Improving access to health facilities in Nouna district,Burkina Faso

The Nouna health district in Burkina Faso, has a population of approximately 275,000 people living in 281 villages, and is served by 25 health facilities, as of 2006. For many people, the time and effort required in traveling to a health facility, which may demand a journey of many kilometers over poor roads on foot, is a deterrent to seeking proper medical care. In this study we examine how access to health facilities in Nouna may be improved by considering the configuration of the road network in addition to the locations of the facilities. We model the situation as a facility location–network design problem and draw conclusions about how best to improve the physical access of the health facilities. Our model shows the extent to which access can be improved when the road network is considered along with facility locations, in contrast to facility locations considered alone.     

A socio-economic optimization model for blood supply chain network design during the COVID-19 pandemic: An interactive possibilistic programming approach for a real case study

In uncertain circumstances like the COVID-19 pandemic, designing an efficient Blood Supply Chain Network (BSCN) is crucial. This study tries to optimally configure a multi-echelon BSCN under uncertainty of demand, capacity, and blood disposal rates. The supply chain comprises blood donors, collection facilities, blood banks, regional hospitals, and consumption points. A novel bi-objective Mixed-Integer Linear Programming (MILP) model is suggested to formulate the problem which aims to minimize network costs and maximize job opportunities while considering the adverse effects of the pandemic. Interactive possibilistic programming is then utilized to optimally treat the problem with respect to the special conditions of the pandemic. In contrast to previous studies, we incorporated socio-economic factors and COVID-19 impact into the BSCN design. To validate the developed methodology, a real case study of a Blood Supply Chain (BSC) is analyzed, along with sensitivity analyses of the main parameters. According to the obtained results, the suggested approach can simultaneously handle the bi-objectiveness and uncertainty of the model while finding the optimal number of facilities to satisfy the uncertain demand, blood flow between supply chain echelons, network cost, and the number of jobs created.     

Reshaping healthcare supply chain using chain-of-things technology and key lessons experienced from COVID-19 pandemic

The COVID-19 (Corona virus disease 2019) pandemic continues to slash through the entire humanity on the earth causing an international health crisis and financial uncertainty. The pandemic has formed a colossal disruption in supply chain networks. It has caused piling higher mortality in patients with comorbidities and generated a surging demand for critical care equipment, vaccines, pharmaceuticals, and cutting-edge technologies. Personal protective equipment, masks, ventilators, testing kits, and even commodities required for daily care have been scarce as lockdown and social distancing guidelines have kicked in. Amidst COVID-19, implementing and executing key processes of the healthcare supply chain (HSC) in a secured, trusted, effective, universally manageable, and the traceable way is perplexing owing to the fragile nature of the HSC, which is susceptible to redundant efforts and systemic risks that can lead to adverse impacts on consumer health and safety. Though the crisis shone a harsh light on the cracks and weaknesses of the HSC, it brings some significant insights into how HSC can be made more resilient and how healthcare industries figure out solutions to mitigate disruptions. While there are innumerable experiences learned from the disruption of this crisis, in this paper, five important areas to analyze the most vital and immediate HSC enhancements including building a resilient supply chain, thinking localization, implementing reliable reverse logistics, breaking down extant silos to achieve end-to-end visibility, and redesigning HSC using digitalization are emphasized. This work identifies important features related to CoT and HSC. Also, this study links these lessons to a potential solution through Chain of Things (CoT) technology. CoT technology provides a better way to monitor HSC products by integrating the Internet of Things (IoT) with blockchain networks. However, such an integrated solution should not only focus on the required features and aspects but also on the correlation among different features. The major objective of this study is to reveal the influence path of CoT on smart HSC development. Hence, this study exploits (i) fuzzy set theory to eliminate redundant and unrelated features; (ii) the Decision-Making and Experimental Evaluation Laboratory (DEMATEL) method to handle the intricate correlation among different features. This fuzzy-DEMATEL (F-DEMATEL) model attempts to direct CoT technology towards smart HSC by identifying the most influencing factors and investors are recommended to contribute to the development of application systems. This work also demonstrates how CoT can act a vital role in handling the HSC issues triggered by the pandemic now and in the post-COVID-19 world. Also, this work proposes different CoT design patterns for increasing opportunities in the HSC network and applied them as imperative solutions for major challenges related to traditional HSC networks.     

Modeling the lockdown relaxation protocols of the Philippine government in response to the COVID-19 pandemic: An intuitionistic fuzzy DEMATEL analysis

The COVID-19 pandemic, which started at Wuhan, has shut down world economies, prompting governments to impose drastic lockdown measures of the economy and the society. As these measures are exhausted, non-COVID-19 related issues such as those associated with the mental and physical well-being of people under lockdowns became an emerging concern. As these issues are evident, not to mention the economic downturn, governments are currently looking at designing lockdown relaxation efforts by simultaneously considering both public health and economic restart. Without documented experiences to rely on, governments are resorting to trial-and-error approach in creating a lockdown exit strategy while preventing succeeding waves of cases that may overwhelm healthcare facilities. Thus, this work pioneers the use of the decision-making trial and evaluation laboratory (DEMATEL) method with intuitionistic fuzzy (IF) sets along with the domain of public health and the emerging COVID-19 pandemic. The DEMATEL handles the intertwined causal relationships among guideline protocols for the relaxation strategy. The intuitionistic fuzzy set theory addresses the vagueness and uncertainty of human judgments in the context of the DEMATEL. A case study of the Philippine government response for the lockdown exit is presented to evaluate the applicability of the proposed method. Findings reveal that compliance of minimum public health standards, limited movement of persons, suspension of physical classes, the prohibition of mass gatherings, non-operation of category IV industries, and non-operation of hotels or similar establishments are the most crucial protocols for such strategy. These findings offer practical insights for the government to allocate resources and impose measures to ensure their implementation, as well as for developing mitigation efforts to cushion their socio-economic impacts. Policy insights and avenues for future works are also discussed.     

COVID-19 crisis and the efficiency of Indian banks: Have they weathered the storm?

The purpose of this study is to determine whether Indian banks were able to weather the COVID-19 storm. We estimate banks’ deposits-generating and operating efficiencies using a two-stage directional distance function-based network data envelopment analysis (DDF-NDEA) approach and seek to capture the immediate impact of COVID-19 on these efficiency measures by comparing their magnitudes in the pre-pandemic (2014/15–2019/20), just 1-year prior to the pandemic (2019/20), and during the pandemic year (2020/21) periods. The study looks at whether the impact of the COVID-19 pandemic was uniform across ownership types and size classes. The empirical findings suggest that the Indian banking system was resilient and withstood the immediate impact of the COVID-19 pandemic. During the study period, however, the large and medium-sized banks experienced some efficiency losses. By and large, regardless of bank group, banks have shown resilience to the shock of the global health pandemic and improvements in efficiency.     

Provisioning health care infrastructure in communities: Empirical evidences from West Bengal,India

We developed a framework to reinvigorate communities in terms of public health care infrastructure provisioning for outpatient needs within the neighborhoods. The health care seeking episode is often influenced by the physical and health care infrastructure availability within the neighborhood, need of the health care seeker as well as personal, household, occupational, and latent perception of the users. This empirical study has been developed for two different groups in West Bengal India, firstly based on location and secondly based on the choice of the health care seeker. In case of resident based approach, we focused on the revisit decision of the rural inhabitants who sometime tend to travel to the regional facilities in urban areas. Facility based approach analyzed the people who were at the regional facilities for health care services. We devised scenarios ascertaining improvisation in service delivery, emergency facility and mobility ease at local public facilities might reduce regional tours and instigate higher utilization of the neighborhood health care facility. We develop integrated choice and latent variable models to incorporate latent perception in choice of scenario for instigating revisit decision. Results showed choice of development scenarios have association with the household structure, social network, locational and infrastructural impedance. This framework lead to two distinct outcomes: (1) method to identify programs, those are essential to by initiate_revisit_to the health care facility (2) perception based assessment of the current mobility and health care infrastructure of the region, which could be instrumental in developing the overall health care infrastructural planning policy as a whole.     

Nexus between drivers of COVID-19 and country risks

COVID-19 has disrupted all spheres of life, including country risk regarding the exposure of economies to multi-dimensional risk drivers. However, it remains unexplored how COVID-19 has impacted different drivers of country risk in a probabilistic network setting. This paper uses two datasets on country-level COVID-19 and country risks to explore dependencies among associated drivers using a Bayesian Belief Network model. The drivers of COVID-19 risk, considered in this paper, are hazard and exposure, vulnerability and lack of coping capacity, whereas country risk drivers are economic, financing, political, business environment and commercial risks. The results show that business environment risk is significantly influenced by COVID-19 risk, whereas commercial risk (demand disruptions) is the least important factor driving COVID-19 and country risks. Further, country risk is mainly influenced by financing, political and economic risks. The contribution of this study is to explore the impact of various drivers associated with the country-level COVID-19 and country risks in a unified probabilistic network setting, which can help policy-makers prioritize drivers for managing the two risks.     

Location and service mix decisions for a managed health care network

For managers of managed health care organizations, the problem of designing a competitive multiple facility network cannot be solved by existing mathematical models. This paper thus presents a nonlinear integer model for determining a facilities design strategy that embodies the economic tradeoffs encompassed in a competitive strategy: minimizing cost and maximizing market share. The integrated location and service mix model determines the number, location and service offerings of facilities that maximize profitability in a two-level hierarchical referral delivery network where an organization's market share is represented by a multiplicative competitive interaction model. To demonstrate the usefulness of the proposed integrated model, a series of problems is solved by an interchange heuristic and compared to the solutions derived by a simpler approach that ignores market competition.     

Location of health care facilities: An analytical approach

The problem of health facilities location is explored under a mathematical optimization approach. Several models are developed for the location of a generalized health facility system in a region in a manner that the selected criteria are optimized. Locational criteria are structured as a hierarchy of social, economic and political attributes and defined analytically using economic and utility theory. A planning framework, based on the models developed, is presented to aid the health planner in the formulation of health facility location decisions.     

Pandemic preparedness and the road to international fascism

The World Health Organization's broad definition of health embraces physical, mental and social well-being. Expressed in its 1946 constitution alongside concepts of community participation and national sovereignty, it reflected an understanding of a world emerging from centuries of colonialist oppression and the public health industry's shameful facilitation of fascism. Health policy would be people-centered, closely tied to human rights and self-determination. The COVID-19 response has demonstrated how these ideals have been undone. Decades of increasing funding within public-private partnerships have corroded the basis of global public health. The COVID-19 response, intended for a virus that overwhelmingly targeted the elderly, ignored norms of epidemic management and human rights to institute a regime of suppression, censorship, and coercion reminiscent of the power systems and governance that were previously condemned. Without pausing to examine the costs, the public health industry is developing international instruments and processes that will entrench these destructive practices in international law. Public health, presented as a series of health emergencies, is being used once again to facilitate a fascist approach to societal management. The beneficiaries will be the corporations and investors whom the COVID-19 response served well. Human rights and individual freedom, as under previous fascist regimes, will lose. The public health industry must urgently awaken to the changing world in which it works, if it is to adopt a role in saving public health rather than contributing to its degradation.     

Spillover and connectedness among G7 real estate investment trusts: The effects of investor sentiment and global factors

This paper examines the dynamic spillover interconnectedness of G7 Real Estate Investment Trusts (REITs) markets. We use the spillover index of Diebold and Yilmaz (2012), the time-varying parameters vector-autoregression (TVP-VAR) model, and the quantile regression approach. The result show that REITs network connectedness is dynamic and experiences an abrupt increase in the first wave of COVID-19 outbreak (2020Q1). We also observe a substantial abrupt decrease in connectedness during the success of vaccination programs (end 2021). The connectedness among assets is much stronger during COVID-19 than before. The REITs of Japan and Italy are net receivers of spillover and those of US and UK are net transmitters of spillovers before and during COVID-19. Conversely, the REIT of Canada and Germany (France) switches from net receivers (contributors) of spillovers before the pandemic to net contributors (receivers) during the COVID-19. Finally, we show that News Sentiment index, Geopolitical Risk index, Economic Policy Uncertainty index, US Treasury yield, and Stock Volatility index influence the spillover magnitude across quantiles.     

Planning for equal transit-based accessibility of healthcare facilities: A case study of Shenzhen,China

Recent location-allocation studies have made considerable progress in optimizing the equality of facility accessibility but are focused on automobile transport to facilities. In cities, however, the transit-based accessibility of essential services is crucial for social equality and sustainable development. In this study, we develop a modified transit-based maximal accessibility equality (MAE) model for optimizing the equality of the transit-based accessibility of healthcare facilities. In this model, equality is quantified as the weighted mean absolute deviation (WMAD) of accessibility across locations. Two scenarios are set up to reallocate resources or allocate newly added resources. The results reveal that the equality of transit-based healthcare accessibility can be significantly improved in both scenarios. A dispersed planning strategy for facilities is suggested to achieve equal accessibility. However, the transit-based optimization results significantly differ from the car-based optimization results, with more supply allocated to facilities close to transit corridors. This finding implies that the traditional car-based MAE model might generate unequal healthcare accessibility for transit-dependent populations and thus lead to biased recommendations for healthcare planning. Furthermore, it shows that traditional car-based optimization may engender a misallocation of healthcare supply, exacerbating the inequality in healthcare accessibility. The necessity of incorporating public transit into public facility planning is highlighted. The improved MAE model can be applied in cities where the supply of public services is relatively adequate and public transit plays an important role in daily mobility.     

Analysis of the impact of COVID-19 pandemic on G20 stock markets

We examine the impact of the COVID-19 pandemic on G20 stock markets from multiple perspectives. To measure the impact of COVID-19 on cross-market linkages and deeply explore the dynamic evolution of risk transmission relations and paths among G20 stock markets, we statically and dynamically measure total, net, and pairwise volatility connectedness among G20 stock markets based on the DY approach by Diebold and Yilmaz (2012, 2014). The results indicate that the total volatility connectedness among G20 stock markets increases significantly during the COVID-19 crisis, moreover, the volatility connectedness display dynamic evolution characteristics during different periods of the COVID-19 pandemic. Besides, we also find that the developed markets are the main spillover transmitters while the emerging markets are the main spillover receivers. Furthermore, to capture the impact of COVID-19 on the volatility spillovers of G20 stock markets, we individually apply the spatial econometrics methods to analyze both the direct and indirect effects of COVID-19 on the stock markets’ volatility spillovers based on the “volatility spillover network matrix” innovatively constructed in this paper. The empirical results suggest that stock markets react more strongly to the COVID-19 confirmed cases and cured cases than the death cases. In general, our study offers some reference for both the investors and policymakers to understand the impact of COVID-19 on global stock markets.     

How have the dependence structures between stock markets and economic factors changed during the COVID-19 pandemic?

This study investigates how the dependence structures between stock markets and economic factors have changed during the COVID-19 pandemic using the dynamic model averaging approach. A series of economic factors such as commodity markets, cryptocurrency, monetary policy, international capital flows, and market uncertainty indices are considered. We find that the importance of economic variables and the sign and size of their coefficients are significantly different from those before the COVID-19 pandemic. The stock markets are most influenced by economic factors during the COVID-19 outbreak.     

How do stock price indices absorb the COVID-19 pandemic shocks?

To assess the resiliency of stock price indices during the COVID-19 crisis, this study provides a distinctive perspective; that is, we evaluate the ability of stock price indices to absorb COVID-19 shocks. We construct the measures of absorptive intensity and duration to identify a stock price’s absorptive capacity. We then employ the Granger causality test and a topology network approach to investigate the interactions of absorptivity among stock price indices. Our results show that stock price absorptivity varies over time and across countries and industries. The US and the Brazil stock indices have relatively high absorptive intensity while short duration. The health care industry shows distinctive trend in absorptive intensity from the other industries. The intensity of the non-cyclical industries such as utilities and consumer staples is high, while the cyclical industries such as banking, real estate, and energy have lower absorptive intensity. Moreover, the utilities, consumer staples, and financials industries are the main resiliency transmitters.     

Metafrontier efficiency analysis for hospital pharmacy services using dynamic network DEA framework

Medication management is a complex but critical process within the healthcare delivery system. The pharmacy department in healthcare facilities is responsible for acquisition, distribution and dispensing of medication to patients that involves a series of network process. This process can be categorized into two main subprocesses: i) pharmacy store and ii) patient services (i.e., ambulatory and inpatient pharmacy). The objective of this study was to investigate the relative efficiency level of the two subprocesses of pharmacy services in Malaysia's public hospitals. We used a nonconvex metafrontier technology to estimate technical efficiency of hospital pharmacies between specialist and nonspecialist hospital categories under the dynamic network data envelopment analysis (DNDEA) framework. For overall efficiency, both specialist and nonspecialist categories had similar mean efficiency scores. However, when measuring the efficiency level according to pharmacy store and patient services separately, the nonspecialist category had a higher mean efficiency score in pharmacy store, whereas for patient service efficiency, both categories had similar results. The patient service efficiency level was lower consistently over time, suggesting that the overall inefficiency of hospital pharmacy is greatly influenced by the inefficiency of the patient service. This suggests that systematic improvements in patient service efficiency should be a higher priority than pharmacy store efficiency to further increase the overall efficiency level. We believe that our findings will provide valuable information to policymakers towards achieving an efficient public healthcare service.     

The effects of health transformation program on patient–healthcare personnel communication and interaction in Turkey

The structure of the Turkish healthcare system is being reorganized under Health Transformation Program (HTP) and some serious changes in healthcare system are being carried out. Effective healthcare personnel and patient communication has a significant impact on patients’ health behaviors and health outcomes. The purpose of this study is to examine the effect of communication dimensions and HTP on patient and healthcare personnel communication and interaction. The survey was conducted with simple random sampling to 9,089 patients in Turkey. Exploratory factor analysis showed three dimensions of communication which are in positive and strong relationship: building relationship, process of physical examination and ending communication. Hierarchical multiple regression was performed to measure the effect of communication dimensions and HTP to patient–healthcare personnel communication and interaction. According to the first step, communication dimensions have a statistically significant effect on patient–healthcare personnel communication and interaction. Introduction of HTP to hierarchical multiple regression explained additional meaningful variance in patient–healthcare personnel communication and interaction, after controlling communication dimensions. It is revealed that, HTP has an important role on communication and interaction. This study has a macro approach and it is limited with the patients’ point of view.     

Improving accessibility to rural health services: The maximal covering network improvement problem

Accessibility to health facilities is a critical factor in effective health treatment for people in rural areas of lesser-developed countries. In many areas accessibility is diminished by the lack of all-weather roads, making access subject to weather conditions. Location-allocation models have been used to prescribe optimal configurations of health facilities in order to maximize accessibility, but these models are based on the assumption that the underlying transport network is static and always available. Essentially, past work has ignored the potential impacts of improvements to the transport system in modeling access. In this paper we propose a model that treats the opposite side of the location/transport equation; that is, a model that treats existing facility locations as fixed and improves health service accessibility by upgrading links of the transport network to all-weather roads. This new model, called the Maximal Covering Network Improvement Problem (MC-NIP) is formulated as an integer-linear programming problem. An application of the MC-NIP model to the Suhum District of Ghana is presented, which shows that even a modest level of road improvement can lead to substantial increases in all-season access to health service.     

Hawkes process modeling of COVID-19 with mobility leading indicators and spatial covariates

Hawkes processes are used in statistical modeling for event clustering and causal inference, while they also can be viewed as stochastic versions of popular compartmental models used in epidemiology. Here we show how to develop accurate models of COVID-19 transmission using Hawkes processes with spatial-temporal covariates. We model the conditional intensity of new COVID-19 cases and deaths in the U.S. at the county level, estimating the dynamic reproduction number of the virus within an EM algorithm through a regression on Google mobility indices and demographic covariates in the maximization step. We validate the approach on both short-term and long-term forecasting tasks, showing that the Hawkes process outperforms several models currently used to track the pandemic, including an ensemble approach and an SEIR-variant. We also investigate which covariates and mobility indices are most important for building forecasts of COVID-19 in the U.S.     

突发公共卫生事件对大学生媒介素养的考量

新冠肺炎疫情爆发以来,网络舆论场规模空前扩大,这既是对大学生媒介能力的挑战,也是提高和重塑大学生媒介素养能力的重要机遇。高校应加强突发公共卫生事件下大学生对网络信息的评判能力和识别能力,从而提高学生的媒介素养和综合能力。