Quantifying optimal resource allocation strategies for controlling epidemics.

Frequent emergence of communicable diseases is a major concern worldwide. Lack of sufficient resources to mitigate the disease burden makes the situation even more challenging for lower-income countries. Hence, strategy development for disease eradication and optimal management of the social and economic burden has garnered a lot of attention in recent years. In this context, we quantify the optimal fraction of resources that can be allocated to two major intervention measures, namely reduction of disease transmission and improvement of healthcare infrastructure. Our results demonstrate that the effectiveness of each of the interventions has a significant impact on the optimal resource allocation in both long-term disease dynamics and outbreak scenarios. The optimal allocation strategy for long-term dynamics exhibits non-monotonic behaviour with respect to the effectiveness of interventions, which differs from the more intuitive strategy recommended in the case of outbreaks. Further, our results indicate that the relationship between investment in interventions and the corresponding increase in patient recovery rate or decrease in disease transmission rate plays a decisive role in determining optimal strategies. Intervention programmes with decreasing returns promote the necessity for resource sharing. Our study provides fundamental insights into determining the best response strategy when controlling epidemics in resource-constrained situations.

Nursing home staff perceptions of well-being during the COVID-19 pandemic: A qualitative study.

AIMS: To explore how nursing home staff perceived their work environment during the COVID-19 pandemic and how this impacted their well-being. DESIGN: A qualitative interview study. METHODS: Interviews were held with twenty-two registered nurses and assistant nurses from five nursing homes in the Netherlands between April 2021 and July 2021. The interviews were analysed using qualitative content analysis. The Standards for Reporting Qualitative Research (SRQR) were followed. RESULTS: Five themes emerged from the interviews and indicated that working during the COVID-19 pandemic impacted perceived well-being of nursing home staff. Three themes concerned experiences at work: eroding care, additional roles and workplace support. Specifically, the increased workload with additional tasks, the constant stream of new guidelines and constrictive personal protective equipment caused discomfort and anxiety. Two other themes concerned experiences outside of work: work-life interference and social interactions and status. The nurses reported that when they returned home after work, they were tired and worried about spreading the virus while facing limited social interactions and support. CONCLUSION: The social distancing measures due to the COVID-19 pandemic negatively impacted nursing home staff well-being by increasing demands in the absence of adequate resources. IMPLICATIONS FOR THE PROFESSION AND/OR PATIENT CARE: The well-being needs of nurses should receive continued attention to ensure the sustainability of healthcare during future crises. PATIENT OR PUBLIC CONTRIBUTION: The nursing home managers participated in recommending the topics to be covered during interviews. IMPACT: What problem did the study address? The pressure of stressful working conditions on the well-being of nurses during the pandemic. What were the main findings? Nurses created strategies to cope with declining well-being. However, the available resources did not alleviate the increased demands caused by the pandemic. Where and on whom will the research have an impact? This study is important for healthcare organizations to understand how the COVID-19 pandemic affected nurses so that they may better prepare for future crises.

Macroeconomic production function of Russia and estimation of the marginal rate of technical substitution in the unprecedented socio-economic realities of 2020-2022

In the period 2020-2022 the Russian economy has been facing the new, unprecedented challenges of coronavirus and sanctions. In order to analyze the current state of affairs, we are offering an econometric study of Russia's macroeconomic production function for 1990-2022 and an estimation of the marginal rate of technical substitution under internal and external restrictions associated with the spread of the Wuhan coronavirus (SARS-CoV-2) and the conduct of Russia's special military operation in Ukraine, accompanied by increased sanctions pressure on the Russian economy. We have obtained several significant results. In the years 1991-1996 the marginal rate of technical substitution was increasing, and in 1997-2020 it was decreasing except for 2008-2009 and 2015. In the context of the Wuhan coronavirus pandemic, the main reasons for the Russian economy's decline in 2020 and growth in 2021 were, first of all, fluctuations in the world crude oil price, and not the Wuhan coronavirus pandemic as such. We did not find any evidence that the decline in the world crude oil price in 2020 was caused by a decrease in demand from China, since Russian oil exports to China increased. Contrary to many negative forecasts, the results of our forecasting of Russia's GDP for 2022 show that under sharply increased sanctions pressure, with the world price of Urals oil at $60 per barrel, the average growth rate will be 0%, while at $70 it will be 4%, and at $80 it will be 7%. Under the reduced demand for Russian gas and the shutdown of the Nord Stream 1 gas pipeline, the forecast volumes of gross natural gas production by Gazprom (excluding Gazprom Neft) in the Tyumen Region for 2022, based on the exponential production function studied by econometric methods, range from 364 to 392 billion cubic meters. Using the example of Great Britain, where in 2021 the average actual export prices for Russian oil and gas were the lowest compared to other Western European countries, we discuss the economic inexpediency of setting marginal prices for Russian energy products by Western consumers.

Macroeconomic production function of Russia and estimation of the marginal rate of technical substitution in the unprecedented socio-economic realities of 2020-2022

In the period 2020-2022 the Russian economy has been facing the new, unprecedented challenges of coronavirus and sanctions. In order to analyze the current state of affairs, we are offering an econometric study of Russia's macroeconomic production function for 1990-2022 and an estimation of the marginal rate of technical substitution under internal and external restrictions associated with the spread of the Wuhan coronavirus (SARS-CoV-2) and the conduct of Russia's special military operation in Ukraine, accompanied by increased sanctions pressure on the Russian economy. We have obtained several significant results. In the years 1991-1996 the marginal rate of technical substitution was increasing, and in 1997-2020 it was decreasing except for 2008-2009 and 2015. In the context of the Wuhan coronavirus pandemic, the main reasons for the Russian economy's decline in 2020 and growth in 2021 were, first of all, fluctuations in the world crude oil price, and not the Wuhan coronavirus pandemic as such. We did not find any evidence that the decline in the world crude oil price in 2020 was caused by a decrease in demand from China, since Russian oil exports to China increased. Contrary to many negative forecasts, the results of our forecasting of Russia's GDP for 2022 show that under sharply increased sanctions pressure, with the world price of Urals oil at $60 per barrel, the average growth rate will be 0%, while at $70 it will be 4%, and at $80 it will be 7%. Under the reduced demand for Russian gas and the shutdown of the Nord Stream 1 gas pipeline, the forecast volumes of gross natural gas production by Gazprom (excluding Gazprom Neft) in the Tyumen Region for 2022, based on the exponential production function studied by econometric methods, range from 364 to 392 billion cubic meters. Using the example of Great Britain, where in 2021 the average actual export prices for Russian oil and gas were the lowest compared to other Western European countries, we discuss the economic inexpediency of setting marginal prices for Russian energy products by Western consumers. © 2022 The authors.

Smallholders Are Not the Same: Under the Hood of Kosovo Agriculture

Economists and policy makers are interested in producers' responses to policies in order to achieve some national or sectoral objectives, e.g., growth, employment, food security. The way producers respond to policy depends on their production function. If producers do not have homogenous production function, policy responses will be heterogeneous. We use the underlying functional relationship to derive homogenous groupings. The paper employs finite regression mixture models to specify and estimate farm groups with regard to pre-specified functional relationship. The proposed approach is illustrated with regard to the aggregate production function of Kosovo agriculture, characterised by high prevalence of small farmers. The results point out to two farm clusters. The first one extracts more output from labour and intermediate consumption. The second one makes a better use of land. Perhaps, surprisingly, both clusters appear quite similar in terms of their stock of production inputs. Cluster 1 however appears to be more specialised. We can conclude that in Kosovo agriculture appearances and size are not primary determinants of productivity.

Forecasting the propagation of pandemic shocks with a dynamic input-output model.

We introduce a dynamic disequilibrium input-output model that was used to forecast the economics of the COVID-19 pandemic. This model was designed to understand the upstream and downstream propagation of the industry-specific demand and supply shocks caused by COVID-19, which were exceptional in their severity, suddenness and heterogeneity across industries. The model, which was inspired in part by previous work on the response to natural disasters, includes the introduction of a new functional form for production functions, which allowed us to create bespoke production functions for each industry based on a survey of industry analysts. We also introduced new elements for modeling inventories, consumption and labor. The resulting model made accurate real-time forecasts for the decline of sectoral and aggregate economic activity in the United Kingdom in the second quarter of 2020. We examine some of the theoretical implications of our model and find that the choice of production functions and inventory levels plays a key role in the propagation of pandemic shocks. Our work demonstrates that an out of equilibrium model calibrated against national accounting data can serve as a useful real time policy evaluation and forecasting tool.

How Innovation Ecosystem Synergy Degree Influences Technology Innovation Performance—Evidence from China’s High-Tech Industry

The technology innovation of high-tech industries has become an important support for the innovation-driven strategy. This study introduces innovation ecosystem synergy as a moderating variable from a systemic and holistic perspective based on the traditional perspective of innovation factor input-output, and helps construct a technology innovation performance driving model based on the Cobb–Douglas knowledge production function, which enriches the discussion perspective and theoretical model research on technology innovation performance. With a sample of 28 provinces in mainland China, this study empirically analyzed the moderating mechanism of innovation performance by innovation synergy in high-tech industries during the two stages of technology development and technology transformation. The findings of the study are as follows: (1) Independent research and development has a positive and significant impact on technology development performance;product innovation has a positive and significant impact on technology transformation performance;(2) Technology introduction can weaken technology development performance due to technology dependence and the inhibitory effect on independent innovation, and inefficient technology renovation can negatively and significantly affect technology transformation performance.;(3) The degree of synergy has a positive and significant impact on the performance of technology development innovation and technology transformation innovation. The degree of synergy has a positive moderating effect on the innovation performance of independent R&D and technology development, as well as product innovation and technology renovation, and a negative moderating effect on the innovation performance of technology introduction and technology development, but no significant moderating effect on technology renovation and technology transformation performance. The research results can provide a reference for the improvement of the technology innovation performance of regional high-tech industries.

Korean Economic Growth Factor Analysis with Total Factor Productivity

Korea has recorded negative real GDP growth only three times in the last 60 years: the oil crisis in 1980, the financial crisis in 1998, and the COVID-19 crisis in 2020. While the economic recession for the first time in 22 years may be attributed to COVID-19, it is more noteworthy is that the growth rate of the Korean economy has been continuously declining. To find counter measures for the decline in the economic growth rate, it is necessary to analyze the cause of the decline in the growth rate. The factors of economic growth can generally be divided into changes in input factors such as labor and capital and productivity. We analyzed the relative contribution of each input factor from 1982 to 2020. Our result suggests that the contributions of capital and labor to economic growth are decreasing over time, and the contribution of TFP is gradually increasing. This study is employing annual time series data to provide up-to-date estimates of TFP and exploring the determinants of TFP to help detect future growth engines for the long-run sustainable development in Korea. © 2022 IEEE.

The interplay of supply and demand shocks: measuring potential output in the COVID-19 pandemic

The coronavirus triggered a record fall of GDP in Croatia, 8.1% in 2020, one of the largest declines in the EU. The large macroeconomic shock stemming from the pandemic has affected both supply and demand. On the one hand, government measures have imposed unprecedented supply-side restrictions. On the other hand, growing uncertainty affected domestic and foreign demand. Croatia was particularly affected by a plunge in international tourism demand. Such a major macroeconomic shock poses a challenge for estimating potential GDP, which is difficult to estimate even in stable economic conditions. When estimating potential GDP in the context of the corona crisis, the main issue is the breakdown of the shock into a permanent and a temporary part (supply and demand shock). In this paper, we try to give the most logical breakdown of Croatian data and describe possible methodological approaches to the estimation of potential GDP during the pandemic. © 2021. All Rights Reserved.

Macroeconomic effects of teleworking in EU27: Stochastic frontier approach

The main aim of this paper is to investigate macroeconomic effects of teleworking during the COVID-19 pandemic, using an atypical approach. We apply stochastic frontier analysis to a Cobb-Douglas production function broadened with teleworkability variable, and analyse the level of (in)efficiency of EU27 countries in producing their GDPs. We find that increasing the percentage of jobs that can be done at home by 1 percentage point reduces the level of technical inefficiency by 3.5%. Additionally, we use a unique e-survey conducted in April and May of 2020, which provides the data on the share of people who started working from home as a results of a COVID-19 situation, and combine it with the teleworkability variable. Overall, our findings suggest that more developed EU countries have a higher share of teleworkable jobs, which in turn reduces their inefficiencies, and furthermore results in more people beginning to work from home in the pandemic. © 2021 Hellenic Association of Regional Scientists. All rights reserved.

When can physical distancing be relaxed? A health production function approach for COVID-19 control policy.

BACKGROUND: To assess if physical distancing measures to control the COVID-19 pandemic can be relaxed, one of the key indicators used is the reproduction number R. Many developing countries, however, have limited capacities to estimate R accurately. This study aims to demonstrate how health production function can be used to assess the state of COVID-19 transmission and to determine a risk-based relaxation policy. METHODS: The author employs a simple "bridge" between epidemiological models and production economics to establish the cumulative number of COVID-19 cases as a short-run total product function and to derive the corresponding marginal product, average product, and production elasticity. Three crucial dates defining the states of transmission, labelled red, yellow, and green zones, are determined. Relaxation policy is illogical in the "red zone" and is not recommended in the "yellow zone". In the "green zone", relaxation can be considered. The Bayesian probability of near term's daily cases meeting a policy target is computed. The method is applied to France, Germany, Italy, the UK, and the US, and to Indonesia as an example of application in developing countries. RESULTS: This study uses data from the WHO COVID-19 Dashboard, beginning from the first recording date for each country until February 28, 2021. As of June 30, 2020, France, Germany, Italy, and the UK had arrived at the "green zone" but with a high risk of transmission re-escalations. In the following weeks, their production elasticities were rising, giving a signal of accelerated transmissions. The signal was corroborated by these countries' rising cases, making them leaving the "green zone" in the later months. By February 28, 2021, the UK had returned to the "green zone", France, Germany, and Italy were still in the "yellow zone", while the US reached the "green zone" at a very high number of cases. Despite being in the "red zone", Indonesia relaxed its distancing measures, causing a sharp rise of cases. CONCLUSIONS: Health production function can show the state of COVID-19 transmission. A rising production elasticity gives an early warning of transmission escalations. The elasticity is a useful parameter for risk-based relaxation policy.

The economic burden of COVID-19 in the United States: Estimates and projections under an infection-based herd immunity approach.

OBJECTIVES: To assess the economic burden of COVID-19 that would arise absent behavioral or policy responses under the herd immunity approach in the United States and compare it to the total burden that also accounts for estimates of the value of lives lost. METHODS: We use the trajectories of age-specific human and physical capital in the production process to calculate output changes based on a human capital-augmented production function. We also calculate the total burden that results when including the value of lives lost as calculated from mortality rates of COVID-19 and estimates for the value of a statistical life in the United States based on studies assessing individual's willingness to pay to avoid risks. RESULTS: Our results indicate that the GDP loss associated with unmitigated COVID-19 would amount to a cumulative US$1.4 trillion by 2030 assuming that 60 percent of the population is infected over three years. This is equivalent to around 7.7 percent of GDP in 2019 (in constant 2010 US$) or an average tax on yearly output of 0.6 percent. After applying the value of a statistical life to account for the value of lives lost, our analyses show that the total burden can mount to between US$17 and 94 trillion over the next decade, which is equivalent to an annual tax burden between 8 and 43 percent. CONCLUSION: Our results show that the United States would incur a sizeable burden if it adopted a non-interventionist herd immunity approach. FUNDING: Research reported in this paper was supported by the Alexander von Humboldt Foundation, the Bill & Melinda Gates Foundation (Project INV-006261), and the Sino-German Center for Research Promotion (Project C-0048), which is funded by the German Research Foundation (DFG) and the National Natural Science Foundation of China (NSFC). Preparation of this article was also supported by the Value of Vaccination Research Network (VoVRN) through a grant from the Bill & Melinda Gates Foundation (Grant OPP1158136). The content is solely the responsibility of the authors.