Validating Child Immunization Coverage from Fine Resolution Mapping with Community-based Ancillary Data

使用基于社区的辅助数据通过精细分辨率绘图验证儿童免疫覆盖率

• 批准号: 2076814
• 金额: --
• 依托单位: University of Southampton
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2018
• 资助国家: 英国
• 起止时间: 2018 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2076814
• 关键词: Validating; Child; Immunization; Coverage; Fine

This research will use this data to predict the child immunization coverage at community level. These findings can be used to account for local validity of fine spatial resolution mapping. The research questions that the research will examine are: 1. What is the child immunization coverage estimated from the routine health information system by community?2. Does the health information system immunization coverage indicate that there are any differences between population groups (e.g. by location, household wealth)?3. What are the levels of child immunization within different communities are as estimated using fine resolution mapping, using techniques developed by WorldPop?4. How accurately does the fine resolution mapping child immunization estimates match with estimates from the routine health information system?5. How can these results be fed back into the fine resolution mapping in order to improve accuracy?Guatemala can be used as a case study to address these questions. Guatemala is a predominantly rural and mountainous country, with an outdated census (last census was in 2002) that likely did not reach full coverage particularly for the indigenous population, who make half of the population. As a response to the social exclusion of the indigenous population, a new model of primary health care was created and implemented in 2003. The new model of health care has focused on socio-cultural inclusion of indigenous population and the strengthening of four rural communities (Ajú and Oliva 2005). This new design, generates routine health data for decision making at local level and data is collected from community surveillance conducted by traditional indigenous midwives (who are also community leaders), community volunteers, local nurses and physicians (Feo and Tobar 2013). The routine health data production is now integrated with the Ministry of Health (MoH) information system and expansion of this primary health care approach to other communities is part of the current political agenda (MSPAS 2016). The findings of this research will increase our knowledge about alternatives for local planning and support the use of local routine information systems for decision making and allocate resources. The findings can prove valuable for other LMICs without a functioning and accurate national HIS through the validation of the validation of the fine resolution mapping estimates.

本研究将利用这些数据预测社区一级的儿童免疫覆盖率。这些发现可以用来解释精细空间分辨率制图的局部有效性。本研究将探讨的研究问题有：1。根据社区常规卫生信息系统估计的儿童免疫接种覆盖率是多少？2.卫生信息系统的免疫覆盖率是否表明人口群体之间存在任何差异（例如，按地点、家庭财富）？3.使用WorldPop开发的技术，使用精细分辨率绘图估计不同社区的儿童免疫水平如何？4.儿童免疫接种估计数的精细分辨率绘图与常规卫生信息系统的估计数相匹配的准确性如何？5.如何将这些结果反馈到精细分辨率映射中以提高精度？危地马拉可以作为解决这些问题的案例研究。危地马拉是一个以农村和山区为主的国家，人口普查已经过时（上一次人口普查是在2002年），可能没有达到全面覆盖，特别是对占人口一半的土著人口。为了解决土著居民受到社会排斥的问题，2003年建立并实施了一种新的初级保健模式。新的保健模式侧重于土著人口的社会文化融合和加强四个农村社区（Ajú和奥利瓦，2005年）。这一新设计生成了用于地方一级决策的常规健康数据，数据来自传统土著助产士（也是社区领袖）、社区志愿者、当地护士和医生进行的社区监测（Feo和Tobar，2013年）。常规健康数据的生产现已与卫生部（MoH）信息系统整合，将这种初级卫生保健方法扩展到其他社区是当前政治议程的一部分（MSPAS 2016）。这项研究的结果将增加我们对地方规划的替代方案的了解，并支持使用当地的日常信息系统进行决策和分配资源。通过验证精细分辨率绘图估计数的有效性，可以证明这些研究结果对没有有效和准确的国家HIS的其他中低收入国家很有价值。