Amber Nicole Thurman’s death from an infection in 2022 is believed to be the first confirmed maternal fatality linked to post-Roe bans.
Reproductive justice advocates have been warning for more than two years that the end of Roe v. Wade would lead to surge in maternal mortality among patients denied abortion care—and that the increase was likely to be greatest among low-income women of color. Now, a new report by ProPublica has uncovered the first such verified death. A 28-year-old medical assistant and Black single mother in Georgia died from a severe infection after a hospital delayed a routine medical procedure that had been outlawed under that state’s six-week abortion ban.
Amber Nicole Thurman’s death, in August 2022, was officially deemed “preventable” by a state committee tasked with reviewing pregnancy-related deaths. Thurman’s case is the first time a preventable abortion-related death has come to public attention since the Supreme Court overturned Roe, ProPublica’s Kavitha Surana reported.
Now, “we actually have the substantiated proof of something we already knew—that abortion bans kill people,” said Mini Timmaraju, president of the abortion-rights group Reproductive Freedom for All, during a call with media. “It cannot go on.”
I don’t see this being examined in any objective and scientific way.
What would be scientific would be to allow women and their doctors to evaluate those risks together and make the decision without Republican lawmakers continuing to try to insert themselves in between. Sorry if that’s too emotional.
I’m also quite sure there are scientific journal papers that cover this. I feel like you are expecting an awful lot from an article about a specific event on politico.
It is literally the highlighted quote in the article: “we actually have the substantiated proof of something we already knew—that abortion bans kill people.”
For someone who complains about others not being objective, I find it unexpected that this is what you would quote to support this assertion by you:
using a sample size of 1 as evidence of an epidemic
