ArticleChaos, solitons, and fractals2020
Determinants of the infection rate of the COVID-19 in the U.S. using ANFIS and virus optimization algorithm (VOA).
Article in Chaos, solitons, and fractals, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 2 of them syntheses that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
17 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Machine Learning Used in Communicable Disease Control: A Scoping Review.Public health reviews · 2026Pooled it
- Application of Artificial Intelligence-Based Regression Methods in the Problem of COVID-19 Spread Prediction: A Systematic Review.International journal of environmental research and public health · 2021Pooled it
- Design Optimization of the Mechanics of a Metamaterial-Based Prosthetic Foot.Materials (Basel, Switzerland) · 2024Article
- A Hybridized Machine Learning Approach for Predicting COVID-19 Using Adaptive Neuro-Fuzzy Inference System and Reptile Search Algorithm.Diagnostics (Basel, Switzerland) · 2023Article
- An innovative ensemble model based on multiple neural networks and a novel heuristic optimization algorithm for COVID-19 forecasting.Expert systems with applications · 2023Article
- An updated estimation approach for SEIR models with stochastic perturbations: Application to COVID-19 data in Bogotá.PloS one · 2023Article
- Probabilistic Approach to COVID-19 Data Analysis and Forecasting Future Outbreaks Using a Multi-Layer Perceptron Neural Network.Diagnostics (Basel, Switzerland) · 2022Article
- Artificial Intelligence for Forecasting the Prevalence of COVID-19 Pandemic: An Overview.Healthcare (Basel, Switzerland) · 2021Review
- Application of machine learning in the prediction of COVID-19 daily new cases: A scoping review.Heliyon · 2021Article
- Status evaluation of provinces affected by COVID-19: A qualitative assessment using fuzzy system.Applied soft computing · 2021Article
- Superiority of Mild Interventions against COVID-19 on Public Health and Economic Measures.Journal of personalized medicine · 2021Article
- COVID-19 cases prediction by using hybrid machine learning and beetle antennae search approach.Sustainable cities and society · 2021Article
- Influence of Meteorological Factors on the COVID-19 Transmission with Season and Geographic Location.International journal of environmental research and public health · 2021Article
- Applications of artificial intelligence in battling against covid-19: A literature review.Chaos, solitons, and fractals · 2021Review
- Optimization in the Context of COVID-19 Prediction and Control: A Literature Review.IEEE access : practical innovations, open solutions · 2021Article
- Generalized Richards model for predicting COVID-19 dynamics in Saudi Arabia based on particle swarm optimization Algorithm.AIMS public health · 2020Article
- Correlation Between Local Air Temperature and the COVID-19 Pandemic in Hubei, China.Frontiers in public healthArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Recently, anovel coronavirus disease (COVID-19) has become a serious concern for global public health. Infectious disease outbreaks such as COVID-19 can also significantly affect the sustainable development of urban areas. Several factors such as population density and climatology parameters could potentially affect the spread of the COVID-19. In this study, a combination of the virus optimization algorithm (VOA) and adaptive network-based fuzzy inference system (ANFIS) was used to investigate the effects of various climate-related factors and population density on the spread of the COVID-19. For this purpose, data on the climate-related factors and the confirmed infected cases by the COVID-19 across the U.S counties was used. The results show that the variable defined for the population density had the most significant impact on the performance of the developed models, which is an indication of the importance of social distancing in reducing the infection rate and spread rate of the COVID-19. Among the climatology parameters, an increase in the maximum temperature was found to slightly reduce the infection rate. Average temperature, minimum temperature, precipitation, and average wind speed were not found to significantly affect the spread of the COVID-19 while an increase in the relative humidity was found to slightly increase the infection rate. The findings of this research show that it could be expected to have slightly reduced infection rate over the summer season. However, it should be noted that the models developed in this study were based on limited one-month data. Future investigation can benefit from using more comprehensive data covering a wider range for the input variables.
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