Is statistics the prize weapon in the Zika arms race?

International political wrangling is stymieing progress in fighting Zika at the cost of a swelling number of infected pregnant women. With no vaccine or medicine to treat the virus, do statisticians hold the answer?

Jessica J Steventon
8 September 2016

Microcephaly is associated with the Zika virus.

Politics and disease epidemics historically do not mix well, and the Zika virus is no exception. Despite the World Health Organisation declaring Zika a global 'public health emergency', the response time of key political leaders is currently hampered by the divisive politics of reproductive health and abortion.In the United States, where there are almost 3,000 Zika cases to date, members of the Republican-held Congress have been accused of dragging their feet when it comes to releasing funds. In response, President Obama’s administration has been forced to repurpose money intended to protect against Ebola to the mosquito-borne Zika epidemic.

What most people don’t realise is that for each new virus, we are effectively starting from scratch

The human cost of such political tardiness is an ever growing number of babies (1,800 in Brazil with 21 cases in the US*) born with microcephaly, a congenital condition associated with abnormal brain development. The virus has swept through the Americas at an alarming rate -- in less than a year Zika has transformed from a mild medical curiosity to a global wrecking ball for public health. Babies born with microcephaly often suffer with blindness, seizures and cognitive, speech and motor problems as they develop. Establishing a link between microcephaly and Zika as quickly as possible was crucial for public health, and was aided by mathematical modeling, a technique increasingly applied in disease epidemics.Twenty countries or territories are now reporting cases of presumed Zika-related microcephaly, according to the World Health Organization, and scientists are warning that the explosive spread of Zika presents a greater challenge than Ebola and even SARS.

As part of the British Science Festival, oD spoke to Dr Adam Kucharski, an assistant professor at the London School of Hygiene and Tropical Medicine, about the challenges faced by statisticians in the fight to predict the transmission and spread of infectious diseases such as Zika. 

A magic number of disease control

“The whole field of mathematical modeling first started over a hundred years ago with malaria,” Kucharski told me.

“One of the things statistical modeling can do is look at how quickly we think the outbreak will be over, and that will make a big difference on how you treat the clinical situation.”

A single number, known as the basic reproduction number, can inform on how rapidly a disease will spread, and how hard it will be to control an epidemic. The number tells us for each infected person, how many secondary people will go on to be infected. Any number above one is worrisome, as it means the disease will spread across an uninfected population unless it is contained.

Knowing the reproduction number is vital for public health agencies, such as the Center for Disease Control and Prevention. With Ebola in West Africa, the reproduction number was somewhere between one and two. Alarmingly, for Zika, this number is between two and four.

This high number explains why Zika has spread so rapidly, which makes developing a vaccine less likely.

No time for a vaccine?

Even when money and science collide and efforts to make a vaccine are fast-tracked, new vaccines take many months or years to develop and safety test, by which time, the virus may have burnt through a population and begun to die out. In reality, this can mean that there are an insufficient number of cases to be able to test if the hard-sought vaccine works.

“What most people don’t realise is that for each new virus, we are effectively starting from scratch,” Kucharski said. “You have to design your trial to fit the epidemic, which is where maths can help.”


Zika is reported in 70 countries and territories as of August 2016

Thus it seems, one size does not fit all when it comes to infectious diseases. The conditions are constantly changing with time, which will affect the spread of the disease and the most effective response.

Zika represents an enduring game of cat-and-mouse played out with statisticians and health professionals.

“It’s a race against time, every delay can cost us exponentially more due to how diseases spread,” Kucharski said.

Whereas Ebola cases are fairly straightforward to identify due to the overt symptoms, Zika is more subtle, and a reliable and rapid diagnostic test is still missing. The virus is difficult to confirm as it only shows up on a diagnostic blood test for a very short period of time often before obvious symptoms, such as a rash, appear. Looking for antibodies that react to Zika is also a challenge as Zika cross-reacts with many other viruses. This makes it difficult for scientists to even identify where the cases are in the first instance. 

Once a large wave of cases has been identified, traditional isolation methods do not work for Zika as the virus is predominantly transmitted via mosquitos. Efforts to eradicate Zika-carrying mosquitos are fraught with ethical, logistical and environmental issues and, so far, has not been achieved. Human sexual transmission of the virus can also occur and is of concern given that many Zika hot spots are desirable tourist and honeymoon destinations.

READ MORE: Climate change increases risk of Zika virus

Using maths to fight disease spread is not new. What is new is the exponentially increasing computing power offered by modern technology. This enables increasingly complex statistical models to better predict future events in record time. In time-critical events such as an infectious disease outbreak, maths represents a high-powered weapon in the armoury that is increasingly being realised internationally.

The unprecedented scale of the Ebola crisis, and the rapid spread of the Zika virus both highlight the need for better evidence to guide more effective responses to contain such disasters. Better evidence requires better funding, and here lies the bureaucratic nightmare that too often delays the ability to defuse the ticking time tomb of infectious disease, with a devastating human toll.

*statistics correct as of August 2016.

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