Continuous evolution and emerging lineage of seasonal human coronaviruses: A multicenter surveillance study.

The seasonal human coronaviruses (HCoVs) have zoonotic origins, repeated infections, and global transmission. The objectives of this study are to elaborate the epidemiological and evolutionary characteristics of HCoVs from patients with acute respiratory illness. We conducted a multicenter surveillance at 36 sentinel hospitals of Beijing Metropolis, China, during 2016-2019. Patients with influenza-like illness (ILI) and severe acute respiratory infection (SARI) were included, and submitted respiratory samples for screening HCoVs by multiplex real-time reverse transcription-polymerase chain reaction assays. All the positive samples were used for metatranscriptomic sequencing to get whole genomes of HCoVs for genetical and evolutionary analyses. Totally, 321 of 15 677 patients with ILI or SARI were found to be positive for HCoVs, with an infection rate of 2.0% (95% confidence interval, 1.8%-2.3%). HCoV-229E, HCoV-NL63, HCoV-OC43, and HCoV-HKU1 infections accounted for 18.7%, 38.3%, 40.5%, and 2.5%, respectively. In comparison to ILI cases, SARI cases were significantly older, more likely caused by HCoV-229E and HCoV-OC43, and more often co-infected with other respiratory pathogens. A total of 179 full genome sequences of HCoVs were obtained from 321 positive patients. The phylogenetical analyses revealed that HCoV-229E, HCoV-NL63 and HCoV-OC43 continuously yielded novel lineages, respectively. The nonsynonymous to synonymous ratio of all key genes in each HCoV was less than one, indicating that all four HCoVs were under negative selection pressure. Multiple substitution modes were observed in spike glycoprotein among the four HCoVs. Our findings highlight the importance of enhancing surveillance on HCoVs, and imply that more variants might occur in the future.

Circulation of respiratory viruses during the COVID-19 pandemic in The Gambia.

Background: In many countries, non-pharmaceutical interventions to limit severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission resulted in significant reductions in other respiratory viruses. However, similar data from Africa are limited. We explored the extent to which viruses such as influenza and rhinovirus co-circulated with SARS-CoV-2 in The Gambia during the COVID-19 pandemic.  Methods: Between April 2020 and March 2022, respiratory viruses were detected using RT-PCR in nasopharyngeal swabs from 1397 participants with influenza-like illness. An assay to detect SARS-CoV-2 and a viral multiplex RT-PCR assay was used as previously described  to detect influenza A and B, respiratory syncytial virus (RSV) A and B, parainfluenza viruses 1-4, human metapneumovirus (HMPV), adenovirus, seasonal coronaviruses (229E, OC43, NL63) and human rhinovirus. Results: Overall virus positivity was 44.2%, with prevalence higher in children <5 years (80%) compared to children aged 5-17 years (53.1%), adults aged 18-50 (39.5%) and >50 years (39.9%), p<0.0001. After SARS-CoV-2 (18.3%), rhinoviruses (10.5%) and influenza viruses (5.5%) were the most prevalent. SARS-CoV-2 positivity was lower in children <5 (4.3%) and 5-17 years (12.7%) than in adults aged 18-50 (19.3%) and >50 years (24.3%), p<0.0001. In contrast, rhinoviruses were most prevalent in children <5 years (28.7%), followed by children aged 5-17 (15.8%), adults aged 18-50 (8.3%) and >50 years (6.3%), p<0.0001. Four SARS-CoV-2 waves occurred, with 36.1%-52.4% SARS-CoV-2 positivity during peak months. Influenza infections were observed in both 2020 and 2021 during the rainy season as expected (peak positivity 16.4%-23.5%). Peaks of rhinovirus were asynchronous to the months when SARS-CoV-2 and influenza peaked. Conclusion: Our data show that many respiratory viruses continued to circulate during the COVID-19 pandemic in The Gambia, including human rhinoviruses, despite the presence of NPIs during the early stages of the pandemic, and influenza peaks during expected months.

A clinico-epidemiological profile, coinfections and outcome of patients with Influenza Like Illnesses (ILI) presenting to the emergency department during the COVID-19 pandemic.

Background: During the COVID-19 pandemic, many patients presented to the emergency department (ED) with features of Influenza-like illnesses (ILI) and with other atypical presentations. This study was done to determine the etiology, co-infections, and clinical profile of patients with ILI. Methods: This prospective observational study included all patients presenting to the ED with fever and/or cough, breathing difficulty, sore throat, myalgia, gastrointestinal complaints (abdominal pain/vomiting/diarrhea), loss of taste and altered sensorium or asymptomatic patients who resided in or travelled from containment zones, or those who had contact with COVID-19 positive patients during the first wave of the pandemic between April and August 2020. Respiratory virus screening was done on a subset of COVID-19 patients to determine co-infection. Results: During the study period, we recruited 1462 patients with ILI and 857 patients with the non-ILI presentation of confirmed COVID-19 infection. The mean age group of our patient population was 51.4 (SD: 14.9) years with a male predominance (n-1593; 68.7%). The average duration of symptoms was 4.1 (SD: 2.9) days. A sub-analysis to determine an alternate viral etiology was done in 293 (16.4%) ILI patients, where 54 (19.4%) patients had COVID 19 and co-infection with other viruses, of which Adenovirus (n-39; 14.0%) was the most common. The most common symptoms in the ILI-COVID-19 positive group (other than fever and/or cough and/or breathing difficulty) were loss of taste (n-385; 26.3%) and diarrhea (n- 123; 8.4%). Respiratory rate (27.5 (SD: 8.1)/minute: p-value < 0.001) and oxygen saturation (92.1% (SD: 11.2) on room air; p-value < 0.001) in the ILI group were statistically significant. Age more than 60 years (adjusted odds ratio (OR): 4.826 (3.348-6.956); p-value: <0.001), sequential organ function assessment score more than or equal to four (adjusted OR: 5.619 (3.526-8.957); p-value: <0.001), and WHO critical severity score (Adjusted OR: 13.812 (9.656-19.756); p-value: <0.001) were independent predictors of mortality. Conclusion: COVID-19 patients were more likely to present with ILI than atypical features. Co-infection with Adenovirus was most common. Age more than 60 years, SOFA score more than or equal to four and WHO critical severity score were independent predictors of mortality.

Mortality in Catalonia during the summer of 2022 and its relation with high temperatures and COVID-19 cases.

Purpose: To analyse the association between the mortality during the summer 2022 and either high temperatures or the COVID-19 wave with data from the Catalan Health Care System (7.8 million people). Methods: We performed a retrospective study using publicly available data of meteorological variables, influenza-like illness (ILI) cases (including COVID-19) and deaths. The study comprises the summer months of the years 2021 and 2022. To compare the curves of mortality, ILI and temperature we calculated the z-score of each series. We assessed the observed lag between curves using the cross-correlation function. Finally, we calculated the correlation between the z-scores using the Pearson correlation coefficient (R2). Results: During the study period, 33,967 deaths were reported in Catalonia (16,416 in the summer of 2021 and 17,551 in the summer of 2022). In 2022, the observed lag and the correlation between the z-scores of temperature and all-cause deaths was 3 days and R2 = 0.86, while between ILI and all-cause deaths was 22 days and R2 = 0.21. This high correlation between temperature and deaths increased up to 0.91 when we excluded those deaths reported as COVID-19 deaths, while the correlation between ILI and non-COVID-19 deaths decreased to -0.19. No correlation was observed between non-COVID deaths and temperature or ILI cases in 2021. Conclusion: Our study suggests that the main cause of the increase in deaths during summer 2022 in Catalonia was the high temperatures and its duration. The contribution of the COVID-19 seems to be limited.

Circulation of respiratory viruses during the COVID-19 pandemic in The Gambia

Background: In many countries, non-pharmaceutical interventions to limit severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission resulted in significant reductions in other respiratory viruses. However, similar data from Africa are limited. We explored the extent to which viruses such as influenza and rhinovirus co-circulated with SARS-CoV-2 in The Gambia during the COVID-19 pandemic. Methods: Between April 2020 and March 2022, respiratory viruses were detected using RT-PCR in nasopharyngeal swabs from 1397 participants with influenza-like illness. An assay to detect SARS-CoV-2 and a viral multiplex RT-PCR assay was used as previously described to detect influenza A and B, respiratory syncytial virus (RSV) A and B, parainfluenza viruses 1-4, human metapneumovirus (HMPV), adenovirus, seasonal coronaviruses (229E, OC43, NL63) and human rhinovirus. Result(s): Overall virus positivity was 44.2%, with prevalence higher in children <5 years (80%) compared to children aged 5-17 years (53.1%), adults aged 18-50 (39.5%) and >50 years (39.9%), p<0.0001. After SARS-CoV-2 (18.3%), rhinoviruses (10.5%) and influenza viruses (5.5%) were the most prevalent. SARS-CoV-2 positivity was lower in children <5 (4.3%) and 5-17 years (12.7%) than in adults aged 18-50 (19.3%) and >50 years (24.3%), p<0.0001. In contrast, rhinoviruses were most prevalent in children <5 years (28.7%), followed by children aged 5-17 (15.8%), adults aged 18-50 (8.3%) and >50 years (6.3%), p<0.0001. Four SARS-CoV-2 waves occurred, with 36.1%-52.4% SARS-CoV-2 positivity during peak months. Influenza infections were observed in both 2020 and 2021 during the rainy season as expected (peak positivity 16.4%-23.5%). Peaks of rhinovirus were asynchronous to the months when SARS-CoV-2 and influenza peaked. Conclusion(s): Our data show that many respiratory viruses continued to circulate during the COVID-19 pandemic in The Gambia, including human rhinoviruses, despite the presence of NPIs during the early stages of the pandemic, and influenza peaks during expected months.Copyright: © 2023 Jarju S et al.

A Cross-Sectional Comparative Characterization of Hematological Changes in Patients with COVID-19 Infection, Non-COVID Influenza-like Illnesses and Healthy Controls.

INTRODUCTION: Studies have documented the role of the "neutrophil-to-lymphocyte ratio" (NLR) in influenza virus infection. In addition, morphometric parameters derived from automated analyzers on the volume, scatter and conductivity of monocytes, neutrophils and lymphocytes in many viral etiologies have helped with their early differentiation. With this background, we aimed to characterize the hematological changes of coronavirus-positive cases and also compare them with the healthy controls and patients affected by non-COVID Influenza-like illnesses so that early isolation could be considered. MATERIAL AND METHODS: This was a cross-sectional analytical study carried out in the years 2020-2022. All cases with COVID-19 and non-COVID-19 Influenza-like illnesses and healthy controls above 18 years were included. Cases were diagnosed according to the WHO guidelines. All samples were processed on a Unicel DxH 800 (Beckman Coulter, California, USA) automated hematology analyzer. The demographic, clinical and regular hematological parameters along with additional parameters such as volume, conductivity and scatter (VCS) of the three groups were compared. RESULTS: The 169 COVID-19 cases were in the moderate to severe category. Compared with 140 healthy controls, the majority of the routine hematological values including the NLR (neutrophil-to-lymphocyte ratio) and PLR (platelet-to-lymphocyte ratio) showed statistically significant differences. A cutoff of an absolute neutrophil count of 4350 cell/cumm was found to have a sensitivity of 76% and specificity of 70% in differentiating moderate and severe COVID-19 cases from healthy controls. COVID-19 and the non-COVID-19 Influenza-like illnesses were similar statistically in all parameters except the PLR, mean neutrophilic and monocytic volume, scatter parameters in neutrophils, axial light loss in monocytes and NLR. Interestingly, there was a trend of higher mean volumes and scatter in neutrophils and monocytes in COVID-19 cases as compared to non-COVID-19 Influenza-like illnesses. CONCLUSION: We demonstrated morphological changes in neutrophils, monocytes and lymphocytes in COVID-19 infection and also non-COVID-19 Influenza-like illnesses with the help of VCS parameters. A cutoff for the absolute neutrophils count was able to differentiate COVID-19 infection requiring hospitalization from healthy controls and eosinopenia was a characteristic finding in cases with COVID-19 infection.

Auditor health and audit outcomes before COVID-19

This study examines whether influenza-like illnesses (ILIs), a potential threat to the conduct of public company audits, are associated with audit outcomes. Because the peak months of flu season overlap with audit busy season, audit offices most at risk of ILIs may be adversely affected. The demanding nature of audit busy season and the culture of audit firms may compel employees to go to work sick, a phenomenon known as presenteeism. When auditors go to work with flu-like symptoms, cognitive functioning is impaired, resulting in brain fog. This impairment may influence auditors' ability to exercise judgment and professional skepticism, leading to adverse outcomes. Using data collected from the Centers for Disease Control and Prevention (CDC) we find that the filing of audit reports is delayed and audit quality suffers in audit offices most at risk of influenza-like-illnesses. The observed effects of health impairments on company outputs have broad implications for both the audit profession and workplaces as a whole. © 2023 Elsevier Inc.

Circulation of respiratory viruses during the COVID-19 pandemic in The Gambia

Background: In many countries, non-pharmaceutical interventions to limit severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission resulted in significant reductions in other respiratory viruses. However, similar data from Africa are limited. We explored the extent to which viruses such as influenza and rhinovirus co-circulated with SARS-CoV-2 in The Gambia during the COVID-19 pandemic. Method(s): Between April 2020 and March 2022, respiratory viruses were detected using RT-PCR in nasopharyngeal swabs from 1397 participants with influenza-like illness. An assay to detect SARS-CoV-2 and a viral multiplex RT-PCR assay was used as previously described to detect influenza A and B, respiratory syncytial virus (RSV) A and B, parainfluenza viruses 1-4, human metapneumovirus (HMPV), adenovirus, seasonal coronaviruses (229E, OC43, NL63) and human rhinovirus. Result(s): Overall virus positivity was 44.2%, with prevalence higher in children <5 years (80%) compared to children aged 5-17 years (53.1%), adults aged 18-50 (39.5%) and >50 years (39.9%), p<0.0001. After SARS-CoV-2 (18.3%), rhinoviruses (10.5%) and influenza viruses (5.5%) were the most prevalent. SARS-CoV-2 positivity was lower in children <5 (4.3%) and 5-17 years (12.7%) than in adults aged 18-50 (19.3%) and >50 years (24.3%), p<0.0001. In contrast, rhinoviruses were most prevalent in children <5 years (28.7%), followed by children aged 5-17 (15.8%), adults aged 18-50 (8.3%) and >50 years (6.3%), p<0.0001. Four SARS-CoV-2 waves occurred, with 36.1%-52.4% SARS-CoV-2 positivity during peak months. Influenza infections were observed in both 2020 and 2021 during the rainy season as expected (peak positivity 16.4%-23.5%). Peaks of rhinovirus were asynchronous to the months when SARS-CoV-2 and influenza peaked. Conclusion(s): Our data show that many respiratory viruses continued to circulate during the COVID-19 pandemic in The Gambia, including human rhinoviruses, despite the presence of NPIs during the early stages of the pandemic, and influenza peaks during expected months.Copyright © 2022 Jarju S et al.

Assessing the impact of COVID-19 interventions on influenza-like illness in Beijing and Hong Kong: an observational and modeling study.

BACKGROUND: The impact of coronavirus diseases 2019 (COVID-19) related non-pharmaceutical interventions (NPIs) on influenza activity in the presence of other known seasonal driving factors is unclear, especially at the municipal scale. This study aimed to assess the impact of NPIs on outpatient influenza-like illness (ILI) consultations in Beijing and the Hong Kong Special Administrative Region (SAR) of China. METHODS: We descriptively analyzed the temporal characteristics of the weekly ILI counts, nine NPI indicators, mean temperature, relative humidity, and absolute humidity from 2011 to 2021. Generalized additive models (GAM) using data in 2011-2019 were established to predict the weekly ILI counts under a counterfactual scenario of no COVID-19 interventions in Beijing and the Hong Kong SAR in 2020-2021, respectively. GAM models were further built to evaluate the potential impact of each individual or combined NPIs on weekly ILI counts in the presence of other seasonal driving factors in the above settings in 2020-2021. RESULTS: The weekly ILI counts in Beijing and the Hong Kong SAR fluctuated across years and months in 2011-2019, with an obvious winter-spring seasonality in Beijing. During the 2020-2021 season, the observed weekly ILI counts in both Beijing and the Hong Kong SAR were much lower than those of the past 9 flu seasons, with a 47.5% [95% confidence interval (CI): 42.3%, 52.2%) and 60.0% (95% CI: 58.6%, 61.1%) reduction, respectively. The observed numbers for these two cities also accounted for only 40.2% (95% CI: 35.4%, 45.3%) and 58.0% (95% CI: 54.1%, 61.5%) of the GAM model estimates in the absence of COVID-19 NPIs, respectively. Our study revealed that, "Cancelling public events" and "Restrictions on internal travel" measures played an important role in the reduction of ILI in Beijing, while the "restrictions on international travel" was statistically most associated with ILI reductions in the Hong Kong SAR. CONCLUSIONS: Our study suggests that COVID-19 NPIs had been reducing outpatient ILI consultations in the presence of other seasonal driving factors in Beijing and the Hong Kong SAR from 2020 to 2021. In cities with varying local circumstances, some NPIs with appropriate stringency may be tailored to reduce the burden of ILI caused by severe influenza strains or other respiratory infections in future.

Wastewater Levels of Respiratory Syncytial Virus Associated with Influenza-like Illness Rates in Children-A Case Study in Larissa, Greece (October 2022-January 2023).

The emergence of the COVID-19 pandemic has led to significant progress in the field of wastewater-based surveillance (WBS) of respiratory pathogens and highlighted its potential for a wider application in public health surveillance. This study aimed to evaluate whether monitoring of respiratory syncytial virus (RSV) in wastewater can provide a comprehensive picture of disease transmission at the community level. The study was conducted in Larissa (Central Greece) between October 2022 and January 2023. Forty-six wastewater samples were collected from the inlet of the wastewater treatment plant of Larissa and analyzed with a real-time reverse transcription polymerase chain reaction (RT-PCR) based method. RSV and SARS-CoV-2 wastewater viral loads (genome copies/100,000 inhabitants) were analyzed against sentinel surveillance data on influenza-like illness (ILI) to identify potential associations. Univariate linear regression analysis revealed that RSV wastewater viral load (lagged by one week) and ILI notification rates in children up to 14 years old were strongly associated (std. Beta: 0.73 (95% CI: 0.31-1.14), p = 0.002, R2 = 0.308). A weaker association was found between SARS-CoV-2 viral load and ILI rates in the 15+ age group (std. Beta: 0.56 (95% CI: 0.06-1.05), p = 0.032, R2 = 0.527). The results support the incorporation of RSV monitoring into existing wastewater-based surveillance systems.

Coughs, colds and "freshers' flu" survey in the University of Cambridge, 2007-2008.

Universities provide many opportunities for the spread of infectious respiratory illnesses. Students are brought together into close proximity from all across the world and interact with one another in their accommodation, through lectures and small group teaching and in social settings. The COVID-19 global pandemic has highlighted the need for sufficient data to help determine which of these factors are important for infectious disease transmission in universities and hence control university morbidity as well as community spillover. We describe the data from a previously unpublished self-reported university survey of coughs, colds and influenza-like symptoms collected in Cambridge, UK, during winter 2007-2008. The online survey collected information on symptoms and socio-demographic, academic and lifestyle factors. There were 1076 responses, 97% from University of Cambridge students (5.7% of the total university student population), 3% from staff and <1% from other participants, reporting onset of symptoms between September 2007 and March 2008. Undergraduates are seen to report symptoms earlier in the term than postgraduates; differences in reported date of symptoms are also seen between subjects and accommodation types, although these descriptive results could be confounded by survey biases. Despite the historical and exploratory nature of the study, this is one of few recent detailed datasets of influenza-like infection in a university context and is especially valuable to share now to improve understanding of potential transmission dynamics in universities during the current COVID-19 pandemic.

Vitamin D3 Supplementation at 5000 IU Daily for the Prevention of Influenza-like Illness in Healthcare Workers: A Pragmatic Randomized Clinical Trial.

Vitamin D supplementation has been shown to reduce the incidence of acute respiratory infections in populations at risk. The COVID-19 pandemic has highlighted the importance of preventing viral infections in healthcare workers. The aim of this study was to assess the hypothesis that vitamin D3 supplementation at 5000 IU daily reduces influenza-like illness (ILI), including COVID-19, in healthcare workers. We conducted a prospective, controlled trial at a tertiary university hospital. A random group of healthcare workers was invited to receive 5000 IU daily vitamin D3 supplementation for nine months, while other random healthcare system workers served as controls. All healthcare workers were required to self-monitor and report to employee health for COVID-19 testing when experiencing symptoms of ILI. COVID-19 test results were retrieved. Incidence rates were compared between the vitamin D and control groups. Workers in the intervention group were included in the analysis if they completed at least 2 months of supplementation to ensure adequate vitamin D levels. The primary analysis compared the incidence rate of all ILI, while secondary analyses examined incidence rates of COVID-19 ILI and non-COVID-19 ILI. Between October 2020 and November 2021, 255 healthcare workers (age 47 ± 12 years, 199 women) completed at least two months of vitamin D3 supplementation. The control group consisted of 2827 workers. Vitamin D3 5000 IU supplementation was associated with a lower risk of ILI (incidence rate difference: -1.7 × 10-4/person-day, 95%-CI: -3.0 × 10-4 to -3.3 × 10-5/person-day, p = 0.015) and a lower incidence rate for non-COVID-19 ILI (incidence rate difference: -1.3 × 10-4/person-day, 95%-CI -2.5 × 10-4 to -7.1 × 10-6/person-day, p = 0.038). COVID-19 ILI incidence was not statistically different (incidence rate difference: -4.2 × 10-5/person-day, 95%-CI: -10.0 × 10-5 to 1.5 × 10-5/person-day, p = 0.152). Daily supplementation with 5000 IU vitamin D3 reduces influenza-like illness in healthcare workers.

Roles for Pathogen Interference in Influenza Vaccination, with Implications to Vaccine Effectiveness (VE) and Attribution of Influenza Deaths.

Pathogen interference is the ability of one pathogen to alter the course and clinical outcomes of infection by another. With up to 3000 species of human pathogens the potential combinations are vast. These combinations operate within further immune complexity induced by infection with multiple persistent pathogens, and by the role which the human microbiome plays in maintaining health, immune function, and resistance to infection. All the above are further complicated by malnutrition in children and the elderly. Influenza vaccination offers a measure of protection for elderly individuals subsequently infected with influenza. However, all vaccines induce both specific and non-specific effects. The specific effects involve stimulation of humoral and cellular immunity, while the nonspecific effects are far more nuanced including changes in gene expression patterns and production of small RNAs which contribute to pathogen interference. Little is known about the outcomes of vaccinated elderly not subsequently infected with influenza but infected with multiple other non-influenza winter pathogens. In this review we propose that in certain years the specific antigen mix in the seasonal influenza vaccine inadvertently increases the risk of infection from other non-influenza pathogens. The possibility that vaccination could upset the pathogen balance, and that the timing of vaccination relative to the pathogen balance was critical to success, was proposed in 2010 but was seemingly ignored. Persons vaccinated early in the winter are more likely to experience higher pathogen interference. Implications to the estimation of vaccine effectiveness and influenza deaths are discussed.

The impact of COVID-19 pandemic on influenza surveillance: A systematic review and meta-analysis.

Background: Influenza activity was reported to be below the seasonal levels during the Coronavirus disease-2019 (COVID-19) pandemic globally. However, during the severe acute respiratory syndrome corona virus-2 outbreak, the routine real-time surveillance of influenza-like illness and acute respiratory infection was adversely affected due to the changes in priorities, economic constraints, repurposing of hospitals for COVID care, and closure of outpatient services. Methods: A systematic review and meta-analysis were carried out to assess the pooled proportion of symptomatic cases tested for influenza virus before the current pandemic in 2019 and during the pandemic in 2020/21. An electronic search of PubMed/MEDLINE, Scopus, and Google Scholar was carried out for the articles reporting the impact of the COVID-19 pandemic on influenza surveillance among humans using search terms. The study was designed based on Preferred Reporting Items for Systematic Reviews and Meta-analyses guidelines and the meta-analysis was performed to synthesize the pooled proportion of patients sampled for influenza with 95% confidence interval (CI). Results: The nine qualified studies from the WHO European region, Canada, Japan, Germany, Italy, Spain, South Africa, and the United States were pooled by random-effects meta-analysis. The overall pooled proportion of symptomatic cases sampled for influenza surveillance before and during the pandemic was 2.38% (95% CI 2.08%-2.67%) and 4.18% (95% CI 3.8%-4.52%), respectively. However, the pooled proportion of samples tested for influenza before the pandemic was 0.69% (95% CI 0.45%-0.92%) and during the pandemic was 0.48% (95% CI 0.28%-0.68%) when studies from Canada were excluded. Conclusion: The meta-analysis concludes that globally there was a decline in influenza surveillance during the COVID-19 pandemic except in Canada.

Evaluation Of Random Forest Model on Influenza Like Illness (ILI) Surveillance Based on Patients Attending Fever OPD During COVID-19 Pandemic at Tertiary Care Hospital, In Raigad District, Maharashtra, India

Introduction: The machine learning and artificial intelligence tools, party and random forest can be used to evaluate surveillance data for better outcomes. The primary objective of the study was to evaluate the utility and reliability of machine learning and artificial intelligence model primary data for the Influenzas Like illness (ILI) Surveillance of patients attending fever OPD in a tertiary care hospital during covid 19 pandemic. The secondary objective was to estimate model statistics to measure the effect of parameters. Methodology: This is a secondary data analysis study based on surveillance data in the tertiary care hospital attached to medical college. The data of 3723 cases was collected by Surveillance team for Influenzas Like Illness (ILI) under Department of Community Medicine in Fever OPD during covid pandemic from 23 March 2020 to 30 June 2020. Data consisted (11) variables. Data was analysed using R Software (4.2.2). Machine learning (ML) and Artificial Intelligence tool party and random forest were applied. Result(s): The random forest model performed better than Party model with model accuracy of 0.9557, AUC of random forest model were 87.4% (sensitivity 0.9533, specificity 0.9685), 89.7% (sensitivity 0.9059, specificity 0.9957) and 88.3% (Sensitivity 0.965, Specificity 0.9527) for confirmed, probable and suspected with different cut-offs. The model found Severity of Patient (Mild, Moderate, Severe), the day of Fever OPD Visit, nature of illness (is asymptomatic?) and age of patient as the most significant factors in decreasing order by mean decrease in Accuracy while the Severity of Patient (Mild, Moderate, Severe), the day of Fever OPD Visit, age of patient and number of symptomatic Complaint (NOC) were found the most significant factors in decreasing order by mean decrease in Gini to predict Covid-19 Test Results. Conclusion(s): The party algorithm was consistent for train and test dataset while for the random forest results were good on train dataset while same model had seen difficulty in prediction class for the test dataset. Copyright © 2022 Wolters Kluwer Medknow Publications. All rights reserved.

Short-term effects of ambient particulate matter (PM1, PM2.5 and PM10) on influenza-like illness in Guangzhou, China.

BACKGROUND: Particulate matter (PM) has been linked to respiratory infections in a growing body of evidence. Studies on the relationship between ILI (influenza-like illness) and PM1 (particulate matter with aerodynamic diameter ≤1 µm) are, however, scarce. The purpose of this study was to investigate the effects of PM on ILI in Guangzhou, China. METHODS: Daily ILI cases, air pollution records (PM1, PM2.5, PM10 and gaseous pollutants), and metrological data between 2014 and 2019 were gathered from Guangzhou, China. To estimate the risk of ILI linked with exposure to PM pollutants, a quasi-Poisson regression was used. Additionally, subgroup analyses stratified by gender, age and season were carried out. RESULTS: For each 10 µg/m3 increase of PM1 and PM2.5 over the past two days (lag01), and PM10 over the past three days (lag02), the relative risks (RR) of ILI were 1.079 (95% confidence interval [CI]: 1.050, 1.109), 1.044 (95% CI: 1.027, 1.062) and 1.046 (95% CI: 1.032, 1.059), respectively. The estimated risks for men and women were substantially similar. The effects of PM pollutants between male and female were basically equivalent. People aged 15-24 years old were more susceptive to PM pollutants. CONCLUSIONS: It implies that PM1, PM2.5 and PM10 are all risk factors for ILI, the health impacts of PM pollutants vary by particle size. Reducing the concentration of PM1 needs to be considered when generating a strategy to prevent ILI.

Bedside Scoring System for Predicting Adverse Outcomes Among Patients Suffering From SARS-CoV-2 Infection.

Aim To develop a clinical risk score to predict adverse outcomes among diabetic hospitalized COVID-19 patients Methods The data was collected retrospectively from patients hospitalized with the SARS-CoV-2 virus at Sri Ramachandra Institute of Higher education and research. It integrated independent variables such as sex, age, glycemic status, socioeconomic status, and preexisting lung conditions. Each variable was assigned a value and the final score was calculated as a sum of all the variables. The final score was then compared with patient outcomes. The patients were scored from 0 to 8 and a score of 3 or more was considered as being at greater risk for developing complications. Number of mortalities in each group, any clinical deterioration requiring ICU admission, and the number of patients requiring a prolonged hospital stay of more than 10 days in each group were noted and the results compared. Results Higher blood glucose levels and preexisting lung conditions like chronic obstructive pulmonary disease (COPD), asthma, and pulmonary tuberculosis have been associated with a higher risk of developing complications related to SARS-CoV-2 illness. Of the 5023 patients enrolled in the study, 2402 had a score of 2 or below, and 2621 had a score of 3 or above. Among patients with a score of 2 or below 1.7% of the patients contracted a severe disease resulting in death. 2.9% were shifted to ICU, but recovered and 12.2% of patients had a prolonged hospital stay. Of those with a score of 3 or greater, 5.1% died, 7.36% were shifted to ICU, but recovered, and 19.5% required a prolonged hospital stay. The observed results were analyzed using the Chi-square test and were found to be significant at a p-level of 0.0001. Conclusion This clinical risk score has been built with routinely available data to help predict adverse outcomes in diabetic patients hospitalized with the SARS-CoV-2 virus. It is a good tool for resource-limited areas as it uses readily available data. It can also be used for other severe acute respiratory illnesses or influenza-like illnesses.

High Influenza Vaccine Effectiveness and Absence of Increased Influenza-like-Illness Epidemic Activity in the 2021-2022 Influenza Season in Catalonia (Spain) Based on Surveillance Data Collected by Sentinel Pharmacies.

Influenza surveillance and influenza vaccination are the key activities for preventing and controlling influenza epidemics. The study assessed the influenza surveillance and influenza vaccination data obtained from sentinel pharmacies of Catalonia, Spain, in the 2021-2022 influenza season. The sentinel pharmacies were selected from all community pharmacies to report all influenza-like illness (ILI) cases detected during the 2021-2022 influenza season and collect influenza surveillance and influenza vaccination data. The ILI cases were identified based on European Centre for Disease Control (ECDC) criteria. The moving epidemic method (MEM) was used to assess the ILI epidemic activity. The screening method was used to assess influenza vaccination effectiveness in patients aged 65-or-more years old. The sentinel pharmacies reported 212 ILI cases with a negative COVID-19 test and a total number of 412 ILI cases. An absence of increased ILI epidemic activity was observed in the 2021-2022 influenza season based on two criteria: (1) Number of ILI cases reported per week in the 2021-2022 influenza season significantly lower than the MEM-based epidemic threshold. (2) Mean number of ILI cases reported per week in the 2021-2022 influenza season significantly lower than during the ILI/influenza epidemic periods detected from 2017 to 2020 using the same methodology. Influenza vaccination was effective in preventing ILI among patients aged 65-or-more-years old. The absence of the influenza epidemic during the 2021-2022 influenza season could be explained by influenza vaccination and COVID-19 prevention measures (wearing face masks, social distancing). The sentinel pharmacies provided influenza surveillance data not provided by traditional influenza surveillance systems.