ArticleScientific reports2021
Improving prediction of COVID-19 evolution by fusing epidemiological and mobility data.
Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.
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Who cites it
24 citing papers in PubMed.
- Explaining COVID-19 dynamics through user activity data from digital platforms with Yandex's self-isolation index as a case study.Scientific reports · 2025Article
- Inferring the timing of individual mobility decisions from accommodation reservation data during the COVID-19 outbreak.Royal Society open science · 2025Article
- A graph-theoretic framework for integrating mobility data into mathematical epidemic models.Infectious Disease Modelling · 2025Article
- Article
- Risk Index of Regional Infection Expansion of COVID-19: Moving Direction Entropy Study Using Mobility Data and Its Application to Tokyo.JMIR public health and surveillance · 2024Article
- Forecasting the spread of COVID-19 based on policy, vaccination, and Omicron data.Scientific reports · 2024Article
- Is it possible to estimate the number of patients with COVID-19 admitted to intensive care units and general wards using clinical and telemedicine data?Einstein (Sao Paulo, Brazil) · 2024Article
- A mixture of mobility and meteorological data provides a high correlation with COVID-19 growth in an infection-naive population: a study for Spanish provinces.Frontiers in public health · 2024Article
- Real-time forecasting of COVID-19 spread according to protective behavior and vaccination: autoregressive integrated moving average models.BMC public health · 2023Article
- Vector Autoregression for Forecasting the Number of COVID-19 Cases and Analyzing Behavioral Indicators in the Philippines: Ecologic Time-Trend Study.JMIR formative research · 2023Article
- The Effectiveness of Mobility Restrictions on Controlling the Spread of COVID-19 in a Resistant Population.International journal of environmental research and public health · 2023Article
- Concentration and size distribution of atmospheric particles in southern Italy during COVID-19 lockdown period.Atmospheric environment (Oxford, England : 1994) · 2023Article
- Replacing discontinued Big Tech mobility reports: a penetration-based analysis.Scientific reports · 2023Article
- Article
- How the Stringency of the COVID-19 Restrictions Influences Motivation for Adherence and Well-Being: The Critical Role of Proportionality.International journal of health policy and management · 2023Article
- Forecasting daily COVID-19 cases with gradient boosted regression trees and other methods: evidence from U.S. cities.Frontiers in public health · 2023Article
- Robust time-series analysis of the effects of environmental factors on the CoViD-19 pandemic in the area of Milan (Italy) in the years 2020-21.Hygiene and environmental health advances · 2022Article
- Development of forecast models for COVID-19 hospital admissions using anonymized and aggregated mobile network data.Scientific reports · 2022Article
- Meteorological factors and non-pharmaceutical interventions explain local differences in the spread of SARS-CoV-2 in Austria.PLoS computational biology · 2022Article
- Using a stochastic continuous-time Markov chain model to examine alternative timing and duration of the COVID-19 lockdown in Kuwait: what can be done now?Archives of public health = Archives belges de sante publique · 2022Article
Corrections and comments
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Authors and funding
8 authors.
Funding
Abstract
We are witnessing the dramatic consequences of the COVID-19 pandemic which, unfortunately, go beyond the impact on the health system. Until herd immunity is achieved with vaccines, the only available mechanisms for controlling the pandemic are quarantines, perimeter closures and social distancing with the aim of reducing mobility. Governments only apply these measures for a reduced period, since they involve the closure of economic activities such as tourism, cultural activities, or nightlife. The main criterion for establishing these measures and planning socioeconomic subsidies is the evolution of infections. However, the collapse of the health system and the unpredictability of human behavior, among others, make it difficult to predict this evolution in the short to medium term. This article evaluates different models for the early prediction of the evolution of the COVID-19 pandemic to create a decision support system for policy-makers. We consider a wide branch of models including artificial neural networks such as LSTM and GRU and statistically based models such as autoregressive (AR) or ARIMA. Moreover, several consensus strategies to ensemble all models into one system are proposed to obtain better results in this uncertain environment. Finally, a multivariate model that includes mobility data provided by Google is proposed to better forecast trend changes in the 14-day CI. A real case study in Spain is evaluated, providing very accurate results for the prediction of 14-day CI in scenarios with and without trend changes, reaching 0.93 [Formula: see text], 4.16 RMSE and 1.08 MAE.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.