in Albany, Buffalo, Coronavirus, Governor Cuomo, New York, New York City, Rochester, Syracuse, Utica-Rome

Covid-19 Cases Increase Unevenly in New York


Through this Summer, Covid-19 case numbers remained low in New York State.  Though the numbers remain far below the levels of March and April, the rate of infection statewide is increasing.  In July and August, the state averaged between three and four cases per 100,000 residents per day.  By October the number had increased to more than seven cases per 100,000 residents.    But the growth is quite uneven.  Some metropolitan areas in upstate New York have seen no growth, while other areas have had substantial increases.  In each case, the daily rate is computed by averaging the number of cases for the preceding seven days.  The data is from the New York State Department of Health.

Despite the growth in cases statewide, New York’s rate of infections remains among the lowest in the nation.  With 7.21 cases per hundred thousand in New York, only Vermont, Maine, Connecticut, and New Hampshire have lower rates.

In part, the growth in the rate of infection in New York reflects the increase nationally, as students return to schools and colleges and more social activities move inside with cooler weather.  Nationally, daily Covid-19 diagnoses have grown from 40,000 at the beginning of September to 50,000 in early October.

Many upstate metropolitan areas, including Buffalo-Niagara Falls, Rochester, Utica-Rome, and Albany-Schenectady-Troy showed variations in infection rates over the summer but did not show large increases in the past month.  Each of the areas had an infection rate of less than six per hundred thousand residents per day in early October.

 

The Growth in New Cases is Concentrated in a Few Counties

Several counties have seen substantial upticks in Covid-19 infection rates, with 10 having infection rates that were greater than 10 per hundred thousand based on the daily average for the seven days ending October 10th.   Chemung, Broome, Cortland, Tioga Steuben, and Schuyler Counties in the Southern Tier saw high rates and substantial increases in Covid cases.  Rockland and Orange Counties in the   Mid-Hudson region also had high rates and significant increases.

While the number of cases in New York State doubled between September and October – from 689 to 1,386, the case growth in New York was concentrated in five counties – Kings County (Brooklyn) – 162, Rockland – 78, Queens – 77, Broome – 63, and Orange – 49.  Together, these locations accounted for more than 420 0f the 698 additional daily cases – 60% of the total – reported in the period ending October 10th compared with the same period in September.  30% of New York’s population lives in these counties.

 

 

Conclusions

The increase in cases in New York is concerning, though, at this point, a few locations have been responsible for much of the increase.  Governor Cuomo has shifted his approach from his initial insistence on regionally consistent limits on personal interactions.  Instead, the state is now applying a form of micro-targeting, imposing stricter rules on hot spots with high levels of infection in an effort to limit the economically damaging effects of restrictions on personal and business activities.  The map below shows one hot-spot in Queens where stricter limits on restaurants and other gatherings have been imposed.

A few of the hotspots in small upstate counties developed because of infections at congregate settings, such as nursing homes and colleges.  Other hotspots have developed where widespread disregard of social distancing and mask-wearing rules have been present.  All of this points to the reality that the State’s success in controlling Covid-19 infection rates during the Summer could disappear if people don’t take the precautions the epidemiologists have recommended.

Write a Comment

Comment

This site uses Akismet to reduce spam. Learn how your comment data is processed.

  1. Thank you John. Great summary of the numbers. And, good point about how the State is responding to the hot spots. It seems logical to have a consistent generalized approach to manage the pandemic at the macro level, and to use a more targeted approach towards the hot spots. Policy by numbers … great theme.