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1620. Effectiveness of the 2016 California Policy Eliminating Non-Medical Exemptions on Vaccine Coverage: A Synthetic Control Analysis

BACKGROUND: Vaccine hesitancy in low vaccine coverage “hot spots” has led to recent outbreaks of vaccine-preventable diseases across the United States. State policies to improve vaccine coverage by restricting non-medical (personal belief) exemptions are heavily debated and their effectiveness is un...

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Detalles Bibliográficos
Autores principales: Nyathi, Sindiso, Karpel, Hannah, Sainani, Kristin L, Maldonado, Yvonne, Hotez, Peter J, Bendavid, Eran, Lo, Nathan C
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6810639/
http://dx.doi.org/10.1093/ofid/ofz360.1484
Descripción
Sumario:BACKGROUND: Vaccine hesitancy in low vaccine coverage “hot spots” has led to recent outbreaks of vaccine-preventable diseases across the United States. State policies to improve vaccine coverage by restricting non-medical (personal belief) exemptions are heavily debated and their effectiveness is unclear due to limited rigorous policy analysis. In 2016, a California policy (SB 277) eliminated non-medical exemptions from kindergarten requirements. To address the ongoing debate on such policies, we performed a quasi-experimental, controlled analysis of the policy’s impact on vaccine and exemption outcomes. METHODS: We used state vaccine coverage and exemption data (2011–2017) from the CDC and health data from public sources. We prespecified a primary outcome of MMR coverage (%) and secondary outcomes of medical and non-medical exemptions (%). We included covariates related to socioeconomic and health measures (e.g., insurance, well child visits) and pre-2016 mean coverage. Using the synthetic control method, with 2016 as the treatment year and a 2-year post-policy period, we constructed a “control” California, from a weighted sum of states. We used permutation testing to repeat the process for each of the other states and their unique synthetic control, to determine whether there was a meaningful difference in California (i.e., a change in California’s coverage relative to its control in the top 5th percentile of states). We tested the model’s sensitivity to various analytical assumptions. RESULTS: Of 43 control states, synthetic California was predominantly comprised of Idaho, Mississippi, and Arkansas, and had a good pre-policy match on outcomes. MMR coverage in California increased by 3.2% relative to synthetic California in the post period (Top 1 of 44 states, Figure 1). Medical exemptions increased by 0.4%, while non-medical exemptions decreased by 2.2% in the post-period (Top 1 of 43 states). The model was robust to changes in covariates and control states. CONCLUSION: The policy resulted in a meaningful increase in MMR coverage and reduction in non-medical exemptions. We measured a modest increase in medical exemptions, but this was offset by the larger reduction in non-medical exemptions. State policies removing non-medical exemptions can be effective in increasing vaccination coverage. [Image: see text] DISCLOSURES: All authors: No reported disclosures.