Evaluation and Obstacle Analysis of Emergency Response Capability in China

How to improve smart emergency preparedness for natural disasters? ---- Evidence from the experience of ten pilot provinces in China for smart emergency

The natural disasters faced by modern urban systems are complex, with multiple disaster-causing factors coexisting and secondary disasters occurring concurrently. With emergency management moving towards smart, natural disaster response has shifted from emergency-centered response to pre-disaster prevention. How to improve the government's natural disaster emergency preparedness has become an important issue that needs to be addressed. Based on the TOE (Technology-Organization-Environment) framework, the fsQCA method was used to explore the improvement path of emergency preparedness capacity of 10 pilot units in China to deal with natural disasters in 2020. Analyze the group effects and interrelationships of technology level, simultaneous supporting facilities, organizational construction, financial investment, external pressure, and social repercussions. The results show that: there exist four conditional groupings of high emergency preparedness in two modes. Two modes are organization-environment dual-drive and technology-organization-environment triple-drive, which have multiple concurrencies and follow the principle of consistent results. There are substitution effects in the conditional groupings of high emergency preparedness. There are causal asymmetries in the conditional groupings of high emergency preparedness and non-high emergency preparedness. This study aims to explore the smart emergency preparedness of ten pilot and to provide ideas for the overall development of "smart emergency response" and the improvement of emergency preparedness for natural disasters.

Urban residents' self-rescue in response to public health emergencies in China: a qualitative study

BACKGROUND

The abject uncertainty and unpredictability of public health emergencies have plagued various countries. Global health governance and international communities are facing long-term and arduous challenges. The self-rescue ability of individuals in a public emergency may be the most powerful trait to improve the survival rate outside the hospital. The study explores the cognitive ability and attitudes of urban residents in China towards self-rescue in response to public health emergencies. It provides appropriate evidence for improving the self-rescue ability of urban residents in China.

METHODS

Sixteen urban residents were selected using the purposive sampling method for semi-structured interviews. Theme analysis was used to collate and analyse the interview data.

RESULTS

Two themes and five sub-themes were analysed. The two themes included cognition and attitude of Chinese urban residents for self-rescue in an emergency. Urban residents believed that their knowledge and skills for self-rescue in an emergency were low. The ability for emergency self-rescue is affected by multiple factors, with relatively limited options for improvement. Nonetheless, the respondents expressed a desire to accept interventions under psychological crisis and a strong willingness to acquire knowledge and skills required for emergency self-rescue.

CONCLUSION

This study investigated the perceptions and attitudes of Chinese urban residents towards emergency self-rescue. The results support enhanced ability of urban residents to respond to public health emergencies, thereby diminishing the negative outcomes. The findings suggest the need for strategies to address the factors affecting emergency self-rescue.

Unleashing the power of emergency response: controlling natural disasters by addressing environmental risk

The primary focus of the analysis is to investigate the impact of emergency response management and environmental risk on natural disasters by controlling the variables of national income and financial development. To investigate the model empirically, we have employed the quantile autoregressive distributed lag model that estimates the short- and long-run estimates across various quantiles. The long-run estimates of emergency response management are negative and significant only at higher quantiles, i.e., from 60 to 95th quantiles. In the short run, emergency response management's estimated coefficients are negative and significant from 70 to 95th quantiles. Environmental risk shows a significant positive correlation with natural disasters across quantiles, while national income and financial development decrease natural disasters in the long run. Furthermore, we observed the asymmetric impact of emergency response management on natural disasters in both the short and long run.

Constructing big data prevention and control model for public health emergencies in China: A grounded theory study

Big data technology plays an important role in the prevention and control of public health emergencies such as the COVID-19 pandemic. Current studies on model construction, such as SIR infectious disease model, 4R crisis management model, etc., have put forward decision-making suggestions from different perspectives, which also provide a reference basis for the research in this paper. This paper conducts an exploratory study on the construction of a big data prevention and control model for public health emergencies by using the grounded theory, a qualitative research method, with literature, policies, and regulations as research samples, and makes a grounded analysis through three-level coding and saturation test. Main results are as follows: (1) The three elements of data layer, subject layer, and application layer play a prominent role in the digital prevention and control practice of epidemic in China and constitute the basic framework of the “DSA” model. (2) The “DSA” model integrates cross-industry, cross-region, and cross-domain epidemic data into one system framework, effectively solving the disadvantages of fragmentation caused by “information island”. (3) The “DSA” model analyzes the differences in information needs of different subjects during an outbreak and summarizes several collaborative approaches to promote resource sharing and cooperative governance. (4) The “DSA” model analyzes the specific application scenarios of big data technology in different stages of epidemic development, effectively responding to the disconnection between current technological development and realistic needs.

Evaluation of Emergency Response Capacity of Urban Pluvial Flooding Public Service Based on Scenario Simulation

The evaluation of emergency response capability under different pluvial flooding scenarios is an essential approach to improve the emergency response capability of flood disasters. A new evaluation method of emergency response capacity of urban public services is proposed based on urban pluvial flooding scenario simulation. Firstly, inundation area and depth under different pluvial flooding scenarios are simulated based on the SCS-CN model. Following that, space densities of all indicators include inundation area and depth, road network and the emergency public service institutions. Then, the indicator weight is determined by the combined weighting method of entropy weight and coefficient of variation. Finally, the emergency response capacity index (of each pixel) is calculated based on the graph stacking method. Taking Erqi District, Zhengzhou City as an example, the emergency response capacity of public service under different urban flooding scenarios is evaluated. The results show that the spatial distribution difference of public service emergency response capacity in Erqi District, Zhengzhou City is obvious, and with the increase of the precipitation return period, the high value area of public service emergency response capability decreases gradually and the low value area increases gradually. This method takes into account the specific urban flooding scenario and the layout of public service institutions and road networks that have strong practicability. the results of the evaluation can provide a reference for the construction of urban flood emergency response capacity and provide support for emergency decision-making.