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

The clustering modeling approach, which incorporated internet-based data sources as the ARGO-type models, produced forecasts that led to error reductions for 17 out of 32 provinces compared to the persistence model and improved correlation values in 20 out

Dianbo Liu, Leonardo Clemente, Canelle Poirier, Xiyu Ding, Matteo Chinazzi, Jessica Davis, Alessandro Vespignani, Mauricio Santillana

J Med Internet Res 2020;22(8):e20285

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Evaluating the Need for Routine COVID-19 Testing of Emergency Department Staff: Quantitative Analysis

the general population, since completely healthy individuals without any acute illness or injury would not visit the ED.In addition, since the two hospitals were unlikely to have significant changes in their employment in the time period for which we were modeling

Yuemei Zhang, Sheng-Ru Cheng

JMIR Public Health Surveill 2020;6(4):e20260

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Dynamics and Development of the COVID-19 Epidemic in the United States: A Compartmental Model Enhanced With Deep Learning Techniques

data for Wuhan and Shanghai and contact tracing information from Hunan Province, a group of researchers built a transmission model to study the impact of social distancing and school closure [18].Theoretical FoundationCompartmental models dominate epidemic modeling

Qi Deng

J Med Internet Res 2020;22(8):e21173

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Multiple Epidemic Wave Model of the COVID-19 Pandemic: Modeling Study

Recent approaches consider mobility and contact networks [10,11], epidemic waves attributable to community networks [12], subepidemic modeling [13], Bayesian modeling and inference [14], models of spatial contacts in large-scale artificial cities [15], and

Efthimios Kaxiras, Georgios Neofotistos

J Med Internet Res 2020;22(7):e20912

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Predictive Modeling for Frailty Conditions in Elderly People: Machine Learning Approaches

Furthermore, patient information such as gender can be included in the study in order to understand gender-related factors for frailty and their impact on hospitalization and mortality among older people.ConclusionsPredictive modeling using the information

Adane Tarekegn, Fulvio Ricceri, Giuseppe Costa, Elisa Ferracin, Mario Giacobini

JMIR Med Inform 2020;8(6):e16678

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Peer Review of “Predicting Health Disparities in Regions at Risk of Severe Illness to Inform Health Care Resource Allocation During Pandemics: Observational Study”

Round 1 ReviewGeneral Comments This study [1] proposes a repeatable modeling process to identify regional population centers with COVID-19 vulnerability using linear regression.

Ross Gore

JMIRx Med 2020;1(1):e25572

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Health Gain, Cost Impacts, and Cost-Effectiveness of a Mass Media Campaign to Promote Smartphone Apps for Physical Activity: Modeling Study

For modeling parsimony, we assumed that there would be no impact of the modeled intervention on health beyond that captured through the diseases previously mentioned, including no impact on obesity, injury, or mental health outcomes.

Anja Mizdrak, Kendra Telfer, Artur Direito, Linda J Cobiac, Tony Blakely, Christine L Cleghorn, Nick Wilson

JMIR Mhealth Uhealth 2020;8(6):e18014

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Prognostic Modeling of COVID-19 Using Artificial Intelligence in the United Kingdom: Model Development and Validation

From a public health perspective, this would play a significant role in allowing policy makers to respond efficiently to surges of COVID-19, which would otherwise risk overwhelming critical care capacity [16].There have been significant recent advances in modeling

Ahmed Abdulaal, Aatish Patel, Esmita Charani, Sarah Denny, Nabeela Mughal, Luke Moore

J Med Internet Res 2020;22(8):e20259

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Real-World Implications of a Rapidly Responsive COVID-19 Spread Model with Time-Dependent Parameters via Deep Learning: Model Development and Validation

In some of these studies, the model parameters are considered as constants due to the complexity of modeling.

Se Young Jung, Hyeontae Jo, Hwijae Son, Hyung Ju Hwang

J Med Internet Res 2020;22(9):e19907

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Primary Care Pre-Visit Electronic Patient Questionnaire for Asthma: Uptake Analysis and Predictor Modeling

In order to ensure that this assumption was valid, another logistic regression model was constructed as a sensitivity analysis, modeling tablet refusal on only first patient visits, removing any potential residual confounding effects of repeated visits.

Andrew Kouri, Janet Yamada, Joanna E M Sale, Sharon E Straus, Samir Gupta

J Med Internet Res 2020;22(9):e19358

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