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Epidemic models are being used by governments to inform public health strategies to reduce the spread of SARS-CoV-2. They simulate potential scenarios by manipulating model parameters that control processes of disease transmission and recovery. However, the validity of these parameters is challenged by the uncertainty of the impact of public health interventions on disease transmission, and the forecasting accuracy of these models is rarely investigated during an outbreak. We fitted a stochastic transmission model on reported cases, recoveries and deaths associated with SARS-CoV-2 infection across 101 countries. The dynamics of disease transmission was represented in terms of the daily effective reproduction number ([Formula: see text] ). The relationship between public health interventions and [Formula: see text] was explored, firstly using a hierarchical clustering algorithm on initial [Formula: see text] patterns, and secondly computing the time-lagged cross correlation among the daily number of policies implemented, [Formula: see text] , and daily incidence counts in subsequent months. The impact of updating [Formula: see text] every time a prediction is made on the forecasting accuracy of the model was investigated. We identified 5 groups of countries with distinct transmission patterns during the first 6 months of the pandemic. Early adoption of social distancing measures and a shorter gap between interventions were associated with a reduction on the duration of outbreaks. The lagged correlation analysis revealed that increased policy volume was associated with lower future [Formula: see text] (75 days lag), while a lower [Formula: see text] was associated with lower future policy volume (102 days lag). Lastly, the outbreak prediction accuracy of the model using dynamically updated [Formula: see text] produced an average AUROC of 0.72 (0.708, 0.723) compared to 0.56 (0.555, 0.568) when [Formula: see text] was kept constant. Monitoring the evolution of [Formula: see text] during an epidemic is an important ...

During the early stage of the COVID-19 outbreak in Wuhan, the lockdown of the densely-populated metropolis caused panic and disorderly behavior among its population. Community governance systems (CGSs) were mobilized to lead community engagement to address the challenges and issues brought about by the sudden quarantine measures, still unprecedented in any part of the world during that time. This commentary aims to describe and analyze the roles of the CGSs, its implementation of culturally-tailored strategies and the performance of new functions as called for by the outbreak. We will introduce the community governance structure which has two parallel administrative units of government including the branches of the Communist Party of China (CPC). The pandemic showed that the roles of the CGSs evolved and may continue to be improved in the future. It is important to engage the community and to have community-based approaches in addressing issues brought about by lockdowns. This community experience in Wuhan provides important lessons for the rest of the world.

In the context of the turbulent international political situation, the uneven development of social development and the stagnation of economic development in recent years, China's promotion of foreign trade and economic transformation and upgrading and the "Belt and Road" strategy are necessary to pay more attention to the research and control of export credit risks, so policy exports is particularly urgent and important for credit insurance institutions to conduct research on credit risk control activities in support of the "going out" process of Chinese goods and capital. At the same time, unlike general commercial financial institutions, the starting point and foothold of credit risk management of policy financial institutions should be "maximizing social benefits" rather than the "maximum economic benefits" of traditional risk management theories. The target set of the risk management system of the export credit insurance institution is repositioned. Therefore, this paper attempts to sort out the research results of the existing policy-oriented export credit institutions, and from the perspective of comprehensive risk management, through the analysis of the characteristics and difficulties of the credit risk management of policy-oriented export credit insurance institutions, the company builds a comprehensive credit risk management system. The ideas and structure are discussed, and preliminary suggestions are put forward on the basis of this, in order to provide reference for the company to further improve the comprehensive risk management system.

Chapter 1. Recent Advances in the Emerging Field of Paleotempestology -- Chapter 2. Archival Evidence of Secular Changes in Georgia Hurricanes: 1750-2012 -- Chapter 3. Near-time Sea Surface Temperature and Tropical Cyclone Intensity in the Eastern North Pacific basin -- Chapter 4. Modern Tropical Cyclone Wind Observation and Analysis -- Chapter 5. Inland Tropical Cyclones and the "Brown Ocean" Concept -- Chapter 6. Typhoon/Hurricane Disaster Prediction and Prevention for Coastal, Offshore and Nuclear Power Plant Infrastructure -- Chapter 7. The use of Global Climate Models for Tropical Cyclone Risk Assessment -- Chapter 8. High Resolution Multi-Decadal Simulations of Tropical Cyclones -- Chapter 9, Analysis of Atlantic Tropical Cyclone Landfall Forecasts in Coupled GCMs on Seasonal and Decadal Timescales -- Chapter 10. Tropical Cyclone Rainfall Changes in a Warmer Climate.

While many published studies have explored the impact of spatial heterogeneity on land-use change, few have focused on regional differences in land-use transition rules caused by urban spatial structure. In this paper, we measured urban land-use diversity by developing self-adaptive kernel density estimation and entropy weight methods and determine the urban spatial structure (composed of urban regions, inner and outer urban-rural fringes, and a rural hinterland) by applying a spectral clustering method. Combining local neighborhood effects and environmental effects, the land-use transition rules of different types of regions were mined to construct a partitioned vector cellular automata (CA) model that zonally simulates urban land-use change. The proposed model was applied to the simulation of the land-use change process in Jiangyin City, China, from 2007 to 2017. The resulting simulation accuracy was higher than that of other well-accepted CA models that do not consider urban spatial structure, and the conventional neighborhood assimilation rule was found not to be applicable to the conversion of construction land. The results and findings demonstrate that the proposed model is an effective means for urban planners to simulate and analyze urban evolution processes of cities with urban spatial structures that fit a concentric circle model.

Traditional cell-based cellular automata (CA) models use a regular cellular grid to represent geographic space, and new approaches to CA models have explored the use of a vector representation of space instead of a regular grid to characterize urban space more realistically. However, less attention has been paid to modeling the interaction between the geospatial information and the irregular cells. To date, the majority of spatial boundaries have been created by individual agencies in an uncoordinated manner. As a consequence, the potential uses of the data collected for land-use change models are limited. In this paper, we propose a new vector-based CA model based on a new constrained irregular space representation using the theory of hierarchical spatial reasoning. For dividing the geographic space considering different items, first land patches are considered as the minimum division unit; then aggregation rules, including attribute, geometric and boundary barrier constraints, are defined; and finally different levels of spatial units are formed through land patches based on aggregation rules. The proposed model is used to simulate the land-use changes in Nanjing, Jiangsu Province, China. The performance validation and comparison illustrate the feasibility of the proposed space representation in a CA model. By using this model, it is expected that the use of the real spatial boundaries that are employed in urban planning could help provide a flexible paradigm to consider various drivers or constraints for realistically simulating land-use changes.