Mosquito Surveillance Software
Mosquito-based arbovirus surveillance data are useful in tracking virus activity. The most basic form of mosquito-based surveillance data presentation – and that currently used by CDC’s ArboNET system – is the number of positive mosquito pools found in collections of a particular mosquito species over a defined time period and area.
CDC encourages surveillance programs to routinely incorporate a more informative index of relative virus activity, the virus infection rate (IR), into their mosquito-based evaluation of local virus activity patterns. At the county level or below, weekly tracking of mosquito IR can provide important predictive indicators of transmission activity levels associated with elevated human risk.
Estimates of the IR are usually presented as the number of infected mosquitoes per 1,000 tested. The simplest estimate, the minimum infection rate (MIR), is calculated: ([number of positive pools / total specimens tested] x 1000), with the data representing a single species or species group collected over a time period and geographic area relevant to the goals of the surveillance program. The MIR uses the assumption that a positive pool contains only one infected mosquito, an assumption that may be invalid when infection rates are high, as has been observed during West Nile virus epidemics.
Dr. Brad Biggerstaff, Mathematical Statistician at CDC/DVBD, developed an easy-to-use program for calculating IR estimates from mosquito pool data using methods that do not require the assumption used in the MIR calculation. This program also includes calculation of confidence intervals which reflect, in part, the sample sizes used in the calculations. The confidence intervals (or any other uncertainty measure) are essential for interpreting the precision of the IR estimate.
The program and instructions are contained in the downloadable zip file below. Written for Excel 2000, this Excel add-in computes point and confidence interval estimates of IRs (i.e., infection prevalence) using data from pooled samples, where pool sizes may differ. Bias-corrected likelihood methods are used to estimate infection rate, and a skew-corrected score confidence interval is computed by default. Traditional methods using the MIR are available for comparison.
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- Page last reviewed: February 21, 2018
- Page last updated: February 12, 2015
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