A new report from the CDC shows the story of COVID-19 is very different from one state to the next.
On a macro scale, the United States had a coronavirus disease 2019 (COVID-19) incidence rate of 119.6 cases per 100,000 people as of April 7th, but a new study from the US Centers for Disease Control and Prevention (CDC) makes clear that the story of COVID-19 at the micro level is much different, varying widely from location to location.
In a recent CDC Morbidity and Mortality Weekly Report, authors provided a state-level update on COVID-19 cases, deaths, and incidence rates for the 50 states, the District of Columbia, and US territories.
The data showed that the cumulative incidence rate from locality to locality ranged from 20.6 to 915.3 per 100,000 within the continental US. The lowest rate was seen in Minnesota; the highest rate was seen in New York City.
“Geographic variation in numbers of COVID-19 cases and deaths, cumulative incidence, and changes in cumulative incidence likely reflects differences in epidemiologic and population factors as well as clinical and public health practices,” wrote corresponding author Virginia Bowen, PhD, MHS, a member of the CDC’s COVID-19 response team.
For the most recent 7 days included in the study, 7-day cumulative incidence rates ranged from 8.3 cases to 418 cases per 100,000, the data showed. As with the earlier statistic, the outliers in the 7-day average were Minnesota and New York City.
Part of the issue, Bowen and colleagues write, is likely related to the timing of when the virus hit specific areas, noting that the first cases to appear in the United States have been traced to travelers who returned from China, followed by community transmission in a few states.
“During the third week of February, California, Oregon, and Washington reported the first US cases with no known travel to China or exposure to a person with confirmed COVID-19,” Bowen and colleagues write.
“Case investigations indicated community transmission in these jurisdictions.”
Another factor is likely population density, according to the authors, who noted that New York City, Washington DC, and Louisiana have all been hard-hit.
“Cumulative incidence in urban areas like NYC and DC exceeds the national average,” they write.
“Louisiana, which experienced a temporarily high population density because of an influx of visitors during Mardi Gras celebrations in mid-February, has a higher cumulative incidence and greater increase in cumulative incidence than other states in the South.”
The timing of social distancing measures and closures, as well as varying testing and containment strategies, also likely at play in the data.
“For example, the state of New York (excluding NYC) reported administering 4.9 tests per 1000 population, which was higher than the national average of 1.6 (CDC, unpublished data, March 25, 2020); this expanded level of testing might have contributed to better ascertainment of cases and might partially explain the state’s higher case count and cumulative incidence,” they write.
Localities that expanded testing at later dates might see later increases in cases and incidence, they write.
Death rates also vary significantly in the data, which Bowen and colleagues say might have a lot to do with the specific populations affected.
For instance, Washington State had outbreaks in skilled-nursing and long-term care facilities, which likely skewed their death rate higher, since an already vulnerable population was affected by those outbreaks. The state had a 4.5% death rate, the same as Michigan’s. Only Kentucky, Oklahoma, and New York City had higher death rates, though Kentucky and Oklahoma each had fewer than 100 deaths total as of April 7th.
The Northern Mariana Islands had the highest death rate, but that was based only on 2 deaths in 8 total cases.
The authors say much more will become clear in the coming months. As of the end of the study period (April 7th), only 12,800 deaths had been reported nationwide. As of April 21st, that number had soared past 44,000.
“Monitoring changes in numbers of reported cases and disease incidence within jurisdictions over time is critical to understanding and responding to the evolving local epidemiology of this outbreak,” the authors conclude.