WJV  Vol.2 No.1 , February 2012
Modelling Influenza Vaccination Outcomes
ABSTRACT
Modelling response to influenza vaccination can improve our understanding of how proposed factors, older age, past exposure to influenza viruses, and health disorders, used together, affect antibody production after influenza vaccination. Knowledge about this may be important when planning influenza vaccination protocols. This problem will be emphasized especially in the future, when many alternative vaccines and vaccination approaches are likely to be allowed for a routine use. A major difficulty, in modelling response to influenza vaccination, is how to identify health parameters, suitable for general use. To deal with the complexity of this task, we reached out for the concept of a systems biology and machine learning methods. Based on this approach, we showed that it is possible to construct useful models of influenza vaccination outcomes. In addition, by varying criteria for definition of the model’s outcome measure, that is, of low antibody response to influenza vaccination, we showed that a set of health parameters, albeit limited, are necessary for model to achieve a wider practical use.

Cite this paper
L. Trtica-Majnaric, N. Sarlija and B. Vitale, "Modelling Influenza Vaccination Outcomes," World Journal of Vaccines, Vol. 2 No. 1, 2012, pp. 12-20. doi: 10.4236/wjv.2012.21002.
References
[1]   W. A. Keitel, T. R. Cate and R. B. Couch, “Efficacy of Sequential Annual Vaccination with Inactivated Influenza Virus Vaccine,” American Journal of Epidemiology, Vol. 127, No. 2, 1988, pp. 53-64.

[2]   K. L. Nichol, K. L. Margolis, J. Wuorenma and T. von Sternberg, “The Efficacy and Cost Effectiveness of Vaccination against Influenza among Elderly Persons Living in the Community,” New England Journal of Medicine, Vol. 331, No. 12, 1994, pp. 778-784. doi:10.1056/NEJM199409223311206

[3]   Center for Disease Control and Prevention, Immunization Practices Advisory Committee, “Prevention and Control of Influenza. Recommendations of the Advisory Committee on Immunization Practices,” MMWR Morbidity, Mortality Weekly Report, Vol. 56, No. RR-6, 2007, pp. 1-54.

[4]   P. A. Gross, A. W. Hermogenes, H. S. Sacks, J. Lau and R. A. Levandowski, “The Efficacy of Influenza Vaccine in Elderly Persons. A Meta-Analysis and Review of the Literature,” Annals of Internal Medicine, Vol. 123, No. 7, 1995, pp. 518-527.

[5]   Zh. M. E. Govaert, M. J. W. Sprenger, G. J. Dinant, K. Aretz, N. Masurel and J. A. Knottnerus, “Immune Response to Influenza Vaccination of Elderly People. A Randomized Double-Blind Placebo-Controlled Trial,” Vaccine, Vol. 12, No. 13, 1994, pp. 1185-1189. doi:10.1016/0264-410X(94)90241-0

[6]   A. M. Palache, I. A. de Bruijn and J. Nauta, “Influenza Immunization. I: Influenza Vaccination Polices and New Vaccine Developments. II: Fifteen Years’ Experience with a Subunit Influenza Vaccine,” Journal of Clinical Research, Vol. 2, 1999, pp. 111-139.

[7]   P. K. Tosh and G. A. Poland, “Emerging Vaccines for Influenza,” Experimental Opinion on Emerging Drugs, Vol. 13, No. 1, 2008, pp. 21-40. doi:10.1517/14728214.13.1.21

[8]   C. van Hoecke, V. Prikazsky, I. Uto and C. Menschikowski, “Immunogenecity of an Inactivated Split Influenza Vaccine in Institutionalized Elderly Patients,” Gerontology, Vol. 42, No. 4, 1996, pp. 190-198. doi:10.1159/000213792

[9]   L. B. Brydak and M. Machala, “Humoral Immune Response to Influenza Vaccination in Patients from High Risk Groups,” Drugs, Vol. 60, No. 1, 2000, pp. 35-53. doi:10.2165/00003495-200060010-00004

[10]   S. Allsup, A. Haycox, M. Regan and M. Gosney, “Is Influenza Vaccination Cost Effective for Healthy People between Ages 65 and 74 Years? A Randomized Controlled Trial,” Vaccine, Vol. 23, No. 5, 2004, pp. 639-645.

[11]   C. van Weel and J. A. Knottnerus, “Evidence-Based Interventions and Comprehensive Treatment,” The Lancet, Vol. 353, No. 9156, 1999, pp. 916-918. doi:10.1016/S0140-6736(98)08024-6

[12]   E. J. Remarque, “Influenza Vaccination in Elderly People,” Experimental Gerontology, Vol. 34, No. 3, 1999, pp. 445-452. doi:10.1016/S0531-5565(99)00007-8

[13]   W. E. Beyer, A. M. Palache, M. J. Sprenger, E. Hendriksen, J. J. Tukker, R. Darioli, G. L. van der Water, N. Masurel and A. D. Osterhaus, “Effects of Repeated Annual Influenza Vaccination on Vaccine Sero-Response in Young and Elderly Adults,” Vaccine, Vol. 14, No. 14, 1996, pp. 1331-1339. doi:10.1016/S0264-410X(96)00058-8

[14]   M. L. Kohut, M. M. Cooper, M. S. Nickolaus, D. R. Russell and J. E. Cunnick, “Exercise and Psychosocial Factors Modulate Immunity to Influenza Vaccine in Elderly Individuals,” Journal of Gerontology, Vol. 57, No. 9, 2002, pp. 557-562.

[15]   M. Hara, K. Tanaka and Y. Hirota, “Immune Response to Influenza Vaccine in Healthy Adults and the Elderly: Association with Nutritional Status,” Vaccine, Vol. 23, No. 12, 2005, pp. 1457-1463. doi:10.1016/j.vaccine.2004.09.022

[16]   M. J. Campbell, “Statistics at Square Two,” Blackwell Publishing, Oxford, 2006. doi:10.1002/9780470755839

[17]   E. J. Remarque, H. J. M. Cools, T. J. Boere, R. J. van der Klis, N. Masurel and G. J. Ligthart, “Functional Disability and Antibody Response to Influenza Vaccine in Elderly Patients in a Dutch Nursing Home,” British Medical Journal, Vol. 312, No. 7037, 1996, p. 1015. doi:10.1136/bmj.312.7037.1015

[18]   P. Larranaga, B. Calvo, R. Santana, C. Bielza, J. Galdiano, I. Inza, R. A. Lozano, G. Santafe, A. Perez and V. Robles, “Machine Learning in Bioinformatics,” Briefings in Bioinformatics, Vol. 7, No. 1, 2005, pp. 86-112. doi:10.1093/bib/bbk007

[19]   F. Iris, “Biological Modeling in the Discovery and Validation of Cognitive Dysfunctions Biomarkers,“ In: C.W. Turck, Ed., Biomarkers for Psychiatric Disorders, Springer, New York, 2008, pp. 473-522. doi:10.1007/978-0-387-79251-4_19

[20]   Lj. Majnari?-Trtica and B. Vitale, “Systems Biology as a Conceptual Framework for Research in Family Medicine; Use in Predicting Response to Influenza Vaccination,” Primary Health Care Research & Development, Vol. 12, No. 4, 2011, pp. 310-321. doi:10.1017/S1463423611000089

[21]   W. A. Keitel, T. R. Cate and R. B. Couch, “Efficacy of Sequential Annual Vaccination with Inactivated Influenza Virus Vaccine,” American Journal of Epidemiology, Vol. 127, No. 2, 1988, pp. 353-364.

[22]   I. H. Witten and E. Franke (Eds.), “Data Mining. Practical Machine Learning Tools and Techniques. Chapter 4. Algorithms: The Basic Methods,” Morgan Kaufmann, San Francisco, 2005.

[23]   D. Gamberger and T. ?muc, “Data Mining Server. Zagreb: Institut Ru?er Bo?kovi?. Laboratory for Information System,” 2001. http://dms.irb.hr/

[24]   F. E. Jr. Harre, “Regression Modeling Strategies with Applications to Linear Models, Logistic Regression and Survival Analysis,” Springer, Berlin, 2001.

[25]   B. Rockhill, “Theorizing About Causes at the Individual Level While Estimating Effects at the Population Level. Implication for Prevention,” Epidemiology, Vol. 16, No. 1, 2005, pp. 124-129. doi:10.1097/01.ede.0000147111.46244.41

[26]   R. Pyhala, L. Kinnunen, V. Kumpulainen, N. Ikonen, M. Kleemola and K. Cantell, “Vaccination-Induced HI Antibody to Influenza A[H1N1] Viruses in Poorly Primed Adults Under Circumstances of Low Antigenic Drift,” Vaccine, Vol. 11, No. 10, 1993, pp. 1013-1017. doi:10.1016/0264-410X(93)90126-I

[27]   D. J. Smith, S. Forrest, D. H. Ackley and A. S. Perelson, “Variable Efficacy of Repeated Annual Influenza Vaccination,” PNAS, Vol. 96, No. 24, 1999, pp. 14001-14006. doi:10.1073/pnas.96.24.14001

[28]   M. F. Fenech, I. E. Dreosti and J. R. Rinaldi, “Folate, Vitamin B12, Homocysteine Status and Chromosome Damage Rate in Lymphocytes of Older Men,” Carcinogenesis, Vol. 18, No. 7, 1997, pp. 1329-1336. doi:10.1093/carcin/18.7.1329

[29]   K. Schroecksnadel, B. Frick, B. Wirleitner, C. Winkler, H. Schennach and D. Fuchs, “Moderate Hyperhomocysteinemia and Immune Activation,” Current Pharmaceutical Biotechnology, Vol. 5, No. 1, 2004, pp. 107-118.

[30]   S. Futagami, H. Takahashi, Y. Norose and M. Kobayashi, “Systemic and Local Immune Responses against Helicobacter pylori Urease in Patients with Chronic Gastritis, Distinct IgA and IgG Productive Sites,” GUT, Vol. 43, No. 2, 1998, pp. 168-175. doi:10.1136/gut.43.2.168

[31]   R. Pecoits-Filho, B. Lindholm and P. Stenvinkel, “The Malnutrition, Inflammation and Atherosclerosis [MIA] Syndrome—The Heart of the Matter,” Nephrology Dialysis Transplantation, Vol. 17, Supplement 11, 2002, pp. 28-31.

[32]   F. Magri, L. Cravello, L. Barili, S. Sarra, W. Cinchetti and F. Salmoiraghi, “Stress and Dementia: The Role of the Hypothalamopituitaryadrenal Axis,” Aging Clinical Experimental Research, Vol. 18, No. 2, 2006, pp. 167-170.

 
 
Top