SARS-CoV-2 BA.5の免疫回避はL452RとF486Vによるもの

投稿日投稿者しとらす

ラモスさんのツイートでの解説より
BA.5の特性と同じくらい重要なのは↓この指摘かも

ぶっちゃけ40歳以上の重篤以上率が20代30代の2倍、3倍、6倍、10倍と増えるし、肥満なだけでも2倍になるので
δとοの病原性の差とか、BA.5の病原性がどうかとか全部誤差です。
自分の所属カテゴリを把握することの方がよっぽど大事

◆Antibody escape of SARS-CoV-2 Omicron BA.4 and BA.5 from vaccine and BA.1 serum
【ScienceDirect　2022年6月9日】

Summary

The Omicron lineage of SARS-CoV-2, which was first described in November 2021, spread rapidly to become globally dominant and has split into a number of sublineages. BA.1 dominated the initial wave but has been replaced by BA.2 in many countries. Recent sequencing from South Africa’s Gauteng region uncovered two new sublineages, BA.4 and BA.5, which are taking over locally, driving a new wave. BA.4 and BA.5 contain identical spike sequences, and although closely related to BA.2, they contain further mutations in the receptor-binding domain of their spikes. Here, we study the neutralization of BA.4/5 using a range of vaccine and naturally immune serum and panels of monoclonal antibodies. BA.4/5 shows reduced neutralization by the serum from individuals vaccinated with triple doses of AstraZeneca or Pfizer vaccine compared with BA.1 and BA.2. Furthermore, using the serum from BA.1 vaccine breakthrough infections, there are, likewise, significant reductions in the neutralization of BA.4/5, raising the possibility of repeat Omicron infections.

◆Outcomes of laboratory-confirmed SARS-CoV-2 infection during resurgence driven by Omicron lineages BA.4 and BA.5 compared with previous waves in the Western Cape Province, South Africa
【medRxiv　2022年7月1日】

Abstract

Objective We aimed to compare clinical severity of Omicron BA.4/BA.5 infection with BA.1 and earlier variant infections among laboratory-confirmed SARS-CoV-2 cases in the Western Cape, South Africa, using timing of infection to infer the lineage/variant causing infection.

Methods We included public sector patients aged ≥20 years with laboratory-confirmed COVID-19 between 1-21 May 2022 (BA.4/BA.5 wave) and equivalent prior wave periods. We compared the risk between waves of (i) death and (ii) severe hospitalization/death (all within 21 days of diagnosis) using Cox regression adjusted for demographics, comorbidities, admission pressure, vaccination and prior infection.

Results Among 3,793 patients from the BA.4/BA.5 wave and 190,836 patients from previous waves the risk of severe hospitalization/death was similar in the BA.4/BA.5 and BA.1 waves (adjusted hazard ratio [aHR] 1.12; 95% confidence interval [CI] 0.93; 1.34). Both Omicron waves had lower risk of severe outcomes than previous waves. Prior infection (aHR 0.29, 95% CI 0.24; 0.36) and vaccination (aHR 0.17; 95% CI 0.07; 0.40 for boosted vs. no vaccine) were protective.

Conclusion Disease severity was similar amongst diagnosed COVID-19 cases in the BA.4/BA.5 and BA.1 periods in the context of growing immunity against SARS-CoV-2 due to prior infection and vaccination, both of which were strongly protective.

◆As BA.5 becomes dominant among new U.S. cases, reduced state reporting is blurring the real-time look at the virus.
【New York Times：Adeel Hassan and Sarah Cahalan　2022年7月5日】

At a glance, the pandemic picture in the United States may seem remarkably stable. The average number of new confirmed coronavirus cases per day has hardly budged for weeks, hovering between 95,000 and 115,000 a day each day in June.

A closer look shows that as public testing sites run by state and local governments have winnowed, more states have also stopped giving daily data updates, creating a foggier look at the state of virus across the country.

That comes as new federal estimates on Tuesday showed that the rapidly spreading Omicron subvariant known as BA.5 has become dominant among new coronavirus cases. As of the week ending Saturday, BA.5 made up about 54 percent of new cases in the United States, according to the Centers for Disease Control and Prevention. Just a week ago, the agency’s estimates had put BA.5 and BA.4, another Omicron subvariant, together as dominant, a trend experts had predicted. The new statistics, released Tuesday morning, are based on modeling and can be revised as more data comes in.

BA.4 and BA.5 are able to evade some of the antibodies produced after coronavirus vaccinations and infections, including infections caused by some other versions of Omicron. But researchers in South Africa recently reported that a spring surge driven by BA.4 and BA.5 did not appear to cause significantly more severe disease than the nation’s first Omicron wave.

The reduction in U.S. public testing means that lab-based P.C.R. testing capacity in July will be only half of what it was in March, according to a recent estimate by Health Catalysts Group, a research and consulting firm. Even a few testing companies announced layoffs and closures last week.

The vast majority of the positive results from popular home test kits are not included in official data, and not everyone who gets infected knows or gets tested. Many Americans appear to be moving even further away from focusing on daily case counting — which, to be sure, have always been an undercount of total infections — as a measure of the nation’s pandemic health. But other Americans with risk factors have said that they feel ignored and abandoned as their governments and neighbors have sought a return to normal.

And some scientists estimate that the current wave of cases is the second largest of the pandemic.

“One of my favorite lines from somebody at the C.D.C. was ‘You don’t need to count the raindrops to know how hard it’s raining,’” Dr. Rochelle Walensky, the director of the Centers for Disease Control and Prevention, said in late June at a conference in Aspen, Colo. “So we can tell by the half a million to a million P.C.R.s we’re doing every day how we’re doing in areas around the country.”

The C.D.C.’s monitoring of community risk levels shows that in its latest update, 33 percent of the American population lived in a high-risk county, in most regions outside the Northeast. In May, the map had been flipped, with the Northeast comprising most of the high-risk counties. The C.D.C. recommends wearing a mask indoors in public under such a designation.

In most of the Northeast, cases have decreased continuously throughout June, according to a New York Times database. In the South, many states have seen cases double or triple over the same time. As of Sunday, more than 113,000 new coronavirus cases are being reported each day in the United States.

“That’s not really a reflection of the total amount of virus circulating in the communities,” said Amesh Adalja, a senior scholar at the Johns Hopkins Center for Health Security at the Bloomberg School of Public Health. He said that his “back of the envelope” estimate was about one million cases per day.

As states report less frequently, changes in the trajectory of the virus are slower to reveal themselves. Nearly every state reported the number of new coronavirus cases, hospitalizations and deaths for five days a week or more in 2020 and 2021, but 23 states now release new data only once a week, according to Times tracking.

California, which once updated its cumulative case and death figures every weekday, now does so only twice weekly. In Florida, case and death data are released just once every two weeks. Just last week, many more public testing sites closed in Alaska, Colorado and Rhode Island.

Recent virus figures have hiccuped around holidays like Memorial Day and Juneteenth, during which many states often pause reporting and then restart tracking afterward, a trend that is sure to continue this week, after the Fourth of July holiday weekend.

“Following the daily test count is less instructive than it was,” Dr. Adalja said, citing the close link between cases and hospitalizations in the past. Today’s numbers should not be treated like checking a sports team’s daily standings or scores, he added.

“I think testing is taking a different role,” he said. “Even when testing was at a different point, it has always been an underestimate.”

To get a localized look at how the virus is faring, Dr. Adalja said that he has come to rely on hospitalizations as a percentage of its capacity. He also checks the C.D.C.’s community levels tracker, which includes new hospital admissions and how many beds are used. He urges a shifting focus to severe disease, rather than tracking the “booms and busts of cases.”

Hospitalizations have increased modestly throughout June, though they remain low. Just over 33,000 people are in American hospitals with the coronavirus on an average day, and fewer than 4,000 are in intensive care. Reports of new deaths remain below 400 a day, down from the country’s daily death toll peak of more than 3,300 deaths in January 2021.

◆Herd immunity thresholds for SARS-CoV-2 estimated from unfolding epidemics【medRxiv　2021年8月1日】

Introduction

Selection acting on unmeasured individual variation is a well-known source of bias in the analysis of populations. It has been shown to affect measured rates of mortality (Keyfitz and Littman; Vaupel et al 1979; Vaupel and Yashin 1985), the survival of endangered species (Kendall and Fox 2002; Jenouvrier et al 2018), the scope of neutral theories of biodiversity and molecular evolution (Steiner and Tuljapurkar 2012, Gomes et al 2019), the risk of diseases whether non-communicable (Aalen et al 2015; Stensrud and Valberg 2017) or infections (Anderson et al 1986; Dwyer et al 1997; Smith et al 2005; Bellan et al 2015; Gomes et al 2019; Corder et al 2020), and the efficacy of interventions such as vaccines (Halloran et al 1996; O’Hagan et al; Gomes et al 2014; Gomes et al 2016; Langwig et al 2017) or symbionts (Pessoa et al 2016; King et al 2018). Building on this knowledge, we addressed how selection on individual variation might affect the course of the coronavirus disease (COVID-19) pandemic (Gomes et al 2020).

COVID-19 is an infectious respiratory disease caused by a virus (severe acute respiratory syndrome coronavirus 2 [SARS-CoV-2]), which was first identified in China in late 2019 and has since spread worldwide leading to considerable human suffering and social disruption. European and American continents have been the most affected, with 0.16% and 0.20% of the respective total populations having died as of the 15 July 2021 (WHO 2021). Here we analyse series of daily deaths attributed to COVID-19 in Spain and Portugal (Iberian Peninsula) to study how individual variation in susceptibility and exposure to a respiratory virus affects its epidemic trajectory. Besides adding to the compendium of neglected effects of selection in population dynamics we hope to stimulate a new approach to study epidemic dynamics.

The main idea developed here is that individual variation in susceptibility or exposure (connectivity) accelerates the acquisition of immunity in populations. More susceptible and more connected individuals have a higher propensity to be infected and thus are likely to become immune earlier. Due to this selective immunization by natural infection, heterogeneous populations acquire herd immunity by natural infection more efficiently than suggested by models that do not fully account for these types of variation. We integrate continuous distributions of susceptibility or connectivity in otherwise basic epidemiological models for COVID-19, which necessarily account for non-pharmaceutical intervention effects, and generate three types of results. First, at national levels the herd immunity threshold by natural infection declines from around 70% to 20-30%. This is newly reported here for Spain and in agreement with recent estimates for England and Scotland (Gomes et al 2021). Second, these inferences can be made relatively early in the pandemic, such as between first and second waves, provided the first wave is sufficiently large and spatially synchronous. Third, we include a selection of results for Portugal to illustrate how the inferential procedure degenerates when national data do not meet certain conditions.