Difference between mortality and case fatality rate

In light of loose use of the term "mortality" with respect to the COVID-19 epidemic, it is important to remember that there is a dramatic difference between mortality and case fatality rates. What I've noticed is that many are referring to a 2-3% "mortality" rate for COVID when what they mean is 2-3% case fatality rate.

Here's why the difference matters...

Mortality Rate = Deaths / Population at Risk Often the denominator for mortality rate is the entire population at the beginning of some time period (usually a year), but sometimes we mean a specific sub-population (for example, Infant Mortality Rate = Infant Deaths / Live Births).

Case Fatality Rate = Deaths / Population with the Condition The case fatality rate is a special subset of mortality rates in that the rate is calculated only based on those with the condition.

Because not everyone gets every condition, Case Fatality Rates are higher--sometimes dramatically so--compared with overall Mortality Rates.

Example:

The Case Fatality Rate for measles is approximately 15%. This means that of those people who get measles, approximately 15 percent die. But we have widespread vaccination, so most people do not get measles. From 2016-2019 there were 0 measles deaths among the United States population of nearly 330 million. Thus, while the Case Fatality Rate remains high, the observed measles Mortality Rate for 2016-2019 in the United States was 0.

In other words: the risk of death is still high for those who contract measles, but the number of cases has been low due to preventative measures (like vaccines).

For COVID-19:
(Based on March 1, 2020 data from WHO)

Mortality Rate = unknown
(was 3,000 deaths / 7,000,000,000 population as of March 1, 2020 but is still rising
Note: The year-end mortality rate will be much higher because the disease is still spreading, but the current number is well below 0.001%)

Case Fatality Rate = 3,000 / 87,137 = 3.4%
Note: This estimate may be too high because not every country has implemented widespread testing, so the number-of-cases denominator may be somewhat low. Best estimates to date of COVID-19 Case Fatality Rate are between 2%-3.4%.

So when you see someone refer to 2-3.4% for the COVID-19 "mortality rate," that does not mean the virus will exterminate 3 percent of the global population. It does mean, however, that we should take the risk seriously.

We can slow the spread through social distancing, good hygiene, and (eventual) vaccine development.

A note about measuring maternal mortality in Texas

You may (or may not) have heard that Texas has the highest maternal mortality in the nation, as a result of recent, dramatic increases in reported maternal deaths.

Or... it doesn't.

Researchers working for the state of Texas conducted a reassessment of the 2012 maternal mortality records. Researchers hypothesize that data entry errors led to records being inaccurately classified as maternal deaths. Knowing, as we do, that maternal mortality reporting has some considerable data accuracy challenges, this seems on the surface to be a good faith effort.

That said, I have concerns with the methods in the Texas analysis (explained in more detail below). In addition, while the authors do a nice job of stating the limitations of their work--data are not comparable to other years or other locations--the news media did exactly the opposite: compare to other places and times.

In 2012 Texas had 147 mortality records with an ICD-10 code indicating maternal mortality (codes A34, O00–O95, or O98–O99). Texas researchers used record matching and extensive death and health record review for the 147 maternal mortality coded deaths. Through this process the researchers identified birth or pregnancy status (within 42 days) at the time of death. This extensive review found a number of false positive results. Researchers then removed these deaths from the maternal mortality count. On this point, the analysis seems both reasonable and robust.

However, any analysis of data coding errors should clearly identify both false positives and false negatives. The search for false positives was (as described above) robust. The search for false negatives, on the other hand, used record matching alone. This may seem a minor point, but it is important because the robust methods used to find false positives were not similarly applied to find false negatives. Moreover, the record linkage process matched on SSN, name, and county of residence. Given their hypothesis of data entry errors, finding exact matches for all three of those open-ended data entry fields raises all sorts of possibilities for missed matches. In other words, the methods introduced potential bias in favor of finding false negatives and against finding false positives.

I recognize that individual case review for 9,000+ death records was probably implausible due to time and funding constraints. Still, more could easily have been done to try and identify false negatives. For example, they might have added a record linkage between all birth records and all death records.

And... Here's the piece that puzzles me most...

The Texas researchers posit (repeatedly) that the number of false positives is some artifact of newer data entry techniques. They state, specifically, that the upswing in the reported maternal mortality rate was driven by an increase in e-reporting:

"The percentage of death certificates submitted electronically increased from 63% in 2010 to 91% in 2012"

But... if electronic reporting was the problem, why wouldn't the problem have shown up in 2010 when 63% was already e-reported? Why do they think an incremental 28 percentage points was pivotal when first 63% was not? And, perhaps most importantly, why do they skip over 2011 when that year (not 2012) was the pivotal year for the increase in reported maternal deaths in Texas? (2011 was also the year TX began restricting family planning and reproductive health services.)

Texas Maternal Mortality Trend
Source: CDC WONDER, Multiple Cause of Death database, and natality database
Note: CDC reports 148 deaths in ICD-10 codes A34, O00-O95,O98-O99), TX reports 147

Unpleasant reversal

In preliminary mortality data out this month from CDC, a few issues stand out. First, estimated life expectancy at birth decreased (by 0.1 year) between 2014 and 2015. Granted, a single year does not a trend make, but some of the underlying details are downright disturbing:

• Drug overdose mortality rates are up (see details for young adults)
• Suicide mortality is up (see details for young adults and for teens)
• Infant mortality (especially unintentional injuries) are up

Infant Mortality Rate by Cause:
Source: CDC

The demography of Thanksgiving

While we acknowledge that the first harvest feast (what we now call Thanksgiving*) in Plymouth came at the end of a hard year, we have few modern references to highlight just how difficult conditions were for those early English settlers.

Of 137 people who made landfall and stayed on in Plymouth (102 from the Mayflower and 35 more from the Fortune), 54 died during the first year. The mortality rate for settlers arriving that first year was nearly 40 percent.**

Population Dynamics for the Plymouth Pilgrims November 1620 - November 1621

	Atlantic Voyage	Docked off Cape Cod	Dec 1620 - Mar 1621	Apr 1621 - Oct 1621	Nov 1621	Total	Crude Rate
Births	1	1	0	0	0	2	21
Deaths	-1	-4	-44	-5	0	-54	-578
In Migrants	102	0	0	0	35	137	--
Total Pilgrims	102	99	55	50	85	--	--

What's perhaps even less well known is that an epidemic of plague, which decimated the Wampanoag tribe between 1616 and 1619 may have been responsible for the tribe's willingness to assist the settlers.

The epidemic wiped out an estimated three quarters of the Wampanoags who lived near Plymouth in the early 1600s. The tribe was estimated to be approximately 8,000 people in 1600, but fewer than 2,000 survived by 1620.

Without help from the Wampanoag, there is little doubt that the mortality rate for the Plymouth Pilgrims would have been much higher.

Sources:
University of Illinois, Department of Anthropology. "Population Of Plymouth Town, Colony & County, 1620-1690."
Edward T. O'Donnell. "Of Plague and Pilgrims: How a Devastating Epidemic Shaped the First Thanksgiving."

Notes:
*Declared a national holiday in 1863.
**If we use current techniques to estimate crude mortality rates - taking the number of deaths and dividing by a reference population estimated as the average of the beginning and ending date populations, the crude death rate was a whopping 577 deaths per 1,000 population.

Healthy living after age 65

A new report from CDC compares life expectancy and healthy life expectancy after age 65 across states in the U.S.

Life expectancy is the average remaining years of life a person can expect to live on the basis of the current mortality rates for the population.

Healthy life expectancy is a population health measure that estimates expected years of life in good health for people at a given age. The measure is useful for public health and public policy analysis. Healthy life expectancy, relative to total life expectancy, can be used to identify populations that might be enduring illness or disability for years. And differences within and among populations can be used to identify areas of greatest need for health interventions.

The most recent analysis shows that Southern states have lower life expectancy and fewer years of healthy life, regardless of race, after age 65 than other states. In the press release, CDC Director Tom Frieden, M.D., M.P.H. writes:

"Where you live in the United States shouldn't determine how long and how healthy you live - but it does...”

Other highlights include:

• Hawaiians have the longest life expectancy and healthy life expectancy after age 65.
• Mississippi residents have the shortest.
• For whites aged 65 years, healthy life expectancy varied from a low of 11.0 years in West Virginia to a high of 18.8 years in DC.
• Mississippi also has the lowest proportion of years of healthy life expectancy to overall life expectancy.
• Vermont has the highest ratio of healthy years to overall years of life expectancy.
• In each state women, on average, have higher life expectancy and healthy life expectancy than men.

For more information, see the full CDC report.

Population Profile: Alabama

POPULATION GROWTH IN ALABAMA:

Population in 2010: 4,779,735
Population in 2000: 4,447,100
Growth rate 2000 to 2010: 7.5%
Sources: U.S. Census Bureau, Census 2010 and Census 2000

Place of Birth: Percent of resident population born in the state of Alabama:

Source: U.S. Census Bureau, American Community Survey 2007-2011

AGE STRUCTURE:

Median age in 2010: 37.9

Alabama Age Structure in 2010:

Source: U.S. Census Bureau, Census 2010 and author's calculations

PUBLIC HEALTH:

Birth rate: 12.4 per 1,000 population (compared with national rate 12.7)
Fertility rate: 61.8 per 1,000 women age 15-44 (compared with national rate 63.2)
Infant mortality rate: 8.28 per 1,000 live births (compared with national rate 6.39)
Sources: U.S. Centers for Disease Control and Prevention: preliminary birth data for 2011, final death data for 2009

Life expectancy: 75.2 years (compared with national 78.6)
Source: Kaiser Family Foundation state health facts 2007

Adult obesity rate in 2011: 32.0 percent
Source: U.S. Centers for Disease Control and Prevention, Behavioral Risk Factor Surveillance System

OTHER FACTS:

Only 3.4 percent of the population in Alabama is foreign-born, compared with a national average of 12.8 percent.
Source: U.S. Census Bureau, American Community Survey 2007-2011

Despite the holiday's association with New Orleans, it is Mobile, Alabama that gets credit for hosting the first Mardi Gras celebration in North America in 1703.
Sources: CNN and History Museum of Mobile

Nation's largest metros growing, but reasons vary

America's biggest metropolitan areas are growing, but for very different reasons, according to a new report from the U.S. Census Bureau.

Among metropolitan areas of 2.5 million people or larger, only Detroit lost population between July 1, 2010 and July 1, 2011. The other twenty large metro areas all saw population growth. However, drivers of growth varied widely among metropolitan areas.

Source: U.S. Census Bureau

DRIVERS OF GROWTH:

Population change occurs because of births, deaths, and migration. Births and deaths, collectively, are referred to as "natural increase."

At the state, county, and local level, migration can measured in a variety of ways, but is often estimated in terms of net international migration (those moving into, or out of, an area from abroad) and net domestic migration (those moving into, or out of, an area from another area within the same nation).

NET DOMESTIC OUT MIGRATION IN THREE LARGEST METROS:

In the nation's three largest metropolitan areas, New York, Los Angeles, and Chicago, population grew as a result of births, longer life expectancy, and international migration.

However, net domestic migration estimates show that more residents moved out of these areas to other parts of the United States than moved into these areas between 2010 and 2011.

DON'T MESS WITH TEXAS:

The largest metropolitan areas in Texas, however, showed an entirely different pattern, acting as magnets for migration from other parts of the United States.

The Dallas-Fort Worth and Houston metro areas both grew by more than 100,000 during the year with 20 percent or more of that growth coming from net domestic migration.

SUNSHINE STATE:

Miami and Tampa, Florida's largest metropolitan areas, were also net-attractors of residents from other parts of the U.S. Miami showed fairly even population growth across all categories (20,400 natural increase, 35,200 international migrants, 36,200 domestic migrants) for net population growth of more than 92,000.

While Tampa attracted more than 27,000 domestic migrants, net international migration was less than 7,000, and an aging population resulted in net natural increase of only 2,300, the lowest of all 21 large metropolitan areas in the report.

GOLDEN STATE:

As noted above, more residents moved out of the Los Angeles metro area than moved in between 2010 and 2011. However, other large metros in California fared better. As a result of net domestic in-migration San Francisco gained 5,900, Riverside-San Bernardino gained more than 15,000, and San Diego grew by 800.


Methodology and Source Notes:
The figures shown above are from the U.S. Census Bureau Population Estimates (vintage 2011). Additional information on patterns of migration can be found in the Current Population Survey report on geographic mobility.

Dia de los Muertos: Life expectancy trends

Historic New England cemeteries are a bit different than cemeteries in many other states in the U.S. in that they were often family plots, on local farms or homesteads, and not in a church yard.

Early Puritans rejected churchyard burials as they rebelled against other "papist" practices, as heretical and idolatrous. Instead, many 17th century New England towns set aside land as common community burial grounds. Headstone images from this period also reflect the rejection of formal Christian iconography in favor of more secular figures, such as skulls representing fate common to all men.
Source: National Park Service

As a result, a hiker often stumbles across tombstones on a typical trek in southern New England. These tiny graveyards provide a tangible record of the region's demographic history.

One of the most striking details, aside from the sizable share of persons who passed away before their fortieth birthday, was that so many tombstones were marked in years and months. In some cases, life was marked in years, months, and days.

Aged 23 years 10 months & 25 days

This is clear physical evidence of a phenomenon clearly understood by demographers: life expectancy was short at the turn of the last century.

There is, too, the startling reminder of high infant mortality in the 1900s New England. One in ten children did not survive to reach their first birthday.

Infant: age 3 months & 3 days

Pregnancy was also a dangerous condition. According to the CDC, "For every 1000 live births, six to nine women in the United States died of pregnancy-related complications." Today those trends have been sharply reversed. Across most populations infant mortality claims fewer than 7 deaths per 1,000 live births, and maternal mortality has declined to 0.1 per 1,000 life births.

But despite these dark statistics, the gravestones mark the longevity of many people who buck the trend.

Demographically speaking, life expectancy is just an average. Some people live far longer, and some much shorter. But the real life outliers are always a pleasant surprise.

Age 74 years 4 months & 20 days

Here is the life-expectancy data behind the anecdotal, archaeological evidence:

Source: U.S. Centers for Disease Control and Prevention Health Data Interactive query system, author's calculations

*Note: Data for 2010 reflect published 2009 statistics

To ensure comparable data over time, the chart above shows life expectancy for white males and for white females, at birth, from 1900 - present. Life expectancy in 1900 was lower than 50 years for whites, both men and women in the United States. Available evidence suggests that life expectancy was even shorter for minority populations (approximately 32 years of age for black men, and 33 for black women in 1900).