Mosquito Surveillance Software

Click here to access the R package PooledInfRate for download from GitHub/CDCgov (Note: The R package will be updated as needed. Check this web page for updates.)

Click here to download Windows Excel 2000/2003 v4 ZIP file. [Zip – 1.43MB]* (Note: This version is operable in Excel 2000 and up to at least Excel Office 365.)

Click here to download Windows Excel 2007 v4 ZIP file. [Zip – 1.53MB]*

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 incorporate 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, traditional 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.

CDC has developed easy-to-use programs for calculating IR estimates from mosquito pool data using methods that do not require the assumption used in the MIR calculation. These programs also include 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.

Two software formats are available. The first is the program and instructions contained in the downloadable zip files above. 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 (see the references in the software documentation).

The second format is as a “package” called PooledInfRate for the R software system. You can access this package on the CDC GitHub site (also see above). Installation instructions are available on the CDC GitHub site, and a package vignette is provided to illustrate usage. Standard R system help pages are for included functions. In addition to the estimation functionality available in the Excel add-in, this R package software includes updated estimation methodology to include Firth’s correction and estimation when using an imperfect test. Further, functionality to compute the commonly used Vector Index is included. See the references cited in the help pages and package vignette for details.


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