COVID-19 Test Positivity Rate as a marker for hospital overload

Abstract

The use of antigen tests for the diagnosis of COVID-19 in Italy has risen sharply in autumn 2020. Although, Italian regions like Alto Adige, Veneto, Toscana, Lazio, Piemonte and Marche did a large use of these tests for screening and surveillance purposes or for implementing diagnosis protocols, in addition to molecular tests, they were not reported in the statistics in the last months of 2020. As a consequence of this situation the test positivity rate (TPR) index, defined as the number of new positive cases divided by the number of tests, has lost in accuracy. Only in the recent days, starting from the 15th of January 2021, antigen tests have become part of the statistics for all the Italian regions. Despite the lack of data, we have noticed that TPR has a strong correlation with the number of patients admitted in hospitals, and that TPR peaks in general precede the peaks of hospitalized people which occur on average about 15 days later.In this paper, we have deepened this intuition, analysing the TPR course and its relationship with the number of hospitalized people. To conduct the study we have defined a novel version of the TPR index which takes into account the number of tests done with respect to the population (considering both molecular and antigen tests), the number of infected individuals, and the number of patients healed. Successively, starting from a limited set of data which were made available in November 2020, we have reconstructed the antigen tests time series of four Italian regions, and we computed the TPR index for them.The results show that TPR peaks precede peaks of hospitalized people in both the first and the second phases of the pandemic in Italy, provided that antigen tests are considered. Moreover, the TPR index trend, can be used to deduct important information on the course of the epidemic, and on the impact of COVID-19 in the health care system, which can be monitored in advance.

The impact of Test Positivity on Surveillance with Asymptomatic Carriers

“…The first wave of the pandemic starting from February 2020 was not considered in the study because antigen tests were not used in Italy. In the second wave (from the 1st of October 2020 to the 10th of January 2021) the data on antigen tests were not available in the official site, however they have been made available for 5 regions: Toscana, Piemonte, Friuli Venezia Giulia, Veneto and the Provincia Autonoma of Bolzano [8]. Since, some of the data collected for Veneto, Friuli and Bolzano are uncertain (see [8] for data collection details), only Toscana and Piemonte were considered in this study, and all the other regions were excluded from the analysis.…”

“…Over the past two years, thanks to the large amount of data collected in the COVID-19 pandemic, new application domains where explored to guide epidemiologic policy-making [4, 5, 6] assessing epidemic dispersal mediated by asymptomatic carriers. Recent studies have highlighted a correlation with the number of patients admitted in hospitals [7, 8], which increases with respect to other indicators like incidence [9] or the daily number of positive cases [10]. This kind of correlation, was exploited to forecast two weeks in advance variations on the number of patients admitted in hospitals on the basis of TPR variations [11], or to define a severity detection rate, to predict ICU admissions [12].…”

“…In this paper, we compare incidence with different TPR calculation methods: standard rolling averages, the methods defined in [8, 11], the adjusted TPR proposed in [19], and a new proposal based on a two level approach. We consider 60 different cases using global and local data from Italy in four waves of the pandemic, starting from the second wave where data on antigen tests were made available for some region (Fall 2020), and the successive Alpha, Delta and Omicron waves.…”

“…Moreover, when antigen tests are used in the TPR calculation an additional problem arises, health care guidelines may recommend that positive antigen tests should be confirmed by NAAT tests because the latest have a better accuracy. These repeated diagnostic tests done for the same positive individuals should also be removed by the denominator [8].…”

Analysis of COVID-19 Test Positivity Rate in West Sumatra, Indonesia: A Cross-sectional Study of One-year Observation

“…Large data analysis should be performed to estimate and control the pandemic across the country and to nd an appropriate strategy to prevent massive mortality due to COVID-19. Some research has pointed to the test positivity rate (TPR) as a reliable indicator to manage the COVID-19 pandemic (5, 6). COVID-19 TPR is also used by World Health Organization (WHO) as a standard to…”