The nerdy amounts of pandemic detail thread

[teuchter]

You can give feedback on the gov.uk dashboard here - what data is useful, how it's presented, etc.

COVID-19 dashboard survey

This survey is about the content and explanations used on the COVID-19 dashboard. It should take no more than 10 minutes to complete. The information you provide will be treated with the strictest confidence and will not be disclosed to anyone outside Public Health England.

docs.google.com

 

[Pickman's model]

You can give feedback on the gov.uk dashboard here - what data is useful, how it's presented, etc.

COVID-19 dashboard survey

This survey is about the content and explanations used on the COVID-19 dashboard. It should take no more than 10 minutes to complete. The information you provide will be treated with the strictest confidence and will not be disclosed to anyone outside Public Health England.

docs.google.com

what did you say in your feedback?

 

[elbows]

I'm waiting till after todays dashboard figures are published before doing another comparison graph. But since the death certificate figures are out, I can say that January 19th remains the peak day of 2nd wave deaths by that measure too, with the number they currently have for the UK for that date being 1404 deaths, quite a bit higher than all other days in this wave.

 

[elbows]

As usual, the red, orange and green lines feature incomplete data towards the end of the period covered. Which does make it a little hard to judge the full extent of the downwards trajectory during post-peak phases, but I expect a lot of the drop seen so far is very real apart from the final bit.

 

[elbows]

Update of that UK chart with latest data. The peak level of death indicated by death certificates (orange) ended up closer to the number positive tests deaths where I used England within 60 days of a positive test (green) instead of sticking to the 28 day limit (red).


So the peak involved a similar level to that seen in the first wave. Currently the death certificate death figures also show the same number of consecutive days, 23, where number of daily deaths was over 1000, for both the first and second waves.

The only data I still have which shows that the first wave peak might have been higher than the second wave peak, is when looking at daily deaths from all causes. But thats a somewhat complex subject since recession and lockdowns and a lack of major flu outbreaks would be expected to result in less deaths from other causes than normal. Anyway I will post a chart about that in a few days when an additional months worth of daily all cause death data becomes available.

 

[elbows]

I have done the following chart showing deaths in each wave before. However this time I have used death certificate deaths instead of positive test deaths, because this is a fairer comparison due to the lack of testing in the first wave making that number artifically low, not to mention my continued dissatisfaction with limiting some death stats to only count those within 28 days of a positive test.


Data is from the 'Covid-19 daily occurrences' tab of this ONS spreadsheet: Deaths registered weekly in England and Wales, provisional - Office for National Statistics

Data included only goes up to Bebruary 5th at the moment, and some of the figures at the end of that period will increase further when future data comes out. London the only region where deaths from September 1st onwards were still a fraction below deaths in the first wave, but only by a very small amount (<50), and that wont be true by the next weeks data.

 

[elbows]

I always hated the 28 day limit, but its making an especially large difference at this stage of things. However despite its effect in terms of undercounting the totals, the difference between these measures is not really affecting the rapid decline trends being seen.

As usual, do not pay much attention to the very latest figures deaths by date of death as they are incomplete. And since death certificate data comes out weekly with additional lag, the orange lines are incomplete for an earlier period than the others. So I'm still waiting to see the extent to which death certificate deaths for that more recent period get closer to the 60 day figures than the 28 day figures.

 

[elbows]

The 28 day vs 60 day figures for England by week, just to underline my complaint.

 

[elbows]

Now in terms of daily deaths from all causes, the following is for England only, because the data comes from the weekly PHE surveillance report additional data spreadsheet (third link down on this page National flu and COVID-19 surveillance reports )

Unlike the other data, it shows a difference between the first wave peak and the second wave peak. Reasons may include the actual number of people really dying as a result of the virus this time compared to the first wave (eg possibly even more undercounting in the first wave). The number of people dying from other causes including few influenza deaths compared to normal, less people dying in initial phases of recession (thats an expected phenomenon as discussed at the start of this thread), possible differences in people seeking emergency medical care and receiving adequate treatment in the first wave compared to the second, etc. So I wouldnt use this data to make bold claims about how bad the peak of this pandemic wave was compared to the first, but its worth keeping in mind.


Also not that compared to most other pandemic graphs, the period resulting from the November national measures did not cause a temporary drop in deaths from all causes, it just stopped them rising for a while.

 

[elbows]

And here I take those figures, add ONS death certificate deaths for ENgland in green, and then subtract the covid deaths from the total deaths to give the orange line.

As expected the phenomenon of the first wave was not repeated to a notable extent in the second wave. The first wave phenomenon (where 'non-covid deaths' orange line rose notably in the same period that covid deaths rose) is going to be some combination of underreporting of Covid deaths, and other deaths caused by the situation such as less people receiving urgentmedical case for other conditions.

 

[elbows]

These days the weekly surveillance report is able to make some distinction between natural infection and vaccination when it comes to looking for antibodies from blood donors

The section is a bit too long to quote in full but here are some nuggets:

Nucleoprotein (Roche N) assays only detect post-infection antibodies, whereas spike (Roche S) assays will detect both post-infection antibodies and vaccine-induced antibodies. Thus, changes in seropositivity for the Roche N assay will reflect the effect of natural infection. Increases in seropositivity as measured by S antibody will reflect both infection and vaccination. Antibody responses to both targets will reflect infection/vaccination occurring at least two to three weeks previously given the time taken to generate a COVID-19 antibody response.

The plateauing of seropositivity in the older age groups likely reflects the role of vaccination in reducing viral infection. The increase in vaccination especially in the older age groups is seen by the dramatic increase in seropositivity using the Roche S assay (Figure 4 ). Prevalence in those aged 17-29 has increased in recent weeks from 20.6% (95% CI 18.2% - 23.2%) in weeks 53 2020 - 03 2021 to 32.5% (95% CI 29.8% - 35.4%) in weeks 4-7 2021 and notably in those aged 70-84 from 8.8% (95% CI 6.0%-12.6%) in weeks 53 2020 - 03 2021 to 41.0% (95% CI 35.8% - 46.4%) in weeks 4-7 2021.

Vaccination is likely to be making an important contribution to the overall increases observed, using the Roche S assay, since the roll out of the vaccination programme particularly in older age groups who have been prioritised for vaccination. The absence of an increase of seropositivity, using the Roche N assay, in the oldest age group may be due to vaccine impact.

From https://assets.publishing.service.g.../966665/Weekly_Flu_and_COVID-19_report_w9.pdf

 

[teuchter]

I'm comparing the "by date reported" and "by date of death" numbers again.
To me we are at another point where they each suggest something different.
The top graph suggests a potential levelling-off (the last four blue bars can only change in an upward direction) while the bottom one suggests a continuing fairly steady decline.
I know this is potentially boring/irrelevant for most people, which is why I put it on this thread instead of the main one.

 

[elbows]

I think I can only answer that with a general point at the moment. Which is that I've had to learn not to read much into 'steps' in deaths by date of death graphs, where values end up similar for 3 or 4 days in a row. Because when they last that long, they dont seem a good guide to what happens next, they have to last longer than that before I would start to pay attention. I'd say there are past examples on both the rising and falling sides of that graph. As for whether daily reported deaths helps figure it out, maybe, but weekends are an annoying moment to analyse recent data so I'd want to take at least part of next weeks figures into account.



I suppose it will be an excuse for me to do the colour-coded thing on top of that base this coming week.

 

[elbows]

Well it hasnt got stuck at the level you were drawing attention to, but now there is another, lower step to keep an eye on.

 

[teuchter]

Well it hasnt got stuck at the level you were drawing attention to,

Indeed - I was just looking at that.

 

[elbows]

 

[elbows]

Indeed - I was just looking at that.

Probably part of a broader phenomenon of the curve trajectory changing. That had to happen at some point or it wouldnt have been curve shaped. Would show up more clearly int he graph I just posted if the blue 'by date or reporting' line wasnt so obscured by my green 'attempt to override 28 day limit by using England 60 ay deaths instead' line. And orange death certificates deaths lag behind so dont cover the relevant period yet.

 

[elbows]

Gradual curving of the decline in the first wave was especially prominent because of regional timing variations and the way infections dragged on in certain settings (eg later care home outbreaks, hospital outbreaks). Of course vaccines may be having an impact this time too, but more detailed studies are required to attempt to show the effects of that in isolation from other factors.

 

[elbows]

I am part way through reading a nerdy SAGE paper regarding the various questions about approach towards future vaccines against SARS-CoV-2.

Since I also have an interest in some limitations with influenza vaccines over time, I am quoting a few bits in particular that I found interesting:

There are other effects observed in influenza serological immunity that relate to the interaction between past and novel exposure to virus. The order of exposure to different variants can result in very different immunity profiles. A second exposure generally boosts antibodies from the first infection. The phenomenon of “original antigenic sin” (OAS) first described in 1960 by ThomasFrancis Jr. (Francis 1960) also relates to the effect of a first exposure to subsequent exposures: pre-existing antibodies from past exposures are preferentially used and boosted upon subsequent exposures such that the repertoire of the polyclonal response is conditioned by the first exposure and the exposure history. This priming effect may also explain the repeated vaccination effect - individuals who have had multiple prior vaccinations to seasonal influenza respond to vaccination with a lower titre than individuals responding to the same vaccine with no prior vaccination history. If these interaction effects are also a feature of the immune response to SARS-CoV-2, we may find it difficult to induce an antibody response as robust as the first to updated vaccines in a population who have been infected with first wave virus or immunized with a Wuhan spike vaccine. Studies are urgently required to understand if human immune responses to repeated exposure to SARS-CoV-2 will be affected by OAS. Some relevant results imminently due from small-scale vaccine update trials such as those from Moderna, and from non-human primate studies in the USA.

There is a lot of other stuff in the document that is of interest. Its from early May.

https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/988226/S1226_Setting_up_medium-_and_long-term_vaccine_strain_selection_and_immunity_management_for_SARS-CoV-2__1_.pdf

I suspect that in the long term we may need to develop a different approach that relies on different mechanisms, rather than just updating the current vaccines, in order to keep social and economic costs of Covid below a certain level. eg:

Additional potential solutions are to invest in developing new vaccination strategies that could induce stronger T cell responses since T cell epitopes might vary less over time.

Another strategy would be to search for more broadly protective vaccines, including universal vaccine candidates, multivalent vaccines, and heterologous prime-boost

 

[2hats]

Interesting results in the light of "festival variants" segueing into a new school/university year...

Not all persons recovering from severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection develop SARS-CoV-2–specific antibodies. We show that nonseroconversion is associated with younger age and higher reverse transcription PCR cycle threshold values and identify SARS-CoV-2 viral loads in the nasopharynx as a major correlate of the systemic antibody response.

That a significant number of PCR positive persons (potential confounder: false positives, but unlikely to account for numbers observed) fail to seroconvert can have implications in vaccine studies where efficacy to asymptomatic infection is assessed. Non-seroconvertors most likely will respond differently to vaccination and those who test PCR positive may erroneously conclude they have some degree of protection from natural immunity or hybrid immunity after a single vaccine dose.

This might be the action of a strong innate system, in younger and healthier cohorts, shutting down an infection of low viral load.
DOI: 10.3201/eid2709.211042.

 

[2hats]

(MIT/Harvard) Further evidence of prior [OC43 beta] coronavirus exposure providing degrees of protective cross-immunity, to severe disease rather than infection, in SARS-CoV-2 episodes. These arise from commonalities in spike S2 proteins which are conserved across that genera of coronaviridae.

Early cross-coronavirus reactive signatures of humoral immunity against COVID-19

Given the conservation of S2 across β-coronaviruses, we found the early development of SARS-CoV-2-specific immunity occurred in tandem with pre-existing common β-coronavirus OC43 humoral immunity in survivors, which was also selectively expanded in individuals that develop a paucisymptomatic infection. These data point to the importance of cross-coronavirus immunity as a correlate of protection against COVID-19.

OC43 specific IgG and IgM antibodies were among the top discriminatory features in survivors. Specifically, OC43-specific IgG was an acute marker of survival of severe disease, whereas OC43-specific IgM response was a marker of moderate disease. While traditionally, IgM is considered a marker of a newly emerging immune response, mounting data suggest that IgM responses can persist throughout infection, continue to affinity mature, and remerge to fight infection from memory.

Deep humoral profiling pointed to the presence of an acute S2-specific Fc-receptor binding signature as a marker of survival of disease and reduced symptomatology, likely evolving from early pre-existing robust cCoV humoral immunity. While these S2-specific humoral immune responses are likely to permit breakthrough infections, the development of future vaccines or boosting regimens able to promote immunity to this highly conserved domain of SARS-CoV-2 may provide broad protection against emerging variants of concern and even other coronaviruses.

DOI: 10.1126/sciimmunol.abj2901.

See also the earlier (LJII) paper Selective and cross-reactive SARS-CoV-2 T cell epitopes in unexposed humans, which highlighted pre-existing memory CD4+ T cells that are cross-reactive to SARS-CoV-2 and a number of common cold human coronaviruses, namely OC43, 229E, NL63, and HKU1.
DOI: 10.1126/science.abd3871.

 

[8ball]

Some really great graphs there and the variety of usages of impenetrable jargon is really taking things a step up. It’s a devastating play at this stage in the game. The crowd has divided into those still dumbstruck at the audacity of the play and those who have broken out into spontaneous, while still slightly uncomprehending, applause.

I’m looking forward to seeing if elbows has enough left in the tank to provide a convincing countermove after such a long initial period of consistent dominance, but I sense we may be moving into the endgame of this quite titanic battle.

 

[elbows]

Same team, overlapping but different set of skills. I cannot even begin to bring to the table what 2hats can!

 

[_Russ_]

Id love to be able to understand what 2hats just posted, I have a feeling its quite significant and for a second there thought I was getting but nope...its gone
Anyone got an idiots guide/translation?

 

[2hats]

It's simply beginning to explain the heterogeneity in outcomes - why some people are asymptomatic, some symptomatic, some fairly ill, whilst others experience severe disease or die. It also hints at potential targets for vaccine designers to [attempt to] futureproof the next generation of SARS-CoV-2 vaccines (particularly in combination vaccines with influenza).

 

[2hats]

More on prior cross-immunity. Others have already floated the idea (DOI: 10.1038/s41577-020-0337-y) that prior BCG vaccination might confer some degree of protection (BCG does provided some cross-immunity to yellow fever)...

This study (Harvard/UCD) demonstrates that pre-existing memory T cells (specifically a memory T cell subset implicated in anti-viral immunity), specific to antigens in previously administered MMR and tetanus-diphtheria-pertussis (Tdap) vaccines, are reactivated by SARS-CoV-2 antigens following either SARS-CoV-2 infection or vaccination. Analysis of recovering COVID-19 patients revealed that MMR or Tdap vaccination is associated with a reduction in COVID-19 disease severity and death. Prior MMR or Tdap vaccination may offer some degree of protection against severe COVID-19.

Protective heterologous T cell immunity in COVID-19 induced by the trivalent MMR and Tdap vaccine antigens.

In summary:

• T cell responses to SARS-CoV-2, MMR, and Tdap vaccine proteins are highly correlated.
• SARS-CoV-2, MMR, and Tdap antigen-experienced T cells share identical T cell receptors (TCRs).
• T cells with shared TCRs have features of TEMRA, a memory anti-viral T cell subset.
• Prior MMR or Tdap vaccination correlates with reduced COVID-19 severity.

(Note the SARS-CoV-2 S2 antigen responses in some uninfected individuals - not inconsistent with the observations in the MIT/Harvard study mentioned in post #111).
DOI: 10.1016/j.medj.2021.08.004.

A commentary paper on such heterologous adaptive immunity suggests these findings might open the door to novel, complementary vaccination schemes, for example, perhaps there is scope to co-ordinate with and take advantage of existing routine immunisation schedules in particular cohorts.
Breathing more breadth into COVID-19 T cell responses.
DOI: 10.1016/j.medj.2021.08.009.

 

[2hats]

This study (Emory/Yale/others), an unsupervised analysis of blood transcriptional profiles across several US studies, revealed three distinct pre-vaccination states. A key observation is that individuals, whose pre-vaccination state are enriched in certain pro-inflammatory response genes (associated with the nuclear kappa factor-B, NFκB, signalling pathway), tended to have higher serum antibody responses one month after vaccination. This suggests pre-vaccination state can significantly influence response to inoculation. Modulation of the innate immune system by next-generation adjuvants targeting NFκB before vaccine administration may improve vaccine responsiveness.

This may also possibly be another contributory factor to the observed strong immunoresponse of infection-then-vaccination hybrid immunity (perhaps also of relevance to a greater dosing interval too) - that prior infection is itself an adjuvant.
DOI: 10.1101/2021.09.26.461847.

 

[elbows]

I regret having somewhat burnt out long ago and not contributed much to this thread for a long time.

I'm not really ready to get back into this side of things properly, but I note the following paper looks in some detail at the pandemic health impact per region. It also uses QALYs as one of its measurements, and thats a measure that featured in my inital post on this thread.

https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/1018698/S1373_Direct_and_Indirect_Health_Impacts_of_C19_Detailed_Paper_.pdf

I cant even begin to summarise it properly right now but here are just a couple of quotes.

People in the most deprived socioeconomic groups have experienced greater adverse health impacts in almost all categories of harm for which we could consider deprivation. From March 2020 to April 2021, the mortality rate in the most deprived quintile after controlling for age and population size was almost double that of the least deprived quintile (264.6 deaths per 100,000 people and 140.4, respectively). Recent estimates for “long COVID” (August 2021) also show that self-reported symptoms are 50% higher in people in the most deprived quintile, compared to the least deprived (1.89% of people experiencing long COVID compared to 1.24%).

Regionally, the pandemic shock and its impacts on the healthcare system varied significantly. Greater London experienced greatest direct health impacts of COVID-19: it had the highest rate of deaths to April 2021 once population size and age were taken into account; it also had the greatest QALY losses from death and morbidity. It experienced relatively lower reductions in elective and outpatient activity than other regions, though the drop in emergency activity in Greater London was greater than most regions (28.4% reduction compared to median of 24.9%). The West Midlands, East Midlands and Yorkshire and the Humber suffered less from direct COVID-19 impacts, but experienced greater impacts through reduced non-COVID-19 activity in the NHS with elective care down more than 38% between February 2020 and February 2021.

 

[2hats]

Another piece of the SARS-CoV-2 immunological response puzzle, here provided by a small study from Columbia/LJII/others (including Sette and Crotty).

They investigated T and B cell responses in naturally infected (deceased) organ donors. Findings were that CD4+ T, CD8+ T, and B cell memory generated in response to infection is present in bone marrow, spleen, lung, and multiple lymph nodes for up to 6 months post-infection.

Importantly - the highest prevalence of SARS-CoV-2-specific memory T and B cells was found in the lungs and lung-associated lymph nodes, where they noted SARS-CoV-2-specific follicular helper T cells. Additionally, SARS-CoV-2-specific germinal centres were active in those particular nodes for at least 6 months post-infection; there was evidence of ongoing germinal centre reactions following resolution of infection, consistent with other reports (cf vaccine thread posts, in particular previous findings of eg Nussenzweig #1511). Additionally:

Germinal centre B cells were detected in donors spanning a broad age range - from 10-74 years, providing compelling evidence that the ability to establish robust germinal centre responses to novel pathogens can be maintained with age.

The low frequency of SARS-CoV-2-specific memory T or B cells found in the spleen suggested that virus infection is generally limited to mucosal sites of entry. Tissue localised and resident memory T and B cells in the lung are likely important for site-specific protection and could be targets for site-specific boosting in vaccination. This study demonstrates that the functional responses of virus-specific T cells are tissue-specific - not only at the site of infection, but also across numerous lymphoid tissues. This suggests that T cells in tissues mediate responses that are functionally adapted to the tissue site, resulting in heterogeneity of immune memory stored throughout the body.

They also found opposing/compensatory effects of humoral and cellular immune responses in lung-associated lymph nodes and lung tissue.
Further, results also indicated ongoing interaction and coordination between T and B cells within lymph nodes - findings which suggest that dynamic coordination of adaptive immune responses across the body is a feature of antiviral immunity to SARS-CoV-2.


Immune response and detail appears to be highly site specific within the body, which should be borne in mind when targeting vaccines and other treatments.

Together, the results indicate local tissue coordination of cellular and humoral immune memory against SARS-CoV-2 for site-specific protection against future infectious challenges.

In conclusion, we reveal here that immunological memory from SARS-CoV-2 infection is maintained as heterogeneous subsets across multiple sites, with active and preferential maintenance in lung and associated lymph nodes, as well as site-specific functional adaptations. These findings support the development of site-specific strategies for monitoring immune memory to infections and vaccines, and for fortifying immune responses at the infection sites.

DOI: 10.1126/sciimmunol.abl9105.

 

[2hats]

Fundamental to gaining insight as to how we may transition to an endemic stage over the coming months/years - here (from Yale/Temple/UNC) a comparative evolutionary analysis of a number of related coronaviridae (SARS-CoV-2 and SARS-CoV, MERS-CoV, HCoV-229E, HCoV-OC43, HCoV-NL63).

These phylogenetic analyses looked at the S, M, and ORF1b genes of the above, considering infection driven anti-nucleocapsid, anti-spike and anti-virus IgG antibody levels, along with reinfection data (collected up to 28 years after infection). From these, estimated profiles of the typical antibody decline and probabilities of reinfection over time under endemic conditions were determined.

Reinfection by SARS-CoV-2 under endemic conditions would likely occur somewhere between 3 months to 5 years after peak antibody response, with a median of 16 months. This protection is less than half the duration derived for current circulating endemic human coronaviruses. Such a timescale clearly feeds into public health decision making for pandemic-to-endemic transition planning.

With sufficient data in due course, the authors hope to be able to determine the decline of vaccine-mediated antibodies, perhaps even assess the duration of immunity and breadth of protection to emerging variants that specific vaccines provide.
DOI: 10.1016/S2666-5247(21)00219-6.