Analysis of environmental factors influencing endemic cholera risks in sub-Saharan Africa.

The recurring cholera outbreaks in sub-Saharan Africa are of growing concern, especially considering the potential acceleration in the global trend of larger and more lethal cholera outbreaks due to the impacts of climate change. However, there is a scarcity of evidence-based research addressing the environmental and infrastructure factors that sustain cholera recurrence in Africa. This study adopts a statistical approach to investigate over two decades of endemic cholera outbreaks and their relationship with five environmental factors: water provision, sanitation provision, raising temperatures, increased rainfall and GDP. The analysis covers thirteen of the forty-two countries in the mainland sub-Saharan region, collectively representing one-third of the region's territory and half of its population. This breadth enables the findings to be generalised at a regional level. Results from all analyses consistently associate water provision with cholera reduction. The stratified model links increased water provision with a reduction in cholera risk that ranged from 4.2 % to 84.1 % among eight countries (out of 13 countries) as well as a reduction of such risk that ranged from 9.8 % to 68.9 % when there is increased sanitation provision, which was observed in nine countries (out of 13). These results indicate that the population's limited access to water and sanitation, as well as the rise in temperatures, are critical infrastructure and environmental factors contributing to endemic cholera and the heightened risk of outbreaks across the sub-Saharan region. Therefore, these are key areas for targeted interventions and cross-border collaboration to enhance resilience to outbreaks and lead to the end of endemic cholera in the region. However, it is important to interpret the results of this study with caution; hence, further investigation is recommended to conduct a more detailed analysis of the impact of infrastructure and environmental factors on reducing cholera risk.

Beyond flood hazard. Mapping the loss probability of pedestrians to improve risk estimation and communication.

The effective communication of flood hazard and risk is a necessary step to foster preparedness and resilience, hence reducing the detrimental impacts of flooding events. Classical flood maps, which show flow depth and velocity, have often proved to be incomprehensible to the majority of people. Some recent studies used color maps to convey the spatial distribution of diverse hazard indexes that, accounting for both water depth and velocity, are intended to communicate the hazard degree in a more intelligible way. It is first shown that these hazard indexes have some inherent limitations, as for example the implicit assumption of a linear relationship between flood hazard and flow velocity. As an alternative, we propose to map the loss probability (LP) of pedestrians exposed to floodwaters, which is a physics-based and data-consistent risk index accounting for both hazard and vulnerability. LP can be easily computed and allows for a sounder estimation and a more effective communication of flood risk to the general public.

Enhancing urban flood forecasting in drainage systems using dynamic ensemble-based data mining.

This study presents a novel approach for urban flood forecasting in drainage systems using a dynamic ensemble-based data mining model which has yet to be utilised properly in this context. The proposed method incorporates an event identification technique and rainfall feature extraction to develop weak learner data mining models. These models are then stacked to create a time-series ensemble model using a decision tree algorithm and confusion matrix-based blending method. The proposed model was compared to other commonly used ensemble models in a real-world urban drainage system in the UK. The results show that the proposed model achieves a higher hit rate compared to other benchmark models, with a hit rate of around 85% vs 70 % for the next 3 h of forecasting. Additionally, the proposed smart model can accurately classify various timesteps of flood or non-flood events without significant lag times, resulting in fewer false alarms, reduced unnecessary risk management actions, and lower costs in real-time early warning applications. The findings also demonstrate that two features, "antecedent precipitation history" and "seasonal time occurrence of rainfall," significantly enhance the accuracy of flood forecasting with a hit rate accuracy ranging from 60 % to 10 % for a lead time of 15 min to 3 h.

Using multi criteria decision analysis in a geographical information system framework to assess drought risk.

In this study we use the Mun river basin to demonstrate how a Multi Criteria Decision Analysis - Geographical Information Systems (MCDA-GIS) methodology can be used to assess drought risk. This paper not only provides a step forward in considering other elements such as land use change, climate within drought risk but also splits annual risk across three seasons (wet, cool and hot), previously not done. We also investigate how land use change, in the form of a/reforestation and changing crop varieties could potentially mitigate future risk. MCDA rankings from experts found that climatic factors such as rainfall, evapotranspiration and maximum temperature were the most significant. By splitting up the seasons we have been able to observe the temporal and spatial changes in drought risk at an increased detail, an important step in mitigating water security issue in the future. Results for cool months found an increased risk in the north and east (Surin, Si Sa Ket and Rio Et). With hot months finding increased risk in the east (Surin and Si Sa Ket especially) and west in Nakon Ratchasima. Whereas the wet season risk was greatest in the West (Nakon Ratchima, Khon Kean and Mara Sarakham). Differences in future land use scenarios compared to 2017 found that if current trends continued (BAU), the areas at risk from drought will increase. However, by changing land use in the form of a/reforestation (COB) or changing crop types (PRO), drought risk will decrease. Thus, the MCDA-GIS methodology serves as a great starting point, providing a high flexibility in data, meaning the methodology can readily applied to other case studies across the world.

Exploring the relationship between urban flood risk and resilience at a high-resolution grid cell scale.

The assessment of flood risk and resilience has become increasingly important in recent years for effective urban flood management. While flood resilience and risk are two distinct concepts with unique assessment metrics, there is lack of quantitative analysis and understanding of the relationship between them. This study aims to investigate this relationship at the grid cell level in urban areas. To assess flood resilience for high-resolution grid cells, this study proposes a performance-based flood resilience metric, which is calculated using the system performance curve based on flood duration and magnitude. Flood risk is calculated as the product of maximum flood depth and probability, considering multiple storm events. The case study of Waterloo in London, UK is analyzed using a two-dimensional cellular automata-based model CADDIES, which consists of 2.7 million grid cells (5 m × 5 m). The results indicate that over 2 % of grid cells have risk values exceeding 1. Furthermore, there is a 5 % difference in resilience values below 0.8 between the 200-year and 2000-year design rainfall events, specifically 4 % for the former and 9 % for the latter. Additionally, the results reveal a complex relationship between flood risk and resilience, though decreasing flood resilience generally leads to increasing flood risk. However, this relationship varies depending on the land cover type, with building, green land, and water body cells showing higher resilience for the same level of flood risk compared to other land uses such as roads and railways. Classifying urban areas into four categories, including high risk vs. low resilience, high risk vs. high resilience, low risk vs. low resilience, and low risk vs. high resilience, is crucial in identifying flood hotspots for intervention development. In conclusion, this study provides an in-depth understanding of the relationship between risk and resilience in urban flooding, which could help improve urban flood management. The proposed performance-based flood resilience metric and the findings from the case study of Waterloo in London could be valuable for decision-makers in developing effective flood management strategies in urban areas.

Dynamic population normalisation in wastewater-based epidemiology for improved understanding of the SARS-CoV-2 prevalence: a multi-site study.

Wastewater-based epidemiology (WBE) is a valuable tool for monitoring the circulation of COVID-19. However, while variations in population size are recognised as major sources of uncertainty, wastewater SARS-CoV-2 measurements are not routinely population-normalised. This paper aims to determine whether dynamic population normalisation significantly alters SARS-CoV-2 dynamics observed through wastewater monitoring, and whether it is beneficial or necessary to provide an understanding of COVID-19 epidemiology. Data from 394 sites in England are used, and normalisation is implemented based on ammoniacal nitrogen and orthophosphate concentrations. Raw and normalised wastewater SARS-CoV-2 metrics are evaluated at the site and spatially aggregated levels are compared against indicators of prevalence based on the Coronavirus Infection Survey and Test and Trace polymerase chain reaction test results. Normalisation is shown, on average, to have a limited impact on overall temporal trends. However, significant variability in the degree to which it affects local-level trends is observed. This is not evident from previous WBE studies focused on single sites and, critically, demonstrates that while the impact of normalisation on SARS-CoV-2 trends is small on average, this may not always be the case. When averaged across many sites, normalisation strengthens the correlation between wastewater SARS-CoV-2 data and prevalence indicators; however, confidence in the improvement is low.

Analysis of potential nature-based solutions for the Mun River Basin, Thailand.

Despite the growth in research and applications of nature-based solutions (NBS) within the literature, there are limited applications in South East Asia, moreover studies which quantitatively assess the impacts of NBS could have on hazard reduction are scarce. This paper addresses this gap by developing and validating MCDA-GIS analysis to map how potential nature strategies could mitigate flood hazard if applied within the Mun River Basin, Thailand. Through a literature review, the top three solutions for flood and drought hazards were found: wetlands, re/afforestation, and changing crop types. These strategies were reviewed and validated with a MCDA-GIS methodology, through land use change (LUC) maps to depict different future scenarios. The results found that flood hazard did decrease when NBS were implemented in the catchment, especially for A/Reforestation, and to a greater extent when a combination of NBS were applied. This article provides specific insights into the current gaps of NBS publications, specifically considering the case of the Mun River Basin, Thailand.

Mechanisms of cholera transmission via environment in India and Bangladesh: state of the science review.

OBJECTIVES: Cholera has a long history in India and Bangladesh, the region where six out of the past seven global pandemics have been seeded. The changing climate and growing population have led to global cholera cases remaining high despite a consistent improvement in the access to clean water and sanitation. We aim to provide a holistic overview of variables influencing environmental cholera transmission within the context of India and Bangladesh, with a focus on the mechanisms by which they act. CONTENT: We identified 56 relevant texts (Bangladesh n = 40, India n = 7, Other n = 5). The results of the review found that cholera transmission is associated with several socio-economic and environmental factors, each associated variable is suggested to have at least one mediating mechanism. Increases in ambient temperature and coastal sea surface temperature support cholera transmission via increases in plankton and a preference of Vibrio cholerae for warmer waters. Increased rainfall can potentially support or reduce transmission via several mechanisms. SUMMARY AND OUTLOOK: Common issues in the literature are co-variance of seasonal factors, limited access to high quality cholera data, high research bias towards research in Dhaka and Matlab (Bangladesh). A specific and detailed understanding of the relationship between SST and cholera incidence remains unclear.

Building knowledge of university campus population dynamics to enhance near-to-source sewage surveillance for SARS-CoV-2 detection.

Wastewater surveillance has been widely implemented for monitoring of SARS-CoV-2 during the global COVID-19 pandemic, and near-to-source monitoring is of particular interest for outbreak management in discrete populations. However, variation in population size poses a challenge to the triggering of public health interventions using wastewater SARS-CoV-2 concentrations. This is especially important for near-to-source sites that are subject to significant daily variability in upstream populations. Focusing on a university campus in England, this study investigates methods to account for variation in upstream populations at a site with highly transient footfall and provides a better understanding of the impact of variable populations on the SARS-CoV-2 trends provided by wastewater-based epidemiology. The potential for complementary data to help direct response activities within the near-to-source population is also explored, and potential concerns arising due to the presence of heavily diluted samples during wet weather are addressed. Using wastewater biomarkers, it is demonstrated that population normalisation can reveal significant differences between days where SARS-CoV-2 concentrations are very similar. Confidence in the trends identified is strongest when samples are collected during dry weather periods; however, wet weather samples can still provide valuable information. It is also shown that building-level occupancy estimates based on complementary data aid identification of potential sources of SARS-CoV-2 and can enable targeted actions to be taken to identify and manage potential sources of pathogen transmission in localised communities.

Performance assessment of coupled green-grey-blue systems for Sponge City construction.

In recent years, Sponge City has gained significant interests as a way of urban water management. The kernel of Sponge City is to develop a coupled green-grey-blue system which consists of green infrastructure at the source, grey infrastructure (i.e. drainage system) at the midway and receiving water bodies as the blue part at the terminal. However, the current approaches for assessing the performance of Sponge City construction are confined to green-grey systems and do not adequately reflect the effectiveness in runoff reduction and the impacts on receiving water bodies. This paper proposes an integrated assessment framework of coupled green-grey-blue systems on compliance of water quantity and quality control targets in Sponge City construction. Rainfall runoff and river system models are coupled to provide quantitative simulation evaluations of a number of indicators of land-based and river quality. A multi-criteria decision-making method, i.e., Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) is adopted to rank design alternatives and identify the optimal alternative for Sponge City construction. The effectiveness of this framework is demonstrated in a typical plain river network area of Suzhou, China. The results demonstrate that the performance of Sponge City strategies increases with large scale deployment under smaller rainfall events. In addition, though surface runoff has a dilution effect on the river water quality, the control of surface pollutants can play a significant role in the river water quality improvement. This framework can be applied to Sponge City projects to achieve the enhancement of urban water management.

Integrated 1D and 2D model for better assessing runoff quantity control of low impact development facilities on community scale.

This study proposes a modelling framework of integrated one-dimensional (1D) and two-dimensional (2D) hydrodynamic modelling to evaluate the effectiveness of sponge city construction at community scale. Through a case study in Zhuhai, we integrate Stormwater Management Model (SWMM) and Cellular Automata Dual-DraInagE Simulation (CADDIES) 2D model to analyze the rainfall-runoff process involving green infrastructures. SWMM is applied to analyze the change of surface runoff control effects before and after the implementation of sponge city low impact development (LID) facilities, and CADDIES is adopted to simulate the propagation of excess runoff on the surface. The results show that the LID facilities can effectively reduce the runoff volume of small and medium-sized rainfall events since the maximum runoff reduction rate is 94.4%. For long-term operation, the LID can capture 52.9% of annual rainfall volume and reduce annual runoff by 28.0%. However, the CADDIES 2D model simulations indicate that LID facilities have little effect on flood alleviation in specific regions under extreme rainfall conditions. In addition, we compared the modelling performance using four different terrain Digital Elevation Model (DEM) resolutions and found that 1 m terrain DEM resolution can produce comparable results to 0.25 m DEM with a fraction of computational time. We also find that the MIKE FLOOD model and the integrated model of SWMM and CADDIES 2D can obtain similar simulation results, the p-value = 0.09 which is >0.05, but SWMM-CADDIES integrated model is more suitable for small-scale simulation.

Assessing the knock-on effects of flooding on road transportation.

Flooding can affect every aspect of our lives and road transportation is not an exception. However, the interaction between floods and transportation was not investigated closely in the past. As transportation is the lifeline of any economy, it is essential to analyse potential dangers and threads that can lead to network capacity restraints. Considering the potential of flooding to affect large areas for long durations, disruptions to transportation can result in extensive knock-on effects. To examine how flooding can impact road transportation a novel methodology was developed into a software tool which integrates flood and traffic models. The flood is simulated with InfoWorks flood model and the traffic is represented by a detailed microscopic model (SUMO), which simulates individual vehicles and their interactions. Comparing normal (dry) traffic scenario with a flooded one yields the impacts of flooding on traffic (travelled distance and time, fuel consumption and CO2 emissions, maps of speed changes on the roads). The results indicated that delays persist long after the perturbations of flooding have subsided and that durations of trip delays are extremely long in some cases whereas distance impacts are typically negligible. Major knock-on effects on the system indicated that even not flooded critical infrastructure should be considered in flood analysis, as their services may be indirectly impacted by the flood conditions. Although substantial, the impacts proved challenging to monetise as time delays are spread around many drivers and some trips (such as delay to a doctor's trip to the hospital) can have significant, but intangible consequences.

Four new isoflavonoids from the stem bark of Erythrina variegata.

Bioassay-directed fractionation of the stem bark extract of Erythrina variegata L. has resulted in the isolation of three new isoflavones: 5,4'-dihydroxy-8-(3,3-dimethylallyl)-2''-methoxyisopropylfurano[4,5:6,7]isoflavone (1), 5,7,4'-trihydroxy-6-(3,3-dimethylallyloxiranylmethyl)isoflavone (2), 5,4'-dihydroxy-8-(3,3-dimethylallyl)-2''-hydroxymethyl-2''-methylpyrano[5,6:6,7]isoflavone (3) and a new isoflavanone, 5,4'-dihydroxy-2'-methoxy-8-(3,3-dimethylallyl)-2'',2''-dimethylpyrano[5,6:6,7]isoflavanone (4) together with seven known compounds, euchrenone b10 (5), isoerysenegalensein E (6), wighteone (7), laburnetin (8), lupiwighteone (9), erythrodiol (10), and oleanolic acid (11). The structures were determined on the basis of spectroscopic analyses and chemical evidence. The effect of these compounds on the proliferation of rat osteogenic sarcoma (UMR106) is also reported.

Synergetic inhibition of metal ions and genistein on alpha-glucosidase.

Inhibition of metal ions and synergetic inhibition of metal ions/genistein on alpha-glucosidase activity has been investigated. We have examined the inhibitory effect of Cu2+, Ni2+, Mg2+, Fe2+, Hg2+, Zn2+, Ca2+, Pb2+, Ag+, V5+, V4+ and Mn2+ ions. The results show that the nature of the inhibition was reversible, slow-binding, non-competitive, and the Ki values of some ions such as Cu2+, Ni2+ and Zn2+ range from 10(-5) to 10(-6) M. Moreover, synergetic inhibitory effect of metal ions and genistein on alpha-glucosidase were studied with kinetics method. It is concluded that the inhibitory effect was much greater when both of them were added to the reactant solution simultaneously than that they were added, respectively, which suggests that the inhibitors seem to bind to the different sites of alpha-glucosidase at the same time. Furthermore, the mechanism of the synergetic inhibition was examined by spectrophotometry.