Number Of Hospital Beds Research Articles

Prevalence, progress, and subgroup disparities in pharmacological antidepressant treatment of those who screen positive for depressive symptoms: A repetitive cross-sectional study in 19 European countries.

SummaryBackgroundThe European Mental Health Action Plan (EMHAP) 2013–2020 promoted community-based mental health services. One potential success indicator is the provision of antidepressant medication to those needing it.MethodsPublic data from two surveys (Health Survey for England, UK; Survey of Health, Ageing and Retirement in Europe) covered 19 European countries across EMHAP phases one (2011–2015) and two (2015–2018). People screening positive for depressive symptoms by self-report were included. The primary outcome was antidepressant use: using country-specific weighted regression models, we estimated temporal trends and subgroup disparities in antidepressant receipt, with secondary analysis by country-level measures including healthcare expenditure.FindingsAcross 37,250 participants, after controlling for age, sex, wealth, and physical disability, antidepressant use (amongst those screening positive) increased significantly in 14/19 countries, with the smallest increase being in Slovenia (adjusted OR[AOR] for trend=1.68[1.20–2.36]) and the highest increase being in Germany (AOR for trend=10.07[7.54–13.46]) and Austria (AOR for trend=10.07[7.32–13.74]). The overall proportion using antidepressants was positively associated with national health expenditure (coefficient=5.43[1.62–9.25]), but not with gross national income per capita or the number of psychiatrists, general practitioners, or psychiatric hospital beds. In 15/19 countries, antidepressants were used less by ≥65-year-olds than 50–64-year-olds, with the smallest differential reported in Luxembourg (AOR=0.70[0.49, 0.98]) and the highest in Germany (AOR=0.28[0.21, 0.37]); this disparity widened in 12/15 countries. Men used antidepressants less than women in 8/19 countries, across phases. In 13/19 countries, people with physical disability were more likely to receive antidepressants, with the smallest gap in Italy (AOR=1.42[1.12–1.80]) and the largest in Israel (AOR=2.34[1.46–3.74]); this disparity narrowed in 5/13 countries. Disparity by wealth was found in 8/19 countries, but its temporal trend varied.InterpretationUsage of antidepressants by those with depressive symptoms has increased, with wide variation between countries and subgroups. Disparities across age, sex, and disability should prompt further research.FundingMedical Research Council (grants MC_PC_17213 and MR/W014386/1), UK National Institute for Health Research (NIHR) Applied Research Collaboration (ARC) East of England, NIHR Cambridge Biomedical Research Centre (BRC-1215-20014).

“We can’t breathe!” – A dilemma faced by Total Technologies (Pvt.) Ltd. amid oxygen cylinder crisis

Learning outcomes This case study aims to be taught at an MBA level. Students who are majoring in the supply chain would benefit the most from this case study. This case study has elements of logistics management, supply chain management, supply chain strategies, warehouse and logistics and responsible supply chain. The learning outcome of this case study could be seen if the students identify the gaps in the real market setting and come up with strategies that would connect and/or fill the areas missing. Teaching objective 1: students should be able to identify unstable demand scenarios and learn how demand collaboration could be implemented in that setting. Teaching objective 2: students should identify how a transparent and interconnected supply chain, both upstream and downstream, can be created. Teaching objective 3: students should be able to understand the role of a responsible supply chain and to define the role and responsibility of each party. Teaching objective 4: students should be able to learn the dynamics of safety stocks, reorder points and incorporate that in warehouse management decisions. Case overview/synopsis Based in Lahore, Pakistan, Total Technologies (Pvt.) Ltd is a company that supplies medical equipment and provides solutions in the health-care industry. This case explores the supply chain issues faced by Tallat Mehmood, who is the Managing Director of the company, during the third wave of the COVID-19 pandemic in April 2021. Oxygen cylinders have become the need of the hour as more and more patients need oxygen. The supply of medical gases across Pakistan has become a logistical issue, causing hospital reserves to be drained without timely replenishment. Increasing the number of beds in hospitals, with limited oxygen outlets, has increased the demand for oxygen cylinders. Operating under unstable demand and not being able to meet it has caused Tallat to realize that the company is out of its comfort zone and is not responding well to the environment. The company needs to redesign the supply chain as well as collaborate with the supplier and buyer to provide better levels of service. Complexity academic level Masters level supply chain courses. Supplementary materials Teaching Notes are available for educators only. Subject code CSS 9: Operations and logistics.

Investigation of poor prognostic markers in covid-19 patients hospitalized from emergency department

On March 11. 2020, the World Health Organization declared the coronavirus disease-2019 (COVID-19) outbreak a pandemic. The surge in the number of infected patients has strained healthcare systems globally. The insufficient number of hospital and intensive care unit (ICU) beds has caused a serious problem in patient care and follow-up worldwide. We determined patients who were admitted to the emergency department and hospitalized with a preliminary diagnosis of COVID-19 between March 11, 2020 and November 15, 2020. We recorded all subjects' admission vital signs, anamnesis, physical examination notes, laboratory tests and notes describing the hospital stay from the hospital information system. Patients discharged without requiring ICU admission were included in the good clinical prognosis (GCP) group. Patients who were admitted to the ICU or died in hospital were included in the poor clinical prognosis (PCP) group. When hematological and biochemical parameters were compared, white cell, neutrophil, platelet counts, glucose, urea, creatinine and bilirubin levels were significantly higher and lymphocyte count, hemoglobin, hematocrit, sodium and chlorine levels were lower in the PCP group. Moreover, sedimentation, C Reactive Protein (CRP), ferritin, High Sensitive Troponin I, D-dimer and lactate levels were significantly higher among patients with a poor prognosis. We assessed and identified the more important potential early indicators of prognosis mentioned in the literature that are applicable in the emergency setting. In light of this information, we aimed to establish a basis for the development of future scoring systems.

Lessons Learnt From a Greenfield Hangar-Based 1,000-Bedded Temporary Hospital in India.

During the COVID-19 pandemic, the total number of hospital beds in the National Capital Region (NCR) of Delhi was 54,321 (roughly 300 beds per one lakh population), which was inadequate for the patients. Therefore, the Indian government initiated the construction of a 1,000-bedded greenfield hangar-based hospital to bridge the healthcare gap. As a result, Intensive Care Unit (ICU) beds in the facility augmented the COVID-19 care ICU beds in the city by 11%. The authors were involved in the planning, developing, and initiating the functioning of 1,000-bedded Dedicated COVID-19 Hospital (DCH). The hospital was conceptualized, built, and operationalized in 12 days only. Lessons learned from this experience would be of benefit should similar situations arise in future. Coordinating structural designing early with the entire project team-from facility administrators and medical practitioners to architects, consultants, and contractors-can result in a structure that better matches the facility's long-term needs and often saves construction time and costs. This article enumerates various challenges faced and the way they were addressed. This hangar-based hospital can be rapidly constructed and deployed on a massive scale. While structural integrity is essential, the planning team was particularly aware of the patient-centric modality of healthcare. Many modifications were carried out in the structure based on patient inputs. Informal discussions with discharged patients and relatives revealed that the human-centric approach was the mainstay of the therapy.

The Geographical Distribution and Influencing Factors of COVID-19 in China.

The study of the spatial differentiation of COVID-19 in cities and its driving mechanism is helpful to reveal the spatial distribution pattern, transmission mechanism and diffusion model, and evolution mechanism of the epidemic and can lay the foundation for constructing the spatial dynamics model of the epidemic and provide theoretical basis for the policy design, spatial planning and implementation of epidemic prevention and control and social governance. Geodetector (Origin version, Beijing, China) is a great tool for analysis of spatial differentiation and its influencing factors, and it provides decision support for differentiated policy design and its implementation in executing the city-specific policies. Using factor detection and interaction analysis of Geodetector, 15 indicators of economic, social, ecological, and environmental dimensions were integrated, and 143 cities were selected for the empirical research in China. The research shows that, first of all, risks of both infection and death show positive spatial autocorrelation, but the geographical distribution of local spatial autocorrelation differs significantly between the two. Secondly, the inequalities in urban economic, social, and residential environments interact with COVID-19 spatial heterogeneity, with stronger explanatory power especially when multidimensional inequalities are superimposed. Thirdly, the spatial distribution and spread of COVID-19 are highly spatially heterogeneous and correlated due to the complex influence of multiple factors, with factors such as Area of Urban Construction Land, GDP, Industrial Smoke and Dust Emission, and Expenditure having the strongest influence, the factors such as Area of Green, Number of Hospital Beds and Parks, and Industrial NOx Emissions having unignorable influence, while the factors such as Number of Free Parks and Industrial Enterprises, Per-GDP, and Population Density play an indirect role mainly by means of interaction. Fourthly, the factor interaction effect from the infected person’s perspective mainly shows a nonlinear enhancement effect, that is, the joint influence of the two factors is greater than the sum of their direct influences; but from the perspective of the dead, it mainly shows a two-factor enhancement effect, that is, the joint influence of the two factors is greater than the maximum of their direct influences but less than their sum. Fifthly, some suggestions are put forward from the perspectives of building a healthy, resilient, safe, and smart city, providing valuable reference and decision basis for city governments to carry out differentiated policy design.

Hospital waste generation during the first wave of COVID-19 pandemic: a case study in Delhi.

In this study, the hospital waste generation rates and compositions in Delhi were examined temporally and spatially during the first COVID-19 wave of April 2020. A total of 11 representative hospitals located in five districts were considered. The pre-COVID hospital waste generation rates were relatively consistent among the districts, ranging from 15 to 23 tonne/month. It is found that the number of hospital beds per capita may not be a significant factor in the hospital waste quantity. Strong seasonal variations were not observed. All districts experienced a drastic decrease in generation rates during the 1-month lockdown. The average rates during the COVID period ranged from 12 to 24 tonne/month. Bio-contaminated and disposable medical product wastes were the most common waste in Delhi’s hospitals, representing 70–80% by weight. The changes in waste composition were however not spatially consistent. The lockdown appeared to have had a higher impact on hospital waste generation rate than on waste composition. The findings are important as the design and operation of a waste management system are sensitive to both waste quantity and quality. Waste records at source helped to minimize waste data uncertainties and allowed a closer examination of generation trends.

How to Reduce Inequity of Access to Cardiac Rehabilitation After Surgical Aortic Valve Replacement. Recommendations for the Post–COVID-19 Era From a Real-World, Population-Based Study

Cardiac rehabilitation (CR) is a class I recommendation after valvular surgery. Few data exist on the level of access to CR after surgical aortic valve replacement (SAVR), and the factors affecting the probability of timely access to CR after SAVR have never been empirically investigated. This study aims at estimating the proportion of SAVR patients who initiated timely CR and understanding to what extent timely access to CR for SAVR patients is influenced by specific characteristics of patients and hospitals. We conducted a real-world, retrospective, population-based study by identifying from the Italian National Hospital Discharge Records all the discharged alive SAVR patients who accessed timely CR from 2009-2016. Two different cutoffs for timely access were considered, i.e. one and 21 days after discharge. A unique dataset was constructed by merging several data sources. Multiple logistic regressions were performed to identify the factors influencing the probability to access to timely CR. 107,545 patients underwent SAVR in Italy from 2009-2016 and were discharged alive. Overall, 71,593 SAVR patients (66.6%) accessed timely CR, with an increasing trend over time. Additional 6,149 patients (5.7%) started CR from 2-21 days after discharge, slightly decreasing over time. The probability of timely CR (one-day cutoff) was significantly higher in older (OR=1.025, p<0.001) female patients (OR = 1.003, p<0.05) and patients with cardiovascular and cerebrovascular comorbidities. Presence of rehabilitation wards and number of rehabilitation beds in the index hospital significantly increased the probability of timely access to CR (OR = 1.105, p<0.001 and OR = 1.006, p<0.001 respectively). Patients hospitalized in private teaching hospitals had the highest predicted probability of timely CR after SAVR. A substantial variation in access to CR was found across Italian regions. Similar results were obtained with the alternative 21-days cutoff. Approximately one-third of SAVR patients did not benefit from CR in Italy, mainly due to shortness of rehabilitation facilities, with relevant disparities across the country. The cessation of CR services during the COVID-19 pandemic provides the opportunity to re-think and innovate CR, shifting from center-based to home-based models. Digital health technologies can supplement traditional health services and grant safe, effective, and equitable access to care, especially for countries with insufficient rehabilitation bed capacity. As CR is associated with better outcomes, we recommend decision-makers to use our results to plan adequate healthcare services, also investing in digital health, to ensure patients' access to cost-effective care.

MỘT SỐ ỨNG DỤNG CỦA ĐA THỨC NỘI SUY LAGRANGE TRONG THỰC TẾ

In this paper, we use Lagrange interpolation method to solve some problems in Agriculture and Health in Vietnam. The data used in this paper are extracted from the data of the General Statistics Office of Vietnam. The Lagrange interpolation method is a good model for forecasting agricultural production as well as the correlation between the number of doctors and the number of hospital beds in medical facilities in Vietnam.

The Impact of Quarantine and Medical Resources on the Control of COVID-19 in Wuhan based on a Household Model

In order to understand how Wuhan curbed the COVID-19 outbreak in 2020, we build a network transmission model of 123 dimensions incorporating the impact of quarantine and medical resources as well as household transmission. Using our new model, the final infection size of Wuhan is predicted to be 50,662 (95%CI: 46,234, 55,493), and the epidemic would last until April 25 (95%CI: April 23, April 29), which are consistent with the actual situation. It is shown that quarantining close contacts greatly reduces the final size and shorten the epidemic duration. The opening of Fangcang shelter hospitals reduces the final size by about 17,000. Had the number of hospital beds been sufficient when the lockdown started, the number of deaths would have been reduced by at least 54.26%. We also investigate the distribution of infectious individuals in unquarantined households of different sizes. The high-risk households are those with size from two to four before the peak time, while the households with only one member have the highest risk after the peak time. Our findings provide a reference for the prevention, mitigation and control of COVID-19 in other cities of the world.

COVID-19 Total Mortality and Relative Waves: the Reasons for the Differences among European Countries

Background: Several mortality waves (between 1 to 5) have been observed over time in the 47 European countries. Material and Methods: The data on mortality rate shown on the WHO dashboard were used, and twelve LEEDELS variables (life expectancy, ecological, economic, demographic and lifestyle) during the period between March 2020 and September 2021. WMVs (weighted median values) were used to calculate the mortality rates and their respective waves. The partition model was used to identify which LEEDELS variables correlated with the mortality rates (predictors). Results: In the partition model four LEEDELS predictors were considered relevant: number of cars per 103 inhabitants, GDP, percentage of population over 65 years old, and life expectancy. The remaining eight LEEDELS variables (total population aged over 65 years old, population density, urban population, education expenditure, number of hospital beds, particulate matter, number of mobile phones, and number of internet connections) were irrelevant. The analysis revealed four pathways (from P1 to P4), which limit or increase the WMVs respectively. The P3 pathway was shown to be at the highest risk of death while P1 was more protective. Conclusions: High GDP, a high percentage of the population over 65 years of age and life expectancy are crucial for WMV containment, represented by P1. The pathway P3, characterized by high GDP, low percentage of population over 65 is at higher risk. Population density, particulate matter, number of hospital beds and expenditure on education, cell phone x 103 inhabitants were not found to be causal variables.

Analysis of the Healthcare and Overall Economic Competitiveness of Santiago, Isabela, Philippines

City of Santiago, Isabela, is otherwise known as the “Queen City of the North” and the only independent component city in region 2 that substantially contributes to the overall production and competitiveness of the region. This study aimed to determine the influence of the state of healthcare to the economic competitiveness, identify the determinants that contribute to the demand for healthcare, discover the factors that affect the choices of consumers to healthcare services, and measure the effect of healthcare inputs on the level of mortality rate in the City of Santiago, Isabela, Philippines. Primary and secondary data were utilized, and even employed descriptive and inferential statistics for the analysis. This study discovered that the competitive index has a significant positive impact on the total annual patients and healthcare facilities while the annual healthcare expenditure of the City of Santiago is insignificant. The demand for healthcare services arises because of demographic, medical-related, and socio-economic factors. Moreover, the prime factor influencing residents' acquiring healthcare services is the quality itself. Lastly, the mortality rate has a significant inverse impact on the number of general practitioners and medical specialists in the city, while the number of hospital beds showed a significant positive effect.

How the COVID-19 pandemic has affected the training of Endocrinology and Nutrition Residents. Results of a survey by the Spanish Society of Endocrinology and Nutrition

IntroductionCOVID-19 disease has become a priority for our healthcare system. The resident physicians training in endocrinology and nutrition (E&N residents) have been integrated into the COVID-19 teams. This study has been designed with the aim of analysing the educational, occupational and health impact on E&N residents. Material and methodsCross-sectional observational study via a web survey, aimed at E&N residents who are members of the SEEN, carried out in November 2020. The following data were analysed: demographic variables, number of beds in the training hospital, alteration of rotations, integration in COVID-19 teams, participation in telemedicine, scientific activity and impact on physical and emotional health. Results87 responses were obtained (27% of all E&N residents), 67.8% women, 28.1 ± 1.8 years, 60% 4th year E&N residents. 84% participated in COVID-19 teams and 93% in the telemedicine consultations of their service. Most have had their rotations interrupted. 97.7% have participated in scientific meetings or virtual congresses and a third of them have collaborated in scientific work on COVID-19 in relation to endocrinology and nutrition. Overall, 75.8% think the pandemic has affected their mood a lot or quite a lot, and 73.8% think that the pandemic has negatively impacted their training. ConclusionsThe SARS-CoV-2 pandemic has compromised the training, work activity and health of E&N residents. They have been integrated both in COVID-19 teams and in the restructured activity of their departments. However, they have managed to continue their training in virtual format and have participated in scientific work.

Factors Influencing Physicians Migration—A Case Study from Romania

Brain drain is a phenomenon that, over time, has followed an upward trend. It is an important component represented by physicians’ migration. For the country of destination, the migration of physicians offers several advantages, whereas the country of origin loses skilled and sometimes highly trained individuals. This process will be reflected both in the efficiency of the health system (severe employment shortage) and in the quality of the health system services. After Romania’s accession to the EU, the migration of doctors intensified, significantly increasing the shortage of physicians. The purpose of this article is to identify the push factors that influence the physicians’ decision to migrate from Romania. For this, a panel regression analysis was applied, highlighting that physicians’ migration is influenced by several factors, such as the number of beds in hospitals, the number of emigrants, unemployment rate, and income. At the same time, we analyzed the extent to which public policy measures addressed to the remuneration of medical staff influenced the propensity towards external mobility of the practicing doctors, already employed and/or graduates. The results confirm that public policies can be a tool for redistributing the labor force allocation on the labor market. Moreover, the results of our analysis highlight that specific measures do not solve the system crises facing the health sector. Systemic, multidimensional changes are needed, adapted to the needs of medical services specific to the geographical area and adequate to the health status of the population.

SARS-CoV-2 transmission in opposition-controlled Northwest Syria: modeling pandemic responses during political conflict

IntroductionTen years of conflict has displaced more than half of Northwest Syria's (NWS) population and decimated the health system, water and sanitation, and public health infrastructure vital for infectious disease control. The first NWS COVID-19 case was declared on July 9, 2020, but impact estimations in this region are minimal. With the rollout of vaccination and emergence of the B.1.617.2 (Delta) variant, we aimed to estimate the COVID-19 trajectory in NWS and the potential effects of vaccine coverage and hospital occupancy.MethodsWe conducted a mixed-method study, primarily including modeling projections of COVID-19 transmission scenarios with vaccination strategies using an age-structured, compartmental susceptible-exposed-infectious-recovered (SEIR) model, supported by data from 20 semi-structured interviews with frontline health workers to help contextualize interpretation of modeling results.ResultsModeling suggested that existing low stringency non-pharmaceutical interventions (NPIs) minimally affected COVID-19 transmission. Maintaining existing NPIs after the Delta variant introduction is predicted to result in a second COVID-19 wave, overwhelming hospital capacity and resulting in a fourfold increased death toll. Simulations with up to 60% vaccination coverage by June 2022 predict that a second wave is not preventable with current NPIs. However, 60% vaccination coverage by June 2022 combined with 50% coverage of mask-wearing and handwashing should reduce the number of hospital beds and ventilators needed below current capacity levels. In the worst-case scenario of a more transmissible and lethal variant emerging by January 2022, the third wave is predicted.ConclusionTotal COVID-19 attributable deaths are expected to remain relatively low owing largely to a young population. Given the negative socioeconomic consequences of restrictive NPIs, such as border or school closures for an already deeply challenged population and their relative ineffectiveness in this context, policymakers and international partners should instead focus on increasing COVID-19 vaccination coverage as rapidly as possible and encouraging mask-wearing.

Distribution of hospital beds across Saudi Arabia from 2015 to 2019: a cross-sectional study.

Adequate access to health care systems is considered a basic human right. Therefore, it is important that health care services be delivered to those who need them most in the most efficient manner possible. We evaluated the distribution of hospital beds across Saudi Arabia from 2015 to 2019 to assess inequalities in hospital resource allocation. This cross-sectional study utilized data from the Health Statistical Yearbook published by the Ministry of Health during the period 2015-2019. The number of hospital beds per 100 000 population was calculated for the 20 health regions. Generation of other parameters, such as the Gini index and the Lorenz curve, was performed to assess the distribution of beds. The Pearson coefficient was calculated to assess the correlation between beds and population in each health region. The ratio of hospital beds to population improved from 2015 to 2019 in areas such as Ha'il, Tabouk and Ta'if, which increased by 89.6, 72.5 and 32.5 respectively. The calculated mean Gini index for bed distribution in the public sector was 0.21; in the private sector it was 0.53. There was a strong positive correlation between population and hospital beds in Riyadh, Qaseem, Eastern and Ha'il regions. In Saudi Arabia the observed inequalities in hospital bed distributions lie mainly in the private sector. It is recommended that policymakers be aware of such inequalities and work on possible reforms to achieve the goals of Saudi Vision 2030.

Community-Based Mental Health Services in Azerbaijan: a Course Toward Development: Развитие внебольничной психиатрической службы Азербайджана.

Community mental health care in Azerbaijan was established in 2011 in the line with the country's mental health reform. The main directions of the reform, as described in the National Mental Health Strategy, were deinstitutionalization, improving quality of care, integration of mental health into primary healthcare, and implementation of modern community-based services. Over the last decade, the number of beds in psychiatric hospitals has significantly decreased, and many psychiatrists and psychiatric nurses have been transferred to primary care facilities. At the same time, programs focusing on comprehensive care have been implemented in different regions of the country. Community mental health services currently employ various kinds of mental health professional including psychiatrists, clinical psychologists, social workers, occupational therapists, and nurses to ensure a multidisciplinary approach to care provision. Team-based care may focus on crisis resolution, psychosocial rehabilitation, case management, family support, and early intervention for psychosis. Among the barriers preventing development of community mental health services, one should note, in particular, stigma belittling the priority of mental healthcare, uncertainty in distribution of authority between the Ministry of Health and the State Agency for Mandatory Health Insurance, and a general scarcity of human resources, especially in the rural regions. Nevertheless, the mental health care in Azerbaijan is continuing its transition from an institutional model to community-based services.

HbA1c level may be a risk factor for oxygen therapy requirement in patients with coronavirus disease 2019.

IntroductionMany clinical studies have identified significant predictors or risk factors for the severity or mortality of coronavirus disease 2019 (COVID‐19) cases. However, there are very limited reports on the risk factors for requiring oxygen therapy during hospitalization. In particular, we sought to investigate whether plasma glucose and HbA1c levels could be risk factors for oxygen therapy requirement.Materials and MethodsA single‐center, retrospective study was conducted of 131 COVID‐19 patients hospitalized at Saitama Medical University Hospital between March 2020 and November 2020. To identify the risk factors for oxygen therapy requirement during hospitalization, a stepwise multivariate binary logistic regression analysis was performed using several clinical parameters commonly obtained on admission, including plasma glucose and HbA1c levels.ResultsOf the 131 patients with COVID‐19, 33.6% (44/131) received oxygen therapy during hospitalization. According to the logistic regression analysis, male sex (odds ratio [OR]: 8.76, 95% confidence interval [CI]: 1.65–46.5, P < 0.05), age (OR: 1.07, 95% CI: 1.02–1.12, P < 0.01), HbA1c levels (OR: 1.94, 95% CI: 1.09–3.44, P < 0.05), and serum C‐reactive protein (CRP) levels (OR: 2.22, 95% CI: 1.54–3.20, P < 0.01) emerged as independent variables associated with oxygen therapy requirement during hospitalization.ConclusionsIn addition to male sex, age, and serum CRP levels, HbA1c levels on admission may serve as a risk factor for oxygen therapy requirement during the clinical course of COVID‐19, irrespective of diabetes history and status. This may contribute to the efficient delegation of limited numbers of hospital beds to patients at risk for oxygen therapy requirement.

Municipal Characteristics of In-Home Death Among Care-Dependent Older Japanese Adults

The provision of in-home and community end-of-life care has emerged as an important policy issue for aging populations around the world. Despite most patients expressing the wish to die at home (as opposed to in the hospital), substantial geographic variation persists in the prevalence of in-home death at the end of life. To assess the association of municipal characteristics with variation in the place of death among care-dependent older people in Japan. In this cross-sectional study using multilevel logistic regression, analyses were performed using national claims data under Japan's long-term care insurance system. The study population included long-term care insurance beneficiaries 65 years and older who died in 2015, excluding those who died from external causes, such as unintentional injuries. Data analyses were conducted from January 1 to April 31, 2021. Predisposing, enabling, and need factors at the individual and municipal levels according to a behavioral model. The outcome was whether individuals died at home or not. This cross-sectional study analyzed 544 836 decedents (median [IQR] age, 87 [81-91] years; 300 142 [55.1%] female). The proportion of in-home deaths was 10.3%. In the multilevel null model, 7.2% of the variance in the place of death was associated with municipal-level characteristics. Municipal characteristics were associated with more of the variance than were prefectural characteristics (2.7%). The largest proportional change (7.3%) in variance at the municipality level was observed when enabling factors (ie, medical and long-term care resources) were added to the model. Municipalities with a high proportion of in-home death were more likely to have a higher supply of clinics, physicians, and care workers providing in-home services per population, as well as a lower number of hospital beds and long-term care facility workers per population. In this cross-sectional study, municipal characteristics explained a substantial proportion of the geographic variance in in-home death in Japan. These results suggest that municipal policy makers need to ensure an adequate supply of clinics, physicians, and care workers providing in-home services to meet the preferences of care-dependent older people who wish to spend their final days at home.

Estimating the Effects of Public Health Measures by SEIR(MH) Model of COVID-19 Epidemic in Local Geographic Areas.

The COVID-19 pandemic of 2020–21 has been a major challenge to public health systems worldwide. Mathematical models of epidemic are useful tools for assessment of the situation and for providing decision-making support for relevant authorities. We developed and implemented SEIR(MH) model that extends the conventional SEIR model with parameters that define public lockdown (the level and start of lockdown) and the medical system capacity to contain patients. Comparative modeling of four regions in Europe that have similar population sizes and age structures, but different public health systems, was performed: Baden-Württemberg, Lombardy, Belgium, and Switzerland. Modeling suggests that the most effective measure for controlling epidemic is early lockdown (exponential effect), followed by the number of available hospital beds (linear effect if the capacity is insufficient, with diminishing returns when the capacity is sufficient). Dynamic management of lockdown levels is likely to produce better outcomes than strict lockdown.

Modeling the effect of time delay in the increment of number of hospital beds to control an infectious disease.

One of the key factors to control the spread of any infectious disease is the health care facilities, especially the number of hospital beds. To assess the impact of number of hospital beds and control of an emerged infectious disease, we have formulated a mathematical model by considering population (susceptible, infected, hospitalized) and newly created hospital beds as dynamic variables. In formulating the model, we have assumed that the number of hospital beds increases proportionally to the number of infected individuals. It is shown that on a slight change in parameter values, the model enters to different kinds of bifurcations, e.g., saddle-node, transcritical (backward and forward), and Hopf bifurcation. Also, the explicit conditions for these bifurcations are obtained. We have also shown the occurrence of Bogdanov-Takens (BT) bifurcation using the Normal form. To set up a new hospital bed takes time, and so we have also analyzed our proposed model by incorporating time delay in the increment of newly created hospital beds. It is observed that the incorporation of time delay destabilizes the system, and multiple stability switches arise through Hopf-bifurcation. To validate the results of the analytical analysis, we have carried out some numerical simulations.