Sector Capacity Research Articles

Evaluation of healthcare facilities and personnel distribution in Lagos State: implications on universal health coverage

ABSTRACT Background Nigeria is considering making Universal Health Coverage (UHC) a common policy goal to ensure that citizens have access to high-quality healthcare services without crippling debt. Globally, there is an acute shortage of human resources for Health (HRH), and the most significant burden is borne by low-income countries, especially in sub-Saharan Africa. This shortage has considerably constrained the achievement of health-related development goals and impeded accelerated progress toward universal health coverage. We examine the existing human resource capacity and the distribution of health facilities in Lagos state in this study, discussing the implications of our findings. Methods The study is descriptive using secondary data analysis. We leverage census-based primary data collected by NOIPoll on health facility assessments in Lagos state. The collected data was analyzed using counts, ratios, rates, and percentages. Results We observe a ratio of 5,014 people to 1 general medical doctor, 2,942 people to 1 specialist, 2,165 people to 1 nurse, and 5,117 people to 1 midwife, which are far higher than the WHO recommendation. We also observe that the ratio of nurses to general medical practitioners is 2.2:1 in urban areas and 2.7:1 in rural. In contrast, the ratio of nurses to specialist medical doctors is 1.3:1 in the urban area and 1.5:1 in the rural areas of Lagos state. The overall nurse per general medical practitioner ratio is 2.3:1 and 1.4:1 for specialist medical doctors. 77.2% of the health facilities surveyed were in the urban areas, with private-for-profit facilities accounting for 82.9%, government facilities accounting for 15.4%, and NGOs/faith clinics accounting for 1.7%. Primary healthcare facilities account for 75.3% of the facilities surveyed, secondary and tertiary facilities account for 24.6% and 0.08%, respectively. Alimosho LGA has the most health facilities (77.38% PHCs, and 22.62% SHCs) and staff strength specifically for general medical practitioners, specialists, nurses, and midwives (16.9%, 19.9%, 16.7%, 17.1%, respectively). Eti-Osa LGA has the best density ratio for generalist doctors, specialist doctors, and nurses per 10,000 (4.42, 12.96, and 11.34 respectively), while Ikeja has the best midwife population density ratio 5.46 per 10,000 population. Conclusion The distribution of health personnel and facilities in Lagos State is not equitable, with evident variation between rural and urban areas. This inequitable distribution could affect the physical distance of health facilities to residents, leading to decreased utilization, ultimately poor health outcomes, and impaired access. Much like child mortality, maternal mortality also exhibits a correlation with healthcare worker density. As the physician density increases linearly, the maternal mortality rate decreases exponentially. However, due to the low number of healthcare workers in Lagos state, doctors, nurses, and midwives are frequently unavailable during childbirth, resulting in increasing infant, neonatal, and maternal death. As such, the government should adopt the UHC strategy in its distribution of facilities and personnel in the state for adequate coverage and optimal performance of the facilities. Also, additional investments are needed in some parts of the state to improve access to tertiary health facilities and leverage private sector capacity.

Tuberculosis incidence and its socioeconomic determi-nants: developing a parsimonious model.

Tuberculosis is a widespread communicable disease, which is one of the top 10 causes of demise globally. Several regression models have been built, and then utilized for the Tuberculosis incidence projections. However, when fitting a multiple linear regression model, an analysis must account for multicollinearity aspects. The present study aimed to develop a parsimonious model that produces unbiased results based on socioeconomic variables as predictors of Tuberculosis incidence. Ecological study. Data were collected from the Karaganda Regional Center of Phthisio-pulmonology and Bureau of National Statistics. By multiple linear regression model, we investigated associations between Tuberculosis incidence rate and socioeconomic determinants in Karaganda region, Kazakhstan, during 2001-2019. A Principal components analysis was performed on the socioeconomic variables with oblique rotation. Furthermore, associations of Tuberculosis incidence with the principal components derived from the Principal components analysis were assessed. The incidence of Tuberculosis in Karaganda region decreased over the period of 2001-2019. Economic development and healthcare capacity were negatively correlated with Tuberculosis incidence. A multiple linear regression equation on Tuberculosis incidence (y) was developed with economic development (x1) and healthcare capacity (x2) clustering two components (utilizing Principal components analysis) to eliminate collinearity: y = 1442 - 454.3x1 - 211.4x2. The incidence of Tuberculosis decreased with the increase of economic development and healthcare capacity. In conclusion, the study indicated that economic development and healthcare capacity are closely associated with the incidence of Tuberculosis. The findings support the implementation of optimal preventive measures for Tuberculosis control, including improving the level of economic status, increasing social protection, health expenditure, and strengthening health sector capacity, which are key determinants of the incidence of Tuberculosis.

Public-private partnership to rapidly strengthen and scale COVID-19 response in Western Kenya.

In Africa almost half of healthcare services are delivered through private sector providers. These are often underused in national public health responses. To support and accelerate the public sector's COVID-19 response, we facilitated recruitment of additional private sector capacity by initiating a public-private partnership (PPP) in Kisumu County, Kenya. In this manuscript we demonstrate this PPP's performance. COVID-19 diagnostic testing formed the basis for a PPP between Kenyan Medical Research Institute (KEMRI), Department of Health Kisumu County, PharmAccess Foundation, and local faith-based and private healthcare facilities: COVID-Dx. First phase COVID-Dx was implemented from June 01, 2020, to March 31, 2021 in Kisumu County, Kenya. Trained laboratory technologists in participating healthcare facilities collected nasopharyngeal and oropharyngeal samples from patients meeting the Kenyan MoH COVID-19 case definition. Healthcare workers in participating facilities collected patient clinical data using a digitized MoH COVID-19 Case Identification Form. We shared aggregated results from these data via (semi-) live dashboards with all relevant stakeholders through their mobile phones and tablets. Statistical analyses were performed using Stata 16 to inform project processes. Nine private facilities participated in the project. A patient trajectory was developed from case identification to result reporting, all steps supported by a semi-real time digital dashboard. A total of 4,324 PCR tests for SARS-CoV-2 were added to the public response, identifying 425 positives, accounting for 16% of all COVID-19 tests performed in the County over the given time-period. Geo-mapped and time-tagged information on incident cases was depicted on Google maps through PowerBI-dashboards and fed back to policymakers for informed rapid decision making. Preferential COVID-19 testing was performed on health workers at risk, with 1,009 tests performed (up to 43% of all County health workforce). We demonstrate feasibility of rapidly increasing the public health sector COVID-19 response through coordinated private sector efforts in an African setting. Our PPP intervention in Kisumu, Kenya was based on a joint testing strategy and demonstrated that semi-real time digitalization of patient trajectories can gain significant efficiencies, linking public and private healthcare efforts, increasing transparency, support better quality health services and informing policy makers to target interventions.

Value-for-Money Drivers in Public-Private Partnerships in Affordable Housing in Indonesia: An Analytic Network Process Perspective

This study aimed to identify the factors expected to drive value-for-money (VfM) when using public-private partnerships (PPPs) for affordable housing in Indonesia. Utilising economy, efficiency and effectiveness as the VfM criteria, the study employed the analytic network process to determine the relative importance of 13 factors compiled from the literature review. The factors were then grouped into five clusters: private sector capacity, transparent and competitive procurement, risk and reward allocation, public sector capacity and the nature of the long-term contract. The data were gathered through a survey of 20 experts with hands-on experience in Indonesia’s PPPs. Effectiveness was identified as the most critical VfM criterion, implying that bringing other VfM aspects into public decisions is indefensible if the outcome, providing low-income customers with suitable housing at rents they can afford, is not achieved. The justified scope and size of the project, clear output-based specifications, quality project planning and preparation and long-term service delivery emerged as the most critical factors enhancing VfM, each with a different focus on a specific VfM criterion based on local weights. At the cluster level, risk and reward allocation ranked the highest. This study also acknowledges several limitations and provides directions for future research.

A Practical Narrative of Tariff Protection in Pakistan

This research work quantifies the changes in effective rates of protection in Pakistan during the last decade of 2011–20. Based on its results, it supports a more flexible trade policy in Pakistan. Further, it identifies the sectors with strong and weak long-run productive capacities and highlights the role of trade barriers in these industries. A key concern is the decreasing productive capacity of textile and leather sectors where the textile industry has the largest share in the total exports from Pakistan. Hence, there is a dire need to invest more in research and development activities in such industries. Finally, the country needs to increase its range of export items and export destinations with more favourable terms of trade, which can be achieved by reducing its historically high import tariff rates. Effective Rate of Protection, Input-Output Table, Industry, Trade, Pakistan JEL Classification: C67, D57, F6, L5, R15

Features of spatial and structural transformations of the economy: European experience and Ukrainian realities

The article focuses on the study of the structural features of the economy of the EU member states and Ukraine. Labor productivity and capital productivity in a sectoral section are analyzed. In particular, changes in the dynamics of labor and capital productivity during 2014-2021 are examined. Based on the results, the sectors that are leaders and can act as determinants of the productive capacity of Ukraine and its regions are identified. The article reveals that the most intensive growth of labor productivity is recorded in such sectors as temporary accommodation and organization of food, as well as information and telecommunications. Capital productivity under the prevailing instability of the dynamics of this indicator is recorded only in construction and in information and telecommunications. The regions of Ukraine are ranked and grouped according to the intensity of labor productivity growth. The comparative analysis of the rates of growth (decline) of capital productivity in the sectors of the economy of Ukraine is carried out. It shows that the growth rate of labor productivity exceeds that of capital productivity. Based on the assessment of the ratio of wage growth rates and labor productivity in the economic sectors, the hypothesis regarding the predominance of labor productivity growth rates over wage growth rates in the majority of the economic sectors is verified. Drivers contributing to the growth of the productive capacity of economic sectors are characterized. The main strategic priorities of the structural transformations of the domestic economy in wartime and post-war recovery are determined, in particular regarding the development of the military-defense complex, which will ensure the long-term political and economic security of Ukraine and the development of industrial and innovative structural elements of the country’s economic system. The article emphasizes the need to create and develop a national innovation platform, which should be a component of the innovation market and the formation of the state system of legal protection of intellectual property, the demands for reform of which were put forward in the process of deepening European integration reforms.

Autoregressive distributed lag estimation of bank financing and Nigerian manufacturing sector capacity utilization

<abstract> <p>This study examined the short-term and long-term relationship between credit financing by commercial banks and capacity utilization of the manufacturing sector in Nigeria. The study employed both classical Multiple Linear Regression (OLS-MLR) and the autoregressive distributed lag model (ARDL) to analyze data representing the period 1981–2020 relating to sectoral credit finance,labor employment,and capacity utilization from the <xref ref-type="bibr" rid="b6">Central Bank of Nigeria Statistical Bulletin (2020)</xref> and <xref ref-type="bibr" rid="b38">World Bank Development Indicators (2021)</xref>. Further,the two estimation procedures were performed within a classical endogenous Cobb-Douglas production function framework that takes technical change into consideration. The bounds test indicated no long-term relationship between bank financing and average capacity utilization of the manufacturing sector in Nigeria. However,the ARDL results revealed that bank financing exerts a positive but insignificant short-term impact on the average capacity utilization of the manufacturing sector in Nigeria. Consequently,the researchers affirm that credit financing by commercial banks in Nigeria has no significant impact on the capacity utilization of the country's manufacturing sector,in neither the short run nor the long run.</p> </abstract>

Integrating digital solutions into national health data systems through public-private collaboration: An early experience of the SPICE platform in Kenya.

Public-private collaborative efforts to address healthcare challenges in low- and middle-income countries have been the focus of digital initiatives to improve both access and quality of health services. We report the early feasibility, experience, and learnings of migrating healthcare data generated from a proprietary, privately owned cloud-based environment into an on-premises National Health Data Center (NHDC) in compliance with Kenya's data management legislation. In 2018, Medtronic LABS entered into a partnership with the Kenya Ministry of Health and other stakeholders to improve access to quality services and data availability for non-communicable diseases (diabetes and hypertension), anchored on the SPICE digital health platform. Data migration from SPICE to the NHDC necessitated the establishment of multi-stakeholder coordination structures, alignment on system configuration requirements, provisioning of on-premises servers, data replication and monitoring. The data replication process showed consistency in format and content with no evidence of data loss. The monitoring of the server uptime and availability, however, exposed overall downtime of 15% of the total time tracked between April and December 2022 caused by Internet Protocol address configuration issues, power outages, firewall rule changes, and unscheduled system maintenance. Monthly tracked downtime however reduced from a high of 28% in April 2022 to 5% in December 2022. Our early experience shows that data migration from proprietary host environments to public "one-stop-shop" national data warehouses are feasible provided investments are made in the requisite infrastructure, software and human resource capacity to ensure long-term sustainability, maintenance, and scale to match cloud-based data hosting. Further, digital health solutions developed in collaboration with non-state actors can be integrated into national data systems, saving Governments the cost and efforts of building similar tools while leveraging private sector capacity.

What are the Priorities of Bureaucrats? Evidence from Conjoint Experiments with Procurement Officials

A well-functioning bureaucracy is a precondition for efficient public goods provision. However, bureaucratic decision-making is still largely seen as a black box. We provide novel insights into the preferences of bureaucrats regarding their work outcomes. We focus on a major public sector activity and survey more than 900 real-life procurement officials in Finland and Germany. The questionnaire includes hypothetical choice experiments to study the relative importance of multiple features in tender outcomes. First, bureaucrats state to have substantial discretion at work but no important incentives. Second, our experimental results show that procurers are particularly worried about avoiding negative risks concerning prices and supplier reputation. Third, an avoidance of bidders with prior bad performance appears to be an extremely important factor. Fourth, procurers value a certain degree of competition, while litigation concerns and regional favoritism play only a small role. The striking lack of heterogeneous effects points towards the role of intrinsic motivation among public buyers in countries with high public sector capacity.

Bridging the cancer care gap and inequities in radiation treatment in India: A narrative review

Cancer is the fifth leading cause of death in India, yet India's cancer care landscape remains fragmented. In this paper, we review the current state of access to radiation therapy and the inequities involved, as well as identify potential solutions to improve access to radiation therapy in cancer. We undertook this narrative literature review, which encompassed database searches (PubMed, Embase, Scopus) and scrutiny of the grey literature (Google Scholar, OpenGrey), using the search terms: “cancer care access disparities,” “radiotherapy accessibility challenges,” “out-of-pocket expenditure in cancer treatment,” “value-based cancer care models,” “cost-effective radiotherapy strategies,”and“resource-limited cancer care solutions.” Our search strategy focused on articles addressing barriers to radiation treatment, inequities in radiation treatment equipment, and optimal radiation techniques in resource-limited settings in India, thereby identifying key challenges and potential interventions. Of the 1933 articles initially retrieved, we included 46 for the preparation of this review. Among the various modalities utilized for the management of cancer, radiation treatment is the most resource-intensive, requiring expensive and dedicated infrastructure. Scarce infrastructure, perpetuating inequities across geographical regions and socioeconomic strata, is responsible for inequities in access to radiation treatment in India. With the advent of newer radiation techniques requiring specialized equipment for the delivery of advanced radiation treatment, these inequities widen in low- and middle-income countries such as India. The challenge lies in providing affordable and equitable radiation treatment without compromising on quality within India's diverse and populous expanse. Bridging these gaps mandates the improvement of the existing infrastructure, fostering local production of quality medical equipment like linear accelerators, establishing and adhering to country-specific standardized treatment guidelines based on volumes, optimally utilizing available equipment like indigenous telecobalt machines and cost-effectiveness evidence, establishment of rural cancer care centers, optimization of private sector capacities and economic support through national insurance schemes.

Enhancing Trajectory-Based Operations for UAVs through Hexagonal Grid Indexing: A Step towards 4D Integration of UTM and ATM

Aviation is expected to face a surge in the number of manned aircraft and drones in the coming years, making it necessary to integrate Unmanned Aircraft System Traffic Management (UTM) into Air Traffic Management (ATM) to ensure safe and efficient operations. This research proposes a novel hexagonal grid-based 4D trajectory representation framework for unmanned aerial vehicle (UAV) traffic management that overcomes the limitations of existing square/cubic trajectory representation methods. The proposed model employs a hierarchical indexing structure using hexagonal cells, enabling efficient ground based strategic conflict detection and conflict free 4D trajectory planning. Additionally, the use of Hexagonal Discrete Global Grid Systems provides a more accurate representation of UAV trajectories, improved sampling efficiency and higher angular resolution. The proposed approach can be used for predeparture conflict free 4D trajectory planning, reducing computational complexity and memory requirements while improving the accuracy of strategic trajectory conflict detection. The proposed framework can also be extended for air traffic flow management trajectory planning, Air Traffic Control (ATC) workload measurement, sector capacity estimation, dynamics airspace sectorization using hexagonal sectors and traffic density calculation, contributing to the development of an efficient UTM system, and facilitating the integration of UAVs into the national airspace system with ATM

Climate Change Adaptation Activities and Needs in US State and Territorial Health Agencies.

To characterize US State and Territorial Health Agencies' (S/THA) climate change adaptation activities and priorities to facilitate appropriate investments, skills development, and support that will strengthen health sector capacity in response to a changing climate. In 2021, we conducted an online survey of S/THA staff requesting information on current activities related to climate change and health, the state of climate and health programming, and anticipated needs and priorities for assistance. We analyzed survey results using descriptive statistics. US State and Territorial Health Agencies. We received responses from 41 of 59 S/THAs (69.5%). Implementation of S/THA climate and health programs (CHPs); engagement in climate and health activities; maintenance of hazard early warning systems and action plans; employment of climate and health communications strategies; capability to assess risks and adaptation needs related to various climate-sensitive conditions; priorities and plans for climate change adaptation in relation to climate-sensitive health risks; climate change adaptation-related partnerships and collaborations; requests of the Association of State and Territorial Health Officials (ASTHO) for advancing climate change adaptation activities; and the impacts of the COVID-19 pandemic on climate change work. Nineteen S/THAs reported having CHPs, the majority of which are federally funded. On average, S/THAs without CHPs reported engagement in fewer climate and health activities and more early warning activities. The S/THAs reported the highest levels of concerns regarding non-vector-borne infectious disease (66%), vector-borne infectious diseases (61%), and extreme heat (61%) hazards. As S/THAs with CHPs report substantially greater climate and health capacity than those without, additional federal and state investments (eg, Building Resilience Against Climate Effects [BRACE]) are urgently needed to catalyze climate and health capacity.

(مورفولوجيّة) السكن في محافظة القدس في ضوء التحديات (الديموغرافيّة) والسياسيّة

This study aims at focusing on the change that occurred in the morphological and demographic characteristics of the population of the Jerusalem governorate during the period from 1997-2022, and its impact on the housing situation, and to identify the indicators of the housing problem and its impact on the residents of the Jerusalem governorate, especially the Holy City.
 Among the most important results: that since the occupation's control over Jerusalem in 1967, it has been practicing a series of continuous policies and procedures aimed at creating a Jewish majority in the city, and fragmenting Palestinian lands, starting with settlement projects, the apartheid wall, and complete control over the city. Classified Area C and other actions.
 The Palestinian urban expansion collides with the accelerating colonial colonialism, which is practiced by the occupation in order to fragment the Palestinian lands. This affected the morphology of the urban environment and exacerbated the housing crisis. It seems that political détente is a prerequisite for improving the economic situation and housing development.
 Despite the ongoing Judaization policy in Jerusalem, the Palestinians in Old Jerusalem constitute an absolute majority of 91.4%, compared to 8.6% for the Israeli occupiers, and the percentage of the Palestinian population in East Jerusalem exceeded 60.42%, compared to 39.58% for the Israeli settlers.
 Among the most important recommendations: that the difficult reality in the governorate of Jerusalem and the city of Jerusalem and its suburbs requires smart and rational initiatives and strategies by Palestinians, Arabs and Muslims to face challenges through political pressure on the occupation to stop its occupational procedures, and reinforce the steadfastness of the Palestinians by maintaining their demographic superiority, and solving various problems facing the Palestinians; By developing the institutional and professional capacity of the various sectors of sustainable development.

The role of market linkage in growth of micro and small scale enterprises: the case of Ambo town, Ethiopia

The research aims to investigate the roles of market linkage for the growth of MSE in Ambo town. The data were collected through questionnaires and interviews. A stratified sampling technique is used to select among the seven business sectors. Data were analyzed using descriptive and inferential statistics. The study elicited five major factors that affects the growth of MSE which include financial capacity, government support, entrepreneurial competency, marketing information, and types of business sectors. The findings from correlation and regression further indicate that there exists a positive and significant relationship between MSEs growth and, financial capacity, government support, entrepreneurial competency, marketing information, and types of business sectors. The concerned bodies should facilitate market linkage enhancement between MSE and the market. MSEs on their part are expected to improve financial capacity and competence. Furthermore, adequate market information has to be collected continuously to improve the linkage. By and general, growth of MSE is attributed to internal as well as external market linkage factors. In addition entrepreneurial competency of the person leading the enterprises is vital in creating good market linkage which in turn brings MSE growth.

Conceptualising a Framework for Construction Sector Capacity

Understanding construction sector capacity allows stakeholders to assess the ability to deliver construction projects critically. However, the capacity concept in the construction sector is dynamic, and interrelationships of capacity at different levels have not been explored thoroughly. Accordingly, this paper reviewed studies on capacity at different levels: sector, organisational, and individual to (1) identify attributes of capacity at each level; (2) map relationships of the capacities in the construction sector; and (3) develop a conceptual framework of project capacity in the construction sector and propose future research directions. This study used an integrative literature review approach to synthesise literature from various domains to describe different levels of the construction sector’s capacity. The findings of the literature review conceptualised a construction sector capacity framework at four levels: sector, organisational, individual, and project. The detailed descriptions of the relevant attributes at each level advance our understanding of capacity within the construction sector and are fundamental to developing capacity assessment tools for the construction sector. The relationships formed in the proposed framework help explain how the capacity at each level affects the system. Findings also serve to identify areas for future research, including investigating interrelationships of attributes in the capacity framework.

Construction industry classification systems: Defining the construction sector in New Zealand

CanConstrucNZ is a partnership programme between New Zealand universities, government agencies, and professional bodies to develop a smart system that enables mapping future pipeline projects with the industry capacity and capability to advise the stakeholders whether the sector will be capable of delivering the proposed construction projects. Defining the scope of the construction sector itself is the first step of the programme that helps measure the construction sector capacity. This paper compares different definitions and approaches of the construction sector boundaries and discusses similarities and differences in the selected classification systems, usually used to define, collect, and generate data for measuring the construction sector. The findings highlight the need for a more comprehensive classification to help generate the correct level of data for measuring the construction sector’s true scope and size, resulting in better policy initiatives, and informing changes in the industry. The findings of this study recommend future research to develop a customised classification system to represent the value of the New Zealand construction sector in a holistic manner.

Health workers labor market before and during the Covid-19 pandemic: Health sector capacity of Serbia

Abstract Background During the COVID-19 pandemic surges, healthcare stakeholders were concerned with the sufficiency of available health workforce capacity. In this study we examined the changes in the supply and demand of physicians, nurses and care workers in Serbia over the period 2011-2021. Methods The National Employment Service (NES) data on total number of unemployed physicians, nurses and care workers, and vacancy data in health sector were described using the annualized % change for the period 2011-2021. The long-term duration of unemployed female physicians and nurses was further analyzed. Results In 2021, NES has registered total of 13,332 unemployed physicians, nurses and care workers, out of which the majority were females (79%), and nurses and care workers (88%). 2021 data on vacancies showed that only 16% of unemployed workers were needed. The peak of health workers unemployment was in 2016, highlighting the period of unemployment rise (2011-2016) at an annualized rate of 3.7% for medical doctors’ specialists, 6.4% for medical doctors without specialization, and 3.2% for nurses and care workers, and the period of unemployment decline (2017-2021) at an annualized rate of -7.9% for medical doctors’ specialists, -10.9% for medical doctors without specialization, and -5.9% for nurses and care workers. The annualized rate of decline was the lowest for female nurses and care workers. On average 53% of all long term unemployed medical doctors, nurses and care workers were women. In comparison to 2019, during the COVID-19 epidemic in 2020 and 2021 the number of vacancies for specialists and nurses and care workers has increased by one-third. Conclusions The study indicated a continuous mismatch between the supply and demand of physicians and nurses in Serbia (a surplus of some categories of nurse-specialists versus a shortage of some doctor specialists). The Serbian stakeholders need to urgently intervene regarding the long-term unemployment of female health workers. Key messages • NES data imply a low capacity of the Serbian health sector to absorb the huge numbers of (long-term) unemployed health workers. • It is necessary to thoroughly examine and counteract the causes of the dramatic number of unemployed health workers on the NES records in Serbia.

Image-Based Multi-Agent Reinforcement Learning for Demand–Capacity Balancing

Air traffic flow management (ATFM) is of crucial importance to the European Air Traffic Control System due to two factors: first, the impact of ATFM, including safety implications on ATC operations; second, the possible consequences of ATFM measures on both airports and airlines operations. Thus, the central flow management unit continually seeks to improve traffic flow management to reduce delays and congestion. In this work, we investigated the use of reinforcement learning (RL) methods to compute policies to solve demand–capacity imbalances (a.k.a. congestion) during the pre-tactical phase. To address cases where the expected demands exceed the airspace sector capacity, we considered agents representing flights who have to decide on ground delays jointly. To overcome scalability issues, we propose using raw pixel images as input, which can represent an arbitrary number of agents without changing the system’s architecture. This article compares deep Q-learning and deep deterministic policy gradient algorithms with different configurations. Experimental results, using real-world data for training and validation, confirm the effectiveness of our approach to resolving demand–capacity balancing problems, showing the robustness of the RL approach presented in this article.

Peak Health Care Burden During the First Three COVID-19 Waves in the Republic of Croatia

Introduction: One of the main concerns during the COVID-19 pandemic was the overload of health care sector capacities. The objective of this paper was to show peak numbers of selected indicators during the three COVID-19 waves in Croatia and ensure information that will enable revision of preparedness plan and potential hospitals` (re)organization. Methods: Retrospective analysis of COVID-19 testing, infections, hospitalizations, ICU admissions, mechanical ventilation support and deceased data collected via capacity surveillance in the Republic of Croatia during the first three waves. Results: Peak hospital bed occupancy rates observed in the 2nd and 3rd waves were 70.19% and 54.60%, compared to maximum capacity during the COVID-19 wave, and 168.90% and 131.38%, compared to maximum capacity between waves, while ICU beds occupancy rates were 75.51% and 70.73%, and 170.51% and 160.37%, respectively. Peak daily numbers were as follows (first/ second/third wave); positive persons: 53/4827/3198; tested persons: 1984/13325/11622; total hospitalized persons: 372/2976/2315; total mechanical ventilation needed: 31/306/278; total ICU hospitalized: unknown/370/348; deceased: 8/92/52. Conclusion: During pandemic waves, the requirements for hospital and ICU beds significantly exceeded standard available health sector capacities. The system has acutely adjusted by increasing the number of beds available for COVID-19 patients. However, given the peaks observed so far, a permanent additional increase or reorganization of hospital capacity is needed to ensure that during the upcoming waves non-COVID-19 and COVID-19 patients won’t be endangered or part of the staff overloaded.

A High-Precision Method for Evaluating Sector Capacity in Bad Weather Based on an Improved WITI Model

The rapid development of the civil aviation industry has increased the pressure on airspace resources in China. The traditional sector capacity assessment method does not take into account the impact of bad weather, resulting in flight plans often deviating markedly from the predicted plans, causing flight delays and affecting the punctuality rate of flights. To solve this issue, we propose a novel evaluation method based on an improved Weather-Impacted Traffic Index (WITI) model to calculate sector capacity. The WITI model is optimized in order to calculate the weather-influence coefficients under different types of bad weather. These coefficients were also considered in a controller workload model. Finally, the model was trained using a deep-neural-network algorithm, which is combined with a linear regression algorithm to calculate sector capacity under different bad weather conditions. The novel approach leads to the output results being within a specified error range, which greatly improves their accuracy. This method was applied to the actual case data of Yinchuan Hedong International Airport to consider different types of bad weather and quantify their severity, which more specifically assesses the sector capacity under the condition of bad weather.