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Objectives: To estimate the expected socio-economic value of booster vaccination in terms of averted deaths and averted closures of businesses and schools using simulation modelling. Methods: The value of booster vaccination in Indonesia is estimated by comparing simulated societal costs under a twelve-month, 187-million–dose Moderna booster vaccination campaign to costs without boosters. The costs of an epidemic and its mitigation consist of lost lives, economic closures and lost education; cost-minimising non-pharmaceutical mitigation is chosen for each scenario. Results: The cost-minimising non-pharmaceutical mitigation depends on the availability of vaccines: the differences between the two scenarios are 14 to 19 million years of in-person education and $153 to $204 billion in economic activity. The value of the booster campaign ranges from $2,500 ($1,400-$4,100) to $2,800 ($1,700-$4,600) per dose in the first year, depending on life-year valuations. Conclusions: The societal benefits of booster vaccination are substantial. Much of the value of vaccination resides in the reduced need for costly non-pharmaceutical mitigation. We propose cost minimisation as a tool for policy decision-making and valuation of vaccination, taking into account all socio-economic costs, and not averted deaths alone.

Objectives: To estimate the expected socio-economic value of booster vaccination in terms of averted deaths and averted closures of businesses and schools using simulation modelling. Methods: The value of booster vaccination in Indonesia is estimated by comparing simulated societal costs under a twelve-month, 187-million–dose Moderna booster vaccination campaign to costs without boosters. The costs of an epidemic and its mitigation consist of lost lives, economic closures and lost education; cost-minimising non-pharmaceutical mitigation is chosen for each scenario. Results: The cost-minimising non-pharmaceutical mitigation depends on the availability of vaccines: the differences between the two scenarios are 14 to 19 million years of in-person education and $153 to $204 billion in economic activity. The value of the booster campaign ranges from $2,500 ($1,400-$4,100) to $2,800 ($1,700-$4,600) per dose in the first year, depending on life-year valuations. Conclusions: The societal benefits of booster vaccination are substantial. Much of the value of vaccination resides in the reduced need for costly non-pharmaceutical mitigation. We propose cost minimisation as a tool for policy decision-making and valuation of vaccination, taking into account all socio-economic costs, and not averted deaths alone.

The COVID-19 pandemic has seen dramatic demand surges for hospital care that have placed a severe strain on health systems worldwide. As a result, policy makers are faced with the challenge of managing scarce hospital capacity to reduce the backlog of non-COVID patients while maintaining the ability to respond to any potential future increases in demand for COVID care. In this paper, we propose a nationwide prioritization scheme that models each individual patient as a dynamic program whose states encode the patient’s health and treatment condition, whose actions describe the available treatment options, whose transition probabilities characterize the stochastic evolution of the patient’s health, and whose rewards encode the contribution to the overall objectives of the health system. The individual patients’ dynamic programs are coupled through constraints on the available resources, such as hospital beds, doctors, and nurses. We show that the overall problem can be modeled as a grouped weakly coupled dynamic program for which we determine near-optimal solutions through a fluid approximation. Our case study for the National Health Service in England shows how years of life can be gained by prioritizing specific disease types over COVID patients, such as injury and poisoning, diseases of the respiratory system, diseases of the circulatory system, diseases of the digestive system, and cancer.

Objectives: To estimate the expected socio-economic value of booster vaccination in terms of averted deaths and averted closures of businesses and schools using simulation modelling. Methods: The value of booster vaccination in Indonesia is estimated by comparing simulated societal costs under a twelve-month, 187-million–dose Moderna booster vaccination campaign to costs without boosters. The costs of an epidemic and its mitigation consist of lost lives, economic closures and lost education; cost-minimising non-pharmaceutical mitigation is chosen for each scenario. Results: The cost-minimising non-pharmaceutical mitigation depends on the availability of vaccines: the differences between the two scenarios are 14 to 19 million years of in-person education and $153 to $204 billion in economic activity. The value of the booster campaign ranges from $2,500 ($1,400-$4,100) to $2,800 ($1,700-$4,600) per dose in the first year, depending on life-year valuations. Conclusions: The societal benefits of booster vaccination are substantial. Much of the value of vaccination resides in the reduced need for costly non-pharmaceutical mitigation. We propose cost minimisation as a tool for policy decision-making and valuation of vaccination, taking into account all socio-economic costs, and not averted deaths alone.

Objectives: To estimate the expected socio-economic value of booster vaccination in terms of averted deaths and averted closures of businesses and schools using simulation modelling. Methods: The value of booster vaccination in Indonesia is estimated by comparing simulated societal costs under a twelve-month, 187-million–dose Moderna booster vaccination campaign to costs without boosters. The costs of an epidemic and its mitigation consist of lost lives, economic closures and lost education; cost-minimising non-pharmaceutical mitigation is chosen for each scenario. Results: The cost-minimising non-pharmaceutical mitigation depends on the availability of vaccines: the differences between the two scenarios are 14 to 19 million years of in-person education and $153 to $204 billion in economic activity. The value of the booster campaign ranges from $2,500 ($1,400-$4,100) to $2,800 ($1,700-$4,600) per dose in the first year, depending on life-year valuations. Conclusions: The societal benefits of booster vaccination are substantial. Much of the value of vaccination resides in the reduced need for costly non-pharmaceutical mitigation. We propose cost minimisation as a tool for policy decision-making and valuation of vaccination, taking into account all socio-economic costs, and not averted deaths alone.

Objectives: To estimate the expected socio-economic value of booster vaccination in terms of averted deaths and averted closures of businesses and schools using simulation modelling. Methods: The value of booster vaccination in Indonesia is estimated by comparing simulated societal costs under a twelve-month, 187-million–dose Moderna booster vaccination campaign to costs without boosters. The costs of an epidemic and its mitigation consist of lost lives, economic closures and lost education; cost-minimising non-pharmaceutical mitigation is chosen for each scenario. Results: The cost-minimising non-pharmaceutical mitigation depends on the availability of vaccines: the differences between the two scenarios are 14 to 19 million years of in-person education and $153 to $204 billion in economic activity. The value of the booster campaign ranges from $2,500 ($1,400-$4,100) to $2,800 ($1,700-$4,600) per dose in the first year, depending on life-year valuations. Conclusions: The societal benefits of booster vaccination are substantial. Much of the value of vaccination resides in the reduced need for costly non-pharmaceutical mitigation. We propose cost minimisation as a tool for policy decision-making and valuation of vaccination, taking into account all socio-economic costs, and not averted deaths alone.

The COVID-19 pandemic and the mitigation policies implemented in response to it have resulted in economic losses worldwide. Attempts to understand the relationship between economics and epidemiology has led to a new generation of integrated mathematical models. The data needs for these models transcend those of the individual fields, especially where human interaction patterns are closely linked with economic activity. In this article, we reflect upon modelling efforts to date, discussing the data needs that they have identified, both for understanding the consequences of the pandemic and policy responses to it through analysis of historic data and for the further development of this new and exciting interdisciplinary field.

The COVID-19 pandemic and the mitigation policies implemented in response to it have resulted in economic losses worldwide. Attempts to understand the relationship between economics and epidemiology has led to a new generation of integrated mathematical models. The data needs for these models transcend those of the individual fields, especially where human interaction patterns are closely linked with economic activity. In this article, we reflect upon modelling efforts to date, discussing the data needs that they have identified, both for understanding the consequences of the pandemic and policy responses to it through analysis of historic data and for the further development of this new and exciting interdisciplinary field.

The COVID-19 pandemic and the mitigation policies implemented in response to it have resulted in economic losses worldwide. Attempts to understand the relationship between economics and epidemiology has led to a new generation of integrated mathematical models. The data needs for these models transcend those of the individual fields, especially where human interaction patterns are closely linked with economic activity. In this article, we reflect upon modelling efforts to date, discussing the data needs that they have identified, both for understanding the consequences of the pandemic and policy responses to it through analysis of historic data and for the further development of this new and exciting interdisciplinary field.

To study the trade-off between economic, social and health outcomes in the management of a pandemic, DAEDALUS integrates a dynamic epidemiological model of SARS-CoV-2 transmission with a multi-sector economic model, reflecting sectoral heterogeneity in transmission and complex supply chains. The model identifies mitigation strategies that optimize economic production while constraining infections so that hospital capacity is not exceeded but allowing essential services, including much of the education sector, to remain active. The model differentiates closures by economic sector, keeping those sectors open that contribute little to transmission but much to economic output and those that produce essential services as intermediate or final consumption products. In an illustrative application to 63 sectors in the United Kingdom, the model achieves an economic gain of between £161 billion (24%) and £193 billion (29%) compared to a blanket lockdown of non-essential activities over six months. Although it has been designed for SARS-CoV-2, DAEDALUS is sufficiently flexible to be applicable to pandemics with different epidemiological characteristics.

The COVID-19 pandemic and the mitigation policies implemented in response to it have resulted in economic losses worldwide. Attempts to understand the relationship between economics and epidemiology has led to a new generation of integrated mathematical models. The data needs for these models transcend those of the individual fields, especially where human interaction patterns are closely linked with economic activity. In this article, we reflect upon modelling efforts to date, discussing the data needs that they have identified, both for understanding the consequences of the pandemic and policy responses to it through analysis of historic data and for the further development of this new and exciting interdisciplinary field.

Human activities have caused massive losses of natural populations across the globe. Like many groups, amphibians have experienced substantial declines worldwide, driven by environmental changes such as habitat conversion, pollution, and disease emergence. Each of these drivers is often found in close association with the presence of roads. Here we report a novel consequence of roads affecting an amphibian native to much of North America, the wood frog (Rana sylvatica). Across 38 populations distributed from southern to central New England, we found that adult wood frogs living adjacent to roads had higher incidence and severity of oedema (indicated by obvious bloating caused by subcutaneous fluid accumulation) during the breeding season than frogs living away from the influence of roads. This effect was best explained by increased conductivity of breeding ponds, prob-ably caused by runoff pollution from road salt used for de-icing. Oedema severity was negatively correlated with locomotor performance in more northerly populations. Interestingly, northern populations experience more intense winters, which tends to result in more de-icing salt runoff and increased energetic demands associated with overwintering cryoprotection needs. Thus, this emerging consequence of roads appears to impose potential fitness costs associated with locomotion, and these effects might be most impactful on populations living in regions where de-icing is most intense.Together, our findings reveal a novel set of impacts of roads and runoff pollution on wood frog physiology and performance, which seem likely to contribute to population decline. Given the global prevalence of roads and increasing salinisation of freshwater habitats, oedema and related impacts could be widespread consequences faced by amphibian populations across much of the planet's temperate zones

The COVID-19 pandemic and the mitigation policies implemented in response to it have resulted in economic losses worldwide. Attempts to understand the relationship between economics and epidemiology has led to a new generation of integrated mathematical models. The data needs for these models transcend those of the individual fields, especially where human interaction patterns are closely linked with economic activity. In this article, we reflect upon modelling efforts to date, discussing the data needs that they have identified, both for understanding the consequences of the pandemic and policy responses to it through analysis of historic data and for the further development of this new and exciting interdisciplinary field.

In response to unprecedented surges in the demand for hospital care during the SARS-CoV-2 pandemic, health systems have prioritized patients with COVID-19 to life-saving hospital care to the detriment of other patients. In contrast to these ad hoc policies, we develop a linear programming framework to optimally schedule elective procedures and allocate hospital beds among all planned and emergency patients to minimize years of life lost. Leveraging a large dataset of administrative patient medical records, we apply our framework to the National Health Service in England and show that an extra 50,750–5,891,608 years of life can be gained compared with prioritization policies that reflect those implemented during the pandemic. Notable health gains are observed for neoplasms, diseases of the digestive system, and injuries and poisoning. Our open-source framework provides a computationally efficient approximation of a large-scale discrete optimization problem that can be applied globally to support national-level care prioritization policies.

In response to unprecedented surges in the demand for hospital care during the SARS-CoV-2 pandemic, health systems have prioritized patients with COVID-19 to life-saving hospital care to the detriment of other patients. In contrast to these ad hoc policies, we develop a linear programming framework to optimally schedule elective procedures and allocate hospital beds among all planned and emergency patients to minimize years of life lost. Leveraging a large dataset of administrative patient medical records, we apply our framework to the National Health Service in England and show that an extra 50,750–5,891,608 years of life can be gained compared with prioritization policies that reflect those implemented during the pandemic. Notable health gains are observed for neoplasms, diseases of the digestive system, and injuries and poisoning. Our open-source framework provides a computationally efficient approximation of a large-scale discrete optimization problem that can be applied globally to support national-level care prioritization policies.

In response to unprecedented surges in the demand for hospital care during the SARS-CoV-2 pandemic, health systems have prioritized patients with COVID-19 to life-saving hospital care to the detriment of other patients. In contrast to these ad hoc policies, we develop a linear programming framework to optimally schedule elective procedures and allocate hospital beds among all planned and emergency patients to minimize years of life lost. Leveraging a large dataset of administrative patient medical records, we apply our framework to the National Health Service in England and show that an extra 50,750–5,891,608 years of life can be gained compared with prioritization policies that reflect those implemented during the pandemic. Notable health gains are observed for neoplasms, diseases of the digestive system, and injuries and poisoning. Our open-source framework provides a computationally efficient approximation of a large-scale discrete optimization problem that can be applied globally to support national-level care prioritization policies.

In response to unprecedented surges in the demand for hospital care during the SARS-CoV-2 pandemic, health systems have prioritized patients with COVID-19 to life-saving hospital care to the detriment of other patients. In contrast to these ad hoc policies, we develop a linear programming framework to optimally schedule elective procedures and allocate hospital beds among all planned and emergency patients to minimize years of life lost. Leveraging a large dataset of administrative patient medical records, we apply our framework to the National Health Service in England and show that an extra 50,750–5,891,608 years of life can be gained compared with prioritization policies that reflect those implemented during the pandemic. Notable health gains are observed for neoplasms, diseases of the digestive system, and injuries and poisoning. Our open-source framework provides a computationally efficient approximation of a large-scale discrete optimization problem that can be applied globally to support national-level care prioritization policies.

In response to unprecedented surges in the demand for hospital care during the SARS-CoV-2 pandemic, health systems have prioritized patients with COVID-19 to life-saving hospital care to the detriment of other patients. In contrast to these ad hoc policies, we develop a linear programming framework to optimally schedule elective procedures and allocate hospital beds among all planned and emergency patients to minimize years of life lost. Leveraging a large dataset of administrative patient medical records, we apply our framework to the National Health Service in England and show that an extra 50,750–5,891,608 years of life can be gained compared with prioritization policies that reflect those implemented during the pandemic. Notable health gains are observed for neoplasms, diseases of the digestive system, and injuries and poisoning. Our open-source framework provides a computationally efficient approximation of a large-scale discrete optimization problem that can be applied globally to support national-level care prioritization policies.

There is a trade-off between the education sector and other economic sectors in the control of SARS-CoV-2 transmission. Here we integrate a dynamic model of SARS-CoV-2 transmission with a 63-sector economic model reflecting sectoral heterogeneity in transmission and economic interdependence between sectors. We identify control strategies which optimize economic production while keeping schools and universities operational and constraining infections such that emergency hospital capacity is not exceeded. The model estimates an economic gain of between £163bn and £205bn for the United Kingdom compared to a blanket lockdown of non-essential activity over six months, depending on hospital capacity. Sectors identified as potential priorities for closure are contact-intensive and/or less economically productive.

Countries have deployed a wide range of policies to prioritize patients to hospital care to address unprecedent surges in demand during the course of the pandemic. Those policies included postponing planned hospital care for non-emergency cases and rationing critical care. We developed a model to optimally schedule elective hospitalizations and allocate hospital general and critical care beds to planned and emergency patients in England during the pandemic. We apply the model to NHS England data and show that optimized scheduling leads to lower years of life lost and costs than policies that reflect those implemented in England during the pandemic. Overall across all disease areas the model enables an extra 50,750-5,891,608 years of life gained when compared to standard policies, depending on the scenarios. Especially large gains in years of life are seen for neoplasms, diseases of the digestive system, and injuries &poisoning.

Countries have deployed a wide range of policies to prioritize patients to hospital care to address unprecedent surges in demand during the course of the pandemic. Those policies included postponing planned hospital care for non-emergency cases and rationing critical care. We developed a model to optimally schedule elective hospitalizations and allocate hospital general and critical care beds to planned and emergency patients in England during the pandemic. We apply the model to NHS England data and show that optimized scheduling leads to lower years of life lost and costs than policies that reflect those implemented in England during the pandemic. Overall across all disease areas the model enables an extra 50,750-5,891,608 years of life gained when compared to standard policies, depending on the scenarios. Especially large gains in years of life are seen for neoplasms, diseases of the digestive system, and injuries &poisoning.

There is a trade-off between the education sector and other economic sectors in the control of SARS-CoV-2 transmission. Here we integrate a dynamic model of SARS-CoV-2 transmission with a 63-sector economic model reflecting sectoral heterogeneity in transmission and economic interdependence between sectors. We identify control strategies which optimize economic production while keeping schools and universities operational and constraining infections such that emergency hospital capacity is not exceeded. The model estimates an economic gain of between £163bn and £205bn for the United Kingdom compared to a blanket lockdown of non-essential activity over six months, depending on hospital capacity. Sectors identified as potential priorities for closure are contact-intensive and/or less economically productive.

There is a trade-off between the education sector and other economic sectors in the control of SARS-CoV-2 transmission. Here we integrate a dynamic model of SARS-CoV-2 transmission with a 63-sector economic model reflecting sectoral heterogeneity in transmission and economic interdependence between sectors. We identify control strategies which optimize economic production while keeping schools and universities operational and constraining infections such that emergency hospital capacity is not exceeded. The model estimates an economic gain of between £163bn and £205bn for the United Kingdom compared to a blanket lockdown of non-essential activity over six months, depending on hospital capacity. Sectors identified as potential priorities for closure are contact-intensive and/or less economically productive.

Countries have deployed a wide range of policies to prioritize patients to hospital care to address unprecedent surges in demand during the course of the pandemic. Those policies included postponing planned hospital care for non-emergency cases and rationing critical care. We developed a model to optimally schedule elective hospitalizations and allocate hospital general and critical care beds to planned and emergency patients in England during the pandemic. We apply the model to NHS England data and show that optimized scheduling leads to lower years of life lost and costs than policies that reflect those implemented in England during the pandemic. Overall across all disease areas the model enables an extra 50,750-5,891,608 years of life gained when compared to standard policies, depending on the scenarios. Especially large gains in years of life are seen for neoplasms, diseases of the digestive system, and injuries &poisoning.

Countries have deployed a wide range of policies to prioritize patients to hospital care to address unprecedent surges in demand during the course of the pandemic. Those policies included postponing planned hospital care for non-emergency cases and rationing critical care. We developed a model to optimally schedule elective hospitalizations and allocate hospital general and critical care beds to planned and emergency patients in England during the pandemic. We apply the model to NHS England data and show that optimized scheduling leads to lower years of life lost and costs than policies that reflect those implemented in England during the pandemic. Overall across all disease areas the model enables an extra 50,750-5,891,608 years of life gained when compared to standard policies, depending on the scenarios. Especially large gains in years of life are seen for neoplasms, diseases of the digestive system, and injuries &poisoning.

There is a trade-off between the education sector and other economic sectors in the control of SARS-CoV-2 transmission. Here we integrate a dynamic model of SARS-CoV-2 transmission with a 63-sector economic model reflecting sectoral heterogeneity in transmission and economic interdependence between sectors. We identify control strategies which optimize economic production while keeping schools and universities operational and constraining infections such that emergency hospital capacity is not exceeded. The model estimates an economic gain of between £163bn and £205bn for the United Kingdom compared to a blanket lockdown of non-essential activity over six months, depending on hospital capacity. Sectors identified as potential priorities for closure are contact-intensive and/or less economically productive.

There is a trade-off between the education sector and other economic sectors in the control of SARS-CoV-2 transmission. Here we integrate a dynamic model of SARS-CoV-2 transmission with a 63-sector economic model reflecting sectoral heterogeneity in transmission and economic interdependence between sectors. We identify control strategies which optimize economic production while keeping schools and universities operational and constraining infections such that emergency hospital capacity is not exceeded. The model estimates an economic gain of between £163bn and £205bn for the United Kingdom compared to a blanket lockdown of non-essential activity over six months, depending on hospital capacity. Sectors identified as potential priorities for closure are contact-intensive and/or less economically productive.

Countries have deployed a wide range of policies to prioritize patients to hospital care to address unprecedent surges in demand during the course of the pandemic. Those policies included postponing planned hospital care for non-emergency cases and rationing critical care. We developed a model to optimally schedule elective hospitalizations and allocate hospital general and critical care beds to planned and emergency patients in England during the pandemic. We apply the model to NHS England data and show that optimized scheduling leads to lower years of life lost and costs than policies that reflect those implemented in England during the pandemic. Overall across all disease areas the model enables an extra 50,750-5,891,608 years of life gained when compared to standard policies, depending on the scenarios. Especially large gains in years of life are seen for neoplasms, diseases of the digestive system, and injuries &poisoning.

Dataset: mcm_ps, Bedford Institute of Oceanography Moored Current Meter Data deployed during cruises to the Eastern Gulf of Maine/Scotian Shelf from Canadian ships R/V Parizeau and R/V Hudson from 1993-1999 as part of the U.S. GLOBEC Georges Bank project (GB project) For a complete list of measurements, refer to the full dataset description in the supplemental file 'Dataset_description.pdf'. The most current version of this dataset is available at: https://www.bco-dmo.org/dataset/2406, National Science Foundation (NSF) unknown GB NSF, National Oceanic and Atmospheric Administration (NOAA) unknown GB NOAA

Dataset: sss, Sea surface temperature, salinity and fluorescence from sensors on R/V Endeavor cruise EN256 in the Gulf of Maine and Georges Bank in October, 1994 as part of the U.S. GLOBEC program (GB project) For a complete list of measurements, refer to the full dataset description in the supplemental file 'Dataset_description.pdf'. The most current version of this dataset is available at: https://www.bco-dmo.org/dataset/2410, National Oceanic and Atmospheric Administration (NOAA) unknown GB NOAA, NSF Division of Ocean Sciences (NSF OCE) OCE-9313670

Dataset: CTD_ps, Bedford Institute of Oceanography CTD Data from 10 cruises to the Eastern Gulf of Maine/Scotian Shelf aboard Canadian ships CCGS Cygnus, R/V Hudson, and R/V Parizeau from 1993-1999 (GB project) For a complete list of measurements, refer to the full dataset description in the supplemental file 'Dataset_description.pdf'. The most current version of this dataset is available at: https://www.bco-dmo.org/dataset/2405, National Science Foundation (NSF) unknown GB NSF, National Oceanic and Atmospheric Administration (NOAA) unknown GB NOAA

Dataset: sss, Sea surface temperature, salinity and fluorescence from sensors on R/V Endeavor cruise EN256 in the Gulf of Maine and Georges Bank in October, 1994 as part of the U.S. GLOBEC program (GB project) For a complete list of measurements, refer to the full dataset description in the supplemental file 'Dataset_description.pdf'. The most current version of this dataset is available at: https://www.bco-dmo.org/dataset/2410, National Oceanic and Atmospheric Administration (NOAA) unknown GB NOAA, NSF Division of Ocean Sciences (NSF OCE) OCE-9313670

Dataset: CTD_ps, Bedford Institute of Oceanography CTD Data from 10 cruises to the Eastern Gulf of Maine/Scotian Shelf aboard Canadian ships CCGS Cygnus, R/V Hudson, and R/V Parizeau from 1993-1999 (GB project) For a complete list of measurements, refer to the full dataset description in the supplemental file 'Dataset_description.pdf'. The most current version of this dataset is available at: https://www.bco-dmo.org/dataset/2405, National Science Foundation (NSF) unknown GB NSF, National Oceanic and Atmospheric Administration (NOAA) unknown GB NOAA

Dataset: CTD_ps, Bedford Institute of Oceanography CTD Data from 10 cruises to the Eastern Gulf of Maine/Scotian Shelf aboard Canadian ships CCGS Cygnus, R/V Hudson, and R/V Parizeau from 1993-1999 (GB project) For a complete list of measurements, refer to the full dataset description in the supplemental file 'Dataset_description.pdf'. The most current version of this dataset is available at: https://www.bco-dmo.org/dataset/2405, National Science Foundation (NSF) unknown GB NSF, National Oceanic and Atmospheric Administration (NOAA) unknown GB NOAA

Dataset: mcm_ps, Bedford Institute of Oceanography Moored Current Meter Data deployed during cruises to the Eastern Gulf of Maine/Scotian Shelf from Canadian ships R/V Parizeau and R/V Hudson from 1993-1999 as part of the U.S. GLOBEC Georges Bank project (GB project) For a complete list of measurements, refer to the full dataset description in the supplemental file 'Dataset_description.pdf'. The most current version of this dataset is available at: https://www.bco-dmo.org/dataset/2406, National Science Foundation (NSF) unknown GB NSF, National Oceanic and Atmospheric Administration (NOAA) unknown GB NOAA

Dataset: mcm_ps, Bedford Institute of Oceanography Moored Current Meter Data deployed during cruises to the Eastern Gulf of Maine/Scotian Shelf from Canadian ships R/V Parizeau and R/V Hudson from 1993-1999 as part of the U.S. GLOBEC Georges Bank project (GB project) For a complete list of measurements, refer to the full dataset description in the supplemental file 'Dataset_description.pdf'. The most current version of this dataset is available at: https://www.bco-dmo.org/dataset/2406, National Science Foundation (NSF) unknown GB NSF, National Oceanic and Atmospheric Administration (NOAA) unknown GB NOAA

Dataset: sss, Sea surface temperature, salinity and fluorescence from sensors on R/V Endeavor cruise EN256 in the Gulf of Maine and Georges Bank in October, 1994 as part of the U.S. GLOBEC program (GB project) For a complete list of measurements, refer to the full dataset description in the supplemental file 'Dataset_description.pdf'. The most current version of this dataset is available at: https://www.bco-dmo.org/dataset/2410, National Oceanic and Atmospheric Administration (NOAA) unknown GB NOAA, NSF Division of Ocean Sciences (NSF OCE) OCE-9313670

Dataset: alongtrackel, Ship data collected along the track during R/V Edwin Link cruises EL9904 and EL9905 in the Gulf of Maine and Georges Bank as part of the U.S. GLOBEC program in 1999. For a complete list of measurements, refer to the full dataset description in the supplemental file 'Dataset_description.pdf'. The most current version of this dataset is available at: https://www.bco-dmo.org/dataset/2413, National Science Foundation (NSF) unknown GB NSF, National Oceanic and Atmospheric Administration (NOAA) unknown GB NOAA

Dataset: alongtrackel, Ship data collected along the track during R/V Edwin Link cruises EL9904 and EL9905 in the Gulf of Maine and Georges Bank as part of the U.S. GLOBEC program in 1999. For a complete list of measurements, refer to the full dataset description in the supplemental file 'Dataset_description.pdf'. The most current version of this dataset is available at: https://www.bco-dmo.org/dataset/2413, National Science Foundation (NSF) unknown GB NSF, National Oceanic and Atmospheric Administration (NOAA) unknown GB NOAA

Dataset: alongtrackel, Ship data collected along the track during R/V Edwin Link cruises EL9904 and EL9905 in the Gulf of Maine and Georges Bank as part of the U.S. GLOBEC program in 1999. For a complete list of measurements, refer to the full dataset description in the supplemental file 'Dataset_description.pdf'. The most current version of this dataset is available at: https://www.bco-dmo.org/dataset/2413, National Science Foundation (NSF) unknown GB NSF, National Oceanic and Atmospheric Administration (NOAA) unknown GB NOAA

Dataset: eventlogs, Event logs from the U.S. GLOBEC Georges Bank project, from 10 vessels and 104 cruises in the Gulf of Maine and Georges Bank area from 1994-1999. Event logs provide an overall summary of the sampling activities during a cruise. For a complete list of measurements, refer to the full dataset description in the supplemental file 'Dataset_description.pdf'. The most current version of this dataset is available at: https://www.bco-dmo.org/dataset/2321, National Science Foundation (NSF) unknown GB NSF, National Oceanic and Atmospheric Administration (NOAA) unknown GB NOAA

Dataset: eventlogs, Event logs from the U.S. GLOBEC Georges Bank project, from 10 vessels and 104 cruises in the Gulf of Maine and Georges Bank area from 1994-1999. Event logs provide an overall summary of the sampling activities during a cruise. For a complete list of measurements, refer to the full dataset description in the supplemental file 'Dataset_description.pdf'. The most current version of this dataset is available at: https://www.bco-dmo.org/dataset/2321, National Science Foundation (NSF) unknown GB NSF, National Oceanic and Atmospheric Administration (NOAA) unknown GB NOAA

Dataset: eventlogs, Event logs from the U.S. GLOBEC Georges Bank project, from 10 vessels and 104 cruises in the Gulf of Maine and Georges Bank area from 1994-1999. Event logs provide an overall summary of the sampling activities during a cruise. For a complete list of measurements, refer to the full dataset description in the supplemental file 'Dataset_description.pdf'. The most current version of this dataset is available at: https://www.bco-dmo.org/dataset/2321, National Science Foundation (NSF) unknown GB NSF, National Oceanic and Atmospheric Administration (NOAA) unknown GB NOAA

Global health research has typically focused on single diseases, and most economic evaluation research to date has analysed technical health interventions to identify 'best buys'. New approaches in the conduct of economic evaluations are needed to help policymakers in choosing what may be good value (ie, greater health, distribution of health, or financial risk protection) for money (ie, per budget expenditure) investments for health system strengthening (HSS) that tend to be programmatic. We posit that these economic evaluations of HSS interventions will require developing new analytic models of health systems which recognise the dynamic connections between the different components of the health system, characterise the type and interlinks of the system's delivery platforms; and acknowledge the multiple constraints both within and outside the health sector which limit the system's capacity to efficiently attain its objectives. We describe priority health system modelling research areas to conduct economic evaluation of HSS interventions and ultimately identify good value for money investments in HSS., Department of Global Health and Population at the Harvard T.H. Chan School of Public Health

The Bedford Institute of Oceanography, E.G.&G., National Marine Fisheries Service, U.S. Geological Survey, and Woods Hole Oceanographic Institution have conducted separate moored array experiments during 1974- 1980 to study various aspects of the regional circulation in the Gulf of Maine and adjacent Scotian and New England shelf and slope regions. The mean currents and current variances measured in these experiments are summarized here in tabular and graphical form, together with other information about each experiment. While there have been few measurements made in the interior of the Gulf of Maine, the map of mean subsurface currents demonstrate (a) a net inflow of Scotian shelf water past Cape Sable into the Gulf, (b) a net inflow of slope water through the Northeast Channel into the Gulf, (c) a partially closed anticyclonic circulation around Georges Bank, and (d) a net outflow of shelf water south of Nantucket from the Gulf of Maine into the New England shelf., Funding was provided by the Department of Interior, Bureau of Land Management under Contract AA 551-MU0-18 and by the National Science Foundation under Grant OCE 80-14941.

The Bedford Institute of Oceanography, E.G.&G., National Marine Fisheries Service, U.S. Geological Survey, and Woods Hole Oceanographic Institution have conducted separate moored array experiments during 1974- 1980 to study various aspects of the regional circulation in the Gulf of Maine and adjacent Scotian and New England shelf and slope regions. The mean currents and current variances measured in these experiments are summarized here in tabular and graphical form, together with other information about each experiment. While there have been few measurements made in the interior of the Gulf of Maine, the map of mean subsurface currents demonstrate (a) a net inflow of Scotian shelf water past Cape Sable into the Gulf, (b) a net inflow of slope water through the Northeast Channel into the Gulf, (c) a partially closed anticyclonic circulation around Georges Bank, and (d) a net outflow of shelf water south of Nantucket from the Gulf of Maine into the New England shelf., Funding was provided by the Department of Interior, Bureau of Land Management under Contract AA 551-MU0-18 and by the National Science Foundation under Grant OCE 80-14941.

The Bedford Institute of Oceanography, E.G.&G., National Marine Fisheries Service, U.S. Geological Survey, and Woods Hole Oceanographic Institution have conducted separate moored array experiments during 1974- 1980 to study various aspects of the regional circulation in the Gulf of Maine and adjacent Scotian and New England shelf and slope regions. The mean currents and current variances measured in these experiments are summarized here in tabular and graphical form, together with other information about each experiment. While there have been few measurements made in the interior of the Gulf of Maine, the map of mean subsurface currents demonstrate (a) a net inflow of Scotian shelf water past Cape Sable into the Gulf, (b) a net inflow of slope water through the Northeast Channel into the Gulf, (c) a partially closed anticyclonic circulation around Georges Bank, and (d) a net outflow of shelf water south of Nantucket from the Gulf of Maine into the New England shelf., Funding was provided by the Department of Interior, Bureau of Land Management under Contract AA 551-MU0-18 and by the National Science Foundation under Grant OCE 80-14941.

This paper explores leadership and governance arrangements in seven developed health systems: Australia, England, Germany, the Netherlands, Norway, Sweden and Switzerland. It presents a cybernetic model of leadership and governance comprising three fundamental functions: priority setting, performance monitoring and accountability arrangements. The paper uses a structured survey to examine critically current arrangements in the seven countries. Approaches to leadership and governance vary substantially, and have to date been developed piecemeal and somewhat arbitrarily. Although there seems to be reasonable consensus on broad goals of the health system there is variation in approaches to setting priorities. Cost-effectiveness analysis is in widespread use as a basis for operational priority setting, but rarely plays a central role. Performance monitoring may be the domain where there is most convergence of thinking, although countries are at different stages of development. The third domain of accountability is where the greatest variation occurs, and where there is greatest uncertainty about the optimal approach. We conclude that a judicious mix of accountability mechanisms is likely to be appropriate in most settings, including market mechanisms, electoral processes, direct financial incentives, and professional oversight and control. The mechanisms should be aligned with the priority setting and monitoring processes.

Author Posting. © American Geophysical Union, 2003. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Journal of Geophysical Research 108, C11 (2003): 8000, doi:10.1029/2003JC002165., Support for the guest editors was provided by NSF grant OCE 02-27679 (RB), the Bedford Institute of Oceanography (PS), and NSF grant OCE 01-07946 (CL).

Author Posting. © American Geophysical Union, 2003. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Journal of Geophysical Research 108, C11 (2003): 8000, doi:10.1029/2003JC002165., Support for the guest editors was provided by NSF grant OCE 02-27679 (RB), the Bedford Institute of Oceanography (PS), and NSF grant OCE 01-07946 (CL).