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State-specific detection probabilities and disease prevalence.

Christopher S Jennelle¹, Evan G Cooch, Michael J Conroy

¹Department of Natural Resources, Fernow Hall, Cornell University, Ithaca, New York 14853, USA. csj9@cornell.edu

Ecological Applications : a Publication of the Ecological Society of America

|May 8, 2007

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Disease prevalence studies in wild animals often ignore detection differences between infected and uninfected individuals. This can lead to inaccurate disease dynamics, highlighting the need to account for detection probability in ecological studies.

Area of Science:

Ecology
Epidemiology
Wildlife Disease

Background:

Disease dynamics in wild populations are often assessed using estimated prevalence or incidence.
These estimates typically rely on raw counts and may not account for observer detection probability variations.
Heterogeneity in detection probabilities, influenced by biotic/abiotic factors, can bias disease frequency estimates.

Purpose of the Study:

To demonstrate the impact of state-specific detection probability heterogeneity on estimated disease prevalence.
To analyze these effects using mark-recapture data from a House Finch and Mycoplasma gallisepticum system.
To compare corrected prevalence estimates with uncorrected (apparent) prevalence.

Main Methods:

Utilized mark-recapture data from a House Finch population infected with Mycoplasma gallisepticum.

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Estimated state-specific detection probabilities for infected and uninfected individuals.

Compared disease prevalence estimates derived from raw counts versus those corrected for detection probability differences.

Main Results:

Detection probabilities differed between infected and uninfected House Finches, with uninfected individuals generally being more detectable.
Uncorrected prevalence estimates were negatively biased when uninfected individuals had higher detection probabilities.
Seasonal variations in apparent prevalence could be artifacts of changing detection probabilities, not true disease dynamics.

Conclusions:

Accounting for differential detection probabilities is crucial for accurate disease frequency estimation in wild populations.
Ignoring detection heterogeneity can lead to spurious conclusions about disease dynamics and drivers.
While mark-recapture is ideal, alternative methods for estimating detection probabilities should be considered for broader applicability.