Johns Hopkins University

$18,000,000.00 CAD

≈ $0.43 for every person in Canada ≈ 230 Canadians' average pay for a year
Department
Global Affairs Canada
Program
International Development Assistance Program
Recipient country
United States
Fiscal year
2015-2016
Agreement period
March 30, 2016 – June 30, 2023
Reference
dfatd-maecd:GC-2016-Q4-0102

Published purpose

This project aims to develop, implement and refine tools and approaches to strengthen country monitoring and reporting in MNCH and nutrition. The purpose of the Real Accountability: Data Analysis for Results (RADAR) project is for the Institute for International Programs of Johns Hopkins University to work with Canadian institutions and organizations, in-country evaluation partners, governments and development partners in a subset of countries where Canada has maternal, newborn and child health (MNCH) programming. Project activities include: (1) support CAN-MNCH in the training of a cadre of Canadian technical experts that are available to assist in implementing the MNCH results tools in DFATD programs with MNCH programming; (2) support the design of an external, Canadian-based, data repository to ensure data quality, comparability and availability in order to generate regular results reports; (3) assist in the implementation of these tools in a select number of Canada’s MNCH countries in order to validate results, refine the methodologies and ensure proper implementation. The ultimate beneficiaries for this project are mothers and children, as this initiative will develop tools to assess the quality of care provided to mothers and children, in the areas of nutrition and newborn health programs.

In plain English AI-generated

This project supports Johns Hopkins University in developing tools and approaches to strengthen monitoring and reporting for maternal, newborn, and child health and nutrition programs in select countries where Canada provides aid.

Category: Foreign Aid Development Primarily funds activity outside Canada

Based on the published description. See how AI categorization works — the linked official record is authoritative.

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View official source record Imported October 12, 2026 from open.canada.ca Grants & Contributions