There is “very, very strong evidence” that COVID-19 was manufactured by the Chinese Government.
Ronald’s space readers should be aware of emerging evidence that the COVID-19 may be a manufactured biological weapon of mass destruction: https://www.youtube.com/watch?v=FHk8SLzgXaA
If the claims are true, then when it comes to the legal principle of the “Design to expose to peril”, all you have to do to qualify as a bio-terrorist is deliberately expose a person, a group of people, a State population, or an entire national population, to this disease.
As the following COVID-19 modelling report reveals, politicians, academics, and other vested interest parties, are intensely focussed upon how to deal with the COVID-19 pandemic problems, whilst studiously ignoring the constitutional framework of Crown Laws that must be complied with.
THE ROADMAP MURDERS
A report that I refer to as South Australia’s COVID-19 Roadmap Murders report can be downloaded from the following URL:
COVID+Ready+Modelling+-+Summary+by+CPHO+-+Final.pdf (sahealth.sa.gov.au)
Note the last line on page 3 of this report:
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Total Deaths – 315 individuals (range: 8, 424)
The content of the report should have made it quite clear that removing South Australia’s border quarantine restrictions was not a lawful move as it would violate both binding Commonwealth laws and State laws that deal with serious risks to the health and safety of the public.
For insight into just how serious these violations of the law are, I have included paragraph 5 of the Constitution and one of Australia’s key anti-terrorism laws in the text below so that anyone who wants to do so, can easily copy and paste this information into a document. For example, any convicted criminal who wants to have their criminal conviction(s) quashed by a court can do so on the basis that their conviction was a gross miscarriage of justice.
THE CONSTITUTION
Paragraph 5 of the Constitution established the cornerstone for any decisions by any decision-maker in the nation that relates to COVID-19 management:
This Act, and all laws made by the Parliament of the Commonwealth under the Constitution, shall be binding on the courts, judges, and people of every State and of every part of the Commonwealth, notwithstanding anything in the laws of any State;
No-one is exempt from accountability under the binding laws of the Commonwealth and if COVID-19 is a manufactured biological weapon of mass destruction (BWMD) then the legal ramifications and consequences for decision-makers and their advisors is of extremely gravity, especially when it comes the issues of aiding and abetting terrorist activity.
TERRORISM 101.
One of the binding laws of the Commonwealth that is of direct relevance to every person in Australia is the following Terrorist Act statute in Section 101.1 of the Commonwealth Criminal Code Act (1995):
(1) A person commits an offence if the person engages in a terrorist act.
Penalty: Imprisonment for life.
Given the severity of the penalty, any COVID-19 decision-maker, whether a private individual or a public official or an advisor, needs to know the following bio-terrorism definition:
Section 100.1(2) (a – e) of this criminal code.
Elements of the definition of terrorist act
(2) Action falls within this subsection if it:
(a) causes serious harm that is physical harm to a person; or
(b) causes serious damage to property; or
(c) causes a person’s death; or
(d) endangers a person’s life, other than the life of the person taking the action; or
(e) creates a serious risk to the health or safety of the public or a section of the public;
Since ignorance of the law is not a legally valid excuse, official COVID-19 decision-makers, and their appointed advisors, need to be fully aware of and comprehend, every Commonwealth, State and Territory Crown Law statute that applies to their decisions.
MATHEMATICAL MODELLING FOR SOUTH AUSTRALIA TO INFORM THE COVID READY PLAN
Prepared by Professor Nicola Spurrier
EXECUTIVE SUMMARY
When the South Australian borders open at a level of 80% vaccination of those over 16 years,
maintaining current Public Health and Social Measures (PHSM, i.e. activity restrictions) along with
the testing and contact tracing capacity in South Australia will allow us to remain within the state’s
hospital ward and ICU capacity.
Relaxing restrictions from current PHSM poses a risk to being able to manage the hospital ward and
ICU demand from COVID-19 infections generated in the community, with a moderate chance of
approximately 15–22% of exceeding ICU capacity if current PHSM remain in place but the mandatory
requirement for facemasks is removed. Furthermore, there is a high chance of approximately 79–
89% of exceeding ward capacity and 81–92% of exceeding ICU capacity if Vaccine Certificates (to
allow higher-risk activities by fully vaccinated individuals) with partial compliance of this new system
are introduced at the 80% vaccination threshold.
Mathematical models are characterised by uncertainty. The amount of uncertainty depends on our
ability to accurately measure the inputs for the model. Predicting human behaviour is inherently
difficult, which explains some of this uncertainty. Mathematical models need to be taken in this
context and be used along with other factors in determining public health response to preventing
disease outbreaks. Modelling remains an extremely useful tool to be able to inform planning and
decision making especially in an environment with no precedence.
OVERVIEW OF THE MODELLING
SA Health, with the assistance of SAHMRI, commissioned mathematical modelling specific to South
Australia to inform decision making about COVID-19 as population vaccination rates reach 80% in
line with Phase B of the National Plan.
The Doherty Institute, which has been undertaking modelling for the Commonwealth Government
throughout the entirety of the pandemic, used models of COVID-19 infection and vaccination to
define a target level of vaccine coverage for transition to Phase B of the National Plan. This national
model was based on the consideration of a range of factors associated with COVID-19 transmission,
severity and vaccine effectiveness for the Delta variant but was not specific for jurisdictions. It
provides a model based on the assumption of a single national epidemic. The Doherty network
continues to provide modelling that informs national approaches to testing, contact tracing,
isolation, quarantine and other aspects of disease control.
The team undertaking the South Australian modelling are specialist academics from the University of
Adelaide who are part of the broader Doherty network. The South Australian COVID modelling is
therefore similar to and informed by work done at the national level.
Mathematical models have inputs and outputs and the outcome of different scenarios can be
considered by changing these inputs. The inputs reflect the public health interventions available to
us which can be summarised as:
1. Vaccination – starting at 80% and assuming a steady increase
2. Public health and social measures (PHSM) – including personal hygiene behaviours, density
requirements and caps on numbers, mask wearing and COVID management plans.
3. Testing, tracing, isolation and quarantine (TTIQ) – this includes testing for COVID, contact
tracing of cases, isolating cases and requirements to quarantine close contacts. The use of
QR check-in information will remain critical.
The South Australian modelling also uses state-specific data. This includes:
- adjusting for the older population in South Australia
- adjusting for differences in vaccination rates across age groups along with state specific
- vaccination forecasts
- the South Australian estimate of transmission potential, reflecting the impact of PHSMs.
The model does not adjust for geographic differences in vaccination rates within the state. The
model has been based on seeding of cases into South Australia at a hypothetical rate of 20 infectious
cases per day for 30 days, noting that not all of these cases will be detected by testing. This rate of
seeding is considered reasonable given the predicted number of people entering South Australia
from the states where there are high rates of community transmission. All scenarios modelled
assume that South Australia will be opening its borders to fully vaccinated people only. The model
does not account for waning immunity over time, nor booster vaccine doses. The model assumes
that the public health and social measures in place at the beginning of border opening remain in
place for a 300-day period. This number of days is used in the model because it is important to map
out the whole hypothetical scenario for the length of time predicted by the modelling. This allows
the most accurate assessment of all likely outputs.
Test trace isolate quarantine (TTIQ)
The modelling has used our best estimate of the TTIQ capacity in South Australia. Up until now South
Australia has used an ‘optimal’ contact tracing system. However, as case numbers increase, contact
tracers will rely more on SMS messaging and the prioritisation of contacting cases will become
critical as the system is no longer able to contact everyone so quickly. This is necessary to cope with
the case numbers and we will move to ‘partial’ TTIQ. The point at which this changes has important
implications on the transmission of the virus. The actual point for transition to partial TTIQ is
untested and therefore unknown. The model involves the best estimate of realistic TTIQ for South
Australia and is called ‘mixed’ TTIQ.
Transmission Potential (TP)
TP refers to the average number of new people a positive COVID case infects. The TP is calculated by
taking into account current PHSM. It reflects the impact of a set of interventions by measurements
of social mobility (using for example Google mobility data), and a weekly national survey to assess
self-reported compliance with COVID safe behaviours. TP involves uncertainty and the model
includes best estimate of TP for South Australia. The TP for South Australia has been measured every
week over the pandemic and closely follows changes in our local restrictions.
Latest data from the scientific literature
The modelling incorporates the most up to date scientific information about COVID-19 transmission
(specific to the Delta variant) and impact of the disease. In addition, the modelling uses the most
recent scientific information about the effectiveness of vaccination in terms of stopping people
getting infected, onward transmission to others, asymptomatic and symptomatic infection, severe
illness, hospitalisation and death.
Outputs
Based on the above inputs, the model produces outputs. These outputs predict, the likelihood of an
outbreak occurring, the likely timing of this and the likely size of the wave. If an outbreak wave
occurs the modelling will also estimate the:
- daily number of cases,
- daily hospital admissions and total hospital ward capacity requirements,
- ICU beds needed; and
- number of deaths from COVID.
These outputs can then be compared against South Australia’s health system capacity, notably the
number of ward beds and ICU beds.
Modelling is an iterative process and three scenarios are the focus of this report:
1. Opening borders at 80% vaccination rate in South Australia and maintaining current PHSM.
2. Opening borders at 80% vaccination rate in South Australia and maintaining current PHSM,
but removing mask wearing requirements.
3. Opening borders at 80% vaccination rate in South Australia and maintaining current PHSM
including masks, but allowing higher risk activities for double-vaccinated people (using
vaccine passports and assuming 75% compliance).
KEY FINDINGS:
Scenario 1: Maintaining current PHSM (i.e., Current Restrictions)
- Under this scenario, the model suggests that South Australia will be able to manage the ward and ICU demand from COVID-19 infections generated in the community.
- The chance of an outbreak – that is averaging more than 100 cases per day over any three-day period – is estimated to be 27%.
- In the event of an outbreak, this scenario is estimated to be manageable with respect to
- hospital capacity:
- Peak Ward Occupancy – 36 beds (range 21, 78)1 and extremely small chance of demand exceeding 200 ward beds
- Peak ICU Occupancy – 9 beds (range 5, 19) and extremely small chance of demand exceeding 30 ICU beds; and
- Total Deaths (over the 300 days) – 13 individuals (range 4, 51).
- Peak Ward Occupancy and Peak ICU Occupancy for those aged 0-11:
- Peak Ward Occupancy (0–11 years) – 7 beds (range 2, 21)
- Peak ICU Occupancy (0–11 years) – 1 beds (range 0, 5).
Scenario 2: Relaxing restrictions from current PHSM – by removing mask mandates in general
settings but keeping all other public health restrictions in place
- The chance of an outbreak is estimated to be 64%.
- In the event of an outbreak, this scenario is estimated to present risks to being able to manage cases in particular with respect to ICU capacity:
- Peak Ward Occupancy – 70 beds (range 23, 203) – and a 3% chance of demand exceeding 200 Ward beds
- Peak ICU Occupancy – 18 beds (range 6, 47) – and a 20% chance of demand exceeding 30 ICU beds and
- Total deaths (over the 300 days) – 55 individuals (range 6, 186).
Scenario 3: Relaxing restrictions from current PHSM – by introducing the use of Vaccine
Certificates (with 75% compliance to this requirement) allowing higher-risk activities by
fully-vaccinated individuals
- The chance of an outbreak is estimated to be 84%.
- In the likely event of an outbreak, this scenario is estimated to present risks to being able to manage cases, in particular with respect to ward and ICU capacity:
- Peak Ward Occupancy – 351 beds (range: 24, 585)– and an 85% chance of demand exceeding 200 Ward beds
- Peak ICU Occupancy – 72 beds (range: 6, 119) – and an 87% chance of demand exceeding 30 ICU beds
- Total Deaths – 315 individuals (range: 8, 424)
1 median (95% confidence interval)
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