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1.
Vaccine ; 39(2): 255-262, 2021 01 08.
Article in English | MEDLINE | ID: covidwho-971210

ABSTRACT

BACKGROUND: Pandemic planning has historically been oriented to respond to an influenza virus, with vaccination strategy being a key focus. As the current COVID-19 pandemic plays out, the Australian government is closely monitoring progress towards development of SARS-CoV2 vaccines as a definitive intervention. However, as in any pandemic, initial supply will likely be exceeded by demand due to limited manufacturing output. METHODS: We convened community juries in three Australian locations in 2019 to assess public acceptability and perceived legitimacy of influenza pandemic vaccination distribution strategies. Preparatory work included literature reviews on pandemic vaccine allocation strategies and on vaccine allocation ethics, and simulation modelling studies. We assumed vaccine would be provided to predefined priority groups. Jurors were then asked to recommend one of two strategies for distributing remaining early doses of vaccine: directly vaccinate people at higher risk of adverse outcomes from influenza; or indirectly protect the general population by vaccinating primary school students, who are most likely to spread infection. RESULTS: Thirty-four participants of diverse backgrounds and ages were recruited through random digit dialling and topic-blinded social media advertising. Juries heard evidence and arguments supporting different vaccine distribution strategies, and questioned expert presenters. All three community juries supported prioritising school children for influenza vaccination (aiming for indirect protection), one by 10-2 majority and two by consensus. Justifications included that indirect protection benefits more people and is likely to be more publicly acceptable. CONCLUSIONS: In the context of an influenza pandemic, informed citizens were not opposed to prioritising groups at higher risks of adverse outcomes, but if resources and epidemiological conditions allow, achieving population benefits should be a strategic priority. These insights may inform future SARS-CoV-2 vaccination strategies.


Subject(s)
COVID-19/epidemiology , Health Care Rationing/organization & administration , Immunization Programs/organization & administration , Influenza Vaccines/supply & distribution , Influenza, Human/prevention & control , Pandemics/prevention & control , Vaccination/ethics , Adolescent , Adult , Australia/epidemiology , Child , Female , Humans , Immunization Schedule , Influenza Vaccines/administration & dosage , Influenza Vaccines/economics , Influenza, Human/epidemiology , Influenza, Human/immunology , Influenza, Human/virology , Male , Middle Aged , Orthomyxoviridae/immunology , Public Health/economics , Public Health/methods , SARS-CoV-2/pathogenicity , Vaccination/economics , Vaccination Coverage/statistics & numerical data
2.
Vaccine ; 39(2): 332-342, 2021 01 08.
Article in English | MEDLINE | ID: covidwho-960153

ABSTRACT

INTRODUCTION: Passive surveillance is recommended globally for the detection of adverse events following immunisation (AEFI) but this has significant challenges. Use of Mobile health for vaccine safety surveillance enables a consumer-centred approach to reporting. The Stimulated Telephone Assisted Rapid Safety Surveillance (STARSS) a randomised control trial (RCT) sought to evaluate the efficacy and acceptability of SMS for AEFI surveillance. METHODS: Multi-centre RCT, participants were adult vaccinees or parents of children receiving any vaccine at a trial site. At enrolment randomisation occurred to one of two SMS groups or a control group. Prompts on days 2, 7 and 14 post-immunisation, were sent to the SMS group, to ascertain if a medical event following immunisation (MEFI) had occurred. No SMS's were sent to the control participants. Those in the SMS who notified an MEFI were pre-randomised to complete a computer assisted telephone interview or a web based report to determine if an AEFI had occurred whilst an AEFI in the controls was determined by a search for passive reports. The primary outcome was the AEFI detection rate in the SMS group compared to controls. RESULTS: We enrolled 6,338 participants, who were equally distributed across groups and who received 11,675 vaccines. The SMS group (4,225) received 12,675 surveillance prompts with 9.8% being non-compliant and not responding. In those that responded 90% indicated that no MEFI had been experienced and 184 had a verified AEFI. 6 control subjects had a reported AEFI. The AEFI detection rate was 13 fold greater in the SMS group when compared with controls (4.3 vs 0.3%). CONCLUSION: We have demonstrated that the STARSS methodology improves AEFI detection. Our findings should inform the wider use of SMS-based surveillance which is particularly relevant since establishing robust and novel pharmacovigilance systems is critical to monitoring novel vaccines which includes potential COVID vaccines.


Subject(s)
COVID-19 , Telemedicine , Adult , Adverse Drug Reaction Reporting Systems , Child , Humans , Immunization , Infant , Population Surveillance , SARS-CoV-2 , Telephone
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