Last Updated: 29/07/2024

A machine-learning ETL extension to DHIS2

Objectives

To build an extract, transform and load (ETL) plugin so that diverse types of data on disease incidence, spread, and interventions, recorded with different methods can be easily uploaded into the District Health Information Software version 2 (DHIS2) open-source platform, to better inform disease elimination efforts.

Principal Institution

TerraFrame, United States

Principal Investigators / Focal Persons

Nathan McEachen

Rationale and Abstract

Nathan McEachen of TerraFrame Inc. in the U.S. will build an extract, transform and load (ETL) plugin so that diverse types of data on disease incidence, spread, and interventions, recorded with different methods can be easily uploaded into the District Health Information Software version 2 (DHIS2) open-source platform, to better inform disease elimination efforts. The DHIS2 is widely used particularly across sub-Saharan Africa to report, analyze and distribute disease-relevant information. However, data collected using different software or in different formats cannot easily be imported despite their potential significance for disease elimination. In cooperation with the Zambia National Malaria Control Centre (NMCC) and their DHIS2-expert in-country partner organization they will identify user requirements for the plugin, such as the systems being used and the nature of the incompatibilities, and test it with NMCCs in other countries.

Date

Nov 2016 — May 2019

Total Project Funding

$100,000

Funding Details
Gates Foundation (GF), United States

Grand Challenges Explorations. Design New Analytics Approaches for Malaria Elimination (Round 17)
Grant ID: INV-010040
Project Site

United States
Zambia

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