell M. Characterization of Viral Load, Viability and Persistence of Influenza A Virus in Air and on Surfaces of Swine Production Facilities. PLOS ONE. 2016;11: e0146616. doi: 10.1371/journal.pone.0146616 26757362

28. Lewis NS, Russell CA, Langat P, Anderson TK, Berger K, Bielejec F, et al. The global antigenic diversity of swine influenza A viruses. eLife. 2016;5: e12217. doi: 10.7554/eLife.12217 27113719

29. Swindle MM, Makin A, Herron AJ, Clubb FJ, Frazier KS. Swine as models in biomedical research and toxicology testing. Vet Pathol. 2012;49: 344–356. doi: 10.1177/0300985811402846 21441112

30. Ng S, Nachbagauer R, Balmaseda A, Stadlbauer D, Ojeda S, Patel M, et al. Novel correlates of protection against pandemic H1N1 influenza A virus infection. Nat Med. 2019;25: 962. doi: 10.1038/s41591-019-0463-x 31160818

31. Powell TJ, Silk JD, Sharps J, Fodor E, Townsend ARM. Pseudotyped Influenza A Virus as a Vaccine for the induction of Heterotypic Immunity. J Virol. 2012; JVI.01820-12. doi: 10.1128/JVI.01820-12 23015719

32. Gelman A. Scaling regression inputs by dividing by two standard deviations. Stat Med. 2008;27: 2865–2873. doi: 10.1002/sim.3107 17960576

33. Gelman A, Jakulin A, Pittau MG, Su Y-S. A weakly informative default prior distribution for logistic and other regression models. Ann Appl Stat. 2008;2: 1360–1383. doi: 10.1214/08-AOAS191

34. Bürkner P-C. brms : An R Package for Bayesian Multilevel Models Using Stan. J Stat Softw. 2017;80.

35. Vehtari A, Gelman A, Gabry J. Practical Bayesian model evaluation using leave-one-out cross-validation and WAIC. Stat Comput. 2017;27: 1413–1432. doi: 10.1007/s11222-016-9696-4

36. Lavielle M, Mbogning C. An improved SAEM algorithm for maximum likelihood estimation in mixtures of non linear mixed effects models. Stat Comput. 2014;24: 693–707. doi: 10.1007/s11222-013-9396-2

37. Mbogning C, Bleakley K, Lavielle M. Between-Subject and Within-Subject Model Mixtures for Classifying HIV Treatment Response. Prog Appl Math. 2012;4: 148–166. doi: 10.3968/j.pam.1925252820120402.S0801

38. Kuhn E, Lavielle M. Maximum likelihood estimation in nonlinear mixed effects models. Comput Stat Data Anal. 2005;49: 1020–1038. doi: 10.1016/j.csda.2004.07.002

39. Chao DL, Halloran ME, Obenchain VJ, L IM Jr. FluTE, a Publicly Available Stochastic Influenza Epidemic Simulation Model. PLOS Comput Biol. 2010;6: e1000656. doi: 10.1371/journal.pcbi.1000656 20126529

40. Punpanich W, Chotpitayasunondh T. A review on the clinical spectrum and natural history of human influenza. Int J Infect Dis. 2012;16: e714–e723. doi: 10.1016/j.ijid.2012.05.1025 22784546

41. Ferguson NM, Cummings DAT, Cauchemez S, Fraser C, Riley S, Meeyai A, et al. Strategies for containing an emerging influenza pandemic in Southeast Asia. Nature. 2005;437: 209–214. doi: 10.1038/nature04017 16079797

42. Tuszynski J , Tuszynski M . The caTools package. 2007.

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