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INTRODUCTION Between 2020 and 2021, MSF’s social sciences team designed and supported implementation of qualitative assessments to better understand community-level outbreak responses and well-being in the context of Covid-19. Assessments were conducted in seven sites, specifically Nigeria, Sierra Leone, Chad, Iraq, Tajikistan, Syria, and Somaliland. Although a single protocol was designed and followed, each site was unique in terms of its setting (e.g. camp, conflict, urban, or rural), who implemented assessments (e.g. field epidemiologists, health promotion staff), timing of implementation (early phase of the pandemic versus late phase), and community involvement. Here we present a synthesis of the assessments to inform future public health responses. METHODS Synthesis involved secondary analysis of qualitative reports over five iterative phases. Phase 1 involved in-depth reading of each report, during which analytic annotation and note-taking took place. In Phase 2, each report was coded inductively. In Phase 3, codes were reviewed, defined, and clustered into initial categories and themes. Phase 4 involved reviewing and refining codes, categories, and themes, and establishing connections. In Phase 5, synthesis findings were organised and written up. The process was managed using the software ATLAS.ti. ETHICS This synthesis is an a posteriori analysis of secondary data. Ethics approval for primary data was granted by officials in Nigeria, Sierra Leone, Chad, Iraq, Tajikistan, Syria, and Somaliland and the MSF Ethics Review Board. RESULTS Overall 138, people participated in the assessments, of which 21 (15%) were women. Participants included health workers, community members, traditional healers, chiefs, young people, women’s leaders and local staff. Four themes were identified: 1) exacerbation of pre-existing vulnerabilities and inequalities; 2) disruption of coping mechanisms; 3) awareness of the risks of Covid-19; 4) community as a public health enabler. The pandemic was seen to magnify existing social inequalities and overall health burden. Public health measures to control the spread of Covid-19 often disrupted community coping mechanisms by causing fear of separation and practical challenges around compliance. Awareness of the risks of Covid-19 and understanding of prevention measures were high, with socio-economic costs of compliance relying on external funding and relief. A community led intervention for effective public health controls varied between sites, depending on previous outbreak experiences (e.g. Ebola and tuberculosis), and/or settings experiencing protracted conflict (e.g. Syria, and Iraq). CONCLUSION Our synthesis illustrates syndemic effects of the pandemic. From an operational perspective, there is a need to diversify humanitarian, social, and health interventions, and strengthen approaches to working with communities to identify how best to take forward public health measures in humanitarian settings. CONFLICTS OF INTEREST None declared.

We propose a general equilibrium framework that highlights the interaction of reserve requirements and a conventional monetary policy in a model that combines endogenous housing loan defaults and financial intermediation frictions due to the costs of enforcing contracts. We use the model to examine how the interaction of these policies affect (i) the credit and business cycle; (ii) the distribution of welfare between savers and borrowers; (iii) the overall welfare objectives when monetary and macroprudential policies are optimised together or individually. We find that models with an optimised reserve ratio rule are effective in reducing the sudden boom and bust of credit and the business cycle. We also find that there are distributive implications of the introduction of reserve ratio where borrowers gain at the expense of savers.

We propose a general equilibrium framework that highlights the interaction of reserve requirements and a conventional monetary policy in a model that combines endogenous housing loan defaults and financial intermediation frictions due to the costs of enforcing contracts. We use the model to examine how the interaction of these policies affect (i) the credit and business cycle; (ii) the distribution of welfare between savers and borrowers; (iii) the overall welfare objectives when monetary and macroprudential policies are optimised together or separately. We find that models with an optimised reserve ratio rule are effective in reducing the sudden boom and bust of credit and the business cycle. We also find that there are a distributive implications of the introduction of reserve ratio where borrowers gain at the expense of savers. However, there is no difference in the overall welfare results whether monetary and macroprudential policies are optimised together or separately.

We present alternative methods for calculating and interpreting the influence of exogenous shocks on historical episodes within the context of DSGE models. We show analytically why different methods for calculating shock decompositions can generate conflicting interpretations of the same historical episodes. We illustrate this point using an extended version of Drautzburg and Uhlig's (2015) model of the U.S. economy, focusing on the periods 1964-1966, 1979-1987, 2007-2008 and 2016-2018. We argue that the best method for analyzing particular episodes is one which isolates the influence of the shocks during the period under consideration and where the initial conditions represent the system's distance from steady state at the beginning of the episode.

Financial Inclusion - access to financial products by households and firms - is one of the main albeit challenging priorities, both for Advanced Economies (AEs) as well as Emerging Markets (EMs), even more so for the latter. Financial inclusion facilitates consumption smoothing, lowers income inequality, enables risk diversification, and tends to positively affect economic growth. Financial stability is another rising priority among policy makers. This is evident in the re-emergence of macroprudential policies after the global financial crisis, minimizing systemic risk, particularly risks associated with rapid credit growth. However, there are significant policy tradeoffs that could exist between both financial inclusion and financial stability, with mixed evidence on the link between the two objectives. Given the importance of macroprudential policies as a toolbox to achieve financial stability, we examine the impact of macroprudential policies on financial inclusion - a potential cause for financial instability if not carefully implemented. Using panel regressions for 67 countries over the period 2000-2014, our results point to mixed effects of macroprudential policies. The usage (and tightening) of some tools, such as the debt-to-income ratio, appear to reduce financial inclusion whereas others, such as the required reserve ratio (RRR), increase it. Specifically, both institutional quality and financial development appear to increase the effectiveness of macroprudential policies on financial inclusion. Institutional quality helps macroprudential policies boost financial inclusion, with mixed effects as a result of financial development, but the results are more significant when we include either institutional quality or financial development. This leads us to believe that macroprudential policies conditional on better institutional quality and financial development improves financial inclusion. This has important policy implications for financial stability.

How informative is a time series representation of a given vector of observables about the structural shocks and impulse response functions in a DSGE model? In this paper we refer to this econometrician’s problem as “E-invertibility” and consider the corresponding information problem of the agents in the assumed DGP, the DSGE model, which we refer to as “A-invertibility” We consider how the general nature of the agents’ signal extraction problem under imperfect information impacts on the econometrician’s problem of attempting to infer the nature of structural shocks and associated impulse responses from the data. We also examine a weaker condition of recoverability. A general conclusion is that validating a DSGE model by comparing its impulse response functions with those of a data VAR is more problematic when we drop the common assumption in the literature that agents have perfect information as an endowment. We develop measures of approximate fundamentalness for both perfect and imperfect information cases and illustrate our results using analytical and numerical examples.

In the next decade the pressures on ocean systems and the communities that rely on them will increase as multiple stressors of climate change, food security and human activities start to impact. Our ability to manage and sustain our oceans will depend on the data we collect and the information and knowledge generated. Much of the uptake of this knowledge will be outside the ocean domain, for example by policy makers, local Governments, custodians and other organizations, so it is imperative that we democratize or open the access and use of ocean data. This paper looks at how technologies, scoped by standards, best practice and communities of practice, can be deployed to change the way that ocean data is accessed, utilized, value added and transformed into information and knowledge. The current portal-download model which requires the user to know what data exists, where it is stored, in what format and with what processing, limits the uptake and use of ocean data. Using examples from a range of disciplines, a web services model of data and information flows is presented. A framework is described, including the systems, processes and human components, which delivers a radical rethink about the delivery of knowledge from ocean data. A series of vision statements describe parts of the future vision along with a series of recommendations about how this may be achieved. The paper recommends the development of virtual test-beds for end to end development of new data workflows and knowledge pathways. This supports the continued development, rationalization and uptake of standards, creates a platform around which a community of practice can be developed, promotes cross discipline engagement from ocean science through to ocean policy, allows for the commercial sector, including the informatics sector, to partner in delivering outcomes and provides a focus to leverage long term sustained funding. The next ten years will be ‘make or break’ for many ocean systems. The decadal challenge is to develop the governance and co-operative mechanisms to harness emerging information technology to deliver on the goal of generating the information and knowledge required to sustain oceans into the future.

We analyze the role of public and private financial frictions in the 2007–2008 economic crisis in the United States by extending the model of Drautzburg and Uhlig (2015) to eleven observable variables using data on all three interest rates in the model (policy, private and public). We also include a preference shock in the model, and present an alternative method for describing shock decompositions during and preceding the crisis designed to isolate the impact of the pre-crisis shocks. The estimated model produces an intuitive description of the evolution of the postwar U.S. economy overall and of the economic crisis at the end of the sample period. We find, in contrast to Drautzburg and Uhlig, that monetary and fiscal policy shocks played a significant role in mitigating the effects of the financial crisis.

How should a forward-looking policy maker conduct monetary policy when she has a finite set of models at her disposal, none of which are believed to be the true data generating process? In our approach, the policy makerfirst assigns weights to models based on relative forecasting performance rather than in-sample fit, consistent with her forward-looking objective. These weights are then used to solve a policy design prob-\ud lem that selects the optimized Taylor-type interest-rate rule that is robust to model uncertainty across a set of well-established DSGE models with and without financial frictions. We find that the choice of weights has a significant impact on the robust optimized rule which is more inertial and aggressive than either the non-robust single model counterparts or the optimal robust rule based on backward-looking weights as\ud in the common alternative Bayesian Model Averaging. Importantly, we show that a price-level rule has excellent welfare and robustness properties, and therefore should be viewed as a key instrument for policy makers facing uncertainty over the nature of\ud financial frictions.

The oceans play an important role in aspects of global sustainability, including climate change, food security and human health. Because of its vast dimensions, internal complexity, and limited accessibility, efficient monitoring and predicting of the ocean forms a collaborative effort of regional and global scale. A key requirement for ocean observing is the need to follow well-defined approaches. Summarized under “Ocean Best Practices” (OBP) are all aspects of ocean observing that require proper and agreed-on documentation, from manuals and standard operating procedures for sensors, strategies for structuring observing systems and associated products, to ethical and governance aspects when executing ocean observing. In Task 6.2 we have developed new tools, and organized workshops with outcomes of Best Practice manuals and scientific publications. The focus has been on improving accuracy of trace element measurements in seawater and also of marine omics analysis, and enhancing reliability, interoperability and quality of sensor measurements for dissolved oxygen, nutrients and carbonate chemistry measurements.

Importance Geographic atrophy (GA) secondary to age-related macular degeneration is a leading cause of visual disability in older individuals. A phase 2 trial suggested that lampalizumab, a selective complement factor D inhibitor, reduced the rate of GA enlargement, warranting phase 3 trials. Objective To assess the safety and efficacy of lampalizumab vs sham procedure on enlargement of GA. Design, Setting, and Participants Two identically designed phase 3 double-masked, randomized, sham-controlled clinical trials, Chroma and Spectri, enrolled participants from August 28, 2014, to October 6, 2016, at 275 sites in 23 countries. Participants were aged 50 years or older, with bilateral GA and no prior or active choroidal neovascularization in either eye and GA lesions in the study eye measuring 2.54 to 17.78 mm 2 with diffuse or banded fundus autofluorescence patterns. Interventions Participants were randomized 2:1:2:1 to receive 10 mg of intravitreous lampalizumab every 4 weeks, sham procedure every 4 weeks, 10 mg of lampalizumab every 6 weeks, or sham procedure every 6 weeks, through 96 weeks. Main Outcomes and Measures Safety and efficacy assessed as mean change from baseline in GA lesion area at week 48 from centrally read fundus autofluorescence images of the lampalizumab arms vs pooled sham arms, in the intent-to-treat population and by complement factor I–profile genetic biomarker. Results A total of 906 participants (553 women and 353 men; mean [SD] age, 78.1 [8.1] years) were enrolled in Chroma and 975 participants (578 women and 397 men; mean [SD] age, 77.9 [8.1] years) were enrolled in Spectri; 1733 of the 1881 participants (92.1%) completed the studies through 48 weeks. The adjusted mean increases in GA lesion area from baseline at week 48 were 1.93 to 2.09 mm 2 across all groups in both studies. Differences in adjusted mean change in GA lesion area (lampalizumab minus sham) were −0.02 mm 2 (95% CI, −0.21 to 0.16 mm 2 ; P = .80) for lampalizumab every 4 weeks in Chroma, 0.16 mm 2 (95% CI, 0.00-0.31 mm 2 ; P = .048) for lampalizumab every 4 weeks in Spectri, 0.05 mm 2 (95% CI, −0.13 to 0.24 mm 2 ; P = .59) for lampalizumab every 6 weeks in Chroma, and 0.09 mm 2 (95% CI, −0.07 to 0.24 mm 2 ; P = .27) for lampalizumab every 6 weeks in Spectri. No benefit of lampalizumab was observed across prespecified subgroups, including by complement factor I–profile biomarker. Endophthalmitis occurred after 5 of 12 447 injections (0.04%) or in 5 of 1252 treated participants (0.4%) through week 48. Conclusions and Relevance In Chroma and Spectri, the largest studies of GA conducted to date, lampalizumab did not reduce GA enlargement vs sham during 48 weeks of treatment. Results highlight the substantial and consistent enlargement of GA, at a mean of approximately 2 mm 2 per year. Trial Registration ClinicalTrials.gov Identifier:NCT02247479andNCT02247531

We construct, estimate and explore the monetary policy consequences of a New Keynesian (NK) behavioural model with bounded-rationality and heterogeneous agents. We radically depart from most existing models of this genre in our treatment of bounded rationality and learning. Instead of the usual Euler learning approach, we assume that agents are internally rational (IR) given their beliefs of aggregate states and prices. The model is inhabited by fully rational (RE) and IR agents where the latter use simple heuristic rules to forecast aggregate variables exogenous to their micro-environment. We find that IR results in an NK model with more persistence and a smaller policy space for rule parameters that induce stability and determinacy. In the most general form of the model, agents learn from their forecasting errors by observing and comparing them with those under RE making the composition of the two types endogenous. In a Bayesian estimation with fixed proportions of RE and IR agents and a general heuristic forecasting rule we find that a pure IR model fits the data better than the pure RE case. However, the latter with imperfect rather than the standard perfect information assumption outperforms IR (easily) and RE-IR composites (slightly), but second moment comparisons suggest that the RE-IR composite can match data better. Our findings suggest that Kalman-filtering learning with RE can match bounded-rationality in matching persistence seen in the data.

Saddlepath learning occurs when agents learn adaptively using a perceived law of motion that has the same form as the saddlepath relationship in rational expectations equilibrium. Under saddlepath learning, we obtain a completely general relationship between determinacy and e-stability, and generalise Minimum State Variable results previously derived only under full information. When the system is determinate, we show that a learning process based on the saddlepath is always e-stable. When the system is indeterminate, we find there is a unique MSV solution that is iteratively e-stable. However, in this case there is a sunspot solution that is learnable as well. We conclude by demonstrating that our results hold for any information set.

The complexity of marine installations for ocean observing systems has grown significantly in recent years. In a network consisting of tens, hundreds or thousands of marine instruments, manual configuration and integration becomes very challenging. Simplifying the integration process in existing or newly established observing systems would benefit system operators and is important for the broader application of different sensors. This article presents an approach for the automatic configuration and integration of sensors into an interoperable Sensor Web infrastructure. First, the sensor communication model, based on OGC's SensorML standard, is utilized. It serves as a generic driver mechanism since it enables the declarative and detailed description of a sensor's protocol. Finally, we present a data acquisition architecture based on the OGC PUCK protocol that enables storage and retrieval of the SensorML document from the sensor itself, and automatic integration of sensors into an interoperable Sensor Web infrastructure. Our approach adopts Efficient XML Interchange (EXI) as alternative serialization form of XML or JSON. It solves the bandwidth problem of XML and JSON.

Following on from Quint and Rabanal (2014), who find that coordination between the monetary authority and macroprudential regulators generates virtually identical results to non-coordination, we extend their model in a variety of ways. We address the zero lower bound for nominal interest rates, feedback of the macroprudential tool on the output growth rate, and the role of reserves. In all cases, we find that there is significant impact on the coefficients of the simple rule and on consumption-equivalent welfare effects.

We examine fiscal-monetary interactions in a New-Keynesian model with deep habits, distortionary taxes and a sovereign risk premium for government debt. Deep habits crucially affect the fiscal transmission mechanism in that these lead to a counter-cyclical mark-up, boosting the size of a demand-driven output expansion with important consequences for monetary and fiscal policy. We employ Bayesian estimates of the model to compute optimal monetary and fiscal policy first in `normal times' with debt starting at its steady state and then in a crisis period with a much higher initial debt-GDP ratio. Policy is conducted in terms of optimal commitment, time consistent and simple Taylor-type rules. Welfare calculations and impulse responses indicate that the ability of the simple rules to closely mimic the Ramsey optimal policy, observed in the literature with optimal monetary policy alone, is still a feature of optimal policy with fiscal instruments, but only with `passive' fiscal policy. For crisis management we find some support for slow consolidation with a more active role for tax increases rather than a decrease in government spending.

This paper examines the implications of imperfect information (II) for optimal monetary policy with a consistent set of informational assumptions for the modeller and the private sector an assumption we term the informational consistency. We use an estimated simple NK model from Levine et al. (2012), where the assumption of symmetric II significantly improves the fit of the model to US data to assess the welfare costs of II under commitment, discretion and simple Taylor-type rules. Our main results are: first, common to all information sets we find significant welfare gains from commitment only with a zero-lower bound constraint on the interest rate. Second, optimized rules take the form of a price level rule, or something very close across all information cases. Third, the combination of limited information and a lack of commitment can be particularly serious for welfare. At the same time we find that II with lags introduces a ‘tying ones hands’ effect on the policymaker that may improve welfare under discretion. Finally, the impulse response functions under our most extreme imperfect information assumption (output and inflation observed with a two-quarter delay) exhibit hump-shaped behaviour and the fiscal multiplier is significantly enhanced in this case.

GEOSS envisions a future wherein decisions and actions for the benefit of humankind are informed by coordinated, comprehensive and sustained Earth observations and information. Ultimately, this requires the ability to integrate information across scientific domains to address issues at regional and global levels. EuroGEOSS, an EC-sponsored FP7 project, has built an initial operating capability (IOC) in the three strategic areas of drought, forestry and biodiversity to facilitate and demonstrate multi-disciplinary applications. EuroGEOSS has implemented a brokering service that allows finding and accessing data from a wide range of standards and domainspecific practices including the use of a semantically rich querying capability. The paper presents the functionalities achieved by EuroGEOSS. The paper also presents the impact of advanced services through an assessment of societal benefits of the extended information availability.

International audience; Access to data on the web has become routine based upon open standards from IETF and W3C. Access to explicitly geospatial data is routinely done using data access standards from the OGC. Geoprocessing services on the web are now being developed. Processing of data must be done to apply or fuse the data to meet specific applications. Standards and implementations for processing of data on the web are just now becoming established. For geospatial data, the OGC has defined the Web Processing Service (WPS) interface standard. Now is a critical time to bring convergence to WPS profiles that make the web an easy to use geospatial computational service. Access to network accessible processing services is bringing geoprocessing to the cyberinfrastructure.

Using a two-bloc endogenous growth model calibrated to two generic sending and receiving countries of equal size, we assess the growth and welfare impact of world migration flows of different skill compositions. The sending country (East) has a lower total factor productivity and a lower endowment of skilled labour. Migration can induce two growth-enhancing effects: an efficiency effect from the more efficient use of labour in the receiving country (West) and a sectoral reallocation effect from a fall in the host country skilled–unskilled wage rates. Despite growth gains, there are both winners (migrants, the representative Western non-migrant household) and losers (the representative Eastern household remaining). Remittances can see the latter group joining the winners.