Building Capacity for COVID-19 Surveillance: A Statistics Course for Health Officials in Seven Low- and Middle-Income Countries

AbstractDuring the COVID-19 pandemic, a group of health program implementors and research analysts across seven low- and middle-income countries (LMICs) alongside Boston-based collaborators convened to implement data-driven approaches for public health response. An intensive statistics and data scie...

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Bibliographic Details
Main Authors: Isabel R. Fulcher, Donald Fejfar, Nichole Kulikowski, Jean-Claude Mugunga, Michael Law, Bethany Hedt-Gauthier
Format: Article
Language:English
Published: Taylor & Francis Group 2024-03-01
Series:Journal of Statistics and Data Science Education
Subjects:
Online Access:https://www.tandfonline.com/doi/10.1080/26939169.2024.2315936
Description
Summary:AbstractDuring the COVID-19 pandemic, a group of health program implementors and research analysts across seven low- and middle-income countries (LMICs) alongside Boston-based collaborators convened to implement data-driven approaches for public health response. An intensive statistics and data science training short course was developed to ensure that in-country researchers could implement the necessary statistical methods for COVID-19 surveillance. The main goal of the course was to enable interpretation of findings from time series analyses and flag potential data issues. This manuscript summarizes our experience teaching this course, including a detailed course overview, participant feedback, and thoughts on how targeted, online courses can be used to support statistical capacity building in LMICs.
ISSN:2693-9169