Timing is everything: COVID-19 caseload pattern and mitigation strategies in 4 US hot spots

Why New York? The question mark writes itself when we see alarming data on geographic disparity of the coronavirus attack rate across America’s cities. Yes, each area has its unique coronavirus curve, but equally, best practices on blunting the curve don’t vary wildly across nations either. How, then, did such stark gaps emerge in individual states’ curves within the United States? Even as states on the US East Coast and West Coast are banding together to figure out a reopening plan, new cases continue to overwhelm the US hospital system. This article seeks to provide a spot check on early trends in four early hot spots. Out west, California, which has a population of ~39 million, reported a cumulative death toll of 544 until 10 April. For New York, that number looks too much like its daily death toll number. New York State, with a population of ~19.5 million, crossed 10,000 lives lost by 13 April. At least three states in the US west coast — California, Oregon and Seattle have now become the national benchmarks for mitigation strategies. Centers for Disease Control and Prevention (CDC), in a new report out on 13 April, analyses the effect of a string of emergency measures on the cumulative caseload based on data from 26 February–1 April. Seattle, San Francisco, New Orleans, and the five boroughs of New York city are covered in the study because of their “substantial” caseload in the early stages of the US spread. The report analyses types and timing of public policies issued at the national, state and local government levels, cumulative number of reported COVID-19 cases, average 3-day percentage change in reported cases and community mobility. Key patterns emerge from the data although they don’t prove causality. Read in chronological order, they illustrate the gradual retreat of entire cities into isolation bubbles. Go a few levels deeper and we see how a cocktail of policy interventions rather than standalone ones is essential to making behaviour change count in the ultimate metric: Caseload.

1. Around 26 February, where the report opens, 8 in 10 people in all the four states all four, left home for work.

2. In a fairly predictable way, the percentage of residents leaving home in all four areas slumped as the number of policies layered on to the initial emergency declaration increased.

3. Community mobility in all four locations declined with each incremental policy issued.

4. In all four metropolitan areas, an emergency declaration was the first policy issued. Stay-at-home orders were typically the last mitigation policy to be announced.

5. Emergency declarations did not result in a sustained change in mobility.

6. Material declines in mobility happened after a combination of policies kicked in: School closures, White House social distancing guidelines, limiting visits to long term care facilities, restaurants and bars becoming take-out only and bans on non-essential gatherings.

7. Another dent in mobility came after stay-at-home orders in all four locations.

In the US, about half of the more than 23,000 deaths reported till date are in the New York metropolitan area. America’s top infectious diseases doctor Anthony Fauci has warned against reopening the US economy in a hurry. “It’s not an on-off switch”, he has cautioned often. Fauci wants an effective three-pronged containment strategy in place first: Testing at scale, ability to isolate those diagnosed with COVID-19 and contact tracing. Right now, the US is nowhere close.

• Healthcare
• USA and Canada
• Anthony Fauci
• Caseload Pattern
• Contact tracing
• Covid-19
• Mitigation Strategies
• US economy

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