Infections levels rose in most EU countries including 4 out of the EU 5 countries

Infections levels rose in most EU countries including 4 out of the EU 5 countries
Global recorded cases surpassed 250 million since the beginning of the pandemic, even as the daily average number of cases has fallen by 36% over the past three months. The virus, particularly the Delta variant, is infecting 50 million people every 90 days; by contrast, it took nearly a year to record the first 50 million Covid-19 cases.  In 55 out of 240 countries, infections are still rising. More than half of all new infections reported worldwide were from countries in Europe. Last week, the WHO said Europe was again the epicentre of the pandemic, with the region reporting an average of more than 30 new cases a day per 100,000 people -- a rate that has almost doubled since September. Hans Kluge, the WHO’s director for the 53 countries in its European region, told reporters, “We are at another critical point of pandemic resurgence,” adding, “Europe is back at the epicentre of the pandemic — where we were one year ago.” Covid-related deaths are also increasing. “If we stay on this trajectory, we could see another half a million Covid-19 deaths in Europe and Central Asia by the first of February next year,” Dr. Kluge said Last week, cases in Germany reached a record high of 33,949 new infections in a day. About 67% of Germany’s residents are fully vaccinated. Russia, Ukraine, and Greece are at or near record levels of reported cases. Eastern Europe has the lowest vaccination rate in the region.  Still, most are optimistic that the worst of the pandemic is over. "We think between now and the end of 2022, this is the point where we get control over this virus ... where we can significantly reduce severe disease and death," Maria Van Kerkhove, an epidemiologist leading the WHO said. Incredibly, after a slow vaccine start, Japan reported no COVID deaths at the weekend. My chart for the week however is this off statnews:

This last week November 01 – November 07 infections levels rose in most EU countries including 4 out of the EU5 countries. In the EU5 cases rose in Italy by 17%, France by 23%, Spain by 11% and Germany by 31%, but fell by 13% in the UK, maybe due to the half-term holiday. Outside the EU5 cases rose in Denmark by 30%, the Netherlands by 39%, Belgium by 21%, Austria by 63%, Switzerland by 47% and Sweden by 1%. This week’s data continues to suggest that Europe is in a fourth wave. On hospitalisations, in the UK they were down 6% this week at ~6,835. One should expect cases and hospitalisations to fall for one more week and then resume growth such that plan B (reintroduction of face coverings and working from home) might possibly be required before the Christmas holidays are reached. In the UK, health secretary Sajid Javid said people should get their Covid booster jabs as part of a “national mission” to avoid restrictions over Christmas. Separate reports suggested that travellers who fail to get their booster jabs could face fresh quarantine and testing requirements. Germany deserves special mention. People without vaccination are responsible for a large part of the serious infections but the group also includes children: they have been slow vaccinating >12 yr olds; for under 12, there is no green light yet for vaccination. While there is a booster recommended for elderly patients & people working in medical services, retirement homes etc., the end of free testing (to force people getting vaccinated) did not have the desired effect. Not having omnipresent testing facilities makes tracking the virus a lot more complicated but this is a good dashboard:

https://impfdashboard.de/en/

Elsewhere, a US court temporarily halted nationwide implementation of the Biden administration’s vaccine/testing mandate, due to take effect from 4 Jan. U.S. Surgeon General Vivek Murthy defended the Biden administration’s federal vaccine mandate, following a court ruling temporarily blocking the policy. Murthy told ABC’s “This Week,” that “The president and the administration wouldn't have put these requirements in place if they didn't think they were appropriate and necessary,” adding, “the administration is certainly prepared to defend them”:

https://www.ca5.uscourts.gov/opinions/unpub/21/21-60845.0.pdf?

In France hospitalisations are continuing to rise, but remain at a much lower level than in the UK at 2,014 in the week, suggesting France has much longer before it will need to contemplate a plan B.  Boosters are likely the only way to combat rising hospitalisations in Europe for the remainder of this year, given likely limited supply of the antiviral pills molnupiravir (Merck & Co/Ridgeback and Paxlovid Pfizer) in the next couple of months. Even so this 4th wave is likely to be the last without pills that can reduce the risk of hospitalization from a COVID-19 infection by 50% and 85-89% respectively. Thus, this could potentially be the last wave where one has to be concerned about the level of hospitalisations from COVID-19, as the combination of booster vaccines and the antiviral pills should keep hospitalisations very low in subseguent waves. So, in summary, for wave four, though, with cases and hospitalisations continuing to rise across much of Europe, there remains the possibility of a tightening of social distancing measures being required this winter. This is weekly new infections:

With COP26 still in mind, the abrupt decline in global carbon dioxide emissions during the COVID-19 pandemic, caused by government-mandated lockdowns, will be all but erased by the end of this year, a consortium of scientists reports this week. It predicts that carbon emissions from burning fossil fuels will rise to 36.4 billion tonnes — an increase of 4.9% — in 2021 compared with last year. That’s a faster recovery than many scientists expected. The rapid rebound, driven in part by the increasing demand for coal in China and India, suggests that emissions will begin to rise anew next year without substantial government efforts to bend the curve, the researchers warn:

The UN Intergovernmental Panel on Climate Change has estimated that the world would need to roughly halve their emissions by 2030 to remain on track to achieve the most aggressive goal in the 2015 Paris climate agreement — limiting warming to 1.5°C above pre-industrial levels. But even with considerable progress at COP26, Davis calls the goal a “tough lift”. The use of renewable-energy technologies such as wind turbines, solar panels and batteries is increasing, but he fears it could be 5–10 years before they are widespread enough to cover future electricity demand and to begin replacing fossil fuels. The report analysed trends independently for the United States, the European Union, India and China and found that emissions are generally returning to their pre-pandemic levels. In the United States and the European Union, where fossil-fuel use was decreasing before the pandemic, carbon dioxide emissions are projected to rise sharply in 2021 but remain around 4% below their 2019 levels. India’s carbon emissions are projected to increase by 12.6% this year, to 2.7 billion tonnes, which is around 7% of the global total and roughly equivalent to the emissions of the European Union.

The world’s largest emitter, China, saw a resurgence in coal consumption owing to government efforts to stimulate the economy during the pandemic. Overall, the report projects that the country’s fossil-fuel emissions will rise by 4% this year, to 11.1 billion tonnes, which is 5.5% above the pre-pandemic level.

Next, an analysis of hundreds of COVID-19 cases suggests that face masks are most protective in specific circumstances, such as exposure to a person with COVID-19 that lasts for more than three hours or that takes place indoors. The study shows that several of the measures collectively known as non-pharmaceutical interventions, such as physical distancing, keeping interactions outdoors and wearing masks, “are in fact helpful” for preventing SARS-CoV-2 transmission, says study co-author Joseph Lewnard. Previous studies provided evidence that masking helps to protect against infection, but the latest work shows that it is beneficial even when other measures, such as distancing, aren’t in use.

Although vaccines/treatments are key to controlling the pandemic, non-pharmaceutical interventions remain important public health measures. But it’s difficult to measure the effectiveness of these interventions in real-world settings. To address this challenge, a group studied cases from roughly 1,280 people in California who tested positive for SARS-CoV-2 between February and September 2021. For each person with COVID-19, the researchers sought out at least one control participant: someone who matched them for factors such as age and sex but who tested negative during the same time period. Participants who’d been exposed to someone known to have COVID-19 provided details about the encounter, such as the setting and duration.

The study found that participants who were not fully vaccinated had the greatest risk of infection when they reported an exposure to someone with COVID-19 that occurred indoors or that lasted for more than three hours. Participants exposed to someone with COVID-19 had lower odds of infection if masks were worn at the encounter than if they weren’t. This protection is especially important for people who were not yet vaccinated,” says Lewnard. But encounters where masks were worn were linked with additional protection for vaccinated participants, too. The analysis also suggests that masks provide the greatest benefit during high-risk exposures — those lasting for more than three hours, occurring indoors or involving a person from another household. Masking did not show a clear benefit when the participant made direct physical contact with a person known to have COVID-19 or when that person was a member of the participant's household:

https://www.medrxiv.org/content/10.1101/2021.10.20.21265295v1

It seems an obvious combination: machine learning and the fight against COVID-19. And yet, despite intense interest and increasing availability of large data sets, success stories of such combinations are few and far between. A group describe a system that they designed and deployed at points of entry into Greece, starting in August 2020. The algorithm, which is built on a method called reinforcement learning, markedly increased the efficiency of testing for SARS-CoV-2 and contributed to Greece’s ability to keep its borders open safely. The work also provides a clear warning about the shortcomings of the comparatively blunt policy tools that most other countries continue to use:

Testing is a problem that machine learning is well suited to solve. Imagine a border-control agent on a Greek island. A flight has just landed, and the agent’s task is to identify and detain anyone who has COVID-19. The agent might want to test all arriving passengers, but the testing capacity on the island is very limited and, more generally, it is never possible to test 100% of any population 100% of the time. The alternative, shutting down the border completely, in an economy highly dependent on tourism, has its own perils. These would include not only a huge financial cost associated with the loss of jobs and income, but also the negative effects of such losses on public health. So the border agent faces a difficult decision: who should be tested?

As has been noted, the value of a test depends on its eventual outcome. In this scenario, a negative test generates only costs: the cost of testing and a delay for the traveller. By contrast, a positive test generates tremendous benefit: prevention of all the cases of COVID-19 that a traveller infected with SARS-CoV-2 would have caused. So, in deciding who to test, the border agent’s optimal strategy is clear: predict which travellers have the highest likelihood of testing positive, and test them. This strategy maximizes the value of testing, because it detects the most travellers with COVID-19 using the lowest number of tests.

If the border agent could predict which incoming passengers are most likely to test positive, tests could be allocated efficiently. Conveniently, data about incoming passengers, their country and region of origin, age and sex, are available digitally, on the passenger locator form that all travellers complete 24 hours before arrival in Greece. It seems straightforward enough to use data from past tests of incoming passengers to predict which ‘types’ of passenger might be more likely to test positive in the future. But, as decades of research in statistics and computer science have shown4, this strategy runs the risk of getting locked into yesterday’s pandemic: given the rapidly evolving dynamics of COVID-19 spread, an algorithm must quickly adapt its predictions to stay one step ahead and still test the right passengers. This is where the value of machine learning becomes clear. Just as an algorithm can be trained to play the game Go by learning which moves lead to winning the game, they trained an algorithm to allocate scarce tests, by learning which passengers are likely to test positive.

Crucially, the algorithm balances two goals. The first, and most natural, goal is to test passenger types who are likely to test positive, by exploiting patterns learnt from previous data about the outcome of tests for SARS-CoV-2 in these different groups. The second, perhaps less intuitive, but equally important, is to explore patterns not reflected in previous data, by testing passenger types about which the algorithm knows little.

Then, at a given port of entry on a given day, the algorithm delivers targeted recommendations to border agents about which passengers to test, while respecting the budget and resource constraints imposed by supply chains, staffing, laboratory capacity and delivery logistics for biological samples. These constraints are real and binding: the authors note that, at the peak of the summer tourism season, there was capacity to test only 18.4% of incoming travellers — even after the Greek National COVID-19 Committee of Experts wisely approved group testing to drive efficiency gains in the lab. The authors draw on the reinforcement-learning strategies that have powered advances in online commerce and marketing. But using such an algorithm in the real world raises its own technical challenges. For example, the algorithm must learn discontinuously, from large batches of testing results, rather than one-by-one from individual results. And the feedback from batch results is delayed, forcing the algorithm to operate uninformed while waiting for results. Solving these challenges required substantial tweaking of the algorithms that are typically designed for easier, more data-rich online settings.

The thorniest challenges, however, are legal and political ones. To comply with the European Union’s General Data Protection Regulation (GDPR), the authors deliberately limited the data available to the algorithm, and thus its accuracy, in close consultation with lawyers, epidemiologists and policymakers. The potential limit placed on the algorithm’s performance by the GDPR highlights how well-intentioned laws to protect privacy can have both positive and negative consequences. In a pandemic that does not respect individuals’ privacy, such regulations can ultimately hamper the ability of a government to protect the health of its citizens. The authors also adapted the algorithm with a policymaker audience in mind, choosing their optimization methods to showcase clearly the value of both algorithm goals: testing high-risk passengers and testing high-uncertainty passengers. The results are impressive. The automated system doubled the efficiency of testing, the number of cases detected per test, allowing border agents to test and quarantine the right passengers, many of whom were asymptomatic, while letting others through to their final destination.

The success of the algorithm presented here highlights the inadequacy of the border policies of nearly all other countries. The decisions underlying these policies — for example, whether to deny all travellers entry to the country or to force the testing or quarantine of all travellers from a given country — have two key flaws. First, these decisions are made about entire countries, rather than individuals, disregarding vast differences between people within countries. Second, they are typically made on the basis of country-level epidemiological data that, as the present study shows, have notable shortcomings.

Had border agents denied entry to all passengers from countries that had concerning metrics, they would have prevented those people with COVID-19 from entering Greece — but at the cost of crushing a key pillar of the economy. Had they simply tested people proportional to a country’s reported COVID-19 metrics rather than algorithmic predictions, however, their testing efficiency would have been much lower. This is because reported COVID-19 metrics can be very different from actual disease prevalence among incoming travellers. Travellers are not randomly drawn from their countries’ populations, and passively collected data on cases of COVID-19 or deaths associated with the disease reflect large reporting biases and systemic barriers to access.

Indeed, by efficiently testing incoming passengers, the authors’ algorithm was able to anticipate spikes in SARS-CoV-2 infection rates among traveller populations almost 9 days earlier than if they had used country-level epidemiological data alone. This indicates the enormous value of intelligent, deliberate data collection and the dangers of relying on blunt, flawed, country-level data for important decisions.

Their work will be remembered as one of the best examples of using data in the fight against COVID-19. It is a compelling story of how a group of researchers partnered with enlightened policymakers to produce a tool that has enormous social value. It highlights the best parts of both academic research and the civil service, and shows the great promise of artificial intelligence for making good decisions — which in many settings can be the difference between life and death:

https://www.nature.com/articles/d41586-021-02556-w

 

Development in UK infections & hospitalisations

Over the week November 1 – November 7 the new infection count fell by 13% to 245,052, with the fall due to the continuing effect of half-term with cases in 10-19 year olds falling, but with cases in other age groups all continuing to rise slowly. Testing levels increased by 9% and so the rate of positive tests fell to 4.1% (prev. 4.8%). Per day infections were between 30,305 and 40,770 (prev. week between 36,294 and 43,349). One would expect cases to continue to fall for another week before starting to slowly rise again for a few weeks. Hospitalisations were down 6% w-o-w at ~6,835 but still around 1,000 per day (based on the first 3 days of the week) with the rate of hospitalisations continuing to go up to 2.8% (prior week 2.6%). The occupancy of ventilators increased by 8% this week to ~22.9% (last week 21.2%), which equates to ~1,026 people, which is only 13% lower than the same week in 2020 (when an average of 1,174 were on ventilators). If hospitalisations rise from here to reach 10,000 a week, then plan B could be back on the table with a return to mask-wearing and potentially working from home. The booster vaccination program should help curb hospitalisations, but the rollout is still slow, something that has now been acknowledged by the government.

Although cases fell significantly this week in children due to the school holidays they didn’t fall in the above 65s and hence hospitalisations didn’t fall much. I expect cases and hopsitalisations to fall for one more week and then resume growth such that plan B (reintroduction of face coverings and working from home) could be required before the Christmas holidays are reached.

Figure 1: UK Weekly Infections Aug 2, 2020 – Nov 07, 2021 (actual); Nov 08 - Dec 26 (projected)

Figure 2: UK Weekly Hospitalisation Aug 2, 2020 – Nov 07, 2021 (actual); Nov 08- Dec 26 (projected) at 1.5% of infections

Figure 3: UK Weekly Hospitalisations Aug 2, 2020 – Nov 07, 2021 (actual); Nov 08 - Dec 26 (projected) at 1% of infections

igure 4: UK Weekly Deaths Aug 2, 2020 – Nov 07, 2021 (actual); Nov 08- Dec 26 (projected) at 0.2% of infections (3wks prior)

 

Development in Vaccinations in the EU5, Israel & the US

The UK has partially vaccinated ~92.5% of its adult population, with a total of 50.2m first doses administered, representing 73.8% of the UK population or 87.4% of the vaccine-eligible 12+ population (prev. week 86.9%). Full immunisation has now been achieved in 86.8% of adults, with a total of 45.8m doses administered to date, covering 67.3% of the total population or 79.7% of the vaccine-eligible 12+ population (prev. week: 79.5%). The vaccination rate for the primary series declined by 3% this week to an average of 59k doses per day, with first doses averaging 39k doses per day and second doses averaging 20k doses.

Looking at vaccination by age, we estimate 42% of the 12-17 age group have received at least one dose (prior week: 37%). This compares with 74% of 18-24 year olds (prior week: 74%), 75% of 25-29 year olds and 95% of those aged 30 and over. Full immunisation has been achieved in 64% of 18-24 year olds (63% in the prior week), 67% of 25-29 year olds (67% in the prior week) and 77% of 30-34 year olds (76% in the prior week) compared with 93% in the 35+ population. The UK has administered 10.1m booster doses (prev. week 7.9m), with an estimated ~56% of over 65s covered with a booster dose (prev. week: 45%).

Looking across the EU4 on the primary vaccination series, Spain has partially vaccinated 91.3% of its adult population, France is at 90%, Italy is on 83.1% and Germany is on 80.5%. Full vaccination rates are 89.8% for Spain, 88.0% for France, 80.4% for Italy and 77.7% for Germany. On the rollout of booster jabs, Germany has administered 2.5m booster doses to date (prev. week: 1.9m), France has administered 3.4m doses to date (prev. week: 2.9m), Italy has administered 2.2m doses (prev. week: 1.6m) and Spain has administered 1.5m doses (prev. week: 962k), having recently started its rollout in over 70s.

The US has partially vaccinated 207.9m adults (206m in the prior week) i.e. 80.5% of the adult population. Full immunisation has been achieved in 70.0% of adults (68.9% in the prior week). A total of 24.1m people have now received a booster dose, with 14.3m doses administered to those over 65, representing 30.5% of the over 65 population.

Israel has now partially vaccinated 71.6% of its total population and has fully vaccinated 65.8% of its population. Booster doses have been administered to 45.7% of the total population and 67% of the adult population (prior week: 67%).

Figure 5: Latest vaccination % for EU5 and US (% adults)

Source: CDC, UK, French, Germany, Spain, Italy governments. *Note, Germany data is based on reported vaccination data. This week, Robert Koch Institute and the German Health Ministry announced that there has been underreporting in the Germany vaccination rates with an estimated 84% of adults partially vaccinated and 80% fully vaccinated (based on survey data)

Figure 6: EU 5, Israel & US Cumulative 1st doses administered

Source: UK, France, Germany, Spain, Italy and Israel governments; CD. Note, country-level data frequently restated for Germany, Italy and Israel.

Figure 7: EU 5, Israel & US Cumulative fully vaccinated

Figure 8: EU 5, Israel & US % of Population received 1 dose

Figure 9: EU 5, Israel & US % of Population fully vaccinated

Figure 10: EU 5, Israel & US Cumulative Booster doses administered

Figure 11: EU 5, Israel & US Cumulative Boosters % of Population

 

Examining the impact of the Vaccine in the UK, US and Israel

Israel, which has fully vaccinated ~90% of its adult population and has administered booster shots to ~67% of its adult population, saw a 15% decline in cases this week, with new severely admissions down 37%, the sixth week in a row we have seen a decline on both metrics. Specifically, cases this week averaged 540 per day while new severely ill admissions averaged 7.5 per day, the lowest level since July 10th. Focus remains on the durability of protection from the booster doses, particularly against the emerging Delta Plus AY.4.2 strain. In the US, daily cases declined by 1% to 76.3k (based on data for first 5 days), with hospitalisations down 8% to 4,915 admissions per day, a weekly level of ~34k admissions, the seventh week in a row we have seen a decline on both metrics. There has been evidence of rising cases in certain states in the US, with the decline in cases having slowed in recent weeks from a double-digit decline in previous weeks to only a 2% decline last week and a 1% decline this week. The US is now considering mandating vaccinations for employees in the private sector to increase vaccination uptake and curb a fourth wave. Recent data on the waning efficacy of vaccination in 80,000 US veterans found that efficacy of the Moderna vaccine against cases declined from 89% in March to 58% by the end of September, with efficacy from the Pfizer/BioNTech vaccine falling from 87% to 45% over the same time period and JNJ efficacy waning from 86% to 13%.

In the UK, cases declined by 13% this week to an average of 35,007 cases per day despite a rise in testing by 9%, with hospital admissions declining by 6% to 1,033 new admissions per day (based on data for the first 3 days). The AY.4.2 Delta Plus variant was identified as a variant under investigation on October 20, 2021. This week, AY.4.2 cases rose by 7,542 to a total of 28,667 cases, compared with a weekly increase of 57,411 sequenced Delta cases, with AY.4.2 accounting for 13% of total new cases in the UK. AY.4.2 is currently thought to be around 10-15% more infectious than the original Delta strain. There is no evidence yet as to whether this strain causes more severe illness than Delta or on impact on vaccine efficacy against hospitalisation. The latest data on COVID-19 hospitalisations by vaccination status as at October 28, 2021 continue to support the UK's decision to roll out boosters in over 50s with 68% of hospitalisations (n=8,338) in over 50s. The latest data suggests the booster rollout could be extended to those over 40 given that hospitalisations in 40-49 year olds now account for 12% of all hospitalisations, compared to hospitalisations in 50-59 year olds, which account for 14% of all hospitalisations.

Vaccine efficacy, based on real-world surveillance data in the UK, shows efficacy against Delta of 60-70% for the Astra vaccine and 75-95% for the Pfizer/BioNTech and Moderna vaccines, with evidence of waning efficacy for both Astra and Pfizer/BioNTech. Effectiveness against hospitalisation from the Delta variant is over 90% for all 3 vaccines. Vaccine efficacy against Delta hospitalisations is estimated to wane from 86.2% to 76.3% for the Astra vaccine in over 65s, compared with 100% to 91% for the Pfizer vaccine in the same population after 5 months. This compares with 94% efficacy of the Astra vaccine in the overall 16+ population, waning to 77% after 5 months, compared with 99.7% efficacy of the Pfizer/BioNTech vaccine waning to 92.7% after 5 months. Initial odds ratio point estimates for vaccine efficacy suggest vaccines are equally effective against cases from the AY.4.2 variant as against the original Delta variant with an OR for the AstraZeneca vaccine of 1.02 (95% CI: 0.95-1.09), Pfizer/BioNTech of 1.08 (95% CI: 1.00-1.16) and Moderna of 0.96 (95% CI: 0.69-1.35). Putting this into perspective, an OR > 1 would suggest lower vaccine effectiveness compared to Delta, with an OR of 1.12 suggesting a modest reduction in vaccine effectiveness from 83% (Pfizer/BioNTech latest reported efficacy against Delta from the UK) to 81%.

Figure 11: Israel Vaccinations compared to Daily Infections

Figure 12: Israel Vaccinations compared to Daily Severely Ill Pts

Figure 13: US Vaccinations compared to Daily InfectionsFigure 14: US Vaccinations compared to hospitalisationsSource: CDC, J.P. Morgan estimates

Figure 15: UK Vaccinations compared to Daily InfectionsFigure 16: UK Vaccinations compared to Daily Hospital Admissions

Looking at the new infection data on a weekly basis over the last week (November 1 – November 7) the EU5 new infections rose by 4% to 519,165 with cases rising in 4 out of 5 countries. Cases rose in Italy by 17% to 36,082, in France by 23% to 50,607, in Spain by 11% to 14,813, in Germany by 31% to 172,611. Cases fell in the UK by 13% to 245,052 due to the half-term break.

Development in New Infections in the EU5

Figure 17: Weekly New Infections Development since Feb 23, 2020 for the EU5 Countries

 

Development in Deaths

  • For the week ending November 7, the total death count in EU5 increased by 7% week on week to 2,604, with deaths increasing in 4 out of 5 countries. Deaths rose in France by 5% to 227, Germany by 72% to 800, in the UK by 7% to 1,173 and by 6% in Italy to 291. In Spain death fell by 46% to 113.

Figure 18: Weekly New Deaths Development since February 2020 for the EU5 Countries

Table 1: Death Rate of Cases during different wavesSince March the death rate has fallen in most countries due to vaccinations and the fall in cases of the Alpha Variant. Death rates are higher for Germany and Italy due to the fall in testing, resulting in less diagnosis.

Death Rate

Italy

France

Spain

Germany

UK

EU 5

23 Feb to 28 Jun

14.4%

19.0%

10.6%

4.7%

15.0%

12.6%

             

5 Jul to 30 Aug

2.1%

0.7%

0.3%

0.7%

2.2%

0.7%

1 Sept – 27 Sept

0.9%

0.4%

0.8%

0.4%

0.5%

0.6%

28 Sept – 25 Oct

0.7%

0.5%

0.9%

0.4%

0.7%

0.7%

26 Oct – 27 Dec

2.3%

2.0%

1.9%

1.7%

1.8%

2.0%

28 Dec- 28 Mar

2.4%

1.7%

1.8%

4.1%

2.7%

2.1%

29 Mar – 5 Jun

2.6%

1.1%

1.2%

1.4%

0.7%

1.3%

6 Jun – 7 Nov

1.1%

0.5%

0.6%

0.7%

0.3%

0.5%

             

 

Development in Hospitalisations

  • Daily Hospital Admissions: Hospital admissions in France were up 18% at 2,014 for the week ending November 7. In the UK, hospital admissions were down 6% to ~6,835.
  • UK hospitalisations by Age: The data was updated on October 14, 2021 for the period up from Sept 5, 2021 to Oct 5, 2021. During September and the first 5 days of October there continued to be a rise in the proportion of people hospitalized above the age of 85. The proportion of hospitalisations from the age group 18-54 continued to fall due to uptake of vaccines. I would anticipate boosters to reverse the rise in hospitalisations in the 85+ age group in the coming weeks, with this data point out the need for boosters, particularly in this age category.

Figure 19: Daily Admissions to Hospital since Feb 23, 2020 for EU4

Figure 20: Daily Hospital Admissions/New Cases since Mar 22 for EU4

Figure 21: England Monthly Hospital Admissions by Age Oct 20 – Oct 21 (Data up to Oct 05)Source: NHS England

Figure 22: UK Hospital Admission as % of cases in the week & % of cases 1 wk prior

Figure 23: Hospital occupancy since Feb 23, 2020 for EU3 (# of beds)Hospital Occupancy: Occupancy rose in France by 3%, in Italy by 15% and in the UK by 1%.

Figure 24: Hospital occupancy since Feb 23, 20 for EU3 (% of beds)

Source: UK.gov; ecdc.europa.eusalute.it

  • ICU Occupancy: Occupancy in the UK increased this week to 22.9% (prev. 21.2%). With hospital admissions down only slightly this week I would anticipate that ventilator occupancy will continue to increase in the coming weeks. ICU occupancy in France increased slightly to 14.4% (prev. 13.7%) of beds occupied and an average of 1,092 beds occupied. In Paris occupancy also rose back to 23% (last week 21%). In Italy occupancy increased by 12%, with the percentage of beds occupied at 5.1% (prev 4.5%).

Figure 25: ICU Occupancy since Feb 23, 2020 for EU3*


Prof.  Justin Stebbing

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