The spread of Covid occurs in a series of waves caused by changes in behavior. The direct impact of the infection can be seen in hospitalizations and deaths. The rates of hospitalizations and deaths has changed, probably from changes in the demographic of the infected communities, and improvements in health care.
The Case Fatality Rate for communities with controlled infections has improved from 3% to as low as 1%. When the hospital systems are stressed, the CFR has risen as high as 8%. The infection is most dangerous to the elderly and those with serious medical problems. It also seems to severely impact a few unlucky individuals.
The time line of infections in the US shows 3 waves in daily cases. The hospital admissions reflect the daily new admissions and the time each person spends in hospital. The hospital admissions relative to daily cases has dropped significantly from wave to wave. This means that now the health care system can deal with a higher level of cases than in March. At the end of Jan, hospitalizations are dropping, vaccinations are above 1M a day and rising. There is a suggestion that the CFR may be starting to drop as the at risk of dying group (>65) is now over 40% vaccinated. It will take around 1 month for the vaccinations to show up affecting death rate. So by end of February the impact should be clear with a halving of the the death rate. (CFR).
The map of the US showing hospital admissions per million in Dec 2020, shows how many states are in trouble, particularly in Central US.
In the US here are a total of 1M beds for 330M people or 3000 per million. At 370 beds /M occupied in Texas, that is about 10% of capacity. The operating assumption is that 60% of beds are occupied by non-Covid patients, leaving 1,200 beds /M available for Covid. In Texas, at 375 on Dec 1, we have have space for cases to go up 3x. In CA they can just tolerate a doubling in cases. These are averages for the state, some local hot spots such as LA are already overwhelmed. States maxed out at around 800 beads/M, with some locations locations overwhelmed.
In Austin, hospital admissions have closely tracked daily case
count. At the peak in infection in July, the admissions got to within 2 x of local hospital capacity. In early December it looks as though hospital capacity will reach the limit again in early January. The move to stage 5 and people getting frightened has caused the hospitalization to start dropping by end of Jan.
If you look closely, any difference depends on the
demographic of the infected population. I looked closely at
the ratio of Hospital Admissions to Daily cases and
compared it to the fraction of the cases over 50 years of
age. The tracking is notable, and statistically significant
99.9% confidence. By extrapolation of the slope, the ratio of
admissions to cases can vary from 0.5 to 5x. The hospital
impact can vary 10x depending on the >50 demographic of
the infected population.
For obvious reasons, the mortality of Covid is a critical
property that affects the entire response to the virus. In the
early stages of an infection, a popular measure is the ratio
of Deaths to Cases called the Case Fatality Rate (CFR)
(see https://ourworldindata.org/coronavirus). CFR values
have ranged from 0.5% in Iceland to 14% in Italy with a
world average of 7%. In the US, the variation is from 1% in
Nebraska, to 10% in Michigan, with a US average of 4%.
In general, these variations have been blamed on non-
uniformities in detection, classification and reporting.
In terms of Case Fatality Rate (CFR), the CFR has been
transformed over the 6 months since this started.
The CFR time line shows that the lad between deaths and cases has increased significantly (see Covid Characteristics for more detail). The CFR for the US with changing lag, shows am improvement from 8% to 2%.
The CFR time line for TX shows a smaller change from 3% to 2%, whereas NY showed a change from 8% to 1%.
In the earliest stages of the infection, NY had a CFR of 8% compared to TX at 3%. By the end of April it was clear that health care stress has a big impact on fatality. To see if these variations might be real, I made a sorted table of CFR for the states based on the data from (https://www.worldometers.
info/coronavirus/country/us), and all the states that were hit
hardest (NY, NJ, MI, LA) have the highest CFR. This clearly
suggests that the loading on the health care system is a
factor. Stress on the hospitals, particularly the ICU should
be related to the daily death count, and the greatest
demand will occur at the peak of the infection. I plotted the
Maximum daily Deaths per Million (MDM) as a proxy for
health care stress against CFR and found a statistically
significant (>99%, R = 0.64) trend. The correlation is better
with deaths than cases, suggesting that it is ICU pressure
that is the problem. There was less or no correlation with
other metrics of health care availability such as number of
doctors, hospital bed count, the head room between deaths
and beds, whether the state was infected early or late
benefiting from health care learning etc. The caution is that
correlation does not mean causality, so this might be just a
useful indicator of a problem.
We also know that the CFR critically depends on the age of
the infected population. In March, 30% over 80 years old
who were infected were dying.
The improvements in CFR have occurred across all age groups. Data from FL shows the CFR for the over 80's is now down to 17%. The improvement appears to be related to improvements in medical processes, such as avoiding ventilators and new drug regimes to control the virus and impacts of infection such as inflammation using steroids.
By April, the variants have started to dominate. It took 2 months fo for the variant (B.1.1.7) to take over the UK in late fall, and based on recent publications it appears to be roughly 60% more infectious and 60% more lethal.
This translates into an Infections per person (Ipp or R(0)) under normal distancing of 9 and an average Case Fatality Rate of 2.7%.
The same variant is dominating in Michigan in April. If you run the models for this, it looks like with relaxation of distancing, the remaining un-vaccinated population will get infected quite quickly - probably by late August. There will also be a period of serious pressure on the health care system in May and June.
Based on data fron March 2021 a comprehensive analysis of COVID data from Israel on over 100,000 cases produced a much clearer profile of the disease. The Asymp : Symp is roughly 1:1. The case rate is roughly age independent.
The Case Hospitalization Rate (CHR), Case Fatality Rate and Vaccinated Case Breathrough Rate (VCBR) are strongly age dependent.
Age CHR CFR VCBR
16-44 7% 0.1% 1%
44-64 22% 1% 2%
>64 58% 18% 3%
By August, the case rate per day in Israel had increased 100x compared to March, About 10x of that can be blamed on reduced vaccine efficiency over time or Delta variant, and the balance on decreases in social isolation.
What is the critical vaccination level in 9/27/21 ?
Herd immunity is often identified as the key to a successful vaccination program. Unfortunately, the Delta variant and increasing breakthrough infections have muddied the waters.
The top graph shows the vaccination progress, and the bottom graph shows the unlagged CFR. The 3 countries with vaccination levels over 60-65% show much lower CFR's of <0.5%, compared to the US and most other countries at 1-2%. This suggests to me that below 60-65% vaccination level, infection in the unvaccinated dominate, whereas over 60-65% breakthroughs dominate and hence the mortality drops. The US is probably 5-10% away from the transition, and is vaccinating at 0.2% per day. This translates to around 1 month away - end of October.
Genetics plays a role in sever Covid reactions
Sever infections seem to group in families.
"One 2020 review suggests that on average, the likelihood of SARS-CoV-2 transmitting to household contacts is 16.9%Trusted Source. But this increases to 41.5% in households made up of the person with the infection and one other contact."
6/21/21 Genetic link to asymptomatic Covid
"A scientific and medical team led by Newcastle University, UK, has demonstrated that the gene, HLA-DRB1*04:01, is found three times as often in people who are asymptomatic. This suggests that people with this gene have some level of protection from severe Covid."
"These genetic effects have about as much influence on susceptibility and seriousness of infection as the effect of obesity or diabetes, Benjamin Neale, a statistical geneticist at the Broad Institute of Harvard and MIT, said at the news conference."
In 9/24/21 "They reveal that in a significant minority of patients with serious COVID-19, the interferon response has been crippled by genetic flaws or by rogue antibodies that attack interferon itself. "Together these two papers explain nearly 14% of severe COVID-19 cases. That is quite amazing," says Qiang Pan- Hammarström, an immunologist at the Karolinska Institute."
10/24/21 More evidence of genetic link in sever Covid
"The researchers found that more than 10% of people who develop severe COVID-19 have misguided antibodies―autoantibodies―that attack the immune system rather than the virus that causes the disease. Another 3.5% or more of people who develop severe COVID-19 carry a specific kind of genetic mutation that impacts immunity. Consequently, both groups lack effective immune responses that depend on type I interferon, a set of 17 proteins crucial for protecting cells and the body from viruses. Whether these proteins have been neutralized by autoantibodies or―because of a faulty gene―were produced in insufficient amounts or induced an inadequate antiviral response, their absence appears to be a commonality among a subgroup of people who suffer from life-threatening COVID-19 pneumonia."
11/21/21 Africa seems to be dodging the worst of the pandemic
Africa has only 6% of the population with symptomatic infection, in comparison to 14% for the US and UK. and less than 6% vaccinated.
"Some researchers say the continent’s younger population -- the average age is 20 versus about 43 in Western Europe — in addition to their lower rates of urbanization and tendency to spend time outdoors, may have spared it the more lethal effects of the virus so far. Several studies are probing whether there might be other explanations, including genetic reasons or past infection with parasitic diseases. On Friday, researchers working in Uganda said they found COVID-19 patients with high rates of exposure to malaria were less likely to suffer severe disease or death than people with little history of the disease."
11/28/21 Omicron variant
The Omicron variant appeared in South Africa with 32 changes, some in the spike protein. At this time no data on Rn or vaccine effect. The daily case rate in SA has gone 4x in 2 weeks, which is high and a big change for a country with low cume cases to date 5%, and low vaccination 30%. The confusing issue is that data from SA is unclear, almost certain there is undercounting, possibility lower Reproduction number due to outdoor lifestyle, genetic factors, pre-exposure to malaria.
One indicator of undercounting is that CFR is 10x the current US level and tests per million are 5x lower in SA. Ignoring quality of hospital treatment, and assuming death counts are much more reliable, the CFR suggests cases could being undercounted 10x, best fit was obtained with asymp = 13x symp. Under testing in SA accounts for 5x.
Using the much higher symptomatic count, the natural roll off Rn fit to case data works for Sept 21 waves, just like TX and NY. The Delta wave in Sept 21, has Rn = 2.5. The lower Rn may well be due to outdoor living, genetics, malaria.
There are 2 possibilities for Omicron, if vaccinations work on Omicron, Rn would have to be 10, may be 20 in the West so unlikely. If vaccinations or prior infection do not protect, then its a new infection across the entire population at Rn = 3.5, may be 7+ in the West - much more likely.
This suggests that Omicron is probably similar infectiousness as Alpha BUT prior infections and/or vaccinations may not protect.