Forensic Entomology: Evaluating Uncertainty Associated With Postmortem Interval (PMI) Estimates With Ecological Models. Academic Article uri icon


  • Estimates of insect age can be informative in death investigations and, when certain assumptions are met, can be useful for estimating the postmortem interval (PMI). Currently, the accuracy and precision of PMI estimates is unknown, as error can arise from sources of variation such as measurement error, environmental variation, or genetic variation. Ecological models are an abstract, mathematical representation of an ecological system that can make predictions about the dynamics of the real system. To quantify the variation associated with the pre-appearance interval (PAI), we developed an ecological model that simulates the colonization of vertebrate remains by Cochliomyia macellaria (Fabricius) (Diptera: Calliphoridae), a primary colonizer in the southern United States. The model is based on a development data set derived from a local population and represents the uncertainty in local temperature variability to address PMI estimates at local sites. After a PMI estimate is calculated for each individual, the model calculates the maximum, minimum, and mean PMI, as well as the range and standard deviation for stadia collected. The model framework presented here is one manner by which errors in PMI estimates can be addressed in court when no empirical data are available for the parameter of interest. We show that PAI is a potential important source of error and that an ecological model is one way to evaluate its impact. Such models can be re-parameterized with any development data set, PAI function, temperature regime, assumption of interest, etc., to estimate PMI and quantify uncertainty that arises from specific prediction systems.

published proceedings

  • J Med Entomol

altmetric score

  • 0.75

author list (cited authors)

  • Faris, A. M., Wang, H., Tarone, A. M., & Grant, W. E.

citation count

  • 8

complete list of authors

  • Faris, AM||Wang, H-H||Tarone, AM||Grant, WE

publication date

  • September 2016