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1.
Embase;
Preprint in English | EMBASE | ID: ppcovidwho-326899

ABSTRACT

A new SARS-CoV-2 variant of concern, Omicron (B.1.1.529), has been identified based on genomic sequencing and epidemiological data in South Africa. Presumptive Omicron cases in South Africa have grown extremely rapidly, despite high prior exposure and moderate vaccination coverage. The available evidence suggests that Omicron spread is at least in part due to evasion of this immune protection, though Omicron may also exhibit higher intrinsic transmissibility. Using detailed laboratory and epidemiological data from South Africa, we estimate the constraints on these two characteristics of the new variant and their relationship. Our estimates and associated uncertainties provide essential information to inform projection and scenario modeling analyses, which are crucial planning tools for governments around the world.

2.
Microbiology Australia ; 42(3):102-103, 2021.
Article in English | EMBASE | ID: covidwho-1665753
3.
PubMed; 2021.
Preprint in English | PubMed | ID: ppcovidwho-296807

ABSTRACT

Background: Countries in the World Health Organization (WHO) European Region differ in terms of the COVID-19 vaccine roll-out speed. We evaluated the health and economic impact of different age-based vaccine prioritisation strategies across this demographically and socio-economically diverse region. Methods: We fitted country-specific age-stratified compartmental transmission models to reported COVID-19 mortality in the WHO European Region to inform the immunity level before vaccine roll-out. Building upon broad recommendations from the WHO Strategic Advisory Group of Experts on Immunisation (SAGE), we examined four strategies that prioritise: all adults (V+), younger (20-59 year-olds) followed by older adults (60+) (V20), older followed by younger adults (V60), and the oldest adults (75+) (V75) followed by incremental expansion to successively younger five-year age groups. We explored four roll-out scenarios based on projections or recent observations (R1-4) - the slowest scenario (R1) covers 30% of the total population by December 2022 and the fastest (R4) 80% by December 2021. Five decision-making metrics were summarised over 2021-22: mortality, morbidity, and losses in comorbidity-adjusted life expectancy (cLE), comorbidity- and quality-adjusted life years (cQALY), and the value of human capital (HC). Six sets of infection-blocking and disease-reducing vaccine efficacies were considered. Findings: The optimal age-based vaccine prioritisation strategies were sensitive to country characteristics, decision-making metrics and roll-out speeds. Overall, V60 consistently performed better than or comparably to V75. There were greater benefits in prioritising older adults when roll-out is slow and when VE is low. Under faster roll-out, V+ was the most desirable option. Interpretation: A prioritisation strategy involving more age-based stages (V75) does not necessarily lead to better health and economic outcomes than targeting broad age groups (V60). Countries expecting a slow vaccine roll-out may particularly benefit from prioritising older adults. Funding: World Health Organization, Bill and Melinda Gates Foundation, the Medical Research Council (United Kingdom), the National Institute of Health Research (United Kingdom), the European Commission, the Foreign, Commonwealth and Development Office (United Kingdom), Wellcome Trust. Research in Context: Evidence before this study: We searched PubMed and medRxiv for articles published in English from inception to 9 Jun 2021, with the search terms: ("COVID-19" OR "SARS-CoV-2") AND ("priorit*) AND ("model*") AND ("vaccin*") and identified 66 studies on vaccine prioritization strategies. Of the 25 studies that compared two or more age-based prioritisation strategies, 12 found that targeting younger adults minimised infections while targeting older adults minimised mortality;an additional handful of studies found similar outcomes between different age-based prioritisation strategies where large outbreaks had already occurred. However, only two studies have explored age-based vaccine prioritisation using models calibrated to observed outbreaks in more than one country, and no study has explored the effectiveness of vaccine prioritisation strategies across settings with different population structures, contact patterns, and outbreak history. Added-value of this study: We evaluated various age-based vaccine prioritisation strategies for 38 countries in the WHO European Region using various health and economic outcomes for decision-making, by parameterising models using observed outbreak history, known epidemiologic and vaccine characteristics, and a range of realistic vaccine roll-out scenarios. We showed that while targeting older adults was generally advantageous, broadly targeting everyone above 60 years might perform better than or comparably to a more detailed strategy that targeted the oldest age group above 75 years followed by those in the next younger five-year age band. Rapid vaccine roll-out has only been observed in a small number of countries. If vaccine coverage can reach 80% by the end of 2021, prioritising older adults may not be optimal in terms of health and economic impact. Lower vaccine efficacy was associated with greater relative benefits only under relatively slow roll-out scenarios considered. Implication of all the available evidence: COVID-19 vaccine prioritization strategies that require more precise targeting of individuals of a specific and narrow age range may not necessarily lead to better outcomes compared to strategies that prioritise populations across broader age ranges. In the WHO European Region, prioritising all adults equally or younger adults first will only optimise health and economic impact when roll-out is rapid, which may raise between-country equity issues given the global demand for COVID-19 vaccines.

4.
Microbiology Australia ; 41(4):177-182, 2020.
Article in English | EMBASE | ID: covidwho-1214009

ABSTRACT

Paul Selleck has been at the Australian Animal Health Laboratory, now the Australian Centre for Disease Preparedness, since 1983. In this time, he was head of the Avian Disease Diagnostic Laboratory, incorporating the National, OIE and FAO Reference Laboratory for Avian Influenza and Newcastle Disease and an OIE Reference Expert for Avian Influenza and Newcastle Disease. He was also involved in the Australian equine and swine influenza outbreaks in 2007 and 2009 respectively and has worked with Hendra, Nipah and SARS at physical containment level 4. Paul now works extensively in Asia, running training courses on biosafety and biosecurity and laboratory diagnosis. He also audits laboratories and runs training courses on quality systems and ISO laboratory accreditation. Towards the end of world war one, the world faced a pandemic, caused not by smallpox or bubonic plague, but by an influenza A virus. The 1918-19 influenza pandemic was possibly the worst single natural disaster of all time, infecting an estimated 500 million people, or one third of the world population and killing between 20 and 100 million people in just over one year. The impact of the virus may have influenced the outcome of the first world war and killed more people than the war itself. The pandemic resulted in global economic disruption. It was a stimulus to establishment of local vaccine production in Australia. Those cities that removed public health restrictions too early experienced a second wave of infections. Unfortunately, it seems that the lessons of infection control and epidemic preparedness must be relearnt in every generation and for each new epidemic.

5.
Microbiology Australia ; 41(4):167, 2020.
Article in English | EMBASE | ID: covidwho-1214007
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