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.

Epidemiology of Non-SARS-CoV2 Human Coronaviruses (HCoVs) in People Presenting with Influenza-like Illness (ILI) or Severe Acute Respiratory Infections (SARI) in Senegal from 2012 to 2020.

In addition to emerging coronaviruses (SARS-CoV, MERS, SARS-CoV-2), there are seasonal human coronaviruses (HCoVs): HCoV-OC43, HCoV-229E, HCoV-NL63 and HCoV-HKU1. With a wide distribution around the world, HCoVs are usually associated with mild respiratory disease. In the elderly, young children and immunocompromised patients, more severe or even fatal respiratory infections may be observed. In Africa, data on seasonal HCoV are scarce. This retrospective study investigated the epidemiology and genetic diversity of seasonal HCoVs during nine consecutive years of influenza-like illness surveillance in Senegal. Nasopharyngeal swabs were collected from ILI outpatients or from SARI hospitalized patients. HCoVs were diagnosed by qRT-PCR and the positive samples were selected for molecular characterization. Among 9337 samples tested for HCoV, 406 (4.3%) were positive: 235 (57.9%) OC43, 102 (25.1%) NL63, 58 (14.3%) 229E and 17 (4.2%) HKU1. The four types circulated during the study period and a peak was noted between November and January. Children under five were the most affected. Co-infections were observed between HCoV types (1.2%) or with other viruses (76.1%). Genetically, HCoVs types showed diversity. The results highlighted that the impact of HCoVs must be taken into account in public health; monitoring them is therefore particularly necessary both in the most sensitive populations and in animals.

An assessment of the current epidemiological and laboratory capacities for influenza-like illnesses and severe acute respiratory infection surveillance, Yemen 2022.

Background and Objectives: We aim to re-activate influenza sentinel surveillance system in Yemen after disruption related to repurposing for COVID-19 pandemic. WHO Country Office (CO) in collaboration with Yemen's Ministry of Public Health and Population (MOPH&P) jointly conducted an assessment mission to assess the current situation of the influenza sentinel surveillance system and assess its capacity to detect influenza epidemics and monitor trends in circulating influenza and other respiratory viruses of epidemic and pandemic potential. This study presents the results of the assessment for three sentinel sites located in Aden, Taiz, and Hadramout/Mukalla. Methodology: A mixed methods approach was used to guide the assessment process and to help achieve the objectives. Data were collected as follows: desk review of the sentinel sites records and data; interviews with stakeholders, including key informants and partners; and direct observation through field visits to the sentinel sites, MOPH&P and the Central Public Health Laboratory (CPHL). Two assessment checklists were used: assessment of sentinel sites for SARI surveillance, and checklist for assessment of availability of SARI sentinel surveillance. Results and Conclusion: COVID-19 has affected health systems and services, and this was demonstrated in this assessment. The influenza sentinel surveillance system in Yemen is not effectively functional; however, there is plenty of room for improvement if investment in the system's restructuring, training, building technical and laboratory capacities, and conducting continuous and regular supervision visits.

SARS-CoV-2 Surveillance Through China Influenza Surveillance Information System - China, December 1, 2022 to February 12, 2023.

Introduction: The World Health Organization (WHO) proposed using influenza surveillance systems to carry out coronavirus disease 2019 (COVID-19) surveillance due to the similarity between the two diseases in some respiratory symptoms. To assess the prevalence of COVID-19, we analyzed the influenza-like illness (ILI) and positive rate of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) detections in ILI patients reported to the influenza Surveillance Information System (CNISIS) since late 2022. Methods: Data related to ILI were reported by national surveillance sentinel hospitals. Positive testing for SARS-CoV-2 and influenza viruses was conducted using real-time reverse transcription polymerase chain reaction (rRT-PCR) detection by the national influenza surveillance network laboratories. Surveillance data were reported to CNISIS. Results: Beginning on December 12, 2022 (Week 50), the ILI percentage increased dramatically, peaking in Week 51 at 12.1%. Subsequently, the ILI percentage began to decline rapidly from Week 52, 2022, and by Week 6, 2023 (February 6-12), the ILI and ILI percentage had returned to the levels observed at the beginning of December 2022. From December 1, 2022 to February 12, 2023, 115,844 specimens were tested for both SARS-CoV-2 and influenza virus. Of these, 30,381 (26.2%) were positive for SARS-CoV-2 and 1,763 (1.5%) were positive for influenza virus. The positive rate of SARS-CoV-2 tests peaked at 74.1% around December 23 and 25. Conclusions: Sentinel-based surveillance, previously established for influenza, is an effective way to track the circulation trend of SARS-CoV-2 during community-level epidemics. There was no co-prevalence of SARS-CoV-2 and influenza virus during the outbreak of SARS-CoV-2, even during the winter influenza season. However, it is important to remain vigilant for the potential rise of influenza activities following the COVID-19 epidemic.

Evaluation of pharmacist guided intervention using procalcitonin and respiratory virus testing.

INTRODUCTION: Acute respiratory infections make up a sizable percentage of emergency department (ED) visits and many result in antibiotics being prescribed. Procalcitonin (PCT) has been found to reduce antibiotic use in both outpatient and critical care settings, yet remains underused in the ED. This study aimed to evaluate whether point of care molecular influenza and Respiratory Syncytial Virus (RSV) testing, PCT, and a pharmacist driven educational intervention in aggregate optimizes antibiotic and antiviral prescribing in the ED setting. METHODS: A randomized trial of the Cobas Liat Flu/RSV Assay, procalcitonin, and the use of pharmacist-led education in patients 0-50 years of age being seen in the ED for Influenza Like Illness (ILI) or acute respiratory illness. The study enrolled 200 ED patients between March 2018 and April 2022. RESULTS: There was little difference in antibiotic or antiviral prescribing between the intervention and control groups in this study (39%-32% = 7.0%, 95% CI: -6.2, 20.2, P = 0.30). However, a post-hoc analysis of the use of procalcitonin showed results were used as indicated in the ED (P = 0.001). CONCLUSION: PCT can be used in both adult and pediatric populations to help guide the decision of whether to treat with antibiotics in the ED setting. Pharmacist guided education may not be a driving factor.

Impact of air pollutants on influenza-like illness outpatient visits under COVID-19 pandemic in the subcenter of Beijing, China.

This study aimed to explore the association between air pollutants and outpatient visits for influenza-like illnesses (ILI) under the coronavirus disease 2019 (COVID-19) stage in the subcenter of Beijing. The data on ILI in the subcenter of Beijing from January 1, 2018 to December 31, 2020 were obtained from the Beijing Influenza Surveillance Network. A generalized additive Poisson model was applied to examine the associations between the concentrations of air pollutants and daily outpatient visits for ILI when controlling meteorological factors and temporal trend. A total of 171 943 ILI patients were included. In the pre-coronavirus disease 2019 (COVID-19) stage, an increased risk of ILI outpatient visits was associated to a high air quality index (AQI) and the high concentrations of particulate matter less than 2.5 (PM2.5 ), particulate matter 10 (PM10 ), sulphur dioxide (SO2 ), nitrogen dioxide (NO2 ), and carbon monoxide (CO), and a low concentration of ozone (O3 ) on lag0 day and lag1 day, while a higher increased risk of ILI outpatient visits was observed by the air pollutants in the COVID-19 stage on lag0 day. Except for PM10 , the concentrations of other air pollutants on lag1 day were not significantly associated with an increased risk of ILI outpatient visits during the COVID-19 stage. The findings that air pollutants had enhanced immediate effects and diminished lag-effects on the risk of ILI outpatient visits during the COVID-19 pandemic, which is important for the development of public health and environmental governance strategies.

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.

Exploring the drop in flu cases during the 2020-2021 season: The Italian case study.

PURPOSE: To explore the 2020-2021 influenza season by describing the case of Italy. METHODS: FluNet was searched for Italian data on virological samples. French, German, and Spanish data were collected for comparison. InfluNet was used for Italian epidemiological data on influenza-like illness (ILI). Data were extracted for the period from the 42nd week of 2020 to the 16th week of 2021 and for the previous 5-year period. The Containment and Health Index were used to describe the containment measures. RESULTS: Among 6818 samples, 0% were positive in Italy in the 2020-2021 season (28.8% in the previous 5-year period; the percentage change in the total number of tested specimens was -51.3%). In France, Germany, and Spain, the percentage change was -23%, -7%, and -61%, respectively. The Italian ILI incidence remained below the baseline levels (mean 0.0144/100,000 inhabitants; range 0.0085-0.0204). In the previous 5-year period, the mean incidence was 0.041/100,000 inhabitants. With the increase in containment measures, a deflection of ILI incidence was described (P = .015). CONCLUSIONS: Despite the reduced number of collected specimens compared to previous seasons and a slight rise in influenza vaccination rates, containment measures represent the most likely factor that helped to reduce cases in the 2020-2021 influenza season in Italy.

Intrest in influenza and influenza like illnesses in Poland 2016-2021 based on Google Trend's data analysis.

INTRODUCTION: Influenza and Influenza Like Illness (ILI) are viral diseases that show seasonality in incidence. Influenza can be effectively prevented with immunization. Vaccination is recommended for risk groups, especially for the elderly, immunocompromised population, with chronic diseases and pregnant women. AIM OF THE STUDY: The purpose of the study was to assess interest in influenza and influenza vaccine in Poland by users of the Google search engine over the last five years using the Google Trends (GT) tool. MATERIAL AND METHODS: Data collected from Google Trends (GT) over a five-year period beginning on 11/9/2016 was analyzed. The time trend analysis focused at four phrases in Polish "grypa", "grypa objawy", "szczepionka przeciw grypie" and "szczepionka na grype", which can be translated into English, as; "flu", "flu symptoms", "flu vaccine", and a colloquial phrase meaning "against the flu vaccine". RESULTS: Before the outbreak of the COVID-19 pandemic, a seasonal increase in inquiries is evident, mimicking the increase in influenza and ILI cases or an increase in interest in the topic during the season in which prophylaxis is carried out using available vaccines. During the COVID-19 pandemic, the seasonal interest in the above topic was disrupted. CONCLUSIONS: During the COVID-19 pandemic, there were changes in the search terms in Polish. This included the timing and amount of queries related to influenza-themed expressions. During the COVID-19 pandemic, there was an increase in influenza and ILI queries during the period of increased incidence of COVID-19.

Rapidly adapting primary care sentinel surveillance across seven countries in Europe for COVID-19 in the first half of 2020: strengths, challenges, and lessons learned.

As the COVID-19 pandemic began in early 2020, primary care influenza sentinel surveillance networks within the Influenza - Monitoring Vaccine Effectiveness in Europe (I-MOVE) consortium rapidly adapted to COVID-19 surveillance. This study maps system adaptations and lessons learned about aligning influenza and COVID-19 surveillance following ECDC / WHO/Europe recommendations and preparing for other diseases possibly emerging in the future. Using a qualitative approach, we describe the adaptations of seven sentinel sites in five European Union countries and the United Kingdom during the first pandemic phase (March-September 2020). Adaptations to sentinel systems were substantial (2/7 sites), moderate (2/7) or minor (3/7 sites). Most adaptations encompassed patient referral and sample collection pathways, laboratory testing and data collection. Strengths included established networks of primary care providers, highly qualified testing laboratories and stakeholder commitments. One challenge was the decreasing number of samples due to altered patient pathways. Lessons learned included flexibility establishing new routines and new laboratory testing. To enable simultaneous sentinel surveillance of influenza and COVID-19, experiences of the sentinel sites and testing infrastructure should be considered. The contradicting aims of rapid case finding and contact tracing, which are needed for control during a pandemic and regular surveillance, should be carefully balanced.

Vaccination policies for healthcare personnel: Current challenges and future perspectives.

Healthcare personnel (HCP) are at occupational risk for acquisition of several vaccine-preventable diseases and transmission to patients. Vaccinations of HCP are justified to confer them immunity but also to protect susceptible patients and healthcare services from outbreaks, HCP absenteeism and presenteeism. Mandatory vaccination policies for HCP are increasingly adopted and achieve high and sustainable vaccination rates in short term. In this article we review the scientific evidence for HCP vaccination. We also address issues pertaining to vaccination policies for HCP and present the challenges of implementation of mandatory versus voluntary vaccination policies. Finally, we discuss the issue of mandatory vaccination of HCP against COVID-19.

Trends in Influenza Infections in Three States of India from 2015-2021: Has There Been a Change during COVID-19 Pandemic?

The COVID-19 pandemic and public health response to the pandemic has caused huge setbacks in the management of other infectious diseases. In the present study, we aimed to (i) assess the trends in numbers of samples from patients with influenza-like illness and severe acute respiratory syndrome tested for influenza and the number and proportion of cases detected from 2015-2021 and (ii) examine if there were changes during the COVID-19 period (2020-2021) compared to the pre-COVID-19 period (2015-2019) in three states of India. The median (IQR) number of samples tested per month during the pre-COVID-19 period was 653 (395-1245), compared to 27 (11-98) during the COVID-19 period (p value < 0.001). The median (IQR) number of influenza cases detected per month during the pre-COVID-19 period was 190 (113-372), compared to 29 (27-30) during the COVID-19 period (p value < 0.001). Interrupted time series analysis (adjusting for seasonality and testing charges) confirmed a significant reduction in the total number of samples tested and influenza cases detected during the COVID-19 period. However, there was no change in the influenza positivity rate between pre-COVID-19 (29%) and COVID-19 (30%) period. These findings suggest that COVID-19-related disruptions, poor health-seeking behavior, and overburdened health systems might have led to a reduction in reported influenza cases rather than a true reduction in disease transmission.

AYUSH 64, a polyherbal Ayurvedic formulation in Influenza-like illness - Results of a pilot study.

BACKGROUND: Influenza-like Illness (ILI) refers to a wide range of viral infections with an important cause of morbidity and mortality worldwide. The global incidence of ILI is estimated at 5-10% in adults and 20-30% in children. In India influenza accounts for 20-42% of monthly acute medical illness hospitalizations during the peak rainy season. AYUSH-64, a poly-herbal drug, is in practice for 40 years for various clinical conditions like fevers, microfilaremia, and inflammatory conditions. OBJECTIVE: A pilot study was conducted to evaluate the safety and efficacy of Ayurvedic formulation, AYUSH-64 in clinically diagnosed ILI for accelerating the recovery. MATERIAL AND METHODS: A prospective, open-label, nonrandomized, single group, single-center pilot clinical study with pre-test and post-test design was conducted at Raja Ramdeo Anandilal Podar Central Ayurveda Research Institute for Cancer, Mumbai, an institute of Central Council for Research in Ayurvedic Sciences (CCRAS) between June 2018 and July 2019. A total of 38 participants of clinically diagnosed ILI (18-65 years) were studied with an one-week intervention of 'AYUSH 64' in a dose of 3 gm/day and three weeks post-treatment observation period. Assessment of parameters viz. improvement in the symptoms of ILI, frequency of usage of acetaminophen, antihistaminic and cough syrup, hematology, liver function and kidney function tests along with incidence of secondary complications, and time to return to a normal routine was done. RESULTS: One-week intervention of AYUSH 64 helped to recover from ILI symptoms with reduced frequency of usage of acetaminophen and antihistaminic. The intervention was safe on hematology and biochemical parameters. No serious adverse effects were observed during the study. CONCLUSION: AYUSH 64 along-with standard care in ILI is safe and efficacious and this may be used in other viral infections with pyrexia as add-on to standard care for early recovery and better outcome.

Distinguishing viruses responsible for influenza-like illness.

The many respiratory viruses that cause influenza-like illness (ILI) are reported and tracked as one entity, defined by the CDC as a group of symptoms that include a fever of 100 degrees Fahrenheit, a cough, and/or a sore throat. In the United States alone, ILI impacts 9-49 million people every year. While tracking ILI as a single clinical syndrome is informative in many respects, the underlying viruses differ in parameters and outbreak properties. Most existing models treat either a single respiratory virus or ILI as a whole. However, there is a need for models capable of comparing several individual viruses that cause respiratory illness, including ILI. To address this need, here we present a flexible model and simulations of epidemics for influenza, RSV, rhinovirus, seasonal coronavirus, adenovirus, and SARS/MERS, parameterized by a systematic literature review and accompanied by a global sensitivity analysis. We find that for these biological causes of ILI, their parameter values, timing, prevalence, and proportional contributions differ substantially. These results demonstrate that distinguishing the viruses that cause ILI will be an important aspect of future work on diagnostics, mitigation, modeling, and preparation for future pandemics.

Respiratory viral infections other than SARS CoV-2 among the North Indian patients presenting with acute respiratory illness during the first COVID-19 wave.

Acute respiratory infections due to viral or bacterial etiology can cause 60 deaths per one lakh population. Viral etiology is more common as compared to bacterial, but lack of definite diagnosis leads to increased usage of empirical antibiotics. During the first wave of the COVID-19 pandemic, there was a need to identify co-infections especially in severe acute respiratory illness (SARI) patients to identify it as one of the cofactors for increased severity of illness and to identify the causative agents in COVID-19 negative individuals. The SARS CoV-2 real time PCR was carried out using ICMR approved kits and the other respiratory viruses were detected using the multiplex commercially available real time  kit. A total of 186 patients presenting with either SARI (89.8%) or influenza like illness (10.2%) were included in the study. Out of these, 43 (23.1%) were positive for SARS CoV-2 RNA and 2 (4.6%) patients with SARI showed concomitant infection with either human rhinovirus or human respiratory syncytial virus . Out of 143 patients negative for SARS CoV-2, 35 (24.5%) were positive for one or more microbial infections and 28 (19.6%) infected with other respiratory viral infection most common being human rhinovirus. The results suggest that viral coinfections are significantly higher among COVID-19 negative individuals (24.5% vs 4.6%) presenting with respiratory illness as compared to COVID-19 positive individuals possibly due to viral interference and competitive advantage of SARS-CoV-2 in modulating the host immunity. Further detailed research is required for the understanding of mechanisms of viral co-infection.

The prior infection with SARS-CoV-2 study (PICOV) in nursing home residents and staff - study protocol description and presentation of preliminary findings on symptoms.

BACKGROUND: The COVID-19 pandemic, caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has presented itself as one of the most important health concerns of the 2020's, and hit the geriatric population the hardest. The presence of co-morbidities and immune ageing in the elderly lead to an increased susceptibility to COVID-19, as is the case for other influenza-like illnesses (ILI) or acute respiratory tract infections (ARI). However, little is known, about the impact of a previous or current infection on the other in terms of susceptibility, immune response, and clinical course. The aim of the "Prior Infection with SARS-COV-2" (PICOV) study is to compare the time to occurrence of an ILI or ARI between participants with a confirmed past SARS-CoV-2 infection (previously infected) and those without a confirmed past infection (naïve) in residents and staff members of nursing homes. This paper describes the study design and population characteristics at baseline. METHODS: In 26 Belgian nursing homes, all eligible residents and staff members were invited to participate, resulting in 1,226 participants. They were classified as naïve or previously infected based on the presence of detectable SARS-CoV-2 antibodies and/or a positive RT-qPCR result before participation in the study. Symptoms from a prior SARS-CoV-2 infection between March and August 2020 were compared between previously infected residents and staff members. RESULTS: Infection naïve nursing home residents reported fewer symptoms than previously infected residents: on average 1.9 and 3.1 symptoms, respectively (p = 0.016). The same effect was observed for infection naïve staff members and previously infected staff members (3.1 and 6.1 symptoms, respectively; p <0.0001). Moreover, the antibody development after a SARS-CoV-2 infection differs between residents and staff members, as previously infected residents tend to have a higher rate of asymptomatic cases compared to previously infected staff members (20.5% compared to 12.4%; p <0.0001). CONCLUSIONS: We can postulate that COVID-19 disease development and symptomatology are different between a geriatric and younger population. Therefore, the occurrence and severity of a future ILI and/or ARI might vary from resident to staff.

Burden and seasonality of medically attended influenza like illness (ILI) in Ethiopia, 2012 to 2017.

BACKGROUND: The influenza virus spreads rapidly around the world in seasonal epidemics, resulting in significant morbidity and mortality. Influenza-related incidence data are limited in many countries in Africa despite established sentinel surveillance. This study aimed to address the information gap by estimating the burden and seasonality of medically attended influenza like illness in Ethiopia. METHOD: Influenza sentinel surveillance data collected from 3 influenza like illness (ILI) and 5 Severe Acute Respiratory Illness (SARI) sites from 2012 to 2017 was used for analysis. Descriptive statistics were applied for simple analysis. The proportion of medically attended influenza positive cases and incidence rate of ILI was determined using total admitted patients and catchment area population. Seasonality was estimated based on weekly trend of ILI and predicted threshold was done by applying the "Moving Epidemic Method (MEM)". RESULT: A total of 5715 medically attended influenza suspected patients who fulfills ILI and SARI case definition (77% ILI and 23% SARI) was enrolled. Laboratory confirmed influenza virus (influenza positive case) among ILI and SARI suspected case was 25% (1130/4426) and 3% (36/1289). Of which, 65% were influenza type A. The predominantly circulating influenza subtype were seasonal influenza A(H3N2) (n = 455, 60%) and Influenza A(H1N1)pdm09 (n = 293, 38.81%). The estimated mean annual influenza positive case proportion and ILI incidence rate was 160.04 and 52.48 per 100,000 population. The Incidence rate of ILI was higher in the age group of 15-44 years of age ['Incidence rate (R) = 254.6 per 100,000 population', 95% CI; 173.65, 335.55] and 5-14 years of age [R = 49.5, CI 95%; 31.47, 130.43]. The seasonality of influenza has two peak seasons; in a period from October-December and from April-June. CONCLUSION: Significant morbidity of influenza like illness was observed with two peak seasons of the year and seasonal influenza A (H3N2) remains the predominantly circulating influenza subtype. Further study need to be considered to identify potential risks and improving the surveillance system to continue early detection and monitoring of circulating influenza virus in the country has paramount importance.

FluWatchers: Evaluation of a crowdsourced influenza-like illness surveillance application for Canadian influenza seasons 2015-2016 to 2018-2019.

BACKGROUND: Sentinel influenza-like illness (ILI) surveillance is an essential component of a comprehensive influenza surveillance program. Community-based ILI surveillance systems that rely solely on sentinel healthcare practices omit important segments of the population, including those who do not seek medical care. Participatory surveillance, which relies on community participation in surveillance, may address some limitations of traditional ILI systems. OBJECTIVE: We aimed to evaluate FluWatchers, a crowdsourced ILI application developed to complement and complete ILI surveillance in Canada. METHODS: Using established frameworks for surveillance evaluations, we assessed the acceptability, reliability, accuracy and usefulness of the FluWatchers system 2015-2016, through 2018-2019. Evaluation indicators were compared against national surveillance indicators of ILI and of laboratory confirmed respiratory virus infections. RESULTS: The acceptability of FluWatchers was demonstrated by growth of 50%-100% in season-over-season participation, and a consistent season-over-season retention of 80%. Reliability was greater for FluWatchers than for our traditional ILI system, although both systems had week-over-week fluctuations in the number of participants responding. FluWatchers' ILI rates had moderate correlation with weekly influenza laboratory detection rates and other winter seasonal respiratory virus detections including respiratory syncytial virus and seasonal coronaviruses. Finally, FluWatchers has demonstrated its usefulness as a source of core FluWatch surveillance information and has the potential to fill data gaps in current programs for influenza surveillance and control. CONCLUSION: FluWatchers is an example of an innovative digital participatory surveillance program that was created to address limitations of traditional ILI surveillance in Canada. It fulfills the surveillance system evaluation criteria of acceptability, reliability, accuracy and usefulness.

Competing Bioaerosols May Influence the Seasonality of Influenza-Like Illnesses, including COVID-19. The Chicago Experience.

Data from Chicago confirm the end of flu season coincides with the beginning of pollen season. More importantly, the end of flu season also coincides with onset of seasonal aerosolization of mold spores. Overall, the data suggest bioaerosols, especially mold spores, compete with viruses for a shared receptor, with the periodicity of influenza-like illnesses, including COVID-19, a consequence of seasonal factors that influence aerosolization of competing species.

Air pollutants and outpatient visits for influenza-like illness in Beijing, China.

BACKGROUND: Air pollution leads to many adverse health conditions, mainly manifested by respiratory or cardiac symptoms. Previous studies are limited as to whether air pollutants were associated to influenza-like illness (ILI). This study aimed to explore the association between air pollutants and outpatient visits for ILI, especially during an outbreak of influenza. METHODS: Daily counts of hospital visits for ILI were obtained from Peking University Third Hospital between January 1, 2015, and March 31, 2018. A generalized additive Poisson model was applied to examine the associations between air pollutants concentrations and daily outpatient visits for ILI when adjusted for the meteorological parameters. RESULTS: There were 35862 outpatient visits at the fever clinic for ILI cases. Air quality index (AQI), PM2.5, PM10, CO and O3 on lag0 days, as well as nitrogen dioxide (NO2) and sulfur dioxide (SO2) on lag1 days, were significantly associated with an increased risk of outpatient visits for ILI from January 2015 to November 2017. From December 2017 to March 2018, on lag0 days, air pollutants PM2.5 [risk ratio (RR) = 0.971, 95% CI: 0.963-0.979], SO2 (RR = 0.892, 95% CI: 0.840-0.948) and CO (RR = 0.306, 95% CI: 0.153-0.612) were significantly associated with a decreased risk of outpatient visits for ILI. Interestingly, on the lag2 days, all the pollutants were significantly associated with a reduced risk of outpatient visits for ILI except for O3. We did not observe the linear correlations between the outpatient visits for ILI and any of air pollutants, which were instead associated via a curvilinear relationship. CONCLUSIONS: We found that the air pollutants may be associated with an increased risk of outpatient visits for ILI during the non-outbreak period and with a decreased risk during the outbreak period, which may be linked with the use of disposable face masks and the change of outdoor activities. These findings expand the current knowledge of ILI outpatient visits correlated with air pollutants during an influenza pandemic.