Seesaw Effect Between COVID-19 and Influenza From 2020 to 2023 in World Health Organization Regions: Correlation Analysis.

BACKGROUND: Seasonal influenza activity showed a sharp decline in activity at the beginning of the emergence of COVID-19. Whether there is an epidemiological correlation between the dynamic of these 2 respiratory infectious diseases and their future trends needs to be explored. OBJECTIVE: We aimed to assess the correlation between COVID-19 and influenza activity and estimate later epidemiological trends. METHODS: We retrospectively described the dynamics of COVID-19 and influenza in 6 World Health Organization (WHO) regions from January 2020 to March 2023 and used the long short-term memory machine learning model to learn potential patterns in previously observed activity and predict trends for the following 16 weeks. Finally, we used Spearman correlation coefficients to assess the past and future epidemiological correlation between these 2 respiratory infectious diseases. RESULTS: With the emergence of the original strain of SARS-CoV-2 and other variants, influenza activity stayed below 10% for more than 1 year in the 6 WHO regions. Subsequently, it gradually rose as Delta activity dropped, but still peaked below Delta. During the Omicron pandemic and the following period, the activity of each disease increased as the other decreased, alternating in dominance more than once, with each alternation lasting for 3 to 4 months. Correlation analysis showed that COVID-19 and influenza activity presented a predominantly negative correlation, with coefficients above -0.3 in WHO regions, especially during the Omicron pandemic and the following estimated period. The diseases had a transient positive correlation in the European region of the WHO and the Western Pacific region of the WHO when multiple dominant strains created a mixed pandemic. CONCLUSIONS: Influenza activity and past seasonal epidemiological patterns were shaken by the COVID-19 pandemic. The activity of these diseases was moderately or greater than moderately inversely correlated, and they suppressed and competed with each other, showing a seesaw effect. In the postpandemic era, this seesaw trend may be more prominent, suggesting the possibility of using one disease as an early warning signal for the other when making future estimates and conducting optimized annual vaccine campaigns.

Healthcare Workers' Attitudes toward Influenza Vaccination: A Behaviour and Social Drivers Survey.

This study aimed to understand the intention and correlation of receiving and recommending influenza vaccine (IV) among healthcare workers (HCWs) in China during the 2022/2023 season using the behavior and social drivers (BeSD) tools. A self-administered electronic survey collected 17,832 participants on a media platform. We investigated the willingness of IV and used multivariate logistic regression analysis to explore its associated factors. The average scores of the 3Cs' model were compared by multiple comparisons. We also explored the factors that potentially correlated with recommendation willingness by partial regression. The willingness of IV was 74.89% among HCWs, and 82.58% of the participants were likely to recommend it to others during this season. Thinking and feeling was the strongest domain independently associated with willingness. All domains in BeSD were significantly different between the hesitancy and acceptance groups. Central factors in the 3Cs model were significantly different among groups (p < 0.01). HCWs' willingness to IV recommendation was influenced by their ability to answer related questions (r = 0.187, p < 0.001) after controlling for their IV willingness and perceived risk. HCWs' attitudes towards IV affect their vaccination and recommendation. The BeSD framework revealed the drivers during the decision-making process. Further study should classify the causes in detail to refine HCWs' education.

Impact of TMPRSS2 Expression, Mutation Prognostics, and Small Molecule (CD, AD, TQ, and TQFL12) Inhibition on Pan-Cancer Tumors and Susceptibility to SARS-CoV-2.

As a cellular protease, transmembrane serine protease 2 (TMPRSS2) plays roles in various physiological and pathological processes, including cancer and viral entry, such as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Herein, we conducted expression, mutation, and prognostic analyses for the TMPRSS2 gene in pan-cancers as well as in COVID-19-infected lung tissues. The results indicate that TMPRSS2 expression was highest in prostate cancer. A high expression of TMPRSS2 was significantly associated with a short overall survival in breast invasive carcinoma (BRCA), sarcoma (SARC), and uveal melanoma (UVM), while a low expression of TMPRSS2 was significantly associated with a short overall survival in lung adenocarcinoma (LUAD), demonstrating TMPRSS2 roles in cancer patient susceptibility and severity. Additionally, TMPRSS2 expression in COVID-19-infected lung tissues was significantly reduced compared to healthy lung tissues, indicating that a low TMPRSS2 expression may result in COVID-19 severity and death. Importantly, TMPRSS2 mutation frequency was significantly higher in prostate adenocarcinoma (PRAD), and the mutant TMPRSS2 pan-cancer group was significantly associated with long overall, progression-free, disease-specific, and disease-free survival rates compared to the wild-type (WT) TMPRSS2 pan-cancer group, demonstrating loss of functional roles due to mutation. Cancer cell lines were treated with small molecules, including cordycepin (CD), adenosine (AD), thymoquinone (TQ), and TQFL12, to mediate TMPRSS2 expression. Notably, CD, AD, TQ, and TQFL12 inhibited TMPRSS2 expression in cancer cell lines, including the PC3 prostate cancer cell line, implying a therapeutic role for preventing COVID-19 in cancer patients. Together, these findings are the first to demonstrate that small molecules, such as CD, AD, TQ, and TQFL12, inhibit TMPRSS2 expression, providing novel therapeutic strategies for preventing COVID-19 and cancers.

COVID-19 Disease and Dermatomyositis: A Mini-Review.

The pandemic of coronavirus disease 2019 (COVID-19) caused by SARS-CoV-2 has caused a large number of deaths, and there is still no effective treatment. COVID-19 can induce a systemic inflammatory response, and its clinical manifestations are diverse. Recently, it has been reported that COVID-19 patients may develop myositis and interstitial pulmonary disease similar to dermatomyositis (DM). This condition is similar to the rapidly progressive interstitial lung disease associated with MDA5+ DM that has a poor prognosis and high mortality, and this poses a challenge for an early identification. Suppression of the immune system can protect COVID-19 patients by preventing the production of inflammatory cytokines. This article attempts to explore the possibility of a relationship between COVID-19 and DM in terms of the potential pathogenesis and clinical features and to analyze the therapeutic effect of the immunosuppressive drugs that are commonly used for the treatment of both DM and COVID-19.

Impacts of transportation and meteorological factors on the transmission of COVID-19.

The ongoing pandemic of 2019 novel coronavirus disease (COVID-19) is challenging global public health response system. We aim to identify the risk factors for the transmission of COVID-19 using data on mainland China. We estimated attack rate (AR) at county level. Logistic regression was used to explore the role of transportation in the nationwide spread. Generalized additive model and stratified linear mixed-effects model were developed to identify the effects of multiple meteorological factors on local transmission. The ARs in affected counties ranged from 0.6 to 9750.4 per million persons, with a median of 8.8. The counties being intersected by railways, freeways, national highways or having airports had significantly higher risk for COVID-19 with adjusted odds ratios (ORs) of 1.40 (p = 0.001), 2.07 (p < 0.001), 1.31 (p = 0.04), and 1.70 (p < 0.001), respectively. The higher AR of COVID-19 was significantly associated with lower average temperature, moderate cumulative precipitation and higher wind speed. Significant pairwise interactions were found among above three meteorological factors with higher risk of COVID-19 under low temperature and moderate precipitation. Warm areas can also be in higher risk of the disease with the increasing wind speed. In conclusion, transportation and meteorological factors may play important roles in the transmission of COVID-19 in mainland China, and could be integrated in consideration by public health alarm systems to better prevent the disease.

Age-dependent Gender Differences in COVID-19 in Mainland China: Comparative Study.

BACKGROUND: The ongoing pandemic of novel coronavirus disease 2019 (COVID-19) is challenging the global public health system. Sex differences in infectious diseases are a common but neglected problem. METHODS: We used the national surveillance database of COVID-19 in mainland China to compare gender differences in attack rate (AR), proportion of severe and critical cases (PSCC), and case fatality rate (CFR) in relation to age, affected province, and onset-to-diagnosis interval. RESULTS: The overall AR was significantly higher in females than in males (63.9 vs 60.5 per 1 million persons; P ˂ .001). In contrast, PSCC and CFR were significantly lower among females (16.9% and 4.0%) than among males (19.5% and 7.2%), with odds ratios of 0.87 and 0.57, respectively (both P ˂ .001). The female-to-male differences were age dependent, and were significant among people aged 50-69 years for AR and in patients aged 30 years or older for both PSCC and CFR (all P ≤ .001). The AR, PSCC, and CFR varied greatly from province to province. However, female-to-male differences in AR, PSCC, and CFR were significant in the epicenter, Hubei province, where 82.2% confirmed cases and 97.4% deaths occurred. After adjusting for age, affected province, and onset-to-diagnosis interval, the female-to-male difference in AR, PSCC, and CFR remained significant in multivariate logistic regression analyses. CONCLUSIONS: We elucidate an age-dependent gender dimorphism for COVID-19, in which females have higher susceptibility but lower severity and fatality. Further epidemiological and biological investigations are required to better understand the sex-specific differences for effective interventions.