Puerto Rico gov: ‘There will be hell to pay’ if data held back on hurricane deaths
Puerto Rico Gov. Ricardo Rosselló said on Thursday that there would be “hell to pay” if territory officials withheld key statistics about the death toll from Hurricane Maria.
Rosselló’s comments came two days after a Harvard University study published in the New England Journal of Medicine pegged the death toll from the hurricane and its immediate aftermath at 4,645 – far higher than the official estimate of 64.
The Harvard study noted that Puerto Rican officials have declined to release mortality statistics that could shed more light on the lives lost after Maria, which ravaged Puerto Rico and other Caribbean islands in September.
“If it’s true, Anderson, there will be hell to pay, because I really want this to be very transparent,” Rosselló told CNN’s Anderson Cooper in an interview. “I want the truth to come out. That’s the bottom line. And I want us to learn from this tragedy.”
Maria caused some $90 billion in damage, making it the third costliest tropical cyclone in the U.S. since 1900, according to the Harvard study.
Rosselló said he was “shocked” to hear that territory officials had withheld the data, noting that he had signed an executive order intended to facilitate the release of the information.
The Puerto Rican government has also hired George Washington University to conduct an assessment of the death toll from Maria. The results of that study were due out in the spring, but have since been delayed.
Rosselló acknowledged that “the best data was not available” to researchers, and said that was why the George Washington University study had taken longer than expected.
“We expected to have a phase one analysis here by May 22, but of course, data has been hard to come by with respect to that,” he said.
The Harvard researchers came up with their death toll estimate for the months after the hurricane hit in September 2017 by surveying thousands of households across the island.
The researchers then produced a post-hurricane mortality estimate and compared it to the official mortality rates for the same time period the previous year.