Post last updated: 20 Jun 2021


Every two weeks, our group provides COVID-19 infection report forecasts for the province of Ontario to the Ontario Modelling Consensus Table (MCT), a partner of the Ontario Science Advisory Table (SAT), which presents this information to the Health Coordination Table of the Ontario Ministry of Health.1 Other modelling groups also provide forecasts to the MCT. After reviewing all forecasts provided, the MCT provides consensus projections to the SAT.

Our forecasts are based on a compartmental epidemic model implemented in our publicly available McMasterPandemic R package, and involve statistical fits to Ontario’s latest infection report data.

Forecast overview

The forecasts presented here were made on 19 April 2021 and 9 May 2021.

The 19 April forecasts were submitted to the MCT for inclusion in the public briefing by the SAT on 29 April 2021.

Because of the delay between the moment of infection and when a case is reported, we cannot directly estimate the effects of changes that occur two weeks or less before the date of our forecasts. As a result, we were not able to fit the effects of the 8 April stay-at-home order in the 19 April forecasts. The best we can do in this case is consider scenarios for the effectiveness of changes (for example, interventions like stay-at-home orders). The scenarios considered for the 19 April forecasts are outlined below.

On 9 May, enough data had accumulated since the 8 April stay-at-home order for us to estimate its effect on transmission, and this estimate is included in that forecast.

We have updated, and will continue to update, this post in order to show the latest infection reports, but the forecasts themselves have not, and will not, be modified after the forecast date.

The most recent infection reports indicate which of the 19 April scenarios turned out to be closest to reality (and therefore suggest the degree to which public health measures, changes in behaviour, or vaccine uptake, have been effective). When multiple changes have occurred simultaneously (for example, closing schools and restricting travel), it is very difficult, if not impossible, to determine which changes had the greatest impact on disease transmission.

Forecast results

The following figures gives the infection report forecasts (curves), with 95% confidence intervals as bands around each forecast curve. Observed infection reports to which the model was fit are plotted with solid points, while observations after the fact are included as hollow points.