Estimating COVID-19 cases in Puerto Rico using an automated surveillance system - Martinez-Lozano, Marijulie; Gadhavi, Rajendra; Vega, Christian; Martinez, Karen G.; Acevedo, Waldo; Joshipura, Kaumudi (Frontiers in Public Health, 2022)
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 November 18, 2020 and June 24, 2021, we sent 1,427,241 messages; 26.8% were reached, and 6,975 participants answered questions pertaining to last 30 days. Participants were 21-93 years old and represented 97.4% of the municipalities. PREPCOVI total COVID-19 cases were higher among females and people between 21-40 years old, and in Arecibo and Bayamón regions. COVID-19 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%-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 system and symptom-based models are useful in estimating COVID-19 cases and time trends, especially when testing is limited.