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

Lead Research Organisation: University of Southampton
Department Name: School of Social Sciences

Abstract

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 Guatemala is a predominantly rural and mountainous country, with an outdated census (last census was in 2002) that likely did not reach full coverage particularly for the indigenous population, who make half of the population.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.

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