As CDC Expects Surge in NJ COVID-19 Cases, New Jerseyans Fear Murphy Reaction

Robert Walker

TRENTON, NJ – The Centers for Disease Control has announced a grim forecast. COVID-19 could surge again this fall, and in New Jersey, residents are beginning to wonder if, and when Governor Phil Murphy could go back into COVID mode.

New Jerseyeans, especially business owners who are just now recovering financially from the last COVID-19 outbreak and subsequent business lockdown, fear the governor will return to forced masking and business closures if he perceives a public health threat on the horizon.

Murphy has said repeatedly that if COVID-19 returns, he will enact whatever measures are necessary to control a future outbreak.


“All options are on the table,” the governor infamously repeated throughout the 2020-2021 crisis.

The CDC’s latest predictions show a potential increase in daily COVID-19 hospital admissions across the United States, with figures likely ranging from 1,100 to 7,500 on September 18.

State- and territory-level ensemble forecasts, which amalgamate forecasts from independent teams into one unified forecast, indicate that over the coming four weeks, the trends in numbers of future hospitalizations are uncertain or predicted to remain stable across all states and territories.

Though ensemble forecasts have consistently been among the most reliable, their historical performance indicates that they are not infallible in predicting rapid shifts in the trends of reported cases, hospitalizations, and deaths. As a result, they should not be solely relied upon when making decisions regarding rapid changes in trends.

This week’s forecast, which consists of contributions from 9 different modeling groups, portrays daily COVID-19 hospital admissions in the United States from June 13 through August 11 and forecasts them through September 18.

The models include various assumptions regarding social distancing levels and other interventions, and they may not always reflect recent behavioral changes. It is essential to consult the individual model descriptions for a comprehensive understanding of the assumptions and methods employed in producing these forecasts.

The data reveals the continued complexity of predicting the path of the pandemic and emphasizes the need for vigilance and adherence to public health guidance in managing the ongoing health crisis.

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