Portal InstitucionalUFPEL

01/10/2019 - 28/02/2022

Ciências da Saúde - Saúde Coletiva

In light of the agenda defined by the Sustainable Development Goals, improving data quality and availability is crucial to ensure countries are in the right direction towards reducing preventable maternal and newborn deaths. Assessing geographic inequalities is challenging since the main sources of information on low- and middle-income countries are not designed to be analyzed spatially. Recent improvements in computer processing power and the increased availability of ancillary data sources have contributed to the development of modeling approaches that aim to provide estimates at finer resolutions than provided by the administrative divisions commonly used in surveys. This project involves using these techniques of geospatial modeling to investigate geographic inequalities by generating high resolution estimates of health indicators. The estimates will be evaluated in two different scenarios: i) aligned with the most recent surveys, map the composite coverage index, a measure of universal health coverage based on essential reproductive, maternal and child health interventions, at second administrative level (e.g the equivalent to district or counties in different countries) and at pixel level (e.g 5 x 5km or 10x 10km); and ii) assess time trends using a geographic perspective to identify spatial patterns of increase in coverage of two vaccines since their introduction in Peru, in the early 2000s.