/gep_health_facilities

An exploratory geo-spatial approach of estimating electricity requirements for health facilities

Primary LanguageJupyter NotebookMIT LicenseMIT

gep_health_facilities

An exploratory geo-spatial approach of estimating electricity requirements for health facilities

Rationale

Globally, it is estimated that ~789 million people live without access to electricity. This is a critical service gap that affects socio-economic development and human well-being, especially in poor, rural populations in least developed areas. At the same time, COVID-19 has brought into sharp focus the importance of electricity in the health sector. Access to electricity, in health clinics and posts, keeps people connected, allows for information management, the refrigeration of medicines and other services to protect vulnerable populations. Therefore, the lack of reliable power is undermining the quality of health care for millions of people. This creates an urgent need to "energize" health facilities so that there is a timely response to the COVID-19 crisis.

This notebook serves as an exploratory geo-spatial approach of estimating electricity requirements for health facilities, in areas where detailed data of this kind is scarce. It leverages existing open access datasets (and models) in order to provide a high level picture of annual electricity requirements in those facilities and later on indicate how these can be met as part of a least-cost electrification and/or prioritization plan. The sample input data focus on the district of Mecanhelas in Mozambique. However, the code can be scaled up at national or even regional level.

Content

  • HF_demand_estimation.ipynb contains the core code
  • Testing_Sample directory contains sample input data for testing including:
    • mecanhelas_admin.gpkg
    • mec_health_index.gpkg
    • mecanhelas_clusters.gpkg
  • maps directory contains sample output maps
  • requirements.txt dependencies info for setting up package requirements

Setting up the environment & running the model

Install from GitHub

Download repository directly or clone it to you designated local directory using:

git clone https://github.com/akorkovelos/gep_health_facilities.git

Requirements

The notebook has been developed in Python 3. We recommend installing Anaconda's free distribution as suited for your operating system.

Once installed, open anaconda prompt and move to your local "gep_health_facilities" directory using:

> cd ..\gep_health_facilities

In order to be able to run the notebook you should install all necessary packages. "requirements.txt" contains all of these and can be easily set up by creating a new virtual environment using:

pip install requirements.txt

Once completed, you can now move to the directory and start a "jupyter notebook" session by simply typing:

..\gep_health_facilities> jupyter notebook 

Credits

Conceptualization & Methodological review : Alexandros Korkovelos
Code development Alexandros Korkovelos
Review, Updates, Modifications: Alexandros Korkovelos
Supervision, Review and Advisory support: Benjamin P. Stewart, Ashish Shrestha, Rhonda Lenai Jordan
Funding: The World Bank