Abstract
At the Centers for Disease Control and Prevention, there is a growing interest in promoting the use of mathematical modeling to support public health policies. This chapter presents three examples of operations research models developed and employed by the Centers for Disease Control and Prevention. First, we discuss the Adult Immunization Scheduler, which uses dynamic programming methods to establish a personalized vaccination schedule for adults aged 19 and older. The second operations research project is a discrete event simulation model used to estimate the throughput and budget for mass vaccination clinics during the 2009–2010 H1N1 pandemic. Lastly, we describe a national HIV resource allocation model that uses nonlinear programming methods to optimize the allocation of funds to HIV prevention programs and populations.
Keywords
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsReferences
Centers for Disease Control and Prevention (2010) Recommended adult immunization schedule—United States. http://www.cdc.gov/vaccines/recs/schedules/downloads/adult/2010/adult-schedule.pdf. Accessed 15 Nov 2010
National Center for Health Statistics—United States (2007 (Revised 2008)) Vaccination coverage among U.S. adults, National Immunization Survey—Adult. http://www.cdc.gov/vaccines/stats-surv/nis/downloads/nis-adult-summer-2007.pdf. Accessed 15 Nov 2010
California Department of Public Health (2010) Pertussis report. p 5
Wendelboe A et al. (2007) Transmission of Bordetella pertussis to young infants. Pediatr Infect Dis J 26(4):293–299
Centers for Disease Control and Prevention (2010) Catch-up Immunization Scheduler for children six years of age and younger. http://www.cdc.gov/vaccines/recs/Scheduler/catchup.htm. Accessed 15 Nov 2010
Engineer FG, Keskinocak P, Pickering LK (2009) OR practice—catch-up scheduling for childhood vaccination. Oper Res 57(6):1307–1319
Smalley HK et al. (2011) Universal tool for vaccine scheduling—applications for children and adults. Interfaces 41(5):436–454
Cho B-H et al. (2011) A tool for the economic analysis of mass prophylaxis operations with an application to H1N1 influenza vaccination clinics. J Public Health Manag Pract 17(1):E22–E28
Washington ML (2009) Evaluating the capability and cost of a mass influenza and pneumococcal vaccination clinic via computer simulation. Med Decis Making 29(4):414–423
Luenberger DG (1979) Introduction to dynamic systems: theory, models, and applications. Wiley, New York, p 446
Zaric GS et al. (1998) The effect of protease inhibitors on the spread of HIV and the development of drug resistance: a simulation study. Simulation 71:262–275
Marks G et al. (2005) Meta-analysis of high-risk sexual behavior in persons aware and unaware they are infected with HIV in the United States: implications for HIV prevention programs. J Acquir Immune Defic Syndr 39:446–453
Weinhardt LS et al. (1999) Effects of HIV counseling and testing on sexual risk behavior: a meta-analytic review of published research, 1985–1997. Am J Public Health 89(9):1397–1405
Marks G et al. (2009) Understanding differences in HIV sexual transmission among Latino and black men who have sex with men: the Brothers y Hermanos study. AIDS Behav 13(4):682–690
Lasry A et al. (2011) A model for allocating CDC’s HIV prevention resources in the United States. Health Care Manag Sci 14(1):115–124
Lasry A et al. (2012) Allocating HIV prevention funds in the United States: recommendations from an optimization model. PLoS ONE 7(6):e37545
Schackman BR et al. (2006) The lifetime cost of current human immunodeficiency virus care in the United States. Med Care 44(11):990–997
The White House Office of National AIDS Policy (2010) National HIV/AIDS strategy for the United States. Washington, DC. p 60
Mooney G (1998) “Communitarian claims” as an ethical basis for allocating health care resources. Soc Sci Med 47(9):1171–1180
Kahn JG, Marseille E (2002) A saga in international HIV policy modeling: preventing mother-to-child HIV transmission. J Policy Anal Manag 21(3):499–505
McGregor M (2006) What decision-makers want and what they have been getting. Value Health 9(3):181–185
Lasry A, Carter MW, Zaric GS (2011) Allocating funds for HIV/AIDS: a descriptive study of KwaDukuza, South Africa. Health Policy Plan 26:33
Lasry A, Richter A, Lutscher F (2009) Recommendations for increasing the use of HIV/AIDS resource allocation models. BMC Public Health 9(Suppl 1):S8
Keeney RL (1988) Structuring objectives for problems of public interest. Oper Res 36(3):396–405
Pinkerton SD et al. (2002) Ethical issues in cost-effectiveness analysis. Eval Program Plann 25:71–83
Granata AV, Hillman AL (1998) Competing practice guidelines: using cost-effectiveness analysis to make optimal decisions. Ann Intern Med 128(1):56–63
Jackson T (1996) Health economics and policy: ethical dilemmas in the science of scarcity. In: Daly J (ed) Ethical intersections: health research, methods, and researcher responsibility. Westview Press, Boulder, CO, p 127–138
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer Science+Business Media New York
About this chapter
Cite this chapter
Lasry, A., Washington, M.L., Smalley, H.K., Engineer, F., Keskinocak, P., Pickering, L. (2013). Public Health Modeling at the Centers for Disease Control and Prevention. In: Zaric, G. (eds) Operations Research and Health Care Policy. International Series in Operations Research & Management Science, vol 190. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-6507-2_1
Download citation
DOI: https://doi.org/10.1007/978-1-4614-6507-2_1
Published:
Publisher Name: Springer, New York, NY
Print ISBN: 978-1-4614-6506-5
Online ISBN: 978-1-4614-6507-2
eBook Packages: Business and EconomicsBusiness and Management (R0)