Presenter: Allisyn Moran, USAID
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Background: Universal Health Care in the post-2015 era aims to achieve and maintain equity as high impact maternal and newborn health interventions are scaled up. A proposed target for the universal health care sub-goal for the SDGs is that, “By 2030, all populations, independent of household income, expenditure or wealth, place of residence or sex, have at a minimum 80% essential health services coverage.” This sub-goal will be measured with a set of tracer coverage indicators that will be disaggregated by wealth quintile, residence and sex at a minimum. Existing methods can be better used to measure and capture inequities in coverage.
Methodology: Apply existing methods and data to describe inequities in coverage of maternal and newborn health interventions by person, place and time. Gaps between coverage between the poorest and richest 20%, and between urban and rural populations will be calculated from Demographic and Health Surveys (DHS) and visualized using “Countdown”-type graphs and maps. Changes between DHS survey rounds in the gap in coverage between these populations will also be calculated and visualized.
Results: Substantial variations in coverage between rich and poor, between urban and rural residents, and over time within these populations are expected within and across low and middle income countries. Calculation of these inequities is possible with existing datasets, and visualization of inequities is feasible with common tools.
Conclusions: The Global Health community aims to achieve and maintain equity as high impact maternal and newborn health interventions are scaled up. This introductory presentation to the panel shows the value and feasibility of visualizing the distribution of inequities in coverage by person, place and time with existing assessment methods and technologies. Other presentations, sessions and panels at the conference that will introduce newer or novel methods of assessing equity will be highlighted.