Letter to the editor: Plenty of coronaviruses but no SARS-CoV-2

The Epistemology of a Positive SARS-CoV-2 Test

We investigate the epistemological consequences of a positive polymerase chain reaction SARS-CoV test for two relevant hypotheses: (i) V is the hypothesis that an individual has been infected with SARS-CoV-2; (ii) C is the hypothesis that SARS-CoV-2 is the cause of flu-like symptoms in a given patient. We ask two fundamental epistemological questions regarding each hypothesis: First, how much confirmation does a positive test lend to each hypothesis? Second, how much evidence does a positive test provide for each hypothesis against its negation? We respond to each question within a formal Bayesian framework. We construe degree of confirmation as the difference between the posterior probability of the hypothesis and its prior, and the strength of evidence for a hypothesis against its alternative in terms of their likelihood ratio. We find that test specificity-and coinfection probabilities when making inferences about C-were key determinants of confirmation and evidence. Tests with < 87% specificity could not provide strong evidence (likelihood ratio > 8) for V against ¬V regardless of sensitivity. Accordingly, low specificity tests could not provide strong evidence in favor of C in all plausible scenarios modeled. We also show how a positive influenza A test disconfirms C and provides weak evidence against C in dependence on the probability that the patient is influenza A infected given that his/her symptoms are not caused by SARS-CoV-2. Our analysis points out some caveats that should be considered when attributing symptoms or death of a positively tested patient to SARS-CoV-2.

Creating and applying SIR modified compartmental model for calculation of COVID-19 lockdown efficiency

We propose a Susceptible-Infected-Recovered (SIR) modified model for Coronavirus disease - 2019 (COVID-19) spread to estimate the efficacy of lockdown measures introduced during the pandemic. As input data, we used COVID-19 epidemiological information collected in fifteen European countries either in private surveys or using official statistics. Thirteen countries implemented lockdown measures, two countries (Sweden, Iceland) not. As output parameters, we studied herd immunity level and time of formation. Comparison of these parameters was used as an indicator of effectiveness / ineffectiveness of lockdown measures. In the absence of a medical vaccine, herd immunity may be regarded as a factor of population adaptation to severe acute respiratory syndrome-related coronavirus-2, the viral pathogen causing COVID-19 disease (SARS-CoV-2), and hence COVID-19 spreading stop. We demonstrated that there is no significant difference between lockdown and no-lockdown modes of COVID-19 containment, in terms of both herd immunity level and the time of achieving its maximum. The rationale for personal and business lockdowns may be found in the avoidance of healthcare system overburdening. However, lockdowns do not prevent any virus with droplet transmission (including SARS-CoV-2) from spreading. Therefore, in case of a future viral pathogen emergence, lockdown measures efficiency should not be overestimated, as it was done almost universally in the world during COVID-19 pandemic.

Adaptation to SARS-CoV-2 under stress: Role of distorted information

BACKGROUND

Since the time of global SARS-CoV-2 spread across the earth in February 2020, most of countries faced the problem of massive stress of their healthcare systems. In many cases, the structural stress was a result of incorrect allocation of medical care resources. In turn, this misallocation resulted from fear and apprehensions that superseded thorough calculations. A key role in exacerbating the healthcare sector overburdening was played by misleading information on the virus and disease caused by it. In the current paper, we study the situation in Russian healthcare system and advance recommendations how to avoid further crises.

MATERIALS AND METHODS

(a) Surveying the medical personnel (231 doctors, 317 nurses and 355 ambulance medical workers of lower levels) in five hospitals and six ambulance centres in Moscow. (b) Content analysis of 3164 accounts in Russian segment of social networks (VKontakte, Facebook, Instagram, Twitter, Odnoklassniki); official and unofficial media (TV, informational webpages).

RESULTS

We revealed positive-feedback loop that threatened the sustainability of Russian care sector. The main knot was occupied by incorrect/exaggerated media coverage of COVID-19. General public scared by misinformation in media and social networks, started to panic. This negative social background undermined the productivity of a significant part of medical workers who were afraid of COVID-19 patients.

CONCLUSIONS

The most serious problems of Russian healthcare sector related to COVID-19 pandemic, were informational problems. The exaggerated information on COVID-19 had big negative influence upon Russian society and healthcare system, despite SARS-CoV-2 relatively low epidemiological hazard.

Adaptation of a Russian population to SARS-CoV-2: Asymptomatic course, comorbidities, mortality, and other respiratory viruses - A reply to Fear versus Data

This study was conducted to assess the spread of SARS-CoV-2 in Russia and the adaptation of the population to the virus in March to June 2020. Two groups were investigated: 1) 12 082 individuals already proven positive for SARS-CoV-2 (clinical information was studied); 2) 7864+4458 individuals with suspected respiratory infections (polymerase chain reaction [PCR] tests and clinical information were studied). In the latter, SARS-CoV-2-positive individuals comprised 5.37% in March and 11.42% in June 2020. Several viral co-infections were observed for SARS-CoV-2. Rhinoviruses accounted for the largest proportion of co-infections (7.91% of samples were SARS-CoV-2-positive); followed by respiratory syncytial virus (7.03%); adenoviruses (4.84%); metapneumoviruses (3.29%); parainfluenza viruses (2.42%); enterovirus D68 (1.10%) and other viruses (entero-, echo-, parecho-) (<1%). Average SARS-CoV-2 case fatality rate in the group of 12 537 individuals was determined to be 0.6% (in contrast to official Russian government statistics of 1.5% mortality). This rate is within the range of mortality caused by other common seasonal respiratory viruses (0.01-2.21% in Russia in 2012 to 2020). Most fatalities occurred in individuals with comorbidities, as for other respiratory viruses. The proportion of SARS-CoV-2 asymptomatic carriers was 56.68% in March and 70.67% in June 2020. This new pathogen presents a substantial risk to human beings as it was not contained at the start of its outbreak in Wuhan and spread worldwide. However, surveillance, prevention and treatment must be strictly evidence-based and not dictated by fear.