Professor Paul Dennis, a geologist and isotope geochemist at the University of East Anglia, compared the deaths in England, Sweden, Spain. He found near identical dynamics, which supports the theory that COVID-19 appears to follow the Gompertz curve in every outbreak region. This implies that social distancing and lockdown has no effect.
COVID-19 appears to follow the Gompertz curve in every outbreak region. This means that government interventions do nothing to stop the virus.
We demonstrate that universal scaling behavior is observed in the current coronavirus (COVID-19) spread in various countries. We analyze the numbers of infected people in selected eleven countries (Japan, USA, Russia, Brazil, China, Italy, Indonesia, Spain,South Korea, UK, and Sweden). By using the double exponential function called the Gompertz function, fG(x)=exp(−e−x), the number of infected people is well described as N(t)=N0 fG(γ(t−t0)), where N0, γ and t0 are the final total number of infected people, the damping rate of the infection probability and the peak time of dN(t)/dt, respectively. The scaled data of infected people in most of the analyzed countries are found to collapse onto a common scaling function fG(x) with x=γ(t−t0) in the range of fG(x) ± 0.05. The recently proposed indicator so-called the K value, the increasing rate of infected people in one week, is also found to show universal behavior. The mechanism for the Gompertz function to appear is discussed from the time dependence of the produced pion numbers in nucleus-nucleus collisions, which is also found to be described by the Gompertz function.
Stockholm is the best population to test Covid theory whereby it was hit hard early and did not have lockdowns. Nobel Prize winner Dr Michael Levitt postulated that the virus burns out when it has infected 15-20% of the population. According to this, he’s right.
So what does this mean? Lockdowns were a waste of time and resources. Minimizing deaths just delays the inevitable. Those countries which were not hit are most likely to see continued spikes and outbreaks. Maybe less during the summer but a second wave later this year.
The Gompertz function describes global dynamics of many natural processes including growth of normal and malignant tissues. On one hand, the Gompertz function defines a fractal. The fractal structure of time-space is a prerequisite condition for the coupling and Gompertzian growth. On the other hand, the Gompertz function is a probability function. Its derivative is a probability density function. Gompertzian dynamics emerges as a result of the co-existence of at least two antagonistic processes with the complex coupling of their probabilities. This dynamics implicates a coupling between time and space through a linear function of their logarithms. The spatial fractal dimension is a function of both scalar time and the temporal fractal dimension. The Gompertz function reflects the equilibrium between regular states with predictable dynamics and chaotic states with unpredictable dynamics; a fact important for cancer chemoprevention. We conclude that the fractal-stochastic dualism is a universal natural law of biological complexity.
Part 1: Exponential Growth is Terrifying
Part 2: Curve Fitting for Understanding
Part 3: COVID19 Never Grows Exponentially
Covid-19 appearance and fast spreading took by surprise the international community. Collaboration between researchers, public health workers and politicians has been established to deal with the epidemic. One important contribution from researchers in epidemiology is the analysis of trends so that both current state and short-term future trends can be carefully evaluated. Gompertz model has shown to correctly describe the dynamics of cumulative confirmed cases, since it is characterized by a decrease in growth rate that is able to show the effect of control measures. Thus, it provides a way to systematically quantify the Covid-19 spreading velocity. Moreover, it allows to carry out short-term predictions and long-term estimations that may facilitate policy decisions and the revision of in-place confinement measures and the development of new protocols. This model has been employed to fit the cumulative cases of Covid-19 from several Chinese provinces and from other countries with a successful containment of the disease. Results show that there are systematic differences in spreading velocity between countries. In countries that are in the initial stages of the Covid-19 outbreak, model predictions provide a reliable picture of its short-term evolution and may permit to unveil some characteristics of the long-term evolution. These predictions can also be generalized to short-term hospital and Intensive Care Units (ICU) requirements, which together with the equivalent predictions on mortality provide key information for health officials.
The COVID-19 epidemic curves are consistent and follow the Gompertz curve. Similar distributions have been reported for Influenza, such as the 1918/19 epidemic in Prussia.