We would like to thank Quaglietta et al. [1] for their interest in our study and making their data available to allow comparison with our article [2] on the impact of the coronavirus disease 2019 (COVID-19) pandemic on pediatric appendicitis.

We welcome new Canadian data on the impact of the pandemic on pediatric appendicitis. We agree with the authors that our article could not reflect the experience of all hospitals and provinces in Canada. The comparison of both articles [1, 2] highlights the fact that multiple factors can impact the risk of complications among children with appendicitis. Beyond common national policies, different provincial and local influences may affect health outcomes. These include public health decisions with regards to the COVID-19 pandemic that were heterogeneous, general organization of pediatric surgical care both in general as well as changes brought about by the pandemic, volume of both emergency department and surgeries at each center, and local organization and patterns of care. Populations’ knowledge and attitudes toward the pandemic may have been different between the different provinces. As mentioned in the methods, our study population was limited to two large pediatric hospitals in Montreal, Québec.

The authors of the commentary also mentioned that lengths of stay were not listed in our manuscript. Our mean length of stay in the pre-pandemic period was 3.46 days [95% confidence interval (CI) = 3.09–3.83], with an adjusted difference in the pandemic period of 0.88 days (95% CI = − 1.65 to − 0.12). This length of stay is slightly longer in the pre-pandemic period than in the results reported by Quaglietta et al. of 2.0 days (median), but the length of stay during the pandemic is of similar magnitude.

In sum, we agree with Quaglietta et al. that provincial and local differences in several aspects of both pediatric surgical care and the COVID-19 pandemic response make it perilous to generalize about a country as large and varied as Canada when using limited local or even provincial datasets.