School-Located Influenza Vaccination: Do Vaccine Clinics at School Raise Vaccination Rates?

BACKGROUND: Only half of US schoolchildren receive influenza vaccine. School-located influenza vaccination (SLIV) might raise vaccination rates but conducting flu vaccine clinics at schools is challenging to implement. We compared 2 school-based programs designed to raise influenza vaccination rates: parent reminder/educational messages sent to parents from schools which is a low-intensity intervention vs the combination of reminder/educational messages plus SLIV clinics which is a high-intensity intervention. METHODS: We assigned 36 schools (6 school districts, 2 per group) to 3 groups: (1) control, ie, no SLIV and no parent reminder/education, (2) parent reminder/education emailed by schools, and (3) parent reminder/education plus SLIV clinics. Some schools had SLIV clinics in prior years. Health department nurses conducted SLIV clinics. RESULTS: Among 24,832 children at 36 schools, vaccination rates were control (51.3%), parent reminder/education-only (41.2%), and reminder/education + SLIV (58.7%). On multivariate analyses which controlled for vaccination in prior seasons, children in reminder/education + SLIV schools had higher vaccination rates (OR 1.27, 95% CI 1.10-1.47), but children in reminder/education-only schools had lower rates (OR 0.87, 95% CI 0.75-1.00) than children in control schools. CONCLUSIONS: Parent reminder/education combined with SLIV clinics raise vaccination rates, but parent reminder/education alone does not.

Text Message Reminders for Child Influenza Vaccination in the Setting of School-Located Influenza Vaccination: A Randomized Clinical Trial.

Half of US school children receive influenza vaccine. In our previous trials, school-located influenza vaccination (SLIV) raised vaccination rates by 5 to 8 percentage points. We assessed whether text message reminders to parents could raise vaccination rates above those observed with SLIV. Within urban elementary schools we randomized families into text message + SLIV (intervention) versus SLIV alone (comparison). All parents were sent 2 backpack notifications plus 2 autodialer phone reminders about SLIV at a single SLIV clinic. Intervention group parents also were sent 3 text messages from the school nurse encouraging flu vaccination via either primary care or SLIV. Among 15 768 children at 32 schools, vaccination rates were text + SLIV (40%) and SLIV control (40%); 4% of students per group received influenza vaccination at SLIV. Text message reminders did not raise influenza vaccination rates above those observed with SLIV alone. More intensive interventions are needed to raise influenza vaccination rates.

Impact of elementary school-located influenza vaccinations: A stepped wedge trial across a community.

BACKGROUND: Influenza vaccination rates among children are low and novel strategies are needed to raise coverage. We measured the impact of school-located influenza vaccination (SLIV) on coverage, examined whether SLIV substitutes for practice-based influenza vaccination ("substitution"), and estimated whether a second year of experience with SLIV increases its impact. METHODS: We implemented a stepped wedge study design with schools as clusters. In Year 1, we randomly allocated schools to SLIV or control. In Year 2, all schools performed SLIV. We used emails (suburban schools) or backpack fliers (both urban and suburban schools) to notify parents, and offered web-based (suburban) or paper-based vaccination (urban) consent forms. Local health department nurses administered SLIV vaccinations and billed insurers. We analyzed state immunization registry data to measure influenza vaccination rates. RESULTS: 42 schools (38,078 children) participated over 2 years. Overall vaccination rates were 5 and 7 percentage points higher among SLIV- school children versus control-school children in suburban (aOR 1.36, 95% CI 1.25-1.49 in Years 1-2 SLIV vs. Year 1 control schools) and urban schools (aOR 1.22, 95% CI 1.10-1.36), respectively, adjusting for prior year's vaccination and other covariates. While no substitution occurred among children attending suburban schools, some substitution occurred among children attending urban schools, although overall vaccination rates were still higher in urban schools due to SLIV. Compared to an initial year of SLIV, more children were vaccinated in a second year of SLIV at urban (8.3% vs. 6.8%, aOR 1.24, 95% CI 1.04-1.47) but not suburban schools (3.5% vs. 2.7%, aOR 1.24, 95% CI 0.98-1.57). CONCLUSIONS: In this stepped wedge trial, SLIV increased overall influenza vaccination rates in suburban and urban schools. Some substitution for primary care vaccination occurred in urban settings. A second year of SLIV expanded its reach slightly in urban schools.

School-located Influenza Vaccinations for Adolescents: A Randomized Controlled Trial.

PURPOSE: We aimed to evaluate the effect of school-located influenza vaccination (SLIV) on adolescents' influenza vaccination rates. METHODS: In 2015-2016, we performed a cluster-randomized trial of adolescent SLIV in middle/high schools. We selected 10 pairs of schools (identical grades within pairs) and randomly allocated schools within pairs to SLIV or usual care control. At eight suburban SLIV schools, we sent parents e-mail notifications about upcoming SLIV clinics and promoted online immunization consent. At two urban SLIV schools, we sent parents (via student backpack fliers) paper immunization consent forms and information about SLIV. E-mails were unavailable at these schools. Local health department nurses administered nasal or injectable influenza vaccine at dedicated SLIV clinics and billed insurers. We compared influenza vaccination rates at SLIV versus control schools using school directories to identify the student sample in each school. We used the state immunization registry to determine receipt of influenza vaccination. RESULTS: The final sample comprised 17,650 students enrolled in the 20 schools. Adolescents at suburban SLIV schools had higher overall influenza vaccination rates than did adolescents at control schools (51% vs. 46%, p < .001; adjusted odds ratio = 1.27, 95% confidence interval 1.18-1.38, controlling for vaccination during the prior two seasons). No effect of SLIV was noted among urbanschools on multivariate analysis. SLIV did not substitute for vaccinations in primary care or other settings; in suburban settings, SLIV was associated with increased vaccinations in primary care or other settings (adjusted odds ratio = 1.10, 95% confidence interval 1.02-1.19). CONCLUSIONS: SLIV in this community increased influenza vaccination rates among adolescents attending suburban schools.

School-Located Influenza Vaccinations: A Randomized Trial.

OBJECTIVE: Assess impact of offering school-located influenza vaccination (SLIV) clinics using both Web-based and paper consent upon overall influenza vaccination rates among elementary school children. METHODS: We conducted a cluster-randomized trial (stratified by suburban/urban districts) in upstate New York in 2014-2015. We randomized 44 elementary schools, selected similar pairs of schools within districts, and allocated schools to SLIV versus usual care (control). Parents of children at SLIV schools were sent information and vaccination consent forms via e-mail, backpack fliers, or both (depending on school preferences) regarding school vaccine clinics. Health department nurses conducted vaccine clinics and billed insurers. For all children registered at SLIV/control schools, we compared receipt of influenza vaccination anywhere (primary outcome). RESULTS: The 44 schools served 19 776 eligible children in 2014-2015. Children in SLIV schools had higher influenza vaccination rates than children in control schools county-wide (54.1% vs 47.4%, P < .001) and in suburban (61.9% vs 53.6%, P < .001) and urban schools (43.9% vs 39.2%; P < .001). Multivariate analyses (controlling for age, grade, vaccination in previous season) confirmed bivariate findings. Among parents who consented for SLIV, nearly half of those notified by backpack fliers and four-fifths of those notified by e-mail consented online. In suburban districts, SLIV did not substitute for primary care influenza vaccination. In urban schools, some substitution occurred. CONCLUSIONS: SLIV raised seasonal influenza vaccination rates county-wide and in both suburban and urban settings. SLIV did not substitute for primary care vaccinations in suburban settings where pediatricians often preorder influenza vaccine but did substitute somewhat in urban settings.

Compliance with a New York State 2010 HIV Testing Law: Is There Racial/Ethnic Bias in HIV Testing? Experience of Monroe County, New York, 2012.

BACKGROUND: While routine HIV testing in the general population is a national recommendation, actual practice may vary. PURPOSE: To determine risk factors associated with HIV testing after the adoption of a New York State law in 2010 mandating that health care providers offer HIV testing in all clinical settings. METHODS: Survey data from Monroe County, New York, were collected in 2012 for adults aged 18-64 years and analyzed in 2014. Logistic regression was used to identify risk factors independently associated with HIV testing and high-risk behavior. RESULTS: Among adults aged 18-34, fewer Whites were offered HIV testing in the past year by their doctors compared with Blacks (34% vs 64%) despite having similar rates of any HIV high-risk behavior (20% overall). For adults aged 35-64 years, fewer Whites than Blacks were ever tested for HIV (42% vs 71%), offered HIV testing in past year (17% vs 40%), and reported any HIV high-risk behavior (3% vs 13%). Latinos showed intermediate levels. With logistic regression analysis, ever tested for HIV was independently associated with only race/ethnicity; offered HIV testing in the past year was associated with females, Blacks and Latinos, aged 18-34 years, and having a routine health checkup in past year; any HIV high-risk behavior was associated with only younger age. CONCLUSIONS: To improve HIV testing rates as well as compliance with state laws and national guidelines, targeted efforts should be considered that improve perceptions of risk and emphasize the value of routine HIV screening, including those directed at White adults and their health care providers.

Using smartphone apps in STD interviews to find sexual partners.

OBJECTIVES: Smartphone applications (apps) are increasingly used to facilitate casual sexual relationships, increasing the risk of sexually transmitted diseases (STDs). In STD investigations, traditional contact elicitation methods can be enhanced with smartphone technology during field interviews. METHODS: In 2013, the Monroe County Department of Public Health conducted a large, multi-infection STD investigation among men who have sex with men (MSM) using both index case and cluster interviews. When patients indicated meeting sexual partners online, disease intervention specialists (DISs) had access to smartphone apps and were able to elicit partners through access to inboxes and profiles where traditional contact information was lacking. Social network mapping was used to display the extent of the investigation and the impact of access to smartphones on the investigation. RESULTS: A total of 14 index patient interviews and two cluster interviews were conducted; 97 individuals were identified among 117 sexual dyads. On average, eight partners were elicited per interview (range: 1-31). The seven individuals who used apps to find partners had an average of three Internet partners (range: 1-5). Thirty-six individuals either had a new STD (n=7) or were previously known to be HIV-positive (n=29). Of the 117 sexual dyads, 21 (18%) originated either online (n=8) or with a smartphone app (n=13). Of those originating online or with a smartphone app, six (29%) partners were located using the smartphone and two (10%) were notified of their exposure via a website. Three of the new STD/HIV cases were among partners who met online. CONCLUSION: Smartphone technology used by DISs in the field improved contact elicitation and resulted in successful partner notification and case finding.

Outbreak of Mycobacterium chelonae infection associated with tattoo ink.

BACKGROUND: In January 2012, on the basis of an initial report from a dermatologist, we began to investigate an outbreak of tattoo-associated Mycobacterium chelonae skin and soft-tissue infections in Rochester, New York. The main goals were to identify the extent, cause, and form of transmission of the outbreak and to prevent further cases of infection. METHODS: We analyzed data from structured interviews with the patients, histopathological testing of skin-biopsy specimens, acid-fast bacilli smears, and microbial cultures and antimicrobial susceptibility testing. We also performed DNA sequencing, pulsed-field gel electrophoresis (PFGE), cultures of the ink and ingredients used in the preparation and packaging of the ink, assessment of source water and faucets at tattoo parlors, and investigation of the ink manufacturer. RESULTS: Between October and December 2011, a persistent, raised, erythematous rash in the tattoo area developed in 19 persons (13 men and 6 women) within 3 weeks after they received a tattoo from a single artist who used premixed gray ink; the highest occurrence of tattooing and rash onset was in November (accounting for 15 and 12 patients, respectively). The average age of the patients was 35 years (range, 18 to 48). Skin-biopsy specimens, obtained from 17 patients, showed abnormalities in all 17, with M. chelonae isolated from 14 and confirmed by means of DNA sequencing. PFGE analysis showed indistinguishable patterns in 11 clinical isolates and one of three unopened bottles of premixed ink. Eighteen of the 19 patients were treated with appropriate antibiotics, and their condition improved. CONCLUSIONS: The premixed ink was the common source of infection in this outbreak. These findings led to a recall by the manufacturer.