Novel data and analyses have played an important role in informing the public health response to the COVID-19 pandemic. Existing surveillance systems were scaled up, and in some instances, new systems developed to meet the challenges posed by the magnitude of the pandemic. Here, we describe the routine and novel data that were used to address urgent
public health questions during the pandemic, underscore challenges in sustainability and equity in data generation, and highlight key lessons learnt for designing scalable data collection systems to support decision-making during a public health crisis.

As countries emerge from the acute phase of the pandemic, COVID-19 surveillance systems are being scaled down. However, as SARS-CoV-2 resurgence remains a threat to global health security, it is important that a minimal cost-effective system remains active that can be rapidly scaled up if necessary. We propose that a retrospective evaluation to identify the cost-
benefit profile of the various data streams collected during the pandemic should be on the scientific research agenda.