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

Abstract

During 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.

Keywords

• Capacity building
• COVID-19
• Surveillance
• Time series modeling