The impact of test positivity on surveillance with asymptomatic carriers

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.

A Low-Cost Early Warning Method for Infectious Diseases with Asymptomatic Carriers

“…The minimum threshold on the average value of the IHR1 allows for us to discriminate critical situations. Indeed, after the spread of the Omicron variant at the end of December 2021, the IHR1 dropped by half [23], reducing healthcare system strain.…”

“…Would a significant increase in test positivity be a sufficient signal to justify the early enactment of drastic measures, such as the lockdown of the 9th of March 2020? Although a relationship between test positivity and mortality was discovered in the first COVID-19 outbreak in Italy [29], the analysis of pandemic data in the successive waves shows that an increase in test positivity alone is not a sufficient condition to identify emergency situations [23]. For example, a similar increase was observed in the Omicron outbreak at the end of December 2021, without the need to make equally drastic decisions.…”

“…Following the approach of [23], we use a definition of TPR based on two levels: one level deals with data collection issues, and the other with epidemiological issues. We let t 1 ,t 2 ,.…”

“…where µ = 5 on the onset [31], and µ = 3 in the Omicron outbreak [32,33]. The details of the calculation are presented in [23].…”

“…However, there are other indicators that could have been used at the initial stages. For example, the Test Positivity Rate (TPR), which is the percentage of positive tests over total tests [23], proved to be more suitable for modelling under-ascertainment due to asymptomatic carriers [24][25][26][27][28]. This indicator was demonstrated to be correlated with excess deaths in the first wave of the pandemic [29], and, most importantly, it anticipates incidence [23].…”