%0 Journal Article %1 Sutton2010176 %A Sutton, K.L. %A Banks, H.T. %A Castillo-Chavez, C. %D 2010 %J Journal of Biological Dynamics %K (microorganisms); 80 Adolescent; Adult; Age Aged, Aged; Bacteria Child, Child; Communicable Computer Control; Disease Factors; Health; Humans; Immunization Infant, Infant; Infections; Middle Models, Newborn; Pneumococcal Pneumococcus Policy; Preschool; Programs; Public Simulation; Streptococcus Theoretical; Vaccination, Vaccines; adolescent; adult; age; aged; and article; child; computer control; health health; human; immunology; infant; infection infection; metabolism; methodology; middle model; newborn; over; pneumococcal pneumoniae pneumoniae; policy; preschool preventive public service; simulation; theoretical vaccination, vaccine, %N 2 %P 176-195 %R http://dx.doi.org/10.1080/17513750903023715 %T Public vaccination policy using an age-structured model of pneumococcal infection dynamics %U http://dx.doi.org/10.1080/17513750903023715 %V 4 %X Public health professionals are charged with the task of designing prevention programs for the effective control of biologically intricate infectious diseases at a population level. The effective vaccination of a population for pneumococcal diseases (infections caused by Streptococcus pneumoniae) remains a relevant question in the scientific community. It is complicated by heterogeneity in individuals' responses to exposure to the bacterium and their responses to vaccination. Due to these complexities, most modelling efforts in this area have been on the cellular/bacteria level. Here, we introduce an age-structured SEIS-type model of pneumococcal diseases and their vaccination. We discuss the use of this framework in predicting the impact of vaccine strategies, with pneumococcal diseases as an example. Using parameter values reasonable for a developed country, we discuss the effects of targeting the colonization and/or infection stages on the age profiles of morbidity in a population. Â\copyright 2010 Taylor & Francis.

@article{Sutton2010176, abstract = {Public health professionals are charged with the task of designing prevention programs for the effective control of biologically intricate infectious diseases at a population level. The effective vaccination of a population for pneumococcal diseases (infections caused by Streptococcus pneumoniae) remains a relevant question in the scientific community. It is complicated by heterogeneity in individuals' responses to exposure to the bacterium and their responses to vaccination. Due to these complexities, most modelling efforts in this area have been on the cellular/bacteria level. Here, we introduce an age-structured SEIS-type model of pneumococcal diseases and their vaccination. We discuss the use of this framework in predicting the impact of vaccine strategies, with pneumococcal diseases as an example. Using parameter values reasonable for a developed country, we discuss the effects of targeting the colonization and/or infection stages on the age profiles of morbidity in a population. {\^A}{\copyright} 2010 Taylor & Francis.}, added-at = {2017-11-10T22:48:29.000+0100}, affiliation = {Center for Research in Scientific Computation, Center for Quantitative Studies in Biomedicine, North Carolina State University, Raleigh, NC 27695-8212, United States; Department of Mathematics and Statistics, Arizona State University, Tempe AZ 85287-1804, United States; Mathematical, Computational and Modeling Sciences Center, Arizona State University, Tempe AZ 85287-1904, United States; School of Human Evolution and Social Change, Arizona State University, Tempe AZ 85287-2404, United States; Santa Fe Institute, Santa Fe, NM 87501, United States}, author = {Sutton, K.L. and Banks, H.T. and Castillo-Chavez, C.}, author_keywords = {Mathematical model; Pneumococcal infections; Vaccine strategies}, biburl = {https://www.bibsonomy.org/bibtex/28c8c27585328e9e4dc21b5122cb249fc/ccchavez}, correspondence_address1 = {Sutton, K. L.; Center for Research in Scientific Computation, Center for Quantitative Studies in Biomedicine, North Carolina State University, Raleigh, NC 27695-8212, United States; email: klsutton@ncsu.edu}, date-added = {2017-11-10 21:45:26 +0000}, date-modified = {2017-11-10 21:45:26 +0000}, document_type = {Article}, doi = {http://dx.doi.org/10.1080/17513750903023715}, interhash = {1b80b385a46ba34c72f2c4152c65be2e}, intrahash = {8c8c27585328e9e4dc21b5122cb249fc}, issn = {17513758}, journal = {Journal of Biological Dynamics}, keywords = {(microorganisms); 80 Adolescent; Adult; Age Aged, Aged; Bacteria Child, Child; Communicable Computer Control; Disease Factors; Health; Humans; Immunization Infant, Infant; Infections; Middle Models, Newborn; Pneumococcal Pneumococcus Policy; Preschool; Programs; Public Simulation; Streptococcus Theoretical; Vaccination, Vaccines; adolescent; adult; age; aged; and article; child; computer control; health health; human; immunology; infant; infection infection; metabolism; methodology; middle model; newborn; over; pneumococcal pneumoniae pneumoniae; policy; preschool preventive public service; simulation; theoretical vaccination, vaccine,}, language = {English}, number = 2, pages = {176-195}, pubmed_id = {22876985}, timestamp = {2017-11-10T22:48:29.000+0100}, title = {Public vaccination policy using an age-structured model of pneumococcal infection dynamics}, url = {http://dx.doi.org/10.1080/17513750903023715}, volume = 4, year = 2010 }