Intelligence Services and the Corona Pandemic

The role of intelligence services in a pandemic like Corona has been amply discussed in public as well as in professional circles. The questions raised and answers given in that context describe the whole range of problems generated by Covid-19, globally affecting governments, societies, economies, financial systems, security, and defense aspects.

 

While billions of individuals are directly or indirectly affected by the consequences of the pandemic, mostly caused by, or resulting from, medical, organizational and sanitary problems, national and international IC (intelligence community) organizations saw themselves immediately confronted with serious questions by governments, hinting at their genuine mission of providing “foreknowledge” or at least timely relevant information on vital major developments. 

What is the role of Intelligence in a pandemic?

As an example that can probably be applied to all other countries as well, the Aspin/Brown Commission Report (1994) summarizes the US IC’s MEDINT mission, as follows:

 

“Collecting and Analyzing Information on World Health Problems. Information on world health problems and the capabilities of foreign countries to cope with them has become increasingly relevant to the ability of the United States to predict and respond to crises in other countries and to protect the health and safety of U.S. military forces and humanitarian workers who may be sent to assist. The movement of dangerous diseases to the United States is another major concern, and health problems can pose threats to the stability of foreign governments. In many cases, information concerning these problems can be obtained without resorting to the use of intelligence capabilities, but in other cases such information will not be readily available. The Commission sees a legitimate role for intelligence here, albeit one that does not involve substantial resources.”

 

The statement underlines the major role and conditions of US medical intelligence: To predict crises in other countries, protect health and safety of military forces and humanitarian workers without absorbing too much money! It remains to be seen whether the limitations involved in that kind of approach can still be maintained, considering the present and possible future pandemics of the same sort and size.

Was the Corona pandemic predictable?

That question seems to be like a natural reflex whenever catastrophes such as pandemics, serious crises, and major political events shake up the world. Usually, the answers given by the intelligence services concerned are:  Principally yes, but…! …Depending always on who poses the question, it used to either be considered naive, unwarranted, or just political rhetoric.

 

Serious answers, though, address fundamental aspects:

  1. On a strategic level, pandemic risk warning has always been part and parcel of Medical Intelligence (MEDINT).  Focusing on and limited to the protection of state actors in their respective military and civilian roles, health early warning tasks have been a standing strategic mission of foreign intelligence services. However, since in most countries, governments normally rely for global pandemic risk analyses and ensuing early warning activities almost totally on national and international scientific academic and private medical research institutions, e.g. the World Health Organization etc., intelligence services never really felt to be on the first line of interest.  In particular, with some highly qualified national scientific institutions doing an outstanding job in predictive pandemic analysis.
  2. Therefore, public health problems, pandemic risks and threats, as well as public sanitary tasks, were, normally, handled by intelligencers only, if operational military or security threats to the state or its institutions were at stake. The regular inclusion of their results in the intelligence cycle in normal times, was, presumably, neither deemed necessary nor mandatory for the IC.

What is the future of MEDINT?

In the face of the present Corona pandemic and with a view to even more serious events in the future, that approach may have to change. Today, intelligence services will have to devote more resources to the global health data and analyses in order to fulfill their mission.

 

On the operational level, an all-source intelligence approach would be more than justified, with the focus directed to:

  1. HUMINT (e.g. recruitment of epidemiologists and other medical specialists capable of predicting major threats);
  2. SIGINT (e.g. emergency reports, exact number of affected victims, change of communication behavior, social tensions, military movements, etc.);
  3. IMINT (e.g. enlargement or construction of new medical facilities, medical support vessel movement, etc.)
  4. SOCMINT (e.g. reactions by social groups, protest movements activities, etc.)
  5. OSINT (e.g. reactions of media, militant or criminal groups, social networks, blogs, etc. to restriction and emergency policies by governments, etc.)

 

That increased effort, however, will not be possible without increased funds and additional technology. In particular, with view to force protection, disinformation operations, fake news, influence and public pressure campaigns on international organizations, there is a strong need for technological and IT support and assistance.

What technological solutions in support of MEDINT are available?

The combination of the different intelligence areas HUMINT, SIGINT, IMINT, SOCMINT, and OSINT creates both political and technological challenges. Each of the areas has special characteristics which must be taken into account in the system design:

  1. HUMINT: The number of HUMINT messages is likely to be lower. However, these are formal reports or simple slips of paper that must be processed using OCR.
  2. SIGINT: The SIGINT area provides a wide range of information. It can be of structured technical nature or contain unstructured data, such as text, audio, or images. One of the challenges is to unify the data model for all SIGINT information. It requires the cooperation of all SIGINT providers which can be a problem.
  3. IMINT: Imaginary information is usually pre-processed by AI-based object detections. Thus, one of the IMINT challenges will be to set up a suitable automatic processing system. It can be assumed that there are only a few AI models for mobile hospitals available so far. The lack of suitable training data complicates the automatic processing of imaginary data.
  4. SOCMINT and OSINT: Both SOCMINT and OSINT require that a data fusion system can be expanded quickly. A new valuable open-source service must be fully integrated into a system within a few days and must not lead to downtime. In contrast to SIGINT, open-source information needs additional validation as the data source is not reliable at all.

 

In addition to the above-mentioned area-specific challenges, there are others:

  1. How is security guaranteed when so many different analysts work on the same system?
  2. How can analysts from different departments collaborate and do we need to motivate them to do so?
  3. How do you ensure that the system scales with your requirements and has no downtime despite the necessary regular updates?

 

The Traversals team consisting of experienced developers, OSINT analysts, and an excellent advisory board has tried out many approaches in the past and followed the most promising ones. The result is a Data Fusion Platform that already answers a multitude of questions raised, subject to continuous improvement.

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