COVID-19 Response – Lessons from Secret Intelligence Failures

ABSTRACT

With COVID-19 global deaths surpassing a million lives as of late-September 2020, there are compelling reasons to examine the epidemic warning process and how public health agencies work with governments to translate their information into action. The problem of failures in this warning-policy interface has long been an issue for intelligence agencies worldwide. This paper explores the problem of intelligence failures and applies their lessons to the warning and response to pandemics and other large-scale health emergencies and disasters. This analysis offers lessons for public health warning and response to future pandemic crises. Pandemic response is potentially more complex than traditional national security issues as government players are augmented by nongovernmental organizations, health practitioners, the private sector, and general public of every country in the world. Learning from the COVID-19 pandemic with an international perspective can aid warning and response to coming waves as well as future epidemics. A set of suggestions are provided for epidemic intelligence warning and response to pandemics presenting whole-of-society and transnational approaches. Included are areas for further research including research avenues to prevent and mitigate the future pandemic events.

KEYWORDS:

• COVID-19
• SARS-CoV-2
• Pandemic
• National security

Introduction

Emerging in late-2019 from Hubei Province, China, SARS-CoV-2 and its related disease COVID-19 have swept around the world, affecting most aspects of life. As of late March 2021, COVID-19 has infected over 125 million worldwide and killed over 2.7 million (Johns Hopkins University & Medicine, 2020). Micah Zenko (2020) has called the COVID-19 pandemic the worst intelligence failure in U.S. history. As early as November 2019, U.S. intelligence services were aware of health crisis that could grow into a “cataclysmic event” (Eyal, 2020). While it has become fashionable to blame U.S. President Donald Trump for downplaying warnings about the virus, all Western governments were caught unprepared (Eyal, 2020). Many of the intelligence lessons discussed here are drawn from the experiences of the U.S. Intelligence Community as it is arguably the most open of the secret intelligence systems; however, those lessons can be applied to many countries’ responses to the pandemic.

The COVID-19 pandemic crisis has noticeably exacerbated the consequences of undermining the paradigm that scientific expertise and empirical research should inform national and international health and emergency policies. Science did not account for factors including political disagreement and public noncompliance with scientific and medical recommendations. Dahl (2020) observed three aspects that worked in combination to the detriment of many national responses: strategic warning that failed to prevent the crisis, specific threat information that was lacking, and policymaker lack of receptivity to the intelligence information. All three factors were at play in the international response to the pandemic.

Changes in the production of news, and how it is circulated and consumed, have allowed for the rise of misinformation, false information not intended to cause harm; disinformation, false information deliberately created or shared; and malinformation, true information intended to cause harm (Irwin, 2020). Misperceptions warp public opinion, undermine debate, and distort policy on issues ranging from climate change to vaccines and have affected discourse on COVID-19 (Nyhan, 2020). The enormous volume of information, both accurate and inaccurate, makes it extremely difficult for individuals to make health decisions and decision makers to craft policy for their constituents (WHO – World Health Organization, 2021a).

The Information Environment

The role of the media is critical in shaping a response to pandemic, although there are shortcomings as the urgency of today’s news cycle may prompt the media to report and give undeserved credibility to misinformation and neglect traditional reporting principles (Tarantola, Parmet, Costanza, & Yu, 2020). In reporting on Sweden’s response to COVID-19 the media was not completely accurate, hindering discussion of best practices. It was also often at a superficial level and did not report the details of policies or a consideration of actual experiences (Irwin, 2020). In a study conducted by the Pew Research Center, 51% of experts polled opined that the information environment will not improve, and new challenges will arise that cannot be countered because of the scale of the Internet environment (Anderson & Rainie, 2017).

During the COVID-19 pandemic, there has been a huge volume of news, both correct and not, making it difficult to find either trustworthy sources or reliable guidance. Because of this information overload, the World Health Organization (WHO) convened a first-ever conference on infodemiology to manage infodemics, establish a research agenda on the issue, and build an international community of practice and research (World Health & Organization, 2020b). The information chaos related to COVID-19 pandemic is further amplified by the unprecedented overload of misinformation (Gradon, 2020). In February 2021, the WHO published a research a research agenda on infodemics, based on the 2020 conferences with additional input from participants in the WHO Information Network for Epidemics (EPI-WIN) (WHO – World Health Organization, 2021a). The research agenda is intended to develop a new interdisciplinary field of study, focus research on combating misinformation, and countering its detrimental effects to public health.

The short- and long-term impacts of the pandemic warrant treating it as a national security issue. The impacts to the global economy have been staggering. In the year following the WHO pandemic declaration the morbidity and mortality have been enormous. Even as the COVID-19 pandemic continues, it is critical for societies to consider its social, economic, and health effects, and prepare to mitigate them. (Tarantola et al., 2020).

There are important differences between secret intelligence efforts and those of the public health and medical communities. In most Western countries, especially in the United States, intelligence informs decision-making but neither makes recommendations about policy nor makes policy decisions. In contrast, the public health and medical communities make both recommendations and, often, policy at nearly every level from transnational organizations such as WHO to local public health agencies and medical authorities. While citizens, and non-citizens alike, are not directly involved with the intelligence and policy making processes, they are in the case of public health. The general populations of countries worldwide are consumers of health and medical information as well as decision makers.

Intelligence Processes

The U.S. intelligence cycle will be used as point of departure for examining intelligence processes. The reasons are two-fold: The U.S. Intelligence Community is – due to its leadership – considered to be the first among equals and its processes are much more open to inspection than most other countries. The intelligence cycle is a five-step process of producing intelligence products for consumers consisting of (1) direction and planning – identifying and defining the areas for intelligence efforts, (2) collection – gathering information, (3) processing – readying the information for analysis, (4) analysis and production – turning the information into reports for consumers, and (5) dissemination – providing the reports to consumers (CIA – Central Intelligence Agency, 1995; Lowenthal, 2015). The process is continuous, fluid, and applicable to any function requiring transforming raw information into products suitable for organizations and individuals to base decisions on. The cycle’s utility is such that in addition to national security, it has been recommended for use against career criminals (O’Leary, 2015) and managing the effects of wildfires (Young, 2018).

The intelligence cycle is useful for examining the steps in the detection, warning, and response to public health emergencies. There is direct application to detection and response to epidemics and pandemics with each step having applicability. Planning and direction manage the process for the entire cycle from determining needs for medical intelligence to delivery of a product to consumers (Richelson, 2012). Collection of intelligence information occurs through a variety of activities ranging from overt and covert human activity to research over the Internet with many parallels to managing medical intelligence. Processing readies the information collected for use by analysts (CIA – Central Intelligence Agency, 1995). Analysis and production involve understanding the issue at hand, organizing information gleaned from collection, synthesis of information, advancing defendable hypothesis, and producing a report for consumers (Steiner, 2015). Dissemination is delivering intelligence products to consumers such as policymakers (CIA – Central Intelligence Agency, 1995). As noted, the intelligence cycle does not include decision-making and policy implementation.

Intelligence Failures

Intelligence failure is an oft-studied topic. Its causes range from a failure to detect a threat to decision makers not understanding an action and making decisions contrary to national interests (Dahl, 2013). Gentry (2008) posited six distinct types of intelligence failures. Notably, only two of the failure types are attributable to the intelligence function, threat warning and opportunity warning failures. Four are the responsibility of leadership and policymakers.

Table

Intelligence Failures
Type	Name	Characteristic
1	Threat Warning	Threat warning failure
2	Threat Response	Leader’s failure to respond effectively to warning
3	Opportunity Warning	Failure to alert policymakers of opportunity
4	Opportunity Response	Leader’s failure to exploit opportunity
5	Vulnerability Identification	Failure to recognize own vulnerabilities
6	Vulnerability Amelioration	Failure to ameliorate vulnerabilities

In the case of pandemic warning and response, two additional types of intelligence failures must be added to Gentry’s typology. The first is the public’s failure to recognize its vulnerabilities to a public health crisis. In the case of COVID-19, the various populations of the countries of the world may not have recognized the severity of pandemic. They may not have been aware of the spread of the virus, it may have seemed too distant to be of concern, or, as has occurred in a number of countries, some part of the population refuses to believe in the disease or acknowledge that it is a threat (Halliday, 2020). The second type of failure is the lack of response on the public side despite an understanding that COVID-19 was, in fact, a threat to life. Examples include refusals to wear masks because they represented a violation of individual liberties or decisions of business owners to remain open despite government policies to the contrary (Weisberg & Nikolewski, 2020). For the purposes of maintaining a consistent taxonomy, we label these Type VII and Type VIII failures respectively.

According to ABC News, the first intelligence reports on the spread of the novel coronavirus in the region of the city of Wuhan in the Hubei Province, China were delivered by the National Center for Medical Intelligence (NCMI), a component of the U.S. Defense Intelligence Agency, as early as the end of November 2019 (Margolin & Meek, 2020). According to the ABC sources, the NCMI report was compiled through wire and computer interception and satellite imagery and concluded that an outbreak of the virus could be a “cataclysmic event” (Perez, 2020). The Pentagon denied the existence of the report (Tucker, 2020), but Israeli media outlets revealed that the U.S. intelligence agencies alerted the North Atlantic Treaty Organization (NATO) and the Israeli Defense Forces (IDF) about the coronavirus outbreak in China in November 2019 (TOI – Times of Israel, 2020). On January 5, 2020, WHO published information on the outbreak in Wuhan, including the number of cases and an outbreak status in a Disease Outbreak News Report. On January 30, 2020, WHO declared the outbreak a Public Health Emergency of International Concern (PHEIC), its highest level of alarm (WHO – World Health Organization, 2021b). The awareness of the COVID-19 crisis gained further attention in January 2020, with academic publications calling the novel coronavirus a global health concern (Wang, Horby, Hayden, & Gao, 2020).

Italy was the first country in Europe to experience the magnitude of the health emergency related to COVID-19 and its experience demonstrated the threat of the disease. On March 11, 2020, WHO declared the outbreak a pandemic calling for whole-of-government approaches to combat the spread of the disease (WHO – World Health Organization, 2021b). In late-March 2020, Harvard Business Review (HBR) reported the response failures of the Italian government, highlighting poor decisions and sounding a warning to the rest of Europe and to the United States (Pisano, Sadun, & Zanini, 2020). HBR researchers noted that the Italian crisis occurred after the virus had impacted China and the models for its containment had been successfully implemented in the countries such as China and South Korea. It was classified a systematic failure to understand and act on information rapidly and effectively. The HBR researchers emphasized the policymakers’ inability to collect and share information, failure to acknowledge the warnings provided by scientific experts, the lack of an approach to meet the threat, lack of a unified strategy in healthcare, and inability to disseminate the acquired knowledge on best practices and potential problems.

The United States of America’s COVID-19 experience provides an important case study on the fusion of intelligence and public health information. These lessons can inform future efforts to detect, warn, and respond to epidemics, Public Health Emergencies of International Concern (PHEIC, pronounced “fake”), and pandemics. While there are likely equally important lessons from other countries worldwide, the United States’ openness with its intelligence activities, through official information, leaks to the media, and other disclosures such as Freedom of Information Act (FOIA) releases, is much greater than most other countries (United States Department of Justice, 2021). In 2014, the Office of the Director of National Intelligence issued its Open Government Plan to increase collaboration within the U.S. federal government and transparency of the Intelligence Community with the public (ODNI – Office of the Director of National Intelligence (ODNI), 2014).

The NMCI report on the outbreak in Wuhan was, reportedly, was briefed to parts of the U.S. government, including the White House, in November 2019. In January and February 2020, The President’s Daily Brief, a highly classified finished intelligence briefing for President Trump and top U.S. officials, contained more than a dozen articles on the spread of the virus (Miller & Nakashima, 2020). As noted, WHO issued a Disease Outbreak News Report on January 5, 2020 and declared a PHEIC on January 30, 2020. A pandemic was not declared until March 11, 2020 (WHO – World Health Organization, 2021b). On January 1, 2020, Centers for Disease Control and Prevention (CDC) Director Robert Redfield was made aware of the magnitude of the virus problem and he briefed Health and Human Services Secretary Alex Azur. On January 18, Azur discussed the virus with President Trump (POGO – Project on Government Oversight, 2021).

By the end of March 2020, the outbreak of the disease in the United States was already considered a substantial problem, with the federal government’s approach cited for an unprecedented indifference and even willful neglect with a catastrophic effect on the American people (Zenko, 2020). The United States did not introduce nation-wide lockdown measures, while some states, counties or cities implemented local or regional lockdowns and quarantines (Gershman, 2020). The governors of the 50 states were required to fashion their own responses to COVID-19 resulting in a fragmented approach to combating the spread of the virus. Recent research has found that state responses became increasingly politicized and the political party of state leadership may have contributed to policies related to the spread of the disease (Neelon, Mutiso, Mueller, Pearce, & Benjamin-Neelon, 2021). The dramatic increase in infection and death rates in the U.S. have been blamed on rapid easing of shelter-in-place and business closure orders, politicization of mask-wearing, and public complacency during summer holidays (Zurcher, 2020). The infection rates increase has also been blamed on the lack of a national contact-tracing program and the absence of enforcement of self-isolation in the U.S. (Khazan, 2020), strategies that were successfully implemented in a number of countries worldwide (Scarpetti, Webb, & Hernandez-Quevedo, 2020; Scott & Wanat, 2020).

There appears to be sufficient warning of the spread of COVID-19 in the United States to have warranted a national response and heightened level of preparedness. Several levels of failure took place including Type II, Threat Response – Leader’s failure to respond effectively to warning; Type V, Vulnerability Identification – Failure to recognize own vulnerabilities, and Type VI, Vulnerability Amelioration – Failure to ameliorate vulnerabilities (Gentry, 2008). In addition, the two additional types of failures identified in this paper also look to have occurred, public failure to recognize its vulnerabilities and public failure to ameliorate its vulnerabilities. It must be recognized, however, that these failures are not uniform throughout the United States as public responses differed from state to state as well as within states themselves.

Pandemic Intelligence

Experiences of intelligence agencies worldwide provide a starting point for managing detection and warning pandemics. There are, however, important differences that must be considered most importantly with managing information and consumer understanding. A pandemic response requires timely and effective public health actions to control spread, suffering, and deaths. Perhaps more important than traditional intelligence collection, epidemic intelligence – a set of capabilities and measurements aligned with the public health response – is an important tool early in health emergency responses (Nash & Geng, 2020). Much of the information surrounding potential epidemic is available to the public as well as the policymakers and professionals managing a crisis. Unlike the intelligence–policy relationship, the public is also a critical consumer of downstream medical information as their actions may determine the success or failure of mitigation efforts. The U.S. Strategy for Pandemic Influenza notes that individuals and families have a critical role in countering a pandemic with individuals have perhaps the most important role in preparedness and response (Homeland Security Council, 2005).

The U.S. Centers for Disease Control and Prevention (CDC) identified numerous stakeholders in public health programs including state and local health departments, education organizations, local governments, representatives of populations disproportionately affected, and private citizens (CDC – Centers for Disease Control and Prevention, 2020b). In the current COVID-19 pandemic environment, stakeholders include nearly every individual and organization globally. The need to engage individuals is clear from the resistance to measures undertaken to limit the spread of COVID-19 that have occurred globally. It is possible that stakeholders may even need to be sorted by political party or perhaps conservative versus progressive groups as their perceptions and responses to the pandemic have been different (Pew Research Center, 2020). Assessing the culture of constituent communities will be critical to assist and enable them to make informed health choices (WHO, Undated).

Epidemic intelligence efforts are becoming recognized as a vital component for warning and response to emerging infectious disease (Wilburn, O’Connor, Walsh, & Morgan, 2019). Epidemic intelligence services such as the CDC Epidemic Intelligence Service conducts operations that are, in some respects, analogous to overt intelligence collection (CDC – Centers for Disease Control and Prevention, 2020a). The European Center for Disease Prevention and Control conducts online collection and surveillance that is similar to intelligence agencies’ open source collection efforts to gather information on emerging disease and assist in response (Semenza et al., 2016). As an example, during the five-year period from 2008 to 2013, the European Center for Disease Prevention and Control detected 116 infectious disease threat events (IDTE) using active and automated Internet searches by a team of epidemiologists at its Emergency Operations Center in Stockholm, Sweden (Semenza et al., 2016). Private sector tools have also been developed for infectious disease monitoring. At the country-level, openly gathered information may be fused with secret intelligence to form the equivalent of all-source intelligence.

In January 2019, the U.S. Director of National Intelligence warned that traditional intelligence threats such as strategic adversaries were now accompanied by new challenges, termed human security, and resulted from the proximity of humans and animals. These new threat areas included emerging infectious diseases that could increasingly be spread by urbanization, international travel, human incursion, and climate change (ODNI – Office of the Director of National Intelligence (ODNI), 2019). In November 2019, an intelligence report from the National Center for Medical Intelligence, part of the U.S. Defense Intelligence Agency, warned of the spread of a pathogen sweeping through China’s Wuhan region. This information was included in the President’s Daily Brief in early January and would have warned the most senior policy makers (Margolin & Meek, 2020).

Dealing with denial and deception has been a traditional concern for intelligence agencies and has potential application for pandemic warning. False information about COVID-19 was mixed with accurate information throughout the pandemic. Fox News, QAnon, and then-President Donald Trump advanced theories that the Chinese government manufactured the virus and withheld information about the outbreak in Wuhan for both the number of cases and the transmissibility of the virus (BBC News – British Broadcasting Company, 2020). In retaliation, the Chinese Ministry of Foreign Affairs advanced the theory that SARS-CoV-2 was created in a U.S. laboratory and brought into China by the U.S. military (Kinetz, 2021). The U.S. media also posits that Russia is understating the number of cases and deaths it has experienced (Dixon, 2020). Concurrently, the Russian media has questioned the efficacy of vaccines developed by or in partnership with U.S. pharmaceutical companies (Hansler, Brown, & Cole, 2021). This Russian, Chinese, and United States state-level information competition has added to the difficulty of detecting and tracing the outbreak of COVID-19.

Politicization of information related to COVID-19 likewise has added to the difficulty of evaluating the pandemic and is likely to affect future outbreaks. In preparing to support policy makers, intelligence officers are expected not to have a preference in policy outcomes or make policy recommendations in presenting their findings (Lowenthal, 2015). Similarly, decision makers should not be pressuring the intelligence process or manipulating intelligence findings to support favored policy actions (Vest, 2009). Pandemic reporting adds the news media, political actors, conspiracy theorists, and the general public as both sources of information and receivers of it. Hart, Chinn, and Soroka (2020) found that politicians appeared more frequently in newspaper coverage and the high level of politicization and polarization in news reporting on COVID-19 may have contributed to the divides in U.S. attitudes on the pandemic. The British Medical Journal reported that the science on the pandemic has been politicized, corrupted, and suppressed for political and financial gain to the detriment of public health (Abbasi, 2020). Politicized information has two detrimental effects on public health. First, it can influence the decision-making and policy on the response to a pandemic. Second, national populations can be misled on the actions they can or should take to protect themselves and those around them.

In June and July 2020, the World Health Organization convened a first-ever scientific conference on infodemiology, the problem with dealing with the large volume of accurate and inaccurate pandemic information (World Health & Organization, 2020b). This new field, initially proposed by Eysenbach (2002), identifies knowledge translation gaps between the best information known by experts and what most people do or believe. The concept was further defined as information science on the Internet or a population with the goal to inform public health and policy (Eysenbach, 2009). Analyzing how people use the Internet for health information and how they share information can provide insights into health behavior of populations. (Choi, Cho, Shim, & Woo, 2016; Eysenbach, 2009).

Analyzing search queries through Google can be used to detect influenza outbreaks in the United States and may have application for discovering potential Public Health Emergencies of International Concern (PHEIC) that might turn into pandemics. Google search data for influenza symptoms was used to develop the now discontinued Google Flu Trends application (Ginsberg et al., 2009). Google Flu Trends initially seemed promising in its ability to estimate the level of influenza 2 weeks faster than the CDC, however, it was discredited when it missed the height of the 2013 season by 140% (Lazer & Kennedy, 2015). From an intelligence viewpoint for warning, a high level of accuracy is not essential for warning rather indicators may be used for additional attention and investigation. Recently, the application of statistical correction methods has shown promise in reducing the errors in Google Flu Trends and may increase its utility in illness estimation and forecasting (Kandula & Shaman, 2019). Additional techniques including remote sensing, communications including social media, and mobile phones use may also provide warning of outbreak. Infectious disease modeling such as the Global Epidemic and Mobility Model have the potential to forecast the worldwide spread of illness considering factors including demographics and human mobility including air travel (Christaki, 2015).

Warning and Response – MERS, SARS

Past PHEICs and pandemics are illustrative of how the detection and warning system functions. The 2003, Severe Acute Respiratory Syndrome (SARS) originated in China and affected more than 8,000 people worldwide with a mortality of about 10% before disappearing (LeDuc & Barry, 2004). The World Health Organization’s Global Outbreak Alert and Response Network (GOARN) was established in 2000 to warn of international public health concerns and provide access to experts and resources for outbreak response (WHO – World Health Organization, 2020a). The World Health Organization (WHO) through its headquarters in Geneva, regional offices, and GOARN were engaged in the global coordination of the response to SARS demonstrating that and infectious disease threat to the world population can be contained (Mackenzie et al., 2004). The response to SARS provided a basis for further progress in the detection and response to the outbreaks of infectious disease and set the stage for the 2012 response to Middle East Respiratory Syndrome.

The 2012 Middle East Respiratory Syndrome (MERS) provided warning of the risks of new (novel) coronaviruses (Mackenzie et al., 2004; WHO – World Health Organization, 2019). MERS emerged in 2012 and has infected nearly 2,500 through November 2019 with a mortality rate of about 34% (CDC – Centers for Disease Control and Prevention, 2020a). As the only U.S. federal health agency for emerging infections disease, the Centers for Disease Control and Prevention (CDC) oversaw preparations for the possible import of MERS, including collaboration with foreign partners (Williams et al., 2015). For COVID-19 and future pandemics, public health authorities at the local, state, national, and international levels must develop and implement a set of metrics aligned with the public health response and enable action by the whole of society including the general public (Nash & Geng, 2020).

Consumers and Stakeholders

In the United States, traditional intelligence has a limited set of consumers, generally restricted to the national security community and policymakers as well as members of Congress with national security oversight functions (Lowenthal, 2015). These consumers include the President and their advisors; members of most of the cabinet departments; Congressional oversight committees such as the House Permanent Select Committee on Intelligence and the Senate Select Committee on Intelligence; foreign partners; and, more recently, state, local, tribal, and territorial governments (ODNI – Office of the Director of National Intelligence (ODNI), 2011). Most nations will have similar lists of intelligence consumers subject to how the government is structured. While arguably, all citizens may be stakeholders in national security, their actual role is limited.

While the U.S. National Strategy for Pandemic Influenza was written for response to avian flu, the measures it contains are applicable to any type of pandemic. Early warning and tracking the spread are critical to containing the spread of disease. Much of the effort is aimed at engaging both international and domestic organizations and partners for both detection of an outbreak of disease and the response to it (Homeland Security Council, 2005).

Political Environment

Youde (2016) noted that the political arena is a poor framework for the international community’s response to challenges posed by health issues like COVID-19, HIV/AIDS, tuberculosis, malaria, and Ebola. While global health has received significantly more attention and resources than previously, it is not because pandemics became a priority political issue. It also must be recognized that response carries risk for policy makers. In response to the 2009 H1N1 outbreak, French Health Minister Roselyne Bachelot 2009 mobilized her ministry and spent hundreds of millions of euros in preparation. When H1N1 did not impact France as expected, she became scapegoat for overreacting to the threat and was forced from office (Eyal, 2020).

As noted, COVID-19 has been a point of political contention between the United States and China since January 2020 with allegations about the point of origin, bioengineering of the virus, accountability, and deliberate use of derogatory language between the countries (Huang, 2020). Chinese messaging including accusations that the virus was planted by the United States into China targets international audiences as well as their own population (Wong, 2020). Incorporating information from all of the various sources into pandemic planning and response is critical although a decision model is not capable of considering all of the social, political and ethical considerations (Shearer, Moss, McVernon, Ross, & McCaw, 2020).

An important consideration in assessing national vulnerabilities is the domestic culture of a nation-state and its sub elements. A possible approach would be to assess the various communities that comprise a country with respect to community efficacy and competence. Public health methodologies provide potential approaches to understanding and evaluating the communities in a country (WHO, Undated). Assessing efficacy looks at social control and communities enforcing behavioral norms, cohesion and social interaction, and a sense of belonging to that community. Community competency includes collaboration in identifying community needs, achieving a working consensus on aims and priorities, forging agreement on how to achieve goals, and effective collaboration on actions (Cottrell, 1976).

In modern societies, it is difficult to define communities, potentially increasing the complexity in assessing how they might react to a pandemic threat. In the United States, for example, communities might be defined in a number of ways including political affiliation, urban versus rural populations, socioeconomic divisions, race, and essential workers (Wilson, 2013). COVID-19 has affected the people in the communities differently and responses have likewise differed. Mask wearing behavior has become politicized with the Republican and Democratic parties becoming identified with wearing or not wearing masks (Kahane, 2020). In the early stages of the pandemic, urban populations were the hardest hit by COVID-19. Since then, less densely populated areas and states have exhibited greater infection rates when adjusted for population (Paul, Arif, Adeyemi, Ghosh, & Han, 2020). Higher income wage earners have had a much greater opportunity to work remotely and, thus, protected themselves from the disease. Lower income workers have had much less opportunity to do so. COVID-19 has affected some minority groups to a much greater extent with Black and Hispanic populations experiencing much higher infection and death rates. Some work populations have been declared essential, including transport workers, grocery clerks, healthcare workers, and food processing (Davenport, Gregg, & Timberg, 2020). These workers generally have little ability to work remotely and often are comprised of workers from ethnic minorities.

There is also an individual component of community competency. The perceived risks of COVID-19 and benefits of healthy behaviors influence individual health actions. People will engage or not engage in health seeking behaviors based on perceived risk.

Conclusions

The business process developed by intelligence agencies has utility for global public health and the medical communities for the management of infodemics and misinformation both during the current COVID-19 pandemic and future emergencies. The study of intelligence failures and successes is also an important area as the relationship between intelligence and policy, and the ways failure can occur, can inform the science relationship with policy (Colglazier, 2020). The most important differences are likely that most information is available to stakeholders and the fact of the world’s population as an important consumer. The World Health Organization’s (World Health & Organization, 2020b) initiative on infodemiology is a vital initiative in managing information that supports the development of health policy as well as shapes the actions of individuals globally. The intelligence process can provide an important point of departure; however, it should be evaluated against other processes that gather and analyze intelligence and information for various consumers.

Areas for Further Research

The World Health Organization (WHO) has published a prioritized research agenda based on their July–August conference on infodemiology (WHO – World Health Organization, 2021a). The series of meetings brought together a multidisciplinary group of experts to define the information problem and develop a way forward for the identification, prioritization, and feasibility of streams of research and underlying research problems (World Health & Organization, 2020b) and, in effect, in February 2021, WHO released a research program to develop a science and discipline around infodemiology (WHO – World Health Organization, 2021a). Interested researchers should reach out to the WHO if they are willing to participate in this important effort.

Further research needs to focus on the opportunities to analyze large data sets, including regional, national and local medical information, supplemented by the data clusters related to demographics and mobility, to examine and process near real-time information on potential threats including the outbreak of the disease. The design and creation of a global early warning system incorporating the medical intelligence is necessary to prevent, detect, respond, and mitigate the consequences of the future pandemic crises. Such a system would require wide-ranging international collaboration of health authorities, intelligence services, academic communities, and experts in strategic communications and education (Moy & Gradon, 2020). Due to the enormous volume of data, it would be necessary to evaluate the opportunities for the application of artificial intelligence (AI) systems and machine learning (ML) to aid and assist agencies responsible for medical intelligence to process and analyze information in order to deliver reliable and actionable intelligence products to stakeholders and decision makers. Google Flu Trends may provide a good point of departure although other search engines may need to be incorporated such as the Chinese engines Baidu and Qihoo 360.

As the current COVID-19 pandemic indicates, the worldwide threat must be addressed on the global scale. The internationalization of pandemic-prevention effort requires universally accepted legal provisions that allow for both the unobstructed exchange of health information and the implementation and enforcement of unified preventive measures. Further research that should be considered is the in-depth study of existing jurisprudence and the formulation of the postulates for appropriate changes in current law, lex lata, and for legislative improvements, lex ferenda.

Another area to consider is the study of the internationalization of health efforts and nonparticipation in such activities. Based on the effects of COVID-19 and its potential aftermath, it needs to be investigated what are the existing effects and prospective consequences of such political decisions as the withdrawal of the United States from the World Health Organization and the noninvolvement of the U.S. in the global vaccine development effort. The comparative study of the feasibility and effectiveness of the national vs. international vaccine design and introduction strategies could provide vital empirical data supporting the decision-making process in the future.

An important research area to also consider is the effectiveness of a broad range of communication measures addressing the disease prevention and mitigation. The COVID-19 pandemic experience indicates, as illustrated in this paper, that the countries that managed to introduce the communication and information strategies early and relied on the community involvement, had a higher rate of public approval for the implementation of various types of mitigation measures such as lockdowns and contact tracing, which translated to lower infection and mortality rates. Finally, further research is needed to study the overlap of disinformation campaigns and fake-news dissemination with the propagation of conspiracy theories and anti-science movements.

Additional information

Notes on contributors

Kacper Gradon

Kacper T. Gradon, Ph.D. is the UCL Honorary Senior Research Associate and visiting professor at the Department of Security and Crime Science, University College London. He is also the Visiting Fulbright Professor at the University of Colorado Boulder – Prevention Science Center and the WHO trainee in Infodemic Management. His research expertise includes multiple homicide, criminal analysis, and counterterrorism.  His current research deals with the application of Open Source Intelligence and digital & Internet forensics and analysis to forecasting and combating cyber-enabled crime and terrorism (including disinformation campaigns). He is also a trained World Health Organization Infodemic Manager. He can be reached at [email protected].

Wesley R. Moy

Wesley R. Moy, Ph.D. is an adjunct lecturer in the Global Security Studies Program in the Advanced Academic Program at Johns Hopkins University. He is also a trained World Health Organization Infodemic Manager. He is a retired intelligence officer from the U.S. Department of Homeland Security and retired U.S. Army strategic intelligence officer. He is a plank holder of the National Counterterrorism Center and has military command experience at the company, battalion, and brigade levels. His expertise is in homeland security intelligence and counterterrorism. He can be reached at [email protected]