Over 30,000 coronavirus cases, 700 deaths resulted due to 18 Trump rallies in 2020: Stanford study

 Over 30,000 coronavirus cases, 700 deaths resulted due to 18 Trump rallies in 2020: Stanford study

In the study by Stanford University, researchers concluded 18 rallies by Trump likely led to more than 30,000 confirmed cases and 700 deaths.

The study analysed 18 rallies by Trump held between June 20 and September 22 this year. (Representative photo: Reuters)

More than 30,000 confirmed cases of coronavirus and over 700 deaths may have been resulted due to about 18 election rallies held by US President Donald Trump, a study has revealed.

Communities paid a high price for Trump rallies: Study

The study by Stanford University titled ‘The Effects of Large Group Meetings on the Spread of COVID-19: The Case of Trump Rallies’, stresses that the communities where the Trump rallies took place “paid a high price in terms of disease and death.”

The research concludes that 18 rallies by Trump held between June 20 and September 22 "ultimately resulted in more than 30,000 incremental confirmed cases of Covid-19” and “likely led to more than 700 deaths”, which may not necessarily have been among attendees, news agency PTI reported.

US President Donald Trump gestures during a campaign event at Smith Reynolds Regional Airport in Winston-Salem, North Carolina, U.S., September 8, 2020. (Photo: Reuters)

“Our analysis strongly supports the warnings and recommendations of public health officials concerning the risk of Covid-19 transmission at large group gatherings, particularly when the degree of compliance with guidelines concerning the use of masks and social distancing is low. The communities in which Trump rallies took place paid a high price in terms of disease and death,” the researchers said in the study.

Joe Biden slams Trump over the study

Reacting to a Twitter post on the study, Democratic Presidential nominee Joe Biden said "President Trump doesn’t care about you. He doesn’t even care about his own supporters."

The study, released Friday, noted that more than 8.7 million Americans have contracted Covid-19, resulting in more than 225,000 deaths.

Gatherings serve as 'superspreader events': Study

The Centers for Disease Control and Prevention (CDC) has advised that large in-person events, particularly in settings where participants do not wear masks or practice social distancing, pose a substantial risk of further contagion, reported PTI.

“There is reason to fear that such gatherings can serve as ‘superspreader events’, severely undermining efforts to control the pandemic,” the study said.

Researchers said the purpose of the study is to shed light on these issues by studying the impact of election rallies held by Trump’s campaign between June 20 and September 30.

Features of Trump rallies

The research says that 'Trump rallies have several distinguishing features that lend themselves to this inquiry'. Following are the features that the study highlights:

  1. Attendees at Trump rallies numbered in the thousands and sometimes in the tens of thousands.
  2. The set of major Trump campaign events is easily identified. "We know whether and when the Trump campaign held a rally in each county. This property allows us to distinguish between “treated” and “untreated” counties," the study said.
  3. The events occurred on identifiable days. The rallies neither recurred within a given county nor stretched across several days. "This feature allows us to evaluate the effects of individual gatherings," said Trump.
  4. Researchers noted that the rallies were not geographically ubiquitous
  5. The degree of compliance with guidelines concerning the use of masks and social distancing was low “in part because the Trump campaign downplayed the risk of infection.

This feature heightens the risk that a rally could become a “superspreader event," the study said.

The researchers said that to capture the effects of subsequent contagion within the pertinent communities, their analysis encompasses up to 10 post-rally weeks for each event, PTI reported.

“Our method is based on a collection of regression models, one for each event, that capture the relationships between post-event outcomes and pre-event characteristics, including demographics and the trajectory of Covid-19 cases, in similar counties.”

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