The B.1.617.2 (delta) variant of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the virus that causes coronavirus disease 2019 (Covid-19), has contributed to a surge in cases in ...India and has now been detected across the globe, including a notable increase in cases in the United Kingdom. The effectiveness of the BNT162b2 and ChAdOx1 nCoV-19 vaccines against this variant has been unclear.
We used a test-negative case-control design to estimate the effectiveness of vaccination against symptomatic disease caused by the delta variant or the predominant strain (B.1.1.7, or alpha variant) over the period that the delta variant began circulating. Variants were identified with the use of sequencing and on the basis of the spike (
) gene status. Data on all symptomatic sequenced cases of Covid-19 in England were used to estimate the proportion of cases with either variant according to the patients' vaccination status.
Effectiveness after one dose of vaccine (BNT162b2 or ChAdOx1 nCoV-19) was notably lower among persons with the delta variant (30.7%; 95% confidence interval CI, 25.2 to 35.7) than among those with the alpha variant (48.7%; 95% CI, 45.5 to 51.7); the results were similar for both vaccines. With the BNT162b2 vaccine, the effectiveness of two doses was 93.7% (95% CI, 91.6 to 95.3) among persons with the alpha variant and 88.0% (95% CI, 85.3 to 90.1) among those with the delta variant. With the ChAdOx1 nCoV-19 vaccine, the effectiveness of two doses was 74.5% (95% CI, 68.4 to 79.4) among persons with the alpha variant and 67.0% (95% CI, 61.3 to 71.8) among those with the delta variant.
Only modest differences in vaccine effectiveness were noted with the delta variant as compared with the alpha variant after the receipt of two vaccine doses. Absolute differences in vaccine effectiveness were more marked after the receipt of the first dose. This finding would support efforts to maximize vaccine uptake with two doses among vulnerable populations. (Funded by Public Health England.).
Vaccines against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the virus that causes coronavirus disease 2019 (Covid-19), have been used since December 2020 in the United Kingdom. ...Real-world data have shown the vaccines to be highly effective against Covid-19 and related severe disease and death. Vaccine effectiveness may wane over time since the receipt of the second dose of the ChAdOx1-S (ChAdOx1 nCoV-19) and BNT162b2 vaccines.
We used a test-negative case-control design to estimate vaccine effectiveness against symptomatic Covid-19 and related hospitalization and death in England. Effectiveness of the ChAdOx1-S and BNT162b2 vaccines was assessed according to participant age and status with regard to coexisting conditions and over time since receipt of the second vaccine dose to investigate waning of effectiveness separately for the B.1.1.7 (alpha) and B.1.617.2 (delta) variants.
Vaccine effectiveness against symptomatic Covid-19 with the delta variant peaked in the early weeks after receipt of the second dose and then decreased by 20 weeks to 44.3% (95% confidence interval CI, 43.2 to 45.4) with the ChAdOx1-S vaccine and to 66.3% (95% CI, 65.7 to 66.9) with the BNT162b2 vaccine. Waning of vaccine effectiveness was greater in persons 65 years of age or older than in those 40 to 64 years of age. At 20 weeks or more after vaccination, vaccine effectiveness decreased less against both hospitalization, to 80.0% (95% CI, 76.8 to 82.7) with the ChAdOx1-S vaccine and 91.7% (95% CI, 90.2 to 93.0) with the BNT162b2 vaccine, and death, to 84.8% (95% CI, 76.2 to 90.3) and 91.9% (95% CI, 88.5 to 94.3), respectively. Greater waning in vaccine effectiveness against hospitalization was observed in persons 65 years of age or older in a clinically extremely vulnerable group and in persons 40 to 64 years of age with underlying medical conditions than in healthy adults.
We observed limited waning in vaccine effectiveness against Covid-19-related hospitalization and death at 20 weeks or more after vaccination with two doses of the ChAdOx1-S or BNT162b2 vaccine. Waning was greater in older adults and in those in a clinical risk group.
A rapid increase in coronavirus disease 2019 (Covid-19) cases due to the omicron (B.1.1.529) variant of severe acute respiratory syndrome coronavirus 2 in highly vaccinated populations has aroused ...concerns about the effectiveness of current vaccines.
We used a test-negative case-control design to estimate vaccine effectiveness against symptomatic disease caused by the omicron and delta (B.1.617.2) variants in England. Vaccine effectiveness was calculated after primary immunization with two doses of BNT162b2 (Pfizer-BioNTech), ChAdOx1 nCoV-19 (AstraZeneca), or mRNA-1273 (Moderna) vaccine and after a booster dose of BNT162b2, ChAdOx1 nCoV-19, or mRNA-1273.
Between November 27, 2021, and January 12, 2022, a total of 886,774 eligible persons infected with the omicron variant, 204,154 eligible persons infected with the delta variant, and 1,572,621 eligible test-negative controls were identified. At all time points investigated and for all combinations of primary course and booster vaccines, vaccine effectiveness against symptomatic disease was higher for the delta variant than for the omicron variant. No effect against the omicron variant was noted from 20 weeks after two ChAdOx1 nCoV-19 doses, whereas vaccine effectiveness after two BNT162b2 doses was 65.5% (95% confidence interval CI, 63.9 to 67.0) at 2 to 4 weeks, dropping to 8.8% (95% CI, 7.0 to 10.5) at 25 or more weeks. Among ChAdOx1 nCoV-19 primary course recipients, vaccine effectiveness increased to 62.4% (95% CI, 61.8 to 63.0) at 2 to 4 weeks after a BNT162b2 booster before decreasing to 39.6% (95% CI, 38.0 to 41.1) at 10 or more weeks. Among BNT162b2 primary course recipients, vaccine effectiveness increased to 67.2% (95% CI, 66.5 to 67.8) at 2 to 4 weeks after a BNT162b2 booster before declining to 45.7% (95% CI, 44.7 to 46.7) at 10 or more weeks. Vaccine effectiveness after a ChAdOx1 nCoV-19 primary course increased to 70.1% (95% CI, 69.5 to 70.7) at 2 to 4 weeks after an mRNA-1273 booster and decreased to 60.9% (95% CI, 59.7 to 62.1) at 5 to 9 weeks. After a BNT162b2 primary course, the mRNA-1273 booster increased vaccine effectiveness to 73.9% (95% CI, 73.1 to 74.6) at 2 to 4 weeks; vaccine effectiveness fell to 64.4% (95% CI, 62.6 to 66.1) at 5 to 9 weeks.
Primary immunization with two doses of ChAdOx1 nCoV-19 or BNT162b2 vaccine provided limited protection against symptomatic disease caused by the omicron variant. A BNT162b2 or mRNA-1273 booster after either the ChAdOx1 nCoV-19 or BNT162b2 primary course substantially increased protection, but that protection waned over time. (Funded by the U.K. Health Security Agency.).
Influencer marketing is the practice of compensating individuals for posting about a product or service on social media. Influencer marketing is on the rise, and many marketers now plan either to ...start using influencers or to increase their use of them in their media mixes. Despite such growth, relatively little strategic or academic insight exists that is specific to influencers. In this article, we describe the roots of influencer marketing and the many different types of influencers that now exist. We identify influencers’ three functional components: the audience, the endorser, and the social media manager. We then detail for each of these components the different sources of value influencers potentially offer marketers. We draw on relevant academic research to offer advice about how to leverage each component strategically. We close by describing how the interplay of these functional components makes influencers a potentially powerful—and undervalued—marketing tool.
The continuum hypothesis states that both deterministic and stochastic processes contribute to the assembly of ecological communities. However, the contextual dependency of these processes remains an ...open question that imposes strong limitations on predictions of community responses to environmental change. Here we measure community and habitat turnover across multiple vertical soil horizons at 183 sites across Scotland for bacteria and fungi, both dominant and functionally vital components of all soils but which differ substantially in their growth habit and dispersal capability. We find that habitat turnover is the primary driver of bacterial community turnover in general, although its importance decreases with increasing isolation and disturbance. Fungal communities, however, exhibit a highly stochastic assembly process, both neutral and non-neutral in nature, largely independent of disturbance. These findings suggest that increased focus on dispersal limitation and biotic interactions are necessary to manage and conserve the key ecosystem services provided by these assemblages.
Purpose
This paper aims to examine how consumers respond to social media influencers that are created through artificial intelligence (AI) and compares effects to traditional (human) influencers.
...Design/methodology/approach
Across two empirical studies, the authors examine the efficacy of AI social media influencers. With Study 1, the authors establish baseline effects for AI influencers and investigate how social-psychological distance impacts consumer perceptions. The authors also investigate the role of an influencer’s agency – being autonomous or externally managed – to test the boundaries of the results and determine the interactive effects between influencer type and influencer agency. Study 2 acts as an extension and validation of Study 1, whereby the authors provide generalisability and overlay the role of need for uniqueness as a moderated mediator.
Findings
The authors show that there are similarities and differences in the ways in which consumers view AI and human influencers. Importantly, the authors find no difference in terms of intention to follow or personalisation. This suggests that consumers are equally open to follow an AI or human influencer, and they perceive the level of personalisation provided by either influencer type as similar. Furthermore, while an AI influencer is generally perceived as having lower source trust, they are more likely to evoke word-of-mouth intentions. In understanding these effects, the authors show that social distance mediates the relationship between influencer type and the outcomes the authors investigate. Results also show that AI influencers can have a greater effect on consumers who have a high need for uniqueness. Finally, the authors find that a lack of influencer agency has a detrimental effect.
Research limitations/implications
The studies investigate consumers’ general response to AI influencers within the context of Instagram, however, future research might examine consumers’ response to posts promoting specific products across a variety of category contexts and within different social media platforms.
Practical implications
The authors find that in some ways, an AI influencer can be as effective as a human influencer. Indeed, the authors suggest that there may be a spill-over effect from consumer experiences with other AI recommendation systems, meaning that consumers are open to AI influencer recommendations. However, the authors find consistent evidence that AI influencers are trusted less than traditional influencers, hence the authors caution brands from rushing to replace human influencers with their AI counterparts.
Originality/value
This paper offers novel insight into the increasingly prominent phenomenon of the AI influencer. Specifically, it takes initial steps towards developing understanding as to how consumers respond to AI influencers and contrast these effects with human influencers.
Artificial intelligence (AI) is at the forefront of a revolution in business and society. AI affords companies a host of ways to better understand, predict, and engage customers. Within marketing, ...AI’s adoption is increasing year-on-year and in varied contexts, from providing service assistance during customer interactions to assisting in the identification of optimal promotions. But just as questions about AI remain with regard to job automation, ethics, and corporate responsibility, the marketing domain faces its own concerns about AI. With this article, we seek to consolidate the growing body of knowledge about AI in marketing. We explain how AI can enhance the marketing function across nine stages of the marketing planning process. We also provide examples of current applications of AI in marketing.
Native advertising is a relatively new form of online advertising that matches the format of surrounding non-advertising content. The fact that native advertising blends into its context risks ...deceiving consumers who may be unaware the content they are viewing is actually advertising. Article-style native advertising, a native ad form that mimics the style of online news articles, is particularly concerning since consumers may not expect advertising to appear in such a format. Such concern is supported by research finding low efficacy of traditional disclosures on article-style native advertisements. We investigate a novel means of increasing ad recognition through the use of companion banner advertising. Across two experiments we demonstrate that inclusion of a companion banner boosts consumer recognition of the paid nature of article-style native advertising to the same degree as a traditional disclosure. In both cases we also find that the negative reactions caused by ad recognition are muted when a native ad is perceived as having higher sponsorship transparency. These effects occur for both familiar and unfamiliar brands. Taken together, results not only detail the efficacy of a new means of achieving adequate disclosure, but also develop greater understanding of how consumers respond to article-style native advertising.
•Recognition of native advertising can be triggered by companion banner advertising.•Companion banner advertising results in the same ensuing effects as text disclosure.•Companion banner advertising is effective for both familiar and unfamiliar brands.•Perceptions of sponsorship transparency mitigate negative effect of ad recognition.
Despite the importance of microbial communities for ecosystem services and human welfare, the relationship between microbial diversity and multiple ecosystem functions and services (that is, ...multifunctionality) at the global scale has yet to be evaluated. Here we use two independent, large-scale databases with contrasting geographic coverage (from 78 global drylands and from 179 locations across Scotland, respectively), and report that soil microbial diversity positively relates to multifunctionality in terrestrial ecosystems. The direct positive effects of microbial diversity were maintained even when accounting simultaneously for multiple multifunctionality drivers (climate, soil abiotic factors and spatial predictors). Our findings provide empirical evidence that any loss in microbial diversity will likely reduce multifunctionality, negatively impacting the provision of services such as climate regulation, soil fertility and food and fibre production by terrestrial ecosystems.
Traditionally, the production and distribution of advertising material has relied on human effort and analog tools. However, technological innovations have given the advertising industry digital and ...automatic tools that enable advertisers to automate many advertising processes and produce "synthetic ads," or ads comprising content based on the artificial and automatic production and modification of data. The emerging practice of synthetic advertising, to date the most sophisticated form of ad manipulation, relies on various artificial intelligence (AI) techniques, such as deepfakes and generative adversarial networks (GANs), to automatically create content that depicts an unreal, albeit convincing, artificial version of reality. In this article, a general framework is constructed to better understand how consumers respond to all forms of ad manipulation. It is anticipated that this article will help explain how consumers respond to the more sophisticated forms of synthetic ads-such as deepfakes-that are emerging at an accelerating rate. To guide research in this area, a research agenda is developed focusing on three manipulated advertising areas: ad falsity, consumer response, and originality. Furthermore, the implications for theory and industry are considered.
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