4.3 Article

COVID-19 Risk Mapping with Considering Socio-Economic Criteria Using Machine Learning Algorithms

Related references

Note: Only part of the references are listed.
Article Environmental Sciences

Spatial modelling of accidents risk caused by driver drowsiness with data mining algorithms

Farbod Farhangi et al.

Summary: In this study, the risk of accidents caused by driver drowsiness in Qazvin province, Iran, was modeled using decision tree, random forest, and support-vector regression algorithms in a GIS environment. Seven spatial criteria were selected as effective criteria in modeling, with speed limit identified as the most important criterion for modeling. The random forest model showed the best overall performance with an AUC value of 0.904.

GEOCARTO INTERNATIONAL (2022)

Article Green & Sustainable Science & Technology

Understanding COVID-19 transmission through Bayesian probabilistic modeling and GIS-based Voronoi approach: a policy perspective

Hemant Bherwani et al.

Summary: COVID-19, originating from Wuhan, China, is spreading rapidly worldwide, with various strategies such as clinical trials, social distancing, and personal protective equipment being implemented. The study focuses on the effectiveness of India's lockdown and social distancing policies, finding that states implementing early lockdowns are better able to control the spread of the disease. High-risk areas can be identified using GIS-based Voronoi approach, providing valuable insights for strategic responses to the pandemic in India.

ENVIRONMENT DEVELOPMENT AND SUSTAINABILITY (2021)

Article Engineering, Environmental

Mapping of landslide susceptibility using the combination of neuro-fuzzy inference system (ANFIS), ant colony (ANFIS-ACOR), and differential evolution (ANFIS-DE) models

Seyed Vahid Razavi-Termeh et al.

Summary: This research utilized the ANFIS algorithm in conjunction with the ACOR and DE algorithms to provide a landslide susceptibility map of the Fahliyan sub-basin. The results indicated that the distance to road, rainfall, and SPI were the most significant factors influencing landslide occurrence in the area.

BULLETIN OF ENGINEERING GEOLOGY AND THE ENVIRONMENT (2021)

Article Environmental Sciences

Spatio-temporal modeling of PM2.5 risk mapping using three machine learning algorithms

Seyedeh Zeinab Shogrkhodaei et al.

Summary: The study focused on the Spatio-temporal modeling and preparation of PM2.5 risk mapping in the urban area of Tehran, Iran. Different parameters' importance and impacts were analyzed under seasonal variations.

ENVIRONMENTAL POLLUTION (2021)

Article Multidisciplinary Sciences

Understanding the role of urban design in disease spreading

Noel G. Brizuela et al.

Summary: Cities are complex systems that impact the health of residents, with inequalities influencing health outcomes. Developing theoretical frameworks at the neighborhood level becomes crucial; research using census data shows that urban activity patterns affect the spatiotemporal spread of diseases. Findings suggest that redesigning cities can limit the geographical scope of outbreaks of influenza-like diseases.

PROCEEDINGS OF THE ROYAL SOCIETY A-MATHEMATICAL PHYSICAL AND ENGINEERING SCIENCES (2021)

Article Multidisciplinary Sciences

Asthma-prone areas modeling using a machine learning model

Seyed Vahid Razavi-Termeh et al.

Summary: This study aimed to determine asthma-prone areas in Tehran, Iran using environmental and spatial factors. Analyzing 872 locations of children with asthma and 13 environmental factors, it was found that distance to parks and streets, as well as PM2.5 and PM10, had the greatest impact on asthma occurrence. The RF model showed good accuracy in predicting asthma occurrence with an AUC of 0.987 and 0.921 for training and testing data, respectively.

SCIENTIFIC REPORTS (2021)

Article Environmental Sciences

Effects of air pollution in Spatio-temporal modeling of asthma-prone areas using a machine learning model

Seyed Vahid Razavi-Termeh et al.

Summary: Industrialization and urbanization have worsened air pollution, impacting public health and asthma. This study modeled the spatial-temporal patterns of asthma in Tehran, Iran using machine learning, finding that PM2.5 had the most significant impact on asthma occurrence. Evaluation results suggested that asthma is more likely to occur in autumn.

ENVIRONMENTAL RESEARCH (2021)

Article Public, Environmental & Occupational Health

Analyzing the Risk to COVID-19 Infection using Remote Sensing and GIS

Shruti Kanga et al.

Summary: The COVID-19 pandemic poses a global threat, requiring a risk assessment framework to assist decision makers in developing effective strategies. A study in Jaipur, India, found higher risk areas in the north-eastern and south-eastern zones, recommending prioritizing these areas for intelligent decision-making regarding COVID-19 risk reduction.

RISK ANALYSIS (2021)

Article Environmental Sciences

Land Subsidence Susceptibility Mapping Using Persistent Scatterer SAR Interferometry Technique and Optimized Hybrid Machine Learning Algorithms

Babak Ranjgar et al.

Summary: This study evaluated land subsidence susceptibility in Shahryar County, Iran using the ANFIS machine learning algorithm, and found that ensembles of ANFIS with ICA and GWO algorithms improved prediction accuracy, with ANFIS-ICA model showing the best performance.

REMOTE SENSING (2021)

Article Environmental Sciences

Spatial Modeling of Asthma-Prone Areas Using Remote Sensing and Ensemble Machine Learning Algorithms

Seyed Vahid Razavi-Termeh et al.

Summary: This study utilized three ensemble machine learning algorithms to model asthma-prone areas in Tehran, Iran. Factors influencing asthma occurrence, such as distance to the street, NDVI, and traffic volume, were identified using spatial databases and remote sensing imagery. The AdaBoost algorithm outperformed Bagging and Stacking algorithms in spatial modeling of asthma-prone areas.

REMOTE SENSING (2021)

Article Environmental Studies

GIS-based spatial modelling of COVID-19 death incidence in Sao Paulo, Brazil

Rodrigo Custodio Urban et al.

Summary: The research findings indicate that there is a correlation between COVID-19 death incidence and social aspects such as population density, average people per household, and informal urban settlements. The geographically weighted regression (GWR) model provides the best explanation for the spatial distribution of COVID-19 in São Paulo city, highlighting the spatial aspects of the data.

ENVIRONMENT AND URBANIZATION (2021)

Article Medicine, General & Internal

Clinical Characteristics of 138 Hospitalized Patients With 2019 Novel Coronavirus-Infected Pneumonia in Wuhan, China

Dawei Wang et al.

JAMA-JOURNAL OF THE AMERICAN MEDICAL ASSOCIATION (2020)

Article Infectious Diseases

Can we contain the COVID-19 outbreak with the same measures as for SARS?

Annelies Wilder-Smith et al.

LANCET INFECTIOUS DISEASES (2020)

Article Infectious Diseases

2019-nCoV (Wuhan virus), a novel Coronavirus: human-to-human transmission, travel-related cases, and vaccine readiness

Robyn Ralph et al.

JOURNAL OF INFECTION IN DEVELOPING COUNTRIES (2020)

Review Infectious Diseases

The SARS-CoV-2 outbreak: What we know

Di Wu et al.

INTERNATIONAL JOURNAL OF INFECTIOUS DISEASES (2020)

Article Environmental Sciences

GIS-based spatial modeling of COVID-19 incidence rate in the continental United States

Abolfazl Mollalo et al.

SCIENCE OF THE TOTAL ENVIRONMENT (2020)

Article Environmental Sciences

A spatio-temporal analysis for exploring the effect of temperature on COVID-19 early evolution in Spain

Alvaro Briz-Redon et al.

SCIENCE OF THE TOTAL ENVIRONMENT (2020)

Article Environmental Sciences

Investigation of effective climatology parameters on COVID-19 outbreak in Iran

Mohsen Ahmadi et al.

SCIENCE OF THE TOTAL ENVIRONMENT (2020)

Article Environmental Sciences

Estimation of COVID-19 prevalence in Italy, Spain, and France

Zeynep Ceylan

SCIENCE OF THE TOTAL ENVIRONMENT (2020)

Article Water Resources

Improving groundwater potential mapping using metaheuristic approaches

Seyed Vahid Razavi-Termeh et al.

HYDROLOGICAL SCIENCES JOURNAL-JOURNAL DES SCIENCES HYDROLOGIQUES (2020)

Article Environmental Sciences

Landslide Susceptibility Mapping Using Machine Learning Algorithms and Remote Sensing Data in a Tropical Environment

Viet-Ha Nhu et al.

INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH (2020)

Article Geosciences, Multidisciplinary

Gully erosion susceptibility mapping using artificial intelligence and statistical models

Seyed Vahid Razavi-Termeh et al.

GEOMATICS NATURAL HAZARDS & RISK (2020)

Article Green & Sustainable Science & Technology

COVID-19: Challenges to GIS with Big Data

Chenghu Zhou et al.

GEOGRAPHY AND SUSTAINABILITY (2020)

Article Environmental Sciences

Spatial Prediction of Nitrate Concentration Using GIS and ANFIS Modelling in Groundwater

Nalini Jebastina et al.

BULLETIN OF ENVIRONMENTAL CONTAMINATION AND TOXICOLOGY (2018)

Article Geosciences, Multidisciplinary

Landslide susceptibility mapping based on frequency ratio and logistic regression models

K. Solaimani et al.

ARABIAN JOURNAL OF GEOSCIENCES (2013)