Fig 1.
Rationale of the method for estimating reporting.
This diagram illustrates transmission events inferred by case investigation of reported secondary cases, with arrows pointing from infectors to infectees. Darker shades are used to indicate documented transmission events, while lighter shades show unknown infectors. Numbers of secondary cases with (blue) or without (orange) known infectors are used to estimate the reporting probability. This example uses an approximate reporting of 50%.
Table 1.
Parameters used for simulating outbreaks.
This table details input parameters used for simulating outbreaks using the R package simulacr. Fixed values were used for all simulations, and reflect the natural history of the 2018–2020 Eastern DRC Ebola outbreak. Variable values changed across simulations.
Table 2.
Metrics used to measure performance in the simulation study.
Fig 2.
Comparison of estimated versus actual reporting.
This graph shows the results of reporting estimated by the method for 4000 simulated outbreaks, broken down by outbreak size category (y-axis). Each dot corresponds to an independent simulation. The vertical red bars indicate the average within each category. True reporting used in the simulations is indicated by colors.
Table 3.
Performance measures from 4000 simulation by reported outbreak size and true reporting level.
Estimate (Monte-carlo standard error).
Fig 3.
Zip plot of showing coverage results.
This graph shows the 95% confidence intervals estimated by the method, broken down by reported outbreak size category and true reporting value. The vertical axis represent the fractional centile of |Z| where and π is reporting. The confidence intervals are ranked by their level of coverage and thus the vertical axis can be used to determine the proportion of confidence intervals that contain the true value where 0.95 would represent a coverage of 95%.
Fig 4.
Absolute error in reporting estimation.
This graph shows, for different simulation settings, the proportion of results within a given margin of absolute error, expressed as the absolute difference between the true and the estimated reporting (in %). Rows correspond to different outbreak size categories (outbreak size as reported). True reporting is indicated in color.
Table 4.
Comparison of absolute error from 4000 simulations between true reporting levels and estimate of reporting by reported outbreak size and true reporting level.