Association of Anti-N and -S Seroprevalence in Asymptom atic, Mildly Symptomatic, and Symptomatic SARS-COV-2 Natural Infection

Backgrounds: SARS-COV-2 infection is not always correlated with protection. Antibody seroprevalence in unvaccinated individuals, which is usually measured by N-specific antibodies, is not necessarily correlated with protection, while antibodies against S protein show a better correlation with protection due to its neutralizing epitopes. In this study, we tried to improve our conception of the hidden perspective of SARS-COV-2 in epidemiological reports and investigate anti-S antibody prevalence among anti-N antibody-positive asymptomatic and mildly symptomatic patients. Material(s) and Method(s): Blood samples were collected from asymptomatic or mildly symptomatic volunteer participants and symptomatic hospitalized patients with negative PCR results from May 30 to June 17, 2020. Detection of SARS-COV-2 antibodies was done using an ELISA kit targeting N or S protein. Finding(s): Totally, 716 samples from volunteer participants and 81 samples from symptomatic hospitalized patients with negative PCR results were evaluated. The test performance-adjusted seroprevalence (%95 CI) of SARS-COV-2 antibody was 17.3% (8.8-25.8%) for anti-N IgG in volunteers and 25.5% (12.8-39.7%) for anti-N and anti-S IgM in hospitalized patients. Among anti-N IgG positive infected individuals, %49.2 (21.4 and 78.8%) were anti-S antibody positive. Conclusion(s): The results showed that SARS-COV-2 infection sometimes occurs in individuals without symptoms or with mild symptoms, but in more than half of them, the produced antibody is not protective. The findings of hospitalized patients showed that the combination of IgM assay with real-time PCR improved the disease diagnosis by more than 25% in cases with negative molecular test results.Copyright © 2022, TMU Press.

Mortality Risk Factors in Patients with COVID-19 Infection: A Case-Control Study in Northeast of Iran

Background and Objectives: COVID-19 is a new disease and little information is available on its risk factors. The aim of this study was to determine the mortality risk factors in patients with COVID-19 in the northeast of Iran. Materials and Methods: A case-control study was conducted. Patients of both sexes with a confirmed diagnosis of Covid-19 infection who died during the study were studied as the case group and patients who were in good general health and ready for discharge were studied as the control group. Data analysis was performed with the STATA software version 14 using descriptive statistics and univariate and multiple logistic regression tests. Results: Six hundred and eleven patients were studied (27% cases and 73% controls). Multiple logistic regression analysis showed that the odds of death were 2.8 times higher in patients over 80 years compared to patients aged 50-60 years. In addition, age under 40 years reduced the odds of mortality by 85% and living in rural areas increased odds of death by 2.2 times. Cough, general fatigue, pain, nausea and vomiting increased the odds of COVID19 survival. Conclusion: The odds of mortality were higher in elder patients with COVID-19. In addition, living in rural areas increased the odds of mortality in patients. Cough and fatigue reduced mortality;however, it is needed to address other hidden factors for sound judgment. © 2021 The Authors. Published by Tehran University of Medical Sciences.

Prevalence of asymptomatic COVID-19 infection using a seroepidemiological survey.

The prevalence of asymptomatic infection by coronavirus disease 2019 (COVID-19) as a critical measure for effectiveness of mitigation strategy has been reported to be widely varied. In this study, we aimed to determine the prevalence of asymptomatic infection using serosurvey on general population. In a cross-sectional seroprevalence survey in Guilan province, Iran, the specific antibody against COVID-19 in a representative sample was detected using rapid test kits. Among 117 seropositive subjects, prevalence of asymptomatic infection was determined based on the history of symptoms during the preceding 3 months. The design-adjusted prevalence of asymptomatic infection was 57.2% (95% confidence interval (CI) 44-69). The prevalence was significantly lower in subjects with previous contacts to COVID-19 patients (12%, 95% CI 2-49) than others without (69%, 95% CI, 46-86). The lowest prevalence was for painful body symptom (74.4%). This study revealed that more than half of the infected COVID-19 patients had no symptoms. The implications of our findings include the importance of adopting public health measures such as social distancing and inefficiency of contact tracing to interrupt epidemic transmission.

1,000,000 cases of COVID-19 outside of China: The date predicted by a simple heuristic.

We forecast 1,000,000 COVID-19 cases outside of China by March 31st, 2020 based on a heuristic and WHO situation reports. We do not model the COVID-19 pandemic; we model only the number of cases. The proposed heuristic is based on a simple observation that the plot of the given data is well approximated by an exponential curve. The exponential curve is used for forecasting the growth of new cases. It has been tested for the last situation report of the last day. Its accuracy has been 1.29% for the last day added and predicted by the 57 previous WHO situation reports (the date 18 March 2020). Prediction, forecast, pandemic, COVID-19, coronavirus, exponential growth curve parameter, heuristic, epidemiology, extrapolation, abductive reasoning, WHO situation report.