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Incidence rate estimation, periodic testing and the limitations of the mid-point imputation approach
Alain Vandormael1,2, Adrian Dobra3, Till Bärnighausen1,4,5,6
1Africa Health Research Institute, KwaZulu-Natal, South Africa.
Background:
It is common to use the mid-point between the latest-negative and earliest-positive test dates as the date of the infection event. However, the accuracy of the mid-point method has yet to be systematically quantified for incidence studies once participants start to miss their scheduled test dates.
Methods:
We used a simulation-based approach to generate an infectious disease epidemic for an incidence cohort with a high (80-100%), moderate (60-79.9%), low (40-59.9%) and poor (30-39.9%) testing rate. Next, we imputed a mid-point and random-point value between the participant's latest-negative and earliest-positive test dates. We then compared the incidence rate derived from these imputed values with the true incidence rate generated from the simulation model.
Results:
The mid-point incidence rate estimates erroneously declined towards the end of the observation period once the testing rate dropped below 80%. This decline was in error of approximately 9%, 27% and 41% for a moderate, low and poor testing rate, respectively. The random-point method did not introduce any systematic bias in the incidence rate estimate, even for testing rates as low as 30%.
Conclusions:
The mid-point assumption of the infection date is unjustified and should not be used to calculate the incidence rate once participants start to miss the scheduled test dates. Under these conditions, we show an artefactual decline in the incidence rate towards the end of the observation period. Alternatively, the single random-point method is straightforward to implement and produces estimates very close to the true incidence rate.
Insights
The mid-point method for estimating infection dates in incidence studies is inaccurate when participants miss tests, leading to false declines in infection rates. A random-point imputation method provides more reliable incidence rate estimates, even with poor testing adherence.
Area of Science:
- Epidemiology
- Biostatistics
Background:
- Estimating infection event dates is crucial for incidence studies.
- The common mid-point method (between latest-negative and earliest-positive tests) lacks systematic accuracy assessment, especially with missed appointments.
Purpose of the Study:
- To evaluate the accuracy of the mid-point method for infection date imputation in incidence studies.
- To compare the mid-point method with a random-point imputation method under varying testing rates.
Main Methods:
- A simulation approach generated an epidemic in an incidence cohort.
- Infection dates were imputed using both mid-point and random-point methods.
- Incidence rates from imputed dates were compared to true simulated rates across different testing rates (high, moderate, low, poor).
Main Results:
- The mid-point method produced erroneous incidence rate declines (<80% testing rate), with errors of 9%, 27%, and 41% for moderate, low, and poor testing rates, respectively.
- The random-point method showed no systematic bias in incidence rate estimates, even at 30% testing rates.
Conclusions:
- The mid-point method is unreliable for calculating incidence rates when test adherence declines.
- This method can create artefactual declines in incidence rates.
- The random-point imputation method is a more accurate and straightforward alternative for incidence rate estimation.
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