The Impact of Public Health Programs on Economic Development

1971 ◽  
Vol 1 (3) ◽  
pp. 285-292 ◽  
Author(s):  
A. Kühner
Keyword(s):  
Economic Value ◽  
Economic Effects ◽  
Economic Losses ◽  
Mortality And Morbidity ◽  
Public Health Programs ◽  
Eradication Program ◽  
Health Investments ◽  
Agricultural Laborers ◽  
Malaria Eradication ◽  
The Impact

This paper is based on an attempt to describe the economic effects of a health program and to measure these effects. Multiple and complex factors make it difficult to determine the economic value of health investments. This problem of measurement may be solved by considering that any improvement of health means an increase and any deterioration of health indicates a decrease in the working capacities of the labor force. This paper suggests that death and disease cause losses of working time and gross domestic product (GDP). The example presented relates to malaria and to the effects of the malaria eradication program in Thailand. For the computation of economic losses due to malaria mortality and morbidity, a model was constructed in which the main variables are combined. The computations show the GDP lost year by year by the agricultural laborers who die or are sick as a result of malaria. The losses of GDP are calculated over a period of 12 years. Their downward trend is attributed to the impact (benefits) of the malaria eradication program. A separate series of computations (Table 2) indicates the economic losses of GDP that would be expected in the absence of a malaria eradication program.

What value do mangroves have in reducing the cost of storm surges?

2020 ◽  
Author(s):  
Christopher Thomas ◽  
Siddharth Narayan ◽  
Joss Matthewman ◽  
Christine Shepard ◽  
Laura Geselbracht ◽  
...  
Keyword(s):  
Storm Surge ◽  
Insurance Industry ◽  
Economic Value ◽  
Storm Surges ◽  
Coastal Flooding ◽  
Economic Losses ◽  
Modelling Framework ◽  
Catastrophe Modelling ◽  
The Cost ◽  
The Impact

<p>With coastlines becoming increasingly urbanised worldwide, the economic risk posed by storm surges to coastal communities has never been greater. Given the financial and ecological costs of manmade coastal defences, the past few years have seen growing interest in the effectiveness of natural coastal “defences” in reducing the risk of flooding to coastal properties, but estimating their actual economic value in reducing storm surge risk remains a challenging subject.</p><p>In this study, we estimate the value of mangroves in reducing annual losses to property from storm surges along a large stretch of coastline in Florida (USA), by employing a catastrophe modelling approach widely used in the insurance industry. We use a hydrodynamic coastal flood model coupled to a property loss model and a large property exposure dataset to estimate annual economic losses from hurricane-driven storm surges in Collier County, a hurricane-prone part of Florida. We then estimate the impact that removing mangroves in the region would have on average annual losses (AAL) caused by coastal flooding. We find that mangroves reduce AAL to properties behind them by over 25%, and that these benefits are distributed very heterogeneously along the coastline. Mangrove presence can also act to enhance the storm surge risk in areas where development has occurred seaward of mangroves.</p><p>In addition to looking at annual losses, we also focus on the storm surge caused by a specific severe event in Florida, based on Hurricane Irma (2017), and we estimate that existing mangroves reduced economic property damage by hundreds of millions of USD, and reduced coastal flooding for hundreds of thousands of people.</p><p>Together these studies aim to financially quantify some of the risk reduction services provided by natural defences in terms of reducing the cost of coastal flooding, and show that these services can be included in a catastrophe modelling framework commonly used in the insurance industry.</p>

Understanding how hydrological forecast quality impacts the management of hydroelectric reservoirs

2021 ◽  
Author(s):  
Maria-Helena Ramos ◽  
Manon Cassagnole ◽  
Ioanna Zalachori ◽  
Guillaume Thirel ◽  
Rémy Garçon ◽  
...  
Keyword(s):  
Economic Value ◽  
Optimal Placement ◽  
Economic Losses ◽  
Positive Bias ◽  
Production Rates ◽  
Hydroelectric Reservoirs ◽  
Hydroelectric Reservoir ◽  
Streamflow Forecasts ◽  
The Impact ◽  
Forecast Quality

<p>The evaluation of inflow forecast quality and value is essential in hydroelectric reservoir management. Forecast value can be quantified by the economic gains obtained when optimizing hydroelectric reservoir operations informed by weather and hydrological forecasts. This study [1] investigates the impact of 7-day streamflow forecasts on the optimal management of hydroelectric reservoirs and the associated economic gains. Flows from ten catchments in France are synthetically generated over a 4-year period to obtain forecasts of different quality in terms of accuracy and reliability. These forecasts define the inflows to ten hydroelectric reservoirs, which are conceptually parametrized. Each reservoir is associated to a downstream power plant with yield 1 which produces electricity valued with a price signal. The system is modelled using linear programming. Relationships between forecast quality and economic value (hydropower revenue) show that forecasts with a recurrent positive bias (overestimation) and low accuracy generate the highest economic losses when compared to the reference management system where forecasts are equal to observed inflows. The smallest losses are observed for forecast systems with under-dispersion reliability bias, while forecast systems with negative bias (underestimation) show intermediate losses. Overall, the losses (which amount to millions of Euros) represent approximately 1% to 3% of the revenue over the study period. Besides revenue, the forecast quality also impacts spillage, stock evolution, production hours and production rates. For instance, forecasting systems that present a positive bias result in a tendency of operations to keep the storage at lower levels so that the reservoir can be able to handle the high volumes expected. This impacts the optimal placement of production at the best hours (i.e. when prices are higher) and the opportunity to produce electricity at higher production rates. Our study showed that when using biased forecasting systems, hydropower production is not only planned during more hours at lower rates but also at hours with lower median prices of electricity. The modelling approaches adopted in our study are certainly far from representing all the complexity of hydropower management under uncertainty. However, they proved to be adapted to obtaining the first orders of magnitude of the value of inflow forecasts in elementary situations.</p><p>[1] https://doi.org/10.5194/hess-2020-410</p>

scholarly journals Quantifying the Benefits of Targeting for Pandemic Response

2021 ◽  
Author(s):  
Sergio Camelo ◽  
Dragos F. Ciocan ◽  
Dan A. Iancu ◽  
Xavier S. Warnes ◽  
Spyros I. Zoumpoulis
Keyword(s):  
Economic Value ◽  
Population Group ◽  
Economic Losses ◽  
Modeling Framework ◽  
Social Contacts ◽  
Policy Makers ◽  
Flexible Modeling ◽  
Trade Offs ◽  
The Impact

To respond to pandemics such as COVID-19, policy makers have relied on interventions that target specific population groups or activities. Such targeting is potentially contentious, so rigorously quantifying its benefits and downsides is critical for designing effective and equitable pandemic control policies. We propose a flexible modeling framework and a set of associated algorithms that compute optimally targeted, time-dependent interventions that coordinate across two dimensions of heterogeneity: population group characteristics and the specific activities that individuals engage in during the normal course of a day. We showcase a complete implementation in a case study focused on the Île-de-France region of France, based on commonly available hospitalization, community mobility, social contacts and economic data. We find that optimized dual-targeted policies have a simple and explainable structure, imposing less confinement on group-activity pairs that generate a relatively high economic value prorated by activity-specific social contacts. When compared to confinements based on uniform or less granular targeting, dual-targeted policies generate substantial complementarities that lead to Pareto improvements, reducing the number of deaths and the economic losses overall and reducing the time in confinement foreach population group. Since dual-targeted policies could lead to increased discrepancies in the confinements faced by distinct groups, we also quantify the impact of requirements that explicitly limit such disparities, and find that satisfactory intermediate trade-offs may be achievable through limited targeting.

scholarly journals Analisis Perkiraan Biaya Ekonomi Deforestasi Di Kalimantan Barat

2019 ◽  
Vol 8 (1) ◽  
pp. 59
Author(s):  
Akhmad Yani
Keyword(s):  
Research Question ◽  
Economic Value ◽  
Economic Loss ◽  
Forest Area ◽  
Economic Losses ◽  
Economic Costs ◽  
West Kalimantan ◽  
High Level ◽  
Almost All ◽  
The Impact

Almost all forest areas in the districts / cities in West Kalimantan experience reduced area. Reducing the area of forest area or deforestation can, of course, have a detrimental impact on the environment which in turn can disrupt the sustainability of development itself. Deforestation has ecological, economic and social impacts. The higher the rate of deforestation, it will cause the potential impact will also increase. West Kalimantan experienced a fairly high level of deforestation. This gives an indication that the impact caused by deforestation in West Kalimantan has a relatively high potential. In other words, deforestation causes losses including economic losses. Related to this, the research question is how much economic value is the loss caused by deforestation in West Kalimantan? This research has 2 (two) objectives: first, calculating the economic costs of deforestation in West Kalimantan during the period 2009-2015, and second, analyzing the effect of the economic costs of deforestation on West Kalimantan's GDP during the period 2009-2015. Based on the data base for the period 2009 to 2015 and using the benefit transfer technique, this research has found that the highest economic losses occur in the secondary production forest and the lowest in the conservation forest area. Furthermore, during the period 2009 to 2015, this study has found that the highest economic loss value occurred in 2013 and the lowest occurred in 2011. Overall, the value of economic losses in the form of a combination of depletion and degradation provides a less significant reduction on the value of the forestry sub-sector GRDP in West Kalimantan.

scholarly journals Impact of the quality of hydrological forecasts on the management and revenue of hydroelectric reservoirs – a conceptual approach

2021 ◽  
Vol 25 (2) ◽  
pp. 1033-1052
Author(s):  
Manon Cassagnole ◽  
Maria-Helena Ramos ◽  
Ioanna Zalachori ◽  
Guillaume Thirel ◽  
Rémy Garçon ◽  
...  
Keyword(s):  
Optimization Model ◽  
Economic Value ◽  
Systematic Evaluation ◽  
Economic Losses ◽  
Conceptual Approach ◽  
Hydroelectric Reservoirs ◽  
Streamflow Forecasts ◽  
Operational Systems ◽  
The Impact

Abstract. The improvement of a forecasting system and the continuous evaluation of its quality are recurrent steps in operational practice. However, the systematic evaluation of forecast value or usefulness for better decision-making is less frequent, even if it is also essential to guide strategic planning and investments. In the hydropower sector, several operational systems use medium-range hydrometeorological forecasts (up to 7–10 d ahead) and energy price predictions as input to models that optimize hydropower production. The operation of hydropower systems, including the management of water stored in reservoirs, is thus partially impacted by weather and hydrological conditions. Forecast value can be quantified by the economic gains obtained with the optimization of operations informed by the forecasts. In order to assess how much improving the quality of hydrometeorological forecasts will improve their economic value, it is essential to understand how the system and its optimization model are sensitive to sequences of input forecasts of different quality. This paper investigates the impact of 7 d streamflow forecasts of different quality on the management of hydroelectric reservoirs and the economic gains generated from a linear programming optimization model. The study is based on a conceptual approach. Flows from 10 catchments in France are synthetically generated over a 4-year period to obtain forecasts of different quality in terms of accuracy and reliability. These forecasts define the inflows to 10 hydroelectric reservoirs, which are conceptually parameterized. Relationships between forecast quality and economic value (hydropower revenue) show that forecasts with a recurrent positive bias (overestimation) and low accuracy generate the highest economic losses when compared to the reference management system where forecasts are equal to observed inflows. The smallest losses are observed for forecast systems with underdispersion reliability bias, while forecast systems with negative bias (underestimation) show intermediate losses. Overall, the losses (which amount to millions of Euros) represent approximately 1 % to 3 % of the revenue over the study period. Besides revenue, the quality of the forecasts also impacts spillage, stock evolution, production hours and production rates, with systematic over- and underestimations being able to generate some extreme reservoir management situations.

scholarly journals Impact of the quality of hydrological forecasts on the managementand revenue of hydroelectric reservoirs – a conceptual approach

2020 ◽  
Author(s):  
Manon Cassagnole ◽  
Maria-Helena Ramos ◽  
Ioanna Zalachori ◽  
Guillaume Thirel ◽  
Rémy Garçon ◽  
...  
Keyword(s):  
Optimization Model ◽  
Economic Value ◽  
Systematic Evaluation ◽  
Economic Losses ◽  
Conceptual Approach ◽  
Hydroelectric Reservoirs ◽  
Streamflow Forecasts ◽  
Operational Systems ◽  
The Impact

Abstract. The improvement of a forecasting system and the continuous evaluation of its quality are recurrent steps in operational practice. However, the systematic evaluation of forecast value or usefulness for better decision-making is less frequent, even if it is also essential to guide strategic planning and investments. In the hydropower sector, several operational systems use medium-range hydrometeorological forecasts (up to 7–10 days ahead) and energy price predictions as input to models that optimize hydropower production. The operation of hydropower systems, including the management of water stored in reservoirs, is thus partially impacted by weather and hydrological conditions. Forecast value can be quantified by the economic gains obtained with the optimization of operations informed by the forecasts. In order to assess how much improving the quality of hydrometeorological forecasts will also improve their economic value, it is also essential to understand how the system and its optimization model are sensitive to sequences of input forecasts of different quality. This paper investigates the impact of 7-day streamflow forecasts of different quality on the management of hydroelectric reservoirs and the economic gains generated from a linear programming optimization model. The study is based on a conceptual approach, where inflows to 10 reservoirs in France are synthetically generated over a 4-year period to obtain forecasts of different quality in terms of accuracy and reliability. Relationships between forecast quality and economic value (hydropower revenue) show that forecasts with a recurrent positive bias (overestimation) and low accuracy generate the highest economic losses, when compared to the reference management system where forecasts are equal to observed inflows. The smallest losses are observed for forecast systems with under-dispersion reliability bias, while forecast systems with negative bias (underestimation) show intermediate losses. Overall, the losses represent approximately 3 % to 1 % (in M€) of the revenue over the study period. Besides revenue, the quality of the forecasts also impacts spillage, stock evolution, production hours and production rates, with systematic over- and under-estimations being able to generate some extreme reservoir management situations.

scholarly journals Estimating the Risk of Declining Funding for Malaria in Ghana: The case for continued investment in the malaria response

2020 ◽  
Author(s):  
Rima Shretta ◽  
Sheetal P Silal ◽  
Keziah Malm ◽  
Wahjib Mohammed ◽  
Joel Narh ◽  
...  
Keyword(s):  
Malaria Elimination ◽  
Plasmodium Falciparum Malaria ◽  
Economic Benefits ◽  
Transmission Model ◽  
Economic Losses ◽  
External Financing ◽  
Financial Barriers ◽  
Mortality And Morbidity ◽  
Potential Risks ◽  
The Impact

Abstract Background: Ghana has made impressive progress against malaria, decreasing mortality and morbidity by over 50% between 2005-2015. These gains have been facilitated in part, due to increased financial commitment from both government and donors. Between 2006 and 2011, total resources for malaria increased from less than USD 25 million in 2006 to over USD 100 million. However, the country still faces a high burden of disease and is at risk of declining external financing due to its strong economic growth and the consequential increased donor requirements for domestic contributions. The resulting financial gap will need to be met domestically to accelerate progress. The purpose of this study was to provide evidence of the economic impact of malaria elimination and the potential risks of withdrawing financing to shape an advocacy strategy for resource mobilization.Methods: A compartmental transmission model was developed to estimate the impact of a range of malaria interventions on the transmission of Plasmodium falciparum malaria between 2018 and 2030. The model projected scenarios that allowed the attainment of elimination using a package of common interventions and scenarios that predicted transmission if interventions were withheld. The outputs of this model were used to generate costs and economic benefits of each option.Results: Elimination was predicted using the interventions outlined in the national strategy, particularly increased net usage and improved case management. Malaria elimination in Ghana was predicted cost USD 961 million between 2020 and 2029. Compared to the baseline, elimination is estimated to prevent 85.5 million cases, save 4,468 lives, and avert USD 2.2 billion in health system expenditures. The economic gain was estimated at USD 32 billion in reduced expenditure, increased household prosperity and productivity gains. Through malaria elimination, Ghana can expect to see a 32-fold return on their investment. Withdrawing interventions, predicted an additional 38.2 clinical cases, 2,500 deaths and additional economic losses of USD 14.1 billion.Conclusions: Although government financing has increased in the past decade, the amount is less than 25% of total malaria financing. The study findings can be used to develop a robust strategy to overcome financial barriers for malaria elimination in Ghana.

Key Aspects of Assessing Effectiveness and Efficiency of Implementation of the Federal Clean Air Project on the Example of the Comprehensive Emission Reduction Action Plan in Nizhny Tagil

2020 ◽  
pp. 48-60
Author(s):  
SV Yarushin ◽  
DV Kuzmin ◽  
AA Shevchik ◽  
TM Tsepilova ◽  
VB Gurvich ◽  
...  
Keyword(s):  
Emission Reduction ◽  
Action Plan ◽  
Local Population ◽  
Ambient Air ◽  
Ambient Air Pollution ◽  
Mortality And Morbidity ◽  
Industrial Enterprises ◽  
Clean Air ◽  
Effectiveness And Efficiency ◽  
The Impact

Introduction: Key issues of assessing effectiveness and economic efficiency of implementing the Federal Clean Air Project by public health criteria are considered based on the example of the Comprehensive Emission Reduction Action Plan realized in the city of Nizhny Tagil, Sverdlovsk Region. Materials and methods: We elaborated method approaches and reviewed practical aspects of evaluating measures taken in 2018–2019 at key urban industrial enterprises accounting for 95 % of stationary source emissions. Results: Summary calculations of ambient air pollution and carcinogenic and non-carcinogenic inhalation health risks including residual risks, evaluation of the impact of air quality on urban mortality and morbidity rates, economic assessment of prevented morbidity and premature mortality cases have enabled us not only to estimate health effects but also to develop guidelines for development and implementation of actions aimed at enhancing effectiveness and efficiency of industrial emission reduction in terms of health promotion of the local population. Conclusions: We substantiate proposals for the necessity and sufficiency of taking remedial actions ensuring achievement of acceptable health risk levels as targets of the Comprehensive Emission Reduction Action Plan in Nizhny Tagil until 2024 and beyond.

Pension Reform in Russia: Assessing the Susceptibility of GDP Production to a Shift in the Number of the Working-Age Population

2019 ◽  
pp. 80-86
Author(s):  
T. P. Skufina ◽  
S. V. Baranov
Keyword(s):  
Pension Reform ◽  
Fixed Capital ◽  
Economic Effects ◽  
Pension Scheme ◽  
Retirement Age ◽  
Working Age ◽  
Working Age Population ◽  
Long Term Forecasting ◽  
The Impact

The presented study considers the susceptibility of gross domestic product (GDP) production to a shift in the number of the working-age population due to an increase in retirement age starting with 2019.Aim. The study aims to examine the quantitative assessments of GDP production in Russia with allowance for the changes in the number of the working-age population due to an increase in the actual retirement age.Tasks. The authors forecast the number of the working-age population with allowance for an increase in the retirement age; develop a model to establish a correlation between the number of the workingage population, investment in fixed capital, and GDP production; quantify the impact of the shift in the number of the working-age population on GDP production in Russia. Methods. This study is based on the results of modeling and long-term forecasting.Results. An economic-mathematical model to establish a correlation between the number of the working-age population, investment in fixed capital, and GDP production is presented. To specify the economic effects of a shift in the number of the working-age population due to an increase in the retirement age, Russia’s GDP production is forecasted for the “old” and “new” (increased retirement age) pension scheme. The forecast is provided for three variants of the number of the working-age population.Conclusions. It is found that with the “old” pension scheme with a lower retirement age GDP production across all three variants will decrease by 2036 compared to 2017. With regard to the “new” scheme that increases the retirement age, it is concluded that an increase in the retirement age is a factor that facilitates GDP production. However, its effect on economic growth will be insignificant.

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