Influenza-like Illness Rates Research Articles

36 A YEAR WITHOUT THE FLU: MODELLING THE EFFECTS ON CARDIOVASCULAR MORTALITY FROM INFLUENZA IN IRELAND

BackgroundCardiovascular diseases (CVDs) are consistently ranked among the leading causes of death among older adults in Ireland. COVID-19 and influenza infection are associated with cardiovascular complications. However, percentage of deaths caused by CVD among adults aged 75 and over in Ireland decreased from 32.9% to 31.0% from 2019 to 2020. Government-imposed social distancing measures resulted in abolition of influenza activity (IA). We analysed population data from the 2010/11–2019/20 influenza seasons to estimate the impact of reduced IA on CVD mortality rates during the COVID-19 pandemic season.MethodsQuarterly mortality data for acute myocardial infarction (AMI) and cerebrovascular disease from first quarter (Q1) 2010 to fourth quarter (Q4) 2020 was obtained from the Central Statistics Office. Weekly data on influenza-like illness (ILI) rates and positive percentages (PP) (i.e. proportion of influenza-positive sentinel respiratory specimens) from week 40 2010 to week 20 2020 was obtained from the Health Protection Surveillance Centre. Excess mortality rate during influenza season was calculated as the percentage difference between Q4/Q1 and preceding third quarter (Q3) mortality rates. We adopted the Goldstein index (ILI rate × PP) as an indicator of IA. Time series analyses, Pearson correlation coefficients (r) and linear regression models were used to evaluate the relationships between IA and excess AMI and cerebrovascular disease mortality rates.ResultsStatistically significant positive associations were observed between IA and excess AMI (r = 0.557, p = 0.011) and cerebrovascular disease (r = 0.858, p < 0.001) mortality rates. Linear regression models predicted 0.072% (95% confidence interval 0.019%, 0.125%) and 0.095% (0.067%, 0.123%) increases in excess AMI and cerebrovascular disease mortality rates respectively per unit increase in IA levels.ConclusionElimination of IA may have contributed towards limiting the effects of COVID-19 on CVD mortality rates, and consequently total excess mortality, among older adults in Ireland.

Novel Methods in the Surveillance of Influenza-Like Illness in Germany Using Data From a Symptom Assessment App (Ada): Observational Case Study.

BackgroundParticipatory epidemiology is an emerging field harnessing consumer data entries of symptoms. The free app Ada allows users to enter the symptoms they are experiencing and applies a probabilistic reasoning model to provide a list of possible causes for these symptoms.ObjectiveThe objective of our study is to explore the potential contribution of Ada data to syndromic surveillance by comparing symptoms of influenza-like illness (ILI) entered by Ada users in Germany with data from a national population-based reporting system called GrippeWeb.MethodsWe extracted data for all assessments performed by Ada users in Germany over 3 seasons (2017/18, 2018/19, and 2019/20) and identified those with ILI (report of fever with cough or sore throat). The weekly proportion of assessments in which ILI was reported was calculated (overall and stratified by age group), standardized for the German population, and compared with trends in ILI rates reported by GrippeWeb using time series graphs, scatterplots, and Pearson correlation coefficient.ResultsIn total, 2.1 million Ada assessments (for any symptoms) were included. Within seasons and across age groups, the Ada data broadly replicated trends in estimated weekly ILI rates when compared with GrippeWeb data (Pearson correlation—2017-18: r=0.86, 95% CI 0.76-0.92; P<.001; 2018-19: r=0.90, 95% CI 0.84-0.94; P<.001; 2019-20: r=0.64, 95% CI 0.44-0.78; P<.001). However, there were differences in the exact timing and nature of the epidemic curves between years.ConclusionsWith careful interpretation, Ada data could contribute to identifying broad ILI trends in countries without existing population-based monitoring systems or to the syndromic surveillance of symptoms not covered by existing systems.

Estimated Cost Effectiveness of Influenza Vaccination for Emergency Medical Services Professionals.

IntroductionBecause of their frequent contact with compromised patients, vaccination against influenza is recommended for all healthcare workers. Recent studies suggest that vaccination decreases influenza transmission to patients and reduces worker illness and absenteeism. However, few emergency medical services (EMS) agencies provide annual vaccination, and the vaccination rate among EMS personnel remains low. Reticence among EMS agencies to provide influenza vaccination to their employees may be due in part to the unknown fiscal consequences of implementing a vaccination program. In this study, we sought to estimate the cost effectiveness of an employer-provided influenza vaccination program for EMS personnel.MethodsUsing data from published reports on influenza vaccination, we developed a cost-effectiveness model of vaccination for a hypothesized EMS system of 100 employees. Model inputs included vaccination costs, vaccination rate, infection rate, costs associated with absenteeism, lost productivity due to working while ill (presenteeism), and medical care for treating illness. To assess the robustness of the model we performed a series of sensitivity analyses on the input variables.ResultsThe proportion of employees contracting influenza or influenza-like illness (ILI) was estimated at 19% among vaccinated employees compared to 26% among non-vaccinated employees. The costs of the vaccine, consumables, and employee time for vaccination totaled $44.19 per vaccinated employee, with a total system cost of $4,419. Compared to no vaccination, a mandatory vaccination program would save $20,745 in lost productivity and medical costs, or $16,325 in net savings after accounting for vaccination costs. The savings were 3.7 times the cost of the vaccination program and were derived from avoided absenteeism ($7,988), avoided presenteeism productivity losses ($10,303), and avoided medical costs of treating employees with influenza/ILI ($2,454). Through sensitivity analyses the model was verified to be robust across a wide range of input variable assumptions. The net monetary benefits were positive across all ranges of input assumptions, but cost savings were most sensitive to the vaccination uptake rate, ILI rate, and presenteeism productivity losses.ConclusionThis cost-effectiveness analysis suggests that an employer-provided influenza vaccination program is a financially favorable strategy for reducing costs associated with influenza/ILI employee absenteeism, presenteeism, and medical care.

Comprehensive learning particle swarm optimization enabled modeling framework for multi-step-ahead influenza prediction

Epidemics of influenza are major public health concerns. Since influenza prediction always relies on the weekly clinical or laboratory surveillance data, typically the weekly Influenza-like illness (ILI) rate series, accurate multi-step-ahead influenza predictions using ILI series is of great importance, especially, to the potential coming influenza outbreaks. This study proposes Comprehensive Learning Particle Swarm Optimization based Machine Learning (CLPSO-ML) framework incorporating support vector regression (SVR) and multilayer perceptron (MLP) for multi-step-ahead influenza prediction. A comprehensive examination and comparison of the performance and potential of three commonly used multi-step-ahead prediction modeling strategies, including iterated strategy, direct strategy and multiple-input multiple-output (MIMO) strategy, was conducted using the weekly ILI rate series from both the Southern and Northern China. The results show that: (1) The MIMO strategy achieves the best multi-step-ahead prediction, and is potentially more adaptive for longer horizon; (2) The iterated strategy demonstrates special potentials for deriving the least time difference between the occurrence of the predicted peak value and the true peak value of an influenza outbreak; (3) For ILI in the Northern China, SVR model implemented with MIMO strategy performs best, and SVR with iterated strategy also shows remarkable performance especially during outbreak periods; while for ILI in the Southern China, both SVR and MLP models with MIMO strategy have competitive prediction performance

Impact of influenza vaccine in reduction of incidence and severity of influenza-like illness.

Vaccination is useful for protection against seasonal influenza but has a low uptake. Evidence of a protective effect of influenza vaccine among Arab populations would be a useful tool for advocacy. To evaluate the impact of vaccine in reducing the incidence and severity of influenza-like illness among health staff of a tertiary care eye hospital in Saudi Arabia. This retrospective cohort study was conducted in 2018-2019. Hospital staff were divided into vaccinated and unvaccinated groups. Influenza-like illness episodes and their severity were compared between the groups and influenza-like illness rate before and after vaccination was reviewed in the vaccinated group. The uptake of flu vaccine among 1180 health staff was 41%. There were 28 (9.3%) and 51 (17%) persons with influenza-like illness in the vaccinated (n = 300) and nonvaccinated (n = 300) groups, respectively. The nonvaccinated group had a significantly higher rate of influenza-like illness than the vaccinated group had. Vaccination, young age and absence of comorbidity were independent protectors against influenza-like illness. Influenza vaccine confers significant protection and reduces the incidence and severity of influenza-like illness. However, this was a retrospective review of health data; therefore, the association of vaccine with outcomes should be considered as a weak form of evidence. The low uptake of influenza vaccine in hospital staff and their dependents is a matter of concern and should be addressed by greater awareness and education. This evidence can be used to improve overall vaccine coverage.

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

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. We aimed to evaluate FluWatchers, a crowdsourced ILI application developed to complement and complete ILI surveillance in Canada. 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. 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. 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.

629Influenza-like illness surveillance in Australia: comparison of general practice data with laboratory-confirmed influenza notifications

Abstract Background Influenza is a respiratory infection responsible for 645,000 annual deaths worldwide. Surveillance systems provide valuable data for monitoring influenza in order to detect outbreaks and guide public health responses. This study aimed to investigate the epidemiology of influenza-like illness (ILI) using two Australian general practice databases (MedicineInsight and the Australian Sentinel Practice Research Network (ASPREN)) and compare them with laboratory-confirmed influenza from the National Notifiable Diseases Surveillance System (NNDSS). Methods All patients who had a consultation in MedicineInsight general practices or ASPREN and all laboratory-confirmed influenza reported by the NNDSS between 2015-2017 were included. Weekly ILI rates per 1,000 consultations (MedicineInsight/ASPREN) were compared with influenza notifications (NNDSS). Results Data was consistent among sources, with higher cases in 2017, among women and patients aged 20-49 years. The peak rate in MedicineInsight almost doubled in 2017 compared to 2015, while in ASPREN it was less pronounced. MedicineInsight ILI curves more closely resembled NNDSS patterns (shape, the start of the season, peaks) than ASPREN, although both were highly correlated with NNDSS (r = 0.90 to 0.97 and r = 0.88 to 0.98, respectively). Conclusions MedicineInsight and ASPREN provided consistent ILI results, both resembling confirmed influenza epidemic curves, suggesting the potential use of routinely collected electronic medical records (MedicineInsight) in influenza surveillance. MedicineInsight provides comprehensive medical data, such as underlying conditions, medications prescribed and vaccination status, which could be used to improve accuracy on influenza detection. Key messages Electronic medical records could be used to monitor ILI in combination with ASPREN for effective early detection of outbreaks.

Correlation between the Level of Social Distancing and Activity of Influenza Epidemic or COVID-19 Pandemic: A Subway Use-Based Assessment.

Social distancing is an effective measure to mitigate the spread of novel viral infections in the absence of antiviral agents and insufficient vaccine supplies. Subway utilization density may reflect social activity and the degree of social distancing in the general population.; This study aimed to evaluate the correlations between subway use density and the activity of the influenza epidemic or coronavirus disease 2019 (COVID-19) pandemic using a time-series regression method. The subway use-based social distancing score (S-SDS) was calculated using the weekly ridership of 11 major subway stations. The temporal association of S-SDS with influenza-like illness (ILI) rates or the COVID-19 pandemic activity was analyzed using structural vector autoregressive modeling and the Granger causality (GC) test. During three influenza seasons (2017–2020), the time-series regression presented a significant causality from S-SDS to ILI (p = 0.0484). During the COVID-19 pandemic in January 2020, S-SDS had been suppressed at a level similar to or below the average of the previous four years. In contrast to the ILI rate, there was a negative correlation between COVID-19 activity and S-SDS. GC analysis revealed a negative causal relationship between COVID-19 and S-SDS (p = 0.0098).; S-SDS showed a significant time-series association with the ILI rate but not with COVID-19 activity. When public transportation use is sufficiently suppressed, additional social mobility restrictions are unlikely to significantly affect COVID-19 pandemic activity. It would be more important to strengthen universal mask-wearing and detailed public health measures focused on risk activities, particularly in enclosed spaces.

Reduction in self-reported influenza-like-illness in school children and household members following influenza vaccine administration \u2013 a cohort study, Israel, 2016\u20137

BackgroundSecond-grade pupils in Israel have been vaccinated against influenza since the winter of 2016–2017. This study aims to appraise the rate reduction of seasonal influenza vaccine among vaccinated children and their household members, and that of the vaccinated cohort and their household members.MethodsThis retrospective cohort study was performed in winter 2016–2017 in Tel-Aviv District, Israel and compared second-grade pupils who were vaccinated at school, with third-grade pupils- who were not vaccinated at school. Parents in nine schools were asked to report prior vaccination against influenza and influenza-like illness (ILI) of their children and other household members. Rate reduction was defined as [(ILI among unvaccinated) – (ILI among vaccinated)] / (ILI among vaccinated) (%).ResultsOf 527 participants, 359 (68.1%) were unvaccinated and 168 (31.9%) vaccinated. Unvaccinated children reported more ILI compared with vaccinated children (19.5% vs. 7.7%), yielding a rate reduction of 60.5%. Unvaccinated children also had a greater number of physicians’ visits and missed school days (35.7% vs. 14.9 and 42.9% vs. 25.6%, respectively). The rate of ILI among household members of unvaccinated children was 34.5%, compared with 25.0% among household members of vaccinated children.The vaccinated cohort (defined as all children in second grade) reported less ILI compared with the unvaccinated cohort (defined as all children in third grade), with a rate reduction of 44.6%. Pupils of the unvaccinated cohort were more likely to miss school days (42.1% vs. 32.0%, respectively), and a higher rate of ILI was reported among household members of the unvaccinated cohort (35.4% vs. 27.3%, respectively).ConclusionInfluenza vaccine administered in school setting reduced ILI among the vaccinated cohort and their household members by 60.5 and 27.5%, respectively, compared with the unvaccinated cohort. Expansion of the vaccination program in a school setting increased the public health benefit of influenza vaccines among both school children and their household members.

Influenza epidemiology and burden of disease in Mongolia, 2013–2014 to 2017–2018

Background: Mongolia is a vast, sparsely populated country in central Asia. Its harsh climate and nomadic lifestyle make the population vulnerable to acute respiratory infections, particularly influenza. Evidence on the morbidity, mortality and socioeconomic impact of influenza in Mongolia is scarce; however, routine surveillance for influenza-like illness (ILI), severe acute respiratory infection (SARI) and laboratory-detected influenza is conducted. This paper describes the epidemiology of influenza and the estimated burden of influenza-associated illness in Mongolia in the five influenza seasons between 2013–2014 and 2017–2018. Methods: Demographic and laboratory data from 152 sentinel surveillance sites on all patients who met the case definitions of ILI and SARI between October 2013 and May 2018 were extracted and analysed as described in A Manual for Estimating Disease Burden Associated with Seasonal Influenza. Results: The estimated annual influenza-associated ILI and SARI rates, presented as ranges, were 1279–2798 and 81–666 cases per 100 000 population, respectively. Children aged &lt;5 years accounted for 67% of all ILI cases and 79% of all SARI cases. The annual specimen positivity for influenza was highest (11–30% for ILI and 8–31% for SARI) for children aged 5–&lt;15 years and children &lt;2 years old, respectively. The annual mortality rate due to pneumonia and SARI was highest among children aged &lt;2 years (15.8–54.0 per 100 000 population). Although the incidence of influenza-associated ILI and SARI was lowest for people aged &gt;65 years, the mortality rate due to pneumonia and SARI (1.2–5.1 per 100 000) was higher than that for those aged 15–64 years. Conclusion: The estimated influenza-associated ILI and SARI incidence rates are high in Mongolia, and children, especially those aged &lt;5 years, have the highest influenza-associated burden in Mongolia. These findings provide evidence for decision-makers in Mongolia to consider targeted influenza vaccination, particularly for children.

Enhancing Influenza Epidemics Forecasting Accuracy in China with Both Official and Unofficial Online News Articles, 2019–2020

Real-time online data sources have contributed to timely and accurate forecasting of influenza activities while also suffered from instability and linguistic noise. Few previous studies have focused on unofficial online news articles, which are abundant in their numbers, rich in information, and relatively low in noise. This study examined whether monitoring both official and unofficial online news articles can improve influenza activity forecasting accuracy during influenza outbreaks. Data were retrieved from a Chinese commercial online platform and the website of the Chinese National Influenza Center. We modeled weekly fractions of influenza-related online news articles and compared them against weekly influenza-like illness (ILI) rates using autoregression analyses. We retrieved 153,958,695 and 149,822,871 online news articles focusing on the south and north of mainland China separately from 6 October 2019 to 17 May 2020. Our model based on online news articles could significantly improve the forecasting accuracy, compared to other influenza surveillance models based on historical ILI rates (p = 0.002 in the south; p = 0.000 in the north) or adding microblog data as an exogenous input (p = 0.029 in the south; p = 0.000 in the north). Our finding also showed that influenza forecasting based on online news articles could be 1–2 weeks ahead of official ILI surveillance reports. The results revealed that monitoring online news articles could supplement traditional influenza surveillance systems, improve resource allocation, and offer models for surveillance of other emerging diseases.

Influenza epidemiology and burden of disease in Mongolia, 2013-2014 to 2017-2018.

BackgroundMongolia is a vast, sparsely populated country in central Asia. Its harsh climate and nomadic lifestyle make the population vulnerable to acute respiratory infections, particularly influenza. Evidence on the morbidity, mortality and socioeconomic impact of influenza in Mongolia is scarce; however, routine surveillance for influenza-like illness (ILI), severe acute respiratory infection (SARI) and laboratory-detected influenza is conducted. This paper describes the epidemiology of influenza and the estimated burden of influenza-associated illness in Mongolia in the five influenza seasons between 2013–2014 and 2017–2018.MethodsDemographic and laboratory data from 152 sentinel surveillance sites on all patients who met the case definitions of ILI and SARI between October 2013 and May 2018 were extracted and analysed as described in A Manual for Estimating Disease Burden Associated with Seasonal Influenza.ResultsThe estimated annual influenza-associated ILI and SARI rates, presented as ranges, were 1279–2798 and 81–666 cases per 100 000 population, respectively. Children aged < 5 years accounted for 67% of all ILI cases and 79% of all SARI cases. The annual specimen positivity for influenza was highest (11–30% for ILI and 8–31% for SARI) for children aged 5– < 15 years and children < 2 years old, respectively. The annual mortality rate due to pneumonia and SARI was highest among children aged < 2 years (15.8–54.0 per 100 000 population). Although the incidence of influenza-associated ILI and SARI was lowest for people aged 365 years, the mortality rate due to pneumonia and SARI (1.2–5.1 per 100 000) was higher than that for those aged 15–64 years.ConclusionThe estimated influenza-associated ILI and SARI incidence rates are high in Mongolia, and children, especially those aged < 5 years, have the highest influenza-associated burden in Mongolia. These findings provide evidence for decision-makers in Mongolia to consider targeted influenza vaccination, particularly for children.

Suggestion of a simpler and faster influenza-like illness surveillance system using 2014\u20132018 claims data in Korea

Influenza is an important public health concern. We propose a new real-time influenza-like illness (ILI) surveillance system that utilizes a nationwide prospective drug utilization monitoring in Korea. We defined ILI-related claims as outpatient claims that contain both antipyretic and antitussive agents and calculated the weekly rate of ILI-related claims, which was compared to weekly ILI rates from clinical sentinel surveillance data during 2014–2018. We performed a cross-correlation analysis using Pearson’s correlation, time-series analysis to explore actual correlations after removing any dubious correlations due to underlying non-stationarity in both data sets. We used the moving epidemic method (MEM) to estimate an absolute threshold to designate potential influenza epidemics for the weeks with incidence rates above the threshold. We observed a strong correlation between the two surveillance systems each season. The absolute thresholds for the 4-years were 84.64 and 86.19 cases per 1000claims for claims data and 12.27 and 16.82 per 1000 patients for sentinel data. The epidemic patterns were more similar in the 2016–2017 and 2017–2018 seasons than the 2014–2015 and 2015–2016 seasons. ILI claims data can be loaded to a drug utilization review system in Korea to make an influenza surveillance system.

Positive Health Externalities of Mandating Paid Sick Leave

AbstractA growing economic literature studies the optimal design of social insurance systems and the empirical identification of welfare‐relevant externalities. In this paper, we test whether mandating employee access to paid sick leave has reduced influenza‐like‐illness (ILI) transmission rates as well as pneumonia and influenza (P&amp;I) mortality rates in the United States. Using uniquely compiled data from administrative sources at the state‐week level from 2010 to 2018 along with difference‐in‐differences methods, we present quasi‐experimental evidence that sick pay mandates have causally reduced doctor‐certified ILI rates at the population level. On average, ILI rates fell by about 11 percent or 290 ILI cases per 100,000 patients per week in the first year.

Using deep ensemble for influenza-like illness consultation rate prediction

The cases of influenza have always been an important global issue. Not only does it affect people’s health, but also a crucial point in the policy implementation of government and health care units. If the trend of the epidemic can be predicted in advance, the public can be reminded to prevent it in advance to achieve control. This study aims to provide reliable forecasting services for changes in influenza-like epidemic trends. By collecting data on the emergency department visit rate of influenza-like illness, and linking the air pollution indicators and open data on temperature and humidity environmental factors, using the stacking method in the Ensemble Learning concept, first constructs deep learning models such like RNN, LSTM for the first stage training, and obtains the input data of the second stage model through cross-validation. This method combines the advantages of each model so that the model can have better performance. In addition, the outbreak calculation method published by the WHO is added to calculate the outbreak threshold of the influenza-like epidemic. This threshold will be used to determine whether the control status of the influenza-like illness is still in a reasonable control stage. The experiment confirmed that the model has a good prediction effect on the trend of the influenza-like epidemic, and the evaluation index MAPE value can get an excellent performance of 8% to 15%. Finally, historical data and future forecast data are integrated on the web page for visual presentation to show the actual status of regional air quality and influenza-like data, and predict whether there is a trend of the influenza-like outbreak in the region.

Higher levels of social and material deprivation are associated with higher rates of influenza-like illness–related emergency department visits: Edmonton, Alberta, 2004–2014

ObjectivesNeighbourhood-level deprivation is associated with hospitalization related to respiratory infections; however, hospitalizations exclude many who seek care with less severe respiratory illnesses. Another major seasonal contributor to respiratory illness-associated healthcare burdens are influenza-like illness (ILI)–related emergency department (ED) visits. We investigated associations between area-level social and material deprivation and ILI-related ED use. Study designThis is a retrospective ecological study. MethodsWe linked ILI-related ED visit data (2004–2014) for Edmonton, Alberta to a Canadian area-level material and social deprivation index, categorizing deprivation into quintiles. Using a multivariable Poisson model with log population as the offset, we modelled the relationship between visit rates and material and social deprivation adjusting for week and season, age, sex and the interaction between age and sex. ResultsWe included 67,585 ILI-related ED visits, representing 1075.5 (95% confidence interval (CI) = 1067.4–1083.6) visits per 100,000 person-years. ILI-related visit rates increased as each of material and social deprivation increased; increases were slightly greater for material deprivation. Comparing the most deprived quintile to the least deprived quintile: for material deprivation, ILI-related ED visit rates were two times higher (rate ratio (RR) = 2.00, 95% CI = 1.96–2.05); and, for social deprivation, one-and-a-half times higher (RR = 1.47, 95% CI = 1.44–1.51). ConclusionsHigher area-level material and social deprivation were associated with higher ILI-related ED visit rates. These findings can be used to identify areas that may need additional public health and healthcare resources and to improve targeting of prevention strategies. Understanding differentials in healthcare use such as this may be especially relevant to ensuring equity of outcomes for pandemic preparedness planning.

A Randomized Trial of Two 2-Dose Influenza Vaccination Strategies for Patients Following Autologous Hematopoietic Stem Cell Transplantation.

Seroprotection and seroconversion rates are not well understood for 2-dose inactivated influenza vaccination (IIV) schedules in autologous hematopoietic stem cell transplantation (autoHCT) patients. A randomized, single-blind, controlled trial of IIV in autoHCT patients in their first year post-transplant was conducted. Patients were randomized 1:1 to high-dose (HD) IIV followed by standard dose (SD) vaccine (HD-SD arm) or 2 SD vaccines (SD-SD arm) 4 weeks apart. Hemagglutination inhibition (HI) assay for IIV strains was performed at baseline, 1, 2, and 6 months post-first dose. Evaluable primary outcomes were seroprotection (HI titer ≥40) and seroconversion (4-fold titer increase) rates and secondary outcomes were geometric mean titers (GMTs), GMT ratios (GMRs), adverse events, influenza-like illness (ILI), and laboratory-confirmed influenza (LCI) rates and factors associated with seroconversion. Sixty-eight patients were enrolled (34/arm) with median age of 61.5 years, majority male (68%) with myeloma (68%). Median time from autoHCT to vaccination was 2.3 months. For HD-SD and SD-SD arms, percentages of patients achieving seroprotection were 75.8% and 79.4% for H1N1, 84.9% and 88.2% for H3N2 (all P > .05), and 78.8% and 97.1% for influenza-B/Yamagata (P = .03), respectively. Seroconversion rates, GMTs and GMRs, and number of ILI or LCIs were not significantly different between arms. Adverse event rates were similar. Receipt of concurrent cancer therapy was independently associated with higher odds of seroconversion (OR, 4.3; 95% CI, 1.2-14.9; P = .02). High seroprotection and seroconversion rates against all influenza strains can be achieved with vaccination as early as 2 months post-autoHCT with either 2-dose vaccine schedules. Australian New Zealand Clinical Trials Registry: ACTRN12619000617167.

Seasonality of Influenza-Like-Illness and Acute Cardiovascular Events Are Related Regardless of Vaccine Effectiveness.

BackgroundInfluenza has been identified as a trigger for stroke and myocardial infarction (MI) with prior studies demonstrating that influenza vaccination may decrease risk of stroke and MI.Methods and ResultsWe used data from the New York Department of Health Statewide Planning and Research Cooperative System to evaluate whether annual variability in influenza vaccination effectiveness (VE) would be associated with cardiovascular events. Daily and monthly counts of outpatient and inpatient visits for influenza‐like illness (ILI), stroke, and MI were identified using International Classification of Diseases, Ninth Revision (ICD‐9) codes; VE data for each year are publicly available. We identified pertinent lags between ILI, stroke, and MI using prewhitening cross‐correlation functions and applied them to autoregressive integrated moving average time series regression models. Time series forecasting systems assessed correlations among ILI, stroke, and MI, and the effect of VE on these relationships. Cross‐correlation functions indicated stroke events increased 1 month after increases in ILI rates; MIs increased immediately. Accounting for seasonality and lag, peaks in ILI rates were significantly related to peaks in stroke (P=0.04) and MI (P=0.01). Time forecasting analyses indicated no relationship between VE and cardiovascular events.ConclusionsWe identified that seasonality of cardiovascular events may be associated with seasonality in ILI, though VE did not modify this relationship.

A spatio-temporal analysis of influenza-like illness in Iran from 2011 to 2016.

Background: Investigating the spatial aspects of the disease can help decision-makers and researchers better understand the pattern of the disease, and is also very important in the implementation of the disease control programs. Given the vast area of Iran, as well as the diverse geographical and climate conditions of the country, using the geographical information system (GIS) is a suitable method for the study of influenza. In this study, we provide a clear picture of the distribution of the influenza-like illness (ILI) in Iranian provinces through the years from 2011 to 2016 by applying a spatio-temporal analysis, using geographic information system (GIS). Disease rates by location and year are estimated, and then hot spots and cold spots are distinguished. Methods: This study was conducted using the ILI incidence rate data recorded in the Iranian Influenza Surveillance System from August 2011 to August 2016. The Choropleth map method and the various equal interval and natural break classifications were used. The local Getis-Ord Gi* method was then used to identify the hot spots and regions where, for some reason, the distribution of the disease had significantly clustered spatially. Statistical analyses were done using the ArcGIS 10.2 software. Results: This study indicates that the highest ILI rate belongs to the period from August 2014 to August 2015 with a rate of 180.26 (95%CI: 177.65 to 182.9) per 100,000 people. The results show that the highest 5-year mean of ILI rate belongs to Zanjan, Markazi, Lorestan, Ilam, North Khorasan, and South Khorasan provinces. Also, results from the local Getis-Ord Gi* method show that ILI has formed a hot spot between the years 2011 and 2013 on the eastern borders of Iran and afterward during the years 2014 to 2016 in the western regions of the country. Conclusion: Given the importance of influenza and its huge economic burden on the society, identifying the hot spot regions can help better manage the disease. This study indicates the distribution of the disease has formed a hot spot in the western regions of the country.

Impact of Public Health Interventions on Seasonal Influenza Activity During the COVID-19 Outbreak in Korea.

BackgroundCOVID-19 was introduced in Korea early and experienced a large outbreak in mid-February. We aimed to review the public health interventions used during the COVID-19 outbreak and describe the impact on seasonal influenza activity in Korea.MethodsNational response strategies and public health interventions, along with daily COVID-19 confirmed cases in Korea were reviewed during the pandemic. National influenza surveillance data were compared between seven sequential seasons. Characteristics of each season, including the rate of influenza-like illness (ILI), duration of epidemic, date of termination of epidemic, distribution of influenza virus strain and hospitalization were analyzed.ResultsAfter various public health interventions including enforced public education on hand hygiene, cough etiquette and staying at home with respiratory symptoms, universal mask use in public places, refrain from non-essential social activities and school closure, the duration of the influenza epidemic in 2019/2020 decreased by 6-12 weeks and the influenza activity peak rated 49.8 ILI/1,000 visits compared to 71.9-86.2 ILI/1,000 visits of previous seasons. During the period of enforced social distancing from week 9 to 17 of 2020, influenza hospitalization cases were 11.9-26.9-fold lower compared with previous seasons. During the 2019/2020 season, influenza B accounted for only 4%, in contrast with previous seasons in which influenza B accounted for 26.6% to 54.9% of all cases.ConclusionsEfforts to activate high level national response not only led to a decrease in COVID-19, but also substantial decrease in seasonal influenza activity. Interventions applied to control COVID-19 may serve as useful strategies for prevention and control of influenza in upcoming seasons.