RESEARCH AND PRACTICE
Effect of Vaccination Coordinators on Socioeconomic Disparities in Immunization Among the 2006 Connecticut Birth Cohort Jessica A. Kattan, MD, MPH, Kathy S. Kudish, DVM, MSPH, Betsy L. Cadwell, MSPH, Kristen Soto, MPH, and James L. Hadler, MD, MPH
Recognizing disparities among population segments can be helpful in identifying barriers and delivering successful public health interventions. Disparities in early childhood vaccinations in the United States among socioeconomic and demographic groups have been described in previous analyses, with certain studies reporting successes in narrowing disparities.1,2 A few studies have examined disparities and risk factors for underimmunization by assessing the influence of census tract characteristics on individual children’s vaccination status.3 This approach is potentially useful because census tract poverty level has been demonstrated to be the most consistently discriminating area measure for monitoring socioeconomic inequalities in health.4 Analytic approaches, including census tract attributes and individual risk factors for underimmunization, allow for a comprehensive examination of health disparities in early childhood vaccinations. In 1993, the Centers for Disease Control and Prevention helped lead a national effort to improve early childhood vaccination rates, the Child Immunization Initiative (CII).5 This effort followed the national measles epidemic in 1989 to 1991, which was particularly severe among infants and preschool-aged children in poorer urban areas.6 Each state and large city receiving Centers for Disease Control and Prevention vaccinations cooperative agreement funding, including Connecticut, was required to develop an Immunization Action Plan (IAP) to improve early childhood vaccination levels. Implemented in 1993, the Connecticut IAP called for funding to support an early childhood vaccination coordinator position for the cities and health districts (i.e., groupings of towns served by a single local health department) with the largest populations of Medicaid and Special Supplemental Nutrition Program for Women, Infants, and Children
Objectives. We examined socioeconomic status (SES) disparities and the influence of state Immunization Action Plan–funded vaccination coordinators located in low-SES areas of Connecticut on childhood vaccination up-to-date (UTD) status at age 24 months. Methods. We examined predictors of underimmunization among the 2006 birth cohort (n = 34 568) in the state’s Immunization Information System, including individual demographic and SES data, census tract SES data, and residence in an area with a vaccination coordinator. We conducted multilevel logistic regression analyses. Results. Overall, 81% of children were UTD. Differences by race/ethnicity and census tract SES were typically under 5%. Not being UTD at age 7 months was the strongest predictor of underimmunization at age 24 months. Among children who were not UTD at age 7 months, only Medicaid enrollment (adjusted odds ratio [AOR] = 0.6; 95% confidence interval [CI] = 0.5, 0.7) and residence in an area with a vaccination coordinator (AOR = 0.7; 95% CI = 0.6, 0.9) significantly decreased the odds of subsequent underimmunization. Conclusions. SES disparities associated with underimmunization at age 24 months were limited. Efforts focused on vaccinating infants born in low SES circumstances can minimize disparities. (Am J Public Health. 2014;104:e74–e81. doi:10.2105/AJPH.2013.301418)
recipients, both markers of low socioeconomic status (SES). To the extent that funding permitted, the state also established outreach worker positions. The rationale for this design derived, in part, from the finding that children in poor urban areas of Connecticut had a much higher risk of measles during the 1989 to 1991 epidemic and from the results of several surveys of school children that retrospectively examined the vaccination status of first-grade students when they were aged 3 and 24 months. These surveys demonstrated substantial disparities in early childhood vaccination levels between children living in urban and nonurban areas and found a much higher probability of underimmunization among children attending public-sector clinics (e.g., community health centers).7 Use of public-sector clinics and living in urban areas in Connecticut are both markers of low SES. The role of the vaccination coordinator is to ensure that all infants born to city or health
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district residents are assigned to a patientcentered medical home (i.e., a comprehensive primary care provider), all providers have reminder---recall systems, all infants appearing to be out of care because of missed vaccinations are identified and returned to care, and provider-specific evaluation and feedback is provided. The size of the IAP program has fluctuated over time, reaching its peak in 2006. During 2006, 66% of the population in Connecticut was included in IAP areas staffed by 16 full-time vaccination coordinators and 10 outreach staff. The possible benefit of having dedicated vaccination coordinators in towns with large populations of Medicaid and Special Supplemental Nutrition Program for Women, Infants, and Children recipients in Connecticut has never been assessed formally. The Connecticut Immunization Registry and Tracking System (CIRTS) is the state’s Immunization Information System. Development of CIRTS began in 1994, and the system has been
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operational statewide for all children born in Connecticut since 1998. All providers are required to report to CIRTS all vaccinations administered to children aged 6 years and younger residing in Connecticut.8 In addition to vaccination information, the CIRTS database contains demographic information (e.g., address, sex, and race/ethnicity) and maternal information (e.g., age at delivery and educational level) regarding each child. CIRTS also contains Medicaid status, generated from periodic matches with the state Medicaid database. CIRTS has been used by IAP-funded cities and health districts to identify children not up-todate (UTD) with vaccinations at age 7 and 19 months and to recommend follow-up attention.
VACCINATION COVERAGE IN CONNECTICUT Connecticut has achieved relatively high statewide vaccination rates. During the 15 years prior to and including the 2006 birth cohort year (i.e., children born during 1992--2006), Connecticut ranked among the top 10 states for the standard vaccination series for children aged 19 to 35 months a total of 13 times and in the top 5 a total of 10 times, according to the National Immunization Survey.9 However, this survey has limited ability to assess vaccination coverage in smaller geographic areas. Efforts to examine risk factors for underimmunization on the individual and census tract level and to close any existing gaps are essential to further improve vaccination rates in Connecticut. Connecticut has provided nearly all vaccines free of charge to providers for vaccination of any child regardless of health insurance status in the state since the 1970s; the state funds vaccines for children who are not eligible for Medicaid or Vaccines for Children. Thus, eligibility for free vaccines should not be a contributor to disparities in vaccination status, as it might be in many states. Our study objectives were to (1) determine whether living in a city or health district with an IAP-funded vaccination coordinator, rather than living in an area without a coordinator, was associated with having higher early childhood age-appropriate vaccination rates approximately 15 years after initial implementation of the IAP, and (2) assess the effects of
individual and census tract characteristics on children’s UTD status regarding early childhood, age-appropriate vaccination series. We hypothesized an association between census tract poverty and UTD status, in line with previous studies that demonstrated census tract poverty to be associated with poor health outcomes and individual poverty to be associated with underimmunization in children.4,10---12
METHODS Our main outcome of interest was underimmunization (i.e., not being UTD) at age 24 months with the 4:3:1:2:3:1:4 vaccine series (‡ 4 doses of diphtheria and tetanus toxoids and acellular pertussis vaccine; ‡ 3 doses of poliovirus vaccine, ‡ 1 dose of measles-mumpsrubella vaccine, ‡ 2 doses of Haemophilus b conjugate vaccine, ‡ 3 doses of hepatitis B vaccine, ‡ 1 dose of varicella vaccine, and ‡ 2---4 age-appropriate doses of pneumococcal polysaccharide-protein conjugate vaccine) among children in the 2006 Connecticut birth cohort. We used 2 doses of Haemophilus b vaccine in the analysis because of the national shortage and subsequent suspension of a booster dose during December 2007 to June 2009.13,14 For measles-mumps-rubella, varicella, and pneumococcal polysaccharideprotein conjugate vaccine, we required ‡1 dose on or after the first birthday to consider vaccination UTD. We designed the definition of our outcome to be consistent with the way CIRTS is queried for UTD status during routine use. Thus, we did not consider the timing of other vaccines, only the number of doses given by age 24 months. We obtained individual data for the 2006 Connecticut birth cohort from CIRTS. We geocoded records to census tracts with ArcGIS version 9.3 (Environmental Systems Research Institute Inc, Redlands, CA) according to address at birth. We excluded children with invalid addresses (e.g., address missing, PO box given, address could not be located on another map service) from further analysis. We determined census tract data for each child by matching the census tract of residence to 2000 census data. To identify individual and census tract predictors of underimmunization at age 24 months,
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we performed bivariate analysis and multilevel logistic regression modeling in SAS version 9.2 (SAS Institute, Cary, NC). We included individual characteristics of race/ethnicity, Medicaid enrollment, UTD status at age 7 months, mother’s age at the time of the child’s birth, and mother’s educational level as predictor variables because we hypothesized these factors to influence UTD status at age 24 months. We also included child’s sex in the analysis as a possible confounder. We defined race/ethnicity in mutually exclusive categories as Hispanic, nonHispanic Black, non-Hispanic White, American Indian, or Asian/Pacific Islander. We defined Medicaid enrollment as continuous enrollment in Medicaid for 12 months or more with no more than 1 break of 45 days, according to the Health Plan Employer Data and Information Set standard.15 We defined UTD at age 7 months as 3 or more doses of diphtheria and tetanus toxoids and acellular pertussis vaccine, 2 or more doses of poliovirus vaccine, 2 or more doses of Haemophilus b vaccine, 2 or more doses of hepatitis B vaccine, and 3 or more doses of pneumococcal polysaccharide-protein conjugate vaccine. Census tract characteristics (defined in the 2000 Census) were the percentage of persons with household income below the federal poverty level and percentage of persons speaking a non-English language at home. We based cutpoints for percentage of persons with household income below the federal poverty level in a census tract on recommendations from the Harvard School of Public Health’s Public Health Disparities Geocoding Project and previous publications.10,11,16 We included non-English language spoken at home as a measure of culture, as used in a previous study.3 We also included residence in an IAP area as a predictor variable, defined as having an address at the time of birth located in a 2006 IAP area. Preliminary models indicated that UTD status at age 7 months was an effect modifier for certain variables. This seemed plausible because (1) the IAP intervention occurring at age 7 months might contribute to the dissimilarity between children who were and were not UTD at age 7 months and their respective predictors of underimmunization at age 24 months, and (2) the practical experience of 2 of the authors with subject matter expertise regarding vaccinations (K. S. K. and J. L. H.) were consistent
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with the possibility that children who were UTD versus not UTD during infancy might have substantially different characteristics. Therefore, to allow differential influence of predictors on the outcome, we fit separate models for children who were and were not UTD at age 7 months. We used multilevel logistic regression models with 3 levels to account for the correlation of observations within census tracts and the correlation of census tracts within counties.
RESULTS A total of 34 989 children were in the 2006 Connecticut birth cohort. We geocoded 34 580 children (99%) with ArcGIS. We subsequently excluded 12 children because their addresses corresponded to census tract borders and could not easily be assigned to a census tract, leaving 34 568 children (99%) in the cohort for analysis. Coverage for individual vaccines was 87% to 96%; overall coverage for the 4:3:1:2:3:1:4 series was 81% (Table 1). In bivariate analysis, we detected statistically significant disparities in 4:3:1:2:3:1:4 series vaccination rates at age 24 months for all SES measures: race/ethnicity, Medicaid status, maternal age, maternal education level, percentage with household income below the federal poverty level in the census tract of residence, and percentage in a census tract speaking a non-English language at home (Table 2).
However, the disparities were limited; the majority of differences in vaccination rates between the highest- and lowest-SES groups were under 5%. The strongest predictor of not being UTD at age 24 months was not being UTD at age 7 months, with a vaccination rate 31 percentage points lower than for children who were UTD at age 7 months (58% vs 89%; P < .001). In bivariate analysis stratifying on UTD status at age 7 months, we found significant associations for some variables with underimmunization at age 24 months (Tables 3 and 4). Among children who were not UTD at age 7 months (Table 3), nearly all individual and both census tract characteristics were associated with underimmunization. However, after adjustment for other covariates in multilevel logistic regression, only Medicaid enrollment and residence in an IAP area were independently associated with underimmunization at age 24 months, (adjusted odds ratio [AOR] = 0.6; 95% confidence interval [CI] = 0.5, 0.7, and AOR = 0.7; 95% CI = 0.6, 0.9, respectively). Among children UTD at age 7 months (Table 4), the individual characteristics that increased the odds of underimmunization at age 24 months were non-Hispanic Black and American Indian race/ethnicity, Medicaid enrollment, and younger maternal age at child’s birth. After multilevel logistic regression, we found only 2 variables to be independently
TABLE 1—Vaccination Status at Age 24 Months for 7 Individual Vaccines and the Combined 4:3:1:2:3:1:4 Series: Connecticut 2006 Birth Cohort Vaccine (No. Doses)
Children With Vaccines Up-to-Date, No. (%)
DTaP (4) Polio (3)
30 086 (87) 32 371 (94)
MMR (1)a
31 354 (91)
Hib (2)
33 099 (96)
Hepatitis B (3)
32 729 (95)
Varicella (1)a
30 947 (90)
PCV (2–4)a,b
30 967 (90)
Entire series (4:3:1:2:3:1:4)
28 102 (81)
Note. DTaP = diphtheria and tetanus toxoids and acellular pertussis; Hib = Haemophilus b; MMR = measles-mumps-rubella; PCV = pneumococcal polysaccharide-protein conjugate vaccine. The sample size was n = 34 568. a Age-appropriate timing of vaccine doses was included, for which ‡ 1 dose on or after the first birthday was required. b Number required based on age at administration; fewer doses are required in children who begin the series late, in accordance with the Advisory Committee on Immunization Practices catch-up schedule. For example, a child who received all PCV doses on time would need 4 doses to be considered up-to-date. However, a child who started the series at 12 months would only need 2 doses, with 1 dose administered after the first birthday.
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associated with underimmunization at age 24 months: Hispanic race/ethnicity, which decreased the odds of underimmunization (AOR = 0.8; 95% CI = 0.7, 0.9), and younger maternal age at child’s birth, which increased the odds of underimmunization; the youngest age group (< 20 years) was the most predictive of underimmunization (AOR = 1.3; 95% CI = 1.1, 1.6). Medicaid enrollment and residence in an IAP area were not protective against underimmunization in this group.
DISCUSSION We examined predictors of early childhood underimmunization in a cohort of Connecticut children for whom longstanding efforts had been made to improve vaccination levels and reduce SES disparities. Results demonstrated that disparities by certain SES measures in vaccination rates at age 24 months still existed but were limited. The strongest predictor of underimmunization was not a direct SES measure, but rather having fallen behind during the first 7 months after birth. Among infants behind in receiving vaccinations at age 7 months, children receiving Medicaid and children who resided in areas with full-time vaccination coordinators were more likely than their counterparts to subsequently achieve UTD status. Collectively, these findings suggest that when intensive vaccination efforts are focused on infants born in low-SES circumstances, including placing dedicated vaccination coordinators in at-risk areas and making use of information from a centralized Immunization Information System, disparities can be minimized. The finding that disparities in vaccination rates by race/ethnicity and SES are now minimal is encouraging. Combined with the overall high vaccination rates of children aged 2 years found in the National Immunization Survey, this suggests that the overall vaccination effort in Connecticut has been successful at reaching all population segments. Connecticut is not alone in this success; nationally, overall vaccination rates have increased and gaps by race/ethnicity have narrowed.17 These national trends are likely a consequence of interventions related to the national strategy (i.e., CII) to increase early childhood
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TABLE 2—Vaccination Status at Age 24 Months by Individual and Census Tract Characteristics: Connecticut 2006 Birth Cohort UTD by Age 24 Mo, No. (%)
Not UTD by Age 24 Mo, No. (%)
Study Population,a No. (%)
UTD, %
Female
13 773 (49)
3088 (48)
16 861 (49)
82
Male (Ref)
14 329 (51)
3377 (52)
17 706 (51)
81
Variable Sex
Pb .07
Race/ethnicity Non-Hispanic Black
3268 (12)
922 (16)
4190 (13)
78
< .001
Hispanic American Indian
6041 (22) 101 (0.4)
1302 (23) 34 (0.6)
7343 (22) 135 (0.4)
82 75
< .01 < .01 < .001
Asian or Pacific Islander
1277 (5)
312 (5)
1589 (5)
80
Non-Hispanic White (Ref)
16 460 (61)
3214 (56)
19 674 (60)
84
Yes
12 524 (45)
3296 (51)
15 820 (46)
79
No (Ref)
15 578 (55)
3170 (49)
18 748 (54)
83
1964 (7) 4870 (18)
505 (9) 1203 (21)
2469 (7) 6073 (18)
80 80
6717 (25)
1486 (25)
8203 (25)
82
13 846 (51)
2654 (45)
16 500 (50)
84
Medicaid recipient
< .001
Mother’s age at child’s birth, y
< .001
< 20 20–24 25–29 ‡ 30 (Ref) Mother’s educational level < high school
3913 (14)
929 (16)
4842 (15)
81
< .001
High school
6966 (26)
1559 (27)
8525 (26)
82
< .01
16 348 (60)
3320 (57)
19 668 (60)
83
23 293 (83)
2946 (46)
26 239 (76)
89
4809 (17)
3520 (54)
8329 (24)
58
> high school (Ref) UTD by age 7 moc Yes (Ref)
< .001
No Household income below federal poverty level in census tract, % 0–< 5 (Ref)
12 663 (45)
2635 (41)
15 298 (44)
83
5–< 10
5698 (20)
1258 (19)
6956 (20)
82
0.12
10–< 20
5076 (18)
1235 (19)
6311 (18)
80
< .001
20–100
4665 (17)
1338 (21)
6003 (17)
78
< .001
Non-English language spoken at home in census tract,d quartile 1 (lowest; Ref)
5458 (19)
1185 (18)
6643 (19)
82
2
6184 (22)
1353 (21)
7537 (22)
82
3
7250 (26)
1517 (23)
8767 (25)
83
0.39
4
9210 (33)
2411 (37)
11 621 (34)
79
< .001
20 479 (73)
4700 (73)
25 179 (73)
81
7623 (27)
1766 (27)
9389 (27)
81
Residence in IAP area
0.86
0.76
Yes No (Ref)
Note. DTaP = diphtheria and tetanus toxoids and acellular pertussis; Hib = Haemophilus b; IAP = Immunization Action Plan; MMR = measles-mumps-rubella; PCV = pneumococcal polysaccharideprotein conjugate vaccine; UTD = up-to-date. UTD defined as receipt of 4:3:1:2:3:1:4 vaccine series by age 24 mo (‡ 4 doses DTaP, ‡ 3 doses poliovirus vaccine, ‡ 1 dose MMR vaccine, ‡ 2 doses Hib conjugate vaccine, ‡ 3 doses hepatitis B vaccine, ‡ 1 dose varicella, and ‡ 2–4 age-appropriate doses of PCV). To be considered UTD for MMR, varicella, and PCV, ‡ 1 dose on or after the first birthday was required. The sample size was n = 34 568. a Missing variables in entire study population ranged from 0% to 4.7%. b P value generated by comparison of percentage UTD for the specified variable compared with the percentage UTD for the reference group. c UTD by age 7 mo was defined as ‡ 3 doses of DTaP, ‡ 2 doses of poliovirus vaccine, ‡ 2 doses of Hib, ‡ 2 doses of hepatitis B vaccine, and ‡ 3 doses of PCV. d Among population aged ‡ 5 y.
vaccination rates, including establishment of jurisdiction-wide Immunization Information Systems, which are used for improving
vaccination levels; removing out-of pocket costs for vaccine and for vaccination as barriers to immunization; improving the quality of vaccine
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delivery systems by conducting practice-based assessments; and setting standards for pediatric vaccination practice that call attention to
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TABLE 3—Predictors of Underimmunization at Age 24 Months Among Children Not Up-to-Date by Age 7 Months: Connecticut 2006 Birth Cohort Variablea
Not UTD by Age 24 Mo, %
OR (95% CI)
AOR (95% CI)b
Sex Female
41
0.9 (0.8, 1.0)
0.9 (0.8, 1.0)
Male (Ref)
43
1.0
1.0
39 33
0.8 (0.7, 0.9) 0.6 (0.6, 0.7)
1.1 (1.0, 1.3) 1.0 (0.8, 1.1)
Race/ethnicity Non-Hispanic Black Hispanic American Indian
45
1.0 (0.5, 2.0)
1.0 (0.5, 2.0)
Asian or Pacific Islander
46
1.1 (0.9, 1.4)
1.0 (0.8, 1.3)
Non-Hispanic White (Ref)
44
1.0
1.0
Yes
38
0.6 (0.6, 0.7)
0.6 (0.5, 0.7)
No (Ref)
49
1.0
1.0
40
0.6 (0.6, 0.7)
0.7 (0.6, 0.9)
51
1.0
1.0
Medicaid recipient
Residence in IAP area Yes No (Ref) Mother’s age at child’s birth, y < 20
34
0.7 (0.6, 0.8)
1.1 (0.9, 1.4)
20–24
37
0.8 (0.7, 0.9)
1.2 (1.0, 1.4)
25–29
40
0.9 (0.8, 1.0)
1.1 (1.0, 1.3)
‡ 30 (Ref)
43
1.0
1.0
Mother’s educational level < high school
32
0.6 (0.5, 0.6)
0.8 (0.7, 1.0)
High school
38
0.7 (0.7, 0.8)
0.9 (0.8, 1.1)
> high school (Ref)
45
1.0
1.0
0–< 5 (Ref)
48
1.0
1.0
5–< 10
41
0.8 (0.7, 0.9)
0.9 (0.8, 1.1)
10–< 20 20–100
41 37
0.7 (0.7, 0.8) 0.6 (0.6, 0.7)
1.0 (0.8, 1.3) 1.1 (0.8, 1.4)
1 (lowest; Ref)
48
1.0
1.0
2
46
0.9 (0.8, 1.1)
1.1 (0.9, 1.3)
3
44
0.8 (0.7, 1.0)
1.1 (0.8, 1.3)
4
38
0.6 (0.6, 0.7)
0.9 (0.7, 1.2)
Household income below federal poverty level in census tract, %
Non-English language spoken at home in census tract,c quartile
Note. AOR = adjusted odds ratio; CI = confidence interval; DTaP = diphtheria and tetanus toxoids and acellular pertussis; Hib = Haemophilus b; IAP = Immunization Action Plan; MMR = measles-mumps-rubella; OR = odds ratio; PCV = pneumococcal polysaccharide-protein conjugate vaccine; UTD = up-to-date. UTD defined as receipt of 4:3:1:2:3:1:4 vaccine series by age 24 mo (‡ 4 doses DTaP, ‡ 3 doses poliovirus vaccine, ‡ 1 dose MMR vaccine, ‡ 2 doses Hib conjugate vaccine, ‡ 3 doses hepatitis B vaccine, ‡ 1 dose varicella, and ‡ 2–4 age-appropriate doses of PCV). To be considered UTD for MMR, varicella, and PCV, ‡ 1 dose on or after the first birthday was required. The sample size was n = 8329; n = 7320 for multilevel analysis. a Missing variables ranged from 0% to 10.7%. b County of residence at birth was included in the model as a random effect. c Among population aged ‡ 5 y.
numerous ways clinicians can efficiently and effectively ensure that all infants in their care receive timely vaccinations.5,18 The specific
interventions that contribute the majority of influence to the national narrowing of SES-related disparities are unknown.
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In our data, residence in an area served by a vaccination coordinator appeared to be significantly protective against underimmunization at age 24 months among children who were behind on immunizations at age 7 months. In Connecticut, IAP coordinators use certain interventions that are part of the national vaccination strategy. They use CIRTS to identify children who are behind at age 7 months to get them back on schedule, and they conduct outreach that can include home visits. This targeted follow-up of children who are behind at age 7 months might help explain the finding that residing in a town with a dedicated vaccination coordinator was a strong predictor of becoming UTD by age 24 months among children who were behind at age 7 months. Although the particular IAP interventions that most effectively increase vaccination coverage are undetermined, our analysis demonstrates that the collective efforts of dedicated vaccination coordinators implementing elements of the national vaccination strategy among populations at risk can make a difference. The finding that Medicaid enrollment was a strong predictor of getting children who were behind at age 7 months back on track by age 24 months was surprising. This observation contrasts with other studies that found that Medicaid, or more generally public insurance, lacked an association with UTD status during early childhood or was associated with underimmunization.19---22 The explanation for our differing observation is unknown. However, previous studies did not stratify on UTD status at an earlier point, and we found that Medicaid was protective only among children who were not UTD at age 7 months. Medicaid enrollment in Connecticut, particularly among children who have already fallen behind, might signal to public health and clinical staff an increased risk for continued underimmunization. Consequently, increased intensity of interventions might be directed toward this vulnerable population during infancy, thus protecting them against underimmunization at age 24 months. Two aspects of the national CII might selectively help infants enrolled in Medicaid catch up after missing vaccinations. First, infants
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TABLE 4—Predictors of Underimmunization at Age 24 Months Among Children Up-to-Date by Age 7 Months: Connecticut 2006 Birth Cohort Variablea
Not UTD by Age 24 Mo, %
OR (95% CI)
AOR (95% CI)b
Sex Female
11
1.0 (0.9, 1.1)
1.0 (0.9, 1.1)
Male (Ref)
11
1.0
1.0
13 11
1.3 (1.1, 1.4) 1.0 (0.9, 1.1)
1.1 (0.9, 1.3) 0.8 (0.7, 0.9)
Race/ethnicity Non-Hispanic Black Hispanic American Indian
18
1.8 (1.1, 3.0)
1.7 (1.0, 3.0)
Asian or Pacific Islander
12
1.2 (1.0, 1.4)
1.2 (1.0, 1.4)
Non-Hispanic White (Ref)
11
1.0
1.0
Yes
12
1.2 (1.1, 1.3)
1.1 (1.0, 1.3)
No (Ref)
10
1.0
1.0
11
1.1 (1.0, 1.1)
1.0 (0.8, 1.1)
11
1.0
1.0
Medicaid recipient
Residence in IAP area Yes No (Ref) Mother’s age at child’s birth, y < 20
13
1.3 (1.1, 1.6)
1.3 (1.1, 1.6)
20–24
12
1.3 (1.1, 1.4)
1.2 (1.1, 1.4)
25–29
12
1.2 (1.1, 1.3)
1.2 (1.1, 1.3)
‡ 30 (Ref)
10
1.0
1.0
Mother’s educational level < high school
12
1.1 (1.0, 1.3)
1.0 (0.8, 1.2)
High school
11
1.1 (1.0, 1.2)
0.9 (0.8, 1.1)
> high school (Ref)
11
1.0
1.0
0–< 5 (Ref)
11
1.0
1.0
5–< 10
11
1.0 (0.9, 1.2)
1.0 (0.9, 1.1)
10–< 20 20–100
11 13
1.1 (1.0, 1.2) 1.3 (1.1, 1.4)
1.0 (0.9, 1.2) 1.1 (0.9, 1.4)
1 (lowest; Ref)
11
1.0
1.0
2
11
1.0 (0.9, 1.1)
1.0 (0.8, 1.1)
3
10
0.8 (0.7, 0.9)
0.8 (0.7, 1.0)
4
13
1.1 (1.0, 1.3)
1.0 (0.8, 1.3)
Household income below federal poverty level in census tract, %
Non-English language spoken at home in census tract,c quartile
Note. AOR = adjusted odds ratio; CI = confidence interval; DTaP = diphtheria and tetanus toxoids and acellular pertussis; Hib = Haemophilus b; IAP = Immunization Action Plan; MMR = measles-mumps-rubella; OR = odds ratio; PCV = pneumococcal polysaccharide-protein conjugate vaccine; UTD = up-to-date. UTD defined as receipt of 4:3:1:2:3:1:4 vaccine series by age 24 mo (‡ 4 doses DTaP, ‡ 3 doses poliovirus vaccine, ‡ 1 dose MMR vaccine, ‡ 2 doses Hib conjugate vaccine, ‡ 3 doses hepatitis B vaccine, ‡ 1 dose varicella, and ‡ 2–4 age-appropriate doses of PCV). To be considered UTD for MMR, varicella, and PCV, ‡ 1 dose on or after the first birthday was required. Sample size was n = 26 239; n = 25 253 for multilevel analysis. a Missing variables ranged from 0% to 2.9%. b County of residence at birth was included in the model as a random effect. c Among population aged ‡ 5 y.
enrolled in Medicaid are likely to receive other services (e.g., the Special Supplemental Nutrition Program for Women, Infants, and
Children). One CII-recommended strategy is to take advantage of visits with other services to check vaccination status and take action. Second,
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the CII recommendation to conduct pediatric practice---specific assessments of vaccination levels followed by discussion of ways to improve them is likely implemented more routinely in clinics serving a high percentage of children who receive Medicaid (e.g., community health centers) than among private pediatric practices primarily serving children with private health insurance.5 Future efforts to examine risk factors for underimmunization during early childhood should include examination of the potential role of Medicaid in helping children catch up. The finding that the strongest predictor of underimmunization at age 24 months was underimmunization at an earlier age is neither new nor surprising.23---26 Connecticut has implemented strategies to address the problem of inadequate care in early childhood, through both IAP and non-IAP mechanisms. Strategies that are not vaccination specific include ensuring that infants are placed in a medical home, medical homes take full responsibility for each assigned child, practice-based reminder---recall and outreach systems for missed appointments are in place, well-child care is free, and documentation of well-child care is necessary to receive Special Supplemental Nutrition Program for Women, Infants, and Children benefits. CIRTS is used by vaccination coordinators to identify infants who are behind at age 7 months. This use of CIRTS appeared to be effective: 58% of those who were behind at 7 months subsequently caught up, and SES disparities observed in an analysis with UTD status at 7 months as the outcome largely disappeared by 24 months (data not shown). Thus, it appears that a key strategy for further improving early childhood vaccination levels and decreasing disparities is enhancement of an old strategy: identifying children who are missing well-child appointments or ageappropriate vaccinations as early as possible after neonatal discharge and getting them back into care. Achieving this goal will require a more complete understanding of why certain infants do not receive routine care or vaccinations early on and will require targeting intervention efforts to the identified problems.
Limitations CIRTS data did not include the 11% of Connecticut children whose parents opted out
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during 2006. Vaccination rates and other characteristics of these children are unknown. However, approximately 89% of the state’s 2006 birth cohort was part of our study population, so our results are likely generalizable to all Connecticut children in a comparable age range. We assumed that all children, whether in IAP areas or on Medicaid or not, had an equal probability of having administered vaccinations recorded in CIRTS. To the extent that this was not true, the magnitude of our findings could be greater or smaller. We have no data to suggest a reporting bias in either direction. Our analysis did not account for children who moved and changed area-based SES or IAP status during the study period; we used only the residential address at time of birth to assign a census tract and an IAP area. Consequently, the census tract and IAP area characteristics assigned to a child might have been inaccurate, depending on where the child moved. This probably resulted in nonsystematic misclassification, diminishing the strength of any measured associations. Also, Medicaid status can change; we determined this as of the final time the child’s CIRTS record was updated, typically at age 19 to 24 months. However, because we used the Health Plan Employer Data and Information Set standard to define the Medicaid variable and not simply Medicaid enrollment, the influence of such inaccuracies was minimal. Furthermore, the effect of such misclassification might be to diminish the strength of association reported. The methods used to examine preintervention disparities were not directly comparable with our methods. In the preintervention analyses, all children residing in the 3 largest urban areas represented low-SES populations, regardless of their immediate census tract SES, but we used more refined measures that were more specific for low SES. In addition, the fact that the IAP measure revealed minimal disparities was relevant, because all 3 urban areas were IAP areas.
Conclusions We demonstrated that disparities by certain SES measures in vaccination levels at age 24 months still exist but are limited. The
strongest predictor of underimmunization at age 24 months was having fallen behind during the 7 months after birth. Among this latter group, 58% were able to subsequently catch up; receiving Medicaid and residing in areas with full-time vaccination coordinators increased the probability of catching up. These findings demonstrate that when special attention is focused on ensuring that infants born in low-SES circumstances receive vaccinations, specifically by identifying and intervening on behalf of children who fall behind early, as identified in a centralized Immunization Information System, disparities can be minimized. j
About the Authors At the time of the study, Jessica A. Kattan was an Epidemic Intelligence Service Officer with the Centers for Disease Control and Prevention (CDC), assigned to the Infectious Diseases Section, Connecticut Department of Public Health, Hartford. Kathy S. Kudish is with the Immunization Program and Kristen Soto is with the Infectious Diseases Section, Connecticut Department of Public Health. Betsy L. Cadwell is with the Office of Surveillance, Epidemiology, and Laboratory Services, CDC, Atlanta, GA. James L. Hadler is a consultant for the Connecticut Emerging Infections Program, New Haven. Correspondence should be sent to Jessica A. Kattan, New York City Department of Health and Mental Hygiene, Bureau of Alcohol and Drug Use Prevention, Care and Treatment, Gotham Center, 42-09 28th Street, 19th Floor, CN#14, Queens, New York 11101-4132 (e-mail: jkattan@ health.nyc.gov). Reprints can be ordered at http://www.ajph. org by clicking the “Reprints” link. This article was accepted April 25, 2013. Note. The findings and conclusions in this report are those of the authors and do not necessarily represent the official position of the CDC.
Contributors J. A. Kattan helped design the study, performed the analysis, and led the writing of the article. K. S. Kudish originated and helped design the study and analyze the data. B. L. Cadwell helped design the study and guided the data analysis. K. Soto helped analyze the data. All authors interpreted data and revised the article. J. L. Hadler helped design the study and supervised all stages.
Acknowledgments We thank Gary Archambault, Diane Fraiter, Melinda Mailhot, Stephanie Poulin, and Vincent Sacco, Connecticut Department of Public Health for their assistance.
Human Participant Protection This study underwent human subjects review at the CDC and was determined to be public health practice, not research.
References 1. Zhao Z, Luman ET. Progress toward eliminating disparities in vaccination coverage among US
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children, 2000---2008. Am J Prev Med. 2010;38(2): 127---137. 2. Smith PJ, Singleton JA. Vaccination coverage estimates for selected counties: achievement of Healthy People 2010 goals and association with indices of access to care, economic conditions, and demographic composition. Public Health Rep. 2008;123(2):155---172. 3. Whitehead SJ, Cui KX, De AK, Ayers T, Effler PV. Identifying risk factors for underimmunization by using geocoding matched to census tracts: a statewide assessment of children in Hawaii. Pediatrics. 2007;120(3): e535---e542. 4. 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(2):312---323. 5. Robinson CA, Sepe SJ, Lin KF. The president’s child immunization initiative—a summary of the problem and the response. Public Health Rep. 1993;108(4): 419---425. 6. Wood DL, Brunell PA. Measles control in the United States: problems of the past and challenges for the future. Clin Microbiol Rev. 1995;8(2):260---267. 7. Immunization Program. Infant Immunization Action Plan and Project Grant Application, October 1, 1992--September 30, 1993. Hartford, CT: Connecticut Department of Public Health; 1992. 8. Connecticut General Statutes Section 19a-7h. Childhood immunization registry. Regulations. Available at: http://www.cga.ct.gov/2011/pub/chap368a. htm#Sec19a-7h.htm. Accessed July 9, 2012. 9. Centers for Disease Control and Prevention. US vaccination coverage reported via National Immunization Survey. Available at: http://www.cdc.gov/ vaccines/stats-surv/nis/default.htm#nis. Accessed July 9, 2012. 10. 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---88. 11. 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(9):1785--1789. 12. Klevens RM, Luman ET. US children living in and near poverty: risk of vaccine-preventable diseases. Am J Prev Med. 2001;20(4, suppl):41---46. 13. Centers for Disease Control and Prevention. Interim recommendations for the use of Haemophilus influenzae Type b (Hib) conjugate vaccines related to the recall of certain lots of Hib-containing vaccines (PedvaxHIBÒ and ComvaxÒ). MMWR Morb Mortal Wkly Rep. 2007;56 (50):1318---1320. 14. Centers for Disease Control and Prevention. Updated recommendations for use of Haemophilus influenzae Type b (Hib) vaccine: reinstatement of the booster dose at ages 12---15 months. MMWR Morb Mortal Wkly Rep. 2009;58(24):673---674. 15. US Department of Health and Human Services. Agency for Healthcare Research and Quality. Established child health care quality measures---HEDIS(R): Child
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Health Care Quality Toolbox. Available at: http://www. ahrq.gov/professionals/quality-patient-safety/qualityresources/tools/chtoolbx/measures/measure4. html#hedisenrollment. Accessed August 7, 2013. 16. Public Health Disparities Geocoding Project. Available at: http://www.hsph.harvard.edu/thegeocodingproject. Accessed July 9, 2012. 17. Centers for Disease Control and Prevention. National, state, and local area vaccination coverage among children aged 19---35 months—United States, 2011. MMWR Morb Mortal Wkly Rep. 2012;61:689---696. 18. Bernier RH, Dietz VJ, Lyons AE, et al. Standards for pediatric immunization practices. JAMA. 1993;269 (14):1817---1822. 19. Santoli JM, Huet NJ, Smith PJ, et al. Insurance status and vaccination coverage among US preschool children. Pediatrics. 2004;113(6, suppl):1959---1964. 20. Fiks AG, Alessandrini EA, Luberti AA, Ostapenko S, Zhang X, Silber JH. Identifying factors predicting immunization delay for children followed in an urban primary care network using an electronic health record. Pediatrics. 2006;118(6):e1680---e1686. 21. Dombkowski KJ, Lantz PM, Freed GL. Risk factors for delay in age-appropriate vaccination. Public Health Rep. 2004;119(2):144---155. 22. Wood D, Donald-Sherbourne C, Halfon N, et al. Factors related to immunization status among inner-city Latino and African-American preschoolers. Pediatrics. 1995;96(2 pt 1):295---301. 23. Centers for Disease Control and Prevention. Early childhood vaccination levels among urban children— Connecticut, 1990 and 1991. MMWR Morb Mortal Wkly Rep. 1992;40(51---52):888---891. 24. Centers for Disease Control and Prevention. Early childhood vaccination in two rural counties—Nebraska, 1991---1992. MMWR Morb Mortal Wkly Rep. 1992;41 (37):688---691. 25. Centers for Disease Control and Prevention. Retrospective assessment of vaccination coverage among school-aged children—selected US cities, 1991. MMWR Morb Mortal Wkly Rep. 1992;41(6):103---107. 26. Guyer B, Hughart N, Hold E, et al. Immunization coverage and its relationship to preventive health care visits among inner-city children in Baltimore. Pediatrics. 1994;94(1):53---58.
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Effect of Vaccination Coordinators on Socioeconomic Disparities in Immunization Among the 2006 Connecticut Birth Cohort Jessica A. Kattan, MD, MPH, Kathy S. Kudish, DVM, MSPH, Betsy L. Cadwell, MSPH, Kristen Soto, MPH, and James L. Hadler, MD, MPH
Recognizing disparities among population segments can be helpful in identifying barriers and delivering successful public health interventions. Disparities in early childhood vaccinations in the United States among socioeconomic and demographic groups have been described in previous analyses, with certain studies reporting successes in narrowing disparities.1,2 A few studies have examined disparities and risk factors for underimmunization by assessing the influence of census tract characteristics on individual children’s vaccination status.3 This approach is potentially useful because census tract poverty level has been demonstrated to be the most consistently discriminating area measure for monitoring socioeconomic inequalities in health.4 Analytic approaches, including census tract attributes and individual risk factors for underimmunization, allow for a comprehensive examination of health disparities in early childhood vaccinations. In 1993, the Centers for Disease Control and Prevention helped lead a national effort to improve early childhood vaccination rates, the Child Immunization Initiative (CII).5 This effort followed the national measles epidemic in 1989 to 1991, which was particularly severe among infants and preschool-aged children in poorer urban areas.6 Each state and large city receiving Centers for Disease Control and Prevention vaccinations cooperative agreement funding, including Connecticut, was required to develop an Immunization Action Plan (IAP) to improve early childhood vaccination levels. Implemented in 1993, the Connecticut IAP called for funding to support an early childhood vaccination coordinator position for the cities and health districts (i.e., groupings of towns served by a single local health department) with the largest populations of Medicaid and Special Supplemental Nutrition Program for Women, Infants, and Children
Objectives. We examined socioeconomic status (SES) disparities and the influence of state Immunization Action Plan–funded vaccination coordinators located in low-SES areas of Connecticut on childhood vaccination up-to-date (UTD) status at age 24 months. Methods. We examined predictors of underimmunization among the 2006 birth cohort (n = 34 568) in the state’s Immunization Information System, including individual demographic and SES data, census tract SES data, and residence in an area with a vaccination coordinator. We conducted multilevel logistic regression analyses. Results. Overall, 81% of children were UTD. Differences by race/ethnicity and census tract SES were typically under 5%. Not being UTD at age 7 months was the strongest predictor of underimmunization at age 24 months. Among children who were not UTD at age 7 months, only Medicaid enrollment (adjusted odds ratio [AOR] = 0.6; 95% confidence interval [CI] = 0.5, 0.7) and residence in an area with a vaccination coordinator (AOR = 0.7; 95% CI = 0.6, 0.9) significantly decreased the odds of subsequent underimmunization. Conclusions. SES disparities associated with underimmunization at age 24 months were limited. Efforts focused on vaccinating infants born in low SES circumstances can minimize disparities. (Am J Public Health. 2014;104:e74–e81. doi:10.2105/AJPH.2013.301418)
recipients, both markers of low socioeconomic status (SES). To the extent that funding permitted, the state also established outreach worker positions. The rationale for this design derived, in part, from the finding that children in poor urban areas of Connecticut had a much higher risk of measles during the 1989 to 1991 epidemic and from the results of several surveys of school children that retrospectively examined the vaccination status of first-grade students when they were aged 3 and 24 months. These surveys demonstrated substantial disparities in early childhood vaccination levels between children living in urban and nonurban areas and found a much higher probability of underimmunization among children attending public-sector clinics (e.g., community health centers).7 Use of public-sector clinics and living in urban areas in Connecticut are both markers of low SES. The role of the vaccination coordinator is to ensure that all infants born to city or health
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district residents are assigned to a patientcentered medical home (i.e., a comprehensive primary care provider), all providers have reminder---recall systems, all infants appearing to be out of care because of missed vaccinations are identified and returned to care, and provider-specific evaluation and feedback is provided. The size of the IAP program has fluctuated over time, reaching its peak in 2006. During 2006, 66% of the population in Connecticut was included in IAP areas staffed by 16 full-time vaccination coordinators and 10 outreach staff. The possible benefit of having dedicated vaccination coordinators in towns with large populations of Medicaid and Special Supplemental Nutrition Program for Women, Infants, and Children recipients in Connecticut has never been assessed formally. The Connecticut Immunization Registry and Tracking System (CIRTS) is the state’s Immunization Information System. Development of CIRTS began in 1994, and the system has been
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operational statewide for all children born in Connecticut since 1998. All providers are required to report to CIRTS all vaccinations administered to children aged 6 years and younger residing in Connecticut.8 In addition to vaccination information, the CIRTS database contains demographic information (e.g., address, sex, and race/ethnicity) and maternal information (e.g., age at delivery and educational level) regarding each child. CIRTS also contains Medicaid status, generated from periodic matches with the state Medicaid database. CIRTS has been used by IAP-funded cities and health districts to identify children not up-todate (UTD) with vaccinations at age 7 and 19 months and to recommend follow-up attention.
VACCINATION COVERAGE IN CONNECTICUT Connecticut has achieved relatively high statewide vaccination rates. During the 15 years prior to and including the 2006 birth cohort year (i.e., children born during 1992--2006), Connecticut ranked among the top 10 states for the standard vaccination series for children aged 19 to 35 months a total of 13 times and in the top 5 a total of 10 times, according to the National Immunization Survey.9 However, this survey has limited ability to assess vaccination coverage in smaller geographic areas. Efforts to examine risk factors for underimmunization on the individual and census tract level and to close any existing gaps are essential to further improve vaccination rates in Connecticut. Connecticut has provided nearly all vaccines free of charge to providers for vaccination of any child regardless of health insurance status in the state since the 1970s; the state funds vaccines for children who are not eligible for Medicaid or Vaccines for Children. Thus, eligibility for free vaccines should not be a contributor to disparities in vaccination status, as it might be in many states. Our study objectives were to (1) determine whether living in a city or health district with an IAP-funded vaccination coordinator, rather than living in an area without a coordinator, was associated with having higher early childhood age-appropriate vaccination rates approximately 15 years after initial implementation of the IAP, and (2) assess the effects of
individual and census tract characteristics on children’s UTD status regarding early childhood, age-appropriate vaccination series. We hypothesized an association between census tract poverty and UTD status, in line with previous studies that demonstrated census tract poverty to be associated with poor health outcomes and individual poverty to be associated with underimmunization in children.4,10---12
METHODS Our main outcome of interest was underimmunization (i.e., not being UTD) at age 24 months with the 4:3:1:2:3:1:4 vaccine series (‡ 4 doses of diphtheria and tetanus toxoids and acellular pertussis vaccine; ‡ 3 doses of poliovirus vaccine, ‡ 1 dose of measles-mumpsrubella vaccine, ‡ 2 doses of Haemophilus b conjugate vaccine, ‡ 3 doses of hepatitis B vaccine, ‡ 1 dose of varicella vaccine, and ‡ 2---4 age-appropriate doses of pneumococcal polysaccharide-protein conjugate vaccine) among children in the 2006 Connecticut birth cohort. We used 2 doses of Haemophilus b vaccine in the analysis because of the national shortage and subsequent suspension of a booster dose during December 2007 to June 2009.13,14 For measles-mumps-rubella, varicella, and pneumococcal polysaccharideprotein conjugate vaccine, we required ‡1 dose on or after the first birthday to consider vaccination UTD. We designed the definition of our outcome to be consistent with the way CIRTS is queried for UTD status during routine use. Thus, we did not consider the timing of other vaccines, only the number of doses given by age 24 months. We obtained individual data for the 2006 Connecticut birth cohort from CIRTS. We geocoded records to census tracts with ArcGIS version 9.3 (Environmental Systems Research Institute Inc, Redlands, CA) according to address at birth. We excluded children with invalid addresses (e.g., address missing, PO box given, address could not be located on another map service) from further analysis. We determined census tract data for each child by matching the census tract of residence to 2000 census data. To identify individual and census tract predictors of underimmunization at age 24 months,
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we performed bivariate analysis and multilevel logistic regression modeling in SAS version 9.2 (SAS Institute, Cary, NC). We included individual characteristics of race/ethnicity, Medicaid enrollment, UTD status at age 7 months, mother’s age at the time of the child’s birth, and mother’s educational level as predictor variables because we hypothesized these factors to influence UTD status at age 24 months. We also included child’s sex in the analysis as a possible confounder. We defined race/ethnicity in mutually exclusive categories as Hispanic, nonHispanic Black, non-Hispanic White, American Indian, or Asian/Pacific Islander. We defined Medicaid enrollment as continuous enrollment in Medicaid for 12 months or more with no more than 1 break of 45 days, according to the Health Plan Employer Data and Information Set standard.15 We defined UTD at age 7 months as 3 or more doses of diphtheria and tetanus toxoids and acellular pertussis vaccine, 2 or more doses of poliovirus vaccine, 2 or more doses of Haemophilus b vaccine, 2 or more doses of hepatitis B vaccine, and 3 or more doses of pneumococcal polysaccharide-protein conjugate vaccine. Census tract characteristics (defined in the 2000 Census) were the percentage of persons with household income below the federal poverty level and percentage of persons speaking a non-English language at home. We based cutpoints for percentage of persons with household income below the federal poverty level in a census tract on recommendations from the Harvard School of Public Health’s Public Health Disparities Geocoding Project and previous publications.10,11,16 We included non-English language spoken at home as a measure of culture, as used in a previous study.3 We also included residence in an IAP area as a predictor variable, defined as having an address at the time of birth located in a 2006 IAP area. Preliminary models indicated that UTD status at age 7 months was an effect modifier for certain variables. This seemed plausible because (1) the IAP intervention occurring at age 7 months might contribute to the dissimilarity between children who were and were not UTD at age 7 months and their respective predictors of underimmunization at age 24 months, and (2) the practical experience of 2 of the authors with subject matter expertise regarding vaccinations (K. S. K. and J. L. H.) were consistent
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with the possibility that children who were UTD versus not UTD during infancy might have substantially different characteristics. Therefore, to allow differential influence of predictors on the outcome, we fit separate models for children who were and were not UTD at age 7 months. We used multilevel logistic regression models with 3 levels to account for the correlation of observations within census tracts and the correlation of census tracts within counties.
RESULTS A total of 34 989 children were in the 2006 Connecticut birth cohort. We geocoded 34 580 children (99%) with ArcGIS. We subsequently excluded 12 children because their addresses corresponded to census tract borders and could not easily be assigned to a census tract, leaving 34 568 children (99%) in the cohort for analysis. Coverage for individual vaccines was 87% to 96%; overall coverage for the 4:3:1:2:3:1:4 series was 81% (Table 1). In bivariate analysis, we detected statistically significant disparities in 4:3:1:2:3:1:4 series vaccination rates at age 24 months for all SES measures: race/ethnicity, Medicaid status, maternal age, maternal education level, percentage with household income below the federal poverty level in the census tract of residence, and percentage in a census tract speaking a non-English language at home (Table 2).
However, the disparities were limited; the majority of differences in vaccination rates between the highest- and lowest-SES groups were under 5%. The strongest predictor of not being UTD at age 24 months was not being UTD at age 7 months, with a vaccination rate 31 percentage points lower than for children who were UTD at age 7 months (58% vs 89%; P < .001). In bivariate analysis stratifying on UTD status at age 7 months, we found significant associations for some variables with underimmunization at age 24 months (Tables 3 and 4). Among children who were not UTD at age 7 months (Table 3), nearly all individual and both census tract characteristics were associated with underimmunization. However, after adjustment for other covariates in multilevel logistic regression, only Medicaid enrollment and residence in an IAP area were independently associated with underimmunization at age 24 months, (adjusted odds ratio [AOR] = 0.6; 95% confidence interval [CI] = 0.5, 0.7, and AOR = 0.7; 95% CI = 0.6, 0.9, respectively). Among children UTD at age 7 months (Table 4), the individual characteristics that increased the odds of underimmunization at age 24 months were non-Hispanic Black and American Indian race/ethnicity, Medicaid enrollment, and younger maternal age at child’s birth. After multilevel logistic regression, we found only 2 variables to be independently
TABLE 1—Vaccination Status at Age 24 Months for 7 Individual Vaccines and the Combined 4:3:1:2:3:1:4 Series: Connecticut 2006 Birth Cohort Vaccine (No. Doses)
Children With Vaccines Up-to-Date, No. (%)
DTaP (4) Polio (3)
30 086 (87) 32 371 (94)
MMR (1)a
31 354 (91)
Hib (2)
33 099 (96)
Hepatitis B (3)
32 729 (95)
Varicella (1)a
30 947 (90)
PCV (2–4)a,b
30 967 (90)
Entire series (4:3:1:2:3:1:4)
28 102 (81)
Note. DTaP = diphtheria and tetanus toxoids and acellular pertussis; Hib = Haemophilus b; MMR = measles-mumps-rubella; PCV = pneumococcal polysaccharide-protein conjugate vaccine. The sample size was n = 34 568. a Age-appropriate timing of vaccine doses was included, for which ‡ 1 dose on or after the first birthday was required. b Number required based on age at administration; fewer doses are required in children who begin the series late, in accordance with the Advisory Committee on Immunization Practices catch-up schedule. For example, a child who received all PCV doses on time would need 4 doses to be considered up-to-date. However, a child who started the series at 12 months would only need 2 doses, with 1 dose administered after the first birthday.
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associated with underimmunization at age 24 months: Hispanic race/ethnicity, which decreased the odds of underimmunization (AOR = 0.8; 95% CI = 0.7, 0.9), and younger maternal age at child’s birth, which increased the odds of underimmunization; the youngest age group (< 20 years) was the most predictive of underimmunization (AOR = 1.3; 95% CI = 1.1, 1.6). Medicaid enrollment and residence in an IAP area were not protective against underimmunization in this group.
DISCUSSION We examined predictors of early childhood underimmunization in a cohort of Connecticut children for whom longstanding efforts had been made to improve vaccination levels and reduce SES disparities. Results demonstrated that disparities by certain SES measures in vaccination rates at age 24 months still existed but were limited. The strongest predictor of underimmunization was not a direct SES measure, but rather having fallen behind during the first 7 months after birth. Among infants behind in receiving vaccinations at age 7 months, children receiving Medicaid and children who resided in areas with full-time vaccination coordinators were more likely than their counterparts to subsequently achieve UTD status. Collectively, these findings suggest that when intensive vaccination efforts are focused on infants born in low-SES circumstances, including placing dedicated vaccination coordinators in at-risk areas and making use of information from a centralized Immunization Information System, disparities can be minimized. The finding that disparities in vaccination rates by race/ethnicity and SES are now minimal is encouraging. Combined with the overall high vaccination rates of children aged 2 years found in the National Immunization Survey, this suggests that the overall vaccination effort in Connecticut has been successful at reaching all population segments. Connecticut is not alone in this success; nationally, overall vaccination rates have increased and gaps by race/ethnicity have narrowed.17 These national trends are likely a consequence of interventions related to the national strategy (i.e., CII) to increase early childhood
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TABLE 2—Vaccination Status at Age 24 Months by Individual and Census Tract Characteristics: Connecticut 2006 Birth Cohort UTD by Age 24 Mo, No. (%)
Not UTD by Age 24 Mo, No. (%)
Study Population,a No. (%)
UTD, %
Female
13 773 (49)
3088 (48)
16 861 (49)
82
Male (Ref)
14 329 (51)
3377 (52)
17 706 (51)
81
Variable Sex
Pb .07
Race/ethnicity Non-Hispanic Black
3268 (12)
922 (16)
4190 (13)
78
< .001
Hispanic American Indian
6041 (22) 101 (0.4)
1302 (23) 34 (0.6)
7343 (22) 135 (0.4)
82 75
< .01 < .01 < .001
Asian or Pacific Islander
1277 (5)
312 (5)
1589 (5)
80
Non-Hispanic White (Ref)
16 460 (61)
3214 (56)
19 674 (60)
84
Yes
12 524 (45)
3296 (51)
15 820 (46)
79
No (Ref)
15 578 (55)
3170 (49)
18 748 (54)
83
1964 (7) 4870 (18)
505 (9) 1203 (21)
2469 (7) 6073 (18)
80 80
6717 (25)
1486 (25)
8203 (25)
82
13 846 (51)
2654 (45)
16 500 (50)
84
Medicaid recipient
< .001
Mother’s age at child’s birth, y
< .001
< 20 20–24 25–29 ‡ 30 (Ref) Mother’s educational level < high school
3913 (14)
929 (16)
4842 (15)
81
< .001
High school
6966 (26)
1559 (27)
8525 (26)
82
< .01
16 348 (60)
3320 (57)
19 668 (60)
83
23 293 (83)
2946 (46)
26 239 (76)
89
4809 (17)
3520 (54)
8329 (24)
58
> high school (Ref) UTD by age 7 moc Yes (Ref)
< .001
No Household income below federal poverty level in census tract, % 0–< 5 (Ref)
12 663 (45)
2635 (41)
15 298 (44)
83
5–< 10
5698 (20)
1258 (19)
6956 (20)
82
0.12
10–< 20
5076 (18)
1235 (19)
6311 (18)
80
< .001
20–100
4665 (17)
1338 (21)
6003 (17)
78
< .001
Non-English language spoken at home in census tract,d quartile 1 (lowest; Ref)
5458 (19)
1185 (18)
6643 (19)
82
2
6184 (22)
1353 (21)
7537 (22)
82
3
7250 (26)
1517 (23)
8767 (25)
83
0.39
4
9210 (33)
2411 (37)
11 621 (34)
79
< .001
20 479 (73)
4700 (73)
25 179 (73)
81
7623 (27)
1766 (27)
9389 (27)
81
Residence in IAP area
0.86
0.76
Yes No (Ref)
Note. DTaP = diphtheria and tetanus toxoids and acellular pertussis; Hib = Haemophilus b; IAP = Immunization Action Plan; MMR = measles-mumps-rubella; PCV = pneumococcal polysaccharideprotein conjugate vaccine; UTD = up-to-date. UTD defined as receipt of 4:3:1:2:3:1:4 vaccine series by age 24 mo (‡ 4 doses DTaP, ‡ 3 doses poliovirus vaccine, ‡ 1 dose MMR vaccine, ‡ 2 doses Hib conjugate vaccine, ‡ 3 doses hepatitis B vaccine, ‡ 1 dose varicella, and ‡ 2–4 age-appropriate doses of PCV). To be considered UTD for MMR, varicella, and PCV, ‡ 1 dose on or after the first birthday was required. The sample size was n = 34 568. a Missing variables in entire study population ranged from 0% to 4.7%. b P value generated by comparison of percentage UTD for the specified variable compared with the percentage UTD for the reference group. c UTD by age 7 mo was defined as ‡ 3 doses of DTaP, ‡ 2 doses of poliovirus vaccine, ‡ 2 doses of Hib, ‡ 2 doses of hepatitis B vaccine, and ‡ 3 doses of PCV. d Among population aged ‡ 5 y.
vaccination rates, including establishment of jurisdiction-wide Immunization Information Systems, which are used for improving
vaccination levels; removing out-of pocket costs for vaccine and for vaccination as barriers to immunization; improving the quality of vaccine
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delivery systems by conducting practice-based assessments; and setting standards for pediatric vaccination practice that call attention to
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TABLE 3—Predictors of Underimmunization at Age 24 Months Among Children Not Up-to-Date by Age 7 Months: Connecticut 2006 Birth Cohort Variablea
Not UTD by Age 24 Mo, %
OR (95% CI)
AOR (95% CI)b
Sex Female
41
0.9 (0.8, 1.0)
0.9 (0.8, 1.0)
Male (Ref)
43
1.0
1.0
39 33
0.8 (0.7, 0.9) 0.6 (0.6, 0.7)
1.1 (1.0, 1.3) 1.0 (0.8, 1.1)
Race/ethnicity Non-Hispanic Black Hispanic American Indian
45
1.0 (0.5, 2.0)
1.0 (0.5, 2.0)
Asian or Pacific Islander
46
1.1 (0.9, 1.4)
1.0 (0.8, 1.3)
Non-Hispanic White (Ref)
44
1.0
1.0
Yes
38
0.6 (0.6, 0.7)
0.6 (0.5, 0.7)
No (Ref)
49
1.0
1.0
40
0.6 (0.6, 0.7)
0.7 (0.6, 0.9)
51
1.0
1.0
Medicaid recipient
Residence in IAP area Yes No (Ref) Mother’s age at child’s birth, y < 20
34
0.7 (0.6, 0.8)
1.1 (0.9, 1.4)
20–24
37
0.8 (0.7, 0.9)
1.2 (1.0, 1.4)
25–29
40
0.9 (0.8, 1.0)
1.1 (1.0, 1.3)
‡ 30 (Ref)
43
1.0
1.0
Mother’s educational level < high school
32
0.6 (0.5, 0.6)
0.8 (0.7, 1.0)
High school
38
0.7 (0.7, 0.8)
0.9 (0.8, 1.1)
> high school (Ref)
45
1.0
1.0
0–< 5 (Ref)
48
1.0
1.0
5–< 10
41
0.8 (0.7, 0.9)
0.9 (0.8, 1.1)
10–< 20 20–100
41 37
0.7 (0.7, 0.8) 0.6 (0.6, 0.7)
1.0 (0.8, 1.3) 1.1 (0.8, 1.4)
1 (lowest; Ref)
48
1.0
1.0
2
46
0.9 (0.8, 1.1)
1.1 (0.9, 1.3)
3
44
0.8 (0.7, 1.0)
1.1 (0.8, 1.3)
4
38
0.6 (0.6, 0.7)
0.9 (0.7, 1.2)
Household income below federal poverty level in census tract, %
Non-English language spoken at home in census tract,c quartile
Note. AOR = adjusted odds ratio; CI = confidence interval; DTaP = diphtheria and tetanus toxoids and acellular pertussis; Hib = Haemophilus b; IAP = Immunization Action Plan; MMR = measles-mumps-rubella; OR = odds ratio; PCV = pneumococcal polysaccharide-protein conjugate vaccine; UTD = up-to-date. UTD defined as receipt of 4:3:1:2:3:1:4 vaccine series by age 24 mo (‡ 4 doses DTaP, ‡ 3 doses poliovirus vaccine, ‡ 1 dose MMR vaccine, ‡ 2 doses Hib conjugate vaccine, ‡ 3 doses hepatitis B vaccine, ‡ 1 dose varicella, and ‡ 2–4 age-appropriate doses of PCV). To be considered UTD for MMR, varicella, and PCV, ‡ 1 dose on or after the first birthday was required. The sample size was n = 8329; n = 7320 for multilevel analysis. a Missing variables ranged from 0% to 10.7%. b County of residence at birth was included in the model as a random effect. c Among population aged ‡ 5 y.
numerous ways clinicians can efficiently and effectively ensure that all infants in their care receive timely vaccinations.5,18 The specific
interventions that contribute the majority of influence to the national narrowing of SES-related disparities are unknown.
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In our data, residence in an area served by a vaccination coordinator appeared to be significantly protective against underimmunization at age 24 months among children who were behind on immunizations at age 7 months. In Connecticut, IAP coordinators use certain interventions that are part of the national vaccination strategy. They use CIRTS to identify children who are behind at age 7 months to get them back on schedule, and they conduct outreach that can include home visits. This targeted follow-up of children who are behind at age 7 months might help explain the finding that residing in a town with a dedicated vaccination coordinator was a strong predictor of becoming UTD by age 24 months among children who were behind at age 7 months. Although the particular IAP interventions that most effectively increase vaccination coverage are undetermined, our analysis demonstrates that the collective efforts of dedicated vaccination coordinators implementing elements of the national vaccination strategy among populations at risk can make a difference. The finding that Medicaid enrollment was a strong predictor of getting children who were behind at age 7 months back on track by age 24 months was surprising. This observation contrasts with other studies that found that Medicaid, or more generally public insurance, lacked an association with UTD status during early childhood or was associated with underimmunization.19---22 The explanation for our differing observation is unknown. However, previous studies did not stratify on UTD status at an earlier point, and we found that Medicaid was protective only among children who were not UTD at age 7 months. Medicaid enrollment in Connecticut, particularly among children who have already fallen behind, might signal to public health and clinical staff an increased risk for continued underimmunization. Consequently, increased intensity of interventions might be directed toward this vulnerable population during infancy, thus protecting them against underimmunization at age 24 months. Two aspects of the national CII might selectively help infants enrolled in Medicaid catch up after missing vaccinations. First, infants
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TABLE 4—Predictors of Underimmunization at Age 24 Months Among Children Up-to-Date by Age 7 Months: Connecticut 2006 Birth Cohort Variablea
Not UTD by Age 24 Mo, %
OR (95% CI)
AOR (95% CI)b
Sex Female
11
1.0 (0.9, 1.1)
1.0 (0.9, 1.1)
Male (Ref)
11
1.0
1.0
13 11
1.3 (1.1, 1.4) 1.0 (0.9, 1.1)
1.1 (0.9, 1.3) 0.8 (0.7, 0.9)
Race/ethnicity Non-Hispanic Black Hispanic American Indian
18
1.8 (1.1, 3.0)
1.7 (1.0, 3.0)
Asian or Pacific Islander
12
1.2 (1.0, 1.4)
1.2 (1.0, 1.4)
Non-Hispanic White (Ref)
11
1.0
1.0
Yes
12
1.2 (1.1, 1.3)
1.1 (1.0, 1.3)
No (Ref)
10
1.0
1.0
11
1.1 (1.0, 1.1)
1.0 (0.8, 1.1)
11
1.0
1.0
Medicaid recipient
Residence in IAP area Yes No (Ref) Mother’s age at child’s birth, y < 20
13
1.3 (1.1, 1.6)
1.3 (1.1, 1.6)
20–24
12
1.3 (1.1, 1.4)
1.2 (1.1, 1.4)
25–29
12
1.2 (1.1, 1.3)
1.2 (1.1, 1.3)
‡ 30 (Ref)
10
1.0
1.0
Mother’s educational level < high school
12
1.1 (1.0, 1.3)
1.0 (0.8, 1.2)
High school
11
1.1 (1.0, 1.2)
0.9 (0.8, 1.1)
> high school (Ref)
11
1.0
1.0
0–< 5 (Ref)
11
1.0
1.0
5–< 10
11
1.0 (0.9, 1.2)
1.0 (0.9, 1.1)
10–< 20 20–100
11 13
1.1 (1.0, 1.2) 1.3 (1.1, 1.4)
1.0 (0.9, 1.2) 1.1 (0.9, 1.4)
1 (lowest; Ref)
11
1.0
1.0
2
11
1.0 (0.9, 1.1)
1.0 (0.8, 1.1)
3
10
0.8 (0.7, 0.9)
0.8 (0.7, 1.0)
4
13
1.1 (1.0, 1.3)
1.0 (0.8, 1.3)
Household income below federal poverty level in census tract, %
Non-English language spoken at home in census tract,c quartile
Note. AOR = adjusted odds ratio; CI = confidence interval; DTaP = diphtheria and tetanus toxoids and acellular pertussis; Hib = Haemophilus b; IAP = Immunization Action Plan; MMR = measles-mumps-rubella; OR = odds ratio; PCV = pneumococcal polysaccharide-protein conjugate vaccine; UTD = up-to-date. UTD defined as receipt of 4:3:1:2:3:1:4 vaccine series by age 24 mo (‡ 4 doses DTaP, ‡ 3 doses poliovirus vaccine, ‡ 1 dose MMR vaccine, ‡ 2 doses Hib conjugate vaccine, ‡ 3 doses hepatitis B vaccine, ‡ 1 dose varicella, and ‡ 2–4 age-appropriate doses of PCV). To be considered UTD for MMR, varicella, and PCV, ‡ 1 dose on or after the first birthday was required. Sample size was n = 26 239; n = 25 253 for multilevel analysis. a Missing variables ranged from 0% to 2.9%. b County of residence at birth was included in the model as a random effect. c Among population aged ‡ 5 y.
enrolled in Medicaid are likely to receive other services (e.g., the Special Supplemental Nutrition Program for Women, Infants, and
Children). One CII-recommended strategy is to take advantage of visits with other services to check vaccination status and take action. Second,
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the CII recommendation to conduct pediatric practice---specific assessments of vaccination levels followed by discussion of ways to improve them is likely implemented more routinely in clinics serving a high percentage of children who receive Medicaid (e.g., community health centers) than among private pediatric practices primarily serving children with private health insurance.5 Future efforts to examine risk factors for underimmunization during early childhood should include examination of the potential role of Medicaid in helping children catch up. The finding that the strongest predictor of underimmunization at age 24 months was underimmunization at an earlier age is neither new nor surprising.23---26 Connecticut has implemented strategies to address the problem of inadequate care in early childhood, through both IAP and non-IAP mechanisms. Strategies that are not vaccination specific include ensuring that infants are placed in a medical home, medical homes take full responsibility for each assigned child, practice-based reminder---recall and outreach systems for missed appointments are in place, well-child care is free, and documentation of well-child care is necessary to receive Special Supplemental Nutrition Program for Women, Infants, and Children benefits. CIRTS is used by vaccination coordinators to identify infants who are behind at age 7 months. This use of CIRTS appeared to be effective: 58% of those who were behind at 7 months subsequently caught up, and SES disparities observed in an analysis with UTD status at 7 months as the outcome largely disappeared by 24 months (data not shown). Thus, it appears that a key strategy for further improving early childhood vaccination levels and decreasing disparities is enhancement of an old strategy: identifying children who are missing well-child appointments or ageappropriate vaccinations as early as possible after neonatal discharge and getting them back into care. Achieving this goal will require a more complete understanding of why certain infants do not receive routine care or vaccinations early on and will require targeting intervention efforts to the identified problems.
Limitations CIRTS data did not include the 11% of Connecticut children whose parents opted out
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during 2006. Vaccination rates and other characteristics of these children are unknown. However, approximately 89% of the state’s 2006 birth cohort was part of our study population, so our results are likely generalizable to all Connecticut children in a comparable age range. We assumed that all children, whether in IAP areas or on Medicaid or not, had an equal probability of having administered vaccinations recorded in CIRTS. To the extent that this was not true, the magnitude of our findings could be greater or smaller. We have no data to suggest a reporting bias in either direction. Our analysis did not account for children who moved and changed area-based SES or IAP status during the study period; we used only the residential address at time of birth to assign a census tract and an IAP area. Consequently, the census tract and IAP area characteristics assigned to a child might have been inaccurate, depending on where the child moved. This probably resulted in nonsystematic misclassification, diminishing the strength of any measured associations. Also, Medicaid status can change; we determined this as of the final time the child’s CIRTS record was updated, typically at age 19 to 24 months. However, because we used the Health Plan Employer Data and Information Set standard to define the Medicaid variable and not simply Medicaid enrollment, the influence of such inaccuracies was minimal. Furthermore, the effect of such misclassification might be to diminish the strength of association reported. The methods used to examine preintervention disparities were not directly comparable with our methods. In the preintervention analyses, all children residing in the 3 largest urban areas represented low-SES populations, regardless of their immediate census tract SES, but we used more refined measures that were more specific for low SES. In addition, the fact that the IAP measure revealed minimal disparities was relevant, because all 3 urban areas were IAP areas.
Conclusions We demonstrated that disparities by certain SES measures in vaccination levels at age 24 months still exist but are limited. The
strongest predictor of underimmunization at age 24 months was having fallen behind during the 7 months after birth. Among this latter group, 58% were able to subsequently catch up; receiving Medicaid and residing in areas with full-time vaccination coordinators increased the probability of catching up. These findings demonstrate that when special attention is focused on ensuring that infants born in low-SES circumstances receive vaccinations, specifically by identifying and intervening on behalf of children who fall behind early, as identified in a centralized Immunization Information System, disparities can be minimized. j
About the Authors At the time of the study, Jessica A. Kattan was an Epidemic Intelligence Service Officer with the Centers for Disease Control and Prevention (CDC), assigned to the Infectious Diseases Section, Connecticut Department of Public Health, Hartford. Kathy S. Kudish is with the Immunization Program and Kristen Soto is with the Infectious Diseases Section, Connecticut Department of Public Health. Betsy L. Cadwell is with the Office of Surveillance, Epidemiology, and Laboratory Services, CDC, Atlanta, GA. James L. Hadler is a consultant for the Connecticut Emerging Infections Program, New Haven. Correspondence should be sent to Jessica A. Kattan, New York City Department of Health and Mental Hygiene, Bureau of Alcohol and Drug Use Prevention, Care and Treatment, Gotham Center, 42-09 28th Street, 19th Floor, CN#14, Queens, New York 11101-4132 (e-mail: jkattan@ health.nyc.gov). Reprints can be ordered at http://www.ajph. org by clicking the “Reprints” link. This article was accepted April 25, 2013. Note. The findings and conclusions in this report are those of the authors and do not necessarily represent the official position of the CDC.
Contributors J. A. Kattan helped design the study, performed the analysis, and led the writing of the article. K. S. Kudish originated and helped design the study and analyze the data. B. L. Cadwell helped design the study and guided the data analysis. K. Soto helped analyze the data. All authors interpreted data and revised the article. J. L. Hadler helped design the study and supervised all stages.
Acknowledgments We thank Gary Archambault, Diane Fraiter, Melinda Mailhot, Stephanie Poulin, and Vincent Sacco, Connecticut Department of Public Health for their assistance.
Human Participant Protection This study underwent human subjects review at the CDC and was determined to be public health practice, not research.
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