Michelle E. Matzko*, Marie Floryan, Christian L. Loyo, Colin N. O’Leary, and Alison E. Stout
Edited by R. Emerson Tuttle and Friederike M. C. Benning
Article | Aug. 30, 2021
- Preventing the next pandemic is critical for protecting human lives, reducing public health costs, and easing financial impacts.
- Surveillance and early detection of microbes with high pandemic potential combined with transparent and timely data sharing are paramount to identifying novel pathogens and limiting injurious spread.
- Public health measures implemented before, during, and after a new pandemic can slow the spread of illness; continued advancements in science and technology curb widespread disease.
“A GAUZE MASK IS 99% PROOF AGAINST INFLUENZA. Doctors wear them. Those who do not wear them get sick. The man or woman or child who will not wear a mask is now a dangerous slacker.”
-San Francisco Chronicle, October 22, 1918
- Introduce the origin of pandemics and candidate pathogens for the next pandemic
- Consider the benefits of zoonotic screening and surveillance for early pandemic detection
- Review specific advances in biotechnology that allow for better preparedness
How do pandemics arise?
Pathogens are microorganisms that cause disease. Human pathogens consist of diverse biological agents: bacteria, viruses, protozoa, fungi, etc., yet few of these pathogens harbor the high-risk features required to cause a pandemic (Fig. 2). Throughout history, pandemics have
been almost exclusively caused by bacteria and viruses due to their high transmissibility and fast rate of spread . Improvements in community sanitation and the advent of antibiotics in the 20th century mitigated the threat of bacterial pandemics. The bacterium Yersinia pestis, which
causes bubonic plague, remained a pandemic-level threat since it arose as a pathogen approximately 4000 years ago . With the advent of antibiotics and improved public sanitation,
its mortality rate fell from 70% to 10% –. Due to robust measures to prevent and treat bacterial infections, viruses currently surpass bacteria as pathogens with the greatest pandemic potential. Viral pathogens of pandemic potential are increasing and a number of features contribute: fast replication, airborne and droplet transmissibility, poor treatment options, and propensity for pre-symptomatic or asymptomatic spread . Of viruses, RNA viruses are
more likely to cause a pandemic than DNA viruses. This is primarily due to their high genetic mutation rate, which in turn increases the potential of RNA viruses to spread more easily among humans and animals and to escape antiviral therapies –. While viruses are currently the most likely pathogens to cause a pandemic in humans, all contemporary pathogens benefit from the potential of unhampered spread via limited geographic barriers.
Figure 2: Characteristics of microorganisms as pandemic threats. aSingle-celled organisms of which parasites may be one type. bStandard (formerly universal) precautions include hand and respiratory hygiene, use of personal protective equipment, sterile and aseptic techniques, etc. . Images created with BioRender.com. Table adapted from references [8,12]–.
Pandemic pathogens primarily arise as zoonoses, or diseases transmitted from animals to humans . Approximately 40–95% of infectious diseases are zoonotic in origin, a rate which varies by the type of microorganism . An estimated 72% of zoonotic diseases arise from a wildlife source . Livestock are also essential to the spread of zoonotic disease, and diseases will often transmit within the human-livestock-wildlife interface . For example, genetic sequencing data from each pandemic influenza virus of the 20th century revealed high genetic similarity to known swine and avian influenza viruses, tracing the origins of these pandemics to multiple animal hosts [26, 27].
Three ecological stages describe the emergence of a pathogen into a pandemic of zoonotic origin (Fig. 3) . During stage one, the pathogen replicates and cycles between animal hosts, which act as natural reservoirs. At this stage it has not yet caused human disease, but a pathogen can spread to other non-human hosts, a new geographic region, or begin to multiply beyond its reservoir. In order to progress to stage two, the pathogen must be able to infect humans. This typically occurs via the acquisition of random genetic mutations, however this is not universally true. For example, urbanization and human encroachment on wildlife habitats
can introduce novel pathogens to society which may already be able to infect humans without acquiring new mutations . Finally in stage three, sustained transmission and spread between humans across the globe occurs, introducing the pathogen to uninfected populations. When the pathogen reaches stage three, it causes a pandemic.
Figure 3: Pathogens can be described as progressing through three stages to becoming a pandemic, outlined by Morse and colleagues . Stage one: the pathogen is circulating and replicating in a non-human organism or environment, also known as a reservoir. Stage two: the pathogen acquires mutations that facilitate its spread from livestock or wildlife animal reservoirs to humans, creating a local disease cluster. Stage three: the pathogen’s uncontrolled replication spreads disease through sustained human-to-human transmission on a global scale, reaching new populations of uninfected people and causing a pandemic.
Committed and relentless study of the features of high-risk pandemic pathogens (transmissibility, mutability) at the early stages of zoonotic disease and the ecological conditions facilitating the transition from an animal pathogen to a human pandemic could serve as a valuable early warning system. Such efforts were highly recommended in the wake of the 2003 SARS outbreak, which was caused by a coronavirus with the potential of turning into a pandemic . The outbreak was not contained due to early detection but rather due to the biological nature of the pathogen along with strict and effective public health measures . Scientists globally argued for early surveillance and screening, discussed further below, but these efforts ultimately lost momentum. Post-SARS remains a clear example as to how relaxation of the scientific study of pathogens of pandemic potential yields lack of preparation for the next.
How do we detect emerging and reemerging pathogens?
Frequent surveillance remains the cornerstone to detecting pathogens circulating in and between animal hosts, reflecting disease risk to animals, disease risk to humans, and the
possibility of an emerging pandemic. Numerous viruses of pandemic potential have wildlife origins, and pathogens have been increasingly crossing the xenographic, or species barrier,
in the last decade. Serious new infections commonly arise from bats (Ebola, Marburg, SARS, COVID-19, Nipah virus), though infectious origins in primates (HIV, Zika) and other mammals (SARS via palm civets) are also common. Influenza has permanent animal reservoirs in waterfowl, poultry, and swine [30, 31]. Bidirectional mixing of viral genomes was spotlighted in the 2009 influenza H1N1 pandemic with more virulent mutations acquired as the flu was shared back and forth between humans and pigs [30, 31].
Numerous domestic and international groups are advocating for preemptive disease surveillance in animals dwelling near humans, specifically high-risk wildlife and animals of the food supply chain. The U.S. Agency for International Development (USAID) is one champion for global pathogen surveillance as a measure of future pandemic prevention. Project PREDICT under USAID is one group carrying the torch of worldwide pathogen surveillance in animals and, to date, has screened 164 000 organisms in humans and animals in 30+ countries, uncovering 947
novel viruses and 217 known viruses of pandemic potential . A counterpart program performing screening (frequent testing of healthy animals and humans) and surveillance
(specific testing for pathogens) in the U.S. includes the National Syndromic Surveillance Program (NSSP). Born out of growing concern for detecting bioterrorism, the NSSP serves as an early warning beacon for diseases of public health concern by sharing hospital emergency departments’ data nationally . Surveillance at multiple levels—wildlife, livestock, veterinary clinics, emergency rooms, public health departments—paired with global data sharing, could be
supported and potentially incentivized to prevent future pandemics. Coordinated data sharing at the global level may help speed the time from novel pathogen detection to recognition of its potential as a disease-causing pandemic pathogen to public health response.
Evidence of success lies both with SARS and COVID-19, where early data sharing of clusters of disease and viral genome sequences allowed rapid test development, global implementation of local surveillance, and public health measures . The continued threat of emerging pandemic pathogens is disruptive to global communities—socioeconomically, politically, and medically—but continued international funding and collaboration can alleviate the burden.
Once a new or high-risk pathogen is identified through screening or surveillance, modern epidemiological techniques can be used to interrogate the pandemic threat. Mathematical modeling of climate data, animal migrations, and human activities can forecast transmissibility, asymptomatic or pre-symptomatic spread, and overall population risk. Additionally, the integration of smartphone technologies aid symptom monitoring, quarantining, or contact tracing. These early prediction models and technological advancements may identify populations benefitting from prompt and/or stricter interventions. Furthermore, laboratory studies provide
valuable information for human infection potential and may translate to preclinical evidence for the development of therapies. These anticipatory investigations allow for timely interventions and early, sophisticated understanding of mechanisms that may help halt the spread of emerging pathogens of pandemic potential.
How do we slow the spread?
Anticipatory actions alone are limited in their effectiveness to slow the spread of a pandemic. Improvements and adherence to public health measures, widespread accessible testing, and clear communication to the public are indispensable tools for intercepting infections and preventing pandemic spread. Public health measures such as quarantines, travel restrictions, wearing masks (for pathogens that transmit through air), and universal screening of healthy individuals indisputably slow the spread of pandemics . As spotlighted at the beginning of this article, the universal recommendations during the COVID-19 pandemic closely mirrored the basic recommendations during the flu pandemic of 1918. At that time, public health officials directed individuals to avoid others, especially the ill, as a form of social distancing, wear face covers, and open windows for air ventilation. The congruence of the public health recommendations from today and a century ago underline that simple measures taken by everyone are the most effective to prevent escalating spread. Furthermore, lawmakers may consider examining data regarding the impact each individual public health measure has on the health of the population, informing public health and economic policies, weighing risk to an individual’s rights and social harms.
Complementary to careful investigation and deployment of effective public health measures, widespread infectious screening of the healthy public is key to identifying and isolating asymptomatic cases, thus limiting pandemic spread. Limitations of testing are unavoidable: sick people will be missed by mass screening measures when the testing denominator is large. Thus, while the effectiveness of widespread screening stands up alone (assuming effective deployment), this tool is most effective when coupled with follow up measures. Directed testing naturally follows screening and who gets tested also matters. Vulnerable populations (racial and ethnic minorities, the elderly, and citizens of low socioeconomic status) have been disproportionately affected by all modern pandemics . During the COVID-19 pandemic, testing capacity in affluent communities was far greater despite targeted efforts in high-risk but low-resource neighborhoods . There are multiple reasons, both for risk of infection and likelihood of getting tested. The most common testing barriers include fear, anticipated stigma, loss of employment, cost, accessibility, or the perceived burden of receiving a positive test result . By the measures of equitable access to testing and high levels of comfort of individuals being tested, no pandemic surveillance program has ever been effective. A shift to cheaper, simpler, faster, at home tests would circumvent a majority of these barriers [39, 40]. Rapid diagnostic tests, including at-home tests have not achieved the same accuracy as standard testing . However, the tradeoff of rapid identification of positive cases, greater societal access to, and more frequent testing would outweigh the intrinsic test limitations. Thus, we propose ongoing financial incentives for developing the scaffolds for at-home and rapid diagnostics which might include masks with built-in rapid tests, saliva or exhaled breath-based tests, or other cutting-edge testing strategies . Further development of pipelines to support citizens with positive test results could rapidly change the course of the next pandemic for the better.
How do we speed countermeasure development?
While surveillance, testing, and non-pharmaceutical public health interventions are critical to slowing the pace of infectious disease transmission, medical countermeasures such as therapeutics and vaccines are essential for treating infected individuals. During an epidemic or pandemic, the rapid development of medical countermeasures is particularly important, especially when physicians lack treatment options beyond supportive care. Although speed is essential when developing medical countermeasures, ensuring safety and efficacy is paramount. To this end, critical scientific development priorities, such as the Apollo Project for Biodefense, and regulatory reforms are establishing stable pipelines for developing novel therapeutics and vaccines for modern pandemics [45, 46].
Prior to COVID-19, the shortest duration of a vaccine’s development was four years for measles. The COVID-19 pandemic accelerated the usage of novel vaccine platforms, such as messenger RNA (mRNA) and viral vector vaccines, that utilize an interchangeable antigen component (which directs immunity against a specific pathogen) built into a fixed scaffold and delivery system (such as an mRNA construct or adenoviral vector) . These vaccine platforms are considered to be “plug and play” vaccines that are defined by the ability to be rapidly designed and redesigned, changing the genetic sequence of the antigen component without altering the scaffold to account for new pathogen threats, including emerging variants of an infectious disease (Fig. 4) . Template redesign can be straightforward, but the process of target identification and optimization is not. The history of the Moderna COVID-19 vaccine began long before COVID-19 as a project to leverage mRNA technology for another coronavirus, Middle East respiratory syndrome coronavirus (MERS-CoV) . The infrastructure and expertise already existed to translate knowledge of designing prior coronavirus vaccines and apply them rapidly to COVID-19.
Figure 4: A model for integrating surveillance and countermeasure development that can be rapidly deployed during an outbreak. (a) Pathogen surveillance (including metagenomic sequencing (i.e. sequencing genomes from a sample of multiple organisms), syndromic surveillance, and other meaures) is used to identify pathogens and pathogen families with pandemic potential. (b) Prototype diagnostic and vaccine scaffolds for pathogen families with pandemic potential are developed. (c) During an outbreak, specific genetic sequence information from the pathogen is input into the scaffold to create a pathogen specific diagnostic or vaccine. (d) Newly-developed, specific medical countermeasures can then be evaluated for efficacy and emergency use. Created with BioRender.com.
Success from the efficient development of coronavirus “plug and play” vaccines could be translated to other pathogens. Efforts are now underway to apply mRNA vaccine technology to the development of other viral vaccines and a malaria (parasite) vaccine. Building a library of prototype vaccines targeting pathogens of pandemic potential (including those identified through surveillance efforts) would contribute to an arsenal of preventative tools. Prior to an outbreak, these prototype vaccines can be designed to serve as scaffolds for vaccine design for related viruses and be brought through preclinical studies and early-stage clinical trials to determine their safety and suggest efficacy. In the event of an outbreak, the vaccine candidates could be modified and launched into later stage trials . With concomitant rapid bridging studies confirming the new candidate vaccine’s safety profile, months would be shaved off the vaccine development timeline. The key is to start this development before the next pandemic starts. The capabilities of prototype vaccines could be expanded by focusing research on vaccines that target multiple viruses within the same family, such as pan-coronavirus vaccines or universal flu vaccines .
In the case of both therapeutics and vaccines, there is much to be learned about conducting rapid, controlled clinical trials during an infectious disease outbreak. Flaws in the design of the AstraZeneca COVID vaccine trial undermined confidence in the vaccine and prevented regulatory approval in the U.S. . At the same time, no clinical trials addressed strategies for dose sparing (providing first doses and delaying second doses of a two-dose vaccine) or mixing-and-matching of different vaccines—both strategies that are being used with limited clinical data to support their use. In the future, regulators could establish standardized clinical trial designs, improve information sharing between investigators, and design publicly-funded trials that explore combinations of different vaccines that individual companies might not otherwise fund.
The scientific and clinical knowledge to rapidly develop medical countermeasures during an infectious disease outbreak exists. However, that knowledge should continuously evolve as more technology is developed. The cost of developing new therapeutics and vaccines and shepherding them through early stage clinical trials is expensive . While government financed pre-purchase agreements during the COVID-19 pandemic absorbed many of these costs, preparing for the next pandemic requires long-term funding. Improving the capabilities of rapid therapeutic and vaccine development platforms can be accomplished by increasing support for agencies, such as the Biomedical Advanced Research Development Agency, Defense Advanced Projects Research Agency, and National Institutes of Health, that fund research into these systems. Improving clinical trial design and launching early stage clinical trials for therapeutics and vaccines that are not immediately necessary requires significant investment in clinical research capabilities and rethinking our traditional paradigms of trial funding. In the absence of an immediate market for a therapeutic or vaccine, additional government support for and funding of these trials may be necessary. Fundamentally, this would take the government-led funding model used for COVID-19 vaccine development and apply it to “Disease X”—some might think of it as “plug and play” with funding—to prevent future pandemics. Without these steps to invest in therapeutic and vaccine development, we may find that we do not have the tools to fight the next pandemic, which may be more severe than the current one.
Novel and reemerging infectious diseases of zoonotic origin have been a major threat to human lives for millenia. With ongoing urbanization, deforestation, and human-animal contact, the threat of the next pandemic looms large and soon. While new infectious diseases cannot be prevented, their spread and destruction can be contained. Preemptive adoption of countermeasures such as increased pathogen surveillance, global data sharing, development of scaffolds for diagnostics, therapeutics, and vaccines will play a large role moving forward. We hope to impart the gravity of preemptive solutions for the protection of human lives in the 21st century and beyond.
This MIT Science Policy Review article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
 Bedford, J. et al. A new twenty-first century science for effective epidemic response. Nature 575, 130–136 (2019). https://doi.org/10.1038/s41586-019-1717-y.
 Villa, S. et al. The COVID-19 pandemic preparedness … or lack thereof: from China to Italy. Global Health & Medicine 2, 73–77 (2020). https://doi.org/10.35772/ghm.2020.01016.
 Kellogg, W. H. & MacMillan, G. An experimental study of the efficacy of gauze face masks. American Journal of Public Health 10, 34–42 (1920). https://doi.org/10.2105/ajph.10.1.34.
 Ott, M., Shaw, S. F., Danila, R. N. & Lynfield, R. Lessons learned from the 1918–1919 influenza pandemic in Minneapolis and St. Paul, Minnesota. Public Health Reports 122,803–810 (2007). https://doi.org/https://dx.doi.org/10.1177/003335490712200612.
 Honigsbaum, M. Pandemic. Lancet 373, P1939 (2009). http://doi.org/10.1016/S0140-6736(09)61053-9.
 Wolfe, N. D., Panosian Dunavan, C. & Diamond, J. Origins of major human infectious diseases. Nature 447, 279–283 (2007). https://doi.org/10.1038/nature05775.
 Morelli, G. et al. Yersinia pestis genome sequencing identifies patterns of global phylogenetic diversity. Nature Genetics 42, 1140–1143 (2010). https://doi.org/10.1038/ng.705.
 Piret, J. & Boivin, G. Pandemics throughout history. Frontiers in Microbiology 11, 631736 (2021). https://doi.org/https://dx.doi.org/10.3389/fmicb.2020.631736.
 Spyrou, M. A. et al. Analysis of 3800-year-old Yersinia pestis genomes suggests Bronze Age origin for bubonic plague. Nature Communications 9, 2234. https://doi.org/10.1038/s41467-018-04550-9.
 Prentice, M. B. & Rahalison, L. Plague. The Lancet 369, 1196–1207 (2007). https://doi.org/10.1016/S0140-6736(07)60566-2.
 Stenseth, N. C. et al. Plague: past, present, and future. PLOS Medicine 5, e3 (2008). https://doi.org/10.1371/journal.pmed.0050003.
 Woolhouse, M. E. J., Brierley, L., McCaffery, C. & Lycett, S. Assessing the epidemic potential of RNA and DNA viruses. Emerging Infectious Diseases 22, 2037–2044 (2016). https://doi.org/10.3201/eid2212.160123.
 Kreuder Johnson, C. et al. Spillover and pandemic properties of zoonotic viruses with high host plasticity. Scientific Reports 5, 14830 (2015). https://doi.org/10.1038/srep14830.
 Holmes, E. C. The evolutionary genetics of emerging viruses. Annual Review of Ecology, Evolution, and Systematics 40, 353–372 (2009). https://doi.org/10.1146/annurev.ecolsys.110308.120248.
 Carrasco-Hernandez, R., Jácome, R., López Vidal, Y. & Ponce de León, S. Are RNA viruses candidate agents for the next global pandemic? A review. ILAR Journal 58, 343–358 (2017). https://doi.org/10.1093/ilar/ilx026.
 Centers for Disease Control and Prevention. Standard precautions (2020). Online: https://www.cdc.gov/oralhealth/infectioncontrol/summary-infection-prevention-practices/standard-precautions.html. Accessed: July, 2021.
 Morse, S. S. et al. Prediction and prevention of the next pandemic zoonosis. Lancet 380, P1956–1965 (2012). https://doi.org/10.1016/S0140-6736(12)61684-5.
 Alvarez-Munoz, S., Upegui-Porras, N., Gomez, A. P. & Ramirez-Nieto, G. Key factors that enable the pandemic potential of RNA viruses and inter-species transmission: A systematic review. Viruses 13, 537 (2021). https://doi.org/10.3390/v13040537.
 Cushing, T. & Jayanti, A. Vaccine platforms. Tech. Rep. (2020). Online: https://www.belfercenter.org/publication/technology-factsheet-vaccine-platforms. Accessed: July, 2021.
 Whitfield, J. Portrait of a serial killer. Nature (2002). https://doi.org/10.1038/news021001-6.
 Fisher, M. C. et al. Emerging fungal threats to animal, plant and ecosystem health. Nature 484, 186–194 (2012). https://doi.org/10.1038/nature10947.
 World Health Organization. World malaria report 2017. Tech. Rep. (2017). Online: https://www.who.int/publications/i/item/9789241565523. Accessed: July, 2021.
 Taylor, L. H., Latham, S. M. & Woolhouse, M. E. Risk factors for human disease emergence. Philosophical Transactions of the Royal Society B 356, 983–989 (2001). https://doi.org/10.1098/rstb.2001.0888.
 Jones, K. E. et al. Global trends in emerging infectious diseases. Nature 451, 990–993 (2008). https://doi.org/10.1038/nature06536.
 Hassell, J. M., Begon, M., Ward, M. J. & Fèvre, E. M. Urbanization and disease emergence: dynamics at the wildlife–livestock–human interface. Trends in Ecology & Evolution 32, 55–67 (2017). https://doi.org/10.1016/j.tree.2016.09.012.
 Cox, N. J. & Subbarao, K. Global epidemiology of influenza: past and present. Annual Review of Medicine 51, 407–421 (2000). https://doi.org/10.1146/annurev.med.51.1.407.
 Horimoto, T. & Kawaoka, Y. Influenza: lessons from past pandemics, warnings from current incidents. Nature Reviews Microbiology 3, 591–600 (2005). https://doi.org/10.1038/nrmicro1208.
 Cui, J., Li, F. & Shi, Z.-L. Origin and evolution of pathogenic coronaviruses. Nature Reviews Microbiology 17, 181–192 (2019). https://doi.org/10.1038/s41579-018-0118-9.
 Hung, L. S. The SARS epidemic in Hong Kong: what lessons have we learned? Journal of the Royal Society of Medicine 96, 374–378 (2003). https://doi.org/10.1258/jrsm.96.8.374.
 Nelson, M. I., Gramer, M. R., Vincent, A. L. & Holmes, E. C. Global transmission of influenza viruses from humans to swine. Journal of General Virology 93, 2195–2203 (2012). https://doi.org/10.1099/vir.0.044974-0.
 Jain, S. et al. Emergence of a novel swine-origin influenza A (H1N1) virus in humans. New England Journal of Medicine 360, 2605–2615 (2009). https://doi.org/10.1056/NEJMoa0903810.
 United States Agency for International Development. PREDICT project. Online: https://p2.predict.global. Accessed: July, 2021.
 Gould, D., Walker, D. & Yoon, P. W. The evolution of BioSense: lessons learned and future directions. Public Health Reports 132, 7S–11S (2017). https://doi.org/10.1177/0033354917706954.
 WHO | Public consultation – Pathogen genetic sequence data (GSD). WHO (2019). URL http://www.who.int/blueprint/what/norms-standards/gsdsharing/en/.
 Viswanathan, M. et al. Universal screening for SARS-CoV-2 infection: a rapid review. Cochrane Database of Systematic Reviews CD013718 (2020). https://doi.org/10.1002/14651858.CD013718.
 National Institute on Aging. Why COVID-19 testing is the key to getting back to normal (2020). Online:
https://www.nia.nih.gov/news/why-covid-19-testing-key-getting-back-normal. Accessed: July, 2021.
 Dryden-Peterson, S. et al. Disparities in SARS-CoV-2 Testing in Massachusetts During the COVID-19 Pandemic. JAMA Network Open 4, e2037067 (2021). https://doi.org/10.1001/jamanetworkopen.2020.37067.
 McElfish, P., Purvis, R., James, L., Willis, D. & Anderson, J. Perceived barriers to COVID-19 testing. International Journal of Environmental Research and Public Health 18, 2278 (2021). https://doi.org/10.3390/ijerph18052278.
 Mina, M. J., Parker, R. & Larremore, D. B. Rethinking Covid-19 test sensitivity — a strategy for containment. New England Journal of Medicine 383, e120 (2020). https://doi.org/10.1056/nejmp2025631.
 Guglielmi, G. Rapid coronavirus tests: a guide for the perplexed. Nature 590, 202–205 (2021). https://doi.org/10.1038/d41586-021-00332-4.
 Yetman, D. Are rapid COVID-19 test results reliable? (2021). Online: https://www.healthline.com/health/how-accurate-are-rapid-covid-tests. Accessed: July, 2021.
 Sheridan, C. COVID-19 spurs wave of innovative diagnostics. Nature Biotechnology 38, 769–772 (2020). https://doi.org/10.1038/s41587-020-0597-x.
 McKinnon, M. et al. Effective communication in a pandemic requires more than ‘the science’ (2020). Online: https://www.ingsa.org/covidtag/covid-19-featured/cpas-communication/. Accessed: July, 2021.
 van der Bles, A. M., van der Linden, S., Freeman, A. L. J. & Spiegelhalter, D. J. The effects of communicating uncertainty on public trust in facts and numbers. PNAS 117, 7672–7683 (2020).
 O’Leary, C., Jayanti, A. & Mina, M. Considering public purpose in the time of COVID-19. Tech. Rep. (2020). Online: https://www.belfercenter.org/publication/considering-public-purpose-time-covid-19. Accessed: July, 2021.
 Bipartisan Commission on Biodefense. The Apollo Program for biodefense — winning the race against biological threats. Tech. Rep. (2021). Online: https://biodefensecommission.org/reports/the-apollo-program-for-biodefense-winning-the-race-against-biological-threats/. Accessed: July, 2021.
 McCarthy, C. Will coronavirus herald a new era in vaccine innovation? (2020). Online: https://www.gavi.org/vaccineswork/will-coronavirus-herald-new-era-vaccine-innovation. Accessed: July, 2021.
 Corbett, K. et al. SARS-CoV-2 mRNA vaccine design enabled by prototype pathogen preparedness. Nature 586, 567–571 (2020). https://doi.org/10.1038/s41586-020-2622-0.
 Krammer, F. Pandemic vaccines: how are we going to be better prepared next time? Med 1, 28–32 (2020). https://doi.org/10.1016/j.medj.2020.11.004.
 Cohen, J. Innovative universal flu vaccine shows promise in first clinical test. Science (2020). https://doi.org/10.1126/science.abg0476.
 How AstraZeneca’s vaccine was hit by flawed trials, defects and politics — but might still save the world (2021). Online: https://www.ft.com/content/d0fd6c4c-939a-43c7-a9b9-47c8d3cab253. Accessed: July, 2021.
 Wouters, O. J., McKee, M. & Luyten, J. Estimated research and development investment needed to bring a new medicine to market, 2009-2018. Journal of the American Medical Association 323, 844–853 (2020). https://doi.org/10.1001/jama.2020.1166.