Pool Strategy for Surveillance Testing of SARS-CoV-2

Abstract

Due to the great morbidity and mortality in the risk groups of the pandemic COVID-19 caused by the emerging coronavirus SARS-CoV-2 and in the absence of effective therapeutic or preventive measures, quarantines, social distancing and the use of masks were the measures most used by health systems to reduce infections. The social, economic and health impact caused by these measures have begun to be evaluated in the different countries. These analyses lead to underestimations because in general they evaluate disease confirmed by a laboratory test and in some cases by epidemiological link without considering asymptomatic or oligosymptomatic infection. Therefore, mitigating fast circulation of the virus requires continuous tracking, detection, and isolation of cases, for which active surveillance able to address asymptomatic cases can make a valuable contribution over the dynamics of the disease in a given society, and to allocate adequate health resources and evaluate the effectiveness of control measures. Mathematical models such as the Susceptible-Exposed-Infectious-Removed (SEIR) allow not only to improve the estimates of the evolution of the pandemic at the local level, but also to evaluate health strategies. In the context of large testing requirements and the expansion of such testing capacity, it is also essential to develop approaches that improve the efficient use of these resources. Active surveillance undoubtedly contributes to improving estimates of virus circulation and it is of particular importance in vulnerable groups of high population density that have one or more risk factors, difficult access to the health system, and inhabit semi-closed facilities such as residential care homes, mental hospitals, prison houses, police stations housing prisoners, etc. Group testing strategies are especially useful for routine community survey and for monitoring of cohesive groups. While the frequency of infection in a population, who have only some symptoms compatible with the disease or do not have any symptoms, may be low, diagnosing even a single positive person typically requires quarantine of the entire group to prevent further spread in the community. In these surveillance strategies, pooling may allow more routine monitoring and detection of low frequency of carriage, thereby improving estimates, informing policy makers, reducing transmission, and alleviating the strain on healthcare services. By means of molecular tests based on RT-qPCR, the pooling strategy has been assayed with different algorithms also for COVID-19, particularly in the asymptomatic population, since a low prevalence of the disease is expected there. This has increased COVID-19 testing throughput while maintaining high sensitivity. Here, we discuss the relevance of some active surveillance strategies to determine key facts about COVID-19 pandemics and review different testing strategies that different countries have applied for tracking SARS-CoV-2.