基于GIS的需求评估方法学研究医疗保健设施电力需求：乌干达案例研究

A GIS-based demand assessmentmethodology to estimate electricity Santiago Sinclair-Lecaros, Dimitrios Mentis, Eng. Sitra Mulepo C.S., Giacomo Falchetta, and Nicolò Stevanato ABSTRACT CONTENTS In Sub-Saharan Africa, more than 640 million people are served by healthcare facilities that either lack electricity access or have unreliable service.On average, 15 percent of the region’s health facilities lack any access toelectricity, and only 40 percent have reliable electricity1(WHO 2023). This hassubstantial implications for access to health services, including the cold chainfor vaccine, blood, and pharmaceutical storage. Additionally, the COVID-19crisis has underscored inequalities in access to electrified health care services,especially in remote rural areas and refugee settlements. Updated information Abstract. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . .22. Review of existing methodologies. . . . . .23. Proposed methodology. . . . . . . . . . . . . . . . .44. Data processing. . . . . . . . . . . . . . . . . . . . . . .115. Results. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .156. Ways forward. . . . . . . . . . . . . . . . . . . . . . . . . 227. Conclusions. . . . . . . . . . . . . . . . . . . . . . . . . . . 23Appendices . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24References. . . . . . . . . . . . . . . . . . . . . . . . . . . . . .33 Technical notes document the research or analyticalmethodology underpinning a publication, interactiveapplication, or tool. This technical note introduces a methodology to estimate electricity require-ment ranges in unserved and under-served health care facilities. It combinesa bottom-up approach to assessing the electricity requirements at the facilitylevel with a GIS-based analysis based on geographic information systems(GIS). The methodology is applied to a case study for existing facilities inUganda in close collaboration with the Ugandan Ministry of Health and the Suggested Citation:Sinclair-Lecaros, S., D.Mentis, E.S. Mulepo C.S., G. Falchetta, and N.Stevanato. 2023. “A GIS-based demand assessmentmethodology to estimate electricity requirementsfor health care facilities: a case study for Uganda.”Technical Note. Washington, DC: World 1. INTRODUCTION teams (VHTs) at the community level up to the national referralhospitals. In between these levels are health center II, healthcenter III, health center IV, general hospital, and regional refer-ral hospital (MoH 2016). The health center level (II, III, IV)has a high presence across the country, especially in remote ruralareas; thus, it is often the first point of access to health services. Access to reliable electricity enables health care facilities to pro-vide better services. Facilities can acquire and optimize electricalmedical equipment such as ventilators and vaccine refrigeratorsas well as access basic utility services, including lighting, water,sanitation, and hygiene services. However, one of the impedi-ments to electrifying health facilities is the data gap on theenergy requirements of such facilities, which is essential fordata-driven planning. In developing economies, health facilitydata related to electrification status, the reliability of supply, and Analysis outputs are integrated into Energy Access Explorer(EAE).6EAE is an online, open-source, and interactive geo-spatial platform that enables users to identify high-priorityareas where energy access can be expanded to achieve importantdevelopment outcomes. The tool synthesizes geospatial datarelated to energy demand and supply. Together, these data setscan help enable better, more integrated and inclusive energy- This technical note introduces a methodology to estimate plau-sible ranges of electricity requirements for health care facilities,especially unserved2and under-served3facilities. It combinesa bottom-up approach4to assessing the electricity require-ments at the facility level with an analysis based on geographicinformation systems (GIS) to assess the catchment populationof each facility. The estimated electricity requirement rangeper facility is the prospective demand to provide the requiredquality health services according to the health center level andits catchment population. The results are not intended to be anestimate of current electricity use. This methodology will providea data-driven, integrated approach to planning for the expansionof energy services in health care. Through more granular geo-spatial information and on-the-ground data on health facilities’ This technical note begins with the “Review of existing method-ologies,” which discusses GIS-based approaches for estimatinghealth facility electricity demand. The “Proposed methodol-ogy” section introduces the input and output data and thetools utilized throughout the different stages, and the “Dataprocessing” section outlines the various data proc