1. Data collection
This database focuses on four pivotal categories—i) Travel, ii) Physical distancing, iii) Closure/Opening, and iv) Public Information—applied across Quebec's 17 AR. The Travel encompasses interventions aimed at regulating the movement of individuals between geographic locations. The Physical distancing involves interventions intended to enforce physical distancing and minimize interpersonal interactions. The Closure/Opening includes a variety of interventions aimed at suspending or resuming operations in different sectors of activity. The Public Information includes, among other details, information related to the phases and alert level changes in Quebec, characterized by different colors (red, orange, yellow, and green). This category was used to identify the specific regions where interventions were implemented and, in some cases, to help determine when interventions might have started or ended. Since the first three categories (travel, physical distancing, and closure/opening) are related to public spaces and have the potential to impact mobility, mental health and even alcohol and cannabis consumption, they were used to construct the QCnPI-Index. These categories collectively included 58 interventions. This classification was essential to ascertain the duration of each implemented intervention, which was not always clear in the timeline.
It is important to note that this database does not cover all interventions, such as mandatory face mask-wearing, which may affect certain categories. Additionally, interventions implemented in specific administrative region sectors are sometimes considered region-wide if they significantly impact a sizable area or population.
2. Data Treatment
The collected data underwent meticulous organization to elucidate various facets of the interventions. In Table 1, we depict the interventions associated with each category. Travel includes the following interventions: travel restrictions, self-isolation protocols, and checkpoints. Similarly, Physical distancing was broken down into curfew, social gathering limitations, and telework protocols. Closure/Opening was segmented into Daycare, Education, Non-essential Services, and Recreation.
3. Data Coding
First, categories were divided by subcategories, and subcategories were further divided by interventions. Some interventions were even further divided into sub-interventions. Only one sub-intervention was divided into micro-sub interventions. All micro-sub interventions, sub-interventions, interventions, subcategories, and categories are identified in Table 1.
Both theoretical and mathematical approaches were deployed to construct the QCnPI-Index as well as its sub-indexes. With both approaches, Sub-interventions within interventions, interventions within subcategories, and subcategories within categories were assigned weights, with the highest value being 1. For instance, as shown in Eq. 1, travel includes three sub-categories self-isolation, checkpoint, and travel restriction with the devoted values 0.3, 0.1, and 0.6 that the total of them equal 1.
Travel = Self-isolation + Checkpoint + Travel Restriction Eq. 1
The absence of sub-interventions or interventions on specific dates were coded as 0. In theoretical approach, to determine the distribution of weights for categories, a consensus approach involving four researchers (JINM, AM, VNMG, CCMP) was applied.
The Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) was utilized to determine the weights of each category, mathematically [13]. In this method, m categories were evaluated by n sub-categories, and n sub-categories were evaluated by x interventions. Each category and sub-categories were assigned a score based on the values of its sub-categories and interventions, respectively. The values referenced in this method are those we determined earlier for interventions, sub-interventions, and sub-categories. This approach provides higher rankings to categories, which exhibit the highest similarity to the ideal solution.
In the context of the QCnPI index, a higher score signifies a greater level of implementation of non-pharmaceutical interventions by the government within a specific administrative region during a given time period. This means that more interventions were simultaneously in effect, reflecting a more comprehensive approach to mitigating the spread of COVID-19. Conversely, lower scores indicate a lower level of intervention implementation, with fewer measures in place during the same period, suggesting a less comprehensive approach.
4. Indices comparison
To assess differences between theoretical and mathematical approaches, a simple correlations analysis was applied [14], where a value of 0.9 or higher, or a value of -0.9 or lower, is considered a high correlation, indicating that both indices measure the same phenomenon almost equally.