Science’s COVID-19 reporting is supported by the Pulitzer Center.

As cases of coronavirus disease 2019 (COVID-19) ballooned last month, people in Europe and North America scrambled to get their hands on surgical masks to protect themselves. Health officials jumped in to discourage them, worried about the limited supply of masks for health care personnel. “Seriously people-STOP BUYING MASKS!” began a 29 February tweet from U.S. Surgeon General Jerome Adams. The World Health Organization and U.S. Centers for Disease Control and Prevention (CDC) have both said that only people with COVID-19 symptoms and those caring for them should wear masks.

But some health experts, including the director of the Chinese Center for Disease Control and Prevention, think that’s a mistake. Health authorities in parts of Asia have encouraged all citizens to wear masks in public to prevent the spread of the virus, regardless of whether they have symptoms. And the Czech Republic took the uncommon step last week of making nose and mouth coverings mandatory in public spaces, prompting a grassroots drive to hand make masks.

Science’s COVID-19 reporting is supported by the Pulitzer Center.

Chinese scientists at the front of that country’s outbreak of coronavirus disease 2019 (COVID-19) have not been particularly accessible to foreign media. Many have been overwhelmed trying to understand their epidemic and combat it, and responding to media requests, especially from journalists outside of China, has not been a top priority.

Science has tried to interview George Gao, director-general of the Chinese Center for Disease Control and Prevention (CDC), for 2 months. Last week he responded.

Science’s COVID-19 reporting is supported by the Pulitzer Center.

COVID-19, caused by the new pandemic coronavirus, is strangely—and tragically—selective. Only some infected people get sick, and although most of the critically ill are elderly or have complicating problems such as heart disease, some killed by the disease are previously healthy and even relatively young. Researchers are now gearing up to scour the patients’ genomes for DNA variations that explain this mystery. The findings could be used to identify those most at risk of serious illness and those who might be protected, and they might also guide the search for new treatments.

The projects range from ongoing studies with DNA for many thousands of participants, some now getting infected with the coronavirus, to new efforts that are collecting DNA from COVID-19 patients in hard-hit places such as Italy. The goal is to compare the DNA of people who have serious cases of COVID-19 (which stands for coronavirus disease 2019)—but no underlying disease like diabetes, heart or lung disease—with those with mild or no disease. “We see huge differences in clinical outcomes and across countries. How much of that is explained by genetic susceptibility is a very open question,” says geneticist Andrea Ganna of the University of Helsinki’s Institute for Molecular Medicine Finland (FIMM).

The University of Rochester (U of R) is paying $9.4 million to settle a high-profile sexual harassment lawsuit that divided an esteemed department, landed two of the plaintiffs on the cover of Time magazine, and was closely watched by other institutions of higher education. The plaintiffs announced the settlement today as they issued a joint statement with the university.

The lawsuit, filed in December 2017 by nine now-former professors and students in U of R’s Department of Brain and Cognitive Sciences, alleged that the university retaliated against and defamed them after they alleged sexual harassment by linguist Florian Jaeger. Three plaintiffs also alleged that Jaeger created a sexually hostile environment. (The university has never found Jaeger guilty of sexual harassment.)

The settlement comes 7 months after the federal judge in the case upheld the legal validity, in whole or in part, of 16 of the plaintiffs’ 17 claims in the lawsuit, clearing the way for a court battle where they would have had to prove the claims were factually accurate. The university had moved to dismiss all the claims.

Roxane Silver studies the health effects of traumatic life events. So it was a no-brainer for the social psychologist at the University of California, Irvine, to ask the National Science Foundation (NSF) to fund a study of how the coronavirus disease 2019 (COVID-19) pandemic would affect the well-being of Americans.

Fortunately for Silver, NSF has a mechanism for fast-tracking time-sensitive ideas like hers. It’s called Rapid Response Research (RAPID). Over the past 3 decades, Silver has used the mechanism seven times to field surveys immediately after mass shootings, hurricanes, and the September 2001 terrorist attacks. On 6 March she sent in her proposal, and 1 week later NSF awarded her $200,000 to begin a study on the long-term impacts of one’s initial response to the pandemic.

Silver is one of a dozen investigators to date who have received RAPID awards relating to COVID-19. And this week, Congress gave NSF an extra $75 million to spend on research that will help “prevent, prepare for, and respond” to the novel coronavirus.

Every day, scientists post dozens of preprints—studies that have not been peer reviewed—on public servers such as bioRxiv. Preprints allow scientists access to cutting-edge findings faster than when authors submit their findings to traditional journals, which often take months to complete reviews.

But what preprints gain in speed, they may lose in reliability and credibility, critics say, because peer review can finger mistakes and deficiencies. That’s a worry especially for findings about medical treatments that nonscientists might misinterpret, possibly at risk to their health. The coronavirus pandemic has only heightened those concerns.

But peer review doesn’t appear to give a big quality boost to preprints, a recent study concludes—at least by one measure. The study, itself a preprint posted 19 March on bioRxiv, compared 56 preprints posted on bioRxiv in 2016 with the peer-reviewed versions later published in journals. Many were studies of genetics and neuroscience. In particular, the researchers examined whether the final papers reported more key details of the research, such as the types of reagents and statistical methods used, than the preprint.

When President Donald Trump recently touted the common malaria treatments hydroxychloroquine and chloroquine as potential remedies for coronavirus disease 2019 (COVID-19), he ignited unprecedented demand for the drugs—and set scientists’ teeth on edge. Although the World Health Organization (WHO) agrees the compounds are worth testing more fully on the pandemic coronavirus, few drug or infectious disease experts—not even the president’s own advisers—share his optimism that the drugs could become “one of the biggest game changers in the history of medicine,” as he tweeted. And many are critical of the small French clinical study of just 42 patients that seems to have touched off most of the excitement.

“The president was talking about hope,” Anthony Fauci, director of National Institute of Allergy and Infectious Diseases, said diplomatically at one of the White House briefings where Trump praised the drugs’ potential.

Others are less diplomatic. Darren Dahly, a co-author of one of several critiques of the initial study and a principal statistician at the University College Cork School of Public Health, said it would be “egregious” to recommend treatments for millions of people based on such a small trial, regardless of its quality. “This is insane!” tweeted Gaetan Burgio, an Australian National University expert on drug resistance, noting what he sees as lapses in the 6-day trial, including inconsistent testing of virus levels in the patients.

For weeks, Russia seemed to have dodged a bullet. As coronavirus disease 2019 (COVID-19) raged just across the border in China, Russia was virtually untouched, reporting just seven confirmed infections as recently as 10 March. Since then, the number has risen fast: Russia has now reported 840 infections, about two-thirds of them in the Moscow region.

Some health care providers have questioned whether Russia truly kept the novel coronavirus at bay. Anastasia Vasilyeva, head of Russia’s Alliance of Doctors trade union, has pointed out that pneumonia cases in Moscow spiked in January—they were 37% higher than in January 2019, according to Rosstat, Russia’s statistics agency. She asserts that COVID-19 must have accounted for at least part of the increase. Others attribute the increase to a greater number of pneumonia patients, anxious about the new coronavirus, seeking treatment.

With COVID-19 cases now indisputably on the rise in Russia, authorities are moving fast to ramp up detection and hospital bed capacity. Russia’s federal coronavirus coordination council says 193,000 tests based on the polymerase chain reaction (PCR) have been done to date. Swabs initially had to be shipped to Siberia for analysis at the State Research Center of Virology and Biotechnology VECTOR. Russia’s Federal Service for the Oversight of Consumer Protection and Welfare (Rospotrebnadzor)—the country’s analog of the U.S. Centers for Disease Control and Prevention—has just expanded testing to its regional laboratories and the Anti-Plague Research Institute.

Jacco Wallinga’s computer simulations are about to face a high-stakes reality check. Wallinga is a mathematician and the chief epidemic modeler at the National Institute for Public Health and the Environment (RIVM), which is advising the Dutch government on what actions, such as closing schools and businesses, will help control the spread of the novel coronavirus in the country.

The Netherlands has so far chosen a softer set of measures than most Western European countries; it was late to close its schools and restaurants and hasn’t ordered a full lockdown. In a 16 March speech, Prime Minister Mark Rutte rejected “working endlessly to contain the virus” and “shutting down the country completely.” Instead, he opted for “controlled spread” of the virus among the groups least at risk of severe illness while making sure the health system isn’t swamped with COVID-19 patients. He called on the public to respect RIVM’s expertise on how to thread that needle. Wallinga’s models predict that the number of infected people needing hospitalization, his most important metric, will taper off by the end of the week. But if the models are wrong, the demand for intensive care beds could outstrip supply, as it has, tragically, in Italy and Spain.

COVID-19 isn’t the first infectious disease scientists have modeled—Ebola and Zika are recent examples—but never has so much depended on their work. Entire cities and countries have been locked down based on hastily done forecasts that often haven’t been peer reviewed. “It has suddenly become very visible how much the response to infectious diseases is based on models,” Wallinga says. For the modelers, “it’s a huge responsibility,” says epidemiologist Caitlin Rivers of the Johns Hopkins University Center for Health Security, who co-authored a report about the future of outbreak modeling in the United States that her center released yesterday.

The $2 trillion stimulus package that the U.S. Senate is working to approve today is aimed at helping the country cope with the massive impact of the coronavirus pandemic. But it also includes at least $1.25 billion for federal research agencies to support scientists trying to better understand coronavirus disease 2019 (COVID-19). In addition, it extends a financial hand to universities that have shut down because of the pandemic, some of which could go to support research that has been disrupted.

Details of the legislation have yet to emerge after Republican and Democratic leaders in Congress worked out their differences in negotiations that ran into the early morning. But a 22-page summary released by the Senate Appropriations Committee this morning contains these highlights: