A friend of mine, another journalist, texts me every few days with the latest coronavirus case and deaths from Singapore. Monday: “Singapore now has 28,000 cases and 22 deaths.” I checked the Johns Hopkins dashboard on Wednesday morning to confirm: 29,364 confirmed Covid-19 cases and still only 22 deaths.
We are all amateur epidemiologists now, and my boyfriend’s fascination with Singapore is all about the remarkably low mortality rate in the country. Based on those numbers, only 0.07 percent of people in Singapore who contracted the coronavirus died from it. Compare that to the United States, where more than 6 percent of confirmed Covid-19 cases have resulted in death.
To look at it differently, this chart compares the total Covid-19 deaths per million people in both countries:
The US is trying to bend the curve. Singapore doesn’t even have a bend to speak of. What is happening?
To begin with, to go back to my friend’s obsession with death rates, that’s a very rough measure. They are extremely vulnerable to variations in tests because the denominators in this equation are confirmed cases – i.e. positive tests. The US and Singapore are interesting examples that demonstrate the usefulness and limitations of this statistic.
The United States almost certainly counts its Covid-19 cases because of too little testing. The actual death rate from infections in the US – the total number of deaths divided by the actual number of infections, confirmed or unconfirmed – is much less than 6 percent. But it is also effectively impossible to know the actual mortality rate at this time, because a not insignificant number of people infected with Covid-19 do not show serious symptoms and therefore are never tested.
Conversely, the death rate in Singapore can be so low because it tests many people with mild or no symptoms.
The country has escalated because of the Covid-19 outbreaks in the dormitories where many of the low-paid migrant workers live in Singapore. You may recall that in late March the island appeared to have controlled Covid-19. Drawing on the lessons of the SARS outbreak in 2003, the country has implemented a rapid testing and tracing program, limiting travel to Singapore and requiring self-quarantines.
But then things started to rise again – almost entirely because of infections among migrant workers, who live together in tightly packed dormitories on the outskirts of the city. When the second wave started to emerge in Singapore in mid-April, about 90 percent of the new cases were found to be foreign workers living in the dormitories.
Therefore, Singapore has implemented a new screening program with the aim of effectively testing every employee living in those facilities. It tests thousands of workers every day, whether or not they show Covid-19 symptoms.
These people are generally young; they have come to Singapore to work on construction projects or in manufacturing or health care. And we know that the mortality rates of Covid-19 among young people are generally much lower than among seniors.
So if you want to understand why the death rate in Singapore is so persistently low, part is a coincidence: the groups of people who got sick had a lower risk of dying. But equally important – if not more important – is the prevalence of testing and the country’s focus on testing these younger and sometimes asymptomatic people.
“This program has likely identified cases that would not otherwise have been presented to healthcare centers for diagnosis,” Ooi Eng Eong, deputy director of the Emerging Infectious Diseases Program at Duke-National University of Singapore Medical School, told email.
That increases the total number of cases, the denominator used to calculate the case’s death rate. Singapore’s tests are skewed by the emphasis on migrant halls, and the country appears to have largely avoided the Covid-19 outbreaks in its nursing homes where more frail older people live.
“While the screening program led to more cases being reported than when case detection was limited to cases that met the COVID-19 case definition, it also expanded the denominator in the death rate calculation: the number of fatalities divided by the total number cases, “he said.
So now you might be wondering why there was an outbreak in these dormitories for migrant workers. It seems to have been a bit of a random chance. The New York Times reported that government officials believed that someone may have picked up the virus in a nearby shopping center preferred by migrant workers. Or they may have been contaminated on a construction site linked to a small cluster of cases. Or both.
Anyway, once the coronavirus arrived at the dorms, it flourished in the living quarters where as many as 20 people share a room. The poor health coverage for migrant workers – depending on their employers, who are keen to limit their financial liability – may also have prevented people from seeking care, allowing the virus to spread before public health authorities could detect it.
This cascade of unpredictable events reminded me a post that my colleague Brian Resnick wrote on Wednesday morning about the chaos theory and the inherent uncertainty of a pandemic:
There is simple mechanics that help me understand the many possible futures we face with the Covid-19 pandemic.
It is the double pendulum and as a physical object it is very simple: one pendulum (a string and a weight) is attached to the bottom of another. The movement is explained by the laws of motion written by Isaac Newton hundreds of years ago.
But small changes in the initial state of the pendulum – say it starts to swing from a slightly higher height, or if the weight of the pendulum balls is slightly heavier, or one of the pendulum arms is slightly longer than the others – leads to vastly different outcomes which are very difficult to predict.
Brian points out that the coronavirus pandemic is even more complicated than the double-pendulum model. It makes the future very difficult to predict.
It’s a complicated recipe, and it’s difficult, if not impossible, to isolate one ingredient that explains why the death rate is so much worse in the US than in Singapore.
But that doesn’t mean we don’t know anything. And the Singapore example meets certain expectations we already have for the disease.
Singapore may be grateful that the worst outbreaks have been in dormitories full of young workers rather than nursing homes, as we’ve seen in the United States and Europe. Certain credit is also due to Singapore’s testing and tracking programs, travel restrictions and strong health care system (despite the differences for migrant workers).
Some of these things could apply in America: the country could better test and track, and it could build a stronger health system. The U.S. has a relatively young population compared to other countries, which is why more testing could potentially reveal a more widespread outbreak – and, paradoxically, a lower death rate – than the current data suggests.
But the coronavirus has already infiltrated nursing homes in the U.S. It is little comfort for seniors and their families, nor for younger people who have become very ill or deceased, to know that the mortality rate is closer to 1 percent (or less) than 6 percent if we only tested younger people and found people who are infected but have no or mild symptoms. Bad luck and a bad first reaction have already distinguished the American outbreak from the one in Singapore.
Each country’s coronavirus experience is a reflection of factors under its control and then of chaos and random happiness beyond the control of anyone, not even Singapore. The same goes for each individual’s risk, a complicated mess of their race, age, economic status, pre-existing medical conditions and biology that science is only just beginning to understand.
I plan to send this article to my friend. I hope it gives some insight into his question. But I don’t expect it to be completely satisfactory either. There is simply too much uncertainty for that.
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