Data Analytics for Predicting COVID-19 Cases in Top Affected Countries: Observations and Recommendations

This article looks at traditional ways of reporting COVID-19 case data through a look at historical data and improves upon the methodology by analyzing both historical data and other external factors. The study team developed a nonlinear autoregressive exogenous input (NARX) neural network-based algorithm that, when compared to traditional data collection in other countries, offers more accurate and viable results.

Resource Details

• Setting/Context of Implementation: Community
• Topics of Practice: Data Collection and Analysis
• Outcomes of Interest: Improve Data Infrastructure
• Level of Evidence: Emerging
• Tools or Materials Included in Resource: No
• Outside of US: No