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Development and modelling of realistic retrofitted Nature-based Solution scenarios to reduce flood occurrence at the catchment scale.

ABSTRACT: Decentralized Nature-based Solutions such as Urban Green Infrastructures (UGI) are increasingly promoted to reduce flooding in urban areas. Many studies have shown the effectiveness of flood control of UGI at a plot or neighbourhood level. Modelling approaches that extrapolate their flood reducing impact to larger catchment scales are often based on a simplistic assumption of different percentages of UGI implementation. Additionally, such approaches typically do not consider the suitable space for UGI and potential implementation constraints. This study proposes a scenario development and modelling approach for a more realistic upscaling of UGI based on empirical insights from a representative neighbourhood. The results from this study, conducted in the metropolitan area of Costa Rica, show that upscaling the full potential for UGI could significantly reduce surface runoff, peak flows, and flood volumes. In particular, the permeable pavement has the highest potential for flood reducing in public space while cisterns perform best at the property level. These results can guide the formation of policies that promote UGI.

SUBMITTER: Chen V

PROVIDER: S-EPMC8249552 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundThe global burden of non-communicable diseases partly reflects growing exposure to ultra-processed food products (UPPs). These heavily marketed UPPs are cheap and convenient for consumers and profitable for manufacturers, but contain high levels of salt, fat and sugars. This study aimed to explore the potential mortality reduction associated with future policies for substantially reducing ultra-processed food intake in the UK.Methods and findingsWe obtained data from the UK Living Cost and Food Survey and from the National Diet and Nutrition Survey. By the NOVA food typology, all food items were categorized into three groups according to the extent of food processing: Group 1 describes unprocessed/minimally processed foods. Group 2 comprises processed culinary ingredients. Group 3 includes all processed or ultra-processed products. Using UK nutrient conversion tables, we estimated the energy and nutrient profile of each food group. We then used the IMPACT Food Policy model to estimate reductions in cardiovascular mortality from improved nutrient intakes reflecting shifts from processed or ultra-processed to unprocessed/minimally processed foods. We then conducted probabilistic sensitivity analyses using Monte Carlo simulation.ResultsApproximately 175,000 cardiovascular disease (CVD) deaths might be expected in 2030 if current mortality patterns persist. However, halving the intake of Group 3 (processed) foods could result in approximately 22,055 fewer CVD related deaths in 2030 (minimum estimate 10,705, maximum estimate 34,625). An ideal scenario in which salt and fat intakes are reduced to the low levels observed in Group 1 and 2 could lead to approximately 14,235 (minimum estimate 6,680, maximum estimate 22,525) fewer coronary deaths and approximately 7,820 (minimum estimate 4,025, maximum estimate 12,100) fewer stroke deaths, comprising almost 13% mortality reduction.ConclusionsThis study shows a substantial potential for reducing the cardiovascular disease burden through a healthier food system. It highlights the crucial importance of implementing healthier UK food policies.

Project description:ObjectiveA realistic seizure diary simulator is currently unavailable for many research needs, including clinical trial analysis and evaluation of seizure detection and seizure-forecasting tools. In recent years, important statistical features of seizure diaries have been characterized. These include (1) heterogeneity of individual seizure frequencies, (2) the relation between average seizure rate and standard deviation, (3) multiple risk cycles, (4) seizure clusters, and (5) limitations on inter-seizure intervals. The present study unifies these features into a single model.MethodsOur approach, Cyclic Heterogeneous Overdispersed Clustered Open-source L-relationship Adjustable Temporally limited E-diary Simulator (CHOCOLATES) is based on a hierarchical model centered on a gamma Poisson generator with several modifiers. This model accounts for the aforementioned statistical properties. The model was validated by simulating 10 000 randomized clinical trials (RCTs) of medication to compare with 23 historical RCTs. Metrics of 50% responder rate (RR50) and median percent change (MPC) were evaluated. We also used CHOCOLATES as input to a seizure-forecasting tool to test the flexibility of the model. We examined the area under the receiver-operating characteristic (ROC) curve (AUC) for test data with and without cycles and clusters.ResultsThe model recapitulated typical findings in 23 historical RCTs without the necessity of introducing an additional "placebo effect." The model produced the following RR50 values: placebo: 17 ± 4%; drug 38 ± 5%; and the following MPC values: placebo: 13 ± 6%; drug 40 ± 4%. These values are similar to historical data: for RR50: placebo, 21 ± 10%, drug: 43 ± 13%; and for MPC: placebo: 17 ± 10%, drug: 41 ± 11%. The seizure forecasts achieved an AUC of 0.68 with cycles and clusters, whereas without them the AUC was 0.51.SignificanceCHOCOLATES represents the most realistic seizure occurrence simulator to date, based on observations from thousands of patients in different contexts. This tool is open source and flexible, and can be used for many applications, including clinical trial simulation and testing of seizure-forecasting tools.

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Development and modelling of realistic retrofitted Nature-based Solution scenarios to reduce flood occurrence at the catchment scale.

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