| Present patient |
Random forest variable importance screening was used to screen variables for fitting a logistic regression model from the GEMS data including only five clinical variables (selected from candidate variables which would be accessible to clinicians at the point-of-care) Brintz et al., 2021. The five variables include: age, blood in stool (yes/no), vomiting (yes/no), breastfeeding status (yes/no), and mid-upper arm circumference (MUAC; as measured in cm) |
| Viral seasonality |
This model included the standardized seasonal sine and cosine curves modeling the country-specific seasonal patterns of viral diarrhea |
| Climate |
This model included rain and temperature averages using a two-week aggregation of the five nearest National Oceanic and Atmospheric Administration (NOAA)-affiliated weather stations to the hospital sites. |
| Historical patient (Pre-test odds) |
Pre-test odds were generated using historical rates of viral diarrhea by site and date using data from the GEMS study. |
| Recent patient (Pre-test odds) |
Pre-test odds were generated using data from patients in the prior four weeks. |
