vox--2020-07-22--Just 3 states meet these basic criteria to reopen and stay safe

All 50 states have moved to reopen their economies , at least partially , after shutting down businesses and gatherings in response to the coronavirus pandemic .
But a Vox analysis suggests that most states haven ’ t made the preparations needed to contain outbreaks — putting themselves at risk for a rise in Covid-19 cases and deaths should they continue to reopen , as many states have already seen .
Experts told me states need three things to be safe to open .
State leaders , from the governor to the legislature to health departments , need to ensure @ @ @ @ @ @ @ unabated .
They need the testing capacity to track and isolate the sick and their contacts .
And they need the hospital capacity to handle a potential surge in Covid-19 cases .
More specifically , states should meet at least five basic criteria .
They should see a two-week drop in coronavirus cases , indicating that the virus is actually abating .
They should have fewer than four daily new cases per 100,000 people per day — to show that cases aren ’ t just dropping but are also below dangerous levels .
@ @ @ @ @ @ @ per 100,000 people per day , letting them quickly track and contain outbreaks .
They need an overall positive rate for tests below 5 percent — another critical indicator for testing capacity .
And states should have at least 40 percent of their ICU beds free to actually treat an influx of people stricken with Covid-19 should it be necessary .
These metrics line up with a range of expert recommendations , as well as the various policy plans put out by both independent groups and government officials to deal with the coronavirus @ @ @ @ @ @ @ mean that a state is ready to safely reopen its economy — a process that describes a wide range of local and state actions .
And failing them doesn ’ t mean a state is in immediate danger of a coronavirus outbreak if it starts to reopen ; with Covid-19 , there ’ s always an element of luck and other factors .
But with these metrics , states can gauge if they have repressed the coronavirus while building the capacity to contain future outbreaks should they come .
In other words , @ @ @ @ @ @ @ for the next phase of the fight .
So far , most states are not there .
As of July 22 , just three states — Connecticut , New Jersey , and New York — met four or five of the goals , which demonstrates strong progress .
Twenty-two states and Washington , DC , hit two or three of the benchmarks .
The other 25 achieved zero or one .
( South Dakota and Wyoming didn ’ t report ICU data , but it wouldn ’ t be enough to change their @ @ @ @ @ @ @ have made the most progress aren ’ t safe to fully reopen .
Without a vaccine or similar treatment , the threat of the coronavirus is still out there .
Especially in states that suffered big outbreaks , such as Arizona and New York , even a lot of progress or some progress doesn ’ t mean all the underlying problems that led to an epidemic are gone .
Nor do the metrics cover everything that states should do before they can safely reopen .
They don ’ t show , for example @ @ @ @ @ @ @ do contact tracing , in which people who came into contact with someone who ’ s sick with Covid-19 are tracked down by “ disease detectives ” and quarantined .
Contact tracing is key to containing an epidemic , but states don ’ t track how many contact tracers they ’ ve hired in a standardized , readily available way .
States also don ’ t have ready data for health care workers ’ access to personal protective equipment , such as masks and gloves — a critical measure of the health care @ @ @ @ @ @ @ difficult to track .
But the map gives an idea of how much progress states have made toward containing the coronavirus and keeping it contained .
States will have to follow these kinds of metrics as they reopen .
If the numbers — especially coronavirus cases — go in the wrong direction again , experts said governments should be ready to bring back restrictions .
If states move too quickly to reopen or respond too slowly to a turn for the worse , they could see a renewed surge in Covid-19 cases .
@ @ @ @ @ @ @ planning for reopening , ” Mark McClellan , a health policy expert at Duke , told me .
“ There will be outbreaks , and there will be needs for pauses and going back — hopefully not too much if we do this carefully.
” So this will be a work in progress , at least until we get a Covid-19 vaccine or the pandemic otherwise ends , whether by natural or human means .
But the metrics can at least help give states an idea of how far along they are in @ @ @ @ @ @ @ ’ s the goal ?
A 10 percent drop in daily new coronavirus cases compared to two weeks ago and a 5 percent drop in cases compared to one week ago , based on data from the New York Times .
Which states meet the goal ?
New Jersey and Arizona — just two states .
Why is this important ?
Guidance from the White House and several independent groups emphasize that states need to see coronavirus cases drop consistently over two weeks before they can say they ’ re ready to begin @ @ @ @ @ @ @ you ’ re out of an outbreak like a sustained reduction in infections .
“ The first and foremost [ metric ] is you want to have a continued decrease in cases , ” Saskia Popescu , an infectious disease epidemiologist , told me .
“ It ’ s a huge piece.
” A simple reduction in cases compared to two weeks prior isn ’ t enough ; it has to be a significant drop , and it has to be sustained over the two weeks .
So for Vox ’ s map @ @ @ @ @ @ @ percent drop in daily new cases compared to two weeks prior and at least a 5 percent drop compared to one week prior .
Reported cases can be a reflection of testing capacity : More testing will pick up more cases , and less testing will pick up fewer .
So it ’ s important that the decrease occur while testing is either growing or already sufficient .
And since states have recently boosted their testing abilities , increases in Covid-19 cases can also reflect improvements in testing .
Even after meeting this @ @ @ @ @ @ @ If a state meets the goal of a reduction in cases compared to one and two weeks ago but cases seemed to go up in recent days , then perhaps it ’ s not time to reopen just yet .
And if cases have dropped but only from a very high baseline of cases , then that ’ s less comforting than a drop from a lower baseline .
“ You have to use common sense , ” Cyrus Shahpar , a director at the public health policy group Resolve to Save Lives @ @ @ @ @ @ @ the goal ?
Fewer than four daily new coronavirus cases per 100,000 people per day , based on data from the New York Times and the Census Bureau .
Which states meet the goal ?
Connecticut , Hawaii , Maine , Massachusetts , New Hampshire , New Jersey , New York , and Vermont — eight states .
Why is this important ?
One of the best ways to know you ’ re getting away from a disease outbreak is to no longer see a high number of daily new infections .
While @ @ @ @ @ @ @ , experts said that four daily new coronavirus cases per 100,000 people is a decent ceiling .
“ If I go from one to two to three [ coronavirus cases a day ] , it ’ s different than going from 1,000 to 2,000 to 3,000 , even though the percent difference is the same , ” Shahpar said .
“ That ’ s why you have to take into account the overall level , too.
” To put it another way , it ’ s not enough for daily new Covid-19 cases @ @ @ @ @ @ @ Cases also should fall below a certain level before a state can be deemed truly safe .
For example , Arizona has seen its daily new cases drop over the past two weeks .
But its daily new cases are still , after controlling for population , the third highest in the country .
That indicates an epidemic that remains out of control .
At the same time , if your state is now below four daily new cases per 100,000 but it ’ s seen a recent uptick in cases , that @ @ @ @ @ @ @ Even the worst-hit states , after all , began with a handful of cases before they saw an exponential surge .
But if your state is below the threshold , it ’ s in a pretty solid place relative to most states .
What ’ s the goal ?
At least 150 tests per 100,000 people per day , based on data from the Covid Tracking Project and the Census Bureau .
Which states meet the goal ?
Alabama , Alaska , Arizona , Arkansas , California , Connecticut , Delaware , Florida @ @ @ @ @ @ @ Iowa , Kentucky , Louisiana , Maine , Maryland , Massachusetts , Michigan , Minnesota , Mississippi , Missouri , Montana , Nebraska , Nevada , New Jersey , New Mexico , New York , North Carolina , North Dakota , Ohio , Oklahoma , South Carolina , Tennessee , Texas , Utah , Vermont , Virginia , Washington , West Virginia , and Wisconsin — for a total of 40 states .
Washington , DC , did as well .
Why is this important ?
Since the beginning of the coronavirus pandemic @ @ @ @ @ @ @ needs the capacity for at least 500,000 Covid-19 tests a day .
Controlling for population , that adds up to about 150 new tests per 100,000 people per day .
Testing is crucial to getting the coronavirus outbreak under control .
When paired with contact tracing , testing lets officials track the scale of the outbreak , isolate the sick , quarantine those the sick came into contact with , and deploy community-wide efforts as necessary .
Testing and tracing are how other countries , like South Korea and Germany , have managed @ @ @ @ @ @ @ reopen their economies .
The idea , experts said , is to have enough surveillance to detect embers before they turn into full wildfires .
“ States should be shoring up their testing capacity not just for what it looks like right now while everyone ’ s in their homes , but as people start to move more , ” Jen Kates , the director of global health and HIV policy at the Kaiser Family Foundation , told me .
“ As people start doing more movement , you ’ ll have to @ @ @ @ @ @ @ to come into contact with each other more.
” The 500,000-a-day goal is the minimum .
Some experts have recommended as many as millions of tests nationwide each day .
But 500,000 is the most often-cited goal , and it ’ s , at the very least , a good start .
It ’ s preferable if states report this number by how many people they ’ ve tested , not just the total number of tests .
For containing an outbreak , it ’ s generally more useful to test 500,000 people @ @ @ @ @ @ @ 500,000 times .
But some states report the figures for total tests , not the number of tested individuals — counting tests for a single person multiple times .
That could skew the numbers .
This goal is also supposed to be for diagnostic tests , not antibody tests .
Diagnostic tests gauge whether a person has the virus in their system and is , therefore , sick right at the moment of the test .
Antibody tests check if someone ever developed antibodies to the virus to see if they had ever @ @ @ @ @ @ @ diagnostic tests give a more recent gauge of the level of infection , they ’ re seen as much more reliable for evaluating the current state of the Covid-19 outbreak in a state .
But some states have mixed up numbers for diagnostic and antibody tests , which could skew the data collected by the Covid Tracking Project .
“ The virus isn ’ t going to care whether they were manipulating the numbers or not in order to look more favorable ; it ’ s going to continue to spread , ” @ @ @ @ @ @ @ the Johns Hopkins Center for Health Security , told me .
“ It ’ s better to really understand what ’ s going on and report that accurately.
” For states honestly reporting these numbers , though , they ’ re a critical measure of their ability to detect , control , and contain coronavirus outbreaks .
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 .
Which states meet the goal ?
Alaska @ @ @ @ @ @ @ Illinois , Maine , Massachusetts , Michigan , Minnesota , Montana , New Hampshire , New Jersey , New Mexico , New York , Rhode Island , Vermont , and West Virginia — for a total of 17 states .
Washington , DC , did as well .
Why is this important ?
The positive or positivity rate , which tracks how many tests come back positive for Covid-19 , is another way to measure testing capacity .
Generally , a higher positive rate suggests there ’ s not enough testing happening .
@ @ @ @ @ @ @ testing lots and lots of people , many of whom don ’ t have the disease or don ’ t show severe symptoms .
The positive testing rate in South Korea , for example , is below 2 percent .
High positive rates indicate only people with obvious symptoms are getting tested , so there ’ s not quite enough testing to match the scope of an outbreak .
Previously , the World Health Organization ( WHO ) recommended a maximum positive rate of 10 percent .
But the WHO more recently recommended @ @ @ @ @ @ @ with the rate for countries that have managed to better control their outbreaks , like Germany , New Zealand , and South Korea .
“ Even lower is better , ” Shahpar said .
The positive rate data is subject to the same limitations as the overall testing data from the Covid Tracking Project .
So if a state includes antibody tests in its test count , it could skew the positive rate to look better than it is .
States only risk hurting themselves if they do this .
What ’ s @ @ @ @ @ @ @ 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 , Illinois , Indiana , Iowa , Kansas , Kentucky , Maryland , Montana , Nebraska , New Jersey , New York , North Dakota , Ohio , Oregon , Utah , and Wisconsin — for a total of 19 states .
Washington , DC , did as well .
Why is this important ?
If a pandemic hits , the @ @ @ @ @ @ @ to treat the most severe cases and potentially save lives .
That ’ s the key goal of “ flattening the curve ” and “ raising the line , ” in which social distancing helps reduce the spread of the disease so the health care system can maintain and grow its capacity to treat an influx of Covid-19 patients .
“ There ’ s this idea that in six weeks we can open more things , ” Amesh Adalja , a senior scholar at the Johns Hopkins Center for Health Security , told @ @ @ @ @ @ @ still there .
It ’ s all about making sure that the case count isn ’ t too immense for our hospital system to deal with.
” The aim is to avoid the nightmare scenario that Italy went through when it had more Covid-19 cases than its health care system could handle , leading to hospitals turning away even dangerously ill patients .
To gauge this , experts recommended looking at ICU capacity , with states aiming to have at most 60 percent occupancy in their ICUs .
Hitting the benchmarks is the @ @ @ @ @ @ @ s map is just one way of tracking success against the coronavirus .
Other groups have come up with their own measures , including Covid Act Now , Covid Exit Strategy , and Test and Trace .
Vox ’ s model uses more up-to-date data than some of these other examples , while focusing not just on the state of the pandemic but also on states ’ readiness to contain Covid-19 outbreaks in the future .
Very few states hit all the marks recommended by experts .
But even those that do shouldn @ @ @ @ @ @ @ They should continue to improve — for example , getting the positive rate below 1 percent , as in New Zealand — and look at even more granular metrics , such as at the city or county level .
Meeting the benchmarks , however , indicates a state is better equipped to contain future coronavirus outbreaks as it eases previous restrictions .
Experts emphasized that states have to keep hitting all these goals week after week and day after day — Covid-19 cases must remain low , testing ability needs to stay high @ @ @ @ @ @ @ enough for an influx of patients — until the pandemic is truly over , whether thanks to a vaccine or other means .
Otherwise , a future wave of coronavirus cases , as seen in past pandemics , could kill many more people .
“ You need to have all the metrics met , ” Popescu said .
“ This needs to be a very incremental , slow process to ensure success.
” And if the numbers do start trending in the wrong direction , states should be ready to shut down at @ @ @ @ @ @ @ .
Maybe not as much as before , as we learn which places are truly at risk of increasing spread .
But experts caution that future shutdowns will likely be necessary to some extent .
“ I do worry we ’ re going to see surges of cases and hot spots , ” Watson said .
“ We do need to keep pushing on building those capacities .
… Otherwise , we ’ re just rolling the dice on the spread of the virus .
It ’ s better if we have more @ @ @ @ @ @ @ s another reason these metrics , along with broader coronavirus surveillance , are so important : They not only help show how far along states are in dealing with their current Covid-19 outbreaks , but will help track progress to stop and prevent future crises as well .
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 @ @ @ @ @ @ @ understanding .
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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 .
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All 50 states have moved to reopen their economies, at least partially, after shutting down businesses and gatherings in response to the coronavirus pandemic.
But a Vox analysis suggests that most states haven’t made the preparations needed to contain outbreaks — putting themselves at risk for a rise in Covid-19 cases and deaths should they continue to reopen. Some states have already had to backtrack on reopening measures.
Experts told me states need three things to be safe to open. State leaders, from the governor to the legislature to health departments, need to ensure the SARS-CoV-2 virus is no longer spreading unabated. They need the testing capacity to track and isolate the sick and their contacts. And they need the hospital capacity to handle a potential surge in Covid-19 cases.
More specifically, states should meet at least five basic criteria. They should see a two-week drop in coronavirus cases, indicating that the virus is actually abating. They should have fewer than four daily new cases per 100,000 people per day — to show that cases aren’t just dropping but are also below dangerous levels. They need at least 150 new tests per 100,000 people per day, letting them quickly track and contain outbreaks. They need an overall positive rate for tests below 5 percent — another critical indicator for testing capacity. And states should have at least 40 percent of their ICU beds free to actually treat an influx of people stricken with Covid-19 should it be necessary.
These metrics line up with a range of expert recommendations, as well as the various policy plans put out by both independent groups and government officials to deal with the coronavirus.
Meeting these metrics doesn’t mean that a state is ready to safely reopen its economy — a process that describes a wide range of local and state actions. And failing them doesn’t mean a state is in immediate danger of a coronavirus outbreak if it starts to reopen; with Covid-19, there’s always an element of luck and other factors.
But with these metrics, states can gauge if they have repressed the coronavirus while building the capacity to contain future outbreaks should they come. In other words, the benchmarks show how ready states are for the next phase of the fight.
So far, most states are not there. Just four states — Colorado, Connecticut, New Jersey, and New York — met four or five of the goals, which demonstrates strong progress. Twenty-five states and Washington, DC, hit two or three of the benchmarks. The remaining 19 achieved zero or one. (Alabama and Florida are excluded due to recent issues with test reporting.)
Even the states that have made the most progress aren’t safe to fully reopen. Without a vaccine or similar treatment, the threat of the coronavirus is still out there. Especially in states that suffered big outbreaks, such as Arizona and New York, even a lot of progress or some progress doesn’t mean all the underlying problems that led to an epidemic are gone.
Nor do the metrics cover everything that states should do before they can safely reopen. They don’t show, for example, if states have the capacity to do contact tracing, in which people who came into contact with someone who’s sick with Covid-19 are tracked down by “disease detectives” and quarantined. Contact tracing is key to containing an epidemic, but states don’t track how many contact tracers they’ve hired in a standardized, readily available way.
States also don’t have ready data for health care workers’ access to personal protective equipment, such as masks and gloves — a critical measure of the health care system’s readiness that’s difficult to track.
But the map gives an idea of how much progress states have made toward containing the coronavirus and keeping it contained.
States will have to follow these kinds of metrics as they reopen. If the numbers — especially coronavirus cases — go in the wrong direction again, experts said governments should be ready to bring back restrictions. If states move too quickly to reopen or respond too slowly to a turn for the worse, they could see a renewed surge in Covid-19 cases.
“Planning for reclosing is part of planning for reopening,” Mark McClellan, a health policy expert at Duke, told me. “There will be outbreaks, and there will be needs for pauses and going back — hopefully not too much if we do this carefully.”
So this will be a work in progress, at least until we get a Covid-19 vaccine or the pandemic otherwise ends, whether by natural or human means. But the metrics can at least help give states an idea of how far along they are in the fight against the coronavirus.
Goal 1: A sustained two-week drop in coronavirus cases
What’s the goal? A 10 percent drop in daily new coronavirus cases compared to two weeks ago and a 5 percent drop in cases compared to one week ago, based on data from the New York Times.
Which states meet the goal? Arizona, California, Colorado, Georgia, Mississippi, Nevada, Oregon, Texas, and Wyoming — a total of nine states.
Why is this important? Guidance from the White House and several independent groups emphasize that states need to see coronavirus cases drop consistently over two weeks before they can say they’re ready to begin reopening. After all, nothing shows you’re out of an outbreak like a sustained reduction in infections.
“The first and foremost [metric] is you want to have a continued decrease in cases,” Saskia Popescu, an infectious disease epidemiologist, told me. “It’s a huge piece.”
A simple reduction in cases compared to two weeks prior isn’t enough; it has to be a significant drop, and it has to be sustained over the two weeks. So for Vox’s map, states need at least a 10 percent drop in daily new cases compared to two weeks prior and at least a 5 percent drop compared to one week prior.
Reported cases can be a reflection of testing capacity: More testing will pick up more cases, and less testing will pick up fewer. So it’s important that the decrease occur while testing is either growing or already sufficient. And since states have recently boosted their testing abilities, increases in Covid-19 cases can also reflect improvements in testing.
Even after meeting this benchmark, continued caution is warranted. If a state meets the goal of a reduction in cases compared to one and two weeks ago but cases seemed to go up in recent days, then perhaps it’s not time to reopen just yet. And if cases have dropped but only from a very high baseline of cases, then that’s less comforting than a drop from a lower baseline.
“You have to use common sense,” Cyrus Shahpar, a director at the public health policy group Resolve to Save Lives, told me.
Goal 2: A low number of daily new Covid-19 cases
What’s the goal? Fewer than four daily new coronavirus cases per 100,000 people per day, based on data from the New York Times and the Census Bureau.
Which states meet the goal? Connecticut, Maine, New Hampshire, New Jersey, New York, and Vermont — just six states.
Why is this important? One of the best ways to know you’re getting away from a disease outbreak is to no longer see a high number of daily new infections. While there’s no universally accepted number, experts said that four daily new coronavirus cases per 100,000 people is a reasonable ceiling.
“If I go from one to two to three [coronavirus cases a day], it’s different than going from 1,000 to 2,000 to 3,000, even though the percent difference is the same,” Shahpar said. “That’s why you have to take into account the overall level, too.”
To put it another way, it’s not enough for daily new Covid-19 cases to drop, even for weeks. Cases also should fall below a certain level before a state can be deemed truly safe.
For example, Arizona has seen its daily new cases drop over the past two weeks. But its daily new cases are still, after controlling for population, the third-highest in the country. That indicates an epidemic that remains out of control.
At the same time, if your state is now below four daily new cases per 100,000 but it’s seen a recent uptick in cases, that’s a reason for caution. Even the worst-hit states, after all, began with a handful of cases before they saw an exponential surge.
But if your state is below the threshold, it’s in a pretty solid place relative to most states.
Goal 3: High coronavirus testing capacity
What’s the goal? At least 150 tests per 100,000 people per day, based on data from the Covid Tracking Project and the Census Bureau.
Which states meet the goal? Alaska, Arkansas, California, Colorado, Connecticut, Delaware, Georgia, Hawaii, Illinois, Indiana, Iowa, Kentucky, Louisiana, Maine, Maryland, Massachusetts, Michigan, Minnesota, Missouri, Montana, Nebraska, New Jersey, New Mexico, New York, North Carolina, North Dakota, Ohio, Oklahoma, Rhode Island, South Dakota, Tennessee, Texas, Utah, Vermont, Virginia, Washington, and West Virginia — 37 states. Washington, DC, did as well. (Alabama and Florida are excluded due to recent issues with test reporting.)
Why is this important? Since the beginning of the coronavirus pandemic, experts have argued that the US needs the capacity for at least 500,000 Covid-19 tests a day. Controlling for population, that adds up to about 150 new tests per 100,000 people per day.
Testing is crucial to getting the coronavirus outbreak under control. When paired with contact tracing, testing lets officials track the scale of the outbreak, isolate the sick, quarantine those the sick came into contact with, and deploy community-wide efforts as necessary. Testing and tracing are how other countries, like South Korea and Germany, have managed to control their outbreaks and started to reopen their economies.
The idea, experts said, is to have enough surveillance to detect embers before they turn into full wildfires.
“States should be shoring up their testing capacity not just for what it looks like right now while everyone’s in their homes, but as people start to move more,” Jen Kates, the director of global health and HIV policy at the Kaiser Family Foundation, told me. “As people start doing more movement, you’ll have to test more, because people are going to come into contact with each other more.”
The 500,000-a-day goal is the minimum. Some experts have recommended as many as millions of tests nationwide each day. But 500,000 is the most often-cited goal, and it’s, at the very least, a good start.
It’s preferable if states report this number by how many people they’ve tested, not just the total number of tests. For containing an outbreak, it’s generally more useful to test 500,000 people one time than to test one person 500,000 times. But some states report the figures for total tests, not the number of tested individuals — counting tests for a single person multiple times. That could skew the numbers.
This goal is also supposed to be for diagnostic tests, not antibody tests. Diagnostic tests gauge whether a person has the virus in their system and is, therefore, sick right at the moment of the test. Antibody tests check if someone ever developed antibodies to the virus to see if they had ever been sick in the past. Since diagnostic tests give a more recent gauge of the level of infection, they’re seen as much more reliable for evaluating the current state of the Covid-19 outbreak in a state.
But some states have mixed up numbers for diagnostic and antibody tests, which could skew the data collected by the Covid Tracking Project.
“The virus isn’t going to care whether they were manipulating the numbers or not in order to look more favorable; it’s going to continue to spread,” Crystal Watson, a senior scholar at the Johns Hopkins Center for Health Security, told me. “It’s better to really understand what’s going on and report that accurately.”
For states honestly reporting these numbers, though, they’re a critical measure of their ability to detect, control, and contain coronavirus outbreaks.
Goal 4: A low test positive rate
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.
Which states meet the goal? Alaska, California, Colorado, Connecticut, Delaware, Illinois, Louisiana, Maine, Maryland, Massachusetts, Michigan, New Hampshire, New Jersey, New Mexico, New York, Ohio, Oregon, Pennsylvania, Rhode Island, Vermont, Washington, West Virginia, and Wyoming — 23 states. Washington, DC, did as well. (Alabama and Florida are excluded due to recent issues with test reporting.)
Why is this important? The positive or positivity rate, which tracks how many tests come back positive for Covid-19, is another way to measure testing capacity.
Generally, a higher positive rate suggests there’s not enough testing happening. 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. The positive testing rate in South Korea, for example, is below 1 percent. High positive rates indicate only people with obvious symptoms are getting tested, so there’s not quite enough testing to match the scope of an outbreak.
Previously, the World Health Organization (WHO) recommended a maximum positive rate of 10 percent. But the WHO more recently recommended 5 percent, which is in line with the rate for countries that have managed to better control their outbreaks, like Germany, New Zealand, and South Korea. “Even lower is better,” Shahpar said.
The positive rate data is subject to the same limitations as the overall testing data from the Covid Tracking Project. So if a state includes antibody tests in its test count, it could skew the positive rate to look better than it is. States only risk hurting themselves if they do this.
Goal 5: Availability of ICU beds
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, Idaho, Illinois, Iowa, Massachusetts, Nebraska, New Hampshire, New Jersey, New Mexico, New York, North Dakota, South Dakota, Utah, Wisconsin, and Wyoming — 17 states.
Why is this important? If a pandemic hits, the health care system needs to be ready to treat the most severe cases and potentially save lives. That’s the key goal of “flattening the curve” and “raising the line,” in which social distancing helps reduce the spread of the disease so the health care system can maintain and grow its capacity to treat an influx of Covid-19 patients.
“There’s this idea that in six weeks we can open more things,” Amesh Adalja, a senior scholar at the Johns Hopkins Center for Health Security, told me. “But the virus is still there. It’s all about making sure that the case count isn’t too immense for our hospital system to deal with.”
The aim is to avoid the nightmare scenario that Italy went through when it had more Covid-19 cases than its health care system could handle, leading to hospitals turning away even dangerously ill patients.
To gauge this, experts recommended looking at ICU capacity, with states aiming to have at most 60 percent occupancy in their ICUs.
Hitting the benchmarks is the beginning, not the end
Vox’s map is just one way of tracking success against the coronavirus. Other groups have come up with their own measures, including Covid Act Now, Covid Exit Strategy, and Test and Trace. Vox’s model uses more up-to-date data than some of these other examples, while focusing not just on the state of the pandemic but also on states’ readiness to contain Covid-19 outbreaks in the future.
Very few states hit all the marks recommended by experts. But even those that do shouldn’t consider the pandemic over. They should continue to improve — for example, getting the positive rate below 1 percent, as in New Zealand — and look at even more granular metrics, such as at the city or county level.
Meeting the benchmarks, however, indicates a state is better equipped to contain future coronavirus outbreaks as it eases previous restrictions.
Experts emphasized that states have to keep hitting all these goals week after week and day after day — Covid-19 cases must remain low, testing ability needs to stay high, and hospital capacity should be good enough for an influx of patients — until the pandemic is truly over, whether thanks to a vaccine or other means. Otherwise, a future wave of coronavirus cases, as seen in past pandemics, could kill many more people.
“You need to have all the metrics met,” Popescu said. “This needs to be a very incremental, slow process to ensure success.”
And if the numbers do start trending in the wrong direction, states should be ready to shut down at least some parts of the economy again. Maybe not as much as before, as we learn which places are truly at risk of increasing spread. But experts caution that future shutdowns will likely be necessary to some extent.
“I do worry we’re going to see surges of cases and hot spots,” Watson said. “We do need to keep pushing on building those capacities. … Otherwise, we’re just rolling the dice on the spread of the virus. It’s better if we have more control of the spread.”
That’s another reason these metrics, along with broader coronavirus surveillance, are so important: They not only help show how far along states are in dealing with their current Covid-19 outbreaks, but will help track progress to stop and prevent future crises as well.
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vox--2020-07-22--Facebook is taking a hard look at racial bias in its algorithms

Facebook has announced it ’ s building teams that will study racial bias baked into the algorithms used on its platform and on Instagram , which it owns .
The move is a significant acknowledgment that the algorithms driving two of the most influential social media platforms can be discriminatory .
Instagram will create an “ equity team ” charged with tasks like analyzing the enforcement of its harassment policies and studying its algorithms for racial bias , the Wall Street Journal reports .
Facebook spokesperson Stephanie Otway told Recode that the team will continue to work with Facebook ’ @ @ @ @ @ @ @ , and added that Facebook will also create a similar equity team .
“ The racial justice movement is a moment of real significance for our company , ” Vishal Shah , a vice president of product at Instagram , said in a statement .
“ Any bias in our systems and policies runs counter to providing a platform for everyone to express themselves.
” Algorithmic bias can be pervasive and impact how a platform treats users by affecting the content and ads they see as well as the way their own posts @ @ @ @ @ @ @ spotting algorithmic bias on their own since , for example , most can ’ t necessarily compare their News Feed with those of other users .
Researchers , civil rights groups , and politicians have sounded alarm bells about algorithmic bias on its platforms , and now Facebook is devoting more resources to addressing the problem .
Notably , the Facebook news comes amid an advertising boycott of the platform organized by major civil rights groups , including the NAACP and the Anti-Defamation League , and just two weeks after the company shared @ @ @ @ @ @ @ , which panned Facebook for failing to address racism and misinformation on its site .
Ahead of the boycott , Instagram acknowledged and pledged to deal with algorithmic bias on its platforms more directly .
As demonstrations against police brutality and racism swept across the United States in mid-June , Instagram head Adam Mosseri announced that the company would look into racial bias on Instagram , including in its account verification policies and approach to content filtering and distribution .
“ While we do a lot of work to help prevent subconscious bias @ @ @ @ @ @ @ take a harder look at the underlying systems we ’ ve built , and where we need to do more to keep bias out of these decisions , ” Mosseri wrote at the time .
We don ’ t know much about the new efforts yet .
Facebook ’ s Otway emphasized that these initiatives are still in the early stages and said the new team will be charged with reviewing a wide variety of issues that marginalized groups may encounter on the Instagram platform .
As an example , she suggested that @ @ @ @ @ @ @ focus on supporting minority-owned businesses .
The company seems especially willing to invest in efforts analyzing the role of bias in its systems after its recently concluded civil rights audit highlighted two pilot programs at the company : a Facebook-built tool called Fairness Flow and a fairness consultation process launched in December .
The auditors also called for Facebook to establish “ processes and guidance designed to prompt issue-spotting and help resolve fairness concerns ” that employees company-wide must follow .
“ The company certainly has the resources to be more proactive and @ @ @ @ @ @ @ a leader , ” Kelley Cotter , a graduate student who studies public understanding of algorithms at Michigan State University , told Recode at the time of the audit .
“ That Facebook still appears to be in an ‘ exploratory ’ phase after years and years of civil rights complaints evidences its reluctance to prioritize public values like equity and justice over its private interests.
” Automated tools can discriminate in myriad ways .
Bias can be inherent in algorithms and artificial intelligence based on who builds these technologies , which assumptions @ @ @ @ @ @ @ ’ re trained , and how they ’ re ultimately deployed .
One notable source of this bias can come from data : If an algorithm is trained using a database that isn ’ t representative of a particular demographic group , it ’ s very possible the algorithm will be inaccurate when applied to people who are part of that group .
Algorithmic bias can have life-changing and dangerous impacts on people ’ s lives .
Résumé-screening algorithms can learn to discriminate against women , for example .
Facial recognition systems used @ @ @ @ @ @ @ gender biases , and they often perform worst when used to identify women with darker skin .
In June , we learned of the first known false arrest of a Black man living in Michigan caused by a facial recognition system .
On social media platforms built by Facebook , there ’ s concern that bias could show up anywhere an automated system makes decisions , including in how Instagram filters content and whose posts get flagged by Facebook ’ s content moderation bots .
There ’ s also concern that the lack @ @ @ @ @ @ @ employees could hinder its efforts to make its product more equitable .
Just under 4 percent of roles at Facebook are held by Black employees , and just over 6 percent are held by Hispanic employees , according to the company ’ s diversity report .
Facebook would not share statistics on the racial diversity of the teams that work on its algorithms and artificial intelligence .
According to Nicol Turner Lee , the director of the Brookings Institution ’ s Center for Technology Innovation , “ Without representative input , the company @ @ @ @ @ @ @ the differential treatment or disparate impacts for communities of color.
” Meanwhile , the capacity these systems have to be discriminatory is why some say the algorithms themselves need to be externally audited , which Facebook thus far has not opted to do .
Facebook “ seems to plan to keep the results of its research in-house , ” Nicolas Kayser-Bril of Algorithm Watch told Recode after the announcement of the new teams .
“ It is unlikely that , were the new ‘ equity and inclusion team ’ to make claims regarding @ @ @ @ @ @ @ researchers will be able to verify them.
” After all , Facebook can say it ’ s improving its algorithms again and again , but it ’ s not clear how those outside the company , including Facebook and Instagram users , would ever know if the changes were actually making an overall difference .
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Facebook has announced it’s building teams that will study racial bias baked into the algorithms used on its platform and on Instagram, which it owns. The move is a significant acknowledgment that the algorithms driving two of the most influential social media platforms can be discriminatory.
Instagram will create an “equity team” charged with tasks like analyzing the enforcement of its harassment policies and studying its algorithms for racial bias, the Wall Street Journal reports. Facebook spokesperson Stephanie Otway told Recode that the team will continue to work with Facebook’s Responsible AI team to study bias, and added that Facebook will also create a similar equity team.
“The racial justice movement is a moment of real significance for our company,” Vishal Shah, a vice president of product at Instagram, said in a statement. “Any bias in our systems and policies runs counter to providing a platform for everyone to express themselves.”
Algorithmic bias can be pervasive and impact how a platform treats users by affecting the content and ads they see as well as the way their own posts get filtered. Users can have trouble spotting algorithmic bias on their own since, for example, most can’t necessarily compare their News Feed with those of other users. Researchers, civil rights groups, and politicians have sounded alarm bells about algorithmic bias on its platforms, and now Facebook is devoting more resources to addressing the problem.
Notably, the Facebook news comes amid an advertising boycott of the platform organized by major civil rights groups, including the NAACP and the Anti-Defamation League, and just two weeks after the company shared the results of its civil rights audit, which panned Facebook for failing to address racism and misinformation on its site.
Ahead of the boycott, Instagram acknowledged and pledged to deal with algorithmic bias on its platforms more directly. As demonstrations against police brutality and racism swept across the United States in mid-June, Instagram head Adam Mosseri announced that the company would look into racial bias on Instagram, including in its account verification policies and approach to content filtering and distribution.
“While we do a lot of work to help prevent subconscious bias in our products, we need to take a harder look at the underlying systems we’ve built, and where we need to do more to keep bias out of these decisions,” Mosseri wrote at the time.
Related Why algorithms can be racist and sexist
We don’t know much about the new efforts yet. Facebook’s Otway emphasized that these initiatives are still in the early stages and said the new team will be charged with reviewing a wide variety of issues that marginalized groups may encounter on the Instagram platform. As an example, she suggested that the company will get behind tools that focus on supporting minority-owned businesses.
The company seems especially willing to invest in efforts analyzing the role of bias in its systems after its recently concluded civil rights audit highlighted two pilot programs at the company: a Facebook-built tool called Fairness Flow and a fairness consultation process launched in December. The auditors also called for Facebook to establish “processes and guidance designed to prompt issue-spotting and help resolve fairness concerns” that employees company-wide must follow.
“The company certainly has the resources to be more proactive and aggressive in its actions, to be a leader,” Kelley Cotter, a graduate student who studies public understanding of algorithms at Michigan State University, told Recode at the time of the audit. “That Facebook still appears to be in an ‘exploratory’ phase after years and years of civil rights complaints evidences its reluctance to prioritize public values like equity and justice over its private interests.”
Automated tools can discriminate in myriad ways. Bias can be inherent in algorithms and artificial intelligence based on who builds these technologies, which assumptions are programmed into them, how they’re trained, and how they’re ultimately deployed. One notable source of this bias can come from data: If an algorithm is trained using a database that isn’t representative of a particular demographic group, it’s very possible the algorithm will be inaccurate when applied to people who are part of that group.
Algorithmic bias can have life-changing and dangerous impacts on people’s lives. Résumé-screening algorithms can learn to discriminate against women, for example. Facial recognition systems used by police can also have racial and gender biases, and they often perform worst when used to identify women with darker skin. In June, we learned of the first known false arrest of a Black man living in Michigan caused by a facial recognition system.
On social media platforms built by Facebook, there’s concern that bias could show up anywhere an automated system makes decisions, including in how Instagram filters content and whose posts get flagged by Facebook’s content moderation bots.
There’s also concern that the lack of racial diversity among Facebook’s employees could hinder its efforts to make its product more equitable. Just under 4 percent of roles at Facebook are held by Black employees, and just over 6 percent are held by Hispanic employees, according to the company’s diversity report. Facebook would not share statistics on the racial diversity of the teams that work on its algorithms and artificial intelligence. According to Nicol Turner Lee, the director of the Brookings Institution’s Center for Technology Innovation, “Without representative input, the company may find itself generating trade-offs that further the differential treatment or disparate impacts for communities of color.”
Meanwhile, the capacity these systems have to be discriminatory is why some say the algorithms themselves need to be externally audited, which Facebook thus far has not opted to do.
Facebook “seems to plan to keep the results of its research in-house,” Nicolas Kayser-Bril of Algorithm Watch told Recode after the announcement of the new teams. “It is unlikely that, were the new ‘equity and inclusion team’ to make claims regarding discrimination or the remediation thereof, independent researchers will be able to verify them.”
After all, Facebook can say it’s improving its algorithms again and again, but it’s not clear how those outside the company, including Facebook and Instagram users, would ever know if the changes were actually making an overall difference.
Open Sourced is made possible by Omidyar Network. All Open Sourced content is editorially independent and produced by our journalists.