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Methods and Applications: Measuring the Capability of Biological Incident Rescue Teams in China: A Fuzzy Analytic Hierarchy Process Based Model — Tianjin Municipality, China, 2022–2023

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  • Abstract

    Introduction

    The swift advancement of biotechnology has presented both opportunities and challenges to our society, thrusting biosafety to the forefront of concern. Consequently, the evaluation of rescue capabilities in the event of a bioterrorism incident becomes of paramount importance. Currently, there is a notable absence of specific measurement criteria and a comprehensive evaluation system. This paper aims to establish a systematic approach towards assessing emergency response capabilities in the context of bioterrorism incidents.

    Methods

    We employed an enhanced Delphi methodology to establish an index evaluation framework. Subsequently, the weight of the judgment matrix was ascertained via the application of the fuzzy comprehensive evaluation approach. This led to the creation of a fuzzy comprehensive evaluation model for bioterrorism rescue capability.

    Results

    A modified Delphi study was conducted involving 11 experts across two rounds, achieving a response rate of 100%. The Kendall coordination coefficients recorded in the first and second rounds were 0.303 and 0.632, respectively (P<0.05). Upon comprehensive analysis involving score, coefficient of variation, and full score ratio, we distinguished five primary indicators and 25 secondary indicators. Subsequently, an evaluation model was developed based on the Analytic Hierarchy Process (AHP) tailored to assess the response to a rescue from bioterrorism.

    Discussion

    The expert panel confirmed consensus on all aspects of the model, validating its comprehensive content. The succeeding course of action involves converting the assessment model to a measurable scale, affirming its functionality, and implementing it in practical evaluation tasks to further enhance the capabilities of the biological incident rescue team.

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  • Funding: Supported by the National Key Research and Development Program of China (2021YFC2600504); relying on the China National Key Research and Development Program-Research on Bioterrorism Prevention and Control Technology in Important Public Places
  • [1] Katz R, Graeden E, Abe K, Attal-Juncqua A, Boyce MR, Eaneff S. Mapping stakeholders and policies in response to deliberate biological events. Heliyon 2018;4(12):e01091. http://dx.doi.org/10.1016/j.heliyon.2018.e01091CrossRef
    [2] GTD. Global Terrorism Database results. 2022. https://www.start.umd.edu/gtd/search/Results.aspx?chart=overtime&search=biological&count=100. [2023-8-19].https://www.start.umd.edu/gtd/search/Results.aspx?chart=overtime&search=biological&count=100
    [3] Zhang LL, Liu X, Li YP, Liu Y, Liu ZP, Lin JC, et al. Emergency medical rescue efforts after a major earthquake: lessons from the 2008 Wenchuan earthquake. Lancet 2012;379(9818):853 − 61. http://dx.doi.org/10.1016/S0140-6736(11)61876-XCrossRef
    [4] Calamai F, Derkenne C, Jost D, Travers S, Klein I, Bertho K, et al. The chemical, biological, radiological and nuclear (CBRN) chain of survival: a new pragmatic and didactic tool used by Paris Fire Brigade. Crit Care 2019;23(1):66. http://dx.doi.org/10.1186/s13054-019-2364-2CrossRef
    [5] Shaw KL, Brook L, Cuddeford L, Fitzmaurice N, Thomas C, Thompson A, et al. Prognostic indicators for children and young people at the end of life: a Delphi study. Palliat Med 2014;28(6):501 − 12. http://dx.doi.org/10.1177/0269216314521852CrossRef
    [6] Zhang H, Huang JS, He X, Lv P, Qiu DL. An analysis of the current status of hospital emergency preparedness for infectious disease outbreaks in Beijing, China. Am J Infect Control 2007;35(1):62 − 7. http://dx.doi.org/10.1016/j.ajic.2006.03.014CrossRef
    [7] Brown GV, Sorrell TC. Building quality in health — the need for clinical researchers. Med J Aust 2009;190(11):627 − 9. http://dx.doi.org/10.5694/j.1326-5377.2009.tb02591.xCrossRef
  • TABLE 1.  The characteristics of experts in the panel.

    CharacteristicsDemographicsCount (n=11)
    GenderMale9
    Female2
    Age (years)35–401
    41–455
    46–502
    Over 503
    SpecialtyUniversity academic5
    Physician4
    Disaster management2
    Title of the jobProfessor9
    Associate professor2
    Education levelMaster3
    Doctoral/PhD8
    Work areaPublic health4
    Disaster rescue1
    Emergency management5
    Rescue technology1
    Working experience (years)5–102
    11–152
    16–204
    Over 203
    Download: CSV

    TABLE 2.  First and second-level index weight distribution and testing.

    IndicatorsWeightsConsistency check
    First Level Indicator
    Capacity building of rescue team A0.13200CI=0.056
    RI=1.120
    CR=0.050
    Maximum characteristic value =5.225
    Emergency response factors of rescue team B0.23053
    Rescue team emergency rescue factors C0.48353
    Rescue team evacuation D0.06378
    Recovery evaluation factors of rescue team E0.09016
    Second Level Indicator
    Emergency response mechanism A10.16734CI=0.071
    RI=1.120
    CR=0.064
    Maximum characteristic value =5.285
    Team building A20.09408
    Material and equipment A30.46158
    Training and exercises A40.20207
    Team composition A50.07493
    Organize, direct and coordinate B10.19634CI=0.067
    RI=0.890
    CR=0.075
    Maximum characteristic value =4.201
    Emergency response mechanism B20.35045
    Information acquisition and analysis B30.33875
    Risk communication B40.11447
    Control of exposed population C10.06259CI=0.088
    RI=1.410
    CR=0.062
    Maximum characteristic value =8.615
    Isolation and quarantine C20.06963
    Field survey and sampling C30.23293
    On-site decontamination C40.16486
    Real-time monitoring C50.04847
    Emergency medical rescue C60.08167
    Epidemiological investigation C70.11844
    Detection and analysis C80.22141
    Research and evaluation D10.58126CI=0.002
    RI=0.520
    CR=0.004
    Maximum characteristic value =3.004
    On-site inspection D20.30915
    Withdraw the team D30.10959
    Physical examination E10.15667CI=0.084
    RI=1.120
    CR=0.075
    Maximum characteristic value =5.336
    Psychological intervention E20.21289
    Recovery of equipment E30.30692
    Mitigation evaluation E40.06353
    Evaluation of effectiveness E50.26000
    Abbreviation: CR=expert authority coefficient; CI=coincidence indicator; RI=random consistency index.
    Download: CSV

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Measuring the Capability of Biological Incident Rescue Teams in China: A Fuzzy Analytic Hierarchy Process Based Model — Tianjin Municipality, China, 2022–2023

View author affiliations

Abstract

Introduction

The swift advancement of biotechnology has presented both opportunities and challenges to our society, thrusting biosafety to the forefront of concern. Consequently, the evaluation of rescue capabilities in the event of a bioterrorism incident becomes of paramount importance. Currently, there is a notable absence of specific measurement criteria and a comprehensive evaluation system. This paper aims to establish a systematic approach towards assessing emergency response capabilities in the context of bioterrorism incidents.

Methods

We employed an enhanced Delphi methodology to establish an index evaluation framework. Subsequently, the weight of the judgment matrix was ascertained via the application of the fuzzy comprehensive evaluation approach. This led to the creation of a fuzzy comprehensive evaluation model for bioterrorism rescue capability.

Results

A modified Delphi study was conducted involving 11 experts across two rounds, achieving a response rate of 100%. The Kendall coordination coefficients recorded in the first and second rounds were 0.303 and 0.632, respectively (P<0.05). Upon comprehensive analysis involving score, coefficient of variation, and full score ratio, we distinguished five primary indicators and 25 secondary indicators. Subsequently, an evaluation model was developed based on the Analytic Hierarchy Process (AHP) tailored to assess the response to a rescue from bioterrorism.

Discussion

The expert panel confirmed consensus on all aspects of the model, validating its comprehensive content. The succeeding course of action involves converting the assessment model to a measurable scale, affirming its functionality, and implementing it in practical evaluation tasks to further enhance the capabilities of the biological incident rescue team.

  • 1. College of Management and Economy, Tianjin University, Tianjin, China
  • 2. Institute of Disaster and Emergency Medicine, Tianjin University, Tianjin, China
  • 3. School of Pharmaceutical Science and Technology, Tianjin University, Tianjin, China
  • 4. Center for Biosafety Research and Strategy, Tianjin University, Tianjin, China
  • Corresponding author:

    Yongzhong Zhang, zyzzjx@tju.edu.cn

  • Funding: Supported by the National Key Research and Development Program of China (2021YFC2600504); relying on the China National Key Research and Development Program-Research on Bioterrorism Prevention and Control Technology in Important Public Places
  • Online Date: October 13 2023
    Issue Date: October 13 2023
    doi: 10.46234/ccdcw2023.174
  • Recent years have seen a rapid increase in both population density and personnel flow, with parallel advancements in biotechnology and information technology. This has resulted in an increasingly complex international biosafety situation, amplified by the potential misuse of biotechnology in bioterrorism activities, posing significant threats to public security and international order (1).

    According to the Global Terrorist Database, there have been approximately 200,000 terrorist attacks worldwide from 1981 to 2021, 41 of which involved bioterrorism. These attacks led to 11 fatalities and 813 disease-related cases (2). Given this context of prevailing biosecurity concerns, current rescue capabilities are proving insufficient to meet the actual requirements.

    Emergency rescue teams and disaster emergency management operations pertaining to biological events are faced with challenges such as inadequate training experience, response capabilities, and a lack of uniform criteria for ability evaluation. Challenges also include an inconsistency in the quality of rescue teams, as well as sluggish team construction. With bioterrorism presenting as a low-probability, high-risk event, there is a scarcity of research literature on the subject. The prevalent assessment system for rescue capability concentrates more on tsunamis, earthquakes, and similar events (3).

    Additionally, the prevailing research relies heavily on the Delphi method. In this method, due to the subjectivity of experts and the ambiguity of indicators, the weights assigned to each indicator are unclear. Consequently, it is challenging to represent the significance of key indices with precise values, leading to less accurate evaluation outcomes (4).

    Therefore, the urgent need for a rigorous evaluation system for the response and rescue in bioterrorism events cannot be overstated.

    • We utilized the Delphi method to construct the indicator system in this research study and deployed the boundary value method for indicator selection. Once identified, we calculated the weight of each index via the analytic hierarchy process and utilized these calculations to construct a fuzzy comprehensive evaluation model. Microsoft Excel (Version 2016; Microsoft, New York, USA) and SPSS software (Version 22.0; IBM, New York, USA) were employed for all statistical analyses. Further details regarding these methodologies are furnished in the Supplementary Material.

    • We elicited insights from experts affiliated with the Chinese Academy of Military Medical Sciences, the Chinese Center for Disease Control and Prevention, and various academic institutions, through comprehensive semi-structured interviews prior to formal correspondence. This approach facilitated dynamic and adaptable dialogues, allowed for customized inquiries according to unique needs, and helped to foster rapport with the interviewees.

      Questions were drafted in accordance with the Guidelines for Capacity Building and Grading Evaluation of National Urban Rescue Teams (draft), exploring their perceptions of bioterrorism events, the core responsibilities of rescue teams, and interdepartmental collaboration, among other relevant topics.

      After assimilating the study’s background, objectives, and methods, the experts offered extensive inputs and recommendations through the provisional indicator framework. Consequently, we refined and improved the draft indicator framework by integrating these expert opinions to guide the subsequent development of the questionnaire.

    • Considering the suitability of the Delphi method and the field-specific requirements of the study, we selected 11 senior professionals as expert participants. These experts were pulled from various domains such as public health, emergency management, or epidemiology. They were drawn from several organizations, including the Chinese Center for Disease Control and Prevention, People’s Liberation Army, People’s Armed Police Force, hospitals, and universities, as well as aggregated from experts at the national and provincial levels, utilizing purposive sampling.

      All chosen expert participants had accumulated over five years of experience in emergency management, disaster-related occupations, or on the subject of research. Each held an associate senior professional title or superior, obtained a minimum of a bachelor’s degree, and was acknowledged for conducting relevant research in their fields. All expert participants voluntarily contributed to the study with good compliance and gave the assurance of their dedication until the study consultations were concluded.

    • Based on the framework derived from literary analysis and expert interviews, the initial draft of the expert consultation questionnaire was developed. This draft showcased the underlying context, explanations pertinent to the index system, assessment of index importance and familiarity, and expert-specific data. Following the first round of expert consultation, the questionnaire was revised to reflect the outcome. The second version incorporated comprehensive scoring averages, coefficients of variance, full score ratios, and each index’s expert opinion from the initial consultation round for reference. Experts assigned weights to every index using a 5-point scale.

    • The Delphi survey was carried out between August 19 and September 20, 2022. We invited a total of 15 specialists from national, provincial, and municipal disease control and prevention centers, health administrative departments, scientific research institutions, and allied domains. After reaching out via email, 11 experts expressed their interest and confirmed their availability to participate. Subsequently, we communicated with these experts through emails soliciting their feedback on the indicator content. This process was repeated for the second round of consultation. Ultimately, all 11 invited experts successfully participated in the full Delphi survey, achieving a response rate of 100%. Information detailing the participant’s demographic characteristics can be found in Table 1.

      CharacteristicsDemographicsCount (n=11)
      GenderMale9
      Female2
      Age (years)35–401
      41–455
      46–502
      Over 503
      SpecialtyUniversity academic5
      Physician4
      Disaster management2
      Title of the jobProfessor9
      Associate professor2
      Education levelMaster3
      Doctoral/PhD8
      Work areaPublic health4
      Disaster rescue1
      Emergency management5
      Rescue technology1
      Working experience (years)5–102
      11–152
      16–204
      Over 203

      Table 1.  The characteristics of experts in the panel.

      Through a combination of literature review, semi-structured expert interviews, and consideration of China’s unique national conditions, the tasks of emergency rescue teams in bioterrorism incidents were distilled into four main responsibilities. These include: controlling exposure within the population and halting transmission to prevent further infection; rapidly curbing the situation through establishing isolation areas, conducting epidemiological investigations, and decontaminating affected regions; identifying biological pathogens and incident types to provide an essential basis for medical services; and mitigating harmful consequences while ensuring thorough on-site recovery. The expert interview questionnaire is presented in Supplementary Table S1.

      In two iterations of expert consultation, our team computed and scrutinized the expert authority coefficient as well as the consistency degree. The given experts’ judgment basis (Ca) values were 0.895 and 0.877 respectively, while the familiarity degree (Cs) values stood at 0.836 and 0.855 in respective order. The expert authority coefficient (CR), on the other hand, was consistently at 0.866, thereby satisfying the Cr≥0.7 criterion. This implies a high level of expert authority and, by extension, the reliability of the expert consultation process (Supplementary Table S2).

      The Kendall coordination coefficient demonstrated a shift from 0.303 (P<0.05) to 0.632 (P<0.05). This increase, falling within the 0.6 to 0.8 range, signifies a high degree of consistency and a low level of significance, thereby indicating a high level of independence among the indicators. Coefficients of variation for the two evaluations were observed to be 0.106 and 0.063 respectively, both under the threshold of 0.25. This detail suggests that expert opinions were notably aligned, yielding consistent evaluation results and validating the credibility of the index system. The results of the Kendall coordination coefficient test can be found in Supplementary Table S3.

      Based on expert feedback and scoring, the boundary value for each index was computed (Supplementary Table S4). The chosen indexes were then consolidated and accordingly adjusted, following expert recommendations. This process eventually yielded five primary indicators and twenty-five secondary indicators for assessing a bioterrorism rescue team’s capability. The significance of these level indexes within the developed evaluation system was gauged in two rounds of expert consultations and group discussions (Supplementary Table S5). Importance was ascertained based on the influence of certain factors on bioterrorism rescue capabilities, thereby determining the final weight of each index (Table 2).

      IndicatorsWeightsConsistency check
      First Level Indicator
      Capacity building of rescue team A0.13200CI=0.056
      RI=1.120
      CR=0.050
      Maximum characteristic value =5.225
      Emergency response factors of rescue team B0.23053
      Rescue team emergency rescue factors C0.48353
      Rescue team evacuation D0.06378
      Recovery evaluation factors of rescue team E0.09016
      Second Level Indicator
      Emergency response mechanism A10.16734CI=0.071
      RI=1.120
      CR=0.064
      Maximum characteristic value =5.285
      Team building A20.09408
      Material and equipment A30.46158
      Training and exercises A40.20207
      Team composition A50.07493
      Organize, direct and coordinate B10.19634CI=0.067
      RI=0.890
      CR=0.075
      Maximum characteristic value =4.201
      Emergency response mechanism B20.35045
      Information acquisition and analysis B30.33875
      Risk communication B40.11447
      Control of exposed population C10.06259CI=0.088
      RI=1.410
      CR=0.062
      Maximum characteristic value =8.615
      Isolation and quarantine C20.06963
      Field survey and sampling C30.23293
      On-site decontamination C40.16486
      Real-time monitoring C50.04847
      Emergency medical rescue C60.08167
      Epidemiological investigation C70.11844
      Detection and analysis C80.22141
      Research and evaluation D10.58126CI=0.002
      RI=0.520
      CR=0.004
      Maximum characteristic value =3.004
      On-site inspection D20.30915
      Withdraw the team D30.10959
      Physical examination E10.15667CI=0.084
      RI=1.120
      CR=0.075
      Maximum characteristic value =5.336
      Psychological intervention E20.21289
      Recovery of equipment E30.30692
      Mitigation evaluation E40.06353
      Evaluation of effectiveness E50.26000
      Abbreviation: CR=expert authority coefficient; CI=coincidence indicator; RI=random consistency index.

      Table 2.  First and second-level index weight distribution and testing.

    • To the best of our knowledge, this represents the first study conducted in China that employs the Delphi survey and the Analytic Hierarchy Process (AHP) to explore expert perspectives, with the aim of establishing a capability evaluation model for biological rescue teams. The derived evaluation model from our study can serve as a useful reference instrumental in the development and enhancement of rescue team capabilities. Furthermore, it provides a robust tool for evaluating the efficacy of rescue teams in the context of bioterrorism incidents.

      The formation of expert panels is integral to the Delphi method. Currently, a well-defined standard for the evaluation of bioterrorism response capabilities does not exist, hence the necessity to establish one through the guidance of an expert panel (5). In the current study, we assembled the panel from a cross-section of professionals in China, including university academicians, hospital executives, and researchers from the CDC. These individuals have established careers in public health, emergency management, and disaster relief and possess a vast array of knowledge in terms of managerial and technical roles. Equipped with a deep understanding and distinctive perspectives on rescue operations, they have generated an evaluative model in this study which can therefore be effectively deployed in critically assessing the management, personal quality, and operational competence of bioterrorism response teams.

      Biological incidents, such as disease epidemics or biohazard spills, pose substantial threats to public health and safety. Consequently, the effective execution of on-site mitigation activities is vital to lessen these events' impact and safeguard lives. These activities extend beyond routine crowd management and decontamination to include critical aspects such as sampling and detection. The quality of the on-site sampling process is paramount as it influences detection accuracy. Given the novelty and diversity of biological warfare agents, their identification relies on both prompt on-site detection and meticulous laboratory monitoring. Optimal outcomes necessitate rapid field detection balanced with rigorous laboratory scrutiny. The nexus between these two aspects deserves due consideration as the detection outcomes significantly influence on-site management strategies and decision-making processes.

      Since the severe acute respiratory syndrome (SARS) outbreak in 2003, China has primarily directed its emergency response capability evaluation system towards public health emergencies (6). The country’s experience with events like the H1N1 influenza pandemic and the coronavirus disease 2019 (COVID-19) pandemic further accentuates the necessity of a robust and efficient emergency response capability evaluation framework.

      Presently, there appears to be an absence of rescue quality assessment. This includes evaluations of comprehensive procedures, the health and equipment deterioration of team personnel, the anticipatory control of the incident, as well as on-site and ultimate controls. To enhance impartiality, third-party evaluations should be contemplated. This approach will not only expedite the incident’s resolution but will also bolster capacity building within rescue teams.

      Team building encompasses the entire cycle of entry, operation, management, and departure of team members. Strategic investment in talent can produce the most enduring contribution to the quality of rescue efforts (7). As such, it is critical to augment funding towards talent development, and to implement regular, capability-focused training and upskilling that align with practical needs, thus fostering sustainable human development. Notably, in the context of China, the role of cross-sectoral collaboration in team building demands acknowledgement, and needs to be incorporated in the initial stages of team design.

      This study, like any other, has limitations that must be recognized. First, due to the infrequency of bioterrorism events and a shortage of related research, we attempted to compose an expert panel for the Delphi investigation by selecting individuals with significant research relevance. Nevertheless, the number of experts chosen was limited, and none were from outside the domestic scope. Secondly, there is a lack of research evaluating the capabilities of rescue teams, which suggests a potential avenue for future research expansion.

      In summary, consensus was achieved on all indicators of the model by the panel of experts, demonstrating good content validity for the overall scale. The subsequent phase involves transforming this evaluation model into a scalable format for distribution via a questionnaire. Moreover, we plan to examine the feasibility of applying this method in other medical capacity assessments, particularly within the realm of emergency medical rescue teams for emerging infectious diseases. Prior to its utilization in actual assessment work, the practicality and implementability of this model must be analyzed in the context of evaluating the capability of a biological event rescue team.

    • No conflicts of interest.

    • All the individuals who participated in this study for their support.

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