Table 1. Challenges, adaptations, and lessons learned in response to the data needs of Ontario’s COVID-19 pandemic response by ICES department.

Department	Examples of Challenges	Adaptations	Lessons Learned
All departments	Public sector research institute with limited staff resources, who were all adjusting to working from home and managing other responsibilities.	Reallocated human resources from low priority, non-COVID-19-related work to COVID-19-related tasks. Worked long hours and on weekends to accommodate timely data and analytic requests	Engaged, dedicated, and committed human resources are imperative to organization’s success
Communications	Weekly analyses and data updates posted to ICES website via COVID-19 Dashboard, often with novel and actionable findings, garnered significant number of media requests and social media engagement	Prioritized media requests and accommodated availability of ICES scientists Social media conversations responded to within 24 hours	Need for active engagement in discussions with ICES scientists on interpretation and messaging of results, and collaboration with research teams to present lay language summaries and other data visualizations Response to social media is vital to engagement with the public, but not all comments needed to be addressed
Data Quality & Information Management	Frequent (initially daily and cumulative) data feeds of new SARS-CoV-2 test result data in text-based format contained rich information but data format was novel and not research-ready Existing clinical and administrative data feeds, which were historically updated bimonthly or quarterly, were not ideal for real-time analyses	Prioritized resources to accommodate data processing (e.g., linkage, standardization, data quality assessments) for frequent data feeds Leveraged new, innovative methods (e.g, text-mining, address matching) to enhance use of COVID-19 related data holdings Expedited posting data (new and historical feeds) in analytical environment for research teams Shared developed tools under open access license for external stakeholders to achieve consistent data interpretations and to circumvent the need to disclose cleaned data to partner organizations	Invest in skill building in other programming language and data cleaning methods to prepare novel datasets and data needs Engage with data providers early to establish processes for data transfers (and contingency plans for delayed transfers) and notification for changes in data structure or contents Utilizing previously established relationships with data providers and content experts allows for immediate cooperation when problem-solving data issues
Information Technology	Existing data analytic environment and infrastructure were not optimal for data processing, computing, and storage of large volumes of data frequently. File format for SARS-CoV-2 testing data (SAS datasets) not efficient for tools used to analyze data (e.g., Python use to clean text-based results)	Implemented enhancements to analytic environments, including the high-performance computing cluster, to expand data storage capacity and improve performance Modified scheduled maintenance to accommodate COVID-19 reporting schedule	Invest in data processing tools (e.g., automation) and skill sets to reduce dependency of manual processes Understanding of the research needs and timelines (e.g., volume of new data and frequency of reporting) by having a more efficient work intake process would help assess data infrastructure needs (e.g., storage, analytic tools)
Privacy and Legal Office and Cybersecurity	Large number of COVID-19-related research and/or analytic projects proposed that aimed to address timely and relevant questions at the same time as other non-COVID-19-related projects requiring privacy support Large number of COVID-19-related requests for data acquisition and data sharing Process to acquire and collect new data requires diligent review before data transfer and utilization	Privacy team enabled prioritization of privacy impact assessments for COVID-19-related projects, data acquisition and data sharing agreements Division of labour amongst expanded team of privacy impact assessment reviewers enabled prioritization of certain requests Policies, agreements, and safeguards were revised to allow scientists and staff to work with ICES data securely while remote	More staff trained and focused on privacy, enables greater capacity to take on work, support shorter timelines and prioritization, while maintaining diligence, integrity, and trust Ongoing and frequent communication with the data partner disclosing data to ICES allowed for understanding of legalities earlier in the data acquisition process
Public Engagement & Knowledge Translation	Need for rapid, public-friendly and accessible materials on COVID-19 data, analytics, and information for public consumption	Prioritized public engagement activities and designed plain language online resources to increase accessibility, understanding, and awareness of COVID-19 related research and ICES COVID-19 Dashboard Convened Public Advisory Council subcommittees to provide rapid turn-around input on certain COVID-19 reports (e.g., in-depth report on SARS-CoV-2 testing among immigrants, refugees, and newcomers to Ontario) Shifted to virtual settings to conduct regular Public Advisory Council meetings and working groups	Input from the Public Advisory Council remains vital for ensuring that the information that ICES puts out on its web-based and social platforms is public-friendly and easily accessible Leveraging members of the Public Advisory Council for nimble input on time sensitive materials for which public input was critical to framing and interpretation of results
Research and Analysis/Data and Analytic Services	Urgency to use newly acquired COVID-19 datasets, which had unfamiliar data structures, contents, and limitations Some Knowledge Users were not previously acquainted to health administrative data and its value for decision making Frequent reporting and tight timelines conflicted with other research project commitments	Created analytical datasets, macros, & definitions to be used across COVID-19 reports, and shared among research teams Initiated working groups with data providers and other organizations to understand new datasets and share knowledge Prioritized resources to accommodate rapid increase in COVID-19 projects	Establishing data working groups within ICES and with other organizations (including teams which ICES has collaborated successfully in the past) to share knowledge about datasets, utility, and limitations is beneficial to ensure consistency concepts and interpretation, and to avoid duplication of efforts Building redundancy (i.e., multiple staff with same knowledge) on dataset contents, analyses, and key deliverables is imperative to projects with unpredictable timelines
Science Office	Competing priorities and timelines between existing investigator-led research projects and work that contributed to the pandemic response Multiple COVID-19 projects proposed by ICES Scientists, often with overlapping objectives	Established committee of staff and scientists to prioritize COVID-19 related initiatives and research projects. Communicated openly with ICES investigators regarding potential delays in pre-existing work Led discussions with Knowledge Users about analytical plans and reports, conceptualized data visualizations and interpreted results for ICES COVID-19 Dashboard. Accommodated media requests to discuss about results presented on the ICES COVID-19 Dashboard, often with short notice.	Prioritization of projects based on objectives and relevance is needed when human resource capacity is limited Fostering collaboration between project teams with similar research interests and complementary knowledge/skills strengthens quality of research impact
Strategic Partnerships	Urgent need to acquire new datasets (often with new data partners) with timely and relevant information to inform pandemic response	Negotiated with existing partners and established new partnerships expeditiously	Building and maintaining strong partnerships with all stakeholders and data custodians enables timely acquisition of data when urgently needed