Correction: Real-Time Forecasting of the COVID-19 Outbreak in Chinese Provinces: Machine Learning Approach Using Novel Digital Data and Estimates From Mechanistic Models (Preprint)

Abstract

BACKGROUND The inherent difficulty of identifying and monitoring emerging outbreaks caused by novel pathogens can lead to their rapid spread; and if left unchecked, they may become major public health threats to the planet. The ongoing coronavirus disease (COVID-19) outbreak, which has infected over 2,300,000 individuals and caused over 150,000 deaths, is an example of one of these catastrophic events. OBJECTIVE We present a timely and novel methodology that combines disease estimates from mechanistic models and digital traces, via interpretable machine learning methodologies, to reliably forecast COVID-19 activity in Chinese provinces in real time. METHODS Our method uses the following as inputs: (a) official health reports, (b) COVID-19–related internet search activity, (c) news media activity, and (d) daily forecasts of COVID-19 activity from a metapopulation mechanistic model. Our machine learning methodology uses a clustering technique that enables the exploitation of geospatial synchronicities of COVID-19 activity across Chinese provinces and a data augmentation technique to deal with the small number of historical disease observations characteristic of emerging outbreaks. RESULTS Our model is able to produce stable and accurate forecasts 2 days ahead of the current time and outperforms a collection of baseline models in 27 out of 32 Chinese provinces. CONCLUSIONS Our methodology could be easily extended to other geographies currently affected by COVID-19 to aid decision makers with monitoring and possibly prevention.

COVID-19 From Symptoms to Prediction: A Statistical and Machine Learning Approach

“…The contribution of AI & ML has resulted in several digital solutions to help o cials reduce COVID-19's impact on society. Developing smart applications [9], predicting future cases [10], applying smart surveillance systems for contact tracing [11], improving testing capabilities [12], and increasing smart diagnostic systems [13] are some of the fresh ideas proposed by AI and ML research communities.…”

The Needs Analysis of the Android-based Online Psychological Assessment Applications Usage for School Counselors in West Sumatra

“…The "classic" assessment and measurement process in the form of a Paper and Pencil Test (PPT) also makes assessment activities inefficient in terms of time and resources used (Ardi, Febriani, et al, 2019;Ardi & Putri, 2020;Bacca-Acosta & Avila-Garzon, 2020;Bai, Elavsky, Kishida, Dvořáková, & Greenberg, 2020;Hamilton et al, 2020). Coupled with the current state of the Covid-19 pandemic, it worsens the condition of psychological assessments in the field, especially for students and other counseling service targets (Ifdil, Fadli, Suranata, Zola, & Ardi, 2020;Liu et al, 2020). The Covid-19 pandemic has made the assessment process no longer able to be done conventionally and must move to a face-to-face process to a digital process.…”