BACKGROUND: Streptococcus pneumoniae, Haemophilus influenzae, and Neisseria meningitidis, which are typically transmitted via respiratory droplets, are leading causes of invasive diseases, including bacteraemic pneumonia and meningitis, and of secondary infections subsequent to post-viral respiratory disease. The aim of this study was to investigate the incidence of invasive disease due to these pathogens during the early months of the COVID-19 pandemic. METHODS: In this prospective analysis of surveillance data, laboratories in 26 countries and territories across six continents submitted data on cases of invasive disease due to S pneumoniae, H influenzae, and N meningitidis from Jan 1, 2018, to May, 31, 2020, as part of the Invasive Respiratory Infection Surveillance (IRIS) Initiative. Numbers of weekly cases in 2020 were compared with corresponding data for 2018 and 2019. Data for invasive disease due to Streptococcus agalactiae, a non-respiratory pathogen, were collected from nine laboratories for comparison. The stringency of COVID-19 containment measures was quantified using the Oxford COVID-19 Government Response Tracker. Changes in population movements were assessed using Google COVID-19 Community Mobility Reports. Interrupted time-series modelling quantified changes in the incidence of invasive disease due to S pneumoniae, H influenzae, and N meningitidis in 2020 relative to when containment measures were imposed. FINDINGS: 27 laboratories from 26 countries and territories submitted data to the IRIS Initiative for S pneumoniae (62 837 total cases), 24 laboratories from 24 countries submitted data for H influenzae (7796 total cases), and 21 laboratories from 21 countries submitted data for N meningitidis (5877 total cases). All countries and territories had experienced a significant and sustained reduction in invasive diseases due to S pneumoniae, H influenzae, and N meningitidis in early 2020 (Jan 1 to May 31, 2020), coinciding with the introduction of COVID-19 containment measures in each country. By contrast, no significant changes in the incidence of invasive S agalactiae infections were observed. Similar trends were observed across most countries and territories despite differing stringency in COVID-19 control policies. The incidence of reported S pneumoniae infections decreased by 68% at 4 weeks (incidence rate ratio 0·32 [95% CI 0·27-0·37]) and 82% at 8 weeks (0·18 [0·14-0·23]) following the week in which significant changes in population movements were recorded. INTERPRETATION: The introduction of COVID-19 containment policies and public information campaigns likely reduced transmission of S pneumoniae, H influenzae, and N meningitidis, leading to a significant reduction in life-threatening invasive diseases in many countries worldwide. FUNDING: Wellcome Trust (UK), Robert Koch Institute (Germany), Federal Ministry of Health (Germany), Pfizer, Merck, Health Protection Surveillance Centre (Ireland), SpID-Net project (Ireland), European Centre for Disease Prevention and Control (European Union), Horizon 2020 (European Commission), Ministry of Health (Poland), National Programme of Antibiotic Protection (Poland), Ministry of Science and Higher Education (Poland), Agencia de Salut Pública de Catalunya (Spain), Sant Joan de Deu Foundation (Spain), Knut and Alice Wallenberg Foundation (Sweden), Swedish Research Council (Sweden), Region Stockholm (Sweden), Federal Office of Public Health of Switzerland (Switzerland), and French Public Health Agency (France).
Background: Streptococcus pneumoniae, Haemophilus influenzae, and Neisseria meningitidis, which are typically transmitted via respiratory droplets, are leading causes of invasive diseases, including bacteraemic pneumonia and meningitis, and of secondary infections subsequent to post-viral respiratory disease. The aim of this study was to investigate the incidence of invasive disease due to these pathogens during the early months of the COVID-19 pandemic. Methods: In this prospective analysis of surveillance data, laboratories in 26 countries and territories across six continents submitted data on cases of invasive disease due to S pneumoniae, H influenzae, and N meningitidis from Jan 1, 2018, to May, 31, 2020, as part of the Invasive Respiratory Infection Surveillance (IRIS) Initiative. Numbers of weekly cases in 2020 were compared with corresponding data for 2018 and 2019. Data for invasive disease due to Streptococcus agalactiae, a non-respiratory pathogen, were collected from nine laboratories for comparison. The stringency of COVID-19 containment measures was quantified using the Oxford COVID-19 Government Response Tracker. Changes in population movements were assessed using Google COVID-19 Community Mobility Reports. Interrupted time-series modelling quantified changes in the incidence of invasive disease due to S pneumoniae, H influenzae, and N meningitidis in 2020 relative to when containment measures were imposed. Findings: 27 laboratories from 26 countries and territories submitted data to the IRIS Initiative for S pneumoniae (62 434 total cases), 24 laboratories from 24 countries submitted data for H influenzae (7796 total cases), and 21 laboratories from 21 countries submitted data for N meningitidis (5877 total cases). All countries and territories had experienced a significant and sustained reduction in invasive diseases due to S pneumoniae, H influenzae, and N meningitidis in early 2020 (Jan 1 to May 31, 2020), coinciding with the introduction of COVID-19 containment measures in each country. By contrast, no significant changes in the incidence of invasive S agalactiae infections were observed. Similar trends were observed across most countries and territories despite differing stringency in COVID-19 control policies. The incidence of reported S pneumoniae infections decreased by 68% at 4 weeks (incidence rate ratio 0·32 [95% CI 0·27–0·37]) and 82% at 8 weeks (0·18 [0·14–0·23]) following the week in which significant changes in population movements were recorded. Interpretation: The introduction of COVID-19 containment policies and public information campaigns likely reduced transmission of S pneumoniae, H influenzae, and N meningitidis, leading to a significant reduction in life-threatening invasive diseases in many countries worldwide. Funding: Wellcome Trust (UK), Robert Koch Institute (Germany), Federal Ministry of Health (Germany), Pfizer, Merck, Health Protection Surveillance Centre (Ireland), SpID-Net project (Ireland), European Centre for Disease Prevention and Control (European Union), Horizon 2020 (European Commission), Ministry of Health (Poland), National Programme of Antibiotic Protection (Poland), Ministry of Science and Higher Education (Poland), Agencia de Salut Pública de Catalunya (Spain), Sant Joan de Deu Foundation (Spain), Knut and Alice Wallenberg Foundation (Sweden), Swedish Research Council (Sweden), Region Stockholm (Sweden), Federal Office of Public Health of Switzerland (Switzerland), and French Public Health Agency (France).
Abstract Human mobility is strongly associated with the spread of SARS-CoV-2 via air travel on an international scale and with population mixing and the number of people moving between locations on a local scale. However, these conclusions are drawn mostly from observations in the context of the global north where international and domestic connectivity is heavily influenced by the air travel network; scenarios where land-based mobility can also dominate viral spread remain understudied. Furthermore, research on the effects of nonpharmaceutical interventions (NPIs) has mostly focused on national- or regional-scale implementations, leaving gaps in our understanding of the potential benefits of implementing NPIs at higher granularity. Here, we use Chile as a model to explore the role of human mobility on disease spread within the global south; the country implemented a systematic genomic surveillance program and NPIs at a very high spatial granularity. We combine viral genomic data, anonymized human mobility data from mobile phones and official records of international travelers entering the country to characterize the routes of importation of different variants, the relative contributions of airport and land border importations, and the real-time impact of the country's mobility network on the diffusion of SARS-CoV-2. The introduction of variants which are dominant in neighboring countries (and not detected through airport genomic surveillance) is predicted by land border crossings and not by air travelers, and the strength of connectivity between comunas (Chile's lowest administrative divisions) predicts the time of arrival of imported lineages to new locations. A higher stringency of local NPIs was also associated with fewer domestic viral importations. Our analysis sheds light on the drivers of emerging respiratory infectious disease spread outside of air travel and on the consequences of disrupting regular movement patterns at lower spatial scales.
INTRODUCTION: Ten 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. METHODS: We 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. RESULTS: Modeling 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. CONCLUSION: Total 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.
This paper develops a unified model of policy diffusion to analyze the speed of adoption of statewide lockdown policies within a federal system during the COVID-19 pandemic. The modified unified model was built to improve our understanding of policy diffusion in contexts where existing models fall short. The authors highlight three main policy diffusion channels: regional, vertical, and internal. The paper shows the empirical test of the model across US states and finds that vertical effects, such as higher approval ratings for President Donald Trump, as well as a comparatively high proportion of COVID-19 federal funding support, bear a strong positive association with the speed of statewide lockdown adoption policies. In addition, certain internal effects are also important - higher governor approval ratings are positively associated with the speed of statewide lockdown adoption policies, as are state and local spending, democratic state governments, and population awareness of the virus. However, other internal factors, such as the stringency of statewide lockdown policies and the relative proportion of COVID-19 deaths in a state, were minimally associated with the speed of lockdown policy adoption. Surprisingly, unlike past studies, horizontal regional effects did not play a significant role in the presented analysis - the speed of adoption of lockdown policies by neighboring states bears no association with the speed of policy adoption of statewide lockdowns. Overall, the results suggest a strong influence of political factors on the speed of statewide lockdown adoption policies in the US. ; Niniejszy artykuł przedstawia ujednolicony model dyfuzji polityki publicznej w celu analizy szybkości przyjmowania stanowych polityk lockdownu w systemie federalnym podczas pandemii COVID-19. Został tu zbudowany zmodyfikowany ujednolicony model w celu lepszego zrozumienia dyfuzji polityki publicznej w kontekstach, w których istniejące modele nie spełniają oczekiwań. Wyróżniono trzy główne kanały dyfuzji polityki ...
International audience ; Background: Streptococcus pneumoniae, Haemophilus influenzae, and Neisseria meningitidis, which are typically transmitted via respiratory droplets, are leading causes of invasive diseases, including bacteraemic pneumonia and meningitis, and of secondary infections subsequent to post-viral respiratory disease. The aim of this study was to investigate the incidence of invasive disease due to these pathogens during the early months of the COVID-19 pandemic.Methods: In this prospective analysis of surveillance data, laboratories in 26 countries and territories across six continents submitted data on cases of invasive disease due to S pneumoniae, H influenzae, and N meningitidis from Jan 1, 2018, to May, 31, 2020, as part of the Invasive Respiratory Infection Surveillance (IRIS) Initiative. Numbers of weekly cases in 2020 were compared with corresponding data for 2018 and 2019. Data for invasive disease due to Streptococcus agalactiae, a non-respiratory pathogen, were collected from nine laboratories for comparison. The stringency of COVID-19 containment measures was quantified using the Oxford COVID-19 Government Response Tracker. Changes in population movements were assessed using Google COVID-19 Community Mobility Reports. Interrupted time-series modelling quantified changes in the incidence of invasive disease due to S pneumoniae, H influenzae, and N meningitidis in 2020 relative to when containment measures were imposed.Findings: 27 laboratories from 26 countries and territories submitted data to the IRIS Initiative for S pneumoniae (62 837 total cases), 24 laboratories from 24 countries submitted data for H influenzae (7796 total cases), and 21 laboratories from 21 countries submitted data for N meningitidis (5877 total cases). All countries and territories had experienced a significant and sustained reduction in invasive diseases due to S pneumoniae, H influenzae, and N meningitidis in early 2020 (Jan 1 to May 31, 2020), coinciding with the introduction of COVID-19 containment measures ...
BACKGROUND: Streptococcus pneumoniae, Haemophilus influenzae, and Neisseria meningitidis, which are typically transmitted via respiratory droplets, are leading causes of invasive diseases, including bacteraemic pneumonia and meningitis, and of secondary infections subsequent to post-viral respiratory disease. The aim of this study was to investigate the incidence of invasive disease due to these pathogens during the early months of the COVID-19 pandemic. METHODS: In this prospective analysis of surveillance data, laboratories in 26 countries and territories across six continents submitted data on cases of invasive disease due to S pneumoniae, H influenzae, and N meningitidis from Jan 1, 2018, to May, 31, 2020, as part of the Invasive Respiratory Infection Surveillance (IRIS) Initiative. Numbers of weekly cases in 2020 were compared with corresponding data for 2018 and 2019. Data for invasive disease due to Streptococcus agalactiae, a non-respiratory pathogen, were collected from nine laboratories for comparison. The stringency of COVID-19 containment measures was quantified using the Oxford COVID-19 Government Response Tracker. Changes in population movements were assessed using Google COVID-19 Community Mobility Reports. Interrupted time-series modelling quantified changes in the incidence of invasive disease due to S pneumoniae, H influenzae, and N meningitidis in 2020 relative to when containment measures were imposed. FINDINGS: 27 laboratories from 26 countries and territories submitted data to the IRIS Initiative for S pneumoniae (62 837 total cases), 24 laboratories from 24 countries submitted data for H influenzae (7796 total cases), and 21 laboratories from 21 countries submitted data for N meningitidis (5877 total cases). All countries and territories had experienced a significant and sustained reduction in invasive diseases due to S pneumoniae, H influenzae, and N meningitidis in early 2020 (Jan 1 to May 31, 2020), coinciding with the introduction of COVID-19 containment measures in each country. By ...
Background Streptococcus pneumoniae, Haemophilus influenzae, and Neisseria meningitidis, which are typically transmitted via respiratory droplets, are leading causes of invasive diseases, including bacteraemic pneumonia and meningitis, and of secondary infections subsequent to post-viral respiratory disease. The aim of this study was to investigate the incidence of invasive disease due to these pathogens during the early months of the COVID-19 pandemic. Methods In this prospective analysis of surveillance data, laboratories in 26 countries and territories across six continents submitted data on cases of invasive disease due to S pneumoniae, H influenzae, and N meningitidis from Jan 1, 2018, to May, 31, 2020, as part of the Invasive Respiratory Infection Surveillance (IRIS) Initiative. Numbers of weekly cases in 2020 were compared with corresponding data for 2018 and 2019. Data for invasive disease due to Streptococcus agalactiae, a non-respiratory pathogen, were collected from nine laboratories for comparison. The stringency of COVID-19 containment measures was quantified using the Oxford COVID-19 Government Response Tracker. Changes in population movements were assessed using Google COVID-19 Community Mobility Reports. Interrupted time-series modelling quantified changes in the incidence of invasive disease due to S pneumoniae, H influenzae, and N meningitidis in 2020 relative to when containment measures were imposed. Findings 27 laboratories from 26 countries and territories submitted data to the IRIS Initiative for S pneumoniae (62 434 total cases), 24 laboratories from 24 countries submitted data for H influenzae (7796 total cases), and 21 laboratories from 21 countries submitted data for N meningitidis (5877 total cases). All countries and territories had experienced a significant and sustained reduction in invasive diseases due to S pneumoniae, H influenzae, and N meningitidis in early 2020 (Jan 1 to May 31, 2020), coinciding with the introduction of COVID-19 containment measures in each country. By ...
Background Streptococcus pneumoniae, Haemophilus influenzae, and Neisseria meningitidis, which are typically transmitted via respiratory droplets, are leading causes of invasive diseases, including bacteraemic pneumonia and meningitis, and of secondary infections subsequent to post-viral respiratory disease. The aim of this study was to investigate the incidence of invasive disease due to these pathogens during the early months of the COVID-19 pandemic. Methods In this prospective analysis of surveillance data, laboratories in 26 countries and territories across six continents submitted data on cases of invasive disease due to S pneumoniae, H influenzae, and N meningitidis from Jan 1, 2018, to May, 31, 2020, as part of the Invasive Respiratory Infection Surveillance (IRIS) Initiative. Numbers of weekly cases in 2020 were compared with corresponding data for 2018 and 2019. Data for invasive disease due to Streptococcus agalactiae, a non-respiratory pathogen, were collected from nine laboratories for comparison. The stringency of COVID-19 containment measures was quantified using the Oxford COVID-19 Government Response Tracker. Changes in population movements were assessed using Google COVID-19 Community Mobility Reports. Interrupted time-series modelling quantified changes in the incidence of invasive disease due to S pneumoniae, H influenzae, and N meningitidis in 2020 relative to when containment measures were imposed. Findings 27 laboratories from 26 countries and territories submitted data to the IRIS Initiative for S pneumoniae (62 434 total cases), 24 laboratories from 24 countries submitted data for H influenzae (7796 total cases), and 21 laboratories from 21 countries submitted data for N meningitidis (5877 total cases). All countries and territories had experienced a significant and sustained reduction in invasive diseases due to S pneumoniae, H influenzae, and N meningitidis in early 2020 (Jan 1 to May 31, 2020), coinciding with the introduction of COVID-19 containment measures in each country. By ...
The role of business as a forerunner of societal change might be in dispute, but the reality is that the main resource of society is the business enterprise. The observations and reflections presented in this article are especially oriented toward the use of and attitudes toward human resources and the unlimited reserves of human talent. Researchers within the disciplines of psychology and sociology often reveal a gap between different worldviews easily resulting in misunderstandings between their realms of research and application. Do these differing views point to the main reason for a relative inapplicability of research results from behavioral science to the working life? It might be pressure on the researchers in those sciences to be "scientific" in a way that better suits the natural sciences, although those traditional scientific ideas are also coming into question. In business, it is often necessary to adopt methods based on the fact that they feel reasonable. Such methods often prove effective later but may not be objectively proven in a way that meets scientific standards. Business functions in both modes, using "trial and error" as a source of knowledge as well as stringency and objective measures, reflecting the virtues of established science. If we look more closely at these phenomena, we find the same kind of conflict among people advocating, respectively, objective and nonobjective approaches to their discipline, whether in science or in business. Such conflicts consume energy, which would be better used in the understanding and integration of different "strategies of knowing" or, which is a point here, "ways of being." A number of questions that have emerged when models and theories have met with "real life" are proposed. It is assumed that consideration of these questions supports a transformation of psychological and sociological disciplines in their relationship with the emerging transformation of business.
AbstractObjectivesThe Covid‐19 pandemic changed the humanity life. Millions of deaths and infections that spread rapidly around the world made all countries take measures to stop the outbreaks and assume the enormous consequences that the Coronavirus is leaving behind. The challenge has been enormous; governments across the world have implemented a wide span of nonpharmaceutical interventions to mitigate the Coronavirus pandemic (SARS‐CoV‐2) and its consequences in economic terms. The aim of this article is to analyze the effects that different kinds of measures taken by Latin American governments had on the daily new infections. The countries analyzed were Argentina, Bolivia, Chile, Colombia, Costa Rica, El Salvador, Guatemala, Honduras, México, Panamá, Peru, Paraguay, Dominican Republic, Uruguay and Venezuela.MethodsA time series cross‐section analysis was performed, which allows studying the evolution of the number of daily cases over time and by country. The timeframe of this study was from the day the first case of coronavirus was registered in a country, until September 14, 2020. We used data from Covid‐19 Dashboard database of Johns Hopkins University and the Oxford Covid‐19 Government Response Tracker data set.ResultsThe Stringency Index did not have a significant influence at the beginning of the pandemic but turned out to be significant and inversely related to DNI during Phases 2 and 3. On the contrary, the Economic and the Sanitary Containment Index was not statistically significant for any of the phases. Furthermore, the level of wealthfare of a country, measured from its GDP per capita, exerts a substantive conditional influence on the management of the Covid‐19 crisis.ConclusionsThe scenarios have been changing and strategies had to change as well in order to be successful because they lose effectiveness and have increased social costs with time. Therefore, understanding the relative effectiveness of such measures had on the disease spreading during the first wave of the outbreak, could help governments to make more informed decisions about how to control future outbreaks of the Covid‐19 pandemic.
Der anthropogene Klimawandel gefährdet das Wohlergehen der Menschheit. Aus diesem Grund haben Politiker wiederholt das Ziel formuliert, die Erhöhung der mittleren globalen Temperatur auf weniger als 2◦C über dem vorindustriellen Wert zu begrenzen. Dazu müssen die globalen Treibhausgasemissionen nahezu vollständig vermieden werden. Da das heutige globale System zur Energienutzung auf fossilen Rohstoffen beruht, erfordert die Reduktion von Treibhausgasemissionen eine fundamentale Umgestaltung unseres Energiesystems. Diese Arbeit erforscht die ökonomischen Anforderungen und Folgen von ambitionierten Klimaschutzzielen. Sie beginnt mit einer allgemeinen Analyse der charakteristischen Dekarbonisierungsmuster des globalen Energiesystems. Diese identifiziert zwei besonders relevante Aspekte von Klimaschutzszenarien: die Nutzung von variablen erneuerbaren Energien (VRE) für Emissionsminderungen im Stromsektor, sowie die Schwierigkeit der Dekarbonisierung des Verkehrssektors. Eine vertiefende Analyse der beiden Solartechnologien Photovoltaik (PV) und solarthermische Kraftwerke (CSP) mit dem IAM REMIND bestätigt die fundamentale Rolle dieser VRE für den Stromsektor. Aufgrund der in der letzten Dekade erreichten Kostensenkung ist PV mittlerweile in Regionen mit hohem mittäglichem Strombedarf und starker Sonneneinstrahlung konkurrenzfähig zu anderen Kraftwerksneubauten. Die Abbildung der Systemintegrationskosten in REMIND hat einen deutlichen Einfluss auf den Wettbewerb zwischen PV und CSP: CSP mit thermischem Speicher und Wasserstoff-Co-Feuerung kann gesicherte Leistung bereitstellen und hat deshalb niedrigere Integrationskosten als PV, wodurch CSP bei hohen Anteilen an VRE konkurrenzfähig wird. Eine modellübergreifende Studie zum Verkehrssektor bestätigt, dass dieser nur schwach auf CO2-Preise unter 100€/t CO2 Höhe reagiert: Bis 2050 hinken relative Emissionsreduktionen im Verkehrssektor 10–30 Jahre hinter denen in anderen Sektoren her, und Flüssigtreibstoffe bleiben Hauptenergieträger. Auf längere Sicht bis 2100 stellt der Verkehrssektor jedoch kein unüberwindbares Hindernis für ambitionierte Klimaschutzziele dar: Bei höheren CO2-Preisen zeigen die Modelle deutliche Reduktionen der Verkehrsemissionen, entweder mittels Wasserstoff-Brennstoffzellen bzw. batteriebetriebene Elektromobile oder mittels Biotreibstoffen der zweiten Generation (möglicherweise mit CCS). Die abschließende Studie beschäftigt sich mit dem Zusammenhang zwischen der Strenge eines Klimaschutzziels und den damit verbundenen technischen und ökonomischen Anforderungen und Folgen. Unsere Ergebnisse zeigen, dass die Umgestaltung des globalen Energiesystems, die zur Einhaltung des 2◦C-Zieles mit einer Zweidrittel-Wahrscheinlichkeit notwendig ist, zu moderaten ökonomischen Kosten erreichbar ist. Dieses Resultat ist abhängig von der zeitnahen Umsetzung umfassender globaler Emisssionsminderungsmaßnahmen sowie der Verfügbarkeit verschiedener Technologien, die die Marktreife noch nicht gänzlich erreicht haben. Verzögert man die Einführung starker Klimaschutzpolitik, so erhöhen sich die Kosten substantiell, was das Erreichen ambitionierter Klimaschutzziele gefährdet. In dieser Arbeit wurde eine umfassende Analyse ambitionierter Klimaschutzszenarien und ihrer ökonomischen Anforderungen und Folgen durchgeführt, wobei ein besonderer Fokus auf der Nutzung erneuerbarer Energien einerseits und Emissionsreduktionen im Verkehr andererseits lag. Auf Basis umfangreicher eigener Modellrechnungen und globaler Modellvergleiche liefert die Arbeit entscheidende Erkenntnisse und Strategien für das Erreichen ambitionierter Klimaschutzziele. ; Anthropogenic climate change is threatening the welfare of mankind. Accordingly, policy makers have repeatedly stated the goal of slowing climate change and limiting the increase of global mean temperature to less than 2 °C above pre-industrial times (the so-called "two degree target"). Stabilizing the temperature requires drastic reductions of greenhouse gas (GHG) emissions to nearly zero. As the global system of energy supply currently relies on fossil fuels, reducing GHG emissions can only be achieved through a full-scale transformation of the energy system. This thesis investigates the economic requirements and implications of different scenarios that achieve stringent climate mitigation targets. It starts with the analysis of characteristic decarbonization patterns and identifies two particularly relevant aspects of mitigation scenarios: deployment of variable renewable energies (VRE) and decarbonization of the transport sector. After investigating these fields in detail, we turned towards one of the most relevant questions for policy makers and analyzed the trade-off between the stringency of a climate target and its economic requirements and implications. All analyses are based on the improvement, application, comparison, and discussion of large-scale IAMs. The novel "mitigation share" metric allowed us to identify the relevance of specific technology groups for mitigation and to improve our understanding of the decarbonization patterns of different energy subsectors. It turned out that the power sector is decarbonized first and reaches lowest emissions, while the transport sector is slowest to decarbonize. For the power sector, non-biomass renewable energies contribute most to emission reductions, while the transport sector strongly relies on liquid fuels and therefore requires biomass in combination with carbon capture and sequestration (CCS) to reduce emissions. An in-depth investigation of the solar power technologies photovoltaics (PV) and concentrating solar power (CSP) in REMIND confirms the dominant role of these variable renewable energies for the decarbonization of the power sector. Recent cost reductions have brought PV to cost-competitiveness in regions with high midday electricity demand and high solar irradiance. The representation of system integration costs in REMIND is found to have significant impact on the competition between PV and CSP in the model: the low integration requirements of CSP equipped with thermal storage and hydrogen co-firing make CSP competitive at high shares of variable renewable energies, which leads to substantial deployment of both PV and CSP in low stabilization scenarios. A cross-model study of transport sector decarbonization confirms the earlier finding that the transport sector is not very reactive to intermediate carbon price levels: Until 2050, transport decarbonization lags 10-30 years behind the decarbonization of other sectors, and liquid fuels dominate the transport sector. In the long term, however, transportation does not seem to be an insurmountable barrier to stringent climate targets: As the price signals on CO2 increase further, transport emissions can be reduced substantially - if either hydrogen fuel cells or electromobility open a route to low-carbon energy carriers, or second generation biofuels (possibly in combination with CCS) allow the use of liquid-based transport modes with low emissions. The last study takes up the fundamental question of this thesis and analyses the trade-off between the stringency of a climate target and the resulting techno-economic requirements and costs. We find that transforming the global energy-economy system to keep a two-thirds likelihood of limiting global warming to below 2 °C is achievable at moderate economic implications. This result is contingent on the near-term implementation of stringent global climate policies and full availability of several technologies that are still in the demonstration phase. Delaying stringent policies and extending the current period of fragmented and weak action will substantially increase mitigation costs, such that stringent climate targets might be pushed out of reach. Should the current weak climate policies be extended until 2030, the transitional mitigation costs for keeping the 2 °C target would increase three-fold compared to a world in which global cooperative action is decided on in 2015 and where first deep emission reductions are achieved in 2020. In case of technology limitations, the urgency of reaching a global climate agreement is even higher. In this thesis, we performed a comprehensive analysis of stringent mitigation scenarios and their economic implications, with a special focus on VRE deployment and transport decarbonization. Based on extensive modeling work and global cross-model analyses, this thesis provides crucial insights and identifies strategies for achieving stringent mitigation targets.
Climate change is one of the biggest issues facing the world. In recent years, several attempts have been made to define international strategies to cope with this threat. As a result, the current climate regime consists in the second commitment period of the Kyoto Protocol. In the meantime, Parties under the UNFCCC are negotiating for the definition and the approval of a new Agreement to be implemented in 2020. While in the first phase of negotiations the main objective was to get also reluctant Annex I countries to ratify the Kyoto Protocol whereas developing countries' concerns remained marginal, last years have been characterized by an increasing role of developing countries both in climate negotiations and in emission levels. Accordingly, this has exacerbated the debate about the CBDR Principle, considering how crucial active involvement of the developing part of the world is in climate actions. In view of this, the research project aims to investigate how the role of developing countries in the fight against climate change has been changing over time. The research consists of three papers. The first one investigates the role of developing countries in the Kyoto Protocol first commitment period (2008-2012) and, in particular, it is focused on the Clean Development Mechanism (CDM), the only instrument that directly involves them. Indeed, CDM projects are still far from being an effective development activity due to the uneven distribution of these projects in a few relatively well-off economies. One potential cause of this imbalance is analyzed in terms of the trade relationships between developed and developing countries. By applying a gravity model to a panel dataset, wellestablished export flows from developed economies towards developing countries are shown to explain why a large proportion of CDM projects are unevenly geographically distributed. This kind of lock-in effect regarding the CDM between developed and developing countries could be avoided by both enhancing the institutional framework in developing countries that host CDM projects and reinforcing compulsory rules for CDM destinations in the least-developed economies. The second paper analyzes the role of these countries in post 2012 negotiations, with particular emphasis on the role that their heterogeneity plays in the formation of coalitions and in the negotiating process. As it has become evident during the last COPs, developing countries have different expectations and concerns about climate change negotiations, reflecting huge differences with respect to their economic, political and human conditions. The emergence in climate negotiations of more differentiated positions compared with the traditional segmentation between developed and developing countries can contribute to explain the deadlock characterizing climate negotiations. By applying a cluster analysis, this paper aims to investigate the role played by heterogeneity in specific characteristics of developing countries in explaining divergent costs and benefits associated with alternative climate negotiation outcomes. By clustering developing countries according to their economic, geographic, environmental, energy and social characteristics, the paper presents some considerations on climate political economy strategies in these countries with respect to existing bargaining coalitions. In particular, cluster results suggest that developing countries are characterized by heterogeneous concerns and conflicting interests that can contribute to explaining the deadlock in climate negotiations. Indeed, in some circumstances, countries may advocate, at the same time, interests that are potentially contrasting, leading to the possibility that very fragile, variegate and unstable alliances will be formed, complicating the negotiation process and leading to a standstill. Given the heterogeneity of countries and their relative differences in costs and benefits related to climate actions, it is necessary to set out compensating schemes, such as the Green Climate Fund (GCF), for the most vulnerable countries in order to reach a successful agreement. Advancing from that point, the third paper addresses the debate about the GCF, especially regarding the resource allocation mechanisms that are still under discussion. A climate-economic computable general equilibrium (CGE) model is developed with the purpose of taking into account a monetary evaluation of climate change damage costs incurred by all countries as well as a mechanism describing the operationalization of the GCF. The purpose is twofold: i) to investigate costs and benefits of ongoing climate negotiations, with particular emphasis on developing countries, and ii) to examine the role of the GCF as a compensating measure in fostering the realization of a more efficient climate agreement. The model used to carry out the research is the GDynE, an energy-environmental version of GDyn developed by Markandya et al. (2015)1, resulting from merging GDyn with GTAP-E, according to Golub (2013)2. The main novelty of the model adopted here is represented by new and explicit equations that allow for the introduction of the climate damage as well as a more wellstructured description of the GCF allocation mechanisms. Results show that, despite the high costs associated to the implementation of a climate policy, developing countries would face even higher costs if they did not act. Thus, the first conclusion we can draw is that, if a costs-benefits criterion were the leading factor driving mitigation decisions, developing countries would gain from actively participating in mitigation policies. However, defining the stringency of the global mitigation target (450 ppm vs 550 ppm) as well as the best structure of compensating mechanisms (GCF) is more complicated. Indeed, climate change policies affect many aspects of a country's economy, such as welfare and GDP. Shifting from a policy evaluation criterion to another can lead to several and often contrasting conclusions. As for the role of GCF, two alternative resource allocation methods have been investigated. Simulation results give some elements to strengthen the discussion about the GCF rules on a quantitative basis. In fact, the preference for an allocation method over the other from the developing world depends on the effects that the different allocation between adaptation and mitigation produces on the whole economy. Given the several aspects affected by resources allocation, also in this case the preference of a country for an allocation method over the other strongly depends on the evaluation criteria. However, results confirm that, as stated in the second paper, the preference of a country for an allocation method is strongly influenced by its characteristics and needs. Therefore, a country-specific GCF should be designed in order to facilitate the negotiation process and to reach a more effective climate agreement.
This thesis analyses both theoretically and empirically some of the issues that emerge when applying environmental policies to the agricultural sector in a trade context. In a first part, Chapter II illustrates the possible leakage effects of environmental policies implemented unilaterally. A computable general equilibrium model is used to quantify the indirect global impacts of a greening of European agriculture through a large shift to organic farming. Organic farming is known for its local environmental benefits, especially on water and soil quality, biodiversity and greenhouse gas emissions. However, organic yields are on average 25% lower than those of conventional farming. We calibrate organic production technologies using micro-level data and find that using organic production techniques on 20% of the European area cultivated with maize, rapeseed, sunflower and wheat results in a large negative productivity shock. This shock affects global markets and induces production and demand displacements, unless the yield gap is reduced. The resulting land use changes are assessed, as well as the corresponding changes in greenhouse gas emissions, chemical inputs use and biodiversity. The negative indirect effects on the environment appear limited compared to the local benefits of adopting greener forms of agriculture in the EU. However, in the case of greenhouse gases, the indirect emissions more than offset the local benefits of organic agriculture. In the case of chemical pollution and biodiversity, results show that indirect effects deserve to be accounted for in life cycle analyses. These findings should not be used to point a finger on organic farming, a large variety of policies and consumption patterns have greater land use change impacts. Nevertheless, they rise some issues, especially on the need for more systematic sustainability assessments, even for environmental polices, the importance of research and development in organic farming to reduce yield gaps and of public policies to help to remove economic factors that could limit the increase of organic yields, such as the relative cost of production factors. In a second part, focus is on crop biodiversity, which is known to maintain agricultural productivity under a large range of environmental conditions. Interactions between crop biodiversity effects, environmental policies and trade are complex. Specialisation induced by trade, following comparative advantages, tends to reduce the number of crops cultivated in a given country and then reduces crop biodiversity. A decrease in crop biodiversity results in lower resilience to pest attacks. To face higher pest attacks, farmers use pesticides. But since pesticides harm environment and human health, governments regulate their use. In a free trade context, an environmental policy on pesticides can thus have a strategic aspect: allowing the use of more pesticides can lead to gain larger agricultural market shares. Chapter III represents these interactions in a Ricardian trade model. It shows that, because not in my backyard effects are larger than strategic impacts, the optimal environmental policy is more stringent under trade than under autarky. Furthermore, because of this stringency, production volatility is generally higher under trade. This could explain part of the background volatility observed on agricultural markets, which have been historically more volatile than those of manufactured products. Chapter IV empirically confirms the positive impact of crop biodiversity on agricultural production using a large dataset on South African agriculture. Developing a structural approach, it also analyses the role played by biodiversity on the exposure of farmers to production risks and downside risks. ; Cette thèse analyse à la fois théoriquement et empiriquement certaines des questions qui se posent lors de l'utilisation de politiques environnementales dans le secteur agricole, en situation de commerce. Dans une première partie, le chapitre II illustre les effets de fuite que peuvent engendrer des politiques environnementales mises en oeuvre unilatéralement. Un modèle d'équilibre général calculable est utilisé pour quantifier les impacts indirects sur l'environnement à l'échelle mondiale d'un accroissement des surfaces dédiées à l'agriculture biologique en Europe. L'agriculture biologique est connue pour ses bénéfices locaux sur l'environnement mais ses rendements sont inférieurs de 25% en moyenne à ceux de l'agriculture conventionnelle. Nous calibrons les technologies de production de l'agriculture biologique avec des données micro-fondées et trouvons qu'utiliser ces techniques sur 20% des surfaces européennes consacrées au maïs, colza, tournesol et blé conduit à un choc de productivité négatif. Ce choc a des conséquences sur les marchés mondiaux et induit des déplacements d'offre et de demande. Les changements d'utilisation des sols résultants sont évalués, ainsi que les changements en termes d'émissions de gaz à effet de serre, d'utilisation d'intrants et de biodiversité. Les effets indirects négatifs sur l'environnement semblent limités, sauf en ce qui concerne les émissions de gaz à effet de serre. Nous montrons également que les effets indirects concernant l'utilisation d'intrants et la biodiversité méritent d'être pris en compte dans les analyses de cycle de vie. Ces résultats ne doivent pas être utilisés pour pointer du doigt l'agriculture biologique, mais ils soulèvent quelques questions, en particulier sur la nécessité d'effectuer des analyses d'impact de façon plus systématique, y compris pour les politiques environnementales, et l'importance de la recherche et développement mais également des politiques publiques pour lever les obstacles techniques et économiques à l'augmentation des rendements en agriculture biologique. Dans une deuxième partie de la thèse, l'attention est portée sur la biodiversité des cultures, reconnue pour stabiliser la productivité agricole sous différentes conditions environnementales. Les interactions entre les effets de cette biodiversité, les politiques environnementales et le commerce sont complexes. La spécialisation induite par le commerce réduit la biodiversité en diminuant le nombre d'espèces cultivées. La biodiversité influe positivement sur les niveaux de production, entre autre, en améliorant la résistance aux ravageurs. Pour faire face à des attaques plus fréquentes, les agriculteurs utilisent des pesticides. Mais ces derniers ont des impacts négatifs sur l'environnement et la santé humaine, leur utilisation est donc réglementée. Une politique environnementale concernant les pesticides peut ainsi avoir un aspect stratégique: autoriser l'utilisation de plus de pesticides peut permettre de gagner en compétitivité. Le chapitre IV représente ces interactions dans un modèle ricardien de commerce. Il montre que, parce que les effets NIMBY sont plus importants que les impacts stratégiques, la politique environnementale est plus stricte en situation de commerce qu'en autarcie. De ce fait, la volatilité de la production agricole est généralement plus élevée en commerce. Cela pourrait en partie expliquer la volatilité de fond observée sur les marchés agricoles, historiquement plus volatiles que ceux des produits manufacturés. Le chapitre IV confirme empiriquement l'impact positif de la biodiversité sur la production agricole en utilisant une large base de données sur l'agriculture sud-africaine. En utilisant une approche structurelle, il analyse également les liens entre biodiversité et exposition des agriculteurs aux risques de production, en particulier ceux à la baisse.
