vox--2020-08-05--Trump still thinks schools should reopen because Covid-19 “will go away.” Really.

Mere weeks after a number of outlets remarked on his “ new tone ” about the coronavirus , President Donald Trump fully reverted to form during a lengthy interview on Wednesday ’ s installment of Fox & Friends .
Echoing widely derided , unscientific comments he made during the early days of the outbreak in January and February , Trump insisted schools should open for in-person instruction because the pandemic “ is going to go away.
” “ My view is the schools should open , ” Trump said .
“ This thing is going away .
It will go @ @ @ @ @ @ @ my view is that schools should be open.
” Suffice it to say that public health experts do not think wishful thinking will be enough to bring Covid-19 under control in the US .
Nor is it the case that the virus is currently “ going away ” — the more than 51,000 new cases reported in the country on Tuesday represent a slight decline from some particularly grim days late last month , when daily new cases exceeded 70,000 , but is still far above the daily case numbers in May and @ @ @ @ @ @ @ , Trump made another stunningly irresponsible statement , claiming children are “ almost immune ” from Covid-19 .
( There ’ s a lot we still don ’ t know about how the disease affects children , but even if their symptoms are generally milder , they can certainly still catch and transmit the disease . )
Trump doesn ’ t seem to have many qualms about letting the pandemic rage on in hopes of boosting the economy ahead of November ’ s election , so perhaps it ’ s not surprising that @ @ @ @ @ @ @ , and other measures taken by state and local officials in response to the pandemic as nothing more than conspiracies to damage him politically .
“ We ’ re set to rock and roll , but the big problem we have is Democrats don ’ t want to open their schools , because they think it ’ s going to hurt the election for the Republicans , ” said Trump — seemingly oblivious to the reality that the problem is the pandemic , not efforts to save lives while responding to it .
@ @ @ @ @ @ @ Trump went to desperate lengths to make it seem as though the US isn ’ t doing that badly with regard to the coronavirus when compared to other countries .
“ You look at Spain is in a big , big second wave .
Italy has a wave going .
A lot of countries are having a [ second wave ] — but nobody ever talks about that .
We have done an incredible job in this country , an incredible job , ” Trump said .
But while new cases in Spain @ @ @ @ @ @ @ last month to 5,760 on Tuesday , that pales in comparison to the 50,000-plus a day that has been the norm in the US for the past month ( Spain reported 26 coronavirus deaths on Tuesday , compared to 1,265 in the US ) .
Despite Trump ’ s statements , the dire situation in the US is apples and oranges compared to Europe .
Trump is barely trying to conceal his efforts to dismantle the Post Office and use the White House as a political prop As is usually the case when @ @ @ @ @ @ @ not named Chris Wallace , the president ’ s misleading and irresponsible claims were met with no pushback .
But the friendly nature of the questioning didn ’ t prevent him from making a number of newsworthy remarks that weren ’ t directly about the coronavirus .
Asked whether he ’ s intentionally sabotaging the Post Office to create difficulties for voters hoping to cast their ballots by mail this November , Trump not only didn ’ t deny it but claimed “ the Postal Service for 40 years has had big problems @ @ @ @ @ @ @ ” to handle a high volume of mailed ballots .
( The Postal Service said on Monday it actually has “ ample capacity ” to handle it . )
Trump ’ s handpicked postmaster general — Louis DeJoy , a Trump megadonor — has overseen changes to the USPS , including the end of overtime pay , that have resulted in service slowdowns .
Coming as they do just weeks before the November ’ s election , elections experts worry that Trump is trying to make his claims that widespread mail-in voting will @ @ @ @ @ @ @ a self-fulfilling prophecy .
Of course , with the coronavirus pandemic making it risky to physically go to polling places , Americans have good reason to want to vote by mail .
Trump , however , indicated on Fox & Friends that he ’ s not particularly worried his efforts to make mail-in voting as burdensome as possible will disenfranchise seniors and other at-risk groups because he thinks the country “ will probably be in very good shape ” with regard to the coronavirus by then — another claim at odds with public @ @ @ @ @ @ @ have warned that this fall will be a very difficult time for public health in the US .
While Trump seems to think the coronavirus isn ’ t all it ’ s cracked up to be , it ’ s a big enough deal to disrupt plans for the Republican National Convention .
With his goal of delivering his big RNC speech later this month before a packed house in North Carolina or Florida now off the table because of the pandemic , Trump told Fox & Friends he ’ s strongly leaning @ @ @ @ @ @ @ .
“ We ’ re thinking about doing it from the White House because there ’ s no movement — it ’ s easy — and I think it ’ s a beautiful setting , ” Trump said .
Citizens for Responsibility and Ethics in Washington ( CREW ) wasted no time responding to that news by characterizing Trump ’ s new plan as an egregious abuse of power .
“ President Trump accepting the GOP nomination from the White House would be completely unprecedented , ” CREW communications director Jordan Libowitz told @ @ @ @ @ @ @ a political speech of this magnitude and visibility on the White House grounds creates the appearance that it ’ s a government-sanctioned event , something multiple laws were written to avoid.
” Fox & Friends hosts , however , didn ’ t press the issue .
Nor did they challenge Trump minutes later when he pushed a baseless and anti-Semitic conspiracy theory about antifa , saying , “ You have Democrats funding them .
They say Soros and they say other people.
” Trump may have wanted a pick-me-up after his disastrous Axios @ @ @ @ @ @ @ News appearance stood in stark contrast with the grilling he received from Axios ’ s Jonathan Swan in an interview that aired Sunday , there were a number of instances where Trump appeared flummoxed by total softballs .
Asked to detail his second-term agenda , Trump — who has repeatedly struggled with this question during interviews on Sean Hannity ’ s show — still couldn ’ t name a single specific thing , and instead started talking about how “ we had the greatest economy in the history of the world ” before @ @ @ @ @ @ @ close out the interview , host Ainsley Earhardt asked Trump what he can do to heal racial strife in the country .
Trump responded by ranting about unemployment rates and his poll numbers .
Trump ’ s hour-long appearances on Fox & Friends often have the feel of public therapy sessions where he can blow off steam , brag about overinflated achievements , and rail against his perceived enemies .
The picture that emerged on Wednesday was one of a president who is remarkably out of touch with what ’ s actually going @ @ @ @ @ @ @ views a pandemic that has now killed nearly 160,000 Americans as a personal affront to his waning reelection hopes .
Every day at Vox , we aim to answer your most important questions and provide you , and our audience around the world , with information that has the power to save lives .
Our mission has never been more vital than it is in this moment : to empower you through understanding .
Vox ’ s work is reaching more people than ever , but our distinctive brand of explanatory journalism takes @ @ @ @ @ @ @ an economic downturn .
Your financial contribution will not constitute a donation , but it will enable our staff to continue to offer free articles , videos , and podcasts at the quality and volume that this moment requires .
Please consider making a contribution to Vox today .

Mere weeks after a number of outlets remarked on his “new tone” about the coronavirus, President Donald Trump fully reverted to form during a lengthy interview on Wednesday’s installment of Fox & Friends.
Echoing widely derided, unscientific comments he made during the early days of the outbreak in January and February, Trump insisted schools should open for in-person instruction because the pandemic “is going to go away.”
“My view is the schools should open,” Trump said. “This thing is going away. It will go away like things go away, and my view is that schools should be open.”
Suffice it to say that public health experts do not think wishful thinking will be enough to bring Covid-19 under control in the US. Nor is it the case that the virus is currently “going away” — the more than 51,000 new cases reported in the country on Tuesday represent a slight decline from some particularly grim days late last month, when daily new cases exceeded 70,000, but is still far above the daily case numbers in May and June.
Yet in his next breath, Trump made another stunningly irresponsible statement, claiming children are “almost immune” from Covid-19. (There’s a lot we still don’t know about how the disease affects children, but even if their symptoms are generally milder, they can certainly still catch and transmit the disease.)
Trump pushes the claim that children are "almost immune" to make his case: "My view is the school's should open. This thing's going away. It will go away like things go away."
So this morning he's said "this thing's going away" and "it will go by." This is where we're at. pic.twitter.com/7KEICeU77T — The Recount (@therecount) August 5, 2020
Trump doesn’t seem to have many qualms about letting the pandemic rage on in hopes of boosting the economy ahead of November’s election, so perhaps it’s not surprising that he views school closures, mask mandates, and other measures taken by state and local officials in response to the pandemic as nothing more than conspiracies to damage him politically.
“We’re set to rock and roll, but the big problem we have is Democrats don’t want to open their schools, because they think it’s going to hurt the election for the Republicans,” said Trump — seemingly oblivious to the reality that the problem is the pandemic, not efforts to save lives while responding to it.
"We're set to rock & roll, but the big problem we have is Democrats don't want to open their schools, b/c they think it's going to hurt the election for the Republicans." - Trump still thinks mask mandates & schools closures are Dem conspiracies, not necessary public health steps pic.twitter.com/56WfTxF978 — Aaron Rupar (@atrupar) August 5, 2020
During another part of the interview, Trump went to desperate lengths to make it seem as though the US isn’t doing that badly with regard to the coronavirus when compared to other countries.
“You look at Spain is in a big, big second wave. Italy has a wave going. A lot of countries are having a [second wave] — but nobody ever talks about that. We have done an incredible job in this country, an incredible job,” Trump said.
"Italy has a wave going. A lot of countries are having a [second wave] -- but nobody ever talks about that. We have done an incredible job in this country, an incredible job." -- Italy reported 190 new Covid cases on Tuesday. The US had 51,185.
The outbreaks are not comparable. pic.twitter.com/ZzwCePBqkE — Aaron Rupar (@atrupar) August 5, 2020
But while new cases in Spain have spiked from under 300 a day last month to 5,760 on Tuesday, that pales in comparison to the 50,000-plus a day that has been the norm in the US for the past month (Spain reported 26 coronavirus deaths on Tuesday, compared to 1,265 in the US). Despite Trump’s statements, the dire situation in the US is apples and oranges compared to Europe.
Trump is barely trying to conceal his efforts to dismantle the Post Office and use the White House as a political prop
As is usually the case when Trump is interviewed by Fox News hosts not named Chris Wallace, the president’s misleading and irresponsible claims were met with no pushback. But the friendly nature of the questioning didn’t prevent him from making a number of newsworthy remarks that weren’t directly about the coronavirus.
Asked whether he’s intentionally sabotaging the Post Office to create difficulties for voters hoping to cast their ballots by mail this November, Trump not only didn’t deny it but claimed “the Postal Service for 40 years has had big problems, and they’re not equipped” to handle a high volume of mailed ballots. (The Postal Service said on Monday it actually has “ample capacity” to handle it.)
Asked on Fox & Friends about Hillary Clinton accusing him of sabotaging the Postal Service, Trump immediately pivots to bashing Clinton and never denies that that's what he's up to pic.twitter.com/zlEMwXxquw — Aaron Rupar (@atrupar) August 5, 2020
Trump’s handpicked postmaster general — Louis DeJoy, a Trump megadonor — has overseen changes to the USPS, including the end of overtime pay, that have resulted in service slowdowns. Coming as they do just weeks before the November’s election, elections experts worry that Trump is trying to make his claims that widespread mail-in voting will result in a “CORRUPT ELECTION” a self-fulfilling prophecy.
Of course, with the coronavirus pandemic making it risky to physically go to polling places, Americans have good reason to want to vote by mail. Trump, however, indicated on Fox & Friends that he’s not particularly worried his efforts to make mail-in voting as burdensome as possible will disenfranchise seniors and other at-risk groups because he thinks the country “will probably be in very good shape” with regard to the coronavirus by then — another claim at odds with public health experts from his own government who have warned that this fall will be a very difficult time for public health in the US.
"By the time we get to [Election Day], we will probably be in very good shape" -- Trump suggests the coronavirus won't be an issue preventing seniors from physically going to the polls in November pic.twitter.com/NOgENfPCdx — Aaron Rupar (@atrupar) August 5, 2020
While Trump seems to think the coronavirus isn’t all it’s cracked up to be, it’s a big enough deal to disrupt plans for the Republican National Convention. With his goal of delivering his big RNC speech later this month before a packed house in North Carolina or Florida now off the table because of the pandemic, Trump told Fox & Friends he’s strongly leaning toward doing it at the White House.
“We’re thinking about doing it from the White House because there’s no movement — it’s easy — and I think it’s a beautiful setting,” Trump said.
Citizens for Responsibility and Ethics in Washington (CREW) wasted no time responding to that news by characterizing Trump’s new plan as an egregious abuse of power.
“President Trump accepting the GOP nomination from the White House would be completely unprecedented,” CREW communications director Jordan Libowitz told Vox in an email. “Giving a political speech of this magnitude and visibility on the White House grounds creates the appearance that it’s a government-sanctioned event, something multiple laws were written to avoid.”
Fox & Friends hosts, however, didn’t press the issue. Nor did they challenge Trump minutes later when he pushed a baseless and anti-Semitic conspiracy theory about antifa, saying, “You have Democrats funding them. They say Soros and they say other people.”
Trump may have wanted a pick-me-up after his disastrous Axios showing
While Trump’s latest Fox News appearance stood in stark contrast with the grilling he received from Axios’s Jonathan Swan in an interview that aired Sunday, there were a number of instances where Trump appeared flummoxed by total softballs.
Asked to detail his second-term agenda, Trump — who has repeatedly struggled with this question during interviews on Sean Hannity’s show — still couldn’t name a single specific thing, and instead started talking about how “we had the greatest economy in the history of the world” before the coronavirus hit.
Unbelievable -- Trump still can't name a single specific thing he wants to accomplish in a second term pic.twitter.com/M5P24zsLI8 — Aaron Rupar (@atrupar) August 5, 2020
Then, to close out the interview, host Ainsley Earhardt asked Trump what he can do to heal racial strife in the country. Trump responded by ranting about unemployment rates and his poll numbers.
Asked as the interview winds down what he can do to heal racial strife in the country, Trump immediately starts ranting about the unemployment rate and his poll numbers. Beyond parody. pic.twitter.com/5PXoKdfueQ — Aaron Rupar (@atrupar) August 5, 2020
Trump’s hour-long appearances on Fox & Friends often have the feel of public therapy sessions where he can blow off steam, brag about overinflated achievements, and rail against his perceived enemies. The picture that emerged on Wednesday was one of a president who is remarkably out of touch with what’s actually going on in the country — one who views a pandemic that has now killed nearly 160,000 Americans as a personal affront to his waning reelection hopes.


vox--2020-08-05--How bad is your state’s Covid-19 outbreak?

The US is now in the middle of what can only be described as a national Covid-19 epidemic , with cases across the country rising at alarming rates in recent weeks .
Public health experts look at a few markers to determine how bad things are in each state : the number of daily new cases ; the infection rate , which can show how likely the virus is to spread ; the percent of tests that come back positive , which should be low in a state with sufficient testing ; and the percent of hospital beds that are @ @ @ @ @ @ @ Vox analysis indicates the vast majority of states report alarming trends across all four benchmarks for coronavirus outbreaks .
Most states still report a high — sometimes very high — number of daily new Covid-19 cases .
Most still have high infection rates .
Most still have test positive rates that are too high , indicating they don ’ t have enough tests to track and contain the scope of their outbreaks .
( The US overall has seen a plateau in new cases in recent days , but at a level much @ @ @ @ @ @ @ have hospitals with intensive care units that are too packed .
Across these benchmarks , only one state — New York — fares well on all four metrics , meaning their epidemics are relatively under control for now .
Only the Northeast currently seems to be doing better with the resurgence of Covid-19 cases .
But that region , particularly New York City , was hit hard by the initial wave of the Covid-19 pandemic , with New York reporting the highest overall death toll for the country so far .
The current @ @ @ @ @ @ @ Florida , is the result of the public and its leaders collectively letting their guard down .
States , with the support of President Donald Trump , moved to reopen — often before they saw sizable drops in daily new Covid-19 cases , and at times so quickly they didn ’ t have time to see if each phase of their reopening was leading to too many more cases .
The public embraced the reopenings , going out and often not adhering to recommended precautions like physical distancing and wearing a mask .
@ @ @ @ @ @ @ government withdrawal and public complacency — that experts have cited again and again in explaining why states are now seeing a resurgence in Covid-19 cases .
“ It ’ s a situation that didn ’ t have to be , ” Jaime Slaughter-Acey , an epidemiologist at the University of Minnesota , told me .
“ For almost three months , you had opportunities to be proactive with respect to mitigating the Covid-19 pandemic and to help normalize culture to adopt practices that would stem the tide of transmissions as well as the @ @ @ @ @ @ @ was not prioritized over the economy.
” The effects are felt not just in terms of more infections , critical illnesses , new chronic conditions , and deaths , but in the long-term financial impact as the economy starts shutting down again , people refuse to go out , and businesses resist reopening during a pandemic .
“ Dead people don ’ t shop .
They don ’ t spend money .
They don ’ t invest in things , ” Jade Pagkas-Bather , an infectious diseases expert and doctor at the University @ @ @ @ @ @ @ When you fail to invest in the health of your population , then there are longitudinal downstream effects.
” The benchmarks tracked by Vox don ’ t cover every important facet of the pandemic .
They don ’ t show , for instance , how well a state is doing with contact tracing , when “ disease detectives ” track down people who may have been infected and push them to quarantine ; the data for how states are doing on that front is still lacking .
And some measures that are helpful @ @ @ @ @ @ @ start to reopen , like whether cases have fallen in the previous two weeks and total tests , are excluded to focus more on the status of each state ’ s current Covid-19 outbreak .
Together , these four benchmarks help give an idea of how each state is doing in its fight against Covid-19 .
Nationwide , it ’ s pretty grim .
1 ) Most states have too many daily new Covid-19 infections What ’ s the goal ?
Fewer than four daily new coronavirus cases per 100,000 people per day @ @ @ @ @ @ @ York Times and the Census Bureau .
Which states meet the goal ?
Maine , New Hampshire , New York , and Vermont — just four states .
Why is this important ?
The most straightforward way to measure whether any place is suffering a big coronavirus outbreak is to look at the number of daily new Covid-19 cases .
There ’ s no widely accepted metric for how many cases , exactly , is too many .
But experts told me that aiming for below 4 daily new cases per 100,000 is @ @ @ @ @ @ @ low enough that a state can say it ’ s starting to get significant control over the virus .
A big caveat to this metric : It ’ s only as good as a state ’ s testing .
Cases can only get picked up if states are actually testing people for the virus .
So if a state doesn ’ t have enough tests , it ’ s probably going to miss a lot of cases — and the reported cases won ’ t tell the full story .
That ’ s @ @ @ @ @ @ @ to use this benchmark by itself , but alongside metrics like the test positive rate .
Along those lines , the number of daily new cases may give a delayed snapshot of a Covid-19 outbreak .
If test results take a week to get reported to the state , then the count for daily new cases will really reflect the state of the outbreak for the previous week .
If testing is adequate in a state , though , the toll of daily new cases gives perhaps the best snapshot of how big @ @ @ @ @ @ @ .
2 ) The coronavirus is spreading too quickly in most states What ’ s the goal ?
An effective reproduction number , or Rt , below 1 , based on data from Rt.live , a site created by two Instagram founders and a data analyst .
Which states meet the goal ?
Arizona , California , Delaware , Florida , Georgia , Indiana , Louisiana , Maine , Michigan , New Jersey , New Mexico , New York , North Carolina , Ohio , Pennsylvania , South Carolina , Tennessee , Texas @ @ @ @ @ @ @ Wisconsin — a total of 21 states .
Why is this important ?
The Rt measures how many people are infected by each person with Covid-19 .
If the Rt is 1 , then an infected person will , on average , spread the coronavirus to one other person .
If it ’ s 2 , then an infected person will spread it to two on average .
And so on .
It ’ s an attempt , then , to gauge how quickly a virus is spreading .
One way to think @ @ @ @ @ @ @ daily new cases , this doesn ’ t give you a snapshot of a state ’ s Covid-19 outbreak today , but where the outbreak is heading in the near future .
The goal is to get the Rt below 1 .
If each infection doesn ’ t lead to another , that would over time lead to zero new Covid-19 cases .
The estimated Rt can be very imprecise — with margins of error that make it hard to know for certain in any state if it ’ s really above or @ @ @ @ @ @ @ come up with different estimates .
That ’ s , unfortunately , just the reality of using limited data to come up with a rough estimate of a disease ’ s overall spread .
The Rt also reflects an average .
If 10 people are infected with Covid-19 , nine spread it to no one else , and one spreads it to 10 , that adds up to an Rt of one .
But it masks the fact that individuals , for whatever reason , can still cause superspreading events — which seem @ @ @ @ @ @ @ Still , the Rt is one of the better measures we have for tracking a pathogen ’ s spread across the whole population .
When paired with the other metrics on this list , it can give us a sense of each state ’ s outbreak now and in the future .
3 ) Most states ’ positive rates for tests are too high What ’ s the goal ?
Below 5 percent of coronavirus tests coming back positive over the past week , based on data from the Covid Tracking Project .
@ @ @ @ @ @ @ , Connecticut , Delaware , Illinois , Maine , Massachusetts , Michigan , Minnesota , Montana , New Hampshire , New Jersey , New Mexico , New York , Vermont , and West Virginia — 15 states .
Washington , DC , did as well .
( Minnesota is excluded due to recent changes in how it reports tests . )
Why is this important ?
To properly track and contain coronavirus outbreaks , states need to have enough testing .
There are all sorts of proposals for how much testing is needed @ @ @ @ @ @ @ day to tens of millions .
But one way to see if a state is testing enough to match its outbreak is the rate of tests that come back positive .
An area with adequate testing should be testing lots and lots of people , many of whom don ’ t have the disease or don ’ t show severe symptoms .
High positive rates indicate that only people with obvious symptoms are getting tested , so there ’ s not quite enough testing to match the scope of an outbreak .
The @ @ @ @ @ @ @ in an ideal world , 0 percent , since that would suggest that Covid-19 is vanquished entirely .
More realistically , in a world going through a big pandemic , the positive rate should be below 5 percent .
But even if a state reaches 5 percent , experts argue it should continue trying to push that number further down , to match nations like Germany , New Zealand , and South Korea that have gotten their positive rates below 3 percent and even 1 percent , in order to truly get a @ @ @ @ @ @ @ as a state is above 5 percent , chances are it ’ s still missing a significant number of Covid-19 cases .
And the higher that number is , the more cases that are very likely getting missed .
So even if your state is reporting a low number of daily new cases , a high positive rate should be a cause for alarm — a sign that there ’ s an outbreak that ’ s only hidden due to a lack of testing .
And if your state is reporting a high @ @ @ @ @ @ @ high positive rate , that ’ s all the more reason for concern , suggesting that the epidemic is even worse than the total case count indicates .
4 ) Most states ’ hospitals don ’ t have much space for Covid-19 patients What ’ s the goal ?
Below 60 percent occupancy of ICU beds in hospitals , based on data from the US Department of Health and Human Services .
Which states meet the goal ?
Alaska , Colorado , Connecticut , Hawaii , Idaho , Illinois , Iowa , Kansas @ @ @ @ @ @ @ New Hampshire , New Jersey , New York , North Dakota , Ohio , South Dakota , Utah , Washington , Wisconsin , and Wyoming — 21 states .
Why is this important ?
One thing the world has seen , from China to Italy to New York , is that Covid-19 can very quickly overwhelm hospitals .
The consequences for this are dire : If any place is suffering a big coronavirus outbreak , and there isn ’ t enough room in a hospital to treat patients , that could lead to @ @ @ @ @ @ @ occupancy rate in states ’ intensive care units helps track how much space hospitals have to deal with more Covid-19 patients .
It also gives a snapshot of just how busy states ’ hospitals are on any given day .
Generally , the goal is to stay below 60 percent occupancy at ICU beds in hospitals .
That ’ s a point when hospitals have enough cushion , experts say , to more effectively treat patients as well as better handle a rush of patients should an outbreak get worse .
This is @ @ @ @ @ @ @ tracking an outbreak .
Since people can take as long as weeks to develop Covid-19 symptoms once they ’ re infected , hospitalizations also take a few weeks to start trending up as cases trend up .
ICU occupancy also isn ’ t the only metric for tracking hospital readiness .
The US Department of Health and Human Services also tracks the percent of people in inpatient beds who have Covid-19 and the percent of inpatient beds occupied in general .
The other benchmarks also give a view of how well a state @ @ @ @ @ @ @ outbreak .
Still , for a general idea of how bad a state ’ s Covid-19 outbreak is and how ready the state is to handle a surge in cases , the ICU occupancy rate is a helpful indicator .
If a state ’ s ICUs are overwhelmed , the state is possibly suffering a big epidemic , or at least not ready for one .
Every day at Vox , we aim to answer your most important questions and provide you , and our audience around the world , with information that @ @ @ @ @ @ @ Our mission has never been more vital than it is in this moment : to empower you through understanding .
Vox ’ s work is reaching more people than ever , but our distinctive brand of explanatory journalism takes resources — particularly during a pandemic and an economic downturn .
Your financial contribution will not constitute a donation , but it will enable our staff to continue to offer free articles , videos , and podcasts at the quality and volume that this moment requires .
Please consider making a contribution to Vox @ @

America’s national Covid-19 epidemic continues, with the US’s daily new cases down from an early January peak but still higher than those of most developed nations — and the country recently surpassing 500,000 deaths due to the disease.
At the state level, things can look even worse than the national picture.
Public health experts look at a few markers to determine how bad things are in each state: the number of daily new cases; the infection rate, which can show how likely the virus is to spread; and the percentage of tests that come back positive, which should be low in a state with sufficient testing. Combined, these three benchmarks can tell you whether or not a state’s coronavirus outbreak is under control.
Vox’s analysis, updated weekly, shows the vast majority of states are reporting alarming trends for coronavirus cases based on these benchmarks. Only one state — Hawaii — fares well on all three metrics, suggesting the vast majority of states don’t have their outbreaks fully under control right now.
The US outbreaks are due to the failure of both the American public and the country’s leaders to take the virus seriously enough; to the extent they did, many let their guard down prematurely. With the support of former President Donald Trump, states moved to reopen — often before seeing sizable drops in daily new Covid-19 cases, and at times so quickly they weren’t able to tell whether each phase of their reopening plan was leading to too many new infections.
The public embraced the reopenings, resuming their usual day-to-day activities and often refusing to adhere to recommended precautions like physical distancing and mask-wearing.
Even as cases began to fall later in the summer, America’s overall caseload remained very high. Yet many states moved to reopen once more, with much of the public embracing the looser restrictions and subsequently going out.
It’s this mix of government withdrawal and public complacency that experts have cited in explaining why states continue to struggle with getting the coronavirus under control.
“It’s a situation that didn’t have to be,” Jaime Slaughter-Acey, an epidemiologist at the University of Minnesota, previously told me, adding, “You had opportunities to be proactive with respect to mitigating the Covid-19 pandemic and to help normalize culture to adopt practices that would stem the tide of transmissions as well as the development of Covid-19 complications. … It was not prioritized over the economy.”
The effects are felt not just in terms of more infections, critical illnesses, new chronic conditions, and deaths, but in the long-term financial impact as the economy struggles, many people still refuse to go out, and businesses resist reopening during a pandemic.
“Dead people don’t shop. They don’t spend money. They don’t invest in things,” Jade Pagkas-Bather, an expert in infectious diseases and a doctor at the University of Chicago, previously told me. “When you fail to invest in the health of your population, then there are longitudinal downstream effects.”
With a Covid-19 vaccination campaign underway, a finish line to this crisis in finally visible. But until America reaches sufficient population protection — and, preferably, herd immunity — every day the coronavirus spreads means more illnesses, hospitalizations, and deaths.
As the country works toward vaccinating everyone, the three benchmarks tracked by Vox give an idea of how each state is doing in its fight against Covid-19 in the meantime. Nationwide, it’s pretty grim.
1) Most states have too many daily new Covid-19 infections
What’s the goal? Fewer than four daily new coronavirus cases per 100,000 people per day, based on data from the Covid Tracking Project and the Census Bureau.
Which states meet the goal? Just one — Hawaii.
Why is this important? The most straightforward way to measure whether any place is experiencing a big coronavirus outbreak is to look at the number of daily new Covid-19 cases.
There’s no widely accepted metric for how many cases, exactly, is too many. But experts told me that aiming for below four daily new cases per 100,000 is generally a good idea — a level low enough that a state can say it’s starting to get significant control over the virus.
A big caveat to this metric: It’s only as good as a state’s testing. Cases can only get picked up if states are actually testing people for the virus. So if a state doesn’t have enough tests, it’s probably going to miss a lot of cases, and the reported cases won’t tell the full story. That’s why it’s important not to use this benchmark by itself, but to use it alongside metrics like the test positive rate.
The number of daily new cases may also give a delayed snapshot of a Covid-19 outbreak. If test results take a week to get reported to the state, the count for daily new cases will really reflect the state of the outbreak for the previous week.
If testing is adequate in a state, though, the toll of daily new cases is perhaps the best insight as to how big a state’s Covid-19 outbreak is.
2) The coronavirus is spreading too quickly in some states
What’s the goal? An effective reproduction number, or Rt, below 1, based on data from the Centre for Mathematical Modeling of Infectious Diseases.
Which states meet the goal? All but Alaska, Minnesota, New Hampshire, North Dakota, and Wyoming — 45 states, as well as Washington, DC.
Why is this important? The Rt measures how many people are infected by each person with Covid-19. If the Rt is 1, then an infected person will, on average, spread the coronavirus to one other person. If it’s 2, then an infected person will spread it to two on average. And so on.
It’s an attempt, then, to gauge how quickly a virus is spreading. One way to think about it: Unlike the count for daily new cases, this gives you a snapshot not of a state’s Covid-19 outbreak today, but of where the outbreak is heading in the near future.
The goal is to get the Rt below 1. If each infection doesn’t lead to another, that would over time lead to zero new Covid-19 cases.
The estimated Rt can be very imprecise, with margins of error that make it hard to know for certain in any state if it’s really above or below 1. Different modelers can also come up with different estimates. That’s, unfortunately, just the reality of using limited data to come up with a rough estimate of a disease’s overall spread.
The Rt also reflects an average. If 10 people are infected with Covid-19, nine spread it to no one else, and one spreads it to 10, that adds up to an Rt of 1. But it masks the fact that individuals, for whatever reason, can still cause superspreading events — which seem of particular concern with the coronavirus.
And the Rt is only as good as the data that goes into calculating it. If a state’s data is poor quality or inconsistent, it might skew the picture. That can help explain why some states with bad and continuing outbreaks may fare better on this benchmark than others.
Still, the Rt is one of the better measures we have for tracking a pathogen’s spread across the whole population. When paired with the other metrics on this list, it can give us a sense of each state’s outbreak now and in the future.
3) Most states’ positive rates for tests are too high
What’s the goal? Less than 5 percent of coronavirus tests coming back positive over the previous week, based on data from the Johns Hopkins Coronavirus Resource Center and the Covid Tracking Project.
Which states meet the goal? Alaska, California, Colorado, Connecticut, Hawaii, Illinois, Indiana, Maine, Maryland, Massachusetts, Michigan, Minnesota, Montana, Nebraska, Nevada, New Mexico, New York, North Dakota, Oregon, Rhode Island, Vermont, Washington, West Virginia, and Wisconsin — 24 states, as well as Washington, DC.
Why is this important? To properly track and contain coronavirus outbreaks, states need to have enough testing. There are all sorts of proposals for how much testing is needed in the US, up to the tens of millions.
But one way to see if a state is testing enough to match its outbreak is the rate of tests that come back positive. An area with adequate testing should be testing lots and lots of people, many of whom don’t have the disease or don’t show severe symptoms. High positive rates indicate that only people with obvious symptoms are getting tested, so there’s not quite enough testing to match the scope of an outbreak.
The goal for the positive rate is, in an ideal world, zero percent, since that would suggest that Covid-19 is vanquished entirely. More realistically, in a world going through a pandemic, the positive rate should be below 5 percent. But even if a state reaches 5 percent, experts argue it should continue trying to push that number further down — to match nations like Australia, New Zealand, and South Korea, which have gotten their positive rates below 3 percent or even 1 percent — in order to truly get ahold of their outbreaks.
As long as a state is above 5 percent, chances are it’s still missing a significant number of Covid-19 cases. And the higher that number is, the more cases that are very likely getting missed.
So even if your state is reporting a low number of daily new cases, a high positive rate should be a cause for alarm — a sign that there’s an outbreak that’s only hidden due to a lack of testing. And if your state is reporting a high number of daily new cases and a high positive rate, that’s all the more reason for concern, suggesting the epidemic is even worse than the total case count indicates.
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vox--2020-08-05--“It’s like we’re flying blind”: The US has a Covid-19 data problem

Six months into America ’ s battle with Covid-19 , we still can ’ t really see the enemy .
There isn ’ t good real-time data on where the virus is and who it is infecting .
Our diagnostic testing is at an all-time high , but it ’ s still missing the vast majority of infections .
We don ’ t have systematic surveillance programs like we do for the flu to fill in the gaps , and we don ’ t have good metrics that tell us how well the virus is being contained .
We ’ @ @ @ @ @ @ @ ’ s happening in many minority communities , which have lower testing rates than white communities .
We don ’ t have good foresight into the future either : As the response to the pandemic grows more fractured , and the policies less consistent and more politicized , it ’ s getting harder to model .
“ It ’ s like we ’ re flying blind , ” says Sarah Cobey , an infectious disease modeler at the University of Chicago .
To extend the metaphor : When airplane pilots can ’ t @ @ @ @ @ @ @ rely on their instruments to guide them through a storm .
But with the pandemic “ we don ’ t even have that , ” Cobey says .
“ We don ’ t even have good numbers to be staring at to guide our flying.
” This blindness is particularly excruciating because institutions — like schools and universities — have to make hugely consequential decisions about reopening without clear data on what ’ s happening on the ground .
The best data we have on community spread of Covid-19 is weeks out of @ @ @ @ @ @ @ won ’ t necessarily be able to monitor the consequences of their decisions in real time .
With a virus capable of exponential growth , these lags in data can result in catastrophe .
What we do know is that we ’ re entering a newly dangerous period .
As temperatures fall and people are forced back indoors in the coming months , it ’ s possible transmission rates of Covid-19 will increase even more .
If we ’ re going to fly this country out of the pandemic , we ’ re @ @ @ @ @ @ @ ’ s going on .
Here ’ s what ’ s missing , and what we so desperately need .
1 ) We don ’ t have good real-time data .
And data is particularly insufficient for minority communities .
Time is everything in the pandemic .
The quicker a Covid-19 case is identified , the quicker it can be isolated , the quicker contacts can be quarantined , the fewer people get infected , and so on .
On a big-picture level : The faster a state or local government can identify @ @ @ @ @ @ @ can act to stem the outbreak .
What we need is a real-time view of Covid-19 transmission .
And it simply doesn ’ t exist .
Ideally , we could get real-time transmission data from rapid Covid-19 diagnostic testing .
But testing is currently backlogged in many places , with people waiting a week or more for results .
So it can ’ t provide real-time data .
Testing also does not provide a complete picture of who is getting infected .
“ Four out of five infections are not ... counted as @ @ @ @ @ @ @ ’ re not being tested ( these include milder or asymptomatic cases ) .
“ Right now , cases are so underreported , and they ’ re not just underreported in a consistent way — they ’ re underreported in a biased way.
” Minority communities , for instance , are not being tested at the same rate as white communities ( despite bearing a disproportionate brunt of the pandemic ’ s toll ) .
According to an investigation by FiveThirtyEight , Black and Hispanic communities face longer wait times for tests , @ @ @ @ @ @ @ in areas primarily inhabited by racial minorities.
” So testing data gives us a skewed picture of what ’ s going on .
Since we can ’ t use testing data for a view of overall community transmission , we have to extrapolate from hospitalizations and deaths .
Researchers know , roughly , the ratio of hospitalizations and deaths to the amount of community spread .
So they can work backward .
Yet hospitalizations and deaths are lagging indicators .
They ’ re indicative of transmission that occurred three weeks ago or more @ @ @ @ @ @ @ weeks can really mean a huge increase in cases or in infections , ” Jaline Gerardin , a Northwestern University computational epidemiologist , says .
If it takes a week for cases to double , she explains , then a three-week lag of data means cases can increase eightfold .
Hospitalization data may also now be less reliable than before , due to the Trump administration .
A recent change in policy to reroute Covid-19 hospitalization data from the Centers for Disease Control and Prevention ( CDC ) to the Department of Health @ @ @ @ @ @ @ information blackouts , ” ProPublica reports .
The Covid Tracking Project , a watchdog journalism group collecting Covid-19 data , writes that “ these problems mean that our hospitalization data — a crucial metric of the COVID-19 pandemic — is , for now , unreliable , and likely an undercount.
” But even pristine hospital data wouldn ’ t tell the whole story of the pandemic .
Older people are more likely to be hospitalized , which makes it harder to deduce outbreaks among younger people from this data source .
Gerardin says @ @ @ @ @ @ @ tends to skew younger than white or Black populations.
” So relying on hospitalization data makes it harder to observe trends in this community .
In the absence of current , comprehensive data , scientists are developing new tools to make the best use of the data available to help guide difficult reopening decisions .
In advising Texas schools on reopenings , Lauren Ancel Meyers , director of the University of Texas Covid-19 Modeling Consortium , and her colleagues have created a calculator to estimate how many students and faculty may come to @ @ @ @ @ @ @ transmission .
If Covid-19 prevalence in the community is 1 in 100 , for example , then a school with 1,000 students and teachers could expect 10 people to arrive infected during a reopening , Meyers and her colleagues report .
( Just one infected person is enough to start a large outbreak . )
But the key thing about this risk calculation is that it ’ s dependent on knowing the prevalence of Covid-19 in a community .
Using hospitalization data , “ we are able to kind of estimate how fast @ @ @ @ @ @ @ prior , ” Meyers says .
Ten days , while helpful , isn ’ t ideal : An outbreak can start to spark up in that time .
That ’ s the best they can do .
But they can ’ t even do it for everywhere in the country : “ Unfortunately , hospitalization data are not kind of widely available for all communities in the country , ” she says .
So not only are some areas blind to their current conditions , they don ’ t even have a clear @ @ @ @ @ @ @ we need : Surveillance testing One of the most commonly reported metrics during the pandemic is the percentage of tests that come back positive .
In May , the World Health Organization advised governments that before reopening , the rate of Covid-19 positive tests should remain at 5 percent or lower for at least 14 days .
If the proportion of positive tests rises above 5 percent consistently , it ’ s a sign there ’ s an outbreak growing in the area ( and not just a sign that more mild cases @ @ @ @ @ @ @ ) .
The problem is that this metric — while helpful — is still crude .
And at times , it can deliver ambiguous conclusions .
“ You could imagine a situation where the the epidemic is growing but the test positivity rate is actually decreasing , ” Gerardin says .
For example , if a university decides to test all its incoming students , or if a company decides to test all its employees before coming back to work , it can inflate the denominator of the equation .
“ Changes in @ @ @ @ @ @ @ tested is really important , ” Cobey says .
“ And we don ’ t [ currently ] understand them.
” Instead of relying on this flawed metric , we need systematic surveillance .
A good surveillance system doesn ’ t need to include everyone tested , but just a predefined segment of the population , tracked carefully , and with good data .
Recently , Cobey and Gerardin consulted with the state of Illinois about setting up a surveillance system .
Their idea is really simple : systematically record all the patients @ @ @ @ @ @ @ .
“ You can estimate the effective reproductive number from that , ” Cobey says .
“ You can get more up-to-date estimates and more precise estimates of what transmission rates are at different times.
” Ideally , “ this would have been up and running before we started coming out of lockdown , ” Gerardin says .
But currently , they say , there ’ s only one outpatient site in Illinois participating as a pilot , and it ’ s not enough to provide useful data .
They ’ re not @ @ @ @ @ @ @ up and running .
“ I don ’ t know of any US state that is doing good surveillance , ” Cobey says , though she admits it ’ s hard to know what ’ s going on everywhere across the country .
And that ’ s part of the problem , too : There ’ s no national standard for what Covid-19 surveillance ought to look like , or one place to go look up programs that exist .
“ It really confuses me why we ’ re not investing in this @ @ @ @ @ @ @ overall .
If testing programs across states were more careful and systematic in their current data collection and reporting — labeling why people received the tests , and if they have symptoms , noting when they started — it would help produce better real-time estimates of transmission .
“ Even where there ’ s more testing , we ’ re almost never seeing the numbers broken down in a reasonable way , ” Cobey says .
“ For instance , we don ’ t know which tests are from asymptomatics or symptomatics , @ @ @ @ @ @ @ or people showing up quite ill in the hospital.
” Just ensuring every recorded case included a “ date of symptom onset ” would be helpful for better surveillance she says .
“ And that ’ s not collected the vast majority of the time.
” Other scientists are trying to find ways to fill in the gaps .
Mauricio Santillana , a computational epidemiologist at Harvard , has been building a machine-learning program to use as a form of disease surveillance .
“ What we seek to identify is , ‘ Can @ @ @ @ @ @ @ identify outbreaks with more confidence ?
’ ” Santillana says .
Santillana and his colleagues combine data from UpToDate ( a search engine for clinicians to look up disease symptoms ) , Google searches for fevers or Covid-19 symptoms , data from digital thermometers that pair with smartphones , and other information streams to predict outbreaks weeks before they show up in case-count data .
“ We ’ re hoping to provide with these kinds of tools , confirmatory information to say , yes , cases are under control , or no , @ @ @ @ @ @ @ ’ t replace traditional surveillance outright .
( It also has some drawbacks : If people ’ s behavior starts changing in terms of Google searches or UpToDate searches , it could potentially alter the predictive ability of the program . )
And while they have piloted the program with some success in China , he says , they ’ re also facing a frustrating roadblock in the US .
“ Agencies such as the CDC see our work to some extent as novel and experimental , even though we have worked with @ @ @ @ @ @ @ , using this data for influenza , “ Santillana says .
“ So that means that they ’ re not paying as much attention , they ’ re not funding our work.
” The state of surveillance testing is frustrating for scientists .
Disease surveillance is no novel concept : It is regularly in use for the flu .
“ I had thought good surveillance would be the most obvious thing for politicians to want to invest in and improve , so they can adjust policy faster and with more data-driven authority , @ @ @ @ @ @ @ not , ” Cobey says .
2 ) We don ’ t have good metrics on containment There ’ s another view we don ’ t have : how well we have this virus contained .
“ If you equate infectious disease transmission to fires , I could tell you where the major [ Covid-19 ] fires are in the US — Florida , Texas , Arizona — I know where the fires are , especially if they are big , ” says Cyrus Shahpar , the former lead of the Global Rapid @ @ @ @ @ @ @ wildfires , authorities will report what percentage of the fire is contained , which is often a reflection of how well firefighting authorities are responding .
With Covid-19 , we have few comparable metrics .
“ I have no idea what percent contained these [ Covid-19 ] fires are , ” Shahpar says .
“ You could have a small fire that isn ’ t contained and that ’ s the problem .
Or you could have a medium fire that is contained and that ’ s better contained .
That matters , @ @ @ @ @ @ @ the biggest information gap.
” What would you want to know to assess Covid containment ?
Shahpar , along with Tom Frieden , who served as CDC director under President Obama , and their group Resolve to Save Lives , have 15 essential indicators for all states to report to better understand how good ( or bad ) of a job they are doing in responding to the pandemic .
They include metrics like : What proportion of cases are isolated within 48 hours ( to get a sense if new sparks in @ @ @ @ @ @ @ ?
What percentage of cases are linked to previously known cases ?
( The less we know about chains of transmission , the less we probably know about the scope of the entire outbreak . )
How long , on average , does it take to isolate a case ?
“ I have no idea how these things are going in Florida and Texas in other any state , really , because they don ’ t report it , ” Shahpar says .
States are all reporting their own hodgepodge of metrics , @ @ @ @ @ @ @ clear picture of pandemic containment at a national level .
Federal guidance from the CDC and White House to states has been slow , and so states had to come up with their own plans .
But that makes the scope of the pandemic hard to track .
“ Even if the metrics aren ’ t great right now , and I think that some places they aren ’ t , you need to know what they are .
So that when we improve , we know that we ’ ve improved , @ @ @ @ @ @ @ Lives is keeping track of which states report this type of containment data , and so far , the vast majority don ’ t .
The states that do track it aren ’ t doing so in a standardized way , so it ’ s hard to make cross-state comparisons .
Shahpar blames a lack of federal guidance .
“ If you look at the 50 reopening plans of each of the states , they ’ re all different , ” he says .
“ They all look different ; what they look @ @ @ @ @ @ @ ’ ve kind of already proceeded into a place where everything ’ s different .
So it ’ s much harder to get it all aligned.
” 3 ) The future of the pandemic is difficult to model right now Everyone wants to know what ’ s going to happen next .
But here ’ s the truth : It ’ s really hard to know what shape the pandemic will take this coming fall .
There ’ s an element of chaos in all of this .
And it ’ s getting @ @ @ @ @ @ @ have understood from the very beginning that this the way this virus spreads fundamentally depends on behavior and politics , ” Meyers says .
“ And our behavior changed in unprecedented , dramatic ways.
” ( Who could have predicted people protesting mask-wearing , for instance ? )
“ We really can not predict what people are going to be doing , you know , next week , ” she says .
For that reason — and others — her team ’ s models never try to project more than three weeks into @ @ @ @ @ @ @ agrees : “ I expect that , you know , our predictive abilities are going to improve with time , ” she says .
“ But at the moment , I think this is a particularly dark spot.
” There are still so many uncertainties that will determine our course : How much of a role kids play in transmission is still a mystery that ’ s being sorted out ( though it ’ s increasingly clear kids can get infected and transmit the virus with frequency ) , and how people will @ @ @ @ @ @ @ While we might not be able to intuit the future , and we might not have great vision on what ’ s currently happening , it doesn ’ t mean we ’ re powerless .
We know the conditions under which the pandemic grows worse .
We can continue to social distance , continue to wear masks , continue to try to test , trace , and isolate .
“ What we see over and over again in our modeling , ” Jeffrey Shaman , an infectious disease modeler at Columbia University , @ @ @ @ @ @ @ open up places like schools safely depends on “ how much virus there is out there right now , how many cases you ’ re seeing in the last four days , and how much it ’ s growing at that time.
” Right now we have to be really cautious , and act knowing that this data arrives already out of date .
Without clear vision in this storm , “ we ’ re going to be living with coronavirus much longer , with much more preventable death and disability than any @ @ @ @ @ @ @ Shahpar says .
In the coming months , the storm might grow worse .
And as temperatures begin to drop , we should prepare for Covid-19 transmission to increase .
“ It ’ s what we see in every other acute respiratory viral infection , ” Cobey says .
Every day at Vox , we aim to answer your most important questions and provide you , and our audience around the world , with information that has the power to save lives .
Our mission has never been more vital than it is @ @ @ @ @ @ @ through understanding .
Vox ’ s work is reaching more people than ever , but our distinctive brand of explanatory journalism takes resources — particularly during a pandemic and an economic downturn .
Your financial contribution will not constitute a donation , but it will enable our staff to continue to offer free articles , videos , and podcasts at the quality and volume that this moment requires .
Please consider making a contribution to Vox today .

Six months into America’s battle with Covid-19, we still can’t really see the enemy.
There isn’t good real-time data on where the virus is and who it is infecting. Our diagnostic testing is at an all-time high, but it’s still missing the vast majority of infections.
We don’t have systematic surveillance programs like we do for the flu to fill in the gaps, and we don’t have good metrics that tell us how well the virus is being contained. We’re particularly in the dark about what’s happening in many minority communities, which have lower testing rates than white communities.
We don’t have good foresight into the future either: As the response to the pandemic grows more fractured, and the policies less consistent and more politicized, it’s getting harder to model.
“It’s like we’re flying blind,” says Sarah Cobey, an infectious disease modeler at the University of Chicago. To extend the metaphor: When airplane pilots can’t see out their windows, they can rely on their instruments to guide them through a storm. But with the pandemic “we don’t even have that,” Cobey says. “We don’t even have good numbers to be staring at to guide our flying.”
This blindness is particularly excruciating because institutions — like schools and universities — have to make hugely consequential decisions about reopening without clear data on what’s happening on the ground. The best data we have on community spread of Covid-19 is weeks out of date when it arrives. And schools won’t necessarily be able to monitor the consequences of their decisions in real time. With a virus capable of exponential growth, these lags in data can result in catastrophe.
What we do know is that we’re entering a newly dangerous period. As temperatures fall and people are forced back indoors in the coming months, it’s possible transmission rates of Covid-19 will increase even more.
If we’re going to fly this country out of the pandemic, we’re going to need more visibility on what’s going on.
Here’s what’s missing, and what we so desperately need.
1) We don’t have good real-time data. And data is particularly insufficient for minority communities.
Time is everything in the pandemic.
The quicker a Covid-19 case is identified, the quicker it can be isolated, the quicker contacts can be quarantined, the fewer people get infected, and so on. On a big-picture level: The faster a state or local government can identify a growing outbreak, the faster it can act to stem the outbreak.
What we need is a real-time view of Covid-19 transmission. And it simply doesn’t exist.
Ideally, we could get real-time transmission data from rapid Covid-19 diagnostic testing. But testing is currently backlogged in many places, with people waiting a week or more for results. So it can’t provide real-time data. Testing also does not provide a complete picture of who is getting infected.
“Four out of five infections are not ... counted as cases,” Cobey says. They’re not being tested (these include milder or asymptomatic cases). “Right now, cases are so underreported, and they’re not just underreported in a consistent way — they’re underreported in a biased way.”
Minority communities, for instance, are not being tested at the same rate as white communities (despite bearing a disproportionate brunt of the pandemic’s toll). According to an investigation by FiveThirtyEight, Black and Hispanic communities face longer wait times for tests, and there are “fewer testing sites in areas primarily inhabited by racial minorities.” So testing data gives us a skewed picture of what’s going on.
Since we can’t use testing data for a view of overall community transmission, we have to extrapolate from hospitalizations and deaths. Researchers know, roughly, the ratio of hospitalizations and deaths to the amount of community spread. So they can work backward.
Yet hospitalizations and deaths are lagging indicators. They’re indicative of transmission that occurred three weeks ago or more.
“Under exponential growth, three weeks can really mean a huge increase in cases or in infections,” Jaline Gerardin, a Northwestern University computational epidemiologist, says. If it takes a week for cases to double, she explains, then a three-week lag of data means cases can increase eightfold.
Hospitalization data may also now be less reliable than before, due to the Trump administration. A recent change in policy to reroute Covid-19 hospitalization data from the Centers for Disease Control and Prevention (CDC) to the Department of Health and Human Services has created “temporary information blackouts,” ProPublica reports. The Covid Tracking Project, a watchdog journalism group collecting Covid-19 data, writes that “these problems mean that our hospitalization data — a crucial metric of the COVID-19 pandemic — is, for now, unreliable, and likely an undercount.”
But even pristine hospital data wouldn’t tell the whole story of the pandemic. Older people are more likely to be hospitalized, which makes it harder to deduce outbreaks among younger people from this data source. Gerardin says in Illinois, “the Hispanic/Latino population tends to skew younger than white or Black populations.” So relying on hospitalization data makes it harder to observe trends in this community.
In the absence of current, comprehensive data, scientists are developing new tools to make the best use of the data available to help guide difficult reopening decisions.
In advising Texas schools on reopenings, Lauren Ancel Meyers, director of the University of Texas Covid-19 Modeling Consortium, and her colleagues have created a calculator to estimate how many students and faculty may come to campus infected based on levels of community transmission. If Covid-19 prevalence in the community is 1 in 100, for example, then a school with 1,000 students and teachers could expect 10 people to arrive infected during a reopening, Meyers and her colleagues report. (Just one infected person is enough to start a large outbreak.)
But the key thing about this risk calculation is that it’s dependent on knowing the prevalence of Covid-19 in a community. Using hospitalization data, “we are able to kind of estimate how fast the virus was spreading about 10 days prior,” Meyers says. Ten days, while helpful, isn’t ideal: An outbreak can start to spark up in that time.
That’s the best they can do. But they can’t even do it for everywhere in the country: “Unfortunately, hospitalization data are not kind of widely available for all communities in the country,” she says.
So not only are some areas blind to their current conditions, they don’t even have a clear view of the recent past.
What we need: Surveillance testing
One of the most commonly reported metrics during the pandemic is the percentage of tests that come back positive. In May, the World Health Organization advised governments that before reopening, the rate of Covid-19 positive tests should remain at 5 percent or lower for at least 14 days. If the proportion of positive tests rises above 5 percent consistently, it’s a sign there’s an outbreak growing in the area (and not just a sign that more mild cases are being discovered due to increased testing).
The problem is that this metric — while helpful — is still crude. And at times, it can deliver ambiguous conclusions. “You could imagine a situation where the the epidemic is growing but the test positivity rate is actually decreasing,” Gerardin says. For example, if a university decides to test all its incoming students, or if a company decides to test all its employees before coming back to work, it can inflate the denominator of the equation.
“Changes in the denominator of who’s being tested is really important,” Cobey says. “And we don’t [currently] understand them.”
Instead of relying on this flawed metric, we need systematic surveillance.
A good surveillance system doesn’t need to include everyone tested, but just a predefined segment of the population, tracked carefully, and with good data.
Recently, Cobey and Gerardin consulted with the state of Illinois about setting up a surveillance system. Their idea is really simple: systematically record all the patients who arrive at outpatient clinics with symptoms. “You can estimate the effective reproductive number from that,” Cobey says. “You can get more up-to-date estimates and more precise estimates of what transmission rates are at different times.”
Ideally, “this would have been up and running before we started coming out of lockdown,” Gerardin says.
But currently, they say, there’s only one outpatient site in Illinois participating as a pilot, and it’s not enough to provide useful data. They’re not sure when the full program will be up and running.
“I don’t know of any US state that is doing good surveillance,” Cobey says, though she admits it’s hard to know what’s going on everywhere across the country. And that’s part of the problem, too: There’s no national standard for what Covid-19 surveillance ought to look like, or one place to go look up programs that exist. “It really confuses me why we’re not investing in this,” Cobey says of surveillance programs overall.
If testing programs across states were more careful and systematic in their current data collection and reporting — labeling why people received the tests, and if they have symptoms, noting when they started — it would help produce better real-time estimates of transmission.
“Even where there’s more testing, we’re almost never seeing the numbers broken down in a reasonable way,” Cobey says. “For instance, we don’t know which tests are from asymptomatics or symptomatics, or if tests come from outpatient sites or people showing up quite ill in the hospital.” Just ensuring every recorded case included a “date of symptom onset” would be helpful for better surveillance she says. “And that’s not collected the vast majority of the time.”
Other scientists are trying to find ways to fill in the gaps. Mauricio Santillana, a computational epidemiologist at Harvard, has been building a machine-learning program to use as a form of disease surveillance.
“What we seek to identify is, ‘Can we help these traditional data sources, identify outbreaks with more confidence?’” Santillana says.
Santillana and his colleagues combine data from UpToDate (a search engine for clinicians to look up disease symptoms), Google searches for fevers or Covid-19 symptoms, data from digital thermometers that pair with smartphones, and other information streams to predict outbreaks weeks before they show up in case-count data.
“We’re hoping to provide with these kinds of tools, confirmatory information to say, yes, cases are under control, or no,” Santillana says. This approach can’t replace traditional surveillance outright. (It also has some drawbacks: If people’s behavior starts changing in terms of Google searches or UpToDate searches, it could potentially alter the predictive ability of the program.) And while they have piloted the program with some success in China, he says, they’re also facing a frustrating roadblock in the US.
“Agencies such as the CDC see our work to some extent as novel and experimental, even though we have worked with the CDC for more than five years, using this data for influenza,“ Santillana says. “So that means that they’re not paying as much attention, they’re not funding our work.”
The state of surveillance testing is frustrating for scientists. Disease surveillance is no novel concept: It is regularly in use for the flu. “I had thought good surveillance would be the most obvious thing for politicians to want to invest in and improve, so they can adjust policy faster and with more data-driven authority, but it turns out it’s not,” Cobey says.
2) We don’t have good metrics on containment
There’s another view we don’t have: how well we have this virus contained.
“If you equate infectious disease transmission to fires, I could tell you where the major [Covid-19] fires are in the US — Florida, Texas, Arizona — I know where the fires are, especially if they are big,” says Cyrus Shahpar, the former lead of the Global Rapid Response Team at the CDC. With wildfires, authorities will report what percentage of the fire is contained, which is often a reflection of how well firefighting authorities are responding.
With Covid-19, we have few comparable metrics. “I have no idea what percent contained these [Covid-19] fires are,” Shahpar says. “You could have a small fire that isn’t contained and that’s the problem. Or you could have a medium fire that is contained and that’s better contained. That matters, and that’s where we have the biggest information gap.”
What would you want to know to assess Covid containment? Shahpar, along with Tom Frieden, who served as CDC director under President Obama, and their group Resolve to Save Lives, have 15 essential indicators for all states to report to better understand how good (or bad) of a job they are doing in responding to the pandemic.
They include metrics like: What proportion of cases are isolated within 48 hours (to get a sense if new sparks in the fire are being quickly contained)? What percentage of cases are linked to previously known cases? (The less we know about chains of transmission, the less we probably know about the scope of the entire outbreak.) How long, on average, does it take to isolate a case?
“I have no idea how these things are going in Florida and Texas in other any state, really, because they don’t report it,” Shahpar says. States are all reporting their own hodgepodge of metrics, which makes it hard to get a clear picture of pandemic containment at a national level. Federal guidance from the CDC and White House to states has been slow, and so states had to come up with their own plans. But that makes the scope of the pandemic hard to track.
“Even if the metrics aren’t great right now, and I think that some places they aren’t, you need to know what they are. So that when we improve, we know that we’ve improved,” Shahpar says.
Resolve to Save Lives is keeping track of which states report this type of containment data, and so far, the vast majority don’t. The states that do track it aren’t doing so in a standardized way, so it’s hard to make cross-state comparisons. Shahpar blames a lack of federal guidance.
“If you look at the 50 reopening plans of each of the states, they’re all different,” he says. “They all look different; what they look at is different. And so we’ve kind of already proceeded into a place where everything’s different. So it’s much harder to get it all aligned.”
3) The future of the pandemic is difficult to model right now
Everyone wants to know what’s going to happen next. But here’s the truth: It’s really hard to know what shape the pandemic will take this coming fall. There’s an element of chaos in all of this. And it’s getting harder to model outcomes.
“We have understood from the very beginning that this the way this virus spreads fundamentally depends on behavior and politics,” Meyers says. “And our behavior changed in unprecedented, dramatic ways.” (Who could have predicted people protesting mask-wearing, for instance?) “We really cannot predict what people are going to be doing, you know, next week,” she says. For that reason — and others — her team’s models never try to project more than three weeks into the future, she says.
Cobey agrees: “I expect that, you know, our predictive abilities are going to improve with time,” she says. “But at the moment, I think this is a particularly dark spot.”
There are still so many uncertainties that will determine our course: How much of a role kids play in transmission is still a mystery that’s being sorted out (though it’s increasingly clear kids can get infected and transmit the virus with frequency), and how people will continue to adhere to mask-wearing guidance.
While we might not be able to intuit the future, and we might not have great vision on what’s currently happening, it doesn’t mean we’re powerless. We know the conditions under which the pandemic grows worse. We can continue to social distance, continue to wear masks, continue to try to test, trace, and isolate.
“What we see over and over again in our modeling,” Jeffrey Shaman, an infectious disease modeler at Columbia University, explains, is that the ability to open up places like schools safely depends on “how much virus there is out there right now, how many cases you’re seeing in the last four days, and how much it’s growing at that time.” Right now we have to be really cautious, and act knowing that this data arrives already out of date.
Without clear vision in this storm, “we’re going to be living with coronavirus much longer, with much more preventable death and disability than any other part of the world,” Shahpar says.
In the coming months, the storm might grow worse. And as temperatures begin to drop, we should prepare for Covid-19 transmission to increase. “It’s what we see in every other acute respiratory viral infection,” Cobey says.