Incidence Of Influenza-like Illness Research Articles

Analysis of the incidence of influenza before and after the COVID-19 pandemic in South Korea.

Influenza outbreaks of varying size occur every year, but during the COVID-19 pandemic, many countries experienced influenza at lower levels. However, following the relaxation of COVID-19 prevention measures in 2022, the incidence of influenza began to increase gradually. Thus, this study compared the occurrence of influenza from week 36 of 2017, before the COVID-19 outbreak, until 2023. The analysis was conducted using influenza-like illness occurrence data available from the Korea Disease Control and Prevention Agency infectious disease website. Additionally, to examine the changes in COVID-19 and influenza occurrence during the pandemic, COVID-19 incidence data from 20 January 2020 to 31 August 2023 were obtained from the KDCA Coronavirus Disease 19 homepage. During the COVID-19 pandemic, which corresponds to the 2020/2021 and 2021/2022 influenza seasons, there was no seasonal influenza epidemic, and the incidence rates were below the usual outbreak levels. However, in the 2022/2023 season, when the spread of COVID-19 had eased, a seasonal pattern similar to that observed before the COVID-19 pandemic was noted. Furthermore, correlation analysis between the rates of influenza-like illness and COVID-19 incidence showed no significant correlation during the entire period. However, a significant correlation emerged in 2023 (r = 0.393, p <0.05). These results suggest that influenza was suppressed during the COVID-19 pandemic but returned to typical seasonal patterns after the COVID-19 prevention policies were eased. The positive correlation observed between the incidences of COVID-19 and influenza in 2023 indicates that COVID-19, no longer a novel pandemic-causing infectious disease, may have transitioned to an endemic pattern similar to seasonal influenza.

Protective Impact of Influenza Vaccination on Healthcare Workers

Background: Influenza vaccine uptake among healthcare workers is crucial for preventing influenza infections, yet its effectiveness needs further investigation. Objectives: This prospective observational study aimed to assess the protective effect of influenza vaccination among healthcare workers in Shenzhen. Methods: We enrolled 100 participants, with 50 receiving the 2023–2024 quadrivalent influenza vaccine (QIV) and 50 serving as unvaccinated controls. Epidemiological data were collected when the participants presented influenza-like illness. Serum samples were collected at three time points (pre-vaccination and 28 and 180 days after vaccination). Hemagglutination inhibition (HI) assay was performed against the strains included in the 2023–2024 QIV (H1N1, H3N2, BV and BY strains) to assess antibody protection levels. Demographics comparisons revealed no significant differences between the vaccinated and control groups (p &gt; 0.05), ensuring group comparability. Results: The incidence of influenza-like illness was significantly lower in the vaccinated (18%) compared to the control group (36%; p = 0.046; OR = 0.39; 95% CI: 0.15 to 0.98). The vaccinated group also exhibited a higher rate of consecutive two-year vaccinations (48% vs. 24% in the control group, p &lt; 0.05). Additionally, the vaccinated healthcare workers were more inclined to recommend vaccination to their families (80% vs. 48%, p &lt; 0.05). HI titers against H1N1 (p &lt; 0.01), H3N2 (p &lt; 0.01), BV (p &lt; 0.001) and BY (p &lt; 0.01) significantly increased in the vaccinated group at 28 days post-vaccination. Moreover, a marked and sustained increase in HI titers against the H3N2 strain (p &lt; 0.001) was observed at 180 days post-vaccination, highlighting the vaccine’s enduring impact on the immune response. The fold change in the HI titers, indicative of the magnitude of the immune response, was significantly higher for H1N1 (p &lt; 0.01), H3N2 (p &lt; 0.001), BV (p &lt; 0.01) and BY (p &lt; 0.05) among the vaccinated individuals compared to the control group, underscoring the vaccine’s efficacy in eliciting a robust and sustained antibody response. Conclusion: Influenza vaccination significantly reduces the incidence of influenza-like illness among healthcare workers and promotes a sustained immune response. The study supports the importance of annual vaccination for this group to enhance personal and public health.

Optimization of timing for maternal immunization to protect newborns from influenza infection

Objectives The primary objective of this systematic review was to identify the optimal timing for immunizing pregnant women to confer the most protection by reducing the incidence of laboratory-confirmed influenza or influenza-like illness in infants less than 6 months of age. Currently, there are gaps in research regarding the timing of administration during the gestational period to provide maximum immunogenicity to the infant. The research question being addressed is: ‘When considering immunization of pregnant mothers with the influenza vaccine, implementing a vaccination program during which trimester in pregnancy would optimize benefits for infants less than 6 months of age in terms of the incidence of laboratory-confirmed influenza and influenza-like illness?’ Design Systematic review/Meta-analysis Methods Randomized controlled trials (RCT’s) and observational studies comparing health outcomes of infants and children up to 6 months of age born to women who received inactivated influenza vaccine during pregnancy with mothers who did not receive the vaccine or received a control vaccine. The primary outcome was laboratory-confirmed influenza infection in infants. Secondary outcome measures included influenza –like illness diagnosed by a clinician and acute respiratory illness. Results 7 studies were included: 2 primary RCT’s and 5 observational studies (prospective and retrospective cohort studies).5 of the 7 studies were suitable to be included in the quantitative synthesis part and and were compared. Forrest plot analysis revealed that vaccinating pregnant mothers in the second and third trimester when compared with any trimester (1,2 and 3) (OR 0.18 vs. 0.65) conferred less protection, promoting vaccination in the first trimester. Conclusions Vaccinating pregnant mothers in the first trimester conferred greater protection to infants than any other trimester.

Assessment of Epidemiological Trend of Influenza-Like Illness in Italy from 2010/2011 to 2023/2024 Season: Key Points to Optimize Future Vaccination Strategies against Influenza.

Seasonal influenza is an acute respiratory infectious disease due to influenza viruses, causing a relevant number of illnesses and deaths each year worldwide. Influenza is a preventable disease by vaccination. The aim of this study was to assess the epidemiology of seasonal influenza in Italy through the analysis of data from the epidemiological and virological RespiVirNet surveillance system for the season 2010/2011 to 2023/2024 to identify the epidemiological key points to plan the most appropriate vaccination strategies. The cumulative and maximum weekly incidence of influenza-like illness (ILI) and epidemic period (beginning, end, duration in weeks) were assessed in the pre-pandemic period (2010/2011-2019/2020) and they were compared to the pandemic and post-pandemic one. In all seasons, children reported the highest incidence values of ILI and longer epidemic periods in contrast with the older population. The epidemic seasons 2020/2021 and 2021/2022 had abnormal trends while in the last seasons 2022/2023 and 2023/2024 the epidemiological and virological trends of ILI were confirmed as reported in the pre-pandemic period but with high intensity. Influenza virus A was predominant: the H3N2 subtype circulated more than virus H1N1pdm09. In the few seasons when influenza virus B was the most frequent influenza agent, it co-circulated with influenza virus A. The monitoring of cases is the fundamental tool to better understand the epidemiology of influenza and to optimize future preventive strategies.

Detection of influenza virus in urban wastewater during the season 2022/2023 in Sicily, Italy.

Seasonal influenza generally represents an underestimated public health problem with significant socioeconomic implications. Monitoring and detecting influenza epidemics are important tasks that require integrated strategies. Wastewater-based epidemiology (WBE) is an emerging field that uses wastewater data to monitor the spread of disease and assess the health of a community. It can represent an integrative surveillance tool for better understanding the epidemiology of influenza and prevention strategies in public health. We conducted a study that detected the presence of Influenza virus RNA using a wastewater-based approach. Samples were collected from five wastewater treatment plants in five different municipalities, serving a cumulative population of 555,673 Sicilian inhabitants in Italy. We used the RT-qPCR test to compare the combined weekly average of Influenza A and B viral RNA in wastewater samples with the average weekly incidence of Influenza-like illness (ILI) obtained from the Italian national Influenza surveillance system. We also compared the number of positive Influenza swabs with the viral RNA loads detected from wastewater. Our study investigated 189 wastewater samples. Cumulative ILI cases substantially overlapped with the Influenza RNA load from wastewater samples. Influenza viral RNA trends in wastewater samples were similar to the rise of ILI cases in the population. Therefore, wastewater surveillance confirmed the co-circulation of Influenza A and B viruses during the season 2022/2023, with a similar trend to that reported for the weekly clinically confirmed cases. Wastewater-based epidemiology does not replace traditional epidemiological surveillance methods, such as laboratory testing of samples from infected individuals. However, it can be a valuable complement to obtaining additional information on the incidence of influenza in the population and preventing its spread.

Indoor environmental factors associated with influenza transmission in mainland China between February and April 2023

BackgroundThe relaxation of strict COVID-19 control measures has led to a considerable increase in the number of influenza cases in 2023. This worrisome situation has posed a greater burden on public health and healthcare systems. Understanding environmental drivers of influenza epidemics can provide valuable insights for developing effective interventions. MethodsWe conducted an online survey from April 13th to 14th, 2023 to investigate the incidence of influenza-like illness (ILI) and influenza A within the past two months. A total of 4916 valid questionnaires were collected in mainland China. The questionnaire explored the relationship between the spread of ILI/Influenza A and factors including personal attributes, living environment, indoor ventilation, and personal behaviours. ResultsOut of the 4916 respondents, 1583 reported having ILI in the past two months, and among them, 456 were infected with influenza A. The multivariate logistic regression analysis revealed significant associations with a lower likelihood of reporting ILI for the following variables: being female (Adjusted OR (aOR) = 0.834), having bedroom ventilation time exceeding 12 hours (aOR = 0.782), wearing masks in public places (aOR = 0.646), and using surgical masks (aOR = 1.417). Conversely, variables associated with an increased risk of ILI included larger household size (>4: aOR = 2.405), presence of odours in the bathroom (aOR = 1.163), commuting by bus (aOR = 1.265), longer indoor stay during weekdays (>18 h: aOR = 1.969), and a history of COVID-19 infection (aOR = 1.459). Furthermore, handwashing after toileting (aOR = 0.694) was associated with a lower reporting of influenza A. ConclusionsOur study innovatively examined the impact of personal and environmental factors on influenza transmission. These observational findings can provide a scientific guidance for preventive measures against influenza.

Optimization of timing for maternal immunization to protect newborns from influenza infection

Objectives The primary objective of this systematic review was to identify the optimal timing for immunizing pregnant women to confer the most protection by reducing the incidence of laboratory-confirmed influenza or influenza-like illness in infants less than 6 months of age. Currently, there are gaps in research regarding the timing of administration during the gestational period to provide maximum immunogenicity to the infant. The research question being addressed is: ‘When considering immunization of pregnant mothers with the influenza vaccine, implementing a vaccination program during which trimester in pregnancy would optimize benefits for infants less than 6 months of age in terms of the incidence of laboratory-confirmed influenza and influenza-like illness?’ Design Systematic review/Meta-analysis Methods Randomized controlled trials (RCT’s) and observational studies comparing health outcomes of infants and children up to 6 months of age born to women who received inactivated influenza vaccine during pregnancy with mothers who did not receive the vaccine or received a control vaccine. The primary outcome was laboratory-confirmed influenza infection in infants. Secondary outcome measures included influenza –like illness diagnosed by a clinician and acute respiratory illness. Results 7 studies were included: 2 primary RCT’s and 5 observational studies (prospective and retrospective cohort studies).5 of the 7 studies were suitable to be included in the quantitative synthesis part and and were compared. Forrest plot analysis revealed that vaccinating pregnant mothers in the second and third trimester when compared with any trimester (1,2 and 3) (OR 0.18 vs. 0.65) conferred less protection, promoting vaccination in the first trimester. Conclusions Vaccinating pregnant mothers in the first trimester conferred greater protection to infants than any other trimester.

Hospital-Based Influenza and Pneumococcal Vaccination for Cancer Patients on Active Treatment and Their Family Members during the COVID-19 Pandemic in Italy: A Single-Center Experience

In patients with cancer, tumor- and treatment-induced immunosuppression are responsible for a four-fold increase in morbidity and mortality caused by influenza and invasive Streptococcus pneumoniae infections compared to the general population. The main oncology societies strongly recommend vaccination in patients with cancer to prevent these infections. However, vaccine hesitancy is a main concern in this population. The aim of this study was to assess the feasibility of in-hospital vaccination for patients under anticancer treatment and their family members (FMs) against influenza and pneumococcal infections during the COVID-19 pandemic in order to increase vaccine coverage. This was a single-center, prospective, observational study conducted at the Department of Oncology of Luigi Sacco University Hospital (Milan, Italy) between October 2020 and April 2021. The main primary outcome was the incidence of influenza-like illness (ILI) and pneumococcal infections. The main secondary outcome was safety. A total of 341 subjects were enrolled, including 194 patients with cancer and 147 FMs. The incidence of ILI was higher among patients than among FMs (9% vs. 2.7%, OR 3.92, p = 0.02). Moreover, two subjects were diagnosed with pneumococcal pneumonia. The most frequent vaccine-related AEs were pain in the injection site (31%) and fatigue (8.7%). In conclusion, this hospital-based vaccination strategy was feasible during the COVID-19 pandemic, representing a potential model to maximize vaccine coverage during a public health emergency.

Viral respiratory infections and air pollution: A review focused on research in Poland

The COVID-19 pandemic has reinforced an interest in the relationship between air pollution and respiratory viral infections, indicating that their burden can be increased under poor air quality. This paper reviews the pathways through which air pollutants can enhance susceptibility to such infections and aggravate their clinical course and outcome. It also summarizes the research exploring the links between various viral infections and exposure to solid and gaseous pollution in Poland, a region characterized by poor air quality, especially during a heating season. The majority of studies focused on concentrations of particulate matter (PM; 86.7%); the other pollutants, i.e., BaP, benzene, CO, NOx, O3, and SO2, were studied less often and sometimes only in the context of a particular infection type. Most research concerned COVID-19, showing that elevated levels of PM and NO2 correlated with higher morbidity and mortality, while increased PM2.5 and benzo[a]pyrene levels were related to worse clinical course and outcome in hospitalized, regardless of age and dominant SARS-CoV-2 variant. PM10 and PM2.5 levels were also associated with the incidence of influenza-like illness and, along with NO2 concentrations, with a higher rate of children's hospitalizations due to lower respiratory tract RSV infections. Higher levels of air pollutants also increased hospitalization due to bronchitis (PM, NOx, and O3) and emergency department admission due to viral croup (PM10, PM2.5, NOx, CO, and benzene). Although the conducted studies imply only correlations and have other limitations, as discussed in the present paper, it appears that improving air quality through reducing combustion processes in energy production in Poland should be perceived as a part of multilayered protection measures against respiratory viral infections, decreasing the healthcare costs of COVID-19, lower tract RSV infections, influenza, and other respiratory viral diseases prevalent between autumn and early spring, in addition to other health and climate benefits.

Can telephone data contribute to a national influenza surveillance system in Australia? A retrospective analysis

Introduction: Data collected from telephone helplines that provide health advice can improve the timeliness and accuracy of disease surveillance, contributing to an appropriate and rapid public health response. We show how these data can forewarn health professionals of increased rates of influenza-like illness (ILI) in the community and discuss implications for COVID-19 syndromic surveillance. Methods: The healthdirect helpline (HH) captures demographic details and characteristics of symptoms from users in 6 Australian states and territories. We compare ILI activity in the HH with ILI activity in emergency department (ED), laboratory, Flutracking and general practice (GP) data using cross-correlation functions. Results: Helpline data correlated strongly with ED data (range in yearly correlations from 0.82-0.99), GP data (0.66 – 0.95) and Flutracking data (0.62-0.89), but yearly correlations with laboratory data varied (0.49-0.95). The highest correlation with laboratory and GP data occurred when HH activity was 1-2 weeks in advance of these data, while correlations with ED and Flutracking data were strongest with no time lag. Discussion: Our analysis demonstrates that the number of ILI-related calls to the HH is a reliable indicator of ILI incidence in Australia. An increase in calls is likely to occur simultaneously with an increase in visits to EDs and prior to an increase in positive laboratory influenza tests and visits to GPs. A surveillance system including these data would assist health practitioners to receive timely and accurate estimates of the level of ILI in the community to better respond to and prepare for seasonal and epidemic influenza.

Impact of health education on promoting influenza vaccination health literacy in primary school students: a cluster randomised controlled trial protocol

IntroductionInfluenza is a major public health threat, and vaccination is the most effective prevention method. However, vaccination coverage remains suboptimal. Low health literacy regarding influenza vaccination may contribute to vaccine...

Infodemiology of Influenza-like Illness: Utilizing Google Trends' Big Data for Epidemic Surveillance.

Background: Influenza-like illness (ILI) encompasses symptoms similar to influenza, affecting population health. Surveillance, including Google Trends (GT), offers insights into epidemic patterns. Methods: This study used multiple regression models to analyze the correlation between ILI incidents, GT keyword searches, and climate variables during influenza outbreaks. It compared the predictive capabilities of time-series and deep learning models against ILI emergency incidents. Results: The GT searches for "fever" and "cough" were significantly associated with ILI cases (p < 0.05). Temperature had a more substantial impact on ILI incidence than humidity. Among the tested models, ARIMA provided the best predictive power. Conclusions: GT and climate data can forecast ILI trends, aiding governmental decision making. Temperature is a crucial predictor, and ARIMA models excel in forecasting ILI incidences.

Immunogenicity, Safety, and Efficacy of Influenza Vaccine in T2DM and T2DM with Chronic Kidney Disease.

Patients with Type 2 diabetes mellitus (T2DM) and Chronic Kidney Disease (CKD) face an increased risk of morbidity and mortality after influenza infection. Several studies have shown that the influenza vaccine effectively prevents morbidity and mortality in T2DM patients. However, there has been limited research aimed at assessing the effectiveness of the trivalent influenza vaccine in T2DM-CKD patients. This study aimed to identify Geometric Mean Titers (GMTs), seroprotection, seroconversion, safety, and efficacy. This open-label clinical trial was conducted at AMC Hospital in Bandung, West Java, Indonesia between June 2021 and July 2022. The study subjects consisted of 41 T2DM and 26 T2DM-CKD patients who were administered the trivalent influenza vaccine. There was a significant difference in the average age, with the T2DM-CKD patients being older. Median titers post-vaccination for the B/Washington virus were higher in the T2DM patients compared to the T2DM-CKD patients, and this difference was statistically significant. A majority, comprising 75.6% of the T2DM and 80.8% of the T2DM-CKD patients monitored post-influenza-vaccination, did not experience any adverse reactions. The most common reaction was the sensation of fever, with incidence rates of 12.2% in the T2DM patients and 15.4% in the T2DM-CKD patients. Furthermore, we observed that the incidence of Influenza-like Illness was highest at 7.3% in the T2DM patients and 7.7% in the T2DM-CKD patients. The trivalent influenza vaccine demonstrated equivalent safety and effectiveness in both groups.

Prediction of Influenza-Like Illness Incidence in Cheras, Malaysia based on Environmental Data using the Generalised Additive Model

Influenza-like illness (ILI) accounts for 500,000 fatalities worldwide yearly. Environmental factors contribute to spread of respiratory infections. This study describes the epidemiological trends of ILI in Cheras, Kuala Lumpur, Malaysia and seeks scientific evidence on ILI activity and environmental factors. Cheras Health District collected ILI surveillance data and the nearest weather station which provided environmental data on mean temperature, humidity, wind speed, cumulative rainfall, particulate matter (PM)10 and PM2.5 levels. A total of 51,245 ILI cases were reported from 1st December 2021 to 30th April 2023. The non-linear relationship between ILI incidence and environmental variables was modelled using the Generalised Additive Model (GAM). The lag time for mean temperature, mean humidity, cumulative rainfall, mean wind speed, PM 10 level, and PM 2.5 level was 2, 3, 3, 3, 0, and 3 days, respectively. The model with the optimal lag better describes ILI case variance (R2=0.5, explained deviance=58%) than the model without lag selection (R2=0.5, explained deviance=57.2%). The Lag Model indicates a significant p-value for PM10 but no significant concurvity between predictor variables. Thus, the final model (R2=0.5, explained deviance=59.2%) has k=15. Higher rainfall, relative humidity, colder temperature, and decreased wind speed increased ILI incidence. PM2.5 and PM10 also contributes to ILI.

Association between ozone and influenza transmissibility in China

BackgroundCommon air pollutants such as ozone (O3), sulfur dioxide (SO2), nitrogen dioxide (NO2), and particulate matter play significant roles as influential factors in influenza-like illness (ILI). However, evidence regarding the impact of O3 on influenza transmissibility in multi-subtropical regions is limited, and our understanding of the effects of O3 on influenza transmissibility in temperate regions remain unknown.MethodsWe studied the transmissibility of influenza in eight provinces across both temperate and subtropical regions in China based on 2013 to 2018 provincial-level surveillance data on influenza-like illness (ILI) incidence and viral activity. We estimated influenza transmissibility by using the instantaneous reproduction number ({R}_{t}) and examined the relationships between transmissibility and daily O3 concentrations, air temperature, humidity, and school holidays. We developed a multivariable regression model for {R}_{t} to quantify the contribution of O3 to variations in transmissibility.ResultsOur findings revealed a significant association between O3 and influenza transmissibility. In Beijing, Tianjin, Shanghai and Jiangsu, the association exhibited a U-shaped trend. In Liaoning, Gansu, Hunan, and Guangdong, the association was L-shaped. When aggregating data across all eight provinces, a U-shaped association was emerged. O3 was able to accounted for up to 13% of the variance in {R}_{t}. O3 plus other environmental drivers including mean daily temperature, relative humidity, absolute humidity, and school holidays explained up to 20% of the variance in {R}_{t}.ConclusionsO3 was a significant driver of influenza transmissibility, and the association between O3 and influenza transmissibility tended to display a U-shaped pattern.

Comparison of Influenza-Like Illness (ILI) incidence data from the novel LeCellPHIA participatory surveillance system with COVID-19 case count data, Lesotho, July 2020 – July 2021

BackgroundWhile laboratory testing for infectious diseases such as COVID-19 is the surveillance gold standard, it is not always feasible, particularly in settings where resources are scarce. In the small country of Lesotho, located in sub-Saharan Africa, COVID-19 testing has been limited, thus surveillance data available to local authorities are limited. The goal of this study was to compare a participatory influenza-like illness (ILI) surveillance system in Lesotho with COVID-19 case count data, and ultimately to determine whether the participatory surveillance system adequately estimates the case count data.MethodsA nationally-representative sample was called on their mobile phones weekly to create an estimate of incidence of ILI between July 2020 and July 2021. Case counts from the website Our World in Data (OWID) were used as the gold standard to which our participatory surveillance data were compared. We calculated Spearman’s and Pearson’s correlation coefficients to compare the weekly incidence of ILI reports to COVID-19 case count data.ResultsOver course of the study period, an ILI symptom was reported 1,085 times via participatory surveillance for an average annual cumulative incidence of 45.7 per 100 people (95% Confidence Interval [CI]: 40.7 – 51.4). The cumulative incidence of reports of ILI symptoms was similar among males (46.5, 95% CI: 39.6 – 54.4) and females (45.1, 95% CI: 39.8 – 51.1). There was a slightly higher annual cumulative incidence of ILI among persons living in peri-urban (49.5, 95% CI: 31.7 – 77.3) and urban settings compared to rural areas. The January peak of the participatory surveillance system ILI estimates correlated significantly with the January peak of the COVID-19 case count data (Spearman’s correlation coefficient = 0.49; P < 0.001) (Pearson’s correlation coefficient = 0.67; P < 0.0001).ConclusionsThe ILI trends captured by the participatory surveillance system in Lesotho mirrored trends of the COVID-19 case count data from Our World in Data. Public health practitioners in geographies that lack the resources to conduct direct surveillance of infectious diseases may be able to use cell phone-based data collection to monitor trends.

From pandemic to endemic: Spatial-temporal patterns of influenza-like illness incidence in a Swiss canton, 1918–1924

In pandemics, past and present, there is no textbook definition of when a pandemic is over, and how and when exactly a respiratory virus transitions from pandemic to endemic spread. In this paper we have compared the 1918/19 influenza pandemic and the subsequent spread of seasonal flu until 1924. We analysed 14,125 reports of newly stated 32,198 influenza-like illnesses from the Swiss canton of Bern. We analysed the temporal and spatial spread at the level of 497 municipalities, 9 regions, and the entire canton. We calculated incidence rates per 1000 inhabitants of newly registered cases per calendar week. Further, we illustrated the incidences of each municipality for each wave (first wave in summer 1918, second wave in fall/winter 1918/19, the strong later wave in early 1920, as well as the two seasonal waves in 1922 and 1924) on a choropleth map. We performed a spatial hotspot analysis to identify spatial clusters in each wave, using the Gi* statistic. Furthermore, we applied a robust negative binomial regression to estimate the association between selected explanatory variables and incidence on the ecological level. We show that the pandemic transitioned to endemic spread in several waves (including another strong wave in February 1920) with lower incidence and rather local spread until 1924 at least. At the municipality and regional levels, there were different patterns of spread both between pandemic and seasonal waves. In the first pandemic wave in summer 1918 the probability of higher incidence was increased in municipalities with a higher proportion of factories (OR 2.60, 95%CI 1.42–4.96), as well as in municipalities that had access to a railway station (OR 1.50, 95%CI 1.16–1.96). In contrast, the strong fall/winter wave 1918 was very widespread throughout the canton. In general, municipalities at higher altitude showed lower incidence. Our study adds to the sparse literature on incidence in the 1918/19 pandemic and subsequent years. Before Covid-19, the last pandemic that occurred in several waves and then became endemic was the 1918–19 pandemic. Such scenarios from the past can inform pandemic planning and preparedness in future outbreaks.

The association between ambient pollutants and influenza transmissibility: A nationwide study involving 30 provinces in China.

The impact of exposure to ambient pollutants on influenza transmissibility is poorly understood. We aim to examine the associations of six ambient pollutants with influenza transmissibility in China and assess the effect of the depletion of susceptibles. Provincial-level surveillance data on weekly influenza-like illness (ILI) incidence and viral activity were utilized to estimate the instantaneous reproduction number (Rt) using spline functions. Log-linear regression and the distributed lag non-linear model (DLNM) were employed to investigate the effects of ambient pollutants-ozone (O3), particulate matter ≤2.5μm (PM2.5), particulate matter ≤10μm (PM10), nitrogen dioxide (NO2), sulfur dioxide (SO2), and carbon monoxide (CO)-on influenza transmissibility across 30 Chinese provinces from 2014 to 2019. Additionally, the potential effects of the depletion of susceptibles and regional characteristics were explored. There is a significantly positive correlation between influenza transmissibility and five distinct ambient pollutants: PM2.5, PM10, SO2, CO, and NO2. On average, these ambient pollutants explained percentages of the variance in Rt: 0.8%, 0.8%, 1.9%, 1.3%, and 1.4%, respectively. Conversely, O3 was found to be negatively associated with Rt, explaining 1.5% of the variance in Rt. When controlling for the effect of susceptibles depletion, the effects of all pollutants were more pronounced. The effects of PM2.5, PM10, CO, and SO2 were higher in the eastern and southern regions. Most ambient pollutants may potentially contribute to the facilitation of human-to-human influenza virus transmission in China. This observed association was maintained even after adjusting for variation in the susceptible population.

Comprehensive surveillance of acute respiratory infections during the COVID-19 pandemic: a methodological approach using sentinel networks, Castilla y León, Spain, January 2020 to May 2022.

BackgroundSince 1996, epidemiological surveillance of acute respiratory infections (ARI) in Spain has been limited to seasonal influenza, respiratory syncytial virus (RSV) and potential pandemic viruses. The COVID-19 pandemic provides opportunities to adapt existing systems for extended surveillance to capture a broader range of ARI.AimTo describe how the Influenza Sentinel Surveillance System of Castilla y León, Spain was rapidly adapted in 2020 to comprehensive sentinel surveillance for ARI, including influenza and COVID-19.MethodsUsing principles and methods of the health sentinel network, we integrated electronic medical record data from 68 basic surveillance units, covering 2.6% of the regional population between January 2020 to May 2022. We tested sentinel and non-sentinel samples sent weekly to the laboratory network for SARS-CoV-2, influenza viruses and other respiratory pathogens. The moving epidemic method (MEM) was used to calculate epidemic thresholds.ResultsARI incidence was estimated at 18,942 cases per 100,000 in 2020/21 and 45,223 in 2021/22, with similar seasonal fold increases by type of respiratory disease. Incidence of influenza-like illness was negligible in 2020/21 but a 5-week epidemic was detected by MEM in 2021/22. Epidemic thresholds for ARI and COVID-19 were estimated at 459.4 and 191.3 cases per 100,000 population, respectively. More than 5,000 samples were tested against a panel of respiratory viruses in 2021/22.ConclusionExtracting data from electronic medical records reported by trained professionals, combined with a standardised microbiological information system, is a feasible and useful method to adapt influenza sentinel reports to comprehensive ARI surveillance in the post-COVID-19 era.

Impact of a Health Education Intervention on the Incidence of Influenza-Like Illnesses (ILI) During Hajj via Smartphone Application.

This study was aimed at demonstrating the impact of a health education intervention on reducing the incidence of influenza-like illnesses symptoms among Malaysian Hajj pilgrims. This study utilizes a quasi-experimental study in the evaluation of the impact of the intervention. Participants were recruited during Hajj orientation courses organized by private Hajj companies. Participants from two companies were assigned to an intervention group and control group, respectively. The intervention group received a smartphone-based health education intervention guided by the Health Belief Model (HBM), while the control group received a regular Hajj guide intervention smartphone application before departure to Hajj. Data on the incidence of influenza-like illnesses (ILI) were collected from participants from two Hajj companies before and after returning from Hajj. Data analysis was conducted using SPSS with descriptive analysis, and analytical tests were conducted at 5% significance level. A total of 102 pilgrims completed the study in both intervention and control groups. The incidence of ILI and Non-ILI symptoms were statistically significant when the intervention and control groups (p = 0.049) were compared. In conclusion, health education has an impact on reducing the incidence of ILI and non-ILI among Hajj pilgrims.