Implementing a First Nation data-sovereign and agile modelling platform for pandemic management: lessons from Manitoba.

Authors

Wanda Phillips-Beck, Josée G Lavoie, Leona Star, Nathan Nickel, Razvan Romanescu

Published in

International journal of circumpolar health. Volume 85. Issue 1. Pages 2749170. Dec 31, 2026. Epub Oct 22, 2026.

Abstract

This paper describes lessons learned from a partnership between the First Nations Health and Social Secretariat of Manitoba (FNHSSM) and researchers at the University of Manitoba to develop a community-led COVID-19 modelling platform. The envisioned tool would allow First Nations leaders to input local data and generate outputs to support decision-making using a stochastic, age-stratified agent-based model of COVID-19 transmission. Although the platform was not fully operationalized during the project, several important lessons emerged. First, the COVID-19 pandemic placed significant demands on human resources, making such an ambitious initiative difficult to implement during an active public health emergency. Second, the project required coordination among multiple teams with distinct expertise, including model developers, dashboard designers, and FNHSSM information technology staff responsible for infrastructure planning. Competing pandemic-related priorities frequently delayed collaboration and implementation. Third, access to administrative data through the Manitoba Centre for Health Policy involved a six-month reporting lag, limiting the availability of timely information needed for emergency response and decision-making. These challenges highlight structural barriers to data-driven pandemic management in First Nations communities. We recommend: (1) providing First Nations organizations and communities with ongoing access to their own administrative data for service delivery, planning, and emergency management; and (2) establishing First Nations-led data centres with sustainable infrastructure and core funding to support data sovereignty, agile reporting, and future public health response efforts.

PMID:
42912129
Bibliographic data and abstract were imported from PubMed on 24 Oct 2026.

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