COVID-19 in Canada: Predictions for the future and control lessons from Asia

Cornelius Christian; Francis Christian

The number of those infected with COVID-19 has been published daily since January 25, 2020. Based on these data from government sources, we can calculate the exponential fit for these cases, as seen in Appendix, Figure 1 . The parameter values from this fit are shown in Table 1 . For policymakers to get a sense of how quickly the number of cases can grow across time, consider Appendix Figure 2 . As an illustrative example, consider the following. On March 20, 2020, there were 1,087 cases of SARS-CoV-2 in Canada. One week later, on March 27, 2020, the amount of cases is expected to more than quintuple to over 5,700, based on the exponential model. A week after that, on April 3, 2020, the number of cases is expected to reach 30,131, if current trends do not abate. These numbers will pose significant threats to ICU bed capacity, and the ability of hospitals to provide front-line medical staff with maximum personal protective equipment (PPE). Canada has ten provinces, four of which seem to be driving this exponential trend: British Columbia, Ontario, Alberta, and Quebec. As of March 20, 2020, 92 percent of Canada's COVID-19 cases come from these four provinces. These four provinces also contain 86 percent of Canada's population, and contain a number of other factors that make them more susceptible to disease transmission: densely populated urban areas, international and national travel hubs, and immigration. The same non-linear least squares method was applied to each individual province's number of COVID-19 case numbers, with results shown in Appendix Figure 3 (British Columbia), Figure 4 (Ontario), Figure 5 (Alberta), and Figure 6 (Quebec). In each of these provinces, an exponential fit appears to model the data well, strongly suggesting good prediction.