scholarly journals Spatio-Temporal Modeling of Immune Response to SARS-CoV-2 Infection

Mathematics ◽  
2021 ◽  
Vol 9 (24) ◽  
pp. 3274
Author(s):  
Talal Alzahrani
Keyword(s):  
T Cells ◽  
Temporal Dynamics ◽  
Numerical Range ◽  
Dimensional Space ◽  
Model Performance ◽  
Baseline Scenario ◽  
Temporal Modeling ◽  
Spatio Temporal ◽  
Load Peak ◽  
Novel Coronavirus

COVID-19 is a disease occurring as a result of infection by a novel coronavirus called SARS-CoV-2. Since the WHO announced COVID-19 as a global pandemic, mathematical works have taken place to simulate infection scenarios at different scales even though the majority of these models only consider the temporal dynamics of SARS-COV-2. In this paper, we present a new spatio-temporal within-host mathematical model of COVID-19, accounting for the coupled dynamics of healthy cells, infected cells, SARS-CoV-2 molecules, chemokine concentration, effector T cells, regulatory T cells, B-lymphocytes cells and antibodies. We develop a computational framework involving discretisation schemes for diffusion and chemotaxis terms using central differences and midpoint approximations within two dimensional space combined with a predict–evaluate–correct mode for time marching. Then, we numerically investigate the model performance using a list of values simulating the baseline scenario for viral infection at a cellular scale. Moreover, we explore the model sensitivity via applying certain conditions to observe the model validity in a comparison with clinical outcomes collected from recent studies. In this computational investigation, we have a numerical range of 104 to 108 for the viral load peak, which is equivalent to what has been obtained from throat swab samples for many patients.

scholarly journals The spatio-temporal epidemic dynamics of COVID-19 outbreak in Africa

2020 ◽  
Author(s):  
Ezra Gayawan ◽  
Olawale Awe ◽  
Bamidele M Oseni ◽  
Ikemefuna C. Uzochukwu ◽  
Adeshina Adekunle ◽  
...  
Keyword(s):  
Temporal Dynamics ◽  
Poisson Model ◽  
The Novel ◽  
African Continent ◽  
Scarce Resources ◽  
Epidemic Dynamics ◽  
Disease Patterns ◽  
Spatio Temporal ◽  
Novel Coronavirus ◽  
The City

AbstractThe novel coronavirus (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), emerged in the city of Wuhan, China in December 2019. Although, the disease appears on the African continent late, it has spread to virtually all the countries. We provide early spatio-temporal dynamics of COVID-19 within the first 62 days of the disease’s appearance on the African continent. We used a two-parameter hurdle Poisson model to simultaneously analyze the zero counts and the frequency of occurrence. We investigate the effects of important healthcare capacities including hospital beds and number of medical doctors in the different countries. The results show that cases of the pandemic vary geographically across Africa with notable high incidence in neighboring countries particularly in West and North Africa. The burden of the disease (per 100,000) was most felt in Djibouti Tunisia, Morocco and Algeria. Temporally, during the first 4 weeks, the burden was highest in Senegal, Egypt and Mauritania, but by mid-April it shifted to Somalia, Chad, Guinea, Tanzania, Gabon, Sudan, and Zimbabwe. Currently, Namibia, Angola, South Sudan, Burundi and Uganda have the least burden. The findings could be useful in implementing epidemiological intervention and allocation of scarce resources based on heterogeneity of the disease patterns.

Spatial capability of the catchment model HYPE to simulate nitrate and phosphorus concentration in the mixed land use Selke catchment, Germany

2020 ◽  
Author(s):  
Salman Ghaffar ◽  
Seifeddine Jomaa ◽  
Michael Rode
Keyword(s):  
Land Use ◽  
Uncertainty Analysis ◽  
Temporal Dynamics ◽  
Model Performance ◽  
Phosphorus Concentration ◽  
Multi Objective ◽  
Nitrate N ◽  
Spatially Distributed ◽  
Mixed Land Use ◽  
Spatio Temporal

<p>Semi-distributed hydrological models are broadly used for estimating nonpoint source pollutant inputs to receiving waterbodies and their source areas and predicting the effects of climate and land-use change on water quality. However, satisfactory assessment of such models is required to test their ability to represent different physiographical characteristics of subjected catchments for future predictions. This spatially-distributed internal model validation is rare. To cover this aspect, the semi-distributed model HYPE (Hydrological Predictions for the Environment) was used to simulate nitrate-N (NO<sub>3</sub>-N) and total phosphorus (TP) concentrations for spatially distributed non-calibrated internal gauging stations. First, HYPE model was applied at a mesoscale nested catchment Selke (463 km<sup>2</sup>) in central Germany to simulate discharge, NO<sub>3</sub>-N and TP concentrations at three gauging stations in main river, which represent the whole geographical features of the catchment from upstream forest-dominant to downstream agricultural-dominant land use. An automatic calibration procedure and uncertainty analysis using the DiffeRential Evolution Adaptive Metropolis (DREAM) tool and a multi-site and multi-objective calibration approach was conducted. Second, the model performance was evaluated using additional internal stations not used for model calibration.</p><p>Results showed that HYPE could represent reasonably well discharge for both calibration (1994-1998) and validation (1999-2014) periods with lowest Nash-Sutcliffe Efficiency (NSE) of 0.75 and percentage bias (PBIAS) of less than 18% with lower predictive uncertainty. There is a decreasing behavior in model performance during the validation period compared to the calibration period, which can be explained by the reduction of precipitation stations. Model performance declined substantially when only the outlet gauging station, representing the mixed land use of the study catchment, was used instead of multisite calibration. Well representation of NO<sub>3</sub>-N and TP load dynamics were resulted by the model showing a highest PBIAS of -16% and -20% for NO<sub>3</sub>-N and TP loads simulations, respectively. Results confirmed that changing seasonal pattern of NO<sub>3</sub>-N concentrations were controlled by combined effects of both hydrological and biogeochemical processes. TP concentration simulations were strongly impacted by the availability of accurate point source data. Results, also, showed the capability of HYPE to simulate spatio-temporal dynamics of NO<sub>3</sub>-N and TP concentrations at eight internal[MRr1] [SGg2]  validation stations with PBIAS values varies in the range of -9% to 14% and -25% to 34% for NO<sub>3</sub>-N and TP concentrations, respectively. Overall results suggested that combination of multi-site and multi-objective calibration using key archetypes gauging stations can strongly support spatio-temporal performance of the semi-distributed HYPE model.</p><p><strong>Keywords</strong>: HYPE model, Nitrate-N, Phosphorus, Internal validation, Uncertainty analysis, multi-site and multi-objective calibration and archetype gauging stations.</p>

scholarly journals Spatial And Spatio-Temporal Epidemiological Approaches To Inform Covid-19 Surveillance And Control: A Review Protocol

2021 ◽  
Author(s):  
Julius Nyerere Odhiambo ◽  
Carrie Brewer Dolan
Keyword(s):  
Temporal Dynamics ◽  
Meta Analysis ◽  
Sub Saharan Africa ◽  
Research Database ◽  
Eligibility Criteria ◽  
Temporal Modeling ◽  
Review Protocol ◽  
Spatio Temporal ◽  
Sub Saharan ◽  
Methodological Aspects

Abstract Introduction: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pathogen/infections that cause coronavirus disease 2019 (Covid-19 ) have afflicted millions worldwide. Understanding the underlying spatial and temporal dynamics can help orient timely public health policies and optimize the targeting of non-pharmaceutical interventions and vaccines to the most vulnerable populations, particularly in resource-constrained settings such as Sub-Saharan Africa (SSA). The review systematically summarises important methodological aspects and specificities of spatial approaches applied to Covid-19 in SSA. Methods: Thematically selected keywords will systematically search for refereed studies in the following electronic databases PubMed, SCOPUS, MEDLINE, CINHAL, and Coronavirus Research Database for peer-reviewed articles from January 2020 to October 2021. Two independent reviewers will screen the title, abstracts, and full texts against predefined eligibility criteria based on methodological relevance and quality. The Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) 2020 procedures will be adhered to during the reporting process.Discussion: A wealth of studies employing spatial and spatio-temporal methodology have appeared in literature in diverse contexts; however, Covid-19 modeling remains in its infancy, and research is needed to characterize uncertainty and validate various modeling regimes appropriately. It is anticipated that the review will aid spatial, spatio-temporal modeling decisions necessary for mitigating the current and future pandemics. Systematic review registration: CRD42021279767

scholarly journals A finite-difference discretization preserving the structure of solutions of a diffusive model of type-1 human immunodeficiency virus

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Joel Alba-Pérez ◽  
Jorge E. Macías-Díaz
Keyword(s):  
Human Immunodeficiency Virus ◽  
T Cells ◽  
Temporal Dynamics ◽  
Continuous System ◽  
Time And Space ◽  
Structure Of Solutions ◽  
Differential Model ◽  
Immunodeficiency Virus ◽  
Spatio Temporal ◽  
Hiv 1

AbstractWe investigate a model of spatio-temporal spreading of human immunodeficiency virus HIV-1. The mathematical model considers the presence of various components in a human tissue, including the uninfected CD4+T cells density, the density of infected CD4+T cells, and the density of free HIV infection particles in the blood. These three components are nonnegative and bounded variables. By expressing the original model in an equivalent exponential form, we propose a positive and bounded discrete model to estimate the solutions of the continuous system. We establish conditions under which the nonnegative and bounded features of the initial-boundary data are preserved under the scheme. Moreover, we show rigorously that the method is a consistent scheme for the differential model under study, with first and second orders of consistency in time and space, respectively. The scheme is an unconditionally stable and convergent technique which has first and second orders of convergence in time and space, respectively. An application to the spatio-temporal dynamics of HIV-1 is presented in this manuscript. For the sake of reproducibility, we provide a computer implementation of our method at the end of this work.

Spatial and temporal dynamics of Pacific capelin Mallotus catervarius in the Gulf of Alaska: implications for ecosystem-based fisheries management

2020 ◽  
Vol 637 ◽  
pp. 117-140 ◽  
Author(s):  
DW McGowan ◽  
ED Goldstein ◽  
ML Arimitsu ◽  
AL Deary ◽  
O Ormseth ◽  
...  
Keyword(s):  
Temporal Dynamics ◽  
Marine Ecosystem ◽  
Gulf Of Alaska ◽  
Data Series ◽  
Limited Information ◽  
Important Species ◽  
Multiple Data ◽  
Spatial And Temporal Dynamics ◽  
Spawning Areas ◽  
Spatio Temporal

Pacific capelin Mallotus catervarius are planktivorous small pelagic fish that serve an intermediate trophic role in marine food webs. Due to the lack of a directed fishery or monitoring of capelin in the Northeast Pacific, limited information is available on their distribution and abundance, and how spatio-temporal fluctuations in capelin density affect their availability as prey. To provide information on life history, spatial patterns, and population dynamics of capelin in the Gulf of Alaska (GOA), we modeled distributions of spawning habitat and larval dispersal, and synthesized spatially indexed data from multiple independent sources from 1996 to 2016. Potential capelin spawning areas were broadly distributed across the GOA. Models of larval drift show the GOA’s advective circulation patterns disperse capelin larvae over the continental shelf and upper slope, indicating potential connections between spawning areas and observed offshore distributions that are influenced by the location and timing of spawning. Spatial overlap in composite distributions of larval and age-1+ fish was used to identify core areas where capelin consistently occur and concentrate. Capelin primarily occupy shelf waters near the Kodiak Archipelago, and are patchily distributed across the GOA shelf and inshore waters. Interannual variations in abundance along with spatio-temporal differences in density indicate that the availability of capelin to predators and monitoring surveys is highly variable in the GOA. We demonstrate that the limitations of individual data series can be compensated for by integrating multiple data sources to monitor fluctuations in distributions and abundance trends of an ecologically important species across a large marine ecosystem.

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