ArticleFrontiers in public health2022
Estimating COVID-19 cases in Puerto Rico using an automated surveillance system.
Article in Frontiers in public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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6 authors at 2 institutions in 3 countries.
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Abstract
Due to concerns regarding limited testing and accuracy of estimation of COVID-19 cases, we created an automated surveillance system called "Puerto Rico Epidemiological Evaluation and Prevention of COVID-19 and Influenza" (PREPCOVI) to evaluate COVID-19 incidence and time trends across Puerto Rico. Automated text message invitations were sent to random phone numbers with Puerto Rican area codes. In addition to reported COVID-19 test results, we used a published model to classify cases from specific symptoms (loss of smell and taste, severe persistent cough, severe fatigue, and skipped meals). Between 18 November 2020, and 24 June 2021, we sent 1,427,241 messages, 26.8% were reached, and 6,975 participants answered questions about the last 30 days. Participants were aged 21-93 years and represented 97.4% of the municipalities. PREPCOVI total COVID-19 cases were higher among women and people aged between 21 and 40 years and in the Arecibo and Bayamón regions. COVID-19 was confirmed, and probable cases decreased over the study period. Confirmed COVID-19 cases ranged from 1.6 to 0.2% monthly, although testing rates only ranged from 30 to 42%. Test positivity decreased from 13.2% in November to 6.4% in March, increased in April (11.1%), and decreased in June (1.5%). PREPCOVI total cases (6.5%) were higher than cases reported by the Puerto Rico Department of Health (5.3%) for similar time periods, but time trends were similar. Automated surveillance systems and symptom-based models are useful in estimating COVID-19 cases and time trends, especially when testing is limited.
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