Since its inception, Cooperative Threat Reduction has measured hard outcomes for biological threat factors. For over 20 years, the Nunn-Luger Score Card has been used to account for the elimination of all weapons and materials of mass destruction. Historically, the hard target for biological threat reduction was to equip and build facilities, so partners could practice laboratory functions safely and securely; the present hard target is to secure facilities. Most disarmament work occurred in the Former Soviet Union, where progress was easy to measure, for example, the number of facility upgrades. Current threat reduction assistance is harder to measure, hinged to relationships with partners around the globe, specifically through cooperative engagement, capacity building, and sharing knowledge and best practices. The current approach presents challenges to measuring outputs and subsequently justifying investments. One method to better account for biological threat reduction is research networking to enhance national and regional expertise and increase global collaboration. Measuring a network’s effectiveness to threat reduction can be borrowed from International Development government and non-government organizations.
A network for research can reinforce the competence and capacity of emerging economies. The thematic focus of a network may vary depending on the topic; however, the intent for establishing a network remains consistent: to support horizontal frameworks for disease surveillance and response. Implementing a research-based network can (1) promote a common understanding of the risk and prevalence of under-reported and under-diagnosed emerging infectious diseases (e.g., rickettsial pathogens); (2) connect researchers to establish needs and gaps across the biological resiliency spectrum of prevent, detect, respond, and recover; and (3) convene funders from agencies that can support areas in life sciences research to promote consolidation of need and prevent duplication of effort, ultimately yielding more effective national public health policies.
Research-based networks increase the ability of individuals and institutions to engage with a wider global community of peers and stakeholders and undertake high-quality life sciences research that is safe and secure in practice. This approach establishes common values and connections that can override policy driven collaborations or detractions between nations in favor of scientific collaborations to address shared problems. Researchers are best placed to identify and address the health priorities and challenges of their respective nations and provide local and national policy-makers with a broad range of high-quality, relevant evidence to inform decision making.
While the value of these relationships is apparent, qualifying the effectiveness of a research-based network is less clear, which is why the initial investment is critical: setting achievable objectives, tied to short and long-term indicators of success ensure value and potential sustainability of the network. A research-based network needs to be initially rooted in (1) regular, straightforward communication; (2) common values; (3) long-term commitment of the participants; (4) incentivized growth; and (5) opportunities for participation in the process. Much of this can be accomplished by selecting champions of effort, establishing terms of reference or a charter for organization, and a regular process for communication (e.g, meetings, newsletters, and calls).
Much of the framework in measuring the effectiveness of International Development can be applied to measuring the effectiveness of Cooperative Threat Reduction. The two fields share common issues of increasingly complex and changing environments, need to be both credible and cost-effective, and complex issues and trends that impact application over the next several years. Results-based management, which is a broad performance management strategy aimed at achieving change sets End-states, indicators, and targets with a monitoring system for regular data check-ins; this process seems to be the most used by development agencies and hold the most promise for assessing the effectiveness of biological threat reduction.
Written by Katie Leahy firstname.lastname@example.org