This paper is in the following e-collection/theme issue:

Infectious Diseases (non-STD/STI) (1592) Registered Report (579)

Published on in Vol 6, No 2 (2020): Apr-Jun

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/19115, first published .
Prediction of the COVID-19 Pandemic for the Top 15 Affected Countries: Advanced Autoregressive Integrated Moving Average (ARIMA) Model

Prediction of the COVID-19 Pandemic for the Top 15 Affected Countries: Advanced Autoregressive Integrated Moving Average (ARIMA) Model

Prediction of the COVID-19 Pandemic for the Top 15 Affected Countries: Advanced Autoregressive Integrated Moving Average (ARIMA) Model

Authors of this article:

Ram Kumar Singh1 Author Orcid Image ;   Meenu Rani2 Author Orcid Image ;   Akshaya Srikanth Bhagavathula3 Author Orcid Image ;   Ranjit Sah4 Author Orcid Image ;   Alfonso J Rodriguez-Morales5 Author Orcid Image ;   Himangshu Kalita6 Author Orcid Image ;   Chintan Nanda6 Author Orcid Image ;   Shashi Sharma7 Author Orcid Image ;   Yagya Datt Sharma8 Author Orcid Image ;   Ali A Rabaan9 Author Orcid Image ;   Jamal Rahmani10 Author Orcid Image ;   Pavan Kumar11 Author Orcid Image
Article Authors Cited by (160) Tweetations (12) Metrics

Journals

  1. Ilie O, Cojocariu R, Ciobica A, Timofte S, Mavroudis I, Doroftei B. Forecasting the Spreading of COVID-19 across Nine Countries from Europe, Asia, and the American Continents Using the ARIMA Models. Microorganisms 2020;8(8):1158 View
  2. Dhamodharavadhani S, Rathipriya R, Chatterjee J. COVID-19 Mortality Rate Prediction for India Using Statistical Neural Network Models. Frontiers in Public Health 2020;8 View
  3. Das R. Forecasting incidences of COVID-19 using Box-Jenkins method for the period July 12-Septembert 11, 2020: A study on highly affected countries. Chaos, Solitons & Fractals 2020;140:110248 View
  4. Archie S, Cucullo L. Cerebrovascular and Neurological Dysfunction under the Threat of COVID-19: Is There a Comorbid Role for Smoking and Vaping?. International Journal of Molecular Sciences 2020;21(11):3916 View
  5. Perone G. ARIMA forecasting of COVID-19 incidence in Italy, Russia, and the USA. SSRN Electronic Journal 2020 View
  6. Li G, Tang D, Song B, Wang C, Qunshan S, Xu C, Geng H, Wu H, He X, Cao Y. Impact of the COVID-19 Pandemic on Partner Relationships and Sexual and Reproductive Health: Cross-Sectional, Online Survey Study. Journal of Medical Internet Research 2020;22(8):e20961 View
  7. Cotrim Junior D, Cabral L. Crescimento dos leitos de UTI no país durante a pandemia de Covid-19: desigualdades entre o público x privado e iniquidades regionais. Physis: Revista de Saúde Coletiva 2020;30(3) View
  8. Walrave M, Waeterloos C, Ponnet K. Adoption of a Contact Tracing App for Containing COVID-19: A Health Belief Model Approach. JMIR Public Health and Surveillance 2020;6(3):e20572 View
  9. Thyagaraju B, Gowda S, Patil S, Srikantiah C, Suresh K. Future trends of COVID-19 disease outbreak in different states in India: a periodic regression analysis. Highlights in BioScience 2020 View
  10. Díaz Pinzón J. Perspectiva del COVID-19 en Colombia para el año 2021. Revista Repertorio de Medicina y Cirugía 2020:128 View
  11. Shur M. Pandemic Equation for Describing and Predicting COVID19 Evolution. Journal of Healthcare Informatics Research 2021;5(2):168 View
  12. De la Sen M, Ibeas A, Agarwal R. On Confinement and Quarantine Concerns on an SEIAR Epidemic Model with Simulated Parameterizations for the COVID-19 Pandemic. Symmetry 2020;12(10):1646 View
  13. De la Sen M, Ibeas A. On an SE(Is)(Ih)AR epidemic model with combined vaccination and antiviral controls for COVID-19 pandemic. Advances in Difference Equations 2021;2021(1) View
  14. Pourmalek F, Rezaei Hemami M, Janani L, Moradi-Lakeh M. Rapid review of COVID-19 epidemic estimation studies for Iran. BMC Public Health 2021;21(1) View
  15. Prasanth S, Singh U, Kumar A, Tikkiwal V, Chong P. Forecasting spread of COVID-19 using google trends: A hybrid GWO-deep learning approach. Chaos, Solitons & Fractals 2021;142:110336 View
  16. Chaurasia V, Pal S. Application of machine learning time series analysis for prediction COVID-19 pandemic. Research on Biomedical Engineering 2022;38(1):35 View
  17. Paul A, Reja S, Kundu S, Bhattacharya S. COVID-19 pandemic models revisited with a new proposal: Plenty of epidemiological models outcast the simple population dynamics solution. Chaos, Solitons & Fractals 2021;144:110697 View
  18. Singh R, Drews M, De La Sen M, Kumar M, Singh S, Pandey A, Srivastava P, Dobriyal M, Rani M, Kumari P, Kumar P. Short-Term Statistical Forecasts of COVID-19 Infections in India. IEEE Access 2020;8:186932 View
  19. Fang L, Wang D, Pan G. Analysis and Estimation of COVID-19 Spreading in Russia Based on ARIMA Model. SN Comprehensive Clinical Medicine 2020;2(12):2521 View
  20. Nistal R, de la Sen M, Gabirondo J, Alonso-Quesada S, Garrido A, Garrido I. A Modelization of the Propagation of COVID-19 in Regions of Spain and Italy with Evaluation of the Transmission Rates Related to the Intervention Measures. Biology 2021;10(2):121 View
  21. Hauben M, Hung E. Effects of the COVID-19 Pandemic on Spontaneous Reporting: Global and National Time-series Analyses. Clinical Therapeutics 2021;43(2):360 View
  22. De la Sen M, Ibeas A, Shaikhet L. On an Sir Epidemic Model for the COVID-19 Pandemic and the Logistic Equation. Discrete Dynamics in Nature and Society 2020;2020:1 View
  23. Sharma D, Khandelwal S. Sentiments analysis : Recitation of the concealed emotions of professionals during COVID-19. Journal of Statistics and Management Systems 2021;24(1):147 View
  24. Gómez-Pau Á, Riba J, Moreno-Eguilaz M. Time Series RUL Estimation of Medium Voltage Connectors to Ease Predictive Maintenance Plans. Applied Sciences 2020;10(24):9041 View
  25. Li Y, Jia W, Wang J, Guo J, Liu Q, Li X, Xie G, Wang F. ALeRT-COVID: Attentive Lockdown-awaRe Transfer Learning for Predicting COVID-19 Pandemics in Different Countries. Journal of Healthcare Informatics Research 2021;5(1):98 View
  26. Zakharov V, Balykina Y, Petrosian O, Gao H. CBRR Model for Predicting the Dynamics of the COVID-19 Epidemic in Real Time. Mathematics 2020;8(10):1727 View
  27. De la Sen M, Ibeas A. On a Controlled Se(Is)(Ih)(Iicu)AR Epidemic Model with Output Controllability Issues to Satisfy Hospital Constraints on Hospitalized Patients. Algorithms 2020;13(12):322 View
  28. Rahmadani F, Lee H. Hybrid Deep Learning-Based Epidemic Prediction Framework of COVID-19: South Korea Case. Applied Sciences 2020;10(23):8539 View
  29. Wang Y, Xu C, Yao S, Zhao Y. Forecasting the epidemiological trends of COVID-19 prevalence and mortality using the advanced α-Sutte Indicator. Epidemiology and Infection 2020;148 View
  30. Lynch C, Gore R. Short-Range Forecasting of COVID-19 During Early Onset at County, Health District, and State Geographic Levels Using Seven Methods: Comparative Forecasting Study. Journal of Medical Internet Research 2021;23(3):e24925 View
  31. Oliveira G, Lima L, Silva I, Ribeiro-Dantas M, Monteiro K, Endo P. Evaluating Social Distancing Measures and Their Association with the Covid-19 Pandemic in South America. ISPRS International Journal of Geo-Information 2021;10(3):121 View
  32. Shah A, Yan X, Qayyum A, Naqvi R, Shah S. Mining topic and sentiment dynamics in physician rating websites during the early wave of the COVID-19 pandemic: Machine learning approach. International Journal of Medical Informatics 2021;149:104434 View
  33. Jackson E. Forecasting COVID-19 Daily Contraction in Sierra Leone with Implications for Policy Formulation. SSRN Electronic Journal 2021 View
  34. Senthil Prakash P, Hariharan B, Kaliraj S, Siva R, Vivek D. WITHDRAWN: The impact of various policy factors implemented for controlling the spread of COVID-19. Materials Today: Proceedings 2021 View
  35. Jiang-ning L, Xian-liang S, An-qiang H, Ze-fang H, Yu-xuan K, Dong L. Forecasting emergency medicine reserve demand with a novel decomposition-ensemble methodology. Complex & Intelligent Systems 2023;9(3):2285 View
  36. Kulshreshtha V, Garg N. Predicting the New Cases of Coronavirus [COVID-19] in India by Using Time Series Analysis as Machine Learning Model in Python. Journal of The Institution of Engineers (India): Series B 2021;102(6):1303 View
  37. Choudhary T, Shaikh M, Khedekar S, Sirwani R, A. Thalor M. Use of Data Science during Worldwide Pandemic : An Efficient and Reliable System to Support Decision Making in Different Sectors. International Journal of Scientific Research in Science and Technology 2021:17 View
  38. Alharbi N. Forecasting the COVID-19 Pandemic in Saudi Arabia Using a Modified Singular Spectrum Analysis Approach: Model Development and Data Analysis. JMIRx Med 2021;2(1):e21044 View
  39. Paprottka F, Rolfes S, Richter D, Kaye K. COVID-19 Pandemic: Evaluation of Socio-Economic Impact on Aesthetic Plastic Surgery Providers. Aesthetic Plastic Surgery 2021;45(4):1877 View
  40. Selvakumar K, Lokesh S. RETRACTED ARTICLE: The prediction of the lifetime of the new coronavirus in the USA using mathematical models. Soft Computing 2021;25(16):10575 View
  41. Yadav S, Yadav P, Yadav N, Yadav C. The Peak and Size of COVID-19 in India: SARIMA and Forecast (Preprint). JMIR Public Health and Surveillance 2020 View
  42. Singh R, Drews M, De la Sen M, Srivastava P, Trisasongko B, Kumar M, Pandey M, Anand A, Singh S, Pandey A, Dobriyal M, Rani M, Kumar P. Highlighting the compound risk of COVID-19 and environmental pollutants using geospatial technology. Scientific Reports 2021;11(1) View
  43. Chen X, Peng F, Zhou X, Zhu J, Chen X, Gong Y, Shupeng W, Niu W. Predicting severe or critical symptoms in hospitalized patients with COVID-19 from Yichang, China. Aging 2021;13(2):1608 View
  44. Gebretensae Y, Asmelash D. Trend Analysis and Forecasting the Spread of COVID-19 Pandemic in Ethiopia Using Box–Jenkins Modeling Procedure. International Journal of General Medicine 2021;Volume 14:1485 View
  45. Feng X, Zhang H, Zhang Y, Sun L, Li J, Wu Y. On fluctuating characteristics of global COVID-19 cases and identification of inflection points. Library Hi Tech 2021;39(3):888 View
  46. Wang Z, Cai B. COVID-19 cases prediction in multiple areas via shapelet learning. Applied Intelligence 2022;52(1):595 View
  47. de Andres P, de Andres-Bragado L, Hoessly L. Monitoring and Forecasting COVID-19: Heuristic Regression, Susceptible-Infected-Removed Model and, Spatial Stochastic. Frontiers in Applied Mathematics and Statistics 2021;7 View
  48. Vierlboeck M, Nilchiani R, Edwards C. The Pandemic Holiday Blip in New York City. IEEE Transactions on Computational Social Systems 2021;8(3):568 View
  49. Jiang J, Park E, Park S. The Impact of the COVID-19 on Economic Sustainability—A Case Study of Fluctuation in Stock Prices for China and South Korea. Sustainability 2021;13(12):6642 View
  50. Shen J, Wang C, Dong C, Tang Z, Sun H. Reductions in mortality resulting from COVID-19 quarantine measures in China. Journal of Public Health 2021;43(2):254 View
  51. De la Sen M, Ibeas A, Garrido A. On a new SEIRDEoIoepidemic model eventually initiated from outside with delayed re-susceptibility and vaccination and treatment feedback controls. Physica Scripta 2021;96(9):095002 View
  52. Liu X, Hu S, Fong S, Crespo R, Herrera-Viedma E. Modelling dynamics of coronavirus disease 2019 spread for pandemic forecasting based on Simulink. Physical Biology 2021;18(4):045003 View
  53. Shoaib M, Salahudin H, Hammad M, Ahmad S, Khan A, Khan M, Baig M, Ahmad F, Ullah M. Performance Evaluation of Soft Computing Approaches for Forecasting COVID-19 Pandemic Cases. SN Computer Science 2021;2(5) View
  54. Nistal R, de la Sen M, Gabirondo J, Alonso-Quesada S, Garrido A, Garrido I. A Study on COVID-19 Incidence in Europe through Two SEIR Epidemic Models Which Consider Mixed Contagions from Asymptomatic and Symptomatic Individuals. Applied Sciences 2021;11(14):6266 View
  55. Shankar S, Mohakuda S, Kumar A, Nazneen P, Yadav A, Chatterjee K, Chatterjee K. Systematic review of predictive mathematical models of COVID-19 epidemic. Medical Journal Armed Forces India 2021;77:S385 View
  56. Nguyen H, Turk P, McWilliams A. Forecasting COVID-19 Hospital Census: A Multivariate Time-Series Model Based on Local Infection Incidence. JMIR Public Health and Surveillance 2021;7(8):e28195 View
  57. Lucic M, Ghazzai H, Lipizzi C, Massoud Y. Integrating County-Level Socioeconomic Data for COVID-19 Forecasting in the United States. IEEE Open Journal of Engineering in Medicine and Biology 2021;2:235 View
  58. Tang Y, Serdan T, Alecrim A, Souza D, Nacano B, Silva F, Silva E, Poma S, Gennari-Felipe M, Iser-Bem P, Masi L, Tang S, Levada-Pires A, Hatanaka E, Cury-Boaventura M, Borges F, Pithon-Curi T, Curpertino M, Fiamoncini J, Leandro C, Gorjao R, Curi R, Hirabara S. A simple mathematical model for the evaluation of the long first wave of the COVID-19 pandemic in Brazil. Scientific Reports 2021;11(1) View
  59. Swapnarekha H, Behera H, Nayak J, Naik B, Kumar P. Multiplicative Holts Winter Model for Trend Analysis and Forecasting of COVID-19 Spread in India. SN Computer Science 2021;2(5) View
  60. Liu C, Lu C, Lin L. Pandemic strategies with computational and structural biology against COVID-19: A retrospective. Computational and Structural Biotechnology Journal 2022;20:187 View
  61. Drews M, Kumar P, Singh R, De La Sen M, Singh S, Pandey A, Kumar M, Rani M, Srivastava P. Model-based ensembles: Lessons learned from retrospective analysis of COVID-19 infection forecasts across 10 countries. Science of The Total Environment 2022;806:150639 View
  62. Naimoli A. Modelling the persistence of Covid-19 positivity rate in Italy. Socio-Economic Planning Sciences 2022;82:101225 View
  63. Haji-Maghsoudi S, Sadeghifar M, Roshanaei G, Mahjub H. The Impact of Control Measures and Holiday Seasons on Incidence and Mortality Rate of COVID-19 in Iran. Journal of Research in Health Sciences 2020;20(4):e00500 View
  64. Gallego F, Martín C, Díaz M, Garrido D. Maintaining flexibility in smart grid consumption through deep learning and deep reinforcement learning. Energy and AI 2023;13:100241 View
  65. Fatimah B, Aggarwal P, Singh P, Gupta A. A comparative study for predictive monitoring of COVID-19 pandemic. Applied Soft Computing 2022;122:108806 View
  66. Gianquintieri L, Brovelli M, Pagliosa A, Dassi G, Brambilla P, Bonora R, Sechi G, Caiani E. Generating High-Granularity COVID-19 Territorial Early Alerts Using Emergency Medical Services and Machine Learning. International Journal of Environmental Research and Public Health 2022;19(15):9012 View
  67. Zhihao L, Junpei W, Xiaoliang Z, Huijun N. RESEARCH ON COVID-19 EPIDEMIC BASED ON ARIMA MODEL. Journal of Physics: Conference Series 2021;2012(1):012063 View
  68. James A, Malagón-Morris R, Gurusinghe S, Roblin P, Bloem C, Wise T, Joseph M, Arquilla B, Daniel P. Evaluating the impact of social distancing on COVID-19 hospitalizations using interrupted time series regression. International Journal of Academic Medicine 2022;8(1):24 View
  69. Khattak A, Chan P, Chen F, Peng H. Time-Series Prediction of Intense Wind Shear Using Machine Learning Algorithms: A Case Study of Hong Kong International Airport. Atmosphere 2023;14(2):268 View
  70. Shah S, Iftikhar A, Khan M, Mansoor M, Mirza A, Bilal M. PREDICTING COVID-19 INFECTIONS PREVALENCE USING LINEAR REGRESSION TOOL. Journal of Experimental Biology and Agricultural Sciences 2020;8(Spl-1- SARS-CoV-2):S01 View
  71. Zhao D, Zhang H, Cao Q, Wang Z, Zhang R. The research of SARIMA model for prediction of hepatitis B in mainland China. Medicine 2022;101(23):e29317 View
  72. McClymont H, Si X, Hu W. Using weather factors and google data to predict COVID-19 transmission in Melbourne, Australia: A time-series predictive model. Heliyon 2023;9(3):e13782 View
  73. Zhu S, Bukharin A, Xie L, Santillana M, Yang S, Xie Y. High-Resolution Spatio-Temporal Model for County-Level COVID-19 Activity in the U.S.. ACM Transactions on Management Information Systems 2021;12(4):1 View
  74. Mansoor M, Mirza A, Long F, Ling Q. An Intelligent Tunicate Swarm Algorithm Based MPPT Control Strategy for Multiple Configurations of PV Systems Under Partial Shading Conditions. Advanced Theory and Simulations 2021;4(12) View
  75. Oh J, Apio C, Park T. Mathematical modeling of the impact of Omicron variant on the COVID-19 situation in South Korea. Genomics & Informatics 2022;20(2):e22 View
  76. Ezike N, Ames Boykin A, Dobbs P, Mai H, Primack B. Exploring Factors That Predict Marketing of e-Cigarette Products on Twitter: Infodemiology Approach Using Time Series. JMIR Infodemiology 2022;2(2):e37412 View
  77. Jia P, Chen L, Lyu D. Fine-Grained Population Mobility Data-Based Community-Level COVID-19 Prediction Model. Cybernetics and Systems 2024;55(1):184 View
  78. K. M. Ravikumar , D. Chandrasekhar . Analysis and Prediction of COVID-19 Pandemic in India. International Journal of Scientific Research in Computer Science, Engineering and Information Technology 2022:229 View
  79. Krivosheev V, Stolyarov A. Atmosphere pressure and COVID-19. Sanitarnyj vrač (Sanitary Doctor) 2021;(7):8 View
  80. Lamsal R, Harwood A, Read M. Twitter conversations predict the daily confirmed COVID-19 cases. Applied Soft Computing 2022;129:109603 View
  81. Dar J, Ijaz M, Almanjahie I, Farooq M, El-Morshedy M, Bashirov A. Statistical Analysis of the COVID-19 Mortality Rates with Probability Distributions: The Case of Pakistan and Afghanistan. Computational and Mathematical Methods in Medicine 2022;2022:1 View
  82. Kumar P, Aishwarya , Srivastava P, Pandey M, Anand A, Biswas J, Drews M, Dobriyal M, Singh R, De la Sen M, Singh S, Pandey A, Kumar M, Rani M. Nitrogen dioxide as proxy indicator of air pollution from fossil fuel burning in New Delhi during lockdown phases of COVID-19 pandemic period: impact on weather as revealed by Sentinel-5 precursor (5p) spectrometer sensor. Environment, Development and Sustainability 2023;26(3):6623 View
  83. Wang Y, Li K, Yuan T, Liu Y. Quantitatively evaluate the impact of domestic aviation control measures on the spread of COVID-19 in China. Scientific Reports 2022;12(1) View
  84. de Souza D, dos Santos E, Alves Júnior F, Nascimento M. On Comparing Cross-Validated Forecasting Models with a Novel Fuzzy-TOPSIS Metric: A COVID-19 Case Study. Sustainability 2021;13(24):13599 View
  85. Liu X, Wang W, Yang Y, Hou B, Olasehinde T, Feng N, Dong X. Nesting the SIRV model with NAR, LSTM and statistical methods to fit and predict COVID-19 epidemic trend in Africa. BMC Public Health 2023;23(1) View
  86. Griette Q, Demongeot J, Magal P. What can we learn from COVID-19 data by using epidemic models with unidentified infectious cases?. Mathematical Biosciences and Engineering 2021;19(1):537 View
  87. Romero García C, Briz-Redón Á, Iftimi A, Lozano M, De Andrés J, Landoni G, Zanin M. Understanding small-scale COVID-19 transmission dynamics with the Granger causality test. Archives of Environmental & Occupational Health 2023;78(5):273 View
  88. Kieu Q, Nguyen T, Hoang A. Gis And Remote Sensing: A Review Of Applications To The Study Of The Covid-19 Pandemic. GEOGRAPHY, ENVIRONMENT, SUSTAINABILITY 2021;14(4):117 View
  89. Vahedi B, Karimzadeh M, Zoraghein H. Spatiotemporal prediction of COVID-19 cases using inter- and intra-county proxies of human interactions. Nature Communications 2021;12(1) View
  90. Cinaglia P, Cannataro M. Forecasting COVID-19 Epidemic Trends by Combining a Neural Network with Rt Estimation. Entropy 2022;24(7):929 View
  91. Wang Y, Xu C, Yao S, Wang L, Zhao Y, Ren J, Li Y. Estimating the COVID-19 prevalence and mortality using a novel data-driven hybrid model based on ensemble empirical mode decomposition. Scientific Reports 2021;11(1) View
  92. Chin W, Chan C. Analyzing the Trends of COVID-19 and Human Activity Intensity in Malaysia. Tropical Medicine and Infectious Disease 2023;8(2):72 View
  93. Lv C, An S, Qiao B, Wu W. Time series analysis of hemorrhagic fever with renal syndrome in mainland China by using an XGBoost forecasting model. BMC Infectious Diseases 2021;21(1) View
  94. Cai M, Luo H, Cui Y, Bueno A. [Retracted] A Study on the Topic‐Sentiment Evolution and Diffusion in Time Series of Public Opinion Derived from Emergencies. Complexity 2021;2021(1) View
  95. Tan C, Singh S, Lai C, Zamri A, Dass S, Aris T, Ibrahim H, Gill B. Forecasting COVID-19 Case Trends Using SARIMA Models during the Third Wave of COVID-19 in Malaysia. International Journal of Environmental Research and Public Health 2022;19(3):1504 View
  96. Comito C, Pizzuti C. Artificial intelligence for forecasting and diagnosing COVID-19 pandemic: A focused review. Artificial Intelligence in Medicine 2022;128:102286 View
  97. Martins V, Branco D, Hallack M. Economic Effects of Micro- and Mini-Distributed Photovoltaic Generation for the Brazilian Distribution System. Energies 2022;15(3):737 View
  98. Silva A, Araújo A, Frias P, Vilela M, Bonfim C. Auto-Regressive Integrated Moving Average Model (ARIMA): conceptual and methodological aspects and applicability in infant mortality. Revista Brasileira de Saúde Materno Infantil 2021;21(2):647 View
  99. Rizwan Hassan S, Ahmad I, Nebhen J, Ur Rehman A, Shafiq M, Choi J. Prediction of COVID-19 Transmission in the United States Using Google Search Trends. Computers, Materials & Continua 2022;71(1):1751 View
  100. Muhaidat J, Albatayneh A, Abdallah R, Papamichael I, Chatziparaskeva G. Predicting COVID-19 future trends for different European countries using Pearson correlation. Euro-Mediterranean Journal for Environmental Integration 2022;7(2):157 View
  101. Liu T, Liu X, Li Y, Liu S, Cao C. Evolving Trends and Research Hotspots in Disaster Epidemiology From 1985 to 2020: A Bibliometric Analysis. Frontiers in Public Health 2021;9 View
  102. Vaughan L, Zhang M, Gu H, Rose J, Naughton C, Medema G, Allan V, Roiko A, Blackall L, Zamyadi A. An exploration of challenges associated with machine learning for time series forecasting of COVID-19 community spread using wastewater-based epidemiological data. Science of The Total Environment 2023;858:159748 View
  103. Abugabah A, Shahid F. Intelligent Health Care and Diseases Management System: Multi-Day-Ahead Predictions of COVID-19. Mathematics 2023;11(4):1051 View
  104. BAYRAM G, YURTSEVER Ö. Efficiency Evaluation of European Countries in terms of COVID-19. International Journal of Advances in Engineering and Pure Sciences 2021;33(3):366 View
  105. Lai H, Tao Y, Shen M, Li R, Zou M, Zhang L, Zhang L. What Is the Impact of Early and Subsequent Epidemic Characteristics on the Pre-delta COVID-19 Epidemic Size in the United States?. Pathogens 2022;11(5):576 View
  106. Permpoonsinsup W, Sunthornwat R. Modified exponential time series model with prediction of total COVID-19 cases in Belgium, Czech Republic, Poland and Switzerland. Statistics in Transition New Series 2022;23(3):147 View
  107. Comito C. How COVID-19 Information Spread in U.S.? The Role of Twitter as Early Indicator of Epidemics. IEEE Transactions on Services Computing 2022;15(3):1193 View
  108. Khan F, Lounis M. Short-term forecasting of daily infections, fatalities and recoveries about COVID-19 in Algeria using statistical models. Beni-Suef University Journal of Basic and Applied Sciences 2021;10(1) View
  109. Hasan I, Dhawan P, Rizvi S, Dhir S. Data analytics and knowledge management approach for COVID-19 prediction and control. International Journal of Information Technology 2023;15(2):937 View
  110. Andrianajaina T, Razafimahefa D, Rakotoarijaina R, Haba C. Grid Search for SARIMAX Parameters for Photovoltaic Time Series Modeling. Global Journal of Energy Technology Research Updates 2022;9:87 View
  111. Uddin M. The moderating role of COVID-19 pandemic on the relationship between CEO characteristics and earnings management: evidence from Bangladesh. Cogent Business & Management 2023;10(1) View
  112. Ahmadi M, Mousavi Z, Khorasani P. INDIVIDUAL AND OCCUPATIONAL COMPONENTS AFFECTING THE QUALITY OF WORK LIFE OF NURSES IN THE COVID-19 PATIENTS CARE UNIT. Nursing and Midwifery Journal 2022;20(6):446 View
  113. de la Vega J, Riba J, Ortega-Redondo J. Mathematical Modeling of Battery Degradation Based on Direct Measurements and Signal Processing Methods. Applied Sciences 2023;13(8):4938 View
  114. Chakraborty D, Goswami D, Ghosh S, Ghosh A, Chan J, Wang L. Transfer-recursive-ensemble learning for multi-day COVID-19 prediction in India using recurrent neural networks. Scientific Reports 2023;13(1) View
  115. Sarmiento Varón L, González-Puelma J, Medina-Ortiz D, Aldridge J, Alvarez-Saravia D, Uribe-Paredes R, Navarrete M. The role of machine learning in health policies during the COVID-19 pandemic and in long COVID management. Frontiers in Public Health 2023;11 View
  116. Cheng X. Use the ARIMA and EMG Models to Predict the Confirmed Cases and ICU Bed Occupancy Data of COVID-19 in Massachusetts and Compare the Accuracy of the Two Models. Highlights in Science, Engineering and Technology 2023;47:194 View
  117. Kiganda C, Akcayol M. Forecasting the Spread of COVID-19 Using Deep Learning and Big Data Analytics Methods. SN Computer Science 2023;4(4) View
  118. Ali Nasser Aldine A. Forecasting Lebanese stocks using ARIMA models. Digital models and solutions 2023;2(1) View
  119. Ma Y, Xu S, Luo Y, Qin Y, Li J, Lei L, He L, Wang T, Yu H, Xie J. Epidemiological characteristics and transmission dynamics of the COVID-19 outbreak in Hohhot, China: a time-varying SQEIAHR model analysis. Frontiers in Public Health 2023;11 View
  120. Teng Y, Jian Y, Chen X, Li Y, Han B, Wang L. Comparison of Three Prediction Models for Predicting Chronic Obstructive Pulmonary Disease in China. International Journal of Chronic Obstructive Pulmonary Disease 2023;Volume 18:2961 View
  121. Lee B, Song H, Apio C, Han K, Park J, Liu Z, Xuwen H, Park T. An analysis of the waning effect of COVID-19 vaccinations. Genomics & Informatics 2023;21(4):e50 View
  122. Khan A. The Role of Predictive Models in Shaping Health-care Policies during COVID-19 Pandemics: Lessons Learned and Future Directions. Journal of Nature and Science of Medicine 2024;7(1):1 View
  123. Zakharov V, Ndiaye S. Two Epidemic Models of Malaria and Their Practical Applications. Doklady Mathematics 2023;108(S1):S8 View
  124. Chen B, Chen R, Zhao L, Ren Y, Zhang L, Zhao Y, Lian X, Yan W, Gao S. High-resolution short-term prediction of the COVID-19 epidemic based on spatial-temporal model modified by historical meteorological data. Fundamental Research 2024;4(3):527 View
  125. Economou F, Chatziparaskeva G, Papamichael I, Loizia P, Voukkali I, Navarro-Pedreño J, Klontza E, Lekkas D, Naddeo V, Zorpas A. The concept of food waste and food loss prevention and measuring tools. Waste Management & Research: The Journal for a Sustainable Circular Economy 2024;42(8):651 View
  126. Shur M. Pandemic Equation and COVID-19 Evolution. Encyclopedia 2024;4(2):682 View
  127. Yang N, Hong R, Chen P, liu Z. An Integrated Reservoir Predictor Based on Spatiotemporal Information Transformation. International Journal of Bifurcation and Chaos 2024;34(04) View
  128. Uwimana A, Mukamana L, Ruranga C, Nzabanita J, Jansen S, Masabo E, Kabano I, Claude S, Rubagiza J, Abdallah J, Mugeni R, Nishimwe A, Mutezimana E, Twizeyimana L, Bahati O, Akili V, Musanabaganwa C, Rukundo G, Semakula M, Twagirumukiza M. Assessment of the socioeconomic impact of COVID-19 in Rwanda: Findings from a country-wide community survey, preliminary analysis to inform further global research. Research in Globalization 2024;8:100230 View
  129. Shi Y, Chen Q, Li Q, Luan H, Wang Q, Hu Y, Gao F, Sai X. EpiRiskNet: incorporating graph structure and static data as prior knowledge for improved time-series forecasting. Applied Intelligence 2024;54(17-18):7864 View
  130. Li X, Liu Z, Ge F, Sun G. [Retracted] A Multiobjective Optimization Model for Prevention and Control of Coronavirus Disease 2019 in China. Discrete Dynamics in Nature and Society 2022;2022(1) View
  131. Chen J, Shi X, Zhang H, Li W, Li P, Yao Y, Miyazawa S, Song X, Shibasaki R. MobCovid: Confirmed Cases Dynamics Driven Time Series Prediction of Crowd in Urban Hotspot. IEEE Transactions on Neural Networks and Learning Systems 2024;35(10):13397 View
  132. Abdul Rahman A, Rajasekaran G, Ramalingam R, Meero A, Seetharaman D. From Data to Diagnosis: Machine Learning Revolutionizes Epidemiological Predictions. Information 2024;15(11):719 View
  133. Babanejaddehaki G, An A, Papagelis M. Disease Outbreak Detection and Forecasting: A Review of Methods and Data Sources. ACM Transactions on Computing for Healthcare 2024 View

Books/Policy Documents

  1. Lv Y, Ren H, Gao X, Sun T, Zhang H, Guo X. Verification and Evaluation of Computer and Communication Systems. View
  2. Kar A, Kar A. Proceedings of International Conference on Computational Intelligence, Data Science and Cloud Computing. View
  3. Majumder P, Ray P. Artificial Intelligence for Information Management: A Healthcare Perspective. View
  4. Sanchez-Daza A, Medina-Ortiz D, Olivera-Nappa A, Contreras S. Modeling, Control and Drug Development for COVID-19 Outbreak Prevention. View
  5. Rodriguez-Morales A, Bonilla-Aldana D. Pandemic Outbreaks in the 21st Century. View
  6. Singh R, Kumar P, Kumar M, Tyagi K, Jain H. Sustainable Agriculture Systems and Technologies. View
  7. Xiu Y, Chan W. AI and Analytics for Public Health. View
  8. Fong S, Marques J, Li G, Dey N, Crespo R, Herrera-Viedma E, Gois F, Neto J. Epidemic Analytics for Decision Supports in COVID19 Crisis. View
  9. Lukman A, Benedicta A, Awotunde J, Okon C, Oludoun O, Oluwakemi A, Ayinde O, Alabi O, Adeniyi A. Modeling, Control and Drug Development for COVID-19 Outbreak Prevention. View
  10. Mohanty A, Sahoo S, Taunk A, Garnayak M, Choudhury S. Handbook of Research on Mathematical Modeling for Smart Healthcare Systems. View
  11. Bharathi M, Meghana Kumar K. IOT with Smart Systems. View
  12. Khanna S, Garg M, Aggarwal S, Thakur H. Proceedings of the International Health Informatics Conference. View
  13. Cao L. Global COVID-19 Research and Modeling. View
  14. Rosser P, Soler S. Safeguarding the World Culture Heritage - Advances and New Perspectives [Working Title]. View
  15. Sayed G, Hassanien A. Artificial Intelligence for Environmental Sustainability and Green Initiatives. View
  16. Cinaglia P. Reference Module in Life Sciences. View