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Meeting Global Health Needs via Infectious Disease Forecasting: Development of a Reliable Data-Driven Framework

Meeting Global Health Needs via Infectious Disease Forecasting: Development of a Reliable Data-Driven Framework

The table was originally published by Dixon et al [5]. a N/A: not applicable. The harvested raw data contained information at varied spatial and temporal resolutions in different file formats. These raw data were harmonized to create the final datasets containing monthly case counts and input features for each region within the country. In situations where the feature data at the regional level were missing, the features aggregated by an average at the national level were used.

Ravikiran Keshavamurthy, Karl T Pazdernik, Colby Ham, Samuel Dixon, Samantha Erwin, Lauren E Charles

JMIR Public Health Surveill 2025;11:e59971

Identifying Weekly Trajectories of Pain Severity Using Daily Data From an mHealth Study: Cluster Analysis

Identifying Weekly Trajectories of Pain Severity Using Daily Data From an mHealth Study: Cluster Analysis

However, the age, sex, and chronic pain conditions of respondents in the main analysis and transition analysis (Multimedia Appendix 4) were similar to those in the full-study population (see the first supplementary in the study by Dixon et al [16]), suggesting that the included participants were representative of the study population. There were limitations in the method used for clustering.

Claire L Little, David M Schultz, Thomas House, William G Dixon, John McBeth

JMIR Mhealth Uhealth 2024;12:e48582