Affiliation:
1. Department of Computer Science and Engineering , University of Bologna , Bologna , Italy
Abstract
Abstract
Objectives
Recent studies show that Test Positivity Rate (TPR) gains a better correlation than incidence with the number of hospitalized patients in COVID-19 pandemic. Nevertheless, epidemiologists remain sceptical concerning the widespread use of this metric for surveillance, and indicators based on known cases like incidence rate are still preferred despite the large number of asymptomatic carriers, which remain unknown. Our aim is to compare TPR and incidence rate, to determine which of the two has the best characteristics to predict the trend of hospitalized patients in the COVID-19 pandemic.
Methods
We perform a retrospective study considering 60 outbreak cases, using global and local data from Italy in different waves of the pandemic, in order to detect peaks in TPR time series, and peaks in incidence rate, finding which of the two indicators has the best ability to anticipate peaks in patients admitted in hospitals.
Results
On average, the best TPR-based approach anticipates the incidence rate of about 4.6 days (95 % CI 2.8, 6.4), more precisely the average distance between TPR peaks and hospitalized peaks is 17.6 days (95 % CI 15.0, 20.4) with respect to 13.0 days (95 % CI 10.4, 15.8) obtained for incidence. Moreover, the average difference between TPR and incidence rate increased to more than 6 days in the Delta outbreak during summer 2021, where presumably the percentage of asymptomatic carriers was larger.
Conclusions
We conclude that TPR should be used as the primary indicator to enable early intervention, and for predicting hospital admissions in infectious diseases with asymptomatic carriers.
Subject
Applied Mathematics,Epidemiology
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