ISSN: 2639-2038
Authors: Turabian JL*
A series of circumstances make it difficult to assess the preliminary results of seroprevalence of COVID-19: the methodological differences, the sampling biases, the problems of precision and reliability of the tests, the variation in prevalence according to the time phase of the outbreak, and the possible loss of antibodies over time since infection. Despite this, the first data indicate that the observed seroprevalence is quite similar in many countries and cities in the world, and can be between 2-3% and 10-15%. These figures indicate that, as expected, the actual number of people who have had COVID-19 is much greater than the number of cases confirmed with the Polymerase Chain Reaction test. However, the infections are not massive, and most of the populations do not have antibodies; herd immunity is far from being achieved, in the case that immunity is effective and long-lasting. So, the march of the coronavirus through the population has just begun. Furthermore, regardless of doubts about the precision of the tests, with a probable low prevalence of COVID-19, the positive predictive value of the seroprevalence test decreases and there will be more false positives, which is erroneously increasing the prevalence value found. These data may indicate increased risks from the second wave of the pandemic. Currently, deescalation of the containment measures will lead to new cases, outbreaks and contacts: only 5-10% of the SARS-CoV-2 iceberg has been made visible so far. This implies that general practitioners must be prepared to attend to new patients in these outbreaks: strong epidemiological information systems, tests, maintenance of telecare in consultations, use of personal protective equipment, contact tracing, etc., until the existence and availability of vaccines, in addition to maintaining care for new health problems and continued care for chronic non-COVID-19 problems.
Keywords: Coronavirus; COVID-19; SARS-CoV-2; General Practice; Epidemiology; Infectious Disease; Outbreak Modelling; Acute Respiratory Infections; Population Surveillance/methods; Public Health Practice
