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The binomial proportion is a classic parameter with many applications and has also been extensively studied in the literature. By contrast, the reciprocal of the binomial proportion, or the inverse proportion, is often overlooked, even though it also plays an important role in various fields. To estimate the inverse proportion, the maximum likelihood method fails to yield a valid estimate when there is no successful event in the Bernoulli trials. To overcome this zero-event problem, several methods have been introduced in the previous literature. Yet to the best of our knowledge, there is little work on a theoretical comparison of the existing estimators. In this paper, we first review some commonly used estimators for the inverse proportion, study their asymptotic properties, and then develop a new estimator that aims to eliminate the estimation bias. We further conduct Monte Carlo simulations to compare the finite sample performance of the existing and new estimators, and also apply them to handle the zero-event problem in a meta-analysis of COVID-19 data for assessing the relative risks of physical distancing on the infection of coronavirus. © 2023 The Authors. International Statistical Review published by John Wiley & Sons Ltd on behalf of International Statistical Institute.
ABSTRACT
Background. Breakthrough infections post-COVID-19 vaccination increase with waning immunity and typically produce milder disease than infections in unvaccinated individuals. We investigated immuno-virologic responses and COVID-19 symptom burden upon breakthrough infection in participants from a Phase 3 study of 2-dose primary series AZD1222 vaccination (NCT04516746) to explore disease attenuation. Methods. Study participants who experienced protocol-defined COVID-19 symptoms initiated a series of illness visits over 28 days with collection of sera, nasopharyngeal (NP) swabs and saliva samples (SS), and documentation of symptoms (data-cut off: July 30, 2021). For baseline-seronegative participants with PCR-confirmed SARS-CoV-2 infection >=15 days after dose 2 of AZD1222 or placebo we assessed: anti-SARS-CoV-2 spike (S), nucleocapsid (N) and neutralizing antibody (Ab) titers by multiplex immunoassay and SARS-CoV-2 pseudovirus assay in sera;viral load by quantitative RT-PCR in NP swabs;and viral shedding by qualitative and quantitative RT-PCR in SS. Data were stratified by age and SARS-CoV-2 variant, and time since primary series dose 2. Results. Illness Day 1 (ILL-D1) S Ab GMTs in AZD1222 vaccinees were similar to peak GMTs seen 14 days after dose 2 of AZD1222 and were higher vs placebo at all timepoints. The magnitude of S Ab response differed by age: median GMTs were lower at ILL-D1 and higher at ILL-D14 in vaccinees aged >=65 vs 18-64 years (Fig.1). ILL-D1 overall, SARS-CoV-2 ancestral, alpha, and epsilon variant viral load titers in NP swabs were lower in vaccinees vs placebo (Fig 2). Mean viral load in NP swabs and viral shedding titers in SS were lower in vaccinees vs placebo at all timepoints. Vaccinees reported fewer COVID-19 symptoms than placebo participants, and experienced shorter symptom duration, particularly for fatigue and difficulty breathing. Figure 1. SARS-CoV-2 spike IgG antibody titers upon SARS-CoV-2 infection by participant age in AZD1222 vaccinees and placebo recipients during illness visits Figure 2. Quantification of viral load (nasopharyngeal swabs quantitative viral titer) by SARS- CoV-2 variant at Illness Visit Day 1 Conclusion. Improved S Ab responses, lower viral loads, and reduced symptom burden upon breakthrough infection in vaccinees vs placebo recipients, suggest that robust recall responses to AZD1222 vaccination may attenuate COVID-19 disease severity and duration. These findings alongside data on cellular immune responses to breakthrough infection will inform understanding of protective immunity to SARS-CoV-2 infection.
ABSTRACT
Background. SARS-CoV-2 vaccine efficacy (VE) against asymptomatic infection and impact on viral shedding during breakthrough infections have critical implications for pandemic control. AZD1222 (ChAdOx1 nCoV-19;2 doses, 4 weeks apart) demonstrated VE of 74.0% (95% CI 65.3, 80.5) against the primary endpoint of symptomatic RT-PCR-confirmed COVID-19 and safety in a Phase 3, 2:1 randomized, placebo-controlled study in the US, Chile and Peru (n=32,451). Here we present exploratory analyses on asymptomatic infections determined by nucleocapsid (N) seroconversion and time to viral clearance in participants with symptomatic infections determined by N seroconversion (primary data cut, March 5, 2021). Methods. N seroconversion was assessed at all scheduled and illness visits in the fully vaccinated analysis set (Table). In this analysis, symptomatic infections are defined as N seroconversion ≥ 15 days post second dose in participants who attended an illness visit with ≥ 1 qualifying COVID-19 symptom and had ≥ 1 positive RT-PCR result for SARS-CoV-2. Asymptomatic infections are defined as N seroconversion ≥ 15 days post second dose in participants who did not meet the criteria for symptomatic infections. In participants with symptomatic infections, viral shedding in saliva was assessed for 28 days and cumulative incidence of viral clearance was determined. Table. AZD1222 VE against symptomatic and potentially asymptomatic SARS-CoV-2 infections as determined by N seroconversion Results. Overall, 358 participants had SARS-CoV-2 infections as determined by N seroconversion (Table). Incidences per 1000 person-years of symptomatic infections were 25.62 for AZD1222 vs 103.42 for placebo (VE 75.23%;95% CI 65.33, 82.31) and of asymptomatic infections were 51.24 vs 111.95 (VE 54.24%;95% CI 39.99, 65.10) (Table). Sensitivity analyses for N seroconversion using the primary endpoint and CDC criteria for defining symptomatic/asymptomatic status were supportive. Median time to viral clearance in saliva in participants with symptomatic infections was 11 days (AZD1222, n=52) vs 16 days (placebo, n=92) (Figure). Conclusion. AZD1222 resulted in lower yet meaningful VE against asymptomatic compared to symptomatic infections, as determined by N seroconversion, and shortened viral shedding in symptomatic SARS-CoV-2 breakthrough infections vs placebo, highlighting its potential contribution to reducing viral transmission.
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Background: A high proportion of COVID-19 patients were reported to have cardiac involvements. Data pertaining to cardiac sequalae is of urgent importance to define subsequent cardiac surveillance.
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The COVID-19 pandemic is a unique challenge to critical thinking. There is an evolutionary adaptive function for the human brain to, at tough times, gives a systematically biased outlook on the future in favor of positive outcomes for ourselves rather than for others. Such a preference of skewed future outcome projections is called optimism bias. The bias results in individuals bypassing the analytic system and relying on the heuristic system which operates on intuition and personal beliefs when it comes to making health-related decisions. Being overly and selectively positive could lead to the distortion of risk assessment as individuals downplay their chance of contracting the virus during an infectious disease outbreak. Yet the literature has previously demonstrated the benefits of being optimistically biased, that it leads to a sense of control and hope, and minimizes our anxiety when we believe bad things are more likely to happen to others, but not to us. We experience a paradox as we fight the COVID-19 battle: On one end is the need for the precise assessment of risk and on the other end is the psychological burden such precision could cost us during a health crisis. Does optimism bias pay off during COVID-19 at the price of critical thinking? What are the costs of the bias for the individual and the society? Is there capacity for the greater critical thinking of individuals in terms of risk assessment under the infectious disease outbreak, despite the influence of optimism bias? The current chapter reviews studies conducted across countries such as France, Italy, Switzerland, United States, United Kingdom, Germany, and China during the COVID-19 crisis on the prevalence and impacts of optimism bias, and sees whether they shed lights on these questions. © 2021 Nova Science Publishers, Inc.
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The emergence of COVID-19 caused the world to panic as it entered the second decade of the 21st century. The unexpected attack of the virus gave rise to an 'infodemic', whereby an overabundance of information, both true and false about the pandemic, spread across the internet and social media (Mheidly & Fares, 2020;Islam et al., 2020). The need for critical thinking is more apparent than ever as research pointed the finger at public fear and uncertainty as the main drivers of misinformation, rumors and conspiracy theories just to name a few. Academics have highlighted the dangers of misinformation in the age of social media, and have called on a collective effort, from journalists to governments, to fight the infodemic that has skewed factual content (Alam et al., 2020) and brought about the mistrust in health organizations and their policies (Depoux et al., 2020). However, what is perhaps more important to possibly curb the proliferation of misinformation is user attitude. While an array of initiatives has been proposed to help combat the problematic phenomenon, staying aware of the hazards of misinformation is also said to be effective to help news consumers discern what is true and what is false (Pennycook et al., 2020). This chapter thus discusses and reviews the importance of being a good skeptic and how a change in user approach can contribute to the fight against misinformation in the digital age amid the pandemic. © 2021 Nova Science Publishers, Inc.