The Role of Proactive Adaptation in International Climate Change Mitigation Agreements

This paper investigates the role of proactive adaptation in international mitigation coalition formation. Adaptation is introduced into a three stage cartel game of coalition formation. We analytically derive the optimal level of mitigation and proactive adaptation for the singletons and coalition members. We introduce the AD-STACO model which is constructed based on the STACO model, which is an applied three-stage cartel formation model with 12 heterogenous regions

TNF signalling drives expansion of bone marrow CD4+ T cells responsible for HSC exhaustion in experimental visceral leishmaniasis

Visceral leishmaniasis is associated with significant changes in hematological function but the mechanisms underlying these changes are largely unknown. In contrast to naïve mice, where most long-term hematopoietic stem cells (LT-HSCs; LSK CD150+ CD34- CD48- cells) in bone marrow (BM) are quiescent, we found that during Leishmania donovani infection most LT-HSCs had entered cell cycle. Loss of quiescence correlated with a reduced self-renewal capacity and functional exhaustion, as measured by serial transfer. Quiescent LT-HSCs were maintained in infected RAG2 KO mice, but lost following adoptive transfer of IFNγ-sufficient but not IFNγ-deficient CD4+ T cells. Using mixed BM chimeras, we established that IFNγ and TNF signalling pathways converge at the level of CD4+ T cells. Critically, intrinsic TNF signalling is required for the expansion and/or differentiation of pathogenic IFNγ+CD4+ T cells that promote the irreversible loss of BM function. These finding provide new insights into the pathogenic potential of CD4+ T cells that target hematopoietic function in leishmaniasis and perhaps other infectious diseases where TNF expression and BM dysfunction also occur simultaneously

Risk profiles and one-year outcomes of patients with newly diagnosed atrial fibrillation in India: Insights from the GARFIELD-AF Registry.

BACKGROUND: The Global Anticoagulant Registry in the FIELD-Atrial Fibrillation (GARFIELD-AF) is an ongoing prospective noninterventional registry, which is providing important information on the baseline characteristics, treatment patterns, and 1-year outcomes in patients with newly diagnosed non-valvular atrial fibrillation (NVAF). This report describes data from Indian patients recruited in this registry. METHODS AND RESULTS: A total of 52,014 patients with newly diagnosed AF were enrolled globally; of these, 1388 patients were recruited from 26 sites within India (2012-2016). In India, the mean age was 65.8 years at diagnosis of NVAF. Hypertension was the most prevalent risk factor for AF, present in 68.5% of patients from India and in 76.3% of patients globally (P < 0.001). Diabetes and coronary artery disease (CAD) were prevalent in 36.2% and 28.1% of patients as compared with global prevalence of 22.2% and 21.6%, respectively (P < 0.001 for both). Antiplatelet therapy was the most common antithrombotic treatment in India. With increasing stroke risk, however, patients were more likely to receive oral anticoagulant therapy [mainly vitamin K antagonist (VKA)], but average international normalized ratio (INR) was lower among Indian patients [median INR value 1.6 (interquartile range {IQR}: 1.3-2.3) versus 2.3 (IQR 1.8-2.8) (P < 0.001)]. Compared with other countries, patients from India had markedly higher rates of all-cause mortality [7.68 per 100 person-years (95% confidence interval 6.32-9.35) vs 4.34 (4.16-4.53), P < 0.0001], while rates of stroke/systemic embolism and major bleeding were lower after 1 year of follow-up. CONCLUSION: Compared to previously published registries from India, the GARFIELD-AF registry describes clinical profiles and outcomes in Indian patients with AF of a different etiology. The registry data show that compared to the rest of the world, Indian AF patients are younger in age and have more diabetes and CAD. Patients with a higher stroke risk are more likely to receive anticoagulation therapy with VKA but are underdosed compared with the global average in the GARFIELD-AF. CLINICAL TRIAL REGISTRATION-URL: http://www.clinicaltrials.gov. Unique identifier: NCT01090362

The economics of adaptation to climate change in integrated assessment models

WU thesis 499

How Harmful are Adaptation Restrictions

The dominant assumption in economic models of climate policy remains that adaptation will be implemented in an optimal manner. There are, however, several reasons why optimal levels of adaptation may not be attainable. This paper investigates the effects of suboptimal levels of adaptation, i.e. adaptation restrictions, on the composition and level of climate change costs and on welfare. Several adaptation restrictions are identified and then simulated in a revised DICE model, extended with adaptation (AD-DICE). We find that especially substantial over-investment in adaptation can be very harmful due to sharply increasing marginal adaptation costs. Furthermore the potential of mitigation to offset suboptimal adaptation is investigated. When adaptation is not possible at extreme levels of climate change, it is cost-effective to use more stringent mitigation policies in order to keep climate change limited, thereby making adaptation possible. Furthermore not adjusting the optimal level of mitigation to these adaptation restrictions may double the costs of adaptation restrictions, and thus in general it is very harmful to ignore existing restrictions on adaptation when devising (efficient) climate policie

The optimal paths of climate change mitigation and adaptation under certainty and uncertainty

Tradeoffs between climate change mitigation and adaptation policies are explored under both certainty and uncertainty with learning using a numerical two-period decision model. We first replicate a version of the Adaptation in DICE climate model (AD-DICE) (de Bruin et al., 2009), which modifies the Dynamic Integrated model of Climate and the Economy (DICE) (Nordhaus and Boyer, 2000) to incorporate climate change adaptation explicitly into the traditional optimisation framework. Our model is then extended to include uncertainty over a probability distribution of expected Climate Sensitivity (CS) values and the implications for optimal mitigation and adaptation levels are then explored. In the certainty model runs, the results of previous studies that incorporated adaptation into the portfolio of climate change responses are largely confirmed. Modelling an uncertain CS with the same expected value as under certainty leads to several insights: before learning occurs, optimal levels of both mitigation and adaptation are lower under uncertainty than under certainty; in this same early period, optimal mitigation and adaptation levels are most sensitive to the respective cost of each strategy, with the mitigation level more dependent on adaptation costs than vice versa; variance in CS – a parameter with long-term effects – affects mitigation levels more than adaptation levels

The Role of Proactive Adaptation in International Climate Change Mitigation Agreements

This paper investigates the role of proactive adaptation in international mitigation coalition formation. Adaptation is introduced into a three stage cartel game of coalition formation. We analytically derive the optimal level of mitigation and proactive adaptation for the singletons and coalition members. We introduce the AD-STACO model which is constructed based on the STACO model, which is an applied three-stage cartel formation model with 12 heterogenous regions