County-level assessment of United States kindergarten vaccination rates for measles mumps rubella (MMR) for the 2014–2015 school year

Kluberg, Sheryl A.; McGinnis, Denise P.; Hswen, Yulin; Majumder, Maimuna S.; Santillana, Mauricio; Brownstein, John S.

doi:10.1016/j.vaccine.2017.09.080

Cited by 7 publications

(6 citation statements)

References 21 publications

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“…Spatial heterogeneity in vaccination can enable outbreaks, as clusters of unvaccinated individuals can cause resurgence despite high overall vaccination rates (e.g., in the case of measles [14,15,16,17] and pertussis [18,19]), despite high vaccination coverage at the national level. Given the importance of spatial heterogeneity, tracking vaccination at a fine spatial scale is also critical as vaccine uptake can vary widely within and between large geographical areas (e.g., in the case of influenza [20]) and large-scale aggregation of vaccination metrics can mask local vulnerabilities [14,21,22,23].…”

Section: Introductionmentioning

confidence: 99%

Characterizing the spatiotemporal heterogeneity of the COVID-19 vaccination landscape

Tiu

Susswein

Merritt

et al. 2021

Preprint

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It is critical that we maximize vaccination coverage across the United States so that SARS-CoV-2 transmission can be suppressed, and we can sustain the recent reopening of the nation. Maximizing vaccination requires that we track vaccination patterns to measure the progress of the vaccination campaign and target locations that may be undervaccinated. To improve efforts to track and characterize COVID-19 vaccination progress in the United States, we integrate CDC and state-provided vaccination data, identifying and rectifying discrepancies between these data sources. We find that COVID-19 vaccination coverage in the US exhibits significant spatial heterogeneity at the county level and statistically identify spatial clusters of undervaccination, all with foci in the southern US. Vaccination progress at the county level is also variable; many counties stalled in vaccination into June 2021 and few recovered by July, with transmission of the Delta variant rapidly rising. Using a comparison with a mechanistic growth model fitted to our integrated data, we classify vaccination dynamics across time at the county scale. Our findings underline the importance of curating accurate, fine-scale vaccination data and the continued need for widespread vaccination in the US, especially in the wake of the highly transmissible Delta variant.

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Section: Introductionmentioning

confidence: 99%

Characterizing the spatiotemporal heterogeneity of the COVID-19 vaccination landscape

Tiu

Susswein

Merritt

et al. 2021

Preprint

View full text Add to dashboard Cite

show abstract

“…For other countries, the number of postcode areas may be larger than the number of schools, which would simplify analyses, or alternative variables such as public and private schools may be more useful. Ideally, school vaccination coverage data are directly available: for instance, in the United States these are available at school level for some states [23], but often grouped by county for analysis [26]; also in Germany they are collected at school entry and then grouped by district [24]. For describing connections between schools, feeder data may be supplemented (or replaced) by individual level household data to build larger networks of schools and identify communities at risk.…”

Section: Discussionmentioning

confidence: 99%

“…There is also a more diffuse group of people who fear side-effects and perceive the diseases as mild [22], but there is not one school identity linked to that group. 4 Vaccination coverages by school are routinely collected in various countries, including Germany and the United States [17,18,[23][24][25], but reporting is frequently done by averaging school coverages locally, by county or district [24,26]. Whereas this is very helpful for signaling which regions are at risk of infection, an average or even a local average does not fully capture the variability between schools, which is essential to fully understand the risk of outbreaks [25].…”

Section: Introductionmentioning

confidence: 99%

Social clustering of unvaccinated children: measles-mumps-rubella vaccination coverage in schools in the Netherlands

Klinkenberg

Hoek

Veldhuijzen

et al. 2022

Preprint

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BackgroundFor the measles-mumps-rubella (MMR) vaccine, the WHO-recommended coverage for herd protection is 95% for measles and 80% for rubella and mumps. However, a national vaccine coverage does not reflect social clustering of unvaccinated children, e.g. in schools of Orthodox Protestant or Anthroposophic identity in The Netherlands. To fully characterise this clustering, we estimated one-dose MMR vaccination coverages at all schools in the Netherlands.MethodsBy combining postcode catchment areas of schools and school feeder data, each child in the Netherlands was characterised by residential postcode, primary and secondary school (referred to as school career). Postcode-level vaccination data were used to estimate vaccination coverages per school career. These were translated to coverages per school, stratified by school identity.ResultsMost schools had vaccine coverages over 99%, but major exceptions were Orthodox Protestant schools (63% in primary and 58% in secondary schools) and Anthroposophic schools (67% and 78%).ConclusionsSchool-level vaccine coverage estimates reveal strong clustering of unvaccinated children. The school feeder data reveal strongly connected Orthodox Protestant and Anthroposophic communities, but separated from one another. This suggests that even at a national one-dose MMR coverage of 97.5%, thousands of children per cohort are not protected by herd immunity.

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“…For other countries, the number of postcode areas may be larger than the number of schools, which would simplify analyses, or alternative variables such as public and private schools may be more useful. Ideally, school vaccination coverage data are directly available: for instance, in the United States these are available at school level for some states [ 24 ], but often grouped by county for analysis [ 27 ]; also in Germany they are collected at school entry and then grouped by district [ 25 ]. For describing connections between schools, feeder data may be supplemented (or replaced) by individual level household data to build larger networks of schools and identify communities at risk.…”

Section: Discussionmentioning

confidence: 99%

“…Vaccination coverages by school are routinely collected in various countries, including Germany and the United States [17,18,[24][25][26], but reporting is frequently done by averaging school coverages locally, by county or district [25,27]. Although this is very helpful for signalling which regions are at risk of infection, an average or even a local average does not fully capture the variability between schools, which is essential to fully understand the risk of outbreaks [26].…”

Section: Introductionmentioning

confidence: 99%

Social clustering of unvaccinated children in schools in the Netherlands

et al. 2022

View full text Add to dashboard Cite

For the measles-mumps-rubella (MMR) vaccine, the WHO-recommended coverage for herd protection is 95% for measles and 80% for rubella and mumps. However, a national vaccine coverage does not reflect social clustering of unvaccinated children, e.g. in schools of Orthodox Protestant or Anthroposophic identity in The Netherlands. To fully characterise this clustering, we estimated onedose MMR vaccination coverages at all schools in the Netherlands. By combining postcode catchment areas of schools and school feeder data, each child in the Netherlands was characterised by residential postcode, primary and secondary school (referred to as school career). Postcode-level vaccination data were used to estimate vaccination coverages per school career. These were translated to coverages per school, stratified by school identity. Most schools had vaccine coverages over 99%, but major exceptions were Orthodox Protestant schools (63% in primary and 58% in secondary schools) and Anthroposophic schools (67% and 78%). School-level vaccine coverage estimates reveal strong clustering of unvaccinated children. The school feeder data reveal strongly connected Orthodox Protestant and Anthroposophic communities, but separated from one another. This suggests that even at a national one-dose MMR coverage of 97.5%, thousands of children per cohort are not protected by herd immunity.

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County-level assessment of United States kindergarten vaccination rates for measles mumps rubella (MMR) for the 2014–2015 school year

Cited by 7 publications

References 21 publications

Characterizing the spatiotemporal heterogeneity of the COVID-19 vaccination landscape

Characterizing the spatiotemporal heterogeneity of the COVID-19 vaccination landscape

Social clustering of unvaccinated children: measles-mumps-rubella vaccination coverage in schools in the Netherlands

Social clustering of unvaccinated children in schools in the Netherlands

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