Covid-19 – New York State
Daily numbers of Cases (i.e., positively tested) and daily numbers of Deaths are shown on a logarithmic scale.
The peak in daily positives of ~10,000 was reached between March 30th and April 4th followed by the peak in daily deaths of ~800 between April 8th and April 11th.
We were able to predict the "location" of the peak in positives about a weak earlier by examining daily growth rate changes and the hospitalization data.
The prediction of the peak in daily deaths is then more straightforward, unless the medical system is highly overwhelmed, which in NYS did not happen though it got very close.
Daily numbers of Cases and daily numbers of Deaths are shown as a percentage of total. (That is, the integral, or the total area under each curve, sums up to 100%.)
Relative shape differences of the two curves are more easily identifiable with such presentation.
Deaths lagging initially but then growing faster and even overshooting the Cases is clearly visible, while on the downhill, Deaths eventually slow down more than the Cases.
The data was smoothed using the SMA3 algorithm (3-day standard moving average).
The Case Fatality Rate
For each date on the x-axis, the total number of deaths (up to and including that date) is divided by the total number of positively tested (up to and including that date) and this ratio is shown as a percentage on the y-axis.
At any given moment of an ongoing pandemic, CFR can be very different and higher than the Infection Fatality Rate (IFR). Best estimate of IFR for the SARS-CoV-2 virus is ~0.3-0.5% or lower.
The Attack Rate
Here, a percentage of new Cases of all newly Tested for Covid-19 (i.e., those at risk).
AR can be an indication of how wide-spread the infection is in the population.
For instance, a 10% of tested positives would imply that ~90% of the population is infection free.
Note the increase of Tested towards the end of Phase One along with the expected decrease of Cases.
Daily numbers of Cases (i.e., positively tested) and Deaths are shown as a function of Cummulative Number of Cases on a log-log scale.
An exponential growth would show as a straight line on this plot.
Customary for such a presentation of pandemic's dynamics, "drop-off" is clearly seen towards the end of Phase One in NYS in both the number of Cases and the number of Deaths.
Day-over-day growth rate is shown in terms of daily percentage growth in the number of positives and in the number of deaths.
For instance, a 3.4% growth rate on April 12th on the blue curve means that the number of positively tested increased by 3.4% from April 11th to April 12th.
An exponential growth would have a constant growth rate. These curves clearly show that, following the inflection point on the path of faster-than-exponential growth towards the peak, the growth dynamic has been characterized by a strongly decreasing rate of growth.
Same as above except with the data having been smoothed using the SMA5 algorithm (5-day standard moving average), in order to reduce the effects of daily fluctuations.
Daily changes in the numbers of hospitalized, of admitted to ICUs, of intubated (i.e., put on ventilators), and of those discharged.
The peak in hospitalization is clearly seen between March 30th and April 2nd. This is when the medical system was under the highest strain.
Hospital data are critical leading indicator of infection fatality and hence most important to be examined especially when the testing is sub-par due to either its availability or its precision or both.
Same hospitalization data as above except the daily numbers have been normalized to totals. That is to say, the integral, or the total area under each curve, sums up to 100%.
Such presentation is useful for comparison of shapes of various curves that are correlated in time.
Also overlaid are the normalized data of positively tested and of daily deaths.
The importance of close, accurate, and near-real-time monitoring of hospitalization data is paramount in staying ahead of the dynamics of the epidemic.
Analysis through June 7, 2020
Sources of data:
NYS Gov. A. Cuomo's daily briefings
NYS Department of Health COVID-19 Tracker