Prevention Trumps Cure

In our fight against infectious disease, new technologies and lessons learnt promise to help us contain the spread of infectious disease more effectively. But what if we could prevent disease outbreaks altogether?

Rapid urbanization, overcrowding and climate change are drivers of disease that must be addressed to prevent future outbreaks. Jeffrey Millstein

Pub­lic health experts had been warn­ing for years that a new pan­dem­ic was long over­due, but when Covid-19 final­ly arrived it still found most gov­ern­ments unpre­pared. This glob­al out­break, if noth­ing else, will have focused minds on how best to pre­vent the next one. One of the basic ele­ments is decid­ing which dis­eases to focus on. The World Health Orga­ni­za­tion (WHO) main­tains a list of pri­or­i­ty dis­eases for research and devel­op­ment. There is a vast num­ber of poten­tial pathogens but only lim­it­ed resources, so the list includes only those thought to pose the great­est poten­tial pub­lic health threat, whether through their epi­dem­ic poten­tial or the fact that there are still few coun­ter­mea­sures in place.

At the end of WHO’s priority disease list sits Disease X.

Beside Covid-19, it cur­rent­ly includes SARS, MERS, Ebo­la, Las­sa fever and Rift Val­ley fever. With this list as its base, the WHO’s R&D Blue­print is a glob­al strat­e­gy and pre­pared­ness plan that pro­vides a research roadmap and tar­get prod­uct pro­files for each dis­ease. “The roadmaps iden­ti­fy key inter­ven­tions, as well as impor­tant R&D gaps,” says WHO spokesper­son Chris­t­ian Lind­meier. WHO reg­u­lar­ly brings togeth­er experts from a wide range of dis­ci­plines to revise which dis­eases need invest­ment and more R&D. The experts include micro­bi­ol­o­gists, clin­i­cal experts, epi­demi­ol­o­gists, pub­lic health pol­i­cy experts, vet­eri­nar­i­ans, anthro­pol­o­gists, bioethi­cists, and bio­log­i­cal weapons experts, among oth­ers.


At the end of WHO’s pri­or­i­ty dis­ease list sits Dis­ease X. This rep­re­sents the knowl­edge that a seri­ous inter­na­tion­al epi­dem­ic could result from a pathogen cur­rent­ly unknown to cause human dis­ease. It could be a new pathogen such as the coro­n­avirus that caus­es Covid-19, a known pathogen that does not usu­al­ly cause human dis­ease epi­demics, or one that is sud­den­ly sub­ject to a change in epi­demi­ol­o­gy or path­o­genic­i­ty, like Zika. “Although we have expe­ri­enced a series of these threats, we can­not pre­dict when or how Dis­ease X will strike,” says Lind­meier. “We need to be ready with basic capa­bil­i­ties for mul­ti­dis­ci­pli­nary research and prod­uct deploy­ment in the affect­ed coun­tries so that they reach the pop­u­la­tions who need them. Access con­sid­er­a­tions must always be at the heart of all R&D efforts.”

We must reassess our relationship with the animal world if we are to reduce the risk of exposure to new pathogens.Qilai Shen/ Panos Pictures

Among the most effec­tive tools to pre­vent an epi­dem­ic are vac­cines. They bol­ster the body’s immune sys­tem and help it fight dis­ease. The prob­lem is that each vac­cine only works against a spe­cif­ic pathogen, and devel­op­ment take years. This means that in the case of a pre­vi­ous­ly unknown or a rapid­ly mutat­ing virus like Dis­ease X, pro­duc­ing a vac­cine ahead of an out­break or in its ear­ly stages has, up to now, been impos­si­ble. Plat­form tech­nolo­gies could be the solu­tion and are being deployed in the search for vac­cine for Covid-19. The Coali­tion for Epi­dem­ic Pre­pared­ness Inno­va­tion (CEPI) is lead­ing these efforts. It was found­ed in 2017 to advance vac­cines against both known threats and pre­vi­ous­ly unknown pathogens. A plat­form tech­nol­o­gy uses the same basic com­po­nents as a back­bone and can be adapt­ed for use against dif­fer­ent pathogens. The new pathogen’s genet­ic or pro­tein sequence is  sim­ply “slot­ted in,” like a video game car­tridge, to pro­duce the vac­cine.


Dis­ease X also refers to pathogens that acquire resis­tance to treat­ment. Overuse of antibi­otics and inten­sive farm­ing meth­ods have con­tributed to the growth in resis­tance, and it is now a sig­nif­i­cant glob­al threat. A grow­ing num­ber of infec­tions, from TB to pneu­mo­nia, are becom­ing hard­er to treat. Giv­en the pace at which microbes are able to evolve, the num­ber of infec­tions resis­tant to almost any avail­able antibi­ot­ic is going to grow. The UN’s Inter­a­gency Coor­di­na­tion Group on Antimi­cro­bial Resis­tance has warned that the num­ber of annu­al deaths as a result of drug-resis­tant infec­tions could reach 10 mil­lion by 2050. One tool that shows con­sid­er­able promise for pre­vent­ing drug-resis­tant out­breaks is AI. Data­bas­es con­tain­ing the genomes from dif­fer­ent strains of pathogen are grow­ing, along with infor­ma­tion about whether they were sus­cep­ti­ble to antibi­otics. Using this data, AI can allow sci­en­tists to iden­ti­fy the DNA sequences that indi­cate resis­tance. This can speed up treat­ment of dis­eases like TB.

BlueDot’s risk software

Infec­tious dis­eases can spread fast in a glob­al­ized world. BlueDot’s risk soft­ware uses flight and mobile phone data to pre­dict their dis­per­sion and impact.

Access considerations must always be at the heart of all R&D efforts.

Christian LindmeierChristian Lindmeier
WHO spokesperson

Nor­mal­ly it takes a series of time-con­sum­ing tests to deter­mine whether a patient has mul­tidru­gre­sis­tant TB, but if the genet­ic code of the bac­teri­um is known, the patient could be pre­scribed the right drugs more quick­ly. Machine learn­ing can also speed up the dis­cov­ery of new antibi­ot­ic com­pounds. Using a machine learn­ing algo­rithm, researchers at the Mass­a­chu­setts Insti­tute of Tech­nol­o­gy have iden­ti­fied a new antibi­ot­ic com­pound that kills dis­ease-caus­ing bac­te­ria that are resis­tant to known antibi­otics. The com­put­er mod­el screens more than 100 mil­lion chem­i­cal com­pounds in days and selects poten­tial antibi­otics that can kill bac­te­ria using mech­a­nisms dif­fer­ent to those of exist­ing drugs.


AI can also help alert the world to the threat of a dis­ease out­break. We were first made aware of Covid-19 in Decem­ber 2019 by Blue­Dot, a com­pa­ny in Toron­to. It used an algo­rithm to trawl noti­fi­ca­tions, dis­ease net­works, glob­al news sto­ries and even air­line tick­et­ing infor­ma­tion to accu­rate­ly pre­dict how the out­break would spread. Blue­Dot founder and CEO, Kam­ran Khan, is an infec­tious dis­ease and pub­lic health physi­cian. His career as a doc­tor began dur­ing the SARS epi­dem­ic of 2003, dur­ing which he saw col­leagues become infect­ed and die. “What we expe­ri­enced in Toron­to was a micro­cosm of what we’re now wit­ness­ing around the world,” he says. “That virus crip­pled our city; this virus has crip­pled the plan­et.”

These diseases are opportunistic, thriving where there is change to the environment, to animal or human hosts, or in the pathogen itself.

BlueDot’s team of data engi­neers, physi­cians and health experts has built algo­rithms that can read text in 65 lan­guages, 24 hours a day, look­ing for more than 150 dis­eases and syn­dromes, and orga­nize and struc­ture this vast amount of text data. “It is about hav­ing a machine play to its strengths, and humans play to theirs,” says Khan. “AI relies on large amounts of his­tor­i­cal data to train a machine to under­stand pat­terns. But with many of the things we’re deal­ing with there are no his­tor­i­cal pat­terns. We do not have 10,000 of these out­breaks that we can train a machine on – we have a hand­ful.” This means we still rely on human knowl­edge of his­to­ry and con­text. “Human intel­li­gence is aug­ment­ed by arti­fi­cial intel­li­gence. The two are com­ple­men­tary; one does not replace the oth­er.”

Human intelligence is augmented by artificial intelligence. The two are complementary; one does not replace the other.

Kamran KhanKamran Khan
CEO, BlueDot


Like oth­er experts, Kahn believes that, to get ahead of the game, we have to look more care­ful­ly at what trig­gers this type of out­break. “Some of the biggest dri­vers are the mass con­sump­tion of wildlife, indus­tri­al­iza­tion of agri­cul­ture and the dis­rup­tion of wildlife ecosys­tems,” he says. “While the life and health of every per­son is more con­nect­ed than ever to those of every­one else, it is also more con­nect­ed to the health of every liv­ing sys­tem on the plan­et.” Covid-19 has inevitably put the focus on zoonoses – dis­eases that orig­i­nate in ani­mal pop­u­la­tions. These account for some 70 per­cent of all new emerg­ing dis­eases. One idea is to track pathogens that have the poten­tial to leap over into humans. The Glob­al Virome Project was found­ed to do just that. It aims to iden­ti­fy the esti­mat­ed 500,000 as yet undis­cov­ered ani­mal virus­es capa­ble of trans­mis­sion to peo­ple, and build a glob­al atlas of zoonot­ic virus­es. These dis­eases are oppor­tunis­tic, thriv­ing where there is change to the envi­ron­ment, to ani­mal or human hosts, or in the pathogen itself. “The mech­a­nisms are com­plex and vary among dis­eases,” says Doreen Robin­son, Chief of Wildlife at the UN Envi­ron­ment Pro­gramme. “This means we need to under­stand the eco­log­i­cal dimen­sions much bet­ter.”


Over 70% of emerging infectious diseases originate from wildlife, sometimes via another animal. Click on the animal to find out which infectious disease is spread to humans from which animals, the name of the pathogen and the mode of transmission. As humans encroach on natural habitats, the risk of these diseases being transmitted to humans increases.


As humans encroach on forests and oth­er nat­ur­al habi­tats, they increase their risk of expo­sure to poten­tial pathogens. Under­stand­ing the rela­tion­ship between envi­ron­men­tal degra­da­tion and the spread of dis­ease is like­ly to be key to pre­vent­ing future out­breaks. It will mean tak­ing action on huge­ly chal­leng­ing areas like ani­mal wel­fare, inten­sive farm­ing, rapid urban­iza­tion, over­crowd­ing, san­i­ta­tion and cli­mate change.

When we protect our planetary health, we are protecting ourselves.

Chief of Wildlife UN Environment Programme

Robin­son argues that now is the time to improve our mon­i­tor­ing and risk assess­ment for zoonot­ic dis­eases, while also improv­ing san­i­tary mea­sures for wild and domes­tic ani­mals con­sumed as food. As our economies return and lock­downs ease, she sees an oppor­tu­ni­ty to launch a robust and account­able post2020 glob­al bio­di­ver­si­ty frame­work to be adopt­ed by all coun­tries, with enough resources to take the nec­es­sary action. But that remains only part of the pic­ture. “Equal­ly, we can­not lose momen­tum on set­ting new tar­gets to reduce green­house gas emis­sions. We need to work more close­ly across human, ani­mal and envi­ron­men­tal health to find sys­temic, holis­tic solu­tions and mit­i­gate future risks,” says Robin­son. “When we pro­tect our plan­e­tary health, we are pro­tect­ing our­selves.”

1 We must invest in AI and machine learning to further accelerate the development of vaccines and speed up the discovery of new antibiotic compounds. 2 In our interconnected world, it is vital that we leverage the power of big data to better predict where infectious diseases could emerge so that we can take swift action to prevent them spreading. 3 New pathogens are emerging, known viruses are mutating. The next outbreak could be far deadlier than Covid-19. We need to prepare today!
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