Dynamics of Vibrio cholerae in a Typical Tropical Lake and Estuarine System: Potential of Remote Sensing for Risk Mapping

Prognostication of zooplankton-driven cholera pathoepidemiological Dynamics: Novel Bayesian-regularized deep NARX neuroarchitecture

BACKGROUND

Cholera outbreaks pose significant health concerns, particularly through freshwater contamination through zooplankton serving as reservoirs for Vibrio Cholerae. Understanding these complex interactions within the aquatic ecosystem through mathematical modeling regimes may help us predict and prevent the spread of Cholera disease spread in affected regions.

METHOD

In this study, an innovative Bayesian regularized deep nonlinear autoregressive exogenous (BRDNARX) neural networks are employed to model the intricate dynamics of Zooplankton-Driven Cholera Disease Transmission (ZDCDT) system. The cholera epidemic propagation through freshwater contamination is uncovered with analysis on densities of phytoplankton, vibrio cholerae carrying zooplankton, human population vector and microbial pathogen vector populous in the marine biosphere. Synthetic data for the ZDCDT is presented for diverse simulations using a modified Adams-Bashforth-Moulton predictor corrector numerical scheme. Subsequently, these temporal data sequences are preprocessed for the novel BRDNARX computing paradigm with an exhaustive assessment on mean square error iterative convergence plots, error histogram charts, regression index reports, input-error crosscorrelation charts, error autocorrelation charts, and time-series response dynamics.

RESULTS AND CONCLUSIONS

Comparative absolute error analysis with reference numerical solution adheres to diminutive disparities of range 10-3 to 10-9. Finally, BRDNARX neurostructures are reconfigured for predictive analysis of ZDCDT system in terms of single and multi-step ahead predictors with mean square error outcomes that range from 10-9 to 10-11. This establishes the efficacy of BRDNARX in correctly adhering to the intricacies of the zooplankton-driven cholera pathoepidemiological dynamics with precise forward prognostication.

Vibrio sp. and Identification of the ctx Gene of Cholera Toxin in the Mandinga Coastal Lagoon, Veracruz, Mexico

Coastal lagoons have undergone changes due to anthropogenic activities, the presence of wastewater discharges, and unsustainable practices that alter water quality, favoring the presence of pathogenic microorganisms such as Vibrio. This study identified the presence of the genes for zinc metalloproteinase (HA) Vibrio sp. and choleric toxin (ctx) Vibrio cholerae, associated with the sources of contamination in the Mandinga Coastal Lagoon (MCL). During 2017, samplings were carried out in which sources of contamination associated with anthropogenic activities were identified. At the same time, water samples were collected from which DNA was extracted and the presence/absence of the HA and ctx genes was detected with a PCR analysis. The HA gene was identified in the three seasons of the year, while the ctx gene was only present in the dry and rainy seasons. The prevalence of both genes in the study area was independent of the presence of the pollution sources identified in the area. The absence of the ctx gene during the northern season is associated with the variability of the physicochemical parameters typical of the season.

Toxigenic Vibrio cholerae can cycle between environmental plastic waste and floodwater: Implications for environmental management of cholera

Globally, there has been a significant rise in cholera cases and deaths, with an increase in the number of low- and middle-income countries (LMICs) reporting outbreaks. In parallel, plastic pollution in LMICs is increasing, and has become a major constituent of urban dump sites. The surfaces of environmental plastic pollution can provide a habitat for complex microbial biofilm communities; this so-called 'plastisphere' can also include human pathogens. Under conditions simulating a peri-urban environmental waste pile, we determine whether toxigenic Vibrio cholerae (O1 classical; O1 El Tor; O139) can colonise and persist on plastic following a simulated flooding event. Toxigenic V. cholerae colonized and persisted on plastic and organic waste for at least 14 days before subsequent transfer to either fresh or brackish floodwater, where they can further persist at concentrations sufficient to cause human infection. Taken together, this study suggests that plastics in the environment can act as significant reservoirs for V. cholerae, whilst subsequent transfer to floodwaters demonstrates the potential for the wider dissemination of cholera. Further understanding of how diseases interact with plastic waste will be central for combating infection, educating communities, and diminishing the public health risk of plastics in the environment.

Distribution and antibiotic resistance of vibrio population in an urbanized tropical lake-the Vembanad-in the southwest coast of India

Among the diverse Vibrio spp. autochthonous to coastal ecosystems, V. cholerae, V. fluvialis, V. vulnificus and V. parahaemolyticus are pathogenic to humans. Increasing sea-surface temperature, sea-level rise and water-related disasters associated with climate change have been shown to influence the proliferation of these bacteria and change their geographic distribution. We investigated the spatio-temporal distribution of Vibrio spp. in a tropical lake for 1 year at a 20-day interval. The abundance of Vibrio spp. was much higher during the south-west monsoon in 2018, when the lake experienced a once-in-a-century flood. The distribution of Vibrio spp. was influenced by salinity (r = 0.3, p < 0.001), phosphate (r = 0.18, p < 0.01) and nitrite (r = 0.16, p < 0.02) in the water. We isolated 470 colonies of Vibrio-like organisms and 341 could be revived further and identified using 16S rRNA gene sequencing. Functional annotations showed that all the 16 Vibrio spp. found in the lake could grow in association with animals. More than 60% of the isolates had multiple antibiotic resistance (MAR) index greater than 0.5. All isolates were resistant to erythromycin and cefepime. The proliferation of multiple antibiotic-resistant Vibrio spp. is a threat to human health. Our observations suggest that the presence of a diverse range of Vibrio spp. is favoured by the low-saline conditions brought about by heavy precipitation. Furthermore, infections caused by contact with Vibrio-contaminated waters may be difficult to cure due to their multiple antibiotic resistances. Therefore, continuous monitoring of bacterial pollution in the lakes is essential, as is the generation of risk maps of vibrio-infested waters to avoid public contact with contaminated waters and associated disease outbreaks.

A new generation of real-time environmental monitoring systems to study the impact of El Niño on disease dynamics

Global warming is drastically altering weather patterns, accentuating the frequency and strength of global events such as the El Niño Southern Oscillation. This alteration is driving the spread of diseases sensitive to climate such as diarrheal diseases. Environmental monitoring through remote sensing, in combination with data from epidemiological surveillance programs, is facilitating the study of infectious disease dynamics associated with El Niño. This integrative approach can inform the development of strategies for mitigating the impact of these diseases on public health. Here, we discuss some of the achievements of this approach in the management, control, and prevention of infectious diseases linked to El Niño.

Assessment of ecosystem health of a micro-level Ramsar coastal zone in the Vembanad Lake, Kerala, India

Health of an ecosystem is very much important as we depend on its goods and services for our existence. Because of this, we need to continuously monitor its health for human benefit and for identifying areas for improvement of our natural systems. The present study tries to assess the condition of a coastal ecosystem within the Vembanad Lake, Kerala, India, using key water quality parameters at micro-level. Principal component analysis identified the minimum required water quality dataset for further analysis and was scored using linear scoring functions. The weighted additive method was used to integrate the individual scores to arrive at a final score representing the ecosystem health. Spline interpolation was applied to develop the ecosystem health map of the study area. Using this method, 35.8% area of the aquatic ecosystem studied was characterized as good, 32.2% as moderate, 26.2% as fair and 5.8% as poor. The assessment results can help the policymakers/managers to make appropriate decisions for the better management of the coastal ecosystems studied. Moreover, this methodology can be replicated for the assessment of coastal regions with similar ecosystem characteristics.

Layer-Averaged Water Temperature Sensing in a Lake by Acoustic Tomography with a Focus on the Inversion Stratification Mechanism

Continuous sensing of water parameters is of great importance to fluid dynamic progress study in oceans, coastal areas and inland waters. The acoustic tomography technique can perform water temperature field measurements horizontally and vertically using sound wave travel information. The layer-averaged water temperature can also be measured with the acoustic tomography method. However, investigations focusing on the stratified mechanism, which consists of stratification form and its influence on inversion error, are seldom performed. In this study, an acoustic tomography experiment was carried out in a reservoir along two vertical slices to observe the layer-averaged water temperature. Specifically, multi-path sound travel information is identified through ray tracing using high-precision topography data obtained via a ship-mounted ADCP during the experiment. Vertical slices between sound stations are divided into different layers to study layer division inversion methods in different preset types. The inversion method is used to calculate the average water temperature and inversion temperature error of every layer. Different layer methods are studied with a comparison of results. The layer division principle studied in this paper can be used for layer-averaged water temperature sensing with multi-path sound transmission information.

Continuous Sensing of Water Temperature in a Reservoir with Grid Inversion Method Based on Acoustic Tomography System

The continuous sensing of water parameters is of great importance to the study of dynamic processes in the ocean, coastal areas, and inland waters. Conventional fixed-point and ship-based observing systems cannot provide sufficient sampling of rapidly varying processes, especially for small-scale phenomena. Acoustic tomography can achieve the sensing of water parameter variations over time by continuously using sound wave propagation information. A multi-station acoustic tomography experiment was carried out in a reservoir with three sound stations for water temperature observation. Specifically, multi-path propagation sound waves were identified with ray tracing using high-precision topography data obtained with ship-mounted ADCP. A new grid inverse method is proposed in this paper for water temperature profiling along a vertical slice. The progression of water temperature variation in three vertical slices between acoustic stations was mapped by solving an inverse problem. The reliability and adaptability of the grid method developed in this research are verified by comparison with layer-averaged water temperature results. The grid method can be further developed for the 3D mapping of water parameters over time, especially in small-scale water areas, where sufficient multi-path propagation sound waves can be obtained.

Effect of Reduced Anthropogenic Activities on Water Quality in Lake Vembanad, India

The United Nation’s Sustainable Development Goal Life Below Water (SDG-14) aims to “conserve and sustainably use the oceans, seas, and marine resources for sustainable development”. Within SDG-14, targets 14.1 and 14.2 deal with marine pollution and the adverse impacts of human activities on aquatic systems. Here, we present a remote-sensing-based analysis of short-term changes in the Vembanad-Kol wetland system in the southwest of India. The region has experienced high levels of anthropogenic pressures, including from agriculture, industry, and tourism, leading to adverse ecological and socioeconomic impacts with consequences not only for achieving the targets set out in SDG-14, but also those related to water quality (SDG-6) and health (SDG-3). To move towards the sustainable management of coastal and aquatic ecosystems such as Lake Vembanad, it is important to understand how both natural and anthropogenic processes affect water quality. In 2020, a unique opportunity arose to study water quality in Lake Vembanad during a period when anthropogenic pressures were reduced due to a nationwide lockdown in response to the global pandemic caused by SARS-CoV-2 (25 March–31 May 2020). Using Sentinel-2 and Landsat-8 multi-spectral remote sensing and in situ observations to analyse changes in five different water quality indicators, we show that water quality improved in large areas of Lake Vembanad during the lockdown in 2020, especially in the more central and southern regions, as evidenced by a decrease in total suspended matter, turbidity, and the absorption by coloured dissolved organic matter, all leading to clearer waters as indicated by the Forel-Ule classification of water colour. Further analysis of longer term trends (2013–2020) showed that water quality has been improving over time in the more northern regions of Lake Vembanad independent of the lockdown. The improvement in water quality during the lockdown in April–May 2020 illustrates the importance of addressing anthropogenic activities for the sustainable management of coastal ecosystems and water resources.