School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, 27 St Andrews Road, Parktown, Johannesburg 2193, South Africa.
Bull World Health Organ. 2013 Mar 1;91(3):174-83. doi: 10.2471/BLT.12.110726. Epub 2013 Jan 11.
To develop a model for identifying areas at high risk for sporadic measles outbreaks based on an analysis of factors associated with a national outbreak in South Africa between 2009 and 2011.
Data on cases occurring before and during the national outbreak were obtained from the South African measles surveillance programme, and data on measles immunization and population size, from the District Health Information System. A Bayesian hierarchical Poisson model was used to investigate the association between the risk of measles in infants in a district and first-dose vaccination coverage, population density, background prevalence of human immunodeficiency virus (HIV) infection and expected failure of seroconversion. Model projections were used to identify emerging high-risk areas in 2012.
A clear spatial pattern of high-risk areas was noted, with many interconnected (i.e. neighbouring) areas. An increased risk of measles outbreak was significantly associated with both the preceding build-up of a susceptible population and population density. The risk was also elevated when more than 20% of infants in a populous area had missed a first vaccine dose. The model was able to identify areas at high risk of experiencing a measles outbreak in 2012 and where additional preventive measures could be undertaken.
The South African measles outbreak was associated with the build-up of a susceptible population (owing to poor vaccine coverage), high prevalence of HIV infection and high population density. The predictive model developed could be applied to other settings susceptible to sporadic outbreaks of measles and other vaccine-preventable diseases.
基于对南非 2009 年至 2011 年全国暴发麻疹的相关因素分析，建立一种用于识别高风险散发性麻疹暴发地区的模型。
从南非麻疹监测计划中获取暴发前和暴发期间发生的病例数据，从地区卫生信息系统中获取麻疹免疫接种和人口规模数据。采用贝叶斯分层泊松模型调查一个地区婴儿麻疹发病风险与首剂疫苗接种覆盖率、人口密度、人类免疫缺陷病毒（HIV）感染背景流行率和预期血清转化率失败之间的关联。利用模型预测结果，于 2012 年识别出新出现的高风险地区。
高风险地区呈现出明显的空间分布模式，存在许多相互关联（即相邻）的地区。麻疹暴发风险显著增加与易感人群的积累和人口密度有关。在人口较多的地区，如果超过 20%的婴儿错过首剂疫苗，那么麻疹暴发的风险也会升高。该模型能够识别出 2012 年麻疹暴发风险较高的地区，并在这些地区采取额外的预防措施。
南非麻疹暴发与易感人群的积累（疫苗接种率低）、HIV 感染率高和人口密度高有关。所开发的预测模型可应用于其他易发生散发性麻疹和其他疫苗可预防疾病暴发的地区。
