Prediction and analysis of COVID-19 daily new cases and cumulative cases: times series forecasting and machine learning models

Y Wang, Z Yan, D Wang, M Yang, Z Li, X Gong… - BMC Infectious …, 2022 - Springer
Background COVID-19 poses a severe threat to global human health, especially the USA,
Brazil, and India cases continue to increase dynamically, which has a far-reaching impact on …

[HTML][HTML] Global Infectious Disease Early Warning Models: An Updated Review and Lessons from the COVID-19 Pandemic

WH Hu, HM Sun, YY Wei, YT Hao - Infectious Disease Modelling, 2024 - Elsevier
An early warning model for infectious diseases is a crucial tool for timely monitoring,
prevention, and control of disease outbreaks. The integration of diverse multi-source data …

Informing climate-health adaptation options through mapping the needs and potential for integrated climate-driven early warning forecasting systems in South Asia—A …

FA Asaaga, ES Tomude, NJ Rickards, R Hassall… - Plos one, 2024 - journals.plos.org
Background Climate change is widely recognised to threaten human health, wellbeing and
livelihoods, including through its effects on the emergence, spread and burdens of climate …

Asymptotic analysis of the SIR model and the Gompertz distribution

D Prodanov - Journal of Computational and Applied Mathematics, 2023 - Elsevier
Abstract The SIR (Susceptible–Infected–Removed) is one of the simplest models for
epidemic outbreaks. The present paper derives a novel, simple, analytical asymptotic …

Using weather factors and google data to predict COVID-19 transmission in Melbourne, Australia: A time-series predictive model

H McClymont, X Si, W Hu - Heliyon, 2023 - cell.com
Background Forecast models have been essential in understanding COVID-19 transmission
and guiding public health responses throughout the pandemic. This study aims to assess …

Predicting the spread of SARS-CoV-2 in Italian regions: the Calabria case study, February 2020–March 2022

F Branda, L Abenavoli, M Pierini, S Mazzoli - Diseases, 2022 - mdpi.com
Despite the stunning speed with which highly effective and safe vaccines have been
developed, the emergence of new variants of SARS-CoV-2 causes high rates of (re) …

[HTML][HTML] Learned prediction of cholesterol and glucose using ARIMA and LSTM models–A comparison

U Krishnamoorthy, V Karthika, MK Mathumitha… - Results in Control and …, 2024 - Elsevier
Painless remedies and diagnosis have become the primary objective in medical sciences as
diseases shoot up. This research addresses the pressing need for cost-effective, non …

Computational aspects of the approximate analytic solutions of the SIR model: applications to modelling of COVID-19 outbreaks

D Prodanov - Nonlinear Dynamics, 2023 - Springer
The SIR (susceptible–infected–recovered) is one of the simplest models for epidemic
outbreaks. The present paper demonstrates the parametric solution of the model in terms of …

Statistics did not prove that the Huanan Seafood Wholesale Market was the early epicentre of the COVID-19 pandemic

D Stoyan, SN Chiu - Journal of the Royal Statistical Society …, 2024 - academic.oup.com
In a recent prominent study, Worobey et al.(2022. The Huanan Seafood Wholesale Market in
Wuhan was the early epicenter of the COVID-19 pandemic. Science, 377 (6609), 951–959) …

COVID-19 patterns in araraquara, brazil: A multimodal analysis

DP Aragão, AGS Junior, A Mondini, C Distante… - International Journal of …, 2023 - mdpi.com
The epidemiology of COVID-19 presented major shifts during the pandemic period. Factors
such as the most common symptoms and severity of infection, the circulation of different …