Delivering COVID self-tests through GetaKit.ca: Creating testing access during a pandemic

At-home testing for respiratory viruses: a minireview of the current landscape

The landscape of at-home testing using over-the-counter (OTC) tests has been evolving over the last decade. The United States Food and Drug Administration Emergency Use Authorization rule has been in effect since the early 2000s, and it was widely employed during the severe acute respiratory syndrome coronavirus 2 pandemic to authorize antigen and nucleic acid detection tests for use in central laboratories as well as OTC. During the pandemic, the first at-home tests for respiratory viruses became available for consumer use, which opened the door for additional respiratory virus OTC tests. Concerns may exist regarding the public's ability to properly collect samples, perform testing, interpret results, and report results to public health authorities. However, favorable comparison studies between OTC testing and centralized laboratory test results suggest that OTC testing may have a place in healthcare, and it is likely here to stay. This mini-review of OTC tests for viral respiratory diseases will briefly cover the regulatory and reimbursement environment, current OTC test availability, as well as the advantages and limitations of OTC tests.

Real world outcomes of distributing Lucira Check-It® COVID self-tests in Ontario, Canada: the GetaKit COVID study

BACKGROUND

In Ontario, Canada we developed and implemented an online screening algorithm for the distribution of HIV self-tests, known as GetaKit. During the COVID pandemic, we adapted the GetaKit algorithm to screen for COVID based on population and infection data and distributed COVID rt-LAMP self-tests (using the Lucira Check-It®) to eligible participants.

METHODS

GetaKit/COVID was a prospective observational study that occurred over a 7-month period from September 2021 to April 2022. All potential participants completed an online registration and risk assessment, including demographic information, COVID symptoms and risk factors, and vaccination status. Bivariate comparisons were performed for three outcomes: results reporting status, vaccination status, and COVID diagnosis status. Data were analysed using Chi-Square for categorial covariates and Independent Samples T-Test and Mann-Whitney U test for continuous covariates. Bivariate logistic regression models were applied to examine associations between the covariates and outcomes.

RESULTS

During the study period, we distributed 6469 COVID self-tests to 4160 eligible participants; 46% identified as Black, Indigenous or a Person of Colour (BIPOC). Nearly 70% of participants reported their COVID self-test results; 304 of which were positive. Overall, 91% also reported being vaccinated against COVID. Statistical analysis found living with five or fewer people, having tested for COVID previously, and being fully vaccinated were positive factors in results reporting. For COVID vaccination, people from large urban centers, who identified their ethnicity as white, and who reported previous COVID testing were more likely to be fully vaccinated. Finally, being identified as a contact of someone who had tested positive for COVID and the presence of COVID-related symptoms were found to be positive factors in diagnosis.

CONCLUSIONS

While most participants who accessed this service were vaccinated against COVID and the majority of diagnoses were identified in participants who had symptoms of, or an exposure to, COVID, our program was able to appropriately link participants to recommended follow-up based on reported risks and results. These findings highlight the utility of online screening algorithms to provide health services, particularly for persons with historical barriers to healthcare access, such as BIPOC or lower-income groups.