On October 27th, the nation is seeing its highest rate of new cases since the beginning of the pandemic, at about 21 new cases per 100K population. Two counties in New Jersey--Essex and Union--have new case rates that are higher than this, and an additional 10 counties (Hudson, Atlantic, Passaic, Middlesex, Morris, Bergen, Burlington, Camden, Gloucester and Ocean) have rates above 10 cases per 100K population. To provide some perspective, we compared new case rates today with new case rates at the peak of New Jersey's pandemic (in April) and the time of lowest infections (July). Today, the rate of new cases is about 13.6/100K, compared to 2.8/100K in July and 48/100K in April. This means that the rate of new cases today is 4.8 times higher than it was in July, and about 30% what it was at the peak in April. If there were a thermometer where July was the low temperature, and April was the high temperature, we would be a little less than 25% of the way to the high temperature.
The goal of this tracker is to provide the most informative regional metrics about COVID-19. When case counts were low, the daily Rt was an important indicator that although cases fluctuated, New Jersey remained below the threshold of 1 that could indicate increased spread. Now that Rt has consistently remained above one for weeks, cases are rising rapidly. With the current case counts, an Rt just barely above one can still result in large numbers of new cases. Thus, we are now in a phase of the outbreak where looking at case numbers and % increases is more informative than Rt. We continue to report Rt, but we want to point out to readers that given current COVID-19 conditions in New Jersey, the case numbers in a region are likely more useful than Rt. On October 27th, Rt in New Jersey remained above 1. In the South, we estimate Rt as 1.05 (CI = 0.99 - 1.10). In the northeast, we estimate Rt at 1.09 (CI = 1.06 - 1.12). In the northwest, we estimate Rt at 1.17 (CI = 1.10 - 1.25). The Rt calculation looks at the way new cases change over time to estimate the rate of transmission, which is the number of people, on average, infected by each infected person. This calculation is an estimation, which means it gives you a best guess, but it also gives you information about how reliable that guess is. In the number above, we report a 95% Confidence Interval (CI). This means we are 95% sure that the Rt is between these two values.
Cases increased last week. The total number of new cases in New Jersey from October 20th-October 26th was 8,371, while the week from October 13th - October 19th saw 7,084 new cases. This is an 18% increase. Increases were highest in northwest NJ (+41%), and lower in northeast NJ(+18%) and southern NJ (+8%). The country last week had about 490,000 new cases, with 409,000 the week before. This is an increase, about 20%.
New deaths doubled last week in New Jersey as a whole. New Jersey reported 78 deaths between October 20th-October 26th, and it reported 39 the week of October 13th - October 19th. Nationally, deaths also increased. The US had 5,587 deaths from COVID-19 last week, and 5,034 the week before. Because the numbers overall are small for deaths in New Jersey, they are particularly susceptible to noise. [Note: on days where a county reported negative new deaths, we excluded that data point from analysis.]
**Data like these are inherently noisy. In the plots, we smooth the data over a 7-day period to help account for the noise. We do not smooth when we report weekly totals. In late June, the state began to include probable deaths as well as confirmed deaths in the numbers reported to the Johns Hopkins database. This caused a large spike in the reported number of new deaths. We included these in the total deaths, but took the spike out of the incremental day analysis to avoid a misleading spike in the graph. Each date's data point includes the average of data seven days prior to that date Please consider these daily plots as a useful rough sketch. State reports and detailed models provide additional information. There are often reports of "negative" deaths and cases, which likely occurs as data are updated. For use in percent changes, we remove "negative values" from the calculations involving increments, but we leave them in the calculations that report cumulative values. For counties with reports of "negative" new cases, we report the data as missing in the heat map.
Contact Sarah Allred at firstname.lastname@example.org
The plots here visualize the progress of COVID-19 across three regions in New Jersey. New cases (first figure) and new deaths (second figure) are shown on the y-axis, and time (in days) is shown on the x-axis. To account for population differences between the three regions, we plot the number of new cases (or deaths) per 100,000 population. For example, if the value on the y-axis is 10, that would mean that 10 out of every 100,000 people tested positive for COVID-19 the previous day. The first day on the graph is March 22, 2020.
We plot a rolling 7-day average of the data. This means that each days number is an average of 7 days. We do this because there are variations in the time it takes to report deaths. For example, a health department might be overwhelmed and unable to enter all the deaths on one day, making the numbers look lower than they should.
In addition to plotting data by county, we also average across three regions of the state. The first is northeastern counties. These are counties that had more than 1000 infections each on 4/1/2020, and include Bergen, Essex, Hudson, Middlesex, Monmouth, Ocean, Passaic and Union counties. The second is northwestern counties. These all had fewer than 1000 infections on 4/1/2020. The third is southern counties, including Atlantic, Burlington, Camden, Cape May, Cumberland, Gloucester, and Salem counties. These counties had fewer than 250 cases on 4/1/2020.