There’s been so much vitriol over vaccines. They can halt cases and save lives, the data and experts say.
But, really, by how much?
James Doti — president emeritus of Chapman University, professor of economics, teacher of statistics and author of econometric texts as well as children’s books — decided to find out.
He gathered COVID-19 case and death data for all 50 states from Jan. 1 to Aug. 10 and used stepwise regression — a way to build models by controlling for variables like density, poverty and governmental COVID-19 restrictions— to find something stunning:
Vaccines prevented some 16.7 million COVID-19 infections in the United States over those seven or so months, and prevented some 245,000 deaths, according to his models.
“It’s absolutely crazy for people not to get vaccinated,” Doti concluded. “The impact in terms of saving lives, reducing caseloads — think about what it would have been like if we had 16 million more cases and nearly 300,000 more deaths during the the recent delta surge. It was horrible as it was. But without vaccinations, it would have been an unmitigated disaster.”
The paper, “The Impact of Vaccinations on COVID-19 Case Rates at the State Level,” from the A. Gary Anderson Center for Economic Research at Chapman University, was published in the Social Science Research Network.
Doti found that for every 1% increase in a state’s vaccination rate, there was a 0.7% decrease in COVID-19 case rates.
California was more well-vaccinated over the time period studied than the rest of the nation. That translated into some 1.6 million fewer cases in the Golden State, according to the models.
As it stands, the U.S. has logged 45.8 million confirmed COVID-19 cases and nearly 750,000 deaths. Without vaccinations, that would look more like 61 million cases and 1 million deaths, Doti’s models suggest.
Crunching numbers
Doti teaches statistics and econometrics at Chapman, and, to make it more interesting, he started looking at COVID-19 data and using it as examples for his students last year.
The numbers raised so many interesting questions. What explains the significant differences by state in COVID-19 death rates? Why is Mississippi so much higher than Vermont?
“A number of academic studies have studied the impact of vaccinations on COVID-19 case rates. These studies, however, do not investigate statewide differences and how those differences can be used to estimate the efficacy of COVID-19 vaccination rates,” the Doti study said.
And so, he controlled for variables that can affect outcomes — vaccination rates, the density of people packed into a geographic area, poverty rates and governmental policies such as school and bar closings, masking and distancing requirements, and the like.
“The statistical results rigorously show that higher vaccination rates led to significantly lower COVID-19 case rates at the state level,” the paper said. But what else also had an effect?
- Density, Doti found, had a big impact early in the pandemic (think New York City in spring of 2020), lost significance in the last half of 2020, then reemerged as a factor this year.
- Poverty rates were significant during all periods. A 1% increase in a state’s poverty rate led to a 0.25% increase in its COVID-19 case rate.
- While official COVID-19 restrictions such as closures, masking and social distancing — called “governmental stringency” and measured by the Oxford University Stringency Index — were significant in reducing case and death rates last year, they had no significance this year, he found. That might be because so many states essentially dropped them as the year wore on.
- Finally, there was no significant evidence that “herd immunity” — resistance to disease thanks to a previous infection — played a role.
Doti is now poring over data from August through late October — including the height of the delta surge — for his next analysis. There were 130,703 COVID-19 deaths nationwide during that time, and 8,180 in California. It will cover the role that race, ethnicity and age played, along with vaccination rates.
Death findings consistent
Several medical experts who reviewed the Doti’s paper said his methodology was “outside the wheelhouse,” but they found that the magnitude of lives saved seems about right, given what other studies have shown.
“The most important finding was the estimate of lives saved by vaccination,” said Dr. John Swartzberg, clinical professor emeritus at UC Berkeley, by email. “That vaccination saves lives is not at all surprising. Carefully performed studies throughout the U.S. as well as other countries have demonstrated the same.
“The data from this paper covered a large part of our delta surge and this, while consistent with several MMWR (Morbidity and Mortality Weekly Report) reports this summer, further emphasizes how well our current vaccines are in protecting people from death from delta.”
The density data are consistent with the observation that the pandemic struck first and hardest in densely populated areas, and from there spread to more rural areas, he said.
“I suspect the finding that density played a less prominent role later in the pandemic is because there was greater community (herd) immunity from previous infection and robust vaccination programs in the more densely populated portions of the state,” Swartzberg said. “This urban/rural divide was also seen throughout much of the U.S. There was and continues to be much more vaccine hesitancy in rural areas.”
A consistent theme throughout the pandemic has been that poverty directly correlates with hospitalization and death — and it’s worth noting that poverty correlates with death in all pandemics that have been studied, as well as with deaths from other infectious diseases. “Tragic,” Swartzberg said.
Andrew Noymer, an epidemiologist and demographer at UC Irvine, said the use of state-level data leads to a not-very-granular analysis, which tends to overstate underlying effects.
“I have zero doubt that more vaccination leads to fewer cases of COVID; and this paper shows this,” Noymer said by email. “But the more one drills down on the paper and the methods used, the less one finds that it brings to the table, in terms of knowing something that we didn’t know yesterday.”
Doti has published several other papers on the pandemic, including one in the Journal of Bioeconomics that used stepwise regression to examine the most significant socioeconomic variables in explaining COVID-19 death rates in 2020 (density, poverty), as well as one in the Centre for Economic Policy Research’s Covid Economics, which analyzed statewide policy interventions, their impact on COVID-19 deaths and on jobs and real gross state product (policy interventions reduced COVID-19 deaths in the U.S. by 358,000 lives in 2020, and resulted in a loss of 7.3 million jobs and a loss of $410 billion).
Source: Orange County Register
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