Importation of SARS-CoV-2 following the“semaine de relâche”and Québec’s COVID-19 burden - a mathematical modeling study

• DOI: 10.1101/2020.07.20.20158451
• Publication Date: 2020-07-22T19:09:36Z
• Authors: A Godin; Y Xia; DL Buckeridge; S Mishra; D Douwes-Schultz; Y Shen; M Lavigne; M Drolet; AM Schmidt; M Brisson; M Maheu-Giroux
• Keywords: 03 medical and health sciences; 0305 other medical science; 3. Good health

AbstractBackgroundThe Canadian epidemics of COVID-19 exhibit distinct early trajectories, with Québec bearing a very high initial burden. Thesemaine de relâche, or March break, took place two weeks earlier in Québec as compared to the rest of Canada. This event may have played a role in the spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). We aimed to examine the role of case importation in the early transmission dynamics of SARS-CoV-2 in Québec.MethodsUsing detailed surveillance data, we developed and calibrated a deterministic SEIR-type compartmental model of SARS-CoV-2 transmission. We explored the impact of altering the number of imported cases on hospitalizations. Specifically, we investigated scenarios without case importation after March break, and as scenarios where cases were imported with the same frequency/timing as neighboring Ontario.ResultsA total of 1,544 and 1,150 returning travelers were laboratory-confirmed in Québec and Ontario, respectively (with symptoms onset before 2020-03-25). The cumulative number of hospitalizations could have been reduced by 55% (95%CrI: 51-59%) had no cases been imported after Québec’s March break. However, had Québec experienced Ontario’s number of imported cases, cumulative hospitalizations would have only been reduced by 12% (95%CrI: 8-16%).InterpretationOur results suggest that case importation played an important role in the early spread of COVID-19 in Québec. Yet, heavy importation of SARS-CoV-2 in early March could be insufficient to resolve interprovincial heterogeneities in cumulative hospitalisations. The importance of other factors-public health preparedness, responses, and capacity-should be investigated.