A Socio-Computational Approach to Predicting Bioweapon Proliferation

Predicting countries that will seek bioweapons (BW) enables the international community to act early in order to prevent these countries from acquiring such weapons. Unfortunately, the literature on countries’ BW programs mainly consists of case studies that focus on one or a few countries. Although case studies are valuable, they are typically not predictive. Moreover, case studies require substantial effort and expertise, and are thus unfeasible for all countries. In this paper, we develop a computational methodology that predicts countries that will seek BW. Our methodology consists of a sociocultural model and indicators that computationally capture expert opinions about why and how countries acquire BW. Our methodology systematically examines all countries in the world and can be used by non-BW experts based on publicly available data. We validate our methodology by examining the methodology’s ability to predict historical BW proliferators.

[1]  Neil Narang,et al.  Poor Man’s Atomic Bomb? Exploring the Relationship between “Weapons of Mass Destruction” , 2014 .

[2]  Paul F. Diehl,et al.  The Correlates of War (Cow) Project Direct Contiguity Data, Version 3.0 , 2002 .

[3]  J. Singer Reconstructing the correlates of war dataset on material capabilities of states, 1816–1985 , 1988 .

[4]  M. Chevrier Impediment to proliferation? Analysing the biological weapons convention , 1995 .

[5]  Gregory D. Koblentz,et al.  Pathogens as Weapons: The International Security Implications of Biological Warfare , 2004, International Security.

[6]  Erik Gartzke,et al.  Determinants of Nuclear Weapons Proliferation , 2007 .

[7]  Sally Totman Democratic People’s Republic of Korea , 2010, World Statistics Pocketbook (Ser. V).

[8]  E. Croddy China's role in the chemical and biological disarmament regimes , 2002 .

[9]  J. David Singer,et al.  Formal alliances, 1815—1939 , 1966 .

[10]  R. Zilinskas,et al.  Iraq's biological weapons. The past as future? , 1997, JAMA.

[11]  M. Diab Syria's chemical and biological weapons: Assessing capabilities and motivations , 1997 .

[12]  Bruce Bueno de Mesquita,et al.  European Community Decision Making : Models, Applications, And Comparisons , 1994 .

[13]  J. David Singer,et al.  Formal Alliances, 1816-1965: an Extension of the Basic Data , 1969 .

[14]  Roger C Herdman,et al.  Technologies Underlying Weapons of Mass Destruction , 1993 .

[15]  Ken Alibek,et al.  Biohazard: The Chilling True Story of the Largest Covert Biological Weapons Program in the World--Told from the Inside by the Man Who Ran It , 1999 .

[16]  Gregory D. Koblentz,et al.  Predicting Peril or the Peril of Prediction? Assessing the Risk of CBRN Terrorism , 2011 .

[17]  J. Tucker,et al.  Historical trends related to bioterrorism: An empirical analysis. , 1999, Emerging infectious diseases.

[18]  M. Thobaben Chemical Addiction , 2009 .

[19]  Noah E. Friedkin,et al.  Social influence and opinions , 1990 .

[20]  A. Cohen Israel and chemical/biological weapons: History, deterrence, and arms control , 2001 .

[21]  Susan B. Martin The Role of Biological Weapons in International Politics: The Real Military Revolution , 2002 .

[22]  M. Leitenberg,et al.  Biological Weapons in the Twentieth Century: A Review and Analysis , 2001, Critical reviews in microbiology.

[23]  Kathleen M. Carley,et al.  Remote assessment of countries’ nuclear, biological, and cyber capabilities: joint motivation and latent capability approach , 2015, Social Network Analysis and Mining.

[24]  A. Lake Confronting backlash states , 1994 .

[25]  John Stuckey Capability distribution, uncertainty, and major power war, 1820–1965 (1972) (with Stuart A. Bremer and , 2012 .

[26]  R. Harkavy Pariah states and nuclear proliferation , 1981, International Organization.

[27]  Bruce Bueno de Mesquita,et al.  Decision-making models, rigor and new puzzles , 2004 .