Emergency Management Information Research Articles

Analysis of the Collaborative Governance Mecharnism of public Emergency Events —— Take the Rainstorm in Henan and Beijing as an Example

In the context of climate change, the increase in extreme weather events and natural disasters has caused a certain degree of damage to economic development, social life, and the physical and mental health of the people. Therefore, further research, promotion, and optimization of the collaboration mechanism between various emergency departments and relevant departments have become particularly important. The research topic of this article is how to establish and optimize the collaboration mechanism of various emergency departments in emergency events, and propose some specific measures and suggestions. The research methods of this paper are as follows: using the case analysis method, through combing and comparing the emergency measures taken in the two cases of extremely heavy rainstorm in Henan Province in 2021 and rainstorm in Beijing in 2023, this paper focuses on the analysis of the shortcomings of the specific emergency cooperation measures taken in the two events, and points out the links that can be improved; Using the comparative analysis method, this paper conducts a comparative study on the collaborative governance mechanism of rainstorm disasters in Beijing and Henan from the three stages of preparation, response and recovery. Finally, this article proposes specific suggestions for the allocation of emergency coordination materials, the implementation of extensive and effective public publicity, the improvement of communication equipment establishment, the promotion of emergency management information sharing, the strengthening of the rights and responsibilities of the emergency management department, and the establishment of a unified governance center to establish emergency cooperation mechanisms.

Epidemiological characteristics of public health emergency events of varicella in China, 2006-2021

Objective: To understand the epidemiological characteristics of public health emergency events (PHEE) of varicella in China from 2006 to 2021 and related response performances. Methods: The data of varicella PHEE in 31 provinces of China from 2006 to 2021 were collected through the Public Health Emergency Management Information System, Microsoft Excel 2019 software and SPSS 26.0 statistical software were used to conduct descriptive epidemiological, statistical analysis on the time, area, location distribution, scale and epidemic management. Results: A total of 11 443 PHEE involving 341 048 related cases were reported from 2006 to 2021, with an annual attack rate of 1.78%-3.80% and a total attack rate of 2.33% (341 048/14 624 042). The number of PHEE and related cases of varicella decreased from 1 107 (35 349) in 2007 to 262 (6 884) in 2012 (Z=-2.40, P<0.001), then increased year by year to 1 318 (42 649) in 2019 (Z=2.58, P<0.001), with a significant decline since 2020. The varicella PHEE in China presents the seasonal characteristics,the peak is from April to June and from October to December, respectively. The sub-peak of varicella PHEE in eastern China generally appears 1-2 months earlier than in central and western China. Varicella PHEE reports are mainly distributed in eastern China, the attack rate is relatively high in western China, school-reported varicella PHEE was 88.26% of the total reports (10 099/11 443). The epidemic scale of varrcella PHEE typically range from 10 to 29 cases per year among the given outbreaks. The M (Q1, Q3) of average number of cases, average duration, and average reporting interval of PHEE were 23 (16,35), 20 (14, 26) days, and 9 (5,19) days, respectively, and the reporting interval was positively correlated with the duration (r=0.854, P<0.001). Conclusions: The varicella PHEE in China from 2006 to 2021 has not been effectively controlled. Schools are the key places to prevent and control varicella PHEE. Improving the sensitivity of varicella PHEE monitoring, strengthening the timely disposal of varicella epidemic, and promoting varicella vaccination are effective measures to prevent and control varicella PHEE.

Factors impacting bus selection: Differences between the middle and later stages of COVID-19

As one of the most important modes of transportation, buses play an essential part in people's journeys. However, less has been known about whether and under what circumstances people will choose to travel by bus during the COVID-19 epidemic. Based on the theory of planned behaviour (TPB), the study examined how the impact of the different stages of COVID-19 (middle stage and later stage), the quality of public transport services and the fear of COVID-19 (FCV-19) are associated with individual choices.An online survey of 404 participants from Anhui Province, China was conducted. We collected data on demography information, together with related TPB constructs (behavioural intentions, self-reported bus use, attitudes, subjective norm, perceived behavioural control, fear of COVID-19 and bus passenger satisfaction). After verifying the scales and the basic TPB model, we established a structural equation model (SEM).Our analysis of the survey data yielded the following results: 1) In the middle stage of the COVID-19 epidemic, fear of COVID-19 was significantly related to the intention to take the bus, and passenger satisfaction was insignificantly related to travel by bus. 2) In the later stage of the COVID-19 epidemic, passenger satisfaction was significantly related to the decision to take the bus, and fear of COVID-19 was significantly related to the intention to travel by bus.These research results not only reveal the internal mechanism of passengers choosing to take the bus but also provide important information for future disaster emergency management. On this basis, some feasible suggestions are made to avoid the decrease of bus ridership and help the public transportation system recover from the crisis.

Conceptual Framework of an Information for Emergency Management for Higher Education in Thai Supply Chain

The objective of research were to develop conceptual framework of an information for emergency management for higher education in Thai supply chain and to evaluate conceptual framework of an information for emergency management for higher education in Thai supply chain. The research sample totalling ten experts consisted of five experts on supply chain , five experts on information system. All of expert must have educational qualification at the doctoral degree level, and must have more than more than four years of work experience The research tool was questionnaire assessing the suitability about conceptual framework of an information for emergency management for higher education in Thai supply chain comprises five elements namely main components suppliers, University, Good service and security, Customers. The data analysed by using arithmetic mean and standard deviation. The assessment about conceptual framework of an information for emergency management for higher education in Thai supply chain using Black-Box technique. The overall model evaluation result was validated at a “Good” level, suggesting that conceptual framework of an information for emergency management for higher education in Thai supply chain aims to support sustainable information system development.

The cycle of disparity: A gap analysis of emergency management and information technology.

Emergency management (EM) requires an appropriate understanding of its situational context in real time. This involves constant communication between emergency operations and administration, so that informed, coordinated decisions can be made in a constantly changing environment using the most critical and updated information. Challenges in EM include adapting to rapidly changing technologies, adoption, and communication. The goal of this needs assessment is to examine how the effective collection and communication of information has been affected by the technology developed to support it, to identify critical disconnects between emergency management professionals and information technology and telecommunications (ITT) professionals, and to identify opportunities for improved application and user interface development. The methods for this qualitative analysis enumerate and categorize some of the communication challenges faced by the EM community as identified by interviews conducted with subject matter experts using the strengths, weaknesses, opportunities, and threats technique. This study finds that the absence of ITT professionals with experience in emergency response and, conversely, the absence of EM professionals working in EM application development create a "cycle of disparity," where the key findings of this study both arise from one central input and feed into to each of the other key findings in a continuous cycle, reinforcing what threats and weaknesses already exist.

Retracted: Volunteer Service Participation Emergency Management Information Collection Platform Based on Big Data Technology

Retracted: Volunteer Service Participation Emergency Management Information Collection Platform Based on Big Data Technology

Agent-based societal impact modeling for infrastructure disruption and countermeasures analyses

Infrastructure disruptions can severely affect societal well-being. Quantifying the societal impacts of infrastructure disruptions and identifying appropriate countermeasures to mitigate them are critical for decision-makers. In this regard, this study measured the societal impact by considering people's achievement/intolerance of survival-related activities and proposed an agent-based societal impact simulation model (ABSISM) for quantitative estimation of the impact. The ABSISM incorporated dynamic interactions between households’ emergency behaviors, infrastructure disruption, and government countermeasures in typhoon disaster scenarios and designed decision rules for three types of agents: household, store, and shelter agents. Specifically, household agents acquire life-supporting resources (food and water) from store and/or shelter agents, and prioritize daily activities to perform under restricted resources by minimizing their experienced suffering level; store and shelter agents provide household agents with essential resources during a disaster. Additionally, the government's response measures (infrastructure recovery, forewarning information issuance, and distribution of supplies) were incorporated into the ABSISM as factors directly or indirectly influencing agents’ behaviors. Finally, this study presented an illustrative case study of Osaka to demonstrate the ABSISM's practical applicability and examines the effectiveness of government countermeasures on reducing the societal impact, which could provide insightful information for emergency management and promotion of sustainable cities.

Deep learning enables super-resolution hydrodynamic flooding process modeling under spatiotemporally varying rainstorms

Real-time information on flooding extent, severity, and duration is necessary for effective metropolitan flood emergency management. Existing pluvial flood analysis methods are unable to simulate real-time regional flooding processes under spatiotemporally varying rainstorms. This paper presents a deep learning-enabled super-resolution hydrodynamic flood analysis method to simulate the real-time pluvial flooding process over a large area under spatiotemporally varying rainstorms. Compared with existing flood downscaling techniques, which are limited to flow depth, the proposed method produces high-resolution flow depth and velocity predictions, providing more comprehensive information for flood emergency management. The proposed method adopts a coarse-grid hydrodynamic model to generate a low-resolution flood map time series, which is subsequently converted to high-resolution flood maps by a deep learning model. The deep learning model can be trained using a limited number of assumed rainfall scenarios, which greatly reduces data preparation effort. The proposed method is applied to a complex terrain of 352 km2 in Hong Kong that covers both mountainous and urban areas. Results show that the proposed method simulates the spatiotemporal variations of flood depth and velocity with root mean square errors as low as 0.082 m and 0.088 m/s, respectively, and correlation coefficients of 0.962 and 0.921, respectively. The computation time for a 48-h rainfall event in the study area is less than 30 s, which is 2690 times faster than the direct fine-grid hydrodynamic analysis. The deep learning-enabled super-resolution hydrodynamic flood analysis method provides a promising computational tool for emergency flood risk management.

Extracting Useful Emergency Information from Social Media: A Method Integrating Machine Learning and Rule-Based Classification.

User-generated contents (UGCs) on social media are a valuable source of emergency information (EI) that can facilitate emergency responses. However, the tremendous amount and heterogeneous quality of social media UGCs make it difficult to extract truly useful EI, especially using pure machine learning methods. Hence, this study proposes a machine learning and rule-based integration method (MRIM) and evaluates its EI classification performance and determinants. Through comparative experiments on microblog data about the "July 20 heavy rainstorm in Zhengzhou" posted on China's largest social media platform, we find that the MRIM performs better than pure machine learning methods and pure rule-based methods, and that its performance is influenced by microblog characteristics such as the number of words, exact address and contact information, and users' attention. This study demonstrates the feasibility of integrating machine learning and rule-based methods to mine the text of social media UGCs and provides actionable suggestions for emergency information management practitioners.

The Benefit of Informed Risk-Based Management of Civil Infrastructures

One of the most interesting applications of Structural Health Monitoring (SHM) is the possibility of providing real-time information on the conditions of civil infrastructures during and following disastrous events, thus supporting decision-makers in prompt emergency operations. The Bayesian decision theory provides a rigorous framework to quantify the benefit of SHM through the Value of Information (VoI) accounting for different sources of uncertainties. This decision theory is based on utility considerations, or, in other words, it is based on risk. Instead, decision-making in emergency management is often based on engineering judgment and heuristic approaches. The goal of this paper is to investigate the impact of different decision scenarios on the VoI. To this aim, a general framework to quantify the benefit of SHM information in emergency management is applied to different decision scenarios concerning bridges under scour and seismic hazards. Results indicate that the considered decision scenario might tremendously affect the results of a VoI analysis. Specifically, the benefit of SHM information could be underestimated when considering non-realistic scenarios, e.g., those based on risk-based decision-making, which are not adopted in practice. Besides, SHM information is particularly valuable when it prevents the selection of suboptimal emergency management actions.

Emergency Information Communication Structure by Using Multimodel Fusion and Artificial Intelligence Algorithm.

With the development of The Times, social events are increasing, and emergency management has gradually become the main helper to solve the crisis in the public domain. By observing the current situation of many countries and regions, we can find that various types of public crises often occur in many countries and regions in the world, which have severely affected people's daily life, lives, and property. Through long-term research and analysis, it can be known that the emergency management mechanism currently established in China has certain shortcomings. The communication problem of emergency information is likely to cause the emergency work to not proceed smoothly. In addition, problems in the communication channels of emergency information are likely to cause problems in the cooperation of various departments when people carry out emergency management work, and the efficiency of the government in dealing with problems will also be reduced in real scenarios. In order to improve the efficiency of emergency information management, this paper aims at the various problems existing and facing in the construction of emergency management system. On this basis, the integration of various relevant emergency information management plan models is analyzed and sorted out, and based on the research and integration of the development of artificial intelligence algorithms. The main research results of emergency information management at home and abroad are comprehensively studied and evaluated. Finally, a QG algorithm based on more model fusion is developed. In the process of analysis, this article uses artificial intelligence algorithms to build a prediction model of multiple modes and collects the data needed to build the model by random extraction. Through the analysis of different data sets, it is used as the basic training data for prediction. Through comprehensive analysis, the model constructed in this paper can promote the sharing of emergency information among departments to a certain extent.

Volunteer Service Participation Emergency Management Information Collection Platform Based on Big Data Technology

In order to fully integrate various emergency management information resources for volunteer service, the author proposes a volunteer service participation in emergency management information collection platform based on big data technology. Taking a municipal government as an example, the current situation of information integration in emergency management is investigated and studied, the needs of various departments are analyzed through interviews and questionnaires, and the problems existing in the government’s information integration are studied. It tries to build a scientific, reasonable, and operational government information integration model based on theories of government information disclosure, government emergency management, and metadata technology. The survey results show the following observation: In the survey results of “the reasons that affect the integration of emergency linkage information of a city government,” the first place is the poor information communication channels between departments, accounting for 22.7%; The second and the third are “administrative system restrictions” and “protection of the interests of the department,” accounting for 21.4% and 19.4%, respectively. It is worth noting that the technical problem of information management is also one of the important factors affecting the government’s emergency response management, accounting for 19.1%. Conclusion. This study analyzes the main shortcomings and reasons of the existing sharing models, so as to construct a reasonable information sharing work model.

Transmission and mortality risk assessment of severe fever with thrombocytopenia syndrome in China: results from 11-years' study

BackgroundThe transmission and fatal risk of severe fever with thrombocytopenia syndrome (SFTS), an emerging infectious disease first discovered in China in 2009, still needed further quantification. This research aimed to analyze the SFTS clusters and assess the transmission and mortality risk for SFTS.MethodsBoth epidemiological investigation and case reports regarding SFTS clusters in China during 2011–2021 were obtained from the Public Health Emergency Information Management System of the Chinese Center for Disease Control and Prevention Information System. The transmission risk was evaluated by using the secondary attack rate (SAR) and relative risk (RR). Mortality risk factors were analyzed using a logistic regression model.ResultsThere were 35 SFTS clusters during 2011–2021 involving 118 patients with a fatality rate of 22.0%. The number of clusters annually increased seasonally from April to September. The clusters mainly occurred in Anhui (16 clusters) and Shandong provinces (8 clusters). The SAR through contact with blood or bloody fluids was much higher than that through contact with non-bloody fluids (50.6% vs 3.0%; χ2 = 210.97, P < 0.05), with an RR of 16.61 [95% confidence interval (CI): 10.23–26.97]. There was a statistically significant difference in the SAR between exposure to the blood of a deceased person during burial preparation and exposure to the living patients’ blood (66.7% vs 34.5%; χ2 = 6.40, P < 0.05), with an RR of 1.93 (95% CI: 1.11–3.37). The mortality risk factors were a long interval from onset to diagnosis [odds ratio (OR) = 1.385), 95% CI: 1.083–1.772, P = 0.009) and advanced age (OR: 1.095, 95% CI: 1.031–1.163, P = 0.01).ConclusionsThe SFTS clusters showed a high mortality rate and resulted in a high SAR. Contact with a bleeding corpse was associated with a higher infection risk, compared with contacting the blood from living patients. It is important to promote early detection and appropriate case management of patients with SFTS, as well as improved handling of their corpses, to prevent further transmission and mortality.Graphical abstract

Comparison of varicella outbreaks in schools in China during different vaccination periods

ABSTRACT The purpose of this study was to investigate the outbreak trend of chickenpox and the epidemiological characteristics of outbreak related cases from 2017 to 2021, and compare the impact of voluntary self-funded single dose vaccination versus mandatory two-dose vaccine vaccination on varicella outbreaks. The data of varicella outbreaks in Jiangsu Province from 2017 to 2021 come from the national public health emergency management information system. We randomly chose 70 outbreaks from 2019 to 2020 for study in order to better understand the features and regularity of breakthrough varicella(BV). In pilot cities with two doses of free VarV, the number of outbreaks decreased from 306 in 2017 to 123 in 2021, while the total number of cases related to the outbreak decreased by 64.6% (P < .01), the median size of the outbreak decreased from 24 cases (range:6–146) to 21 cases (range:10–93) (P < .01), and the incidence rate also decreased from 2.01/100 to 1.33/100. The proportion of cases with high fever, severe rash and complications in the BV group was lower than that in the primary varicella (PV), and the differences were statistically significant. The incidence rate of varicella among students who had post-exposure prophylaxis (PEP) activities was 1.42% (488/ 33,878), and 1.63% (2468/ 148,943) among those who did not (p = .005). The single-dose varicella vaccination was less effective in controlling the outbreaks, and the success of the full implementation of the routine two-dose varicella vaccination plan in the pilot cities provided a basis for implementation in the whole province, and long-term follow-up studies are needed to evaluate the effect of the new strategy in the future.

Research on Solving Path of Negative Effect of “Information Cocoon Room” in Emergency

The “information cocoon” can hinder the normal dissemination and flow of emergency information during emergencies. It is important to explore the factors of this effect and to resolve the negative effects of the information cocoon, so as to help the public to “break out of the cocoon” and help the government to better promote emergency information management. Based on information ecology theory and the S-O-R model, this study designed questionnaires using a Likert five-level scale and selected 388 publics from several smart city pilot areas in Changsha, Zhuzhou, Shaoshan, and Yueyang cities in Hunan Province. Field research was conducted based on four factors, information ontology, information technology, government regulation, and social network, and empirical analysis was conducted through structural equations. The study shows that information ontology, information technology, government regulation, and social networks have significant effects on the information cocoon effect by influencing the reinforcement of public information preferences. Among them, government regulation ( P = 0.34) has the most significant effect on the reinforcement of public information preferences, followed by information ontology ( P = 0.32) and social networks ( P = 0.31), and information technology ( P = 0.29) has the weakest effect. Combining the results of empirical analysis, we propose a four-dimensional path of “information-technology-regulation-value” to break the cocoon. By optimizing information ontology, using technology for good governance, promoting algorithmic fairness, and enhancing social stickiness, we help the public break through the shackles and negative effects of the information cocoon and promote the harmonious, stable, and healthy development of the emergency information field.

Epidemiological and Clinical Characteristics of Influenza Outbreaks Among Children in Chongqing, China.

Influenza is a global serious public health threat. Seasonal influenza among children in Chongqing has been a heavy health burden. To date, few studies have examined the spatial and temporal characteristics of influenza. This research sheds new light on correlating them with influenza outbreaks with data of over 5 years (2014–2018). All cluster outbreaks among preschool and school-age children reported in Chongqing were collected through the Public Health Emergency Management Information System. The demographical, epidemiological, and clinical data of the cases were analyzed. From 2014 to 2018, a total of 111 preschool- and school-based influenza-like illness outbreaks involving 3,549 cases were identified. Several clinical symptoms that were analyzed in this study showed significant contrast between influenza A and B. Spatial autocorrelation analysis over the 5-year data detected Xiushan district being the most likely cluster. The exploration of the spatial distribution and clinical characteristics of influenza cluster of children in Chongqing could help the effective implementation of health policies. Future studies should be conducted to monitor the outbreaks of influenza among children.

Analysis of epidemic characteristics of anthrax in China from 2017 to 2019 and molecular typing of Bacillus anthracis

Objective: To analyze the epidemiological characteristics of anthrax in China from 2017 to 2019 and molecular typing of Bacillus anthracis isolated from some provinces (autonomous regions). Methods: Surveillance data of anthrax cases reported from 2017 to 2019 in the Infectious Disease Surveillance information System of China Disease Prevention and Control and the Public Health Emergency Reporting and Management Information System were collected, and descriptive epidemiological methods were used to analyze the epidemic characteristics, including the temporal, geographic and demographic distribution of this disease. A total of 47 strains of Bacillus anthracis isolated from 2017 to 2019 were analyzed by canSNP and MLVA15. Results: A total of 951 cases of anthrax were reported from 2017 to 2019, of which 938 were cutaneous anthrax, representing 98.63% of the total number reported. It was mainly distributed in the west and northeast of China, and the three provinces with the highest number of cases were Gansu (215), Sichuan (202) and Qinghai (191). Cases had been reported throughout the year, more cases occurred in the summer and autumn, and August was the month with the most cases,66.35% (211/318), 72.32% (243/336) and 68.01% (202/297) of cases were reported during June to September. The age distribution was mainly between 20 and 59 years old, accounting for more than 80% of all cases. The number of male cases was significantly higher than that of female cases, the ratio of male to female was about 3∶1. The occupations were mainly herdsmen and farmers, accounting for 49.70% to 58.18% and 31.45% to 36.70%, respectively. Public health events occurred every year, and 29 events had been reported from 2017 to 2019. canSNP analysis showed that 37 of the 47 strains belonged to the A.Br.001/002 subgroup and 10 belonged to the A.Br.Ames subgroup. MLVA15 analysis showed that there were 17 genotypes, of which 10 genotypes contained only one strain. Conclusion: Cutaneous anthrax was the predominant clinical type in China from 2017 to 2019.The seasonal, geographic and demographic distribution characteristics were evident.Molecular typing methods such as canSNP and MLVA15 can be used to trace the source of infectious diseases and provide technical support for anthrax prevention and control.

Characterization of the host range and sensitivity to fungicides of Trichothecium spp. associated with fruit rot in the field and in storage

AbstractDuring 2017–2019, we observed Trichothecium spp. causing fruit rot in the field and in storage. This study was conducted to examine morphological differences of the species from different hosts, reveal the species’ potential host range, and evaluate the efficacy of five fungicides. Six strains of Trichothecium spp. isolated from nectarine, peach and walnut were selected. Although the colony morphology, mycelial growth rate and spore size differed among hosts, phylogenetic analysis based on the internal transcribed spacer and part of the 5ʹ end of the β‐tubulin gene showed that all tested strains belonged to Trichothecium roseum. For its host range, 23 kinds of fruit were examined using T. roseum strain YT‐1 as an inoculum; 10 kinds of fruit, including pear, apple, mango, Chinese chestnut, pepino melon, fig and durian, were susceptible to T. roseum, with minimum inoculation concentrations ranging from 104 to 105 spores/ml. The fungicides that most effectively inhibited the six isolates were fluazinam and fludioxonil, with EC50 values of 0.07–0.1 and 0.01–0.04 μg/ml, respectively, followed by difenoconazole (0.81–2.96 μg/ml), boscalid (5.43–13.51 μg/ml) and azoxystrobin (9.18–27.25 μg/ml). Improvement of the shelf life of nectarines held in plastic trays was explored using allyl isothiocyanate (AITC) against T. roseum YT‐1. The application of 10 μl/L AITC significantly suppressed disease symptoms. The findings provide useful information for future disease emergency management in the field and for food preservation.

Blockchain: A potential technology to improve the performance of collaborative emergency management with multi-agent participation

As the complexity of emergencies continues to increase, responding to them often exceeds the capabilities of any single public agency, multi-agent collaborative participation is an inevitable tendency in the development of emergency management. In the collaborative emergency response, it is important to support various responders with a unified platform to assist in decision-making, distribution of resources, and coordination of emergency operation. In recent years, blockchain has provided strong support for the innovation of emergency management mechanisms with its technical advantages such as distributed storage, decentralization, consensus algorithms, tamper-proof, traceability, and smart contract. This study firstly reviews the development of blockchain and its application in emergency management. Secondly, the connotation and key dilemmas of the multi-agent collaborative emergency management mechanism are expounded from two aspects of the multi-agent participation and the construction of a collaborative mechanism. Then, the possibility of using blockchain to facilitate the innovation of multi-agent collaborative emergency management mechanism is analyzed from the aspects of emergency management information sharing, resource storage and distribution, the rights and obligations of multiple subjects, supervision, reward and punishment. Finally, a conceptual model of a multi-agent collaborative emergency management mechanism based on alliance chain and public chain is proposed. The application of blockchain provides a new perspective and motivation for the innovation of emergency management system. This study provides a new method for improving the multi-agent collaborative emergency management mechanism, and is an important supplement and innovation to existing emergency management studies.

Design and simulation of a counter measure analysis system in a decision support system ONERS for nuclear emergency

In this work, a Counter Measures Analysis System (CMAS) is developed in the Online Nuclear Emergency Response System (ONERS) to suggest protective actions for minimizing radiation exposure to people during accidental releases of radionuclides to the environment. CMAS is designed with PHP, Java and MySQL database engine in Web-GIS environment to enable online computations and visualization of results. CMAS maps the dispersion model simulated radiological doses to each village unit by spatial aggregation of dose from all the grid cells contained within village unit and delineates the domain into areas assigned with several protective actions taking into account of dose criteria. It also computes residual and averted doses along with timing of different protective actions in each village. The effectiveness of CMAS is tested by simulating the consequences for a hypothetical accident. Results suggest that CMAS provides realistic estimates of protective actions following the spatial dispersion and dose pattern at each village unit. Comparison with conventional grid-based calculations indicate CMAS provides more practical suggestion of protection strategy compared to grid-based suggestions due to the conservative nature of estimates and attribution of all necessary information for emergency management. Sensitivity tests with respect to accident source term and dose criteria indicate that CMAS produces corresponding variation in impacted areas and protective actions confirming consistent performance.