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Forecasting high-priority infectious disease surveillance regions: A socioeconomic model

机译:预测高优先级传染病监测区域:一种社会经济模型

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Background. Few researchers have assessed the relationships between socioeconomic inequality and infectious disease outbreaks at the population level globally. We use a socioeconomic model to forecast national annual rates of infectious disease outbreaks.Methods. We constructed a multivariate mixed-effects Poisson model of the number of times a given country was the origin of an outbreak in a given year. The dataset included 389 outbreaks of international concern reported in the World Health Organization's Disease Outbreak News from 1996 to 2008. The initial full model included 9 socioeconomic variables related to education, poverty, population health, urbanization, health infrastructure, gender equality, communication, transportation, and democracy, and 1 composite index. Population, latitude, and elevation were included as potential confounders. The initial model was pared down to a final model by a backwards elimination procedure. The dependent and independent variables were lagged by 2 years to allow for forecasting future rates.Results. Among the socioeconomic variables tested, the final model included child measles immunization rate and telephone line density. The Democratic Republic of Congo, China, and Brazil were predicted to be at the highest risk for outbreaks in 2010, and Colombia and Indonesia were predicted to have the highest percentage of increase in their risk compared to their average over 1996-2008. Conclusions. Understanding socioeconomic factors could help improve the understanding of outbreak risk. The inclusion of the measles immunization variable suggests that there is a fundamental basis in ensuring adequate public health capacity. Increased vigilance and expanding public health capacity should be prioritized in the projected high-risk regions. ? 2012 The Author 2012. Published by Oxford University Press on behalf of the Infectious Diseases Society of America. All rights reserved. For Permissions, please e-mail: journals.permissions@oup. com.
机译:背景。几乎没有研究者评估了全球人口水平上社会经济不平等与传染病暴发之间的关系。我们使用社会经济模型来预测全国每年的传染病暴发率。我们构建了一个多元混合效应Poisson模型,该模型描述了特定国家/地区在特定年份爆发疾病的次数。该数据集包括1996年至2008年间在世界卫生组织的疾病暴发新闻中报道的389起国际关注的暴发。最初的完整模型包括9个与教育,贫困,人口健康,城市化,卫生基础设施,性别平等,通讯,交通有关的社会经济变量,民主和1个综合指数。人口,纬度和海拔被视为潜在的混杂因素。通过向后淘汰程序将初始模型缩减为最终模型。因变量和自变量滞后2年,以便预测未来利率。在测试的社会经济变量中,最终模型包括儿童麻疹免疫率和电话线密度。预计刚果民主共和国,中国和巴西在2010年的暴发风险最高,与1996-2008年的平均水平相比,哥伦比亚和印度尼西亚的风险增高百分比预计最高。结论了解社会经济因素可能有助于增进对爆发风险的了解。麻疹免疫变量的加入表明,确保充分的公共卫生能力具有根本的基础。在预计的高风险地区,应提高警惕并扩大公共卫生能力。 ? 2012作者2012。由牛津大学出版社代表美国传染病学会出版。版权所有。有关许可,请发送电子邮件至:journals.permissions@oup。 com。

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