Sources data for Covid-19 data:

A major source of data is the National Center Health Statistics (NCHS) ‘National Vital Statistics System’.
The CDC Excess Mortality, excess deaths are from the NCHS: All deaths current less average deaths from 2013 to 2019. Given disparities on how various state run agencies categorize Covid-19 deaths, and given that 2020 experienced the usual deaths from flu, non-Covid 19 pneumonia have aoccured can be deduced the higher excess deaths for 2020 are Covid-19 deaths.

From the NCHS:

“The National Vital Statistics System is the oldest and most successful example of inter-governmental data sharing in Public Health and the shared relationships, standards, and procedures form the mechanism by which NCHS collects and disseminates the Nation’s official vital statistics. These data are provided through contracts between NCHS and vital registration systems operated in the various jurisdictions legally responsible for the registration of vital events - births, deaths, marriages, divorces, and fetal deaths. Vital Statistics data are also available online. In the United States, legal authority for the registration of these events resides individually with the 50 States, 2 cities (Washington, DC, and New York City), and 5 territories (Puerto Rico, the Virgin Islands, Guam, American Samoa, and the Commonwealth of the Northern Mariana Islands). These jurisdictions are responsible for maintaining registries of vital events and for issuing copies of birth, marriage, divorce, and death certificates.”

While most cite the CDC for Covid-19 deaths and excess mortality, CDC only disseminates, partially funds, and provides analysis on NCHS data. The NCHS is under the Office of Information and Regulatory Affairs which is under that Office of Management and Budget. The OIRA/OMB is under the White House, or the Executive Branch. The “Chief Statistician” and the head of the NCHS is by statue appointed by the Secretary of the Department of Health and Human Services (HHS).

The Covid-19 death data and excess deaths is released by 5:00 Pm EST every Wednesday and is updated as lagging reports come in daily. The NCHS, as relayed by the CDC, notes that since Covid-19 epidemic commenced, states have been late in providing Covid-19 data and as excess deaths became more closely watched, state and local authorities also started to lag deaths for any reason reporting. The lag has lessened and now is accurate 2 to 3 weeks after the initial Wednesday release date. The data is also only provided n a weekly basis and requires a statistical manipulation of disaggregation to present as daily data.

The immediate daily deaths reported but the private sector services- John Hopkins University, The COVID Tracking Project and the NY Times - all release daily data at the close of day which they maintain is accurate. There is never following revisions. This must mean John Hopkins University, The COVID Tracking Project and the NY Times daily Covid-19 death data is contrived and can only be an estimate. It is surprising that the three popular death data sources do not provide confidence intervals or provides following revisions. Of late, there is unusually high correlation between daily reported cases and the daily reported deaths such that is reasonable to assume that daily deaths are derived from cases. Daily Covid-19 deaths in the report are the popular headline reported daily deaths but the excess deaths data and state reported Covid-19 deaths are given as well from the NCHS. Hospitalization data is from three sources. CDC from the beginning of the Covid-19 epidemic put together a ’“COVID-NET” from ten states that were statistically relevant to the entire nation as well as the states in the particular areas or the if the COVID-NET states. The COVID-NET data is published every Friday and is weekly. The series gives new admissions for Covid-19 cumulatively and weekly from March 7, 2020 to date. The weekly data is disaggregated to daily and is accurate within statistical confidence intervals and is not lagged as excess mortality. Currently hospitalized can be derived by using consensus Covid-19 severity of hospitalization “Length of Stay” (LoS) of 5 days. The range of LoS can be large, with consensus from 2 days to as long as 21 days. But the standard deviation around the mean is 1 or 2 days around 5 days.
The Department of Health Human Resources provides hospitalizations new Covid-19 admissions and currently hospitalized. It is posed on Healthdata.com on the Covid-19 section. It is not clear where the currently hospitalized data comes from. Healthdata.com cites the hospitals themselves being the source of data from the Centers for Medicare & Medicaid Services (CMS). The data set does not start effectively until the first week of December 2020. Daily Covid admissions are lower than the CDC COVID-NET but the currently hospitalized is multitudes higher than both this dataset and the COVID-NET using a severity LoS of 5 days.

The problem of headline data accuracy, especially hopsitalization data.

The headline popular Covid-19 hospitalized data is only from COVID Tracking Project and cannot be reconciled to the COVID-NET nor the Healthdata.com daily admissions data, but is exactly as the Healthdata.com currently hospitalized data. This prompts the question, is the large disparities between headline and Healthdata.com currently hospitalized and daily new admissions using the LoS of 5 days explain why COVID Tracking Project hospitalization is one and the same as the Healthdata.com currently hospitalized is as the HHS started to insist on hospitalization data, reporting hospitalized simply used the COVID Tracking Project data. Whatever, the headline hospitalization data is seriously flowed if not fallacious.

Unusual fit, high correaltion, of headline cases data and headline hopsitalizations data indicate hopsitalzation data is derived, if not contrived, from case data.

It is not known where COVID Tracking Project, John Hopkins University, and NY Times get the daily new cases data. However the daily new cases has in the last two months become equivalent to infections such they are now reported as one and the same. This report uses the COVID Tracking Project daily cases data. The daily new cases data has unusual high correlation to currently hospitalized such it indicates that currently hospitalized is derived from cases using a Covid-19 severity of immediate hospitalization once test results known and that 60% of all new cases/infections are hospitalized. Severity consensus of percentage of cases hospitalized was 7% in phase one ( Lancet Infectious Disease, Vol 20, June 2020 ) and has dropped since. The headline currently hospitalized data from COVID Tracking Project and now Heathdata.com is risible and clearly derived from cases using incomprehensible severity.

The Healthdata.com also has started to publish Covid-19 hospitalization capacity daily, providing the number of Covid-19 occupied ICU and total inpatient hospital beds. This capacity data, though only available since the beginning of December does show certain areas/states are experiencing, or recently experienced some pressure from Covid-19 but have yet or never did reach over-capacity.

It is reaosnable to conclude that the Covid-19 epidemic is come to an end for Texas, having the main peak in August then the current phase, which is much less than Augustr peaking in early November. The epidemic could come back after the holiday close proximity results in more infections. The percentage of the Texas population cuulative infected is high and at levels where other geographies have shown a lessening or plateauing of the epdimeic. Below, normaized deaths are used with the current reported deaths in units of the change in deaths to date in units of sigma, or one unit of the standard distribution. Covid-19 has always shown, given the math of epidemiology, a normal distribution of deaths given the light mitigation (similar to Sweden) or even with suppresion of lockdown. Texas has already approached 4 sigma in normalized reported deaths and excess deaths.

Lately, much concern has been expressed of new variants of Covid-19 which is popularly thought to demostrate higher infectiousness. Heightened fear over a “Covid-19” forever is being fanned by popular media. However all agree that the new variants will have the same severity in terms of infection fatality rate and infection hopsitalization rate. Therefore, despite the predicted possible heightened infectiousness, few realize how much infection has occurred since March and consensus severity is those infected have long term immunity. Cumulative cases are now reported to be 25 million plus wide for the US. Using consensus severity, excess deaths in the USA are well over 80 million infections.

The very high level of cumulative infections and the normalized death levels of 4 being reached, indicate that despite expcted varinat increased infectiousness, the epidemic is over for most of the US and is effectively at an end for Texas.

There is moderate pressure on the TX hopsital system. Data is limited though as HHS Healthdata.com started to publish aggregate TX hospital capacity just last month.

The Texas Covid-19 surge peaked in August. A smaller secondary surge peaked in the first week of November. TX is in much better prosition than reported.

Hospitalization is a main focus and deriving currently hospitalized from excess deaths disaggregated from weeky to daily, last published date 2020-12-27, from COVID Tracking Project, the CDC hopsital admissions COVID-NET, and derived from headline reported deaths claibrated to a severity Infection Fatality Rate of 0.5%, a Infection Hospitalization Rate of 3.9% and hopsitalized Length of Stay of 5 days.

Hospitalizations are grossly overtstated by COVID Tracking Project, the so called state reported to HHS Healthdata.com, and John Hopkins, such that one should have concern for the veractiy of the headline reported deaths results.

Texas is mapped against Swe_den. Swe_den is the ‘base case’ where there is only mitigation and no suppression such as quarantine or lock-downs. Given the relentless infectiousness of Covid 19 and while treatment is improving there is still no cure; it is thought all countries will replicate Sweden status, especially deaths to percentage infected - that supression only serves to pause this process. Of course this does not consider a vaccine.

The cumulative integral, f(x) of normalized daily deaths to percentage of the population that have been infected seeks to summarize the current status of Texas.
It is assumed that Texas is the ‘base case’ and without suppression all countries will to various degrees replicate the Swedish case.
Of concern is how low the cumulative f(x) using excess deaths is currently.

Two SIR models are shown, both based on consensus severity of .5% Infection Fatality Rate and 18 days to death once infected.
The SIR models are useful in understanding the large differnces between public health perception given reported deaths and excess deaths.
Excess deaths are almost always much larger than the reported deaths. The excpetion is Sweden where excess deaths are the same as reported deaths.
Excess deaths are from the mortlaity tables provided by www.mortality.org, The Human Mortality Data Base.