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“Flatten the curve” is a familiar refrain, but it bears repeating. Like any outbreak, COVID-19 will reach a peak number of concurrent cases—the top of the curve—before dissipating into a downward trajectory.

If we did nothing to slow the spread, the peak would far exceed the capacity of current health systems. The influx of COVID-19 emergencies would overwhelm health workers and hospital beds, and leave thousands upon thousands without care.

Where possible, we are implementing social distancing measures—alongside handwashing, disinfection, and protective personal equipment (particularly for health workers)—in order to slow the spread, lower the peak, and ensure health care systems can meet patient needs throughout the pandemic. Think of flattening the curve like downgrading from a fast-moving hurricane to a plodding tropical storm.

Tragically, social distancing is most difficult to implement for those that most need its protective benefit—people living in crowded urban areas, refugee camps, and areas with poor sanitation access. That social distancing is an accessible option for��some��people in��some��places—but not for those who need it most—is clear evidence of the health inequity PATH works to address.

It’s likely that more severe cases are being tested and reported, while mild and asymptomatic cases go untested. We know the disease is��more��common and��less��severe than current numbers indicate, but we don’t yet know by how much. We also don’t know the extent to which mild or asymptomatic cases are advancing the spread and carrying it to those at higher risk.

Testing limitations have hampered our ability to get the numbers that would best inform decisions about where and when to tighten (or loosen) protective measures.

To get a fuller picture of COVID-19, we need a tool called a serologic diagnostic (one is in development now). Rather than identifying a virus when a person is��currently��sick, a serologic diagnostic can detect whether a person was��previously��infected—even after the disease has resolved. With this information, we can begin to understand the proportion of the population that is being infected over time.

Even in places where the disease is most common, reported cases are currently at about 1 in every 500 people. Worst-case scenario modeling predicts up to 80% of the world population will be infected. That would be 400 in every 500. So, where are we right now?

If there is relatively little asymptomatic infection, then we are still at the very beginning of the curve and have a long way to go. To the extent more of us have been infected, communities are building herd immunity. This can be part of our strategy for moving forward, even in the near term.

Unfortunately, we just don’t know. Many unanswered questions remain about how COVID-19 will behave in these settings. How will the younger populations on the African continent affect transmissibility? What will be the effect of higher ambient temperatures? How much of the disease will be reported by surveillance systems, and how well will they track the spread? Ultimately, how successfully will these regions be able to flatten the curve and allow their health system to cope?

This is all difficult—if not impossible—to predict. Fortunately, we are already seeing national preparedness investments paying off. And PATH is supporting country partners throughout these regions as they use new and existing disease-agnostic tools for COVID-19.

For example, in Senegal,����by utilizing and expanding existing systems originally developed for Ebola and malaria. In Vietnam,��, and community-based surveillance systems that enable targeted response.

In the long-term, these health system strengthening efforts will play a vital role in responding to future outbreaks beyond COVID-19.

In Vietnam, PATH and partners leveraged existing systems to create new online COVID-19 reporting forms in just nine days. Decision-makers used the data in real time to inform strategy. Here, PATH’s Ngo Tuan reviews the data. Photo: PATH.

5. Are we tracking the right health system indicators?

It’s increasingly obvious that measuring health system capacity should be at the top of our COVID-19 surveillance priorities. Since our goal is to ensure capacity matches patient need, we need to measure things like hospital and ICU admissions and the need for oxygen.

These are relatively simple measures to put in place, but time is of the essence. This pandemic is unprecedented in our lifetimes. Let the same be said for the global collaboration that comes next.

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