For more than two years, the daily count of new Covid-19 infections has been how most people understood the trajectory of the pandemic.

Now, experts say, daily case counts don't mean what they used to — making them a much more flawed metric. People should still take precautionary measures against Covid, but for an otherwise healthy person, the average case isn't nearly as serious as it once was: The majority of Americans are now vaccinated, and recent variants and subvariants are causing less severe forms of illness.

That's good news, of course, but it does make it harder to gauge your pandemic risk levels these days. When is indoor dining a safe bet, and when should you order takeout? Should you go to the movies this weekend or wait for the current Covid wave to die down?

Daily case counts can't answer those questions on their own anymore. Luckily, experts say there's a series of metrics you can track alongside daily cases to help you make those types of informed decisions. Here's what you need to know:

How daily case counts can still be useful

Dr. Andrew Noymer, an epidemiologist and associate professor of population health and disease prevention at the University of California, Irvine, says that daily case counts can still be useful — as long as you know how to read them.

First: Focus on local cases in your area rather than national data, "because the timing of various peaks and valleys differs from place to place," Noymer tells CNBC Make It. You can track local Covid data on the Centers for Disease Control and Prevention's (CDC) county-level Covid Data Tracker, alongside most state and county health department websites.

From there, Noymer recommends "looking at trends" — like comparing cases from one week to the next — rather than the specific numbers.

"When things get worse, we should change our behavior," he says. "At that point, masking in public indoor spaces is something that people should definitely consider. It's relatively easy to do, and we know it works."

You should also track hospitalizations and ICU numbers

Hospitalization statistics — including the number of people in intensive care units (ICU) — are an indication of the severity of Covid-19 infections in your area. But don't take them at face value, Noymer says: These stats include so-called "incidental cases," which occur "when a person is hospitalized for something else, like hernia repair, then tests positive for Covid."

That's why Noymer recommends looking at hospitalization and ICU numbers in tandem. In Orange County, California, where he's based, hospitalizations have been "swelling" recently, while ICU numbers "have been quite low and stable," he says. "I've used that to infer that most of the a lot of the hospitalizations are actually incidental cases, and Covid infections aren't as serious as before."

You might also want to watch local hospitalization and ICU numbers for your specific age group, to better evaluate your own personal risk at any given time. It's a tactic endorsed by Dr. Jason Wilson, an emergency medicine physician at Tampa General Hospital and professor at the University of South Florida, who says it can help you "get a sense of how serious cases are at a given time."

You probably don't need to pay close attention to death rates while assessing your current level of risk. They're a "lagging indicator," Noymer says — meaning they're better at showing how bad the pandemic was a couple weeks ago, rather than right now.

The 'percent positive' metric can also be helpful in small doses

Throughout the pandemic, the percent positive — also known as the "positivity rate" — has been used to gauge the severity of a Covid-19 outbreak in a particular location.

There's a common misconception that the figure refers to the percentage of people who have tested positive for Covid out of an entire population. In reality, it's the percentage of people who tested positive out of the number of people who got tested.

That makes it a difficult stat to interpret. Earlier in the pandemic, every test result was reported to agencies like the CDC. Now, the testing numbers sent to government agencies largely come from the PCR tests people take to confirm their positive at-home test results.

Percent positive rates can also have different meanings in different localities, depending on the prevalence of Covid testing across various pockets of the U.S. So to learn the most from this metric, Noymer suggests looking at how it changes "over relatively short time frames, in the same place."

In other words, the actual numbers for this metric aren't really that helpful. Instead, pay attention to whether the positivity rate in your area rises or falls from week-to-week.

Think of these metrics like the weather

Moving forward, Wilson suggests using Covid metrics like a weather forecast: not a guarantee, but a tool for assessing your risk and taking the necessary precautions.

Get in the habit of checking these Covid measures regularly, he says — especially when getting Covid and having to quarantine would adversely affect your upcoming plans. After all, you wouldn't consult the weather forecast once and then assume that condition will remain the same for the rest of the month.

Similarly, Wilson says, checking multiple Covid metrics provides a more complete picture of your risk, the way that looking at temperature, humidity, and forecasted precipitation says more about the weather than the temperature alone.

"This is a good analogy for how we're probably going to deal with Covid in the indefinite future," he says. "It'll help us make reasonable decisions."

Wilson recommends bookmarking the CDC's county-level data tracker. Enter your state and then your county to bring up a page of Covid metrics, along with a dashboard that displays a color-coded level of risk — green for low, yellow for medium, orange for high — and recommended precautions for each level.

"It's a quick-glance tool that can help you understand how to be a little safer at a given time," says Wilson. "If I look at the CDC dashboard and see orange, I'm putting a mask on when I go to any indoor spaces."

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