Socio-demographic data collection and equity in covid-19 in Toronto.

Toronto, Ontario, Canada is home to 8% of Canada's population and 11% of Canada's coronavirus cases [1]. There is significant income inequality; 25% of children and 20% of adults live in poverty [2]. 52% of the population is racialized. Income and race are risk factors for covid-19 so a pandemic strategy needs to be equitable to be effective [1]. To flatten the curve, we needed to focus on who is under the curve, but, at the start of the pandemic, little routine socio-demographic data was being collected by public health.

Reports of higher rates covid-19 in Black populations in the USA and UK and the rise of Black Lives Matter in spring 2020 led Toronto communities to question whether similar disparities were present locally. An open letter to the Government of Ontario calling for race based data collection [3], newspaper op-eds and multi-media interviews crystalized in the development of a backbone organization the Black Health Equity Working Group (BHEWG) which linked Black communities, academics, service providers and policy specialists.

BHEWG developed a strategy for the collection and use of socio-demographic data including race/ethnicity and income in which initial analysis of existing area-based data was used as way of highlighting the need for individual level data collection at testing, tracing and hospitalization. A longer-term goal was for socio-demographic data collection when people renew their Ontario Health Insurance Plan cards. The strategy included suggested tools for data collection and the development of a data governance framework (available on request). The aim was to use data to improve equity by changing practice in all parts of the system involved in pandemic: public health units, City of Toronto, the Province of Ontario and Federal Government.

Encouraging government analysts and policy organizations to use existing area based data from the census to map disparities was a vital first step. These analyses reported covid-19 rates 10 times higher in some areas and the best predictors were the percentage of racialized populations in an area and income [4].

The analyses maintained media interest and pressure on government and public health. Neighbouring public health units (Peel and Middlesex London) and one Province (Manitoba) started collecting race based data in April 2020. Toronto Public Health started collecting race/ethnicity, income, housing data at the time of tracing in May 2020 [5].

By June, the Ontario Government changed the law so that socio-demographic data would be collected at tracing by all public health units. Tracing information would be linked so that hospitalization rates could be measured. Testing sites were set up to be, quick, low barrier and easy to implement; because of this socio-demographic data collection was considered too onerous [6].

To achieve a more equitable pandemic, data has to be analysed and used. And, the publication of the data ensures transparency and accountability.

In July, Toronto's Mayor joined the Medical Officer of Health to present the first analyses of socio-demographic disaggregated individual level data by Toronto Public Health. Racialized groups were over represented in covid-19 cases and hospitalizations; and Black populations, and Latino populations had covid-19 case rates 6–11 times that of the White population. The City announced immediate interventions for hard hit areas which started in July 2020 and a public consultation focussed on improving the equity of the response [7].

Interventions included community based multi-lingual public health campaigns, community testing and pop-up testing sites, free masks, free voluntary isolation sites, eviction prevention advocacy, food security programs, free digital access and emergency child-care [1].

Focussed strategies for the Black population were deployed following the community consultation in August [8].

Monthly data analysis and reporting has monitored progress, kept the issue visible and some may argue offers some evidence that the public health and social support changes may have been partially effective. The Latino population had the highest rate-ratio of covid-19 compared to the White population in June but this decreased as area based strategies were brought in. The rate-ratio in the Black population has decreased steadily; from 9 in August to 2.2 by end December 2020 (Fig. 1).

Fig. 1

Covid-19 case-rate ratios for racialized groups vs White population; Toronto, June - Dec 2020

By the end of 2020, the Province of Ontario had announced its own assistance to support pandemic response in hard hit areas [9], and were investigating socio-demographic data collection for the vaccine roll-out. In addition, the Federal Government announced a national socio-demographic data collection initiative and a pandemic equity model [10].

The call for disaggregated data aligned community, academics, clinicians and policy makers. The collection, analysis and presentation of data led to changes in the public health response and may have improved the equity of the response. The equity of the response improved following both area focussed and sub-population-based approaches. Further evidence will be needed to determine which changes can be linked to improved pandemic equity. The positive experience of the collection and use of disaggregated data collection and use during covid-19 has increased the appetite for a longer-term strategy for socio-demographic data collection.

Declaration of Competing Interest

No interests to declare