Computational Epidemiology Group, Children's Hospital Informatics Program, Division of Emergency Medicine, Boston Children's Hospital, MA, USA.
Computational Epidemiology Group, Children's Hospital Informatics Program, Division of Emergency Medicine, Boston Children's Hospital, MA, USA; Department of Social and Behavioral Sciences, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
Vaccine. 2017 Nov 7;35(47):6444-6450. doi: 10.1016/j.vaccine.2017.09.080. Epub 2017 Oct 14.
United States kindergarten measles-mumps-rubella (MMR) vaccination rates are typically reported at the state level by the Centers for Disease Control and Prevention (CDC). The lack of local MMR data prevents identification of areas with low vaccination rates that would be vulnerable to the spread of disease. We collected county-level vaccination rates for the 2014-2015 school year with the objective of identifying these regions. We requested county-level kindergarten vaccination data from state health departments, and mapped these data to visualize geographic patterns in achievement of the 95% MMR vaccination target. We aggregated the county-level data to the state level for comparison against CDC state estimates. We also analyzed the relationship of MMR vaccination level with county-level and state-level poverty (using U.S. census data), using both a national mixed model with state as a random effect, and individual linear regression models by state. We received county vaccination data from 43 states. The median kindergarten MMR vaccination rate was 96.0% (IQR 89-98) across all counties, however, we estimated that 48.4% of the represented counties had vaccination rates below 95%. Our state estimates closely reflected CDC values. Nationally, every 10% increase in under-18 county poverty was associated with a 0.24% increase in MMR vaccination rates (95% CI: -0.07%; 0.54%), but the direction of this relationship varied by state. We found that county data can reveal vaccination trends that are unobservable from state-level data, but we also discovered that the current availability of county-level data is inadequate. Our findings can be used by state health departments to identify target areas for vaccination programs.
美国疾病控制与预防中心（CDC）通常按州报告幼儿园麻疹-腮腺炎-风疹（MMR）疫苗接种率。由于缺乏当地 MMR 数据，无法确定接种率低且易受疾病传播影响的地区。我们收集了 2014-2015 学年的县级疫苗接种率数据，目的是确定这些地区。我们向州卫生部门请求县级幼儿园疫苗接种数据，并将这些数据映射到地图上，以直观地展示实现 95%MMR 疫苗接种目标的地域模式。我们将县级数据汇总到州一级，以便与 CDC 的州估计值进行比较。我们还使用国家混合模型（州为随机效应）和各州的个体线性回归模型，分析了 MMR 疫苗接种水平与县和州贫困程度（使用美国人口普查数据）之间的关系。我们收到了 43 个州的县级疫苗接种数据。所有县的幼儿园 MMR 疫苗接种率中位数为 96.0%（IQR 89-98），但我们估计有 48.4%的县的疫苗接种率低于 95%。我们的州估计值与 CDC 的值非常接近。全国范围内，18 岁以下县贫困率每增加 10%，MMR 疫苗接种率就会增加 0.24%（95%CI：-0.07%；0.54%），但这种关系的方向因州而异。我们发现，县级数据可以揭示从州级数据中无法观察到的疫苗接种趋势，但我们也发现目前县级数据的可用性不足。州卫生部门可以利用这些发现来确定疫苗接种计划的目标地区。
