#PAGE_PARAMS# #ADS_HEAD_SCRIPTS# #MICRODATA#

Evaluation of a city-wide school-located influenza vaccination program in Oakland, California, with respect to vaccination coverage, school absences, and laboratory-confirmed influenza: A matched cohort study


Autoři: Jade Benjamin-Chung aff001;  Benjamin F. Arnold aff001;  Chris J. Kennedy aff001;  Kunal Mishra aff001;  Nolan Pokpongkiat aff001;  Anna Nguyen aff001;  Wendy Jilek aff001;  Kate Holbrook aff003;  Erica Pan aff003;  Pam D. Kirley aff005;  Tanya Libby aff005;  Alan E. Hubbard aff001;  Arthur Reingold aff001;  John M. Colford, Jr. aff001
Působiště autorů: Division of Epidemiology and Biostatistics, University of California, Berkeley, Berkeley, California, United States of America aff001;  Francis I. Proctor Foundation, University of California, San Francisco, San Francisco, California, United States of America aff002;  Division of Communicable Disease Control and Prevention, Alameda County Public Health Department, Oakland, California, United States of America aff003;  Department of Pediatrics, Division of Infectious Diseases, University of California, San Francisco, San Francisco, California, United States of America aff004;  California Emerging Infections Program, Oakland, California, United States of America aff005
Vyšlo v časopise: Evaluation of a city-wide school-located influenza vaccination program in Oakland, California, with respect to vaccination coverage, school absences, and laboratory-confirmed influenza: A matched cohort study. PLoS Med 17(8): e32767. doi:10.1371/journal.pmed.1003238
Kategorie: Research Article
doi: https://doi.org/10.1371/journal.pmed.1003238

Souhrn

Background

It is estimated that vaccinating 50%–70% of school-aged children for influenza can produce population-wide indirect effects. We evaluated a city-wide school-located influenza vaccination (SLIV) intervention that aimed to increase influenza vaccination coverage. The intervention was implemented in ≥95 preschools and elementary schools in northern California from 2014 to 2018. Using a matched cohort design, we estimated intervention impacts on student influenza vaccination coverage, school absenteeism, and community-wide indirect effects on laboratory-confirmed influenza hospitalizations.

Methods and findings

We used a multivariate matching algorithm to identify a nearby comparison school district with pre-intervention characteristics similar to those of the intervention school district and matched schools in each district. To measure student influenza vaccination, we conducted cross-sectional surveys of student caregivers in 22 school pairs (2017 survey, N = 6,070; 2018 survey, N = 6,507). We estimated the incidence of laboratory-confirmed influenza hospitalization from 2011 to 2018 using surveillance data from school district zip codes. We analyzed student absenteeism data from 2011 to 2018 from each district (N = 42,487,816 student-days). To account for pre-intervention differences between districts, we estimated difference-in-differences (DID) in influenza hospitalization incidence and absenteeism rates using generalized linear and log-linear models with a population offset for incidence outcomes. Prior to the SLIV intervention, the median household income was $51,849 in the intervention site and $61,596 in the comparison site. The population in each site was predominately white (41% in the intervention site, 48% in the comparison site) and/or of Hispanic or Latino ethnicity (26% in the intervention site, 33% in the comparison site). The number of students vaccinated by the SLIV intervention ranged from 7,502 to 10,106 (22%–28% of eligible students) each year. During the intervention, influenza vaccination coverage among elementary students was 53%–66% in the comparison district. Coverage was similar between the intervention and comparison districts in influenza seasons 2014–2015 and 2015–2016 and was significantly higher in the intervention site in seasons 2016–2017 (7%; 95% CI 4, 11; p < 0.001) and 2017–2018 (11%; 95% CI 7, 15; p < 0.001). During seasons when vaccination coverage was higher among intervention schools and the vaccine was moderately effective, there was evidence of statistically significant indirect effects: The DID in the incidence of influenza hospitalization per 100,000 in the intervention versus comparison site was −17 (95% CI −30, −4; p = 0.008) in 2016–2017 and −37 (95% CI −54, −19; p < 0.001) in 2017–2018 among non-elementary-school-aged individuals and −73 (95% CI −147, 1; p = 0.054) in 2016–2017 and −160 (95% CI −267, −53; p = 0.004) in 2017–2018 among adults 65 years or older. The DID in illness-related school absences per 100 school days during the influenza season was −0.63 (95% CI −1.14, −0.13; p = 0.014) in 2016–2017 and −0.80 (95% CI −1.28, −0.31; p = 0.001) in 2017–2018. Limitations of this study include the use of an observational design, which may be subject to unmeasured confounding, and caregiver-reported vaccination status, which is subject to poor recall and low response rates.

Conclusions

A city-wide SLIV intervention in a large, diverse urban population was associated with a decrease in the incidence of laboratory-confirmed influenza hospitalization in all age groups and a decrease in illness-specific school absence rate among students in 2016–2017 and 2017–2018, seasons when the vaccine was moderately effective, suggesting that the intervention produced indirect effects. Our findings suggest that in populations with moderately high background levels of influenza vaccination coverage, SLIV programs are associated with further increases in coverage and reduced influenza across the community.

Klíčová slova:

California – Hospitalizations – Influenza – Schools – Surveys – Vaccination and immunization – Vaccines – Caregivers


Zdroje

1. Thompson WW, Shay DK, Weintraub E, Brammer L, Cox N, Anderson LJ, et al. Mortality associated with influenza and respiratory syncytial virus in the United States. JAMA. 2003;289:179–86. doi: 10.1001/jama.289.2.179 12517228

2. Fiore AE, Uyeki TM, Broder K, Finelli L, Euler G, Singleton M, et al. Prevention and control of influenza with vaccines: recommendations of the Advisory Committee on Immunization Practices (ACIP), 2010. Morb Mortal Wkly Rep. 2010;59:1–62.

3. Glezen WP, Couch RB. Interpandemic influenza in the Houston area, 1974–76. N Engl J Med. 1978;298:587–92. doi: 10.1056/NEJM197803162981103 628375

4. Monto AS, Sullivan KM. Acute respiratory illness in the community. Frequency of illness and the agents involved. Epidemiol Infect. 1993;110:145–60. doi: 10.1017/s0950268800050779 8432318

5. Fox JP, Cooney MK, Hall CE, Foy HM. Influenza virus infections in Seattle families, 1975–1979: II. Pattern of infection in invaded households and relation of age and prior antibody to occurrence of infection and related illness. Am J Epidemiol. 1982;116:228–42. doi: 10.1093/oxfordjournals.aje.a113408 7114034

6. Foy HM, Cooney MK, Hall C, Malmgren J, Fox JP. Case-to-case intervals of rhinovirus and influenza virus infections in households. J Infect Dis. 1988;157:180–2. doi: 10.1093/infdis/157.1.180 2826607

7. Long CE, Hall CB, Cunningham CK, Weiner LB, Alger KP, Gouveia M, et al. Influenza surveillance in community-dwelling elderly compared with children. Arch Fam Med. 1997;6:459–65. doi: 10.1001/archfami.6.5.459 9305689

8. Neuzil KM, Fiore AE, Schieber RA. Evolution of the Pediatric Influenza Vaccination Program in the United States. Pediatrics. 2012;129:S51–3. doi: 10.1542/peds.2011-0737B 22383481

9. Longini IM, Halloran ME, Nizam A, Wolff M, Mendelman PM, Fast PE, et al. Estimation of the efficacy of live, attenuated influenza vaccine from a two-year, multi-center vaccine trial: implications for influenza epidemic control. Vaccine. 2000;18:1902–9. doi: 10.1016/s0264-410x(99)00419-3 10699339

10. Longini IM. A Theoretic framework to consider the effect of immunizing schoolchildren against influenza: implications for research. Pediatrics. 2012;129:S63–7. doi: 10.1542/peds.2011-0737D 22383483

11. Centers for Disease Control and Prevention. Estimates of flu vaccination coverage among children—United States, 2017–18 flu season. Atlanta: Centers for Disease Control and Prevention; 2018 [cited 2018 Dec 11]. Available from: https://www.cdc.gov/flu/fluvaxview/coverage-1718estimates-children.htm.

12. Centers for Disease Control and Prevention. Estimates of influenza vaccination coverage among adults—United States, 2017–18 flu season. Atlanta: Centers for Disease Control and Prevention; 2018 [cited 2019 Jun 28]. Available from: https://www.cdc.gov/flu/fluvaxview/coverage-1718estimates.htm.

13. Healthy People 2020. Immunization and infectious diseases. Washington (DC): US Department of Health and Human Services; 2019 [cited 2019 Aug 23]. Available from: https://www.healthypeople.gov/2020/topics-objectives/topic/immunization-and-infectious-diseases/objectives.

14. Weycker D, Edelsberg J, Halloran ME, Longini IM, Nizam A, Ciuryla V, et al. Population-wide benefits of routine vaccination of children against influenza. Vaccine. 2005;23:1284–93. doi: 10.1016/j.vaccine.2004.08.044 15652671

15. Gaglani MJ. Editorial commentary: school-located influenza vaccination: why worth the effort? Clin Infect Dis. 2014;59:333–5. doi: 10.1093/cid/ciu344 24829211

16. King JC, Stoddard JJ, Gaglani MJ, Moore KA, Magder L, McClure E, et al. Effectiveness of school-based influenza vaccination. N Engl J Med. 2006;355:2523–32. doi: 10.1056/NEJMoa055414 17167135

17. Davis MM, King JC, Moag L, Cummings G, Magder LS. Countywide school-based influenza immunization: direct and indirect impact on student absenteeism. Pediatrics. 2008;122:e260–5. doi: 10.1542/peds.2007-2963 18595972

18. Kjos SA, Irving SA, Meece JK, Belongia EA. Elementary school-based influenza vaccination: evaluating impact on respiratory illness absenteeism and laboratory-confirmed influenza. PLoS ONE. 2013;8:e72243. doi: 10.1371/journal.pone.0072243 23991071

19. Pannaraj PS, Wang H-L, Rivas H, Wiryawan H, Smit M, Green N, et al. School-located influenza vaccination decreases laboratory-confirmed influenza and improves school attendance. Clin Infect Dis. 2014;59:325–32. doi: 10.1093/cid/ciu340 24829215

20. Pebody RG, Green HK, Andrews N, Zhao H, Boddington N, Bawa Z, et al. Uptake and impact of a new live attenuated influenza vaccine programme in England: early results of a pilot in primary school-age children, 2013/14 influenza season. Eurosurveillance. 2014;19:20823. doi: 10.2807/1560-7917.es2014.19.22.20823 24925457

21. Pebody RG, Green HK, Andrews N, Boddington NL, Zhao H, Yonova I, et al. Uptake and impact of vaccinating school age children against influenza during a season with circulation of drifted influenza A and B strains, England, 2014/15. Euro Surveill. 15;20:30029. doi: 10.2807/1560-7917.ES.2015.20.39.30029 26537222

22. Pebody R, Sile B, Warburton F, Sinnathamby M, Tsang C, Zhao H, et al. Live attenuated influenza vaccine effectiveness against hospitalisation due to laboratory-confirmed influenza in children two to six years of age in England in the 2015/16 season. Euro Surveill. 2017;22:30450. doi: 10.2807/1560-7917.ES.2017.22.4.30450 28182539

23. Humiston SG, Schaffer SJ, Szilagyi PG, Long CE, Chappel TR, Blumkin AK, et al. Seasonal influenza vaccination at school: a randomized controlled trial. Am J Prev Med. 2014;46:1–9. doi: 10.1016/j.amepre.2013.08.021 24355665

24. Szilagyi PG, Schaffer S, Rand CM, Vincelli P, Eagan A, Goldstein NPN, et al. School-located influenza vaccinations: a randomized trial. Pediatrics. 2016;138:e20161746. doi: 10.1542/peds.2016-1746 27940785

25. Szilagyi PG, Schaffer S, Rand CM, Goldstein NPN, Hightower AD, Younge M, et al. Impact of elementary school-located influenza vaccinations: a stepped wedge trial across a community. Vaccine. 2018;36:2861–9. doi: 10.1016/j.vaccine.2018.03.047 29678459

26. Wiggs-Stayner KS, Purdy TR, Go GN, McLaughlin NC, Tryzynka PS, Sines JR, et al. The impact of mass school immunization on school attendance. J Sch Nurs. 2006;22:219–22. doi: 10.1177/10598405050220040601 16856776

27. Mears CJ, Lawler EN, Sanders LD 3rd, Katz BZ. Efficacy of LAIV-T on absentee rates in a school-based health center sample. J Adolesc Health. 2009;45:91–4. doi: 10.1016/j.jadohealth.2008.12.010 19541255

28. Graitcer SB, Dube NL, Basurto-Davila R, Smith PF, Ferdinands J, Thompson M, et al. Effects of immunizing school children with 2009 influenza A (H1N1) monovalent vaccine on absenteeism among students and teachers in Maine. Vaccine. 2012;30:4835–41. doi: 10.1016/j.vaccine.2012.05.008 22609012

29. Yoo B-K, Humiston SG, Szilagyi PG, Schaffer SJ, Long C, Kolasa M. Cost effectiveness analysis of elementary school-located vaccination against influenza—results from a randomized controlled trial. Vaccine. 2013;31:2156–64. doi: 10.1016/j.vaccine.2013.02.052 23499607

30. Schmier J, Li S, King JC, Nichol K, Mahadevia PJ. Benefits and costs of immunizing children against influenza at school: an economic analysis based on a large-cluster controlled clinical trial. Health Aff (Millwood). 2008;27:w96–104. doi: 10.1377/hlthaff.27.2.w96 18216044

31. McBean M, Hull HF, O’Connor H. Possible herd immunity in the elderly following the vaccination of school children with live, attenuated trivalent influenza vaccine: a person-level analysis. Procedia Vaccinol. 2011;4:59–70. doi: 10.1016/j.provac.2011.07.009

32. Hull HF, McBean AM, Caldwell D, O’Connor H. Assessing herd immunity in the elderly following the vaccination of school children with live attenuated trivalent influenza vaccine (LAIV): a county-level analysis. Procedia Vaccinol. 2010;2:90–8.

33. Tran CH, Sugimoto JD, Pulliam JRC, Ryan KA, Myers PD, Castleman JB, et al. School-located influenza vaccination reduces community risk for influenza and influenza-like illness emergency care visits. PLoS ONE. 2014;9:e114479. doi: 10.1371/journal.pone.0114479 25489850

34. Szilagyi PG, Schaffer S, Rand CM, Goldstein NPN, Vincelli P, Hightower AD, et al. School-located influenza vaccinations for adolescents: a randomized controlled trial. J Adolesc Health. 2018;62:157–63. doi: 10.1016/j.jadohealth.2017.09.021 29248390

35. Szilagyi PG, Schaffer S, Rand CM, Goldstein NP, Hightower AD, Younge M, et al. School-located influenza vaccination: do vaccine clinics at school raise vaccination rates? J Sch Health. 2019;89:1004–12. doi: 10.1111/josh.12840 31612491

36. Grohskopf LA, Olsen SJ, Sokolow LZ, Bresee JS, Cox NJ, Broder KR, et al. Prevention and control of seasonal influenza with vaccines: recommendations of the Advisory Committee on Immunization Practices (ACIP)—United States, 2014–15 influenza season. Morb Mortal Wkly Rep. 2014;63:691–7.

37. Grohskopf LA, Sokolow LZ, Olsen SJ, Bresee JS, Broder KR, Karron RA. Prevention and control of influenza with vaccines: recommendations of the Advisory Committee on Immunization Practices, United States, 2015–16 influenza season. Morb Mortal Wkly Rep. 2015;64:818–25.

38. Grohskopf LA, Sokolow LZ, Broder KR, Olsen SJ, Karron RA, Jernigan DB, et al. Prevention and control of seasonal influenza with vaccines: recommendations of the Advisory Committee on Immunization Practices—United States, 2016–17 influenza season. Morb Mortal Wkly Rep. 2016;65:1–54. doi: 10.15585/mmwr.rr6505a1

39. Centers for Disease Control and Prevention. Seasonal influenza vaccine effectiveness, 2016–2017. Atlanta: Centers for Disease Control and Prevention; 2018 [cited 2019 Jun 14]. Available from: https://www.cdc.gov/flu/vaccines-work/2016-2017.html.

40. Rolfes MA, Flannery B, Chung JR, O’Halloran A, Garg S, Belongia EA, et al. Effects of influenza vaccination in the United States During the 2017–2018 influenza season. Clin Infect Dis. 2019;69:1845–53. doi: 10.1093/cid/ciz075 30715278

41. Arnold BF, Khush RS, Ramaswamy P, London AG, Rajkumar P, Ramaprabha P, et al. Causal inference methods to study nonrandomized, preexisting development interventions. Proc Natl Acad Sci U S A. 2010;107:22605–10. doi: 10.1073/pnas.1008944107 21149699

42. Diamond A, Sekhon JS. Genetic matching for estimating causal effects: a general multivariate matching method for achieving balance in observational studies. Rev Econ Stat. 2013;95:932–45. doi: 10.1162/REST_a_00318

43. Rubin DB. The design versus the analysis of observational studies for causal effects: parallels with the design of randomized trials. Stat Med. 2007;26:20–36. doi: 10.1002/sim.2739 17072897

44. Chaves SS, Lynfield R, Lindegren ML, Bresee J, Finelli L. The US Influenza Hospitalization Surveillance Network. Emerg Infect Dis. 2015;21:1543–50. doi: 10.3201/eid2109.141912 26291121

45. R Core Team. R: a language and environment for statistical computing. Vienna: R Foundation for Statistical Computing; 2017.

46. California Department of Public Health. California Department of Public Health (CDPH) influenza surveillance program. Sacramento: California Department of Public Health; 2019 [cited 2019 Jun 14]. Available from: https://www.cdph.ca.gov/Programs/CID/DCDC/pages/immunization/flu-reports.aspx.

47. Freedman DA. On the so-called “Huber sandwich estimator” and “robust standard errors.” Am Stat. 2006;60:299–302. doi: 10.1198/000313006X152207

48. Zou G. A modified Poisson regression approach to prospective studies with binary data. Am J Epidemiol. 2004;159:702–6. doi: 10.1093/aje/kwh090 15033648

49. Wing C, Simon K, Bello-Gomez RA. Designing difference in difference studies: best practices for public health policy research. Annu Rev Public Health. 2018;39:453–69. doi: 10.1146/annurev-publhealth-040617-013507 29328877

50. Arnold BF, Ercumen A, Benjamin-Chung J, Colford JM. Negative controls to detect selection bias and measurement bias in epidemiologic studies. Epidemiology. 2016;27:637–41. doi: 10.1097/EDE.0000000000000504 27182642

51. Lash TL, Fox MP, Fink AK. Applying quantitative bias analysis to epidemiologic data. New York: Springer Science & Business Media; 2011.

52. Gelman A, Jakulin A, Pittau MG, Su Y-S. A weakly informative default prior distribution for logistic and other regression models. Ann Appl Stat. 2008;2:1360–83. doi: 10.2307/30245139

53. Hastie T, Tibshirani R. Generalized additive models. London: Chapman and Hall; 1990.

54. Friedman J, Hastie T, Tibshirani R. Regularization paths for generalized linear models via coordinate descent. J Stat Softw. 2010;33:1–22. 20808728

55. Breiman L. Random forests. Mach Learn. 2001;45:5–32.

56. Friedman JH. Greedy function approximation: a gradient boosting machine. Ann Stat. 2001;29:1189–232.

57. Zimmerman RK, Nowalk MP, Chung J, Jackson ML, Jackson LA, Petrie JG, et al. 2014–2015 influenza vaccine effectiveness in the United States by vaccine type. Clin Infect Dis. 2016;63:1564–73. doi: 10.1093/cid/ciw635 27702768

58. Jackson ML, Chung JR, Jackson LA, Phillips CH, Benoit J, Monto AS, et al. Influenza vaccine effectiveness in the United States during the 2015–2016 season. N Engl J Med. 2017;377:534–43. doi: 10.1056/NEJMoa1700153 28792867

59. Flannery B, Chung JR, Thaker SN, Monto AS, Martin ET, Belongia EA, et al. Interim estimates of 2016–17 seasonal influenza vaccine effectiveness—United States, February 2017. Morb Mortal Wkly Rep. 2017;66:167–71. doi: 10.15585/mmwr.mm6606a3 28207689

60. Nosek BA, Alter G, Banks GC, Borsboom D, Bowman SD, Breckler SJ, et al. Promoting an open research culture. Science. 2015;348:1422–5. doi: 10.1126/science.aab2374 26113702

61. Yin JK, Heywood AE, Georgousakis M, King C, Chiu C, Isaacs D, et al. Systematic review and meta-analysis of indirect protection afforded by vaccinating children against seasonal influenza: implications for policy. Clin Infect Dis. 2017;65:719–28. doi: 10.1093/cid/cix420 28475770

62. Hughes MM, Reed C, Flannery B, Garg S, Singleton JA, Fry AM, et al. Projected population benefit of increased effectiveness and coverage of influenza vaccination on influenza burden—United States. Clin Infect Dis. 2020;70:2496–502. doi: 10.1093/cid/ciz676 31344229

63. Shinall MC, Plosa EJ, Poehling KA. Validity of parental report of influenza vaccination in children 6 to 59 months of age. Pediatrics. 2007;120:e783–7. doi: 10.1542/peds.2007-0052 17908736

64. Irving SA, Donahue JG, Shay DK, Ellis-Coyle TL, Belongia EA. Evaluation of self-reported and registry-based influenza vaccination status in a Wisconsin cohort. Vaccine. 2009;27:6546–9. doi: 10.1016/j.vaccine.2009.08.050 19729083

65. Brown C, Clayton-Boswell H, Chaves SS, Prill MM, Iwane MK, Szilagyi PG, et al. Validity of parental report of influenza vaccination in young children seeking medical care. Vaccine. 2011;29:9488–92. doi: 10.1016/j.vaccine.2011.10.023 22015394

66. Centers for Disease Control and Prevention. Full and partial flu vaccination coverage in young children, six immunization information systems sentinel sites, 2012–13–2016–17. Atlanta: Centers for Disease Control and Prevention; 2017 [cited 2019 Jul 9]. Available from: https://www.cdc.gov/flu/fluvaxview/full-partial-vaccination-children-2017.htm.


Článek vyšel v časopise

PLOS Medicine


2020 Číslo 8
Nejčtenější tento týden
Nejčtenější v tomto čísle
Kurzy

Zvyšte si kvalifikaci online z pohodlí domova

Aktuální možnosti diagnostiky a léčby litiáz
nový kurz
Autoři: MUDr. Tomáš Ürge, PhD.

Střevní příprava před kolonoskopií
Autoři: MUDr. Klára Kmochová, Ph.D.

Závislosti moderní doby – digitální závislosti a hypnotika
Autoři: MUDr. Vladimír Kmoch

Aktuální možnosti diagnostiky a léčby AML a MDS nízkého rizika
Autoři: MUDr. Natália Podstavková

Jak diagnostikovat a efektivně léčit CHOPN v roce 2024
Autoři: doc. MUDr. Vladimír Koblížek, Ph.D.

Všechny kurzy
Přihlášení
Zapomenuté heslo

Zadejte e-mailovou adresu, se kterou jste vytvářel(a) účet, budou Vám na ni zaslány informace k nastavení nového hesla.

Přihlášení

Nemáte účet?  Registrujte se

#ADS_BOTTOM_SCRIPTS#