In late December 2020, the Chinese government reported the presence of an ongoing outbreak of pneumonia associated with a novel coronavirus, called severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), in the Wuhan region. On February, the World Health Organization (WHO) named the disease as coronavirus disease 2019 (COVID-19). By the end of March, most countries already had cases of this disease. As part of the control actions, the countries began to carry out diagnostic tests, under the WHO indications. The Ecuadorian Ministry of Public Health (MPH) implemented the application of diagnostic tests, aimed at cases with clinical symptoms compatible with COVID-19.

To face the COVID-19 pandemic, several governments took into account the model described as the “Oxford Study,” which conceives a way of acting to “flatten the curve” (referring to the contagion curve),^{Reference Ferguson, Laydon and Nedjati Gilani1} which consists of imposing more extreme social withdrawal measures if the income in intensive care units (ICUs) increases, and softening them if they decrease, assuming that sooner or later the majority of the population will develop the infection.

However, it is known of the existence of other models that, in addition to the implementation of social isolation measures, involve the search for the symptomatic population, massively practicing tests to detect the infection in the initial stages.²

According to the WHO (2020), any case confirmed by the laboratory, regardless of clinical signs or symptoms, is considered a positive COVID-19 case.³ In Ecuador, the case definition is practically the same, but health workers are restricted to applying laboratory tests only to those patients who present symptoms. This measure suggests the systematic exclusion of the asymptomatic population, without it being integrated, in any way, as part of the epidemiological strategy to stop transmission in the community.

On the basis of the above, this article aims to evaluate the relevance of this model of detection of positive cases of COVID-19 implemented by the Ecuadorian MPH and to compare it with those of the other countries that decided to carry out diagnostic tests on asymptomatic patients and suspicious contacts. For this purpose, the information produced by the Ministry of Public Health of Ecuador was used.⁴

METHODS

The statistical evaluations presented in this article are based on probability analyses, determined using Bayes’ Theorem, where the results are represented with numbers between 0 and 1. The formulations were carried out under the Conditioned Probability modality, that is, probability of an event A occurring when an event B occurs. The estimates were oriented to try to specify the type of relationship between the variables “COVID-19 tests applied” and the “possibility of occurrence of a positive COVID-19 case.” According to WHO,⁵ a case is considered as positive COVID-19 if it is confirmed by laboratory, independent of clinical signs or symptoms.

Bayes’ Theorem is formulated as follows^{Reference Jøsang6}:

$$P{(\rm{A}|B)} = P{(\rm{B|A}}) \times P({\rm{A}}) \;\hbox/ \;P(\rm{B})$$

where P(A) is the probability of event A, P(B) is the probability of event B, P (A|B) is the probability of observing event A if B is true; and, P(B|A) is the probability of observing event B if A is true.

In this case, Pa represents COVID-19 confirmed patients with obvious signs of infection, while Pb represents confirmed patients with COVID-19 who had no obvious signs of infection or any type of symptoms.

This gives rise to 2 differentiated approaches that would consist of the observation of:

1. Pa (symptomatic | examined) + Pb (asymptomatic | examined)

2. Pa (symptomatic | examined)

In the first case, it would be based on a principle of randomness (symptomatic + nonsymptomatic), and in the second, selectivity (symptomatic).

With this in mind, the possibility of occurrence obtained in Ecuador, based on the second principle (selectivity), was compared—thanks to the reports issued periodically by the Ecuadorian Ministry of Public Health on COVID-19 positive cases—with the cases of South Korea and Iceland, based on the first principle (randomness), until April 13, 2020.^{Reference Center7,Reference Wu and McGoogan8}

All the COVID-19 tests applied in relation to the confirmed cases per million inhabitants were determined in the 3 countries.

RESULTS

In Ecuador, from March 31 to April 13, 2020, a total of 24,553 COVID-19 tests were carried out, obtaining a total of 7529 COVID-19 confirmed patients.⁴ Taking into account the size of the country’s population (17,468,736 people), it is observed that, between March 31 and April 13, 2020, there was a growth that exceeded 472 test/million inhabitants to 1406 test/million inhabitants (Figure 1). The average positivity found is: Pa = 0.26 ± 0.33.

FIGURE 1 Dates of Applied COVID-19 Tests.

For comparative purposes, this selective approach based on the study of the proportion of confirmed cases of COVID-19 only among the symptomatic (Pa), was compared with the randomized approach used by Iceland and South Korea, which tested both symptomatic and nonsymptomatic (Pa + Pb). As results, during this period, Korea applied 534,552 tests and obtained 10,519 positive COVID-19 cases (Pa + Pb = 0.020); Iceland performed 36,339 tests and obtained 1720 positive cases (Pa + Pb = 0.047); and Ecuador carried out 24,553 tests and obtained 7529 positive cases (Pa = 0.307). When comparing the results of Ecuador with respect to with Korea and Iceland, it is inferred that Pa (symptomatic | examined) has a greater probability than Pb (nonsymptomatic | examined). Thus, in cases with obvious symptoms of COVID-19, a significant correlation with the positivity of the test will be observed more frequently (Figure 2).

FIGURE 2 COVID-19 Tests Applied Per Million Inhabitants.