Test positivity – Evaluation of a new metric to assess epidemic dispersal mediated by non-symptomatic cases

Abstract

Epidemic control may be hampered when the percentage of asymptomatic cases is high. To estimate whether test positivity may assist in policy-making, it was explored in the first 60 to 90 epidemic days in six Latin American countries that reported their first COVID-19 case between February and March, 2020: Argentina, Bolivia, Chile, Cuba, Mexico, and Uruguay. Test positivity (TP) is the percentage of test-positive individuals recorded on a given day out of all individuals tested on the same day. The epidemic data of the country infected last (Uruguay) was first analyzed to evaluate TP as well as: (i) the daily ratio of secondary over primary infections (apparent reproductive ratio or ARR); (ii) tests conducted per million inhabitants (TPMI), (iii) the temporal data on the number of active cases (all test-positive cases minus deaths and recovered patients), and (iv) that of recovered patients. Later, significant patterns identified in the first step were assessed in the six countries. The Uruguayan data indicated that (i) TP was positively correlated with the ARR (r=.92, p<0.01); (ii) TP informed more than the ARR: while major data departures revealed by the ARR were also detected by TP, TP exhibited patterns not shown by ARR; and (iii) three temporal stages were observed, which differed from one another in both TP and TPMI medians (P<0.01) and, together, revealed a negative relationships between TPMI and TP. The six Latin American countries showed that TP was positively correlated with deaths/million inhabitants or DMI (r=.62, p<0.01). The temporal analysis of policies revealed four patterns: (1) low testing and high DMI, (2) high testing and low DMI; (3) an intermediate pattern, and (4) high testing and high DMI (where isolation was not pursued). Findings support the hypothesis that test positivity may inform as much as, if not more than classic metrics, such as the TPMI. If complemented with high-resolution geographical data, these indicators could inform policy-makers when and where epidemic control measures are or are not successful. .

Residential clustering of COVID-19 cases and efficiency of building-wide compulsory testing notices as a transmission control measure in Hong Kong

“…However, our findings indicate that the higher RTD test-positivity in the fifth wave is likely to be a reflection of the higher community prevalence of infection in the substantially larger epidemic wave that occurred. It corresponds with the established use of test-positivity rates as an indicator assessing epidemic dynamics (21-23).…”

Heterogeneity in COVID-19 infection among older persons in South Africa: Evidence from national surveillance data

“…These include backlogs in laboratory processing particularly during high transmission periods, prioritization of severe cases for testing would introduce bias toward the number of people testing positive and periodic stock outs of consumables ( 32 , 33 ). Researchers have described the test positivity as a useful metric when asymptomatic cases are high, and this, together with plots of the number of active confirmed cases, can be used to monitor the epidemic ( 38 ). However, as lockdown restrictions have been lifted and severity of COVID-19 has decreased, the number of people testing has declined ( 39 ).…”

The impact of Test Positivity on Surveillance with Asymptomatic Carriers

“…Finally, a negative correlation between TPR and the number of administered tests was evidenced in some studies [19, 4, 12]. Basically, when the number of conducted tests increases, test positivity tends to decrease, and thus some variations of TPR may be linked to an increased volume of testing.…”

“…Typical applications include estimating the prevalence of diseases in the population, see [1] for malaria disease and [2] for COVID-19, or establish levels of community transmission from sentinel sites in the COVID-19 pandemic [3]. 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].…”