Origin of the H1N1 (Russian influenza) pandemic of 1977-A risk assessment using the modified Grunow-Finke tool (mGFT).

In 1977, the Soviet Union (Union of Soviet Socialist Republics [USSR]) notified the World Health Organization (WHO) about an outbreak of H1N1 influenza, which later spread to many countries. The H1N1 strain of 1977 reappeared after being absent from the world for over 20 years. This pandemic simultaneously spread to several cities in the USSR and China. Many theories have been postulated to account for the emergence of this pandemic, including natural and unnatural origins. The purpose of this study was to use the modified Grunow-Finke risk assessment tool (modified Grunow-Finke tool [mGFT]) to investigate the origin of the 1977 H1N1 pandemic. Data was collected from WHO archives and published documents. The assessment of the pandemic's origin involved the utilization of a modified version of the original Grunow-Finke risk assessment tool (GFT). Using the mGFT, the final score was 37 out of 60 points (probability: 62%), indicating a high likelihood that the Russian influenza pandemic of 1977 was of unnatural origin. Several variables supported this finding, including the sudden re-emergence of a previously extinct strain, a genetic signature of laboratory modification for vaccine development, and unusual epidemiology. Inter-rater reliability was moderate to high. By applying the mGFT to the 1977 Russian influenza pandemic, we established a high probability that this pandemic was of unnatural origin. Although this is not definitive, it is consistent with the possibility that it originated from an incompletely attenuated live influenza vaccine. The mGFT is a useful risk analysis tool to evaluate the origin of epidemics.

Use of a risk assessment tool to determine the origin of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2).

The origin of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is contentious. Most studies have focused on a zoonotic origin, but definitive evidence such as an intermediary animal host is lacking. We used an established risk analysis tool for differentiating natural and unnatural epidemics, the modified Grunow-Finke assessment tool (mGFT) to study the origin of SARS-COV-2. The mGFT scores 11 criteria to provide a likelihood of natural or unnatural origin. Using published literature and publicly available sources of information, we applied the mGFT to the origin of SARS-CoV-2. The mGFT scored 41/60 points (68%), with high inter-rater reliability (100%), indicating a greater likelihood of an unnatural than natural origin of SARS-CoV-2. This risk assessment cannot prove the origin of SARS-CoV-2 but shows that the possibility of a laboratory origin cannot be easily dismissed.

A machine learning-based universal outbreak risk prediction tool.

In order to prevent and control the increasing number of serious epidemics, the ability to predict the risk caused by emerging outbreaks is essential. However, most current risk prediction tools, except EPIRISK, are limited by being designed for targeting only one specific disease and one country. Differences between countries and diseases (e.g., different economic conditions, different modes of transmission, etc.) pose challenges for building models with cross-country and cross-disease prediction capabilities. The limitation of universality affects domestic and international efforts to control and prevent pandemic outbreaks. To address this problem, we used outbreak data from 43 diseases in 206 countries to develop a universal risk prediction system that can be used across countries and diseases. This system used five machine learning models (including Neural Network XGBoost, Logistic Boost, Random Forest and Kernel SVM) to predict and vote together to make ensemble predictions. It can make predictions with around 80%-90 % accuracy from economic, cultural, social, and epidemiological factors. Three different datasets were designed to test the performance of ML models under different realistic situations. This prediction system has strong predictive ability, adaptability, and generality. It can give universal outbreak risk assessment that are not limited by border or disease type, facilitate rapid response to pandemic outbreaks, government decision-making and international cooperation.

Monitoring the burden of COVID-19 and impact of hospital transfer policies on Australian aged-care residents in residential aged-care facilities in 2020.

BACKGROUND: Residential aged-care facilities in Australia emerged as the high-risk setting the COVID-19 outbreaks due to community transmission. The vulnerable aged-care residents of these facilities suffered due to low hospital transfers and high mortality and morbidity rates. This study aimed to monitor and report the burden of COVID-19 in residential aged-care facilities across Australia and the impact of hospital transfer policies on resident hospitalisation during the first year of the pandemic. METHODS: We conducted a retrospective cohort study by collecting data from weekly aged-care outbreak reports published by open sources and official government sources between 1st March and 20th November 2020. A comprehensive line list of outbreaks was created using open-source data. The line list included the name of the facility, location, COVID-19 cases among residents, & staff, resident hospitalisations, mode of transmission, number of resident deaths, and state policies involving resident hospitalisation. We also searched the websites of these facilities to collect data on their COVID-19 policies for the residents, staff, and visitors. Statistical analyses were performed on the data obtained. RESULTS: 126 aged-care COVID-19 outbreaks were identified in Australia during the study period. The incidence rate of COVID-19 infections among aged-care residents in Australia was (1118.5 per 100,000 resident population) which is 10 times higher than the general population (107.6 per 100,000 population). The hospitalisation rate for aged-care residents in Australia was 0.93 per 100,000 population. The hospitalisation rate of aged-care residents in Victoria was 3.14 per 100,000 population despite having the highest COVID-19 cases. Excluding South Australia, all states followed ad-hoc case-by-case hospital transfer policies for aged-care residents. CONCLUSION: This study documented a higher risk of COVID-19 infection for aged-care residents and workers but found low hospitalisation rates among residents across Australia. The hospitalisation rates in Victoria were higher than the national average but low when considering the COVID-19 infection rates in the state. The hospitalisation rates could have been impacted due to the state hospital transfer policies at that time. Immediate transfer of infected residents to hospitals may improve their survival and reduce the risk of infection to the other residents, as healthcare settings have more advanced infection control measures and are well-equipped with trained staff and resources.

Artificial intelligence in public health: the potential of epidemic early warning systems.

The use of artificial intelligence (AI) to generate automated early warnings in epidemic surveillance by harnessing vast open-source data with minimal human intervention has the potential to be both revolutionary and highly sustainable. AI can overcome the challenges faced by weak health systems by detecting epidemic signals much earlier than traditional surveillance. AI-based digital surveillance is an adjunct to-not a replacement of-traditional surveillance and can trigger early investigation, diagnostics and responses at the regional level. This narrative review focuses on the role of AI in epidemic surveillance and summarises several current epidemic intelligence systems including ProMED-mail, HealthMap, Epidemic Intelligence from Open Sources, BlueDot, Metabiota, the Global Biosurveillance Portal, Epitweetr and EPIWATCH. Not all of these systems are AI-based, and some are only accessible to paid users. Most systems have large volumes of unfiltered data; only a few can sort and filter data to provide users with curated intelligence. However, uptake of these systems by public health authorities, who have been slower to embrace AI than their clinical counterparts, is low. The widespread adoption of digital open-source surveillance and AI technology is needed for the prevention of serious epidemics.

Modeling on the Effects of Deliberate Release of Aerosolized Inhalational Bacillus anthracis (Anthrax) on an Australian Population.

This study aimed to determine optimal mitigation strategies in the event of an aerosolized attack with Bacillus anthracis, a category A bioterrorism agent with a case fatality rate of nearly 100% if inhaled and untreated. To simulate the effect of an anthrax attack, we used a plume dispersion model for Sydney, Australia, accounting for weather conditions. We determined the radius of exposure in different sizes of attack scenarios by spore quantity released per second. Estimations of different spore concentrations were then used to calculate the exposed population to inform a Susceptible-Exposed-Infected-Recovered (SEIR) deterministic mathematical model. Results are shown as estimates of the total number of exposed and infected people, along with the burden of disease, to quantify the amount of vaccination and antibiotics doses needed for stockpiles. For the worst-case scenario, over 500,000 people could be exposed and over 300,000 infected. The number of deaths depends closely on timing to start postexposure prophylaxis. Vaccination used as a postexposure prophylaxis in conjunction with antibiotics is the most effective mitigation strategy to reduce deaths after an aerosolized attack and is more effective when the response starts early (2 days after release) and has high adherence, while it makes only a small difference when started late (after 10 days).

Uptake of influenza, pneumococcal and herpes zoster vaccines among people with heart failure and atrial fibrillation.

BACKGROUND: Cardiovascular diseases are the major cause of hospitalisation and death globally. Infections exacerbate cardiovascular events among cardiac patients, contributing to all-cause mortality. Vaccination is a cheap and effective intervention that can prevent infection. In Australia, influenza, pneumococcal and herpes zoster vaccines are recommended and funded for high-risk adults such as cardiac patients. There is high prevalence of high-risk adults in Western Sydney. OBJECTIVES: This study investigates the uptake of influenza, pneumococcal and herpes zoster vaccines in patients admitted with heart failure and atrial fibrillation in a tertiary hospital in Western Sydney and factors associated with the uptake of the vaccines. METHODS: Consecutive patients' hospitalised between 2014 and 2018 with heart failure or atrial fibrillation as principal diagnoses were identified. Information on patients' social demographic, clinical and vaccination status was collected and described using descriptive analysis. Univariate and multivariate analyses were conducted to determine factors associated with the uptake of the vaccines. RESULTS: Low uptake for pneumococcal (40-45 %) and herpes zoster (15 %) vaccines were found. Prevalence of influenza vaccination was lower among participants younger than 65 (51-72 %) than in older ones (78-96 %). Australia-born participants were more likely to receive pneumococcal vaccine than those born overseas (OR 2.02, 95 % CI 1.05-3.89). Participants 65 years or older and those with comorbidities such as hypertension, COPD and chronic renal impairment were more likely to receive the vaccines. CONCLUSION: Multidisciplinary strategies are needed to improve access to vaccination, community knowledge, community engagement, and healthcare provider support to provide appropriate care to migrants and younger cardiac patients and reduce morbidity and mortality in this high-risk group.

Modelling vaccination capacity at mass vaccination hubs and general practice clinics: a simulation study.

BACKGROUND: COVID-19 mass vaccination programs place an additional burden on healthcare services. We aim to model the queueing process at vaccination sites to inform service delivery. METHODS: We use stochastic queue network models to simulate queue dynamics in larger mass vaccination hubs and smaller general practice (GP) clinics. We estimate waiting times and daily capacity based on a range of assumptions about appointment schedules, service times and staffing and stress-test these models to assess the impact of increased demand and staff shortages. We also provide an interactive applet, allowing users to explore vaccine administration under their own assumptions. RESULTS: Based on our assumed service times, the daily throughput for an eight-hour clinic at a mass vaccination hub ranged from 500 doses for a small hub to 1400 doses for a large hub. For GP clinics, the estimated daily throughput ranged from about 100 doses for a small practice to almost 300 doses for a large practice. What-if scenario analysis showed that sites with higher staff numbers were more robust to system pressures and mass vaccination sites were more robust than GP clinics. CONCLUSIONS: With the requirement for ongoing COVID-19 booster shots, mass vaccination is likely to be a continuing feature of healthcare delivery. Different vaccine sites are useful for reaching different populations and maximising coverage. Stochastic queue networks offer a flexible and computationally efficient approach to simulate vaccination queues and estimate waiting times and daily throughput to inform service delivery.

Global epidemiology of vaccine-derived poliovirus 2016-2021: A descriptive analysis and retrospective case-control study.

Background: Vaccine derived poliovirus (VDPV) remains a major barrier to polio eradication, and recent growing emergences are concerning. This paper presents the global epidemiology of circulating VDPV (cVDPV) by exploring associations between demographic and socioeconomic factors with its recent rise. Methods: Data on reported cVDPV cases and isolates between January 1 2016 and June 30 2021 were compiled from EPIWATCH, an open-source observatory for outbreak scanning and analysis, the World Health Organisation (WHO) and ProMed, and analysed descriptively. Reports containing cVDPV case information were included while duplicates and defective links were excluded. Data collection occurred from April 5 2021 to July 16 2021. To identify factors associated with cVDPV, a retrospective case-control study comparing socioeconomic profiles of countries which reported cVDPV with those that did not was undertaken with weighted logistic regression analysis. Findings: cVDPV caused by serotype 2 poliovirus was the predominant strain (95%) of 1818 total human cVDPV cases reported. Of 40 countries reporting cVDPV cases or isolates, 22 (55%) had polio vaccination coverages below 80%. Low vaccination coverage (Adjusted OR = 83·41, 95% CI: [5·01, 1387·71], p = 0·0020) was found to be associated with increased odds of reporting cVDPV after adjusting for confounding effects of GDP per capita, female adult literacy rates, maternal mortality rate, and Global Peace Index. Interpretation: Our findings reinforce the importance of maintaining high levels of vaccination, as risk of re-emergence rises when immunity wanes. Interventions to increase vaccination and standards of living in developing countries, coupled with robust surveillance are required if humanity hopes to eradicate polio in the near future. Funding: This research was supported by the MRFF 2021 Frontier Health and Medical Research Grant (ID RFRHPI000280), Department of Health, the Australian Government.

Adapt or die: how the pandemic made the shift from EBM to EBM+ more urgent.

Evidence-based medicine (EBM's) traditional methods, especially randomised controlled trials (RCTs) and meta-analyses, along with risk-of-bias tools and checklists, have contributed significantly to the science of COVID-19. But these methods and tools were designed primarily to answer simple, focused questions in a stable context where yesterday's research can be mapped more or less unproblematically onto today's clinical and policy questions. They have significant limitations when extended to complex questions about a novel pathogen causing chaos across multiple sectors in a fast-changing global context. Non-pharmaceutical interventions which combine material artefacts, human behaviour, organisational directives, occupational health and safety, and the built environment are a case in point: EBM's experimental, intervention-focused, checklist-driven, effect-size-oriented and deductive approach has sometimes confused rather than informed debate. While RCTs are important, exclusion of other study designs and evidence sources has been particularly problematic in a context where rapid decision making is needed in order to save lives and protect health. It is time to bring in a wider range of evidence and a more pluralist approach to defining what counts as 'high-quality' evidence. We introduce some conceptual tools and quality frameworks from various fields involving what is known as mechanistic research, including complexity science, engineering and the social sciences. We propose that the tools and frameworks of mechanistic evidence, sometimes known as 'EBM+' when combined with traditional EBM, might be used to develop and evaluate the interdisciplinary evidence base needed to take us out of this protracted pandemic. Further articles in this series will apply pluralistic methods to specific research questions.

Influenza cases in nine aged care facilities in Sydney, Australia over a three-year surveillance period, 2018-2020.

BACKGROUND: Influenza outbreaks in aged care facilities are a major public health concern. In response to the severe 2017 influenza season in Australia, enhanced influenza vaccines were introduced from 2018 onwards for those over 65 and more emphasis was placed on improving vaccination rates among aged care staff. During the COVID-19 pandemic, these efforts were then further escalated to reduce the additional burden that influenza could pose to facilities. METHODS: An observational epidemiological study was conducted from 2018 to 2020 in nine Sydney (Australia) aged care facilities of the same provider. De-identified vaccination data and physical layout data were collected from participating facility managers from 2018 to 2020. Active surveillance of influenza-like illness was carried out from 2018 to 2020 influenza seasons. Correlation and Poisson regression analyses were carried out to explore the relationship between physical layout variables to occurrence of influenza cases. RESULTS: Influenza cases were low in 2018 and 2019, and there were no confirmed influenza cases identified in 2020. Vaccination rates increased among staff by 50.5% and residents by 16.8% over the three-year period of surveillance from 2018 to 2020. For each unit increase in total number of beds, common areas, single rooms, all types of rooms (including double occupancy rooms), the influenza cases increased by 1.02 (95% confidence interval:1.018-1.025), 1.04 (95% confidence interval: 1.019-1.073), 1.03 (95% confidence interval: 1.016-1 0.038) and 1.02 (95% confidence interval:1.005-1.026) times which were found to be statistically significant. For each unit increase in the proportion of shared rooms, influenza cases increased by 1.004 (95% confidence interval:1.0001-1.207) which was found to be statistically significant. CONCLUSIONS: There is a relationship between influenza case counts and aspects of the physical layout such as facility size, and this should be considered in assessing risk of outbreaks in aged care facilities. Increased vaccination rates in staff and COVID-19 prevention and control measures may have eliminated influenza in the studied facilities in 2020.

The ability of face masks to reduce transmission of microbes.

CLINICAL RELEVANCE: Optometrists have been advised to wear face masks during the COVID-19 pandemic. This study examined whether face masks were equally protective against transmission of microbes. BACKGROUND: The aim of the current study was to examine the ability of face masks to reduce transmission of microbes in aerosols and during speech. METHODS: Different face masks, surgical, medical 3-ply and cloth masks with different layers were used. The masks were tested under the ASTM standard F2101-1 to measure their ability to reduce the transmission of aerosolised Staphylococcus aureus. Bacterial cells in different sized aerosols were captured on agar plates. The ability of masks to reduce the transmission of bacteria during speech over 30 cm was measured. Bacteria were captured in masks or on agar plates at a distance of 30 cm during the speech. RESULTS: All masks reduced the transmission of aerosolised S. aureus (p ≤ 0.007). The medical 3-ply and cloth masks with three layers reduced the transmission of S. aureus aerosols (3.3 µm) by 98% and surgical and seven-layer masks reduced this by 100%. An antibacterial silver mask showed significantly greater transmission of S. aureus in aerosols of 4.7 µm (16 ± 6 cells) and 3.3 µm (122 ± 66 cells) compared to all other masks (0-3 cells and 0-15 cells, respectively; p ≤ 0.016). Surgical and three-layer masks had significantly worse filtration of 1.1 µm aerosols than for other aerosol sizes. Wearing a mask reduced the transmission of bacteria during speech, but the inner surface of these masks became contaminated with 528-3060 bacterial cells. CONCLUSIONS: Face masks effectively reduce the transmission of microbes in laboratory tests. Face masks made with seven layers were very effective at stopping transmission of S. aureus in all aerosol particle sizes. However, face masks become rapidly contaminated during wear. If masks are to be re-used, they should be regularly replaced or appropriately washed.

Thrombosis with Thrombocytopenia Syndrome (TTS) following AstraZeneca ChAdOx1 nCoV-19 (AZD1222) COVID-19 vaccination - A risk-benefit analysis for people < 60 years in Australia.

The AstraZeneca ChAdOx1 nCoV-19 (AZD1222) vaccine is associated with Thrombosis with Thrombocytopenia Syndrome (TTS) in 3/100,000 vaccinations with high fatality rates reported in many countries. We conducted a risk-benefit analysis for Australians aged 18-59 years, comparing the risk of vaccination versus infection, and rate of TTS to other vaccines which prompted policy change following rare adverse events - rotavirus, smallpox and oral polio vaccines. COVID-19 deaths over 12 months range from 0 to 417 in current and future worst case scenarios. In the past 15 months 20 COVID-19 deaths occurred in people < 60 years compared to 890 deaths over 60 years. The estimated possible number of TTS cases is 347, with vaccine-related deaths ranging from 17 to 153if 80% of adults 18-59 years are vaccinated. The reported rate of TTS is in the same range as rare but serious adverse events associated with other vaccines that have been subject to policy change. In Australia, the potential risks of the AZD1222 vaccine in younger adults, who are at low risk of dying from COVID-19, may outweigh the benefits.

The Molecular Epidemiology and Clinical Phylogenetics of Rhinoviruses Among Paediatric Cases in Sydney, Australia.

OBJECTIVES: Rhinoviruses (RV) represent the most common aetiological agent of all acute respiratory tract infections across all age groups and a significant burden of disease among children. Recent studies have shown that RV-A and RV-C species are associated with increased disease severity. In order to better understand the potential associations between RV species and clinical features among paediatric cases, this study aimed to integrate genetic and epidemiological data using Bayesian phylogenetic methods. METHODS: Potential associations between RV species and subtypes, and clinical disease severity using a matched dataset of 52 RV isolates sampled from children (< 18 years) in Sydney, Australia, between 2006 and 2009 were uncovered using epidemiological and phylogenetic methods. RESULTS: It was found that RV-C was significantly more likely to be isolated from paediatric cases aged < 2 years compared with RV-A, although no significant differences in recorded symptoms were observed. Significant phylogenetic-trait associations between age and the VP4/VP2 capsid protein phylogeny suggest that age-specific variations in infectivity among subtypes may may be possible. CONCLUSION: This study adds to the growing body of epidemiological evidence concerning RV. Improving surveillance and testing for RV, including routine whole genome sequencing, may improve understanding of the varied disease outcomes of RV species and subtypes. Future studies could aim to identify specific genetic markers associated with age-specific infectivity of RV, which could inform treatment practices and public health surveillance of RV.

Using open-source intelligence to identify early signals of COVID-19 in Indonesia.

OBJECTIVE: Open-source data from online news reports and informal sources may provide information about outbreaks before official notification. This study aims to evaluate the use of open-source data from the epidemic observatory, EpiWATCH, to identify the early signals of pneumonia of unknown cause as a proxy for COVID-19 in Indonesia. METHODS: Using open-source data on pneumonia of unknown cause in Indonesia between 1 November 2019 and 31 March 2020 (extracted from EpiWATCH, an open-source epidemic observatory), a descriptive analysis was performed to identify the trend of pneumonia of unknown cause in Indonesia before official notification of COVID-19 cases. RESULTS: A rise in reports of pneumonia of unknown cause was identified in Indonesia, starting from late January 2020. There were 304 reported cases of pneumonia of unknown cause, 30 of which occurred before the identification of the first COVID-19 cases on 2 March 2020. The early signals of pneumonia of unknown cause in Indonesia may indicate possible unrecognized circulation of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) before official detection. DISCUSSION: Open-source data may provide rapid, unvalidated information for early detection of outbreaks. Although unvalidated, such information may be used to supplement or trigger investigation and testing. As EpiWATCH sources global information, this methodology can be repeated for other countries within the Western Pacific Region, and for other diseases.

Experimental Evidence for the Optimal Design of a High-Performing Cloth Mask.

Cloth masks can be an alternative to medical masks during pandemics. Recent studies have examined the performance of fabrics under various conditions; however, the performance against violent respiratory events such as human sneezes is yet to be explored. Accordingly, we present a comprehensive experimental study using sneezes by a healthy adult and a tailored image-based flow measurement diagnostic system evaluating all dimensions of protection of commonly available fabrics and their layered combinations: the respiratory droplet blocking efficiency, water resistance, and breathing resistance. Our results reveal that a well-designed cloth mask can outperform a three-layered surgical mask for such violent respiratory events. Specifically, increasing the number of layers significantly increases the droplet blocking efficiency, on average by ∼20 times per additional fabric layer. A minimum of three layers is necessary to resemble the droplet blocking performance of surgical masks, and a combination of cotton/linen (hydrophilic inner layer)-blends (middle layer)-polyester/nylon (hydrophobic outer layer) exhibited the best performance among overall indicators tested. In an optimum three-layered design, the average thread count should be greater than 200, and the porosity should be less than 2%. Furthermore, machine washing at 60 °C did not significantly impact the performance of cloth masks. These findings inform the design of high-performing homemade cloth masks.

Modelling of optimal vaccination strategies in response to a bioterrorism associated smallpox outbreak.

The reemergence of smallpox as a bioterrorism attack is now an increasing and legitimate concern. Advances in synthetic biology have now made it possible for the virus to be synthesized in a laboratory, with methods publicly available. Smallpox introduction into a susceptible population, with increased immunosuppression and an aging population, raises questions of how vaccination should be used in an epidemic situation when supply may be limited. We constructed three modified susceptible-latent-infectious-recovered (SEIR) models to simulate targeted, ring and mass vaccination in response to a smallpox outbreak in Sydney, Australia. We used age-specific distributions of susceptibility, infectivity, contact rates, and tested outputs under different assumptions. The number of doses needed of second- and third-generation vaccines are estimated, along with the total number of deaths at the end of the epidemic. We found a faster response is the key and ring vaccination of traced contacts is the most effective strategy and requires a smaller number of doses. However if public health authorities are unable to trace a high proportion of contacts, mass vaccination with at least 125,000 doses delivered per day is required. This study informs a better preparedness and response planning for vaccination in a case of a smallpox outbreak in a setting such as Sydney.

Effect of statin use on the risk of influenza and influenza vaccine effectiveness.

BACKGROUND: Some studies have shown that statins reduce the efficacy of influenza vaccine. The aim was to examine the impact of statins on influenza and influenza vaccine effectiveness (VE). METHODS: This study was a post-hoc analysis of subjects in a prospective case-control study of influenza and acute myocardial infarction, where data on influenza infection, vaccination and statin use was collected. Study participants, aged ≥40 years were recruited from tertiary hospitals in Sydney from 2008 to 2010. Univariate and logistic regression analysis was performed. RESULTS: Of total 559 participants, 276 (49.4%) had been vaccinated and 196 (35.1%) were taking statins. The rate of laboratory confirmed influenza was significantly higher in unvaccinated statin users (adjusted odds ratio (AOR), 2.44; 95% CI: 1.06-5.62) compared to unvaccinated non-users. The VE was 98% overall, and not significantly different between statin users (92.4%) and non-statin users (100%). In adjusted analysis of all subjects, vaccination was significantly protective (AOR, 0.02; 95% CI: 0.01-0.15), and statins remained significantly associated with influenza risk (AOR, 2.47; 95% CI: 1.08-5.64). CONCLUSION: There was no significant difference in influenza VE by statin use, and vaccine was highly effective in both statin users and non-users. There was a significantly higher risk of influenza among statin users, independent of vaccination. Statins may increase the risk of influenza through immunomodulatory mechanisms, or this may be confounded by other risk factors for influenza. It is important that people on statins should be vaccinated against influenza.