Comprehensive reports on loop performance are generated periodically.
Subsequently, through methods of abduction, new vocabularies of form and potentials in performance are generated primarily through computational exploration.
Since the global data indicated that ripples stayed elevated for at least two successive days of learning (day 6 and 7), a similar plot for the day following the highest ripple density and subsequent behavioral performance was generated (Fig. 5B).
CHW performance was generated by three indicators: reporting rate, health knowledge and household coverage.
A 13-variable model with strong predictive performance was generated using a forward search strategy (mean AUC = 0.673).
More detailed breakdowns of performance were generated by calculating the proportion of times districts were correctly classified within narrower prevalence bins (2.5%), across all simulations.
An indicator on the CHWs' performance was generated by using both frequency of visitation to households and the satisfaction score as reported by the target mothers.
Finally, the variable of the CHWs' performance was generated by adding the score of the household visitation and the score of satisfaction, and categorized into five quintiles as: poorest (0), poor (1), moderate (2), high (3) and highest (4).
Routine data management and regular reports to track the accrual of patients and quality indicators of study performance are generated by EMMES and shared with the PERCH core team at JHSPH and with the site investigators.
