App-based COVID-19 surveillance and prediction: The COVID Symptom Study Sweden

The app-based COVID Symptom Study was launched in Sweden in April 2020 to contribute to real-time COVID-19 surveillance. We enrolled 143,531 study participants ([≥]18 years) who contributed 10.6 million daily symptom reports between April 29, 2020 and February 10, 2021. Data from 19,161 self-reported PCR tests were used to create a symptom-based model to estimate the individual probability of symptomatic COVID-19, with an AUC of 0.78 (95% CI 0.74-0.83) in an external dataset. These individual probabilities were used to estimate daily regional COVID-19 prevalence, which were in turn used together with current hospital data to predict next week COVID-19 hospital admissions. We found that this hospital prediction model demonstrated a lower median absolute percentage error (MdAPE: 25.9%) across the five most populated regions in Sweden during the first pandemic wave than a model based on case notifications (MdAPE: 30.3%). During the second wave, the error rates were similar. When applying the same model to an English dataset, not including local COVID-19 test data, we observed MdAPEs of 22.3% and 19.0%, respectively, highlighting the transferability of the prediction model.

Aspirin and NSAID use and the risk of COVID-19

Early reports raised concern that use of non-steroidal anti-inflammatory drugs (NSAIDs) may increase risk of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) disease (COVID-19). Users of the COVID Symptom Study smartphone application reported use of aspirin and other NSAIDs between March 24 and May 8, 2020. Users were queried daily about symptoms, COVID-19 testing, and healthcare seeking behavior. Cox proportional hazards regression was used to determine the risk of COVID-19 among according to aspirin or non-aspirin NSAID users. Among 2,736,091 individuals in the U.S., U.K., and Sweden, we documented 8,966 incident reports of a positive COVID-19 test over 60,817,043 person-days of follow-up. Compared to non-users and after stratifying by age, sex, country, day of study entry, and race/ethnicity, non-aspirin NSAID use was associated with a modest risk for testing COVID-19 positive (HR 1.23 [1.09, 1.32]), but no significant association was observed among aspirin users (HR 1.13 [0.92, 1.38]). After adjustment for lifestyle factors, comorbidities and baseline symptoms, any NSAID use was not associated with risk (HR 1.02 [0.94, 1.10]). Results were similar for those seeking healthcare for COVID-19 and were not substantially different according to lifestyle and sociodemographic factors or after accounting for propensity to receive testing. Our results do not support an association of NSAID use, including aspirin, with COVID-19 infection. Previous reports of a potential association may be due to higher rates of comorbidities or use of NSAIDs to treat symptoms associated with COVID-19. One Sentence SummaryNSAID use is not associated with COVID-19 risk.

Large differences in community COVID-19 testing across geographic areas in a Swedish region with 385,000 inhabitants

BackgroundSufficient community testing for suspected COVID-19 regardless of residential area is essential for a successful test-trace-isolate strategy. AimThis study aimed to elucidate area level characteristics linked to testing rates. MethodsFree-of-charge diagnostic tests (PCR) of SARS-CoV-2 was made available to the general public in late June 2020 in Uppsala County, Sweden, at four main test stations, and to a lesser extent at other health care units. We analysed 35,794 tests performed on individuals from 346 postal codes, from 24 June to 12 October 2020. ResultsWe observed varying testing rates across postal code areas within Uppsala City as well as in Uppsala County. Testing rates were lower in areas characterized by longer distance to the nearest test station, lower neighbourhood deprivation index indicating higher deprivation (NDI) and higher proportion of inhabitants with foreign background. Multivariable regression models could not separate influences of foreign background and NDI on COVID-19 testing rates as these were collinear. Further, we did not detect any association between COVID-19 hospitalization rates and testing rates, indicating that underlying community infection rates did not substantially affect test frequency during this period. ConclusionWe observed that testing rates were associated with distance to test station and socioeconomic and demographic circumstances. As lower testing rates can contribute to inequity in pandemic health effects, there is an urgent need to ensure adequate test accessibility in all parts of society.