US to renew Iraq sanctions waiver for 45 days

The US has signaled to Iraq it’s willingness to extend sanctions waivers enabling the country to continue importing vital Iranian gas and electricity imports. (File/AP)
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Updated 12 February 2020

US to renew Iraq sanctions waiver for 45 days

  • The US slapped tough sanctions on the Iranian energy sector in late 2018 and initially granted Iraq a 45-day waiver
  • Baghdad relies on gas and electricity imports from its neighbor Tehran to supply about a third of its power grid

BAGHDAD: The United States will grant Iraq a brief 45-day extension to a waiver allowing Baghdad to continue importing Iranian gas despite American sanctions, an Iraqi official told AFP on Wednesday.
The US slapped tough sanctions on the Iranian energy sector in late 2018 and initially granted Iraq a 45-day waiver before repeatedly extending it for 90 or 120 days.
Baghdad relies on gas and electricity imports from its neighbor Tehran to supply about a third of its power grid, crippled by years of conflict and poor maintenance.
“The extension this time will be for just 45 days, with some strict conditions,” the senior Iraqi official said.
The two countries were still in talks over what exactly those conditions were.
Washington has repeatedly insisted Iraq wean itself off Iran by partnering with American companies to capture natural gas to use for its power plants and to improve transmission of electricity into homes to reduce waste.
Iraq signed a memorandum of understanding with US powerhouse General Electric last year and has been in talks with other energy firms, but contracts have not yet been signed.
Both American and Iraqi officials told AFP the US was frustrated with Baghdad’s slow progress.
The latest waiver was set to expire this week but the US did not want to create additional pressure on prime minister-designate Mohammad Allawi, who is trying to form a new cabinet at a time of turmoil in Iraq.
“Washington didn’t want to hamstring Allawi just as he was starting out,” the official said.
Failing to renew the waiver could have exposed Iraq to secondary sanctions for dealing with Iran’s energy sector and central bank, both blacklisted by the US.
The waiver has allowed Iraq to continue importing about 1,400 megawatts of electricity and 28 million cubic meters (988 million cubic feet) of Iranian gas over the last 15 months.
Baghdad pays for the imports by depositing Iraqi dinars into an account at the state-owned Trade Bank of Iraq, which Iran is technically allowed to use to purchase non-sanctioned goods.
A few payments have been made but Iran had been unable to access the funds due to ongoing technical disputes.
TBI chairman Faisal Al-Haimus told AFP last month that if the waiver was not renewed, his bank would be forced to stop processing the payments.


Man vs. machine in bid to beat virus

Updated 20 February 2020

Man vs. machine in bid to beat virus

  • Human and artificial intelligence are racing ahead to detect and control outbreaks of infectious disease

BOSTON: Did an artificial-intelligence system beat human doctors in warning the world of a severe coronavirus outbreak in China?

In a narrow sense, yes. But what the humans lacked in sheer speed, they more than made up in finesse.

Early warnings of disease outbreaks can help people and governments to save lives. In the final days of 2019, an AI system in Boston sent out the first global alert about a new viral outbreak in China. But it took human intelligence to recognize the significance of the outbreak and then awaken response from the public health community.

What’s more, the mere mortals produced a similar alert only a half-hour behind the AI systems.

For now, AI-powered disease-alert systems can still resemble car alarms — easily triggered and sometimes ignored. A network of medical experts and sleuths must still do the hard work of sifting through rumors to piece together the fuller picture. It is difficult to say what future AI systems, powered by ever larger datasets on outbreaks, may be able to accomplish.

The first public alert outside China about the novel coronavirus came on Dec. 30 from the automated HealthMap system at Boston Children’s Hospital. At 11:12 p.m. local time, HealthMap sent an alert about unidentified pneumonia cases in the Chinese city of Wuhan. The system, which scans online news and social media reports, ranked the alert’s seriousness as only 3 out of 5. It took days for HealthMap researchers to recognize its importance.

Four hours before the HealthMap notice, New York epidemiologist Marjorie Pollack had already started working on her own public alert, spurred by a growing sense of dread after reading a personal email she received that evening.

“This is being passed around the internet here,” wrote her contact, who linked to a post on the Chinese social media forum Pincong. The post discussed a Wuhan health agency notice and read in part: “Unexplained pneumonia???”

Pollack, deputy editor of the volunteer-led Program for Monitoring Emerging Diseases, known as ProMed, quickly mobilized a team to look into it. ProMed’s more detailed report went out about 30 minutes after the terse HealthMap alert.

Early warning systems that scansocial media, online news articles and government reports for signs of infectious disease outbreaks help inform global agencies such as the World Health Organization — giving international experts a head start when local bureaucratic hurdles and language barriers might otherwise get in the way.

Some systems, including ProMed, rely on human expertise. Others are partly or completely automated.

“These tools can help hold feet to the fire for government agencies,” said John Brownstein, who runs the HealthMap system as chief innovation officer at Boston Children’s Hospital. “It forces people to be more open.”

The last 48 hours of 2019 were a critical time for understanding the new virus and its significance. Earlier on Dec. 30, Wuhan Central Hospital doctor Li Wenliang warned his former classmates about the virus in a social media group — a move that led local authorities to summon him for questioning several hours later.

Li, who died Feb. 7 after contracting the virus, told The New York Times that it would have been better if officials had disclosed information about the epidemic earlier. “There should be more openness and transparency,” he said.

ProMed reports are often incorporated into other outbreak warning systems. including those run by the World Health Organization, the Canadian government and the Toronto startup BlueDot. WHO also pools data from HealthMap and other sources.

Computer systems that scan online reports for information about disease outbreaks rely on natural language processing, the same branch of artificial intelligence that helps answer questions posed to a search engine or digital voice assistant.

But the algorithms can only be as effective as the data they are scouring, said Nita Madhav, CEO of San Francisco-based disease monitoring firm Metabiota, which first
notified its clients about the outbreak in early January.

Madhav said that inconsistency in how different agencies report medical data can stymie algorithms. The text-scanning programs extract keywords from online text, but may fumble when organizations variously report new virus cases, cumulative virus cases, or new cases in a given time interval. The potential for confusion means there is almost always still a person involved in reviewing the data.

“There’s still a bit of human in the loop,” Madhav said.

Andrew Beam, a Harvard University epidemiologist, said that scanning online reports for key words can help reveal trends, but the accuracy depends on the quality of the data. He also notes that these techniques are not so novel.

“There is an art to intelligently scraping web sites,” Beam said. “But it’s also Google’s core technology since the 1990s.”

Google itself started its own Flu Trends service to detect outbreaks in 2008 by looking for patterns in search queries about flu symptoms. Experts criticized it for overestimating flu prevalence. Google shut down the website in 2015 and handed its technology to nonprofit organizations such as HealthMap to use Google data to build their own models.

Google is now working with Brownstein’s team on a similar web-based approach for tracking the geographical spread of the tick-borne Lyme disease.

Scientists are also using big data to model possible routes of early disease transmission.