农村基层疫情防控逻辑、困境与优化路径

新型冠状病毒疫情发生时,正值中国春节前后,疫情的突发性、严重性和大规模的流动人口跨区域迁移返乡,致使农村成为疫情防控的重要战场。剖析当下农村基层政府在疫情防控工作中的执行场域及样态发现,无缝隙政府模式运作下"网格化+精细化+信息化"的运行机制构成了当下农村疫情防控的主要策略。但当下农村疫情防控仍面临着集体行动不合理、行为习惯不科学、部分党政干部不作为和医疗物资不充足的现实困境。优化基层疫情防控路径,必须提高农村居民卫生意识,凝聚民心共克危机;明确基层应急管理标准依据,增加农村应急物资储备;合理利用大数据,加强基层应急管理信息化建设;推进危机防控内外部监督,建立有效的主体问责和容错机制。     

新冠肺炎疫情对攀西康养产业发展的影响及对策建议

对比四川省五大经济区的疫情,攀西经济区具有确诊人数总量和新增量最少、治愈率最高、治疗时间最短等突出表现,彰显出其独特的"六度"禀赋和优良的生态环境优势。提出把握疫情后康养产业发展的四机遇,把康养产业建设成为四川省重要的支柱产业,构建"医疗+康养+防控"融合发展新模式,融入成渝地区双城经济圈共同打造康养产业集群等对策建议,确保攀西康养产业高质量和可持续发展。     

北京城市发展新区医疗资源空间分布研究

本文借助于Arc GIS软件,探究了北京城市发展新区医疗资源的空间分布情况,与功能核心区和功能拓展区做对比分析。分析结果表示,北京市医疗资源在空间上分布极不均衡,主要集聚在城中心区域,北京城市发展新区医疗机构分布呈现随机状态但比较稀疏。     

重大突发公共卫生事件及其防控政策对互联网零工经济平台劳动生产率的影响——以外卖骑手为例

2019年底新冠疫情的爆发，给人们的工作生活带来了前所未有的冲击，以外卖为代表的互联网零工经济平台对于确保人民生活质量起到了重要作用。为了减少上门配送带来的直接接触，防止疫情扩散，2020年2月6日商务部联合国家卫生健康委员会针对餐饮行业出台了“无接触配送”防控政策。外卖骑手一方面需要稳定输出其劳动生产率，以缓解自身的生存压力；另一方面还需要严格遵守防控政策，避免在配送过程中病毒的传播。本文基于饿了么平台的外卖数据，结合国家卫生健康委员会公布的疫情数据，首先，研究了新冠疫情的严重程度对外卖骑手劳动生产率(配送业绩、产能利用率和配送质量)的影响；其次，本文还探讨了政府推行的“无接触配送”政策是否会缓解新冠疫情对外卖骑手劳动生产率的冲击，以及这种影响随疫情发展的动态变化。研究结果表明，新冠疫情的严重程度会显著负向影响骑手的配送业绩和产能利用率，但是并不会显著影响配送质量。此外，本文发现，“无接触配送”政策会加重疫情对配送业绩的冲击，并且随着疫情逐步得到控制，这种负向影响会越来越大。本文通过对新冠疫情背景下外卖配送问题的探讨，弥补了对重大突发公共卫生事件下零工经济研究的不足，并且为外卖平台和...     

“万达广场”模式城市综合体研究

建筑综合体的出现是城市聚集的产物,当人口聚集、用地紧张到一定程度的时候,在这个区域的核心部分就会出现这样一种综合物业。万达集团历经十余年打造的以"万达广场"为品牌的城市综合体实现了快速发展,预计2012年实现开业70座万达广场。对万达模式城市综合体的研究极具现实意义。     

荆州市中心商业区地下空间开发利用浅析

城市中心商业区地下空间不仅是城市居民社会活动和城市空间的重要组成部分,而且是不可再生资源。地下空间资源作为城市空间资源的重要组成部分之一,可以吸纳相当一部分城市功能和城市活动,有利于城市历史文化的保护,满足城市的更新改造需求,有利于保存地面建筑风貌、创造城市开敞空间,使城市发展获得生机。伴随着荆州市城市化进程的加快,迫于城市中心商业区交通拥挤、环境质量差、人口流动密度大等方面的压力,地下空间的开发利用逐步受到重视。本文在对中心商业区地下空间资源开发利用的影响因素进行简要分析的同时,阐述了开发利用地下空间对于荆州市的作用与意义,提出:我们应当重视对有限的城市地下空间资源进行开发与利用,达到城市地下空间资源的合理利用,真正实现城市的可持续发展。     

更新城镇经营理念统筹城乡经济社会发展

城镇化是统筹城乡经济社会协调发展的最佳途径，它能够整合城乡经济各要素，提高资源的集中与优化配置程度，提高人口的聚集程度和最经济地改善基础设施条件，促进农村经济的结构化升级，推动农村富余劳动力向非农产业的转移。以昭平为例，作为地处山区的农业县，要更为有效地推进城镇化，改变城镇化滞后于经济发展的现状：我认为，用经营城市的理念经营城镇，是推进城镇化的有效途径。     

城市间的“孟母三迁”——公共服务影响劳动力流向的经验研究

本文利用2005年1%人口抽样调查中劳动力流动的微观数据与220个地级市的城市特征数据,研究了公共服务与工资等城市特征对劳动力流向的影响。估计结果显示,劳动力选择流向某个城市,不仅为了获得该城市更高的工资水平和就业机会,而且还为了享受该城市的基础教育和医疗服务等公共服务。通过控制户籍制度的影响和剔除来自公共服务相关行业的劳动力需求方面的影响后,公共服务影响劳动力流向的作用仍然稳健。同时,我们还发现长期流动的劳动力更会选择流向公共服务好的城市。基于我们的实证发现,公共服务均等化政策可以在一定程度上缓解人口向公共服务水平好且工资水平也高的大城市集聚的状况,促使劳动力的空间分布更加均匀化。然而,从变量标准化后的回归结果看,公共服务影响劳动力流向的作用系数都小于工资对劳动力流向的影响,因此,政策制定者不能高估公共服务均等化对分散人口分布的作用,而应对人口继续流向大城市的趋势有科学的预判,并优先对长期居住的外来劳动力提供平等的公共服务。     

重大传染病疫情演化情境下应急物资配置决策建模分析:以新冠肺炎疫情为例

基于对新冠肺炎疫情时空分布的分析,从时段、关键事件、传播动力学、空间分布、感染规模、信息特征、医疗资源等7个维度构建了重大传染病疫情演化的5种情境,提出了各种情境下需要解决的5个关键应急物资配置决策问题。综合考虑应急物资配置的空间、信息、物资、供应、需求和网络等特性,分析了每一个决策问题进行建模优化的关键因素。基于这些关键因素构建了一个多周期贝叶斯序贯决策模型,给出了求解步骤和解析解,并结合武汉疫情进行了算例分析,验证了模型的有效性。在重大传染病疫情演化情境下,综合考虑这些关键因素,应用贝叶斯决策分析进行应急物资配置决策建模有利于建立更加符合实际的决策模型,减少决策损失。     

疫情防控下高校教育管理的数字化建设:现实与未来

新冠肺炎疫情防控过程折射出目前高校教育管理在数字化建设进程中存在诸多薄弱和滞后环节,主要包括数据平台不完善、"数据孤岛"现象严重、教育管理队伍数据理念落后等。这些问题的成因既包括长久以来高校数字化建设资源不均衡等硬件原因,也包括高校对教育管理队伍数据能力建设的重视程度不够、数据能力提升不自觉等内在原因。未来应当要从理念更新、规范制定、平台建设和人才培养等方面下功夫,推动高校教育管理数字化建设,跟上高等教育现代化改革步伐,完成立德树人使命。     

Counterterrorism resource allocation during a pandemic: The effects of dynamic target valuations when facing a strategic terrorist

The outbreak of pandemics such as COVID-19 can result in cascading effects for global systemic risk. To combat an ongoing pandemic, governmental resources are largely allocated toward supporting the health of the public and economy. This shift in attention can lead to security vulnerabilities which are exploited by terrorists. In view of this, counterterrorism during a pandemic is of critical interest to the safety and well-being of the global society. Most notably, the population flows among potential targets are likely to change in conjunction with the trend of the health crisis, which leads to fluctuations in target valuations. In this situation, a new challenge for the defender is to optimally allocate his/her resources among targets that have changing valuations, where his/her intention is to minimize the expected losses from potential terrorist attacks. In order to deal with this challenge, in this paper, we first develop a defender–attacker game in sequential form, where the target valuations can change as a result of the pandemic. Then we analyze the effects of a pandemic on counterterrorism resource allocation from the perspective of dynamic target valuations. Finally, we provide some examples to display the theoretical results, and present a case study to illustrate the usability of our proposed model during a pandemic.     

Governmental anti-pandemic policies,vaccination, population mobility,Twitter narratives,and the spread of COVID-19: Evidence from the European Union countries

We provide large-scale empirical evidence on the effects of multiple governmental regulatory and health policies, vaccination, population mobility, and COVID-19-related Twitter narratives on the spread of a new coronavirus infection. Using multiple-level fixed effects panel data model with weekly data for 27 European Union countries in the period of March 2020–June 2021, we show that governmental response policies were effective both in reducing the number of COVID-19 infection cases and deaths from it, particularly, in the countries with higher level of rule of law. Vaccination expectedly helped to decrease the number of virus cases. Reductions in population mobility in public places and workplaces were also powerful in fighting the pandemic. Next, we identify four core pandemic-related Twitter narratives: governmental response policies, people's sad feelings during the pandemic, vaccination, and pandemic-related international politics. We find that sad feelings’ narrative helped to combat the virus spread in EU countries. Our findings also reveal that while in countries with high rule of law international politics’ narrative helped to reduce the virus spread, in countries with low rule of law the effect was strictly the opposite. The latter finding suggests that trust in politicians played an important role in confronting the pandemic.     

Optimal control analysis of a multigroup SEAIHRD model for COVID-19 epidemic

The COVID-19 pandemic has threatened public health and caused substantial economic loss to most countries worldwide. A multigroup susceptible–exposed–asymptomatic–infectious–hospitalized–recovered–dead (SEAIHRD) compartment model is first constructed to model the spread of the disease by dividing the population into three age groups: young (aged 0–19), prime (aged 20–64), and elderly (aged 65 and over). Then, we develop a free terminal time, partially fixed terminal state optimal control problem to minimize deaths and costs associated with hospitalization and the implementation of different control strategies. And the optimal strategies are derived under different assumptions about medical resources and vaccination. Specifically, we explore optimal control strategies for reaching herd immunity in the COVID-19 outbreak in a free terminal time situation to evaluate the effect of nonpharmaceutical interventions (NPIs) and vaccination as control measures. The transmission rate of SARS-CoV-2 is calibrated by using real data in the United States at the early stage of the epidemic. Through numerical simulation, we conclude that the outbreak of COVID-19 can be contained by implementing appropriate control of the prime age population and relatively strict control measures for young and elderly populations. Within a specific period, strict control measures should be implemented before the vaccine is marketed.     

How Asymptomatic Transmission Influences Mitigation and Suppression Strategies during a Pandemic

Asymptomatic transmission complicates any public health strategies to combat a pandemic, which proved especially accurate in the case of COVID-19. Although asymptomatic cases are not unique to COVID-19, the high asymptomatic case rate raised many problems for developing effective public health interventions. The current modeling effort explored how asymptomatic transmission might impact pandemic responses in four key areas: isolation procedures, changes in reproduction rate, the potential for reduced transmission from asymptomatic cases, and social adherence to public health measures. A high rate of asymptomatic cases effectively requires large-scale public health suppression and mitigation procedures given that quarantine procedures alone could not prevent an outbreak for a virus such as SARS-CoV-2. This problem only becomes worse without lowering the effective reproduction rate, and even assuming the potential for reduced transmission, any virus with a high degree of asymptomatic transmission will likely produce a pandemic. Finally, there is a concern that asymptomatic individuals will also refuse to adhere to public health guidance. Analyses indicate that, given certain assumptions, even half of the population adhering to public health guidance could reduce the peak and flatten the curve by over 90%. Taken together, these analyses highlight the importance of taking asymptomatic cases into account when modeling viral spread and developing public health intervention strategies.     

Pandemic refuges: Lessons from 2 years of COVID-19

This paper relates evidence from the COVID-19 pandemic to the concept of pandemic refuges, as developed in literature on global catastrophic risk. In this literature, a refuge is a place or facility designed to keep a portion of the population alive during extreme global catastrophes. COVID-19 is not the most extreme pandemic scenario, but it is nonetheless a very severe global event, and it therefore provides an important source of evidence. Through the first 2 years of the COVID-19 pandemic, several political jurisdictions have achieved low spread of COVID-19 via isolation from the rest of the world and can therefore classify as pandemic refuges. Their suppression and elimination of COVID-19 demonstrates the viability of pandemic refuges as a risk management measure. Whereas prior research emphasizes island nations as pandemic refuges, this paper uses case studies of China and Western Australia to show that other types of jurisdictions can also successfully function as pandemic refuges. The paper also refines the concept of pandemic refuges and discusses implications for future pandemics.     

Strategic flexibility analysis of HRD research and practice post COVID-19 pandemic

ABSTRACT

While governments, intergovernmental organizations, non-profits, corporations are all aware that disruptions through pandemics and other natural bio-disasters like the COVID-19 pandemic can happen, barely are we proactive about them. Instead, we are always reactive. In a virtual Town Hall meeting of the Academy of Human Resource Development (AHRD) held on 9 April 2020, on the theme ‘How is the pandemic a game-changer for HRD?,’ the President of AHRD, Laura Bierema, challenged HRD scholars to determine the possible futures of HRD scholarship post-COVID-19 Pandemic. This article proposes the use of the Strategic Flexibility Framework (SFF) to determine the possible futures of HRD post-COVID-19 pandemic. I first discuss the SFF as a scenario planning and analysis tool. I then developed four scenarios of possible futures for HRD Research and Practice post-COVID-19 pandemic. These scenarios include the ‘Meaning of work,’ ‘Leadership,’ ‘Contactless Commerce & Education,’ and ‘Volunteerism.’ I conclude by discussing the important opportunities that can serve as intervention points for post-COVID-19 HRD theory, research, and practice.     

震后多目标动态应急医疗设施选址-伤员转运问题研究

地震等灾害的突发性和破坏性常导致部分伤员无法得到快速有效的救治，同时会给伤员造成一定的负面心理，影响救援效率。本文综合考虑救护车辆（救护车、直升机）和医疗设施容量的动态变化、各类伤员生存概率随时间动态变化以及伤员心理状况变化，构建了最大化伤员生存数量和最小化心理成本的震后伤员二级后送模式的医疗设施选址-伤员转运双目标动态规划模型。运用epsilon约束法有效处理双目标模型，以玉树地震后伤员后送问题为例，采用CPLEX对模型进行求解，通过分析医疗资源数量对伤员转运数量的影响，表明在伤员后送过程中，增加临时医院数量或容量与救护车数量比增加后方医院数量或容量与直升机数量更有效；考虑伤员的心理成本，为了提高伤员存活率，在灾害前期，可以通过增加救护车数量，转运更多的重伤员，而中后期提高临时医院容量，尽量优先转运轻伤员。     

Effects of air pollution and weather on the initial COVID-19 outbreaks in United States,Italy, Spain,and China: A comparative study

Contrasting effects have been identified in association of weather (temperature and humidity) and pollutant gases with COVID-19 infection, which could be derived from the influence of lockdowns and season change. The influence of pollutant gases and climate during the initial phases of the pandemic, before the closures and the change of season in the northern hemisphere, is unknown. Here, we used a spatial-temporal Bayesian zero-inflated-Poisson model to test for short-term associations of weather and pollutant gases with the relative risk of COVID-19 disease in China (first outbreak) and the countries with more cases during the initial pandemic (the United States, Spain and Italy), considering also the effects of season and lockdown. We found contrasting association between pollutant gases and COVID-19 risk in the United States, Italy, and Spain, while in China it was negatively associated (except for SO₂). COVID-19 risk was positively associated with specific humidity in all countries, while temperature presented a negative effect. Our findings showed that short-term associations of air pollutants with COVID-19 infection vary strongly between countries, while generalized effects of temperature (negative) and humidity (positive) with COVID-19 was found. Our results show novel information about the influence of pollution and weather on the initial outbreaks, which contribute to unravel the mechanisms during the beginning of the pandemic.     

The Impact of Social Media and Digital Platforms Experience on SME International Orientation: The Moderating Role of COVID-19 Pandemic

Drawing on network learning theory, it investigates the effect of small and medium-sized enterprises' (SMEs) experience of using foreign and domestic social network services (SNS) and foreign and domestic platforms (such as B2B digital platforms) on their international orientation. We further examine the moderating effects of the COVID-19 pandemic on the relationship between digital experience and international orientation. Empirical results from a sample of 373 observations from 250 Chinese SMEs show that their use of foreign SNS and B2B digital platforms has a stronger positive impact on their international orientation than their use of domestic SNS and B2B digital platforms. Even with the COVID-19 pandemic, SMEs' use of foreign SNS still has a stronger positive impact on their international orientation than their use of domestic SNS. Moreover, the COVID-19 pandemic mitigates the positive impact of their use of both foreign and domestic platforms on their international orientation. This study presents some interesting theoretical and practical implications for SMEs' digitalization and internationalization.