Emerging Infections Program Efforts to Address Health Equity - Volume 21, Number 9—September 2015 - Emerging Infectious Disease journal - CDC

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Emerging Infections Program Efforts to Address Health Equity - Volume 21, Number 9—September 2015 - Emerging Infectious Disease journal - CDC

Volume 21, Number 9—September 2015
THEME ISSUE
Emerging Infections Program

Emerging Infections Program

Emerging Infections Program Efforts to Address Health Equity

On This Page

• EIP and Health Disparities
• EIP Health Equity Working Group
• Future Directions
• Suggested Citation

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• Figure 1
• Figure 2

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James L. Hadler , Duc J. Vugia, Nancy M. Bennett, and Matthew R. Moore

Author affiliations: Connecticut Emerging Infections Program, Yale School of Public Health, New Haven, Connecticut, USA (J.L. Hadler); California Emerging Infections Program, California Department of Public Health, Richmond, California, USA (D.J. Vugia); New York Emerging Infections Program, University of Rochester Medical Center, Rochester, New York, USA (N.M. Bennett); Centers for Disease Control and Prevention, Atlanta, Georgia, USA (M.R. Moore)

Suggested citation for this article

Abstract

The Emerging Infections Program (EIP), a collaboration between (currently) 10 state health departments, their academic center partners, and the Centers for Disease Control and Prevention, was established in 1995. The EIP performs active, population-based surveillance for important infectious diseases, addresses new problems as they arise, emphasizes projects that lead to prevention, and develops and evaluates public health practices. The EIP has increasingly addressed the health equity challenges posed by Healthy People 2020. These challenges include objectives to increase the proportion of Healthy People–specified conditions for which national data are available by race/ethnicity and socioeconomic status as a step toward first recognizing and subsequently eliminating health inequities. EIP has made substantial progress in moving from an initial focus on monitoring social determinants exclusively through collecting and analyzing data by race/ethnicity to identifying and piloting ways to conduct population-based surveillance by using area-based socioeconomic status measures.

Describing health disparities and achieving health equity have been priorities of the national public health agenda for the past 20 years. One of the 2 goals of Healthy People (HP) 2010, the public health agenda for 2000–2010, was to “eliminate health disparities among different segments of the population, including differences that occur by gender, race or ethnicity, education or income, disability, geographic location, or sexual orientation” (1). In addition, HP 2010 included a related public health infrastructure objective (23.4), to track HP 2010 objectives by each population group. HP 2020, the agenda for 2010–2020, specifically added mention of social determinants of health. It reframed the goal and the related infrastructure objective, the former as “Achieve health equity, eliminate disparities, and improve the health of all groups,” and the latter, now Public Health Infrastructure Objective (7.1), as “Increase the proportion of population-based Healthy People 2020 objectives for which national data are available for all population groups” with a specific subobjective (7.3) “by socioeconomic status” (2).The World Health Organization, in a similar vein, recently recognized that addressing the social determinants of health was a key priority to eventually achieving health equity (3).

The Emerging Infections Program (EIP), established by the Centers for Disease Control and Prevention (CDC) in 1995, is a network that now includes 10 state health departments and their collaborators in local health departments, academic institutions, other federal agencies, and public health and clinical laboratories, with a catchment area of ≈44 million persons (4–7). In addition to performing active, population-based surveillance for important infectious diseases, EIP activities are intended to be flexible and address new problems as they arise, answer critical public health questions, emphasize projects that lead to prevention, and develop and evaluate public health practices. In this context, the EIP has increasingly taken on the challenges posed by HP 2010 and HP 2020, moving from a focus on monitoring social determinants exclusively through collecting and analyzing data by race/ethnicity to identifying and piloting ways to conduct population-based surveillance by using socioeconomic status (SES) measures with an ultimate focus on working toward health equity.

Most data collected by EIP sites comes from laboratory-based surveillance for bacterial, parasitic, and viral diseases, which does not include individual-level SES information. Missing data, especially ethnicity, is a consistent challenge. However, because residency in an EIP catchment area is a requirement for inclusion in surveillance, and to enable deduplication of multiple reports, addresses of residence for individual case-patients are collected at the time of diagnosis, making it possible to link cases to specific census tracts. With linkage to census tract, a wealth of data on census tract–level SES status indicators (e.g., poverty, education level, crowding) becomes available. Seminal work done by Nancy Krieger and colleagues in the Public Health Disparities Geocoding Project found that these census tract–level SES measures, especially low SES status (usually the lowest quartile or quintile of each measure), often predict disease incidence and mortality rates (8,9) and do so within and across groups defined by race/ethnicity. These authors recommended routine use of area-based SES measures in disease surveillance to describe and monitor, over time, disparities by SES, particularly poverty as measured by the percentage of persons in a census tract who lived below the federal poverty level.

In this article, we describe the evolution of EIP involvement in monitoring health disparities and in working toward health equity. These efforts began with a focus on race/ethnicity and, more recently, have included the piloting use of area-based SES measures under the guidance of a Health Equity Working Group.

Dr. Hadler has worked with the EIP since its inception in 1995, first as the Connecticut State Epidemiologist and, more recently, at the Yale School of Public Health where he is clinical professor of epidemiology. He is co-chair of the Council of State and Territorial Epidemiologists Health Disparities Subcommittee. His research interests include infectious disease surveillance and prevention and health inequities.

Acknowledgments

We acknowledge the contributions of the members of the EIP Steering Committee and the Health Equity Workgroup for their interest in expanding EIP surveillance to include measures of socioeconomic status and to develop standardized protocols to facilitate it.

The work on this manuscript was supported directly by the Centers for Disease Control and Prevention (CDC) (M.R.M.) or by Cooperative Agreement 5U50-CK000195 from the CDC (J.L.H., D.J.V., N.M.B.). The authors have no conflicts of interest to disclose.

References

1. US Department of Health and Human Services. Healthy People 2010: understanding and improving health. 2nd ed. Washington (DC): US Government Printing Office; 2000. p. 11 [cited 2015 Apr 11]. http://www.healthypeople.gov/2010/document/pdf/uih/2010uih.pdf
2. US Department of Health and Human Services. Healthy People 2020 topics and objectives: public health infrastructure [cited 2015 Apr 11].http://www.healthypeople.gov/2020/topics-objectives/topic/public-health-infrastructure/objectives
3. Commission on Social Determinants of Health. Closing the gap in a generation: health equity through action on the social determinants of health. Final report of the Commission on Social Determinants of Health. Geneva: the Commission; 2008 [cited 2015 Apr 11].http://www.who.int/social_determinants/thecommission/finalreport/en/
4. Centers for Disease Control and Prevention. Emerging Infections Programs [cited 2015 Apr 11]. http://www.cdc.gov/ncezid/dpei/eip/index.html
5. Pinner RW. Addressing the challenges of emerging infectious disease. Am J Med Sci. 1996;311:3–8. DOIPubMed
6. Pinner RW, Rebmann CA, Schuchat A, Hughes JM. Disease surveillance and the academic, clinical, and public health communities. Emerg Infect Dis.2003;9:781–7.PubMed
7. Pinner RW, Lynfield R, Hadler JL, Schaffner W, Farley MM, Frank ME, Cultivation of an adaptive domestic network for surveillance and evaluation of emerging infections. [zzz–zzz.]. Emerg Infect Dis. 2015;21:1499–1509.
8. Krieger N, Chen JT, Waterman PD, Rehkopf DH, Subramanian SV. Painting a truer picture of US socioeconomic and racial/ethnic health inequalities: The Public Health Disparities Geocoding Project. Am J Public Health. 2005;95:312–23. DOIPubMed
9. Public Health Disparities Geocoding Project Monograph [cited 2015 Feb 15]. http://www.hsph.harvard.edu/thegeocodingproject
10. Bennett NM, Buffington J, LaForce FM. Pneumococcal bacteremia in Monroe County, New York: incidence, case fatality, and comorbid conditions.Am J Public Health. 1992;82:1513–6. DOIPubMed
11. Robinson KA, Baughman W, Rothrock G, Barrett NL, Pass M, Lexau C, Epidemiology of invasive Streptococcus pneumoniae infections in the United States, 1995–1998. Opportunities for prevention in the conjugate vaccine era. JAMA. 2001;285:1729–35. DOIPubMed
12. Flannery B, Schrag S, Bennett NM, Lynfield R, Harrison LH, Reingold A, Impact of childhood vaccination on racial disparities in invasiveStreptococcus pneumoniae infections. JAMA. 2004;291:2197–203. DOIPubMed
13. Talbot TR, Poehling KA, Hartert TV, Arbogast PG, Halasa NB, Mitchel E, Elimination of racial differences in invasive pneumococcal disease in young children after introduction of the conjugate pneumococcal vaccine. Pediatr Infect Dis J. 2004;23:726–31. DOIPubMed
14. Poehling KA, Talbot TR, Griffin MR, Craig AS, Whitney CG, Zell E, Decline in invasive pneumococcal disease among young infants and elimination of racial differences in disease rates following introduction of the pneumococcal conjugate vaccine. JAMA. 2006;295:1668–74. DOIPubMed
15. Wortham JM, Zell ER, Pondo T, Harrison LH, Schaffner W, Lynfield R, Racial disparities in invasive Streptococcus pneumoniae infections, 1998–2009. Clin Infect Dis. 2014;58:1250–7. DOIPubMed
16. US Department of Health and Human Services (DHHS). HHS action plan to reduce health disparities: a nation free of disparities in health and health care. Washington (DC): The Department; 2011 [cited 2015 Apr 12]. http://minorityhealth.hhs.gov/npa/files/Plans/HHS/HHS_Plan_complete.pdf
17. Ramakrishnan M, Moisi JC, Klugman KP, Iglesias JM, Grant LR, Mpoudi-Etame M, Increased risk of invasive bacterial infections in African people with sickle-cell disease: a systematic review and meta-analysis. Lancet Infect Dis. 2010;10:329–37. DOIPubMed
18. Muhammad RD, Oza-Frank R, Zell E, Link-Gelles R, Narayan KM, Schaffner W, Epidemiology of invasive pneumococcal disease among high-risk adults since the introduction of pneumococcal conjugate vaccine for children. Clin Infect Dis. 2013;56:e59–67. DOIPubMed
19. Nuorti JP, Butler JC, Gelling L, Kool JL, Reingold AL, Vugia DJ. Epidemiologic relation between HIV and invasive pneumococcal disease in San Francisco County, California. Ann Intern Med. 2000;132:182–90. DOIPubMed
20. Burton DC, Flannery B, Bennett NM, Farley MM, Gershman K, Harrison LH, Socioeconomic and racial/ethnic disparities in the incidence of bacteremic pneumonia among US adults. Am J Public Health. 2010;100:1904–11. DOIPubMed
21. Soto K, Petit S, Hadler JL. Changing disparities in invasive pneumococcal disease by socioeconomic status and race/ethnicity in Connecticut, 1998–2008. Public Health Rep. 2011;126(Suppl 3):81–8 .PubMed
22. Schuchat A, Oxtoby M, Cochi S, Sikes RK, Hightower A, Plikaytis B, Population-based risk factors for neonatal group B streptococcal disease: results of a cohort study in metropolitan Atlanta. J Infect Dis. 1990;162:672–7. DOIPubMed
23. Schwartz B, Schuchat A, Oxtoby MJ, Cochi SL, Hightower A, Broome CV. Invasive group B streptococcal disease in adults. A population-based study in metropolitan Atlanta. JAMA. 1991;266:1112–4. DOIPubMed
24. Schrag SJ, Zywicki S, Farley MM, Reingold AL, Harrison LH, Lefkowitz LB, Group B streptococcal disease in the era of intrapartum antibiotic prophylaxis. N Engl J Med. 2000;342:15–20. DOIPubMed
25. Centers for Disease Control and Prevention. Diminishing racial disparities in early-onset neonatal group B streptococcal disease—United States, 2000–2003. MMWR Morb Mortal Wkly Rep. 2004;53:502–5 .PubMed
26. Centers for Disease Control and Prevention. Perinatal group B streptococcal disease after universal screening recommendations—United States, 2003–2005. MMWR Morb Mortal Wkly Rep. 2007;56:701–5 .PubMed
27. Centers for Disease Control and Prevention. Trends in perinatal group B streptococcal disease–United States, 2000–2006. MMWR Morb Mortal Wkly Rep. 2009;58:109–12 .PubMed
28. Jordan HT, Farley MM, Craig A, Mohle-Boetani J, Harrison LH, Petit S, Revisiting the need for vaccine prevention of late-onset neonatal group B streptococcal disease: a multistate, populations-based analysis. Pediatr Infect Dis J. 2008;27:1057–64. DOIPubMed
29. Weston EJ, Pondo T, Lewis MM, Martell-Cleary P, Morin C, Jewell B, The burden of invasive early-onset neonatal sepsis in the United States, 2005–2008. Pediatr Infect Dis J. 2011;30:937–41. DOIPubMed
30. O’Brien KL, Beall B, Barrett NL, Cieslak PR, Reingold A, Farley MM, Epidemiology of invasive group A Streptococcus disease in the United States, 1995–1999. Clin Infect Dis. 2002;35:268–76 . DOIPubMed
31. Passaro DJ, Smith DS, Hett EC, Reingold AL, Daily P, Van Beneden CA, Invasive group A streptococcal infections in the San Francisco Bay area, 1989–1999. Epidemiol Infect. 2002;129:471–8. DOIPubMed
32. Yousey-Hindes KM, Hadler JL. Neighborhood socioeconomic status and influenza hospitalizations among children: New Haven County, Connecticut, 2003–2010. Am J Public Health. 2011;101:1785–9. DOIPubMed
33. Tam K, Yousey-Hindes K, Hadler JL. Influenza-related hospitalization of adults associated with low census tract socioeconomic status and female sex in New Haven County, Connecticut, 2007–2011. Influenza Other Respir Viruses. 2014;8:274–81.
34. Bemis K, Marcus R, Hadler JL. Socioeconomic status and campylobacteriosis, Connecticut, USA, 1999–2009 [Letter]. Emerg Infect Dis.2014;20:1240–2 .PubMed
35. Niccolai LM, Julian PJ, Bilinski A, Mehta NR, Meek JI, Zelterman D, Geographic povery and racial/ethnic disparities in cervical cancer precursor rates in Connecticut, 2008–2009. Am J Public Health. 2013;103:156–63. DOIPubMed
36. Lembo NJ. Pneumococcal infections in children with sickle cell disease: increased incidence, immunological defects, vaccine failure, and prospects for the future. J Natl Med Assoc. 1981;73:43–5 .PubMed
37. Roongpiboonsopit D, Harimi HA. Quality assessment of online street and rooftop geocoding services. Cartogr Geogr Inf Sci. 2010;37:301–18.
38. Hampton KH, Fitch MK, Allshouse WB, Doherty IA, Gesink DC, Leone PA, Mapping health data: improved privacy protection with donut method geomasking. Am J Epidemiol. 2010;172:1062–9. DOIPubMed
39. McEwen BS. Protective and damaging effects of stress mediators. N Engl J Med. 1998;338:171–9. DOIPubMed
40. Shonkoff JP, Garner AS; Committee on Psychosocial Aspects of Child and Family Health. Committee on Early Childhood, Adoption, and Dependent Care; Section on Developmental and Behavioral Pediatrics. The lifelong effects of early childhood adversity and toxic stress. Pediatrics.2012;129:e232–46. DOIPubMed

Figures

• Figure 1. Simplified causal pathway previously accessible by using Emerging Infections Program (EIP) data.
• Figure 2. Framework for considering social disparities of health determined by the Commission on Social Determinants of Health, World Health Organization (3).

Suggested citation for this article: Hadler JL, Vugia DJ, Bennett NM, Moore MR. Emerging Infections Program efforts to address health equity. Emerg Infect Dis. 2015 Sept [date cited]. http://dx.doi.org/10.3201/eid2109.150275

DOI: 10.3201/eid2109.150275