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Background Understanding severity of infections with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and its variants is crucial to inform public health measures. Here we used coronavirus disease 2019 (COVID-19) patient data from Hong Kong to characterize the severity profile of COVID-19. Methods Time-varying and age-specific effective severity measured by case hospitalization risk and hospitalization fatality risk was estimated with all individual COVID-19 case data collected in Hong Kong from 23 January 2020 through 26 October 2022 over 6 epidemic waves. The intrinsic severity of Omicron BA.2 was compared with the estimate for the ancestral strain with the data from unvaccinated patients without previous infections. Results With 32 222 COVID-19 hospitalizations and 9669 deaths confirmed over 6 epidemic waves, the time-varying hospitalization fatality risk dramatically increased from <10% before the largest fifth wave of Omicron BA.2 to 41% during the peak of the fifth wave when hospital resources were severely constrained. The age-specific fatality risk in unvaccinated hospitalized Omicron cases was comparable to the estimates for unvaccinated cases with the ancestral strain. During epidemics predominated by Omicron BA.2, fatality risk was highest among older unvaccinated patients. Conclusions Omicron has comparable intrinsic severity to the ancestral Wuhan strain, although the effective severity is substantially lower in Omicron cases due to vaccination. [ABSTRACT FROM AUTHOR]

Most of the existing researches on public health events focus on the number and duration of events in a year or month, which are carried out by regression equation. COVID-19 epidemic, which was discovered in Wuhan, Hubei Province, quickly spread to the whole country, and then appeared as a global public health event. During the epidemic period, Chinese netizens inquired about the dynamics of COVID-19 epidemic through Baidu search platform, and learned about relevant epidemic prevention information. These groups' search behavior data not only reflect people's attention to COVID-19 epidemic, but also contain the stage characteristics and evolution trend of COVID-19 epidemic. Therefore, the time, space and attribute laws of propagation of COVID-19 epidemic can be discovered by deeply mining more information in the time series data of search behavior. In this study, it is found that transforming time series data into visibility network through the principle of visibility algorithm can dig more hidden information in time series data, which may help us fully understand the attention to COVID-19 epidemic in Chinese provinces and cities, and evaluate the deficiencies of early warning and prevention of major epidemics. What's more, it will improve the ability to cope with public health crisis and social decision-making level. [ABSTRACT FROM AUTHOR]

Background: The understanding of viral positivity and seroconversion during the course of coronavirus disease 2019 (COVID-19) is limited.Objective: To describe patterns of viral polymerase chain reaction (PCR) positivity and evaluate their correlations with seroconversion and disease severity.Design: Retrospective cohort study.Setting: 3 designated specialty care centers for COVID-19 in Wuhan, China.Participants: 3192 adult patients with COVID-19.Measurements: Demographic, clinical, and laboratory data.Results: Among 12 780 reverse transcriptase PCR tests for severe acute respiratory syndrome coronavirus 2 that were done, 24.0% had positive results. In 2142 patients with laboratory-confirmed COVID-19, the viral positivity rate peaked within the first 3 days. The median duration of viral positivity was 24.0 days (95% CI, 18.9 to 29.1 days) in critically ill patients and 18.0 days (CI, 16.8 to 19.1 days) in noncritically ill patients. Being critically ill was an independent risk factor for longer viral positivity (hazard ratio, 0.700 [CI, 0.595 to 0.824]; P < 0.001). In patients with laboratory-confirmed COVID-19, the IgM-positive rate was 19.3% in the first week, peaked in the fifth week (81.5%), and then decreased steadily to around 55% within 9 to 10 weeks. The IgG-positive rate was 44.6% in the first week, reached 93.3% in the fourth week, and then remained high. Similar antibody responses were seen in clinically diagnosed cases. Serum inflammatory markers remained higher in critically ill patients. Among noncritically ill patients, a higher proportion of those with persistent viral positivity had low IgM titers (<100 AU/mL) during the entire course compared with those with short viral positivity.Limitation: Retrospective study and irregular viral and serology testing.Conclusion: The rate of viral PCR positivity peaked within the initial few days. Seroconversion rates peaked within 4 to 5 weeks. Dynamic laboratory index changes corresponded well to clinical signs, the recovery process, and disease severity. Low IgM titers (<100 AU/mL) are an independent risk factor for persistent viral positivity.Primary Funding Source: None. [ABSTRACT FROM AUTHOR]

Objective: Recently, the number of gynecological cancer patients infected with SARS-CoV-2 has been increasing. This article was committed to studying the influence of gynecological tumor treatment history compared to the Coronavirus Disease 2019 (COVID-19), which was of great significance for the treatment of gynecological cancer patients during the outbreak of COVID-19. Methods: We retrospectively analyzed the diagnosis and treatment of six gynecological cancer patients infected with SARS-CoV-2 in Tongji Hospital in Wuhan from January 30 to March 25, 2020. To better explain the treatment of gynecological cancer patients during the epidemic of COVID-19, we summarized the case characteristics, auxiliary examination, treatment plan, and outcome of these six patients. Results: We observed a high rate of nosocomial SARS-CoV-2 infection among these six gynecological cancer patients, who were in a low immune state. Also, due to the influence of cancer treatment history, COVID-19-related atypical symptoms became the first symptom of COVID-19 in some cases, which increased the difficulty of diagnosis. Furthermore, in terms of treatment for these cases, immune boosters and reagents that raised white blood cells were applied, except for in symptomatic antiviral treatment. At present, all patients in this study were discharged from the hospital with a good prognosis. Conclusion: After cancer-related treatment, the gynecological cancer patients became more susceptible to COVID-19. Besides, the history of cancer treatment made the diagnosis of COVID-19 difficult, which also affected the treatment of COVID-19. Therefore, we put forward the corresponding therapy suggestions for gynecological cancer patients during the outbreak of COVID-19. [ABSTRACT FROM AUTHOR]

To confirm the relationship between sex and the progression of Coronavirus Disease-19 (COVID-19), and its potential mechanism, among severe patients. For this retrospective study, we included 168 consecutive severe patients with pathogen-confirmed COVID-19 who were hospitalized between January 16th and February 4th, 2020, at Tongji Hospital in Wuhan, China. Clinical characteristics, laboratory parameters, and outcomes were compared and analyzed between males and females. In the present study, we analyzed 168 severe patients with COVID-19, including 86 males and 82 females, and 48 patients (28.6%) were diagnosed as critically ill. Of 86 male patients, 12.8% (11/86) died and 75.6% (65/86) were discharged; of 82 female patients, 7.3% (6/82) died and 86.6% (71/82) were discharged. Eleven laboratory parameters showed significant differences between male and female patients, and six of them were higher during the whole clinical course in patients who died than in patients who were discharged. In adjusted logistic regression analysis, males with comorbidities presented a higher risk of being critically ill than males without comorbidities (OR = 3.824, 95% CI = 1.279–11.435). However, this association attenuated to null in female patients (OR = 2.992, 95% CI = 0.937–9.558). A similar sex-specific trend was observed in the relation between age and critically ill conditions. We highlighted sex-specific differences in clinical characteristics and prognosis. Male patients appeared to be more susceptible to age and comorbidities. Sex is an important biological variable that should be considered in the prevention and treatment of COVID-19. Author summary: Overall, our results highlight sex-specific differences in clinical characteristics and prognosis to COVID-19, which are consistent with the sex-bias observed in other COVID-19 related studies. We also provided more evidence and explored the underlying mechanism with epidemiological analysis. Six candidate laboratory indicators with significant sex differences were considered as potential mediators affecting the prognosis of COVID-19. The age-specific risk distributions of COVID-19 showed a positive correlation between the prognosis and age/ comorbidities, which was significantly affected by sex. We also emphasize that sex is a biological variable that should be considered in the prevention and therapy of COVID-19. It is our hope that these methods may serve as a guide to the clinician in providing timely and specific therapy. Obviously, future studies are warranted to elucidate the different pathways and cellular responses between women and men. The key challenge is how best to use this disparity for providing adequate protection in both males and females. [ABSTRACT FROM AUTHOR]