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  1. Article ; Online: What would have happened anyway? Population data source considerations when estimating background incident rates of adverse events following immunisation to inform vaccine safety.

    Clothier, Hazel J / Shetty, Aishwarya N / Mesfin, Yonatan / Mackie, Michael / Pearce, Christopher / Buttery, Jim P

    Vaccine

    2024  Volume 42, Issue 5, Page(s) 1108–1115

    Abstract: Introduction: Understanding background incident rates of adverse events following immunisation (AEFI) is essential to rapidly detect, evaluate, respond to, and communicate about vaccine safety concerns, especially for new vaccines. Creating estimates ... ...

    Abstract Introduction: Understanding background incident rates of adverse events following immunisation (AEFI) is essential to rapidly detect, evaluate, respond to, and communicate about vaccine safety concerns, especially for new vaccines. Creating estimates based on geographic specific population level data is increasingly important, as new AEFI presentations will be subject to the same local influences of population demography, exposures, health system variations and level of health care sought.
    Methods: We conducted a retrospective cohort analysis of hospital admissions, emergency department presentations and general practice consultations from 2015 to 2019-before introduction of COVID-19, Mpox or Shingrix vaccination-to estimate background incident rates for 37 conditions considered potential AEFI of special interest (AESI). Background incident rates per 100,000 population were calculated and presented as cases expected to occur coincidentally 1 day, 1 week and 6 weeks post-vaccination, by life-stage age-groups and presenting healthcare setting. We then assessed the proportional contribution of each data source to inform each AESI background rate estimate.
    Results: 16,437,156 episodes of the 37 AESI were identified. Hospital admissions predominantly informed 19 (51%) of AESI, including exclusively ADEM and CVST; 8 AESI (22%) by primary care, and 10 (27%) a mix. Four AESI (allergic urticaria, Bell's palsy, erythema multiform and sudden death) were better informed by emergency presentations than admissions, but conversely 11 AESI (30%) were not captured in ICD-10 coded emergency presentations at all.
    Conclusions: Emergent safety concerns are inevitable in population-wide implementation of new vaccines, therefore understanding local background rates aids both safety signal detection as well as maintaining public confidence in vaccination. Hospital and primary care data sources can be interrogated to inform expected background incident rates of adverse events that may occur following vaccination. However, it is necessary to understand which data-source provides best intelligence according to nature of condition and presenting healthcare setting.
    MeSH term(s) Humans ; Retrospective Studies ; Adverse Drug Reaction Reporting Systems ; Vaccination/adverse effects ; Immunization/adverse effects ; Vaccines/adverse effects
    Chemical Substances Vaccines
    Language English
    Publishing date 2024-01-22
    Publishing country Netherlands
    Document type Journal Article
    ZDB-ID 605674-x
    ISSN 1873-2518 ; 0264-410X
    ISSN (online) 1873-2518
    ISSN 0264-410X
    DOI 10.1016/j.vaccine.2024.01.025
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  2. Article ; Online: Acute disseminated encephalomyelitis and transverse myelitis following COVID-19 vaccination - A self-controlled case series analysis.

    Morgan, Hannah J / Clothier, Hazel J / Sepulveda Kattan, Gonzalo / Boyd, James H / Buttery, Jim P

    Vaccine

    2024  Volume 42, Issue 9, Page(s) 2212–2219

    Abstract: Acute Disseminated Encephalomyelitis (ADEM) and Transverse Myelitis (TM) are within the group of immune mediated disorders of acquired demyelinating syndromes. Both have been described in temporal association following various vaccinations in case ... ...

    Abstract Acute Disseminated Encephalomyelitis (ADEM) and Transverse Myelitis (TM) are within the group of immune mediated disorders of acquired demyelinating syndromes. Both have been described in temporal association following various vaccinations in case reports and case series and have been evaluated in observational studies. A recent analysis conducted by The Global Vaccine Data Network (GVDN) observed an excess of ADEM and TM cases following the adenoviral vectored ChAdOx1 nCoV-19 (AZD1222) and mRNA-1273 vaccines, compared with historically expected background rates from prior to the pandemic. Further epidemiologic studies were recommended to explore these potential associations. We utilized an Australian vaccine datalink, Vaccine Safety Health-Link (VSHL), to perform a self-controlled case series analysis for this purpose. VSHL was selected for this analysis as while VSHL data are utilised for GVDN association studies, they were not included in the GVDN observed expected analyses. The VSHL dataset contains vaccination records sourced from the Australian Immunisation Register, and hospital admission records from the Victorian Admitted Episodes Dataset for 6.7 million people. These datasets were used to determine the relative incidence (RI) of G040 (ADEM) and G373 (TM) ICD-10-AM coded admissions in the 42-day risk window following COVID-19 vaccinations as compared to control periods either side of the risk window. We observed associations between ChAdOx1 adenovirus vector COVID-19 vaccination and ADEM (all dose RI: 3.74 [95 %CI 1.02,13.70]) and TM (dose 1 RI: 2.49 [95 %CI: 1.07,5.79]) incident admissions. No associations were observed between mRNA COVID-19 vaccines and ADEM or TM. These findings translate to an extremely small absolute risk of ADEM (0.78 per million doses) and TM (1.82 per million doses) following vaccination; any potential risk of ADEM or TM should be weighed against the well-established protective benefits of vaccination against COVID-19 disease and its complications. This study demonstrates the value of the GVDN collaboration leveraging large population sizes to examine important vaccine safety questions regarding rare outcomes, as well as the value of linked population level datasets, such as VSHL, to rapidly explore associations that are identified.
    MeSH term(s) Humans ; Australia/epidemiology ; ChAdOx1 nCoV-19 ; COVID-19/epidemiology ; COVID-19/prevention & control ; COVID-19 Vaccines/adverse effects ; Encephalomyelitis, Acute Disseminated/chemically induced ; Encephalomyelitis, Acute Disseminated/epidemiology ; Myelitis, Transverse/etiology ; Myelitis, Transverse/complications ; Vaccination/adverse effects ; Vaccines
    Chemical Substances ChAdOx1 nCoV-19 (B5S3K2V0G8) ; COVID-19 Vaccines ; Vaccines
    Language English
    Publishing date 2024-02-12
    Publishing country Netherlands
    Document type Case Reports ; Journal Article
    ZDB-ID 605674-x
    ISSN 1873-2518 ; 0264-410X
    ISSN (online) 1873-2518
    ISSN 0264-410X
    DOI 10.1016/j.vaccine.2024.01.099
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  3. Article ; Online: Vulval (Lipschütz) ulcers in young females associated with SARS-CoV-2 infection and COVID-19 vaccination: case series.

    Crofts, Victoria Litza / Clothier, Hazel J / Mallard, John / Buttery, Jim P / Grover, Sonia R

    Archives of disease in childhood

    2023  Volume 108, Issue 4, Page(s) 326–327

    MeSH term(s) Female ; Humans ; COVID-19/prevention & control ; COVID-19 Vaccines/adverse effects ; SARS-CoV-2 ; Ulcer/etiology ; Vaccination ; Vulvar Diseases/etiology
    Chemical Substances COVID-19 Vaccines
    Language English
    Publishing date 2023-01-06
    Publishing country England
    Document type Letter
    ZDB-ID 524-1
    ISSN 1468-2044 ; 0003-9888 ; 1359-2998
    ISSN (online) 1468-2044
    ISSN 0003-9888 ; 1359-2998
    DOI 10.1136/archdischild-2022-325149
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  4. Article ; Online: Interdisciplinary Learning Health System Response to Public Vaccine Concerns.

    Dimaguila, Gerardo Luis / Javed, Muhammad / Clothier, Hazel J / Hickman, Jo / Petrovic, Dan / Machingaifa, Francesca / Kaufman, Jessica / Habibabadi, Sedigh Khademi / Palmer, Christopher / Buttery, Jim

    Studies in health technology and informatics

    2024  Volume 310, Page(s) 1146–1150

    Abstract: In Victoria, Australia, jurisdictional vaccine safety service is conducted by SAEFVIC (Surveillance of Adverse Events Following Vaccination in the Community). SAEFVIC developed a public Vaccine Safety Report (saefvic.online/vaccinesafety) to present key ... ...

    Abstract In Victoria, Australia, jurisdictional vaccine safety service is conducted by SAEFVIC (Surveillance of Adverse Events Following Vaccination in the Community). SAEFVIC developed a public Vaccine Safety Report (saefvic.online/vaccinesafety) to present key surveillance information. This study applies an interdisciplinary learning health system approach to evaluate the report, taking into consideration public expressions of concern on social media.
    MeSH term(s) Humans ; Learning Health System ; Vaccines/adverse effects ; Vaccination/adverse effects ; Interdisciplinary Studies ; Victoria
    Chemical Substances Vaccines
    Language English
    Publishing date 2024-01-25
    Publishing country Netherlands
    Document type Journal Article
    ISSN 1879-8365
    ISSN (online) 1879-8365
    DOI 10.3233/SHTI231144
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  5. Article ; Online: Background rates of hospital transfer and death in Australian aged care facilities: estimates to assist interpretation of rates after COVID-19 vaccination.

    Clothier, Hazel J / Mesfin, Yonatan M / Strange, Steven / Buttery, Jim P

    The Medical journal of Australia

    2021  Volume 215, Issue 4, Page(s) 180–181

    MeSH term(s) Aged ; Australia ; COVID-19/mortality ; COVID-19/prevention & control ; COVID-19 Vaccines/administration & dosage ; Homes for the Aged/organization & administration ; Hospital Mortality/trends ; Hospitalization/statistics & numerical data ; Humans ; Nursing Homes/organization & administration ; Residential Facilities ; Vaccination/trends
    Chemical Substances COVID-19 Vaccines
    Language English
    Publishing date 2021-07-15
    Publishing country Australia
    Document type Letter
    ZDB-ID 186082-3
    ISSN 1326-5377 ; 0025-729X
    ISSN (online) 1326-5377
    ISSN 0025-729X
    DOI 10.5694/mja2.51170
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  6. Article ; Online: Audiovestibular adverse events following COVID-19 vaccinations.

    Shetty, Aishwarya N / Morgan, Hannah J / Phuong, Linny K / Mallard, John / Vlasenko, Diana / Pearce, Christopher / Crawford, Nigel W / Buttery, Jim P / Clothier, Hazel J

    Vaccine

    2024  Volume 42, Issue 8, Page(s) 2011–2017

    Abstract: Introduction: Evidence regarding audiovestibular adverse events post COVID-19 vaccination to date has been inconclusive regarding a potential association. This study aimed to determine if there was an increase in audiovestibular events following COVID- ... ...

    Abstract Introduction: Evidence regarding audiovestibular adverse events post COVID-19 vaccination to date has been inconclusive regarding a potential association. This study aimed to determine if there was an increase in audiovestibular events following COVID-19 vaccination in South-eastern Australia during January 2021-March 2023.
    Methods: A multi-data source approach was applied. First, a retrospective observational analysis of spontaneous reports of audiovestibular events to a statewide vaccine safety surveillance service, SAEFVIC. Second, a self-controlled case series analysis using general practice data collected via the POpulation Level Analysis and Reporting (POLAR) tool.
    Results and conclusions: This study is the first to demonstrate an increase in general practice presentations of vertigo following mRNA vaccines (RI = 1.40, P <.001), and tinnitus following both the Vaxzevria® adenovirus vector and mRNA vaccines (RI = 2.25, P <.001 and 1.53, P <.001 respectively). There was no increase in hearing loss following any COVID-19 vaccinations. Our study, however, was unable to account for the potential of concurrent COVID-19 infections, which literature has indicated to be associated with audiovestibular events. Healthcare providers and vaccinees should be alert to potential audiovestibular complaints after COVID-19 vaccination. Our analysis highlights the importance of using large real-world datasets to gather reliable evidence for public health decision making.
    MeSH term(s) Humans ; COVID-19/prevention & control ; COVID-19 Vaccines/adverse effects ; mRNA Vaccines ; Retrospective Studies ; Vaccination/adverse effects
    Chemical Substances COVID-19 Vaccines ; mRNA Vaccines
    Language English
    Publishing date 2024-02-22
    Publishing country Netherlands
    Document type Journal Article ; Observational Study
    ZDB-ID 605674-x
    ISSN 1873-2518 ; 0264-410X
    ISSN (online) 1873-2518
    ISSN 0264-410X
    DOI 10.1016/j.vaccine.2024.02.051
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  7. Article ; Online: Shoulder injury following COVID-19 vaccine administration: a case series and proposed diagnostic algorithm.

    Petrakis, Nikki / Addison, Mel / Penak, Bianca / Schrader, Silja / Mallard, John / Clothier, Hazel J / Buttery, Jim P / Crawford, Nigel W / Cheng, Daryl R

    Expert review of vaccines

    2023  Volume 22, Issue 1, Page(s) 299–306

    Abstract: Background: Shoulder Injury Related to Vaccine Administration (SIRVA) is a preventable adverse event following incorrect vaccine administration, which can result in significant long-term morbidity. There has been a notable surge in reported cases of ... ...

    Abstract Background: Shoulder Injury Related to Vaccine Administration (SIRVA) is a preventable adverse event following incorrect vaccine administration, which can result in significant long-term morbidity. There has been a notable surge in reported cases of SIRVA as a rapid national population-based COVID-19 immunization program has been rolled out across Australia.
    Methods: Surveillance of Adverse Events Following Vaccination in the Community (SAEFVIC) in Victoria identified 221 suspected cases of SIRVA following the commencement of the COVID-19 vaccination program, reported between February 2021 and February 2022. This review describes the clinical features and outcomes of SIRVA in this population. Additionally, a suggested diagnostic algorithm is proposed, in order to facilitate early recognition and management of SIRVA.
    Results: 151 cases were confirmed as SIRVA, with 49.0% having received vaccines at state vaccination centers. 75.5% were suspected incorrect administration site, with most patients experiencing shoulder pain and restricted movement within 24 hours of vaccination, lasting on average 3 months.
    Conclusion: Improved awareness and education regarding SIRVA is imperative in a pandemic vaccine roll-out. The development of a structured framework for evaluating and managing suspected SIRVA will aid in timely diagnosis and treatment, essential to mitigate potential long-term complications.
    MeSH term(s) Humans ; Algorithms ; COVID-19/diagnosis ; COVID-19/prevention & control ; COVID-19 Testing ; COVID-19 Vaccines/administration & dosage ; Shoulder Injuries ; Vaccination ; Vaccines ; Victoria/epidemiology
    Chemical Substances COVID-19 Vaccines ; Vaccines
    Language English
    Publishing date 2023-03-09
    Publishing country England
    Document type Review ; Journal Article
    ZDB-ID 2181284-6
    ISSN 1744-8395 ; 1476-0584
    ISSN (online) 1744-8395
    ISSN 1476-0584
    DOI 10.1080/14760584.2023.2189463
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  8. Article ; Online: Australasian Institute of Digital Health Summit 2022-Automated Social Media Surveillance for Detection of Vaccine Safety Signals: A Validation Study.

    Khademi Habibabadi, Sedigheh / Palmer, Christopher / Dimaguila, Gerardo L / Javed, Muhammad / Clothier, Hazel J / Buttery, Jim

    Applied clinical informatics

    2022  Volume 14, Issue 1, Page(s) 1–10

    Abstract: Background: Social media platforms have emerged as a valuable data source for public health research and surveillance. Monitoring of social media and user-generated data on the Web enables timely and inexpensive collection of information, overcoming ... ...

    Abstract Background: Social media platforms have emerged as a valuable data source for public health research and surveillance. Monitoring of social media and user-generated data on the Web enables timely and inexpensive collection of information, overcoming time lag and cost of traditional health reporting systems.
    Objectives: This article identifies personally experienced coronavirus disease 2019 (COVID-19) vaccine reactions expressed on Twitter and validate the findings against an established vaccine reactions reporting system.
    Methods: We collected around 3 million tweets from 1.4 million users between February 1, 2021, to January 31, 2022, using COVID-19 vaccines and vaccine reactions keyword lists. We performed topic modeling on a sample of the data and applied a modified F1 scoring technique to identify a topic that best differentiated vaccine-related personal health mentions. We then manually annotated 4,000 of the records from this topic, which were used to train a transformer-based classifier to identify likely personally experienced vaccine reactions. Applying the trained classifier to the entire data set allowed us to select records we could use to quantify potential vaccine side effects. Adverse events following immunization (AEFI) referred to in these records were compared with those reported to the state of Victoria's spontaneous vaccine safety surveillance system, SAEFVIC (Surveillance of Adverse Events Following Vaccination In the Community).
    Results: The most frequently mentioned potential vaccine reactions generally aligned with SAEFVIC data. Notable exceptions were increased Twitter reporting of bleeding-related AEFI and allergic reactions, and more frequent SAEFVIC reporting of cardiac AEFI.
    Conclusion: Social media conversations are a potentially valuable supplementary data source for detecting vaccine adverse event mentions. Monitoring of online observations about new vaccine-related personal health experiences has the capacity to provide early warnings about emerging vaccine safety issues.
    MeSH term(s) Humans ; Social Media ; COVID-19 Vaccines/adverse effects ; COVID-19/epidemiology ; COVID-19/prevention & control ; Vaccination ; Vaccines/adverse effects ; Adverse Drug Reaction Reporting Systems
    Chemical Substances COVID-19 Vaccines ; Vaccines
    Language English
    Publishing date 2022-11-09
    Publishing country Germany
    Document type Journal Article
    ISSN 1869-0327
    ISSN (online) 1869-0327
    DOI 10.1055/a-1975-4061
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  9. Article ; Online: Real-world Nuvaxovid COVID-19 vaccine safety profile after first 100,000 doses in Australia, 2022-2023

    Clothier, Hazel J / Parker, Claire / Mallard, John H / Effler, Paul / Bloomfield, Lauren / Carcione, Dale / Buttery, Jim P

    medRxiv

    Abstract: Introduction Nuvaxovid became available in Australia from February 2022, a year later than the first COVID-19 vaccines were released. It was a much-anticipated alternative vaccine for people that had either suffered an adverse event to and/or were ... ...

    Abstract Introduction Nuvaxovid became available in Australia from February 2022, a year later than the first COVID-19 vaccines were released. It was a much-anticipated alternative vaccine for people that had either suffered an adverse event to and/or were hesitant to receive one of the mRNA or adenovirus based COVID-19 vaccines. Although safety from clinical trials was reassuring, small trial population size, relatively low administration rates worldwide and limited post-licensure intelligence meant potential rare adverse events were underinformed. Methods We conducted a retrospective observational analysis of adverse events following immunisation (AEFI) spontaneously reported to SAFEVAC, the integrated vaccine safety surveillance system used by Victoria and Western Australia, Australia. Reports received from 14 Feb 2022 to 30 June 2023 were analysed by vaccinee demographics, reported reactions and COVID-19 vaccine dose received and compared as reporting rates (RR) per 100,000 doses administered. Results 356 AEFI reports were received, following 102,946 Nuvaxovid doses administered. Rates were higher post dose 1 than dose 2 (rate ratio 1.5, p=0.0008); primary series than booster (rate ratio 2.4, p<0.0001); in females than males (rate ratio 1.4, p<0.01), especially those aged 30-49 years (RR=1.6, p=0.002). Serious AEFI included 76 chest pain (RR=73.8), two myocarditis (RR=1.9) and 20 pericarditis (RR=19.4). No cases of Guillain Barre or thrombosis with thrombocytopaenia syndromes were reported and no deaths attributable to vaccination. Conclusion The shared SAFEVAC platform enables pooling of clinically reviewed data across jurisdictions, increasing the safety profile evidence base of novel vaccines like Nuvaxovid and improving the odds for identification and description of rare events across all vaccines.
    Keywords covid19
    Language English
    Publishing date 2024-03-18
    Publisher Cold Spring Harbor Laboratory Press
    Document type Article ; Online
    DOI 10.1101/2024.03.17.24304409
    Database COVID19

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  10. Article ; Online: Menstrual cycle changes increased following COVID-19 mRNA vaccination: Social media validation and self-controlled case series analysis

    Shetty, Aishwarya N / Kattan, Gonzalo Sepulveda / Javed, Muhammad / Pearce, Christopher / Clothier, Hazel J / Buttery, Jim P

    medRxiv

    Abstract: Objectives - To investigate if there was an increase in menstrual abnormality related presentation post COVID-19 vaccination. Design - BERTopic machine learning, with a guided topic modelling option was used to analyse mentions of menstrual change in ... ...

    Abstract Objectives - To investigate if there was an increase in menstrual abnormality related presentation post COVID-19 vaccination. Design - BERTopic machine learning, with a guided topic modelling option was used to analyse mentions of menstrual change in relation to COVID-19 vaccination on the social media platform Reddit. Self-controlled case series (SCCS) analysis using general practice data collected via the POpulation Level Analysis and Reporting (POLAR) tool with permission from Primary Health Networks (PHNs) as the de-identified dataset owners in Victoria and New South Wales. Setting: Globally for social media analysis. Victoria and New South Wales (NSW), Australia for POLAR. Participants: For social media analysis, people who made a Reddit post about menstrual concerns post COVID-19 vaccine. For the SCCS analysis, people who presented to a POLAR GP registered practice with a new menstrual abnormality diagnosis. Exposures: COVID-19 vaccination with adenovirus vector [AstraZenecas Vaxzervria ChadOx1-S], mRNA [Pfizer-BioNTechs Comirnaty BNT162b2 and Modernas Spikevax] or protein-subunit [Novavaxs Nuvaxovid]). Outcomes and Measures: Scraped social media posts were pre-processed, analysed for positive, negative, and neutral sentiments and topic modelled. Menstrual abnormality presentations of interest were isolated from the general practice dataset aggregated by POLAR, by searching for relevant SNOMED CT codes. Similarly, relative incidence (RI) was calculated for all COVID-19 vaccine types. Results: Social media analysis saw peaks in menstrual change posts on Reddit since the global COVID-19 vaccine rollout. The SCCS analysis demonstrates an increase in general practice presentations of menstrual abnormality diagnosis following mRNA vaccines (RI= 1.14, 95% CI: 1.07 to 1.22, P <0.001). Conclusions and Relevance: This study demonstrates an increase in menstrual abnormality presentations following COVID-19 mRNA vaccination. Our findings validate the concerns raised on social media so people who are vaccinated or are considering future vaccines feel heard, supported, and validated. Our analysis highlights the importance of using large real-world datasets to gather reliable evidence for public health decision making.
    Keywords covid19
    Language English
    Publishing date 2023-10-31
    Publisher Cold Spring Harbor Laboratory Press
    Document type Article ; Online
    DOI 10.1101/2023.10.26.23297643
    Database COVID19

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