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We aimed to assess the risk of SARS-CoV-2 infection for polling station members during the Catalan elections in February 2021. We compared the incidence 14 days after the elections between a cohort of polling station members (N= 18,304) and a control cohort paired by age, sex and place of residence. A total of 37 COVID-19 cases (0.2%) were confirmed in the members of the polling stations and 43 (0.23%) in the control group (p-value 0.576). Our study suggests that there was no greater risk of infection for the members of the polling stations.
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BackgroundTo date, characterisation studies of COVID-19 have focussed on hospitalised or intensive care patients. We report for the first time on the natural history of COVID-19 disease from first diagnosis, including both outpatient and hospital care. MethodsData was obtained from SIDIAP, a primary care records database covering >6 million people (>80% of the population of Catalonia), linked to COVID-19 RT-PCR tests, hospital emergency and inpatient, and mortality registers. All participants >=15 years, diagnosed with COVID-19 in outpatient between 15th March and 24th April 2020 (10th April for outcome studies) were included. Baseline characteristics, testing, and 30-day outcomes (hospitalisation for COVID-19 and all-cause fatality) were analysed. ResultsA total of 121,263 and 95,467 COVID-19 patients were identified for characterisation and outcome studies, respectively. Women (57.8%) and age 45-54 (20.2%) were predominant. 44,709 were tested, with 32,976 (73.8%) PCR+. From 95,467 cases, a 14.6% [14.4-14.9] were hospitalised in the month after diagnosis, with male predominance (19.2% vs 11.3%), peaking at age 75-84. Overall 30-day fatality was 4.0% [95%CI 3.9%-4.2%], higher in men (4.8%) than women (3.4%), increasing with age, and highest in those residing in nursing homes (25.3% [24.2% to 26.4%]). ConclusionsCOVID-19 is seen in all age-sex strata, but severe forms of disease cluster in older men and nursing home residents. Although initially managed in primary care, 15% of cases require hospitalization within a month, with overall fatality of 4%.
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ObjectivesThere is uncertainty about when the first cases of COVID-19 appeared in Spain, as asymptomatic patients can transmit the virus. We aimed to determine whether influenza diagnoses masked early COVID-19 cases and, if so, estimate numbers of undetected COVID-19 cases in a large database of primary-care records covering >6 million people in Catalonia. DesignTime-series study of influenza and COVID-19 cases, using all influenza seasons from autumn-winter 2010-2011 to autumn-winter 2019-2020. SettingPrimary care, Catalonia, Spain. ParticipantsPeople registered in one of the contributing primary-care practices, covering >6 million people and >85% of the population. Main outcome measuresWeekly new cases of influenza and COVID-19 diagnosed in primary care. AnalysesDaily counts of both cases were computed using the total cases recorded over the previous 7 days to avoid weekly effects on recording practice. Epidemic curves were characterised for the 2010-2011 to 2019-2020 influenza seasons. Influenza seasons with a similar epidemic curve and peak case number as the 2019-2020 season were used to model predictions for 2019-2020. ARIMA models were fitted to the included influenza seasons, overall and stratified by age, to estimate expected case numbers. Daily excess influenza cases were defined as the number of observed minus expected cases. ResultsFour influenza season curves (2011-2012, 2012-2013, 2013-2014, and 2016-2017) were used to estimate the number of expected cases of influenza in 2019-2020. Between 4 February 2020 and 20 March 20202, 8,017 (95% CI: 1,841 to 14,718) excess influenza cases were identified. This excess was highest in the 15-64 age group. ConclusionsCOVID-19 cases may have been present in the Catalan population when the first imported case was reported on 25 February 2020. COVID-19 carriers may have been misclassified as influenza diagnoses in primary care, boosting community transmission before public health measures were taken. In future, the surveillance of excess influenza cases using widely available primary-care electronic medical records could help detect new outbreaks of COVID-19 or other influenza-like illness-causing pathogens. Earlier detection would allow public health responses to be initiated earlier than during the current crisis.
