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  1. Fulltext Scoping review of modelling studies assessing the impact of disruptions to essential health services during COVID-19
    Veettil SK, Schwerer L, Kategeaw W, Toth D, Samore MH, Hutubessy R, et al.
    BMJ Open, 2023 Sep 26;13(9):e071799.
    PMID: 37751952 DOI: 10.1136/bmjopen-2023-071799
    BACKGROUND: Studies assessing the indirect impact of COVID-19 using mathematical models have increased in recent years. This scoping review aims to identify modelling studies assessing the potential impact of disruptions to essential health services caused by COVID-19 and to summarise the characteristics of disruption and the models used to assess the disruptions.

    METHODS: Eligible studies were included if they used any models to assess the impact of COVID-19 disruptions on any health services. Articles published from January 2020 to December 2022 were identified from PubMed, Embase and CINAHL, using detailed searches with key concepts including COVID-19, modelling and healthcare disruptions. Two reviewers independently extracted the data in four domains. A descriptive analysis of the included studies was performed under the format of a narrative report.

    RESULTS: This scoping review has identified a total of 52 modelling studies that employed several models (n=116) to assess the potential impact of disruptions to essential health services. The majority of the models were simulation models (n=86; 74.1%). Studies covered a wide range of health conditions from infectious diseases to non-communicable diseases. COVID-19 has been reported to disrupt supply of health services, demand for health services and social change affecting factors that influence health. The most common outcomes reported in the studies were clinical outcomes such as mortality and morbidity. Twenty-five studies modelled various mitigation strategies; maintaining critical services by ensuring resources and access to services are found to be a priority for reducing the overall impact.

    CONCLUSION: A number of models were used to assess the potential impact of disruptions to essential health services on various outcomes. There is a need for collaboration among stakeholders to enhance the usefulness of any modelling. Future studies should consider disparity issues for more comprehensive findings that could ultimately facilitate policy decision-making to maximise benefits to all.

    Matched MeSH terms: Models, Theoretical
  2. Anthropogenic climate change exacerbates the risk of successive flood-heat extremes: Multi-model global projections based on the Inter-Sectoral Impact Model Intercomparison Project
    Zhou J, Wu C, Yeh PJ, Ju J, Zhong L, Wang S, et al.
    Sci Total Environ, 2023 Sep 01;889:164274.
    PMID: 37209749 DOI: 10.1016/j.scitotenv.2023.164274
    The successive flood-heat extreme (SFHE) event, which threatens the securities of human health, economy, and building environment, has attracted extensive research attention recently. However, the potential changes in SFHE characteristics and the global population exposure to SFHE under anthropogenic warming remain unclear. Here, we present a global-scale evaluation of the projected changes and uncertainties in SFHE characteristics (frequency, intensity, duration, land exposure) and population exposure under the Representative Concentration Pathway (RCP) 2.6 and 6.0 scenarios, based on the multi-model ensembles (five global water models forced by four global climate models) within the Inter-Sectoral Impact Model Intercomparison Project 2b framework. The results reveal that, relative to the 1970-1999 baseline period, the SFHE frequency is projected to increase nearly globally by the end of this century, especially in the Qinghai-Tibet Plateau (>20 events/30-year) and the tropical regions (e.g., northern South America, central Africa, and southeastern Asia, >15 events/30-year). The projected higher SFHE frequency is generally accompanied by a larger model uncertainty. By the end of this century, the SFHE land exposure is expected to increase by 12 % (20 %) under RCP2.6 (RCP6.0), and the intervals between flood and heatwave in SFHE tend to decrease by up to 3 days under both RCPs, implying the more intermittent SFHE occurrence under future warming. The SFHE events will lead to the higher population exposure in the Indian Peninsula and central Africa (<10 million person-days) and eastern Asia (<5 million person-days) due to the higher population density and the longer SFHE duration. Partial correlation analysis indicates that the contribution of flood to the SFHE frequency is greater than that of heatwave for most global regions, but the SFHE frequency is dominated by the heatwave in northern North America and northern Asia.
    Matched MeSH terms: Models, Theoretical
  3. Appraisal of data-driven techniques for predicting short-term streamflow in tropical catchment
    Yeoh KL, Puay HT, Abdullah R, Abd Manan TS
    Water Sci Technol, 2023 Jul;88(1):75-91.
    PMID: 37452535 DOI: 10.2166/wst.2023.193
    Short-term streamflow prediction is essential for managing flood early warning and water resources systems. Although numerical models are widely used for this purpose, they require various types of data and experience to operate the model and often tedious calibration processes. Under the digital revolution, the application of data-driven approaches to predict streamflow has increased in recent decades. In this work, multiple linear regression (MLR) and random forest (RF) models with three different input combinations are developed and assessed for multi-step ahead short-term streamflow predictions, using 14 years of hydrological datasets from the Kulim River catchment, Malaysia. Introducing more precedent streamflow events as predictor improves the performance of these data-driven models, especially in predicting peak streamflow during the high-flow event. The RF model (Nash-Sutcliffe efficiency (NSE): 0.599-0.962) outperforms the MLR model (NSE: 0.584-0.963) in terms of overall prediction accuracy. However, with the increasing lead-time length, the models' overall prediction accuracy on the arrival time and magnitude of peak streamflow decrease. These findings demonstrate the potential of decision tree-based models, such as RF, for short-term streamflow prediction and offer insights into enhancing the accuracy of these data-driven models.
    Matched MeSH terms: Models, Theoretical*
  4. A new meta-heuristic optimization-based MPPT control technique for green energy harvesting from photovoltaic systems under different atmospheric conditions
    Kishore DJK, Mohamed MR, Sudhakar K, Peddakapu K
    Environ Sci Pollut Res Int, 2023 Jul;30(35):84167-84182.
    PMID: 37358770 DOI: 10.1007/s11356-023-28248-8
    At present, a photovoltaic (PV) system takes responsibility to reduce the risk of global warming and generate electricity. However, the PV system faces numerous problems to track global maximum peak power (GMPP) owing to the nonlinear nature of the environment especially due to partial shading conditions (PSC). To solve these difficulties, previous researchers have utilized various conventional methods for investigations. Nevertheless, these methods have oscillations around the GMPP. Hence, a new metaheuristic method such as an opposition-based equilibrium optimizer (OBEO) algorithm is used in this work for mitigating the oscillations around GMPP. To find the effectiveness of the proposed method, it can be evaluated with other methods such as SSA, GWO, and P&O. As per the simulation outcome, the proposed OBEO method provides maximum efficiency against all other methods. The efficiency for the proposed method under dynamic PSC is 95.09% in 0.16 s, similarly, 96.17% for uniform PSC and 86.25% for complex PSC.
    Matched MeSH terms: Models, Theoretical*
  5. Prediction of outcomes in traumatic brain injury: The IMPACT and CRASH prognostic models in a single neurosurgical center, Malaysia
    Abdullah JM, Idris Z, Ghani AR, Lim MS
    J Neurosurg Sci, 2023 Jun;67(3):367-373.
    PMID: 33709663 DOI: 10.23736/S0390-5616.21.05249-8
    BACKGROUND: Traumatic brain injury (TBI) has recently become a major concern for public health care and a socioeconomic burden internationally. Prognostic models are mathematical models developed from specific populations which are used to predict the mortality and unfavorable outcomes especially in trauma centers. Hence, we formulate a study to perform an external validation of the IMPACT and CRASH prognostic models; the CRASH model to predict 14-day mortality and 6-month unfavorable outcome and the IMPACT model to estimate 6-month mortality and unfavorable outcome in a single center cohort of TBI patients in Malaysia.

    METHODS: All patients with traumatic brain injury (mild, moderate, and severe) who were admitted to Queen Elizabeth Hospital from November 1, 2017, to January 31, 2019, were prospectively analyzed through a data collection sheet. The discriminatory power of the models was assessed as area under the receiver operating characteristic curve and calibration was assessed using the Hosmer-Lemeshow (H-L) goodness-of-fit test and Cox calibration regression analysis.

    RESULTS: We analyzed 281 patients with significant TBI treated in a single neurosurgical center in Malaysia over a 2-year period. The overall observed 14-day mortality was 9.6%, a 6-month unfavorable outcome of 23.5%, and a 6-month mortality of 13.2%. Overall, both the CRASH and IMPACT models showed good discrimination with AUCs ranging from 0.88 to 0.94 and both models calibrating satisfactorily H-L GoF P>0.05 and calibration slopes >1.0 although IMPACT seemed to be slightly more superior compared to the CRASH model.

    CONCLUSIONS: The CRASH and IMPACT prognostic models displayed satisfactory overall performance in our cohort of TBI patients, but further investigations on factors contributing to TBI outcomes and continuous updating on both models remain crucial.

    Matched MeSH terms: Models, Theoretical
  6. Technical-economic framework for designing of water pumping system based on photovoltaic clean energy with water storage for drinking application
    Naderipour A, Nowdeh SA, Babanezhad M, Najmi ES, Kamyab H, Abdul-Malek Z
    Environ Sci Pollut Res Int, 2023 Jun;30(28):71754-71765.
    PMID: 34499303 DOI: 10.1007/s11356-021-16342-8
    In this paper, the technical-economic framework for designing of water pumping system based on photovoltaic clean energy with water tank storage is presented to supply drinking water of customers for remote areas. The objective function is to minimize the net present cost (NPC) (as economic index) including initial investment costs, maintenance, and replacement costs, and reliability constraint is defined as customer's water not supplied probability (CWNSP) as technical index. A meta-heuristic intelligent water drops algorithm (IWDA) is proposed to optimize the solar water pumping system considering NPC and CWNSP with high accuracy and speed of optimization in achieving the global solution. The simulation results show that the proposed method is capable of responding to customer's water demand by optimally sizing components and water storage tank based on IWDA which is inspired based on flowing the water drops in rivers by achieving the lowest cost with optimal reliability. The NPC of the system with CWNSP equal to 3.17 % is obtained 0.24 M$ for 6-m-high water extraction. The results showed that with increasing the water extraction height, the NPC increased, and the reliability also weakened. Moreover, the superiority of the IWDA is confirmed compared with particle swarm optimization (PSO) in designing a water pumping system with the lowest NPC.
    Matched MeSH terms: Models, Theoretical*
  7. Synthesis, DFT study, theoretical and experimental spectroscopy of fatty amides based on extra-virgin olive oil and their antibacterial activity
    Farhan N, Rageh Al-Maleki A, Ataei S, Muhamad Sarih N, Yahya R
    Bioorg Chem, 2023 Jun;135:106511.
    PMID: 37027951 DOI: 10.1016/j.bioorg.2023.106511
    Medication products from natural materials are preferred due to their minimal side effects. Extra-virgin olive oil (EVOO) is a highly acclaimed Mediterranean diet and a common source of lipids that lowers morbidity and disease severity. This study synthesised two fatty amides from EVOO: hydroxamic fatty acids (FHA) and fatty hydrazide hydrate (FHH). The Density Functional Theory (DFT) was applied to quantum mechanics computation. Nuclear magnetic resonance (NMR), Fourier transforms infrared (FTIR), and element analysis were used to characterise fatty amides. Likewise, the minimum inhibitory concentration (MIC) and timing kill assay were determined. The results revealed that 82 % for FHA and 80 % for FHH conversion were achieved. The amidation reagent/EVOO ratio (mmol: mmol) was 7:1, using the reaction time of 12 h and hexane as an organic solvent. The results further revealed that fatty amides have high antibacterial activity with low concentration at 0.04 μg/mL during eight h of FHA and 0.3 μg/mL during ten h of FHH. This research inferred that FHA and FHH could provide an alternative and effective therapeutic strategy for bacterial diseases. Current findings could provide the basis for the modernisation/introduction of novel and more effective antibacterial drugs derived from natural products.
    Matched MeSH terms: Models, Theoretical*
  8. A novel mechanism measurement of predator interference in predator-prey models
    Alebraheem J, Abu-Hassan Y
    J Math Biol, 2023 Apr 27;86(5):84.
    PMID: 37103566 DOI: 10.1007/s00285-023-01914-8
    A characteristic of ecosystems is the existence of manifold of independencies which are highly complex. Various mathematical models have made considerable contributions in gaining a better understanding of the predator-prey interactions. The main components of any predator-prey models are, firstly, how the different population classes grow and secondly, how the prey and predator interacts. In this paper, the two populations' growth rates obey the logistic law and the carrying capacity of the predator depends on the available number of prey are considered. Our aim is to clarify the relationship between models and Holling types functional and numerical responses in order to gain insights into predator interferences and to answer an important question how competition is carried out. We consider a predator-prey model and a two-predator one-prey model to explain the idea. The novel approach is explained for the mechanism measurement of predator interference through depending on numerical response. Our approach gives good correspondence between an important real data and computer simulations.
    Matched MeSH terms: Models, Theoretical
  9. Fulltext Unsteady natural convection flow of blood Casson nanofluid (Au) in a cylinder: nano-cryosurgery applications
    Azmi WFW, Mohamad AQ, Jiann LY, Shafie S
    Sci Rep, 2023 Apr 09;13(1):5799.
    PMID: 37032402 DOI: 10.1038/s41598-023-30129-6
    Nano-cryosurgery is one of the effective ways to treat cancerous cells with minimum harm to healthy adjacent cells. Clinical experimental research consumes time and cost. Thus, developing a mathematical simulation model is useful for time and cost-saving, especially in designing the experiment. Investigating the Casson nanofluid's unsteady flow in an artery with the convective effect is the goal of the current investigation. The nanofluid is considered to flow in the blood arteries. Therefore, the slip velocity effect is concerned. Blood is a base fluid with gold (Au) nanoparticles dispersed in the base fluid. The resultant governing equations are solved by utilising the Laplace transform regarding the time and the finite Hankel transform regarding the radial coordinate. The resulting analytical answers for velocity and temperature are then displayed and visually described. It is found that the temperature enhancement occurred by arising nanoparticles volume fraction and time parameter. The blood velocity increases as the slip velocity, time parameter, thermal Grashof number, and nanoparticles volume fraction increase. Whereas the velocity decreases with the Casson parameter. Thus, by adding Au nanoparticles, the tissue thermal conductivity enhanced which has the consequence of freezing the tissue in nano-cryosurgery treatment significantly.
    Matched MeSH terms: Models, Theoretical
  10. Coupling SWAT and Bi-LSTM for improving daily-scale hydro-climatic simulation and climate change impact assessment in a tropical river basin
    Yang S, Tan ML, Song Q, He J, Yao N, Li X, et al.
    J Environ Manage, 2023 Mar 15;330:117244.
    PMID: 36621311 DOI: 10.1016/j.jenvman.2023.117244
    Global climate change has led to an increase in both the frequency and magnitude of extreme events around the world, the risk of which is especially imminent in tropical regions. Developing hydrological models with better capabilities to simulate streamflow, especially peak flow, is urgently needed to facilitate water resource planning and management as well as climate change mitigation efforts in the tropics. In view of the need, this paper explores the feasibility of improving streamflow simulation performance in the tropical Kelantan River Basin (KRB) of Peninsular Malaysia through coupling a conceptual process-based hydrological model - Soil and Water Assessment Tool (SWAT) with a deep learning model - Bidirectional Long Short-Term Memory (Bi-LSTM) in two ways. All SWAT parameters were set as their default values in one hybrid model (SWAT-D-LSTM), whereas three most sensitive SWAT parameters were calibrated in the other hybrid model (SWAT-T-LSTM). Comparison of daily streamflow simulation results have shown that SWAT-T-LSTM consistently performs better than SWAT-D-LSTM as well as the stand-alone SWAT and Bi-LSTM model throughout the simulation period. Particularly, SWAT-T-LSTM performs considerably better than the other three models in simulating daily peak flow. Based on the latest projection results of five GCMs from the Sixth Phase of the Coupled Model Intercomparison Project (CMIP6) under three emission scenarios (SSP1-2.6, SSP2-4.5, SSP5-8.5), the best-performed SWAT-T-LSTM was run to assess the potential impacts of climate change on streamflow in the KRB. Ensemble assessment results have concluded that both average and extreme streamflow is much likely to increase considerably in the already wet northeast monsoon season from November to January, which has surely raised the alarm for more frequent flood occurrence in the KRB.
    Matched MeSH terms: Models, Theoretical
  11. Fulltext A multiscale mathematical model describing the growth and development of bambara groundnut
    Dodd J, Sweby PK, Mayes S, Murchie EH, Karunaratne AS, Massawe F, et al.
    J Theor Biol, 2023 Mar 07;560:111373.
    PMID: 36509139 DOI: 10.1016/j.jtbi.2022.111373
    A principal objective in agriculture is to maximise food production; this is particularly relevant with the added demands of an ever increasing population, coupled with the unpredictability that climate change brings. Further improvements in productivity can only be achieved with an increased understanding of plant and crop processes. In this respect, mathematical modelling of plants and crops plays an important role. In this paper we present a two-scale mathematical model of crop yield that accounts for plant growth and canopy interactions. A system of nonlinear ordinary differential equations (ODEs) is formulated to describe the growth of each individual plant, where equations are coupled via a term that describes plant competition via canopy-canopy interactions. A crop of greenhouse plants is then modelled via an agent based modelling approach in which the growth of each plant is described via our system of ODEs. The model is formulated for the African drought tolerant legume bambara groundnut (Vigna subterranea), which is currently being investigated as a food source in light of climate change and food insecurity challenges. Our model allows us to account for plant diversity and also investigate the effect of individual plant traits (e.g. plant canopy size and planting distance) on the yield of the overall crop. Informed with greenhouse data, model results show that plant positioning relative to other plants has a large impact on individual plant yield. Variation in physiological plant traits from genetic diversity and the environmental effects lead to experimentally observed variations in crop yield. These traits include plant height, plant carrying capacity, leaf accumulation rate and canopy spread. Of these traits plant height and ground cover growth rates are found to have the greatest impact on crop yield. We also consider a range of different planting arrangements (uniform grid, staggered grid, circular rings and random allocation) and find that the staggered grid leads to the greatest crop yield (6% more compared to uniform grid). Whilst formulated specifically for bambara groundnut, the generic formulation of our model means that with changes to certain parameter's, it may be extended to other crop species that form a canopy.
    Matched MeSH terms: Models, Theoretical
  12. Mathematical Model of COVID-19 Pandemic with Double Dose Vaccination
    Peter OJ, Panigoro HS, Abidemi A, Ojo MM, Oguntolu FA
    Acta Biotheor, 2023 Mar 06;71(2):9.
    PMID: 36877326 DOI: 10.1007/s10441-023-09460-y
    This paper is concerned with the formulation and analysis of an epidemic model of COVID-19 governed by an eight-dimensional system of ordinary differential equations, by taking into account the first dose and the second dose of vaccinated individuals in the population. The developed model is analyzed and the threshold quantity known as the control reproduction number [Formula: see text] is obtained. We investigate the equilibrium stability of the system, and the COVID-free equilibrium is said to be locally asymptotically stable when the control reproduction number is less than unity, and unstable otherwise. Using the least-squares method, the model is calibrated based on the cumulative number of COVID-19 reported cases and available information about the mass vaccine administration in Malaysia between the 24th of February 2021 and February 2022. Following the model fitting and estimation of the parameter values, a global sensitivity analysis was performed by using the Partial Rank Correlation Coefficient (PRCC) to determine the most influential parameters on the threshold quantities. The result shows that the effective transmission rate [Formula: see text], the rate of first vaccine dose [Formula: see text], the second dose vaccination rate [Formula: see text] and the recovery rate due to the second dose of vaccination [Formula: see text] are the most influential of all the model parameters. We further investigate the impact of these parameters by performing a numerical simulation on the developed COVID-19 model. The result of the study shows that adhering to the preventive measures has a huge impact on reducing the spread of the disease in the population. Particularly, an increase in both the first and second dose vaccination rates reduces the number of infected individuals, thus reducing the disease burden in the population.
    Matched MeSH terms: Models, Theoretical
  13. Economic and environmental life cycle perspectives on two engineered wood products: comparison of LVL and GLT construction materials
    Balasbaneh AT, Sher W, Yeoh D, Yasin MN
    Environ Sci Pollut Res Int, 2023 Feb;30(10):26964-26981.
    PMID: 36374387 DOI: 10.1007/s11356-022-24079-1
    The embodied carbon of building materials and the energy consumed during construction have a significant impact on the environmental credentials of buildings. The structural systems of a building present opportunities to reduce environmental emissions and energy. In this regard, mass timber materials have considerable potential as sustainable materials over other alternatives such as steel and concrete. The aim of this investigation was to compare the environment impact, energy consumption, and life cycle cost (LCC) of different wood-based materials in identical single-story residential buildings. The materials compared are laminated veneer lumber (LVL) and glued laminated timber (GLT). GLT has less global warming potential (GWP), ozone layer depletion (OLD), and land use (LU), respectively, by 29%, 37%, and 35% than LVL. Conversely, LVL generally has lower terrestrial acidification potential (TAP), human toxicity potential (HTP), and fossil depletion potential (FDP), respectively, by 30%, 17%, and 27%. The comparative outcomes revealed that using LVL reduces embodied energy by 41%. To identify which of these materials is the best alternative, various environmental categories, embodied energy, and cost criteria require further analysis. Therefore, the multi-criteria decision-making (MCDM) method has been applied to enable robust decision-making. The outcome showed that LVL manufacturing using softwood presents the most sustainable choice. These research findings contribute to the body of knowledge about the use of mass timber in construction.
    Matched MeSH terms: Models, Theoretical
  14. Low-gradient magnetic separation of magnetic nanoparticles under continuous flow: Experimental study, transport mechanism and mathematical modelling
    Tan YW, Leong SS, Lim J, Yeoh WM, Toh PY
    Electrophoresis, 2022 Nov;43(21-22):2234-2249.
    PMID: 35921231 DOI: 10.1002/elps.202200078
    Low-gradient magnetic separation (LGMS) of magnetic nanoparticles (MNPs) has been proven as one of the techniques with great potential for biomedical and environmental applications. Recently, the underlying principle of particle capture by LGMS, through a process known as magnetophoresis, under the influence of hydrodynamic effect has been widely studied and illustrated. Even though the hydrodynamic effect is very substantial for batch processes, its impact on LGMS operated at continuous flow (CF) condition remained largely unknown. Hence, in this study, the dynamical behaviour of LGMS process operated under CF was being studied. First, the LGMS experiments using poly(sodium 4-styrenesulfonate)-functionalized-MNP as modelled particle system were performed through batchwise (BW) and CF modes at different operating conditions. Here BW operation was used as a comparative study to elucidate the transport mechanism of MNP under the similar environment of CF-LGMS process, and it was found out that the convection induced by magnetophoresis (timescale effective is ∼1200 s) is only significant at far-from-magnet region. Hence, it can be deduced that forced convection is more dominant on influencing the transport behaviour of CF-LGMS (with resident time ≤240 s). Moreover, we found that the separation efficiency of CF-LGMS process can be boosted by the higher number of magnets, the higher MNP concentration and the lower flowrate of MNP solution. To better illustrate the underlying dynamical behaviour of LGMS process, a mathematical model was developed to predict its kinetic profile and separation efficiency (with average error of ∼2.6% compared to the experimental results).
    Matched MeSH terms: Models, Theoretical
  15. Mathematical Modelling of Dengue Transmission with Intervention Strategies Using Fractional Derivatives
    Hamdan N', Kilicman A
    Bull Math Biol, 2022 Oct 26;84(12):138.
    PMID: 36287255 DOI: 10.1007/s11538-022-01096-2
    This paper deals with a deterministic mathematical model of dengue based on a system of fractional-order differential equations (FODEs). In this study, we consider dengue control strategies that are relevant to the current situation in Malaysia. They are the use of adulticides, larvicides, destruction of the breeding sites, and individual protection. The global stability of the disease-free equilibrium and the endemic equilibrium is constructed using the Lyapunov function theory. The relations between the order of the operator and control parameters are briefly analysed. Numerical simulations are performed to verify theoretical results and examine the significance of each intervention strategy in controlling the spread of dengue in the community. The model shows that vector control tools are the most efficient method to combat the spread of the dengue virus, and when combined with individual protection, make it more effective. In fact, the massive use of personal protection alone can significantly reduce the number of dengue cases. Inversely, mechanical control alone cannot suppress the excessive number of infections in the population, although it can reduce the Aedes mosquito population. The result of the real-data fitting revealed that the FODE model slightly outperformed the integer-order model. Thus, we suggest that the FODE approach is worth to be considered in modelling an infectious disease like dengue.
    Matched MeSH terms: Models, Theoretical
  16. Fulltext Mathematical modeling of COVID-19 pandemic in India using Caputo-Fabrizio fractional derivative
    Pandey P, Gómez-Aguilar JF, Kaabar MKA, Siri Z, Mousa AAA
    Comput Biol Med, 2022 Jun;145:105518.
    PMID: 35447461 DOI: 10.1016/j.compbiomed.2022.105518
    The range of effectiveness of the novel corona virus, known as COVID-19, has been continuously spread worldwide with the severity of associated disease and effective variation in the rate of contact. This paper investigates the COVID-19 virus dynamics among the human population with the prediction of the size of epidemic and spreading time. Corona virus disease was first diagnosed on January 30, 2020 in India. From January 30, 2020 to April 21, 2020, the number of patients was continuously increased. In this scientific work, our main objective is to estimate the effectiveness of various preventive tools adopted for COVID-19. The COVID-19 dynamics is formulated in which the parameters of interactions between people, contact tracing, and average latent time are included. Experimental data are collected from April 15, 2020 to April 21, 2020 in India to investigate this virus dynamics. The Genocchi collocation technique is applied to investigate the proposed fractional mathematical model numerically via Caputo-Fabrizio fractional derivative. The effect of presence of various COVID parameters e.g. quarantine time is also presented in the work. The accuracy and efficiency of the outputs of the present work are demonstrated through the pictorial presentation by comparing it to known statistical data. The real data for COVID-19 in India is compared with the numerical results obtained from the concerned COVID-19 model. From our results, to control the expansion of this virus, various prevention measures must be adapted such as self-quarantine, social distancing, and lockdown procedures.
    Matched MeSH terms: Models, Theoretical
  17. Fulltext Asymmetric impact of temperature on COVID-19 spread in India: Evidence from quantile-on-quantile regression approach
    Irfan M, Razzaq A, Suksatan W, Sharif A, Madurai Elavarasan R, Yang C, et al.
    J Therm Biol, 2022 Feb;104:103101.
    PMID: 35180949 DOI: 10.1016/j.jtherbio.2021.103101
    The emergence of new coronavirus (SARS-CoV-2) has become a significant public health issue worldwide. Some researchers have identified a positive link between temperature and COVID-19 cases. However, no detailed research has highlighted the impact of temperature on COVID-19 spread in India. This study aims to fill this research gap by investigating the impact of temperature on COVID-19 spread in the five most affected Indian states. Quantile-on-Quantile regression (QQR) approach is employed to examine in what manner the quantiles of temperature influence the quantiles of COVID-19 cases. Empirical results confirm an asymmetric and heterogenous impact of temperature on COVID-19 spread across lower and higher quantiles of both variables. The results indicate a significant positive impact of temperature on COVID-19 spread in the three Indian states (Maharashtra, Andhra Pradesh, and Karnataka), predominantly in both low and high quantiles. Whereas, the other two states (Tamil Nadu and Uttar Pradesh) exhibit a mixed trend, as the lower quantiles in both states have a negative effect. However, this negative effect becomes weak at middle and higher quantiles. These research findings offer valuable policy recommendations.
    Matched MeSH terms: Models, Theoretical
  18. A review of alternative climate products for SWAT modelling: Sources, assessment and future directions
    Tan ML, Gassman PW, Liang J, Haywood JM
    Sci Total Environ, 2021 Nov 15;795:148915.
    PMID: 34328938 DOI: 10.1016/j.scitotenv.2021.148915
    Alternative climate products, such as gauge-based gridded data, ground-based weather radar, satellite precipitation and climate reanalysis products, are being increasingly applied for hydrological modelling. This review aims to summarize the studies that have evaluated alternative climate products within Soil and Water Assessment Tool (SWAT) applications and to propose future research directions, primarily for modelers who wish to study limited gauge, ungauged or transnational river basins. A total of 126 articles have been identified since 2004, the majority of which have been published within the last five years. About 58% of the studies were conducted in Asia, mostly in China and India, while another 14% were reported for United States studies. CFSR and TRMM are the most popular applied products in SWAT modelling, followed by PERSIANN, CMADS, APHRODITE, CHIRPS and NEXRAD. Generally, the performance of climate products is region-dependent; e.g., CFSR typically performs well in the United States and South America, but performs more poorly for Asia, Africa and mountainous basin conditions, as compared to other products. In contrast, the CMADS, TRMM, APRHODITE and NEXRAD have shown the strongest capability for supporting SWAT modelling in these regions. However, most of the evaluated products contain only precipitation input; therefore, merging reliable precipitation with CFSR-temperature is recommended for hydro-climatic modelling. Future research directions include: (1) examination of optimal combinations; e.g. CHIRPS-precipitation and CFSR-temperature, for simulating streamflow in different types of river basins; (2) development of a standardized validation scheme which incorporates the commonly accepted products, statistical approaches and temperature variables; (3) further evaluation of existing climate data products to accurately capture extreme events, pattern and indices as well as WGEN statistics; (4) improvement of climate data in terms of averaging approach, bias correction and additional factors or indices integration; and (5) bias correction of CMIP6 climate projections using the optimal climate data combinations.
    Matched MeSH terms: Models, Theoretical
  19. Fulltext Macroalgae in biomonitoring of metal pollution in the Bay of Bengal coastal waters of Cox's Bazar and surrounding areas
    Rakib MRJ, Jolly YN, Dioses-Salinas DC, Pizarro-Ortega CI, De-la-Torre GE, Khandaker MU, et al.
    Sci Rep, 2021 10 25;11(1):20999.
    PMID: 34697391 DOI: 10.1038/s41598-021-99750-7
    Although coastal water marine algae have been popularly used by others as indicators of heavy metal pollution, data within the Bay of Bengal for the estuarine Cox's Bazar region and Saint Martin's Island has remained scarce. Using marine algae, the study herein forms an effort in biomonitoring of metal contamination in the aforementioned Bangladesh areas. A total of 10 seaweed species were collected, including edible varieties, analyzed for metal levels through the use of the technique of EDXRF. From greatest to least, measured mean metal concentrations in descending order have been found to be K > Fe > Zr > Br > Sr > Zn > Mn > Rb > Cu > As > Pb > Cr > Co. Potential toxic heavy metals such as Pb, As, and Cr appear at lower concentration values compared to that found for essential mineral elements. However, the presence of Pb in Sargassum oligocystum species has been observed to exceed the maximum international guidance level. Given that some of the algae species are cultivated for human consumption, the non-carcinogenic and carcinogenic indices were calculated, shown to be slightly lower than the maxima recommended by the international organizations. Overall, the present results are consistent with literature data suggesting that heavy metal macroalgae biomonitoring may be species-specific. To the best of our knowledge, this study represents the first comprehensive macroalgae biomonitoring study of metal contamination from the coastal waters of Cox's Bazar and beyond.
    Matched MeSH terms: Models, Theoretical
  20. Fulltext Optimal virtual water flows for improved food security in water-scarce countries
    Maroufpoor S, Bozorg-Haddad O, Maroufpoor E, Gerbens-Leenes PW, Loáiciga HA, Savic D, et al.
    Sci Rep, 2021 10 25;11(1):21027.
    PMID: 34697363 DOI: 10.1038/s41598-021-00500-6
    The worsening water scarcity has imposed a significant stress on food production in many parts of the world. This stress becomes more critical when countries seek self-sufficiency. A literature review shows that food self-sufficiency has not been assessed as the main factor in determining the optimal cultivation patterns. However, food self-sufficiency is one of the main policies of these countries and requires the most attention and concentration. Previous works have focused on the virtual water trade to meet regional food demand and to calculate trade flows. The potential of the trade network can be exploited to improve the cropping pattern to ensure food and water security. To this end, and based on the research gaps mentioned, this study develops a method to link intra-country trade networks, food security, and total water footprints (WFs) to improve food security. The method is applied in Iran, a water-scarce country. The study shows that 781 × 106 m3 of water could be saved by creating a trade network. Results of the balanced trade network are input to a multi-objective optimization model to improve cropping patterns based on the objectives of achieving food security and preventing water crises. The method provides 400 management scenarios to improve cropping patterns considering 51 main crops in Iran. Results show a range of improvements in food security (19-45%) and a decrease in WFs (2-3%). The selected scenario for Iran would reduce the blue water footprint by 1207 × 106 m3, and reduce the cropland area by 19 × 103 ha. This methodology allows decision makers to develop policies that achieve food security under limited water resources in arid and semi-arid regions.
    Matched MeSH terms: Models, Theoretical
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