Government Epidemic Prevention and Economic Growth Path Under Public Health Emergency: Theoretical Model and Simulation Analysis

Epidemiologic and clinical updates on viral infections in Saudi Arabia

In the past two decades, the world has witnessed devastating pandemics affecting the global healthcare infrastructure and disrupting society and the economy worldwide. Among all pathogens, viruses play a critical role that is associated with outbreaks due to their wide range of species, involvement of animal hosts, easily transmitted to humans, and increased rates of infectivity. Viral disease outbreaks threaten public health globally due to the challenges associated with controlling and eradicating them. Implementing effective viral disease control programs starts with ongoing surveillance data collection and analyses to detect infectious disease trends and patterns, which is critical for maintaining public health. Viral disease control strategies include improved hygiene and sanitation facilities, eliminating arthropod vectors, vaccinations, and quarantine. The Saudi Ministry of Health (MOH) and the Public Health Authority (also known as Weqayah) in Saudi Arabia are responsible for public health surveillance to control and prevent infectious diseases. The notifiable viral diseases based on the Saudi MOH include hepatitis diseases, viral hemorrhagic fevers, respiratory viral diseases, exanthematous viral diseases, neurological viral diseases, and conjunctivitis. Monitoring trends and detecting changes in these viral diseases is essential to provide proper interventions, evaluate the established prevention programs, and develop better prevention strategies. Therefore, this review aims to highlight the epidemiological updates of the recently reported viral infections in Saudi Arabia and to provide insights into the recent clinical treatment and prevention strategies.

Interface-Engineered Field-Effect Transistor Electronic Devices for Biosensing

Promising advances in molecular medicine have promoted the urgent requirement for reliable and sensitive diagnostic tools. Electronic biosensing devices based on field-effect transistors (FETs) exhibit a wide range of benefits, including rapid and label-free detection, high sensitivity, easy operation, and capability of integration, possessing significant potential for application in disease screening and health monitoring. In this perspective, the tremendous efforts and achievements in the development of high-performance FET biosensors in the past decade are summarized, with emphasis on the interface engineering of FET-based electrical platforms for biomolecule identification. First, an overview of engineering strategies for interface modulation and recognition element design is discussed in detail. For a further step, the applications of FET-based electrical devices for in vitro detection and real-time monitoring in biological systems are comprehensively reviewed. Finally, the key opportunities and challenges of FET-based electronic devices in biosensing are discussed. It is anticipated that a comprehensive understanding of interface engineering strategies in FET biosensors will inspire additional techniques for developing highly sensitive, specific, and stable FET biosensors as well as emerging designs for next-generation biosensing electronics.

The Early Warning Mechanism of Public Health Emergencies Through Whistleblowing: A Perspective Based on Considering the Uncertainty of Risk Perception

Purpose

During the early warning period of public health emergencies, the information released by whistleblowers on the risk posed by the given event can reduce uncertainty in the public's risk perception and help governments take timely actions to contain the large-scale dissemination of risk. The purpose of this study is to give full play to whistleblowers and draw attention to the risk events, forming a pluralistic model of the risk governance during the early warning period of public health emergencies.

Methods

We construct an evolutionary game model of the early warning of public health emergencies through whistleblowing that involves the government, whistleblowers, and the public, discussing the mechanism of interaction between these subjects under the uncertainty of risk perception. Furthermore, we use numerical simulations to analyze the influence of changes in the relevant parameters on the evolutionary trajectory of the subjects' behaviors.

Results

The results of the research are obtained by numerical simulation of the evolutionary game model. The results show that the public's cooperation with the government encourages the latter to take a positive guidance strategy. Increasing the reward for whistleblowers within an acceptable cost, strengthening the propaganda of the mechanism and the higher level of risk perception of the government and whistleblowers will promote whistleblowers' vocalization actively. When the government's reward for whistleblowers is lower, the whistleblowers choose negative vocalization with the improvement of the public's risk perception. If there is no mandatory guidance from the government at this point, the public is prone to passively cooperating with the government owing to a lack of risk-related information.

Conclusion

Establishing an early warning mechanism through whistleblowing is important for containing risk in the early warning period of public health emergencies. Building the whistleblowing mechanism in daily work can improve the effectiveness of the mechanism and enhance the public's risk perception better when the public health emergencies arise.

Trade-Off between COVID-19 Pandemic Prevention and Control and Economic Stimulus

The coronavirus disease 2019 (COVID-19) pandemic has posed a severe threat to public health and economic activity. Governments all around the world have taken positive measures to, on the one hand, contain the epidemic spread and, on the other hand, stimulate the economy. Without question, tightened anti-epidemic policy measures restrain people's mobility and deteriorate the levels of social and economic activity. Meanwhile, loose policy measures bring little harm to the economy temporarily but could accelerate the transmission of the virus and ultimately wreck social and economic development. Therefore, these two kinds of governmental decision-making behaviors usually conflict with each other. With the purpose of realizing optimal socio-economic benefit over the full duration of the epidemic and to provide a helpful suggestion for the government, a trade-off is explored in this paper between the prevention and control of the epidemic, and economic stimulus. First, the susceptible-infectious-recovered (SIR) model is introduced to simulate the epidemic dynamics. Second, a state equation is constructed to describe the system state variable-the level of socio-economic activity dominated by two control variables. Specifically, these two variables are the strengths of the measures taken for pandemic prevention and control, and economic stimulus. Then, the objective function used to maximize the total socio-economic benefit over the epidemic's duration is defined, and an optimal control problem is developed. The statistical data of the COVID-19 epidemic in Wuhan are used to validate the SIR model, and a COVID-19 epidemic scenario is used to evaluate the proposed method. The solution is discussed in both static and dynamic strategies, according to the knowledge of the epidemic's duration. In the static strategy, two scenarios with different strengths (in terms of anti-epidemic and economic stimulus measures) are analyzed and compared. In the dynamic strategy, two global optimization algorithms, including the dynamic programming (DP) and Pontryagin's minimum principle (PMP), respectively, are used to acquire the solutions. Moreover, a sensitivity analysis of model parameters is conducted. The results demonstrate that the static strategy, which is independent of the epidemic's duration and can be easily solved, is capable of finding the optimal strengths of both policy measures. Meanwhile, the dynamic strategy, which generates global optimal trajectories of the control variables, can provide the path that leads to attaining the optimal total socio-economic benefit. The results reveal that the optimal total socio-economic benefit of the dynamic strategy is slightly higher than that of the static strategy.

The impact of public health events on green economy efficiency in the context of environmental regulation

Public health crises have become one of the greatest threats to sustainable global economic development. It is therefore important to explore the impact of public health events on green economic efficiency. However, few studies have specifically examined the relationship between public health security and green economic efficiency. Based on the relevant data of 30 Chinese provinces from 2011 to 2019, this paper explores the impact of public health on green economic efficiency by establishing a four-stage SBM-DEA model to construct green economic efficiency indicators and using a panel model. A moderating effect model is established to explore the moderating effect of environmental regulation on the impact of public health on green economic efficiency. In addition, this paper examines the heterogeneity of public health impact on green economic efficiency in terms of geographic location, carbon pilot, and transportation level. It is found that, first, public health events have a significant hindering effect on green economic efficiency. Second, environmental regulation has a significant moderating effect on the impact of public health events on green economic efficiency. Third, the impact of public health events on green economic efficiency changes from hindering to facilitating as the intensity of environmental regulation increases. Fourth, the impact of public health events on green economic efficiency is heterogeneous in terms of geographic location, carbon pilot, and transportation level. The above studies have implications for how to balance economic development and environmental protection in case of a public safety event.

An Intelligent Mechanism for COVID-19 Emergency Resource Coordination and Follow-Up Response

As a serious emergency in 2020, COVID-19 had a great impact on people's lives. In this paper, short-term and long-term response to emergency supplies needs after the outbreak of COVID-19 in a region is studied. Firstly, a comparative study of different regional resource coordination options in the early stages of COVID-19 is conducted using a multiobjective decision-making approach to arrive at the optimal solution. Then, a system dynamics model is established for the follow-up development of the epidemic, to predict the long-term development trend of the epidemic, and to study the urgency of the needs of different materials in different periods. The results show that time and satisfaction are the two most important indicators in the decision-making of the material deployment programme in the early stages of an outbreak. In the long-term control of the epidemic, the number of patients with minor illnesses generally peaks around 20 days, while the number of patients with severe illnesses generally peaks around 40 days, providing a focus for the supply of supplies at different times in the actual development of the epidemic, in order to better and more effectively control the epidemic and reduce inefficient consumption of supplies.