WHONET is a free desktop Windows application for the management and analysis of microbiology laboratory data with a particular focus on antimicrobial resistance surveillance developed and supported by the WHO Collaborating Centre for Surveillance of Antimicrobial Resistance at the Brigham and Women's Hospital in Boston, Massachusetts. WHONET, available in 28 languages, supports local, national, regional, and global surveillance efforts in over 2,300 hospital, public health, animal health, and food laboratories in over 130 countries worldwide.
WHONET also includes a data import module called BacLink for the capture and standardization of data from existing desktop applications, laboratory instruments, and laboratory information systems.
We offer both 32-bit and 64-bit versions of WHONET.
Either version should work well for most users.
The 32-bit version of Microsoft Office is more common in the world than the 64-bit version.
So for this reason, we recommend the 32-bit version of WHONET for most users.
32-bit installation (142 MB)
64-bit installation (145 MB)
Build date: 2020-10-14
We are excited to announce that WHONET offers a new data structure option called SQLite, which offers many advantages over the simple dBASE structure that WHONET has used for many years including:
For many years, WHONET has had the ability to present temporal trends in organism frequencies and resistance proportions in the form of descriptive statistics and graphs. The user could then examine these trends and graphs individually in efforts to detect and characterize possible community or hospital outbreaks of microorganisms. WHONET was not able to highlight potential clusters in an automatic fashion in order to focus the attention of the software user on possible outbreaks or to provide statistical guidance as to whether observed trends were statistically significant.
To facilitate the early and broad detection of possible outbreaks, we have integrated a powerful freeware tool developed for purposes of cluster detection in public health data.
SaTScan™, a trademark of Martin Kulldorf, was developed under the joint auspices of Martin Kulldorf, of the National Cancer Institute and of Farzad Mostarashi at the New York City Department of Health and Mental Hygiene. Dr. Kulldorf is an Associate Professor and Biostatistician at Harvard Medical School and Harvard Pilgrim Health Care, Department of Ambulatory Care and Prevention, Boston, USA.
Kulldorf M. and Information Management Services, Inc. SaTScan™ v.7.0: Software for the spatial and time-scan statistics. http://www.satscan.org
Another useful feature of WHONET is the creation of lists of isolates or patients that meet certain criteria – for example a lists of patients with MRSA or positive blood cultures from the neonatal intensive care unit. WHONET can create such lists as well as summarize the results in a number of different ways.
Click on “Analysis type”, and select “Isolate listing and summary”. For the summary, by default WHONET will use the variable “Organism” for the rows and “Specimen date” by month for the columns.
For this tutorial, make one small change to the options. Next to specimen date appears the option “Month”. Because there is only one month of data to analyze in this tutorial, it will be more interesting to show the results by day or by week. Select the option “Day”. Leave the other options unchanged, and click “OK”. Click on “Begin analysis”. In this example, WHONET will show you a list of all isolates from the data set with Enterobacteriaceae, as below.
You can read more about WHONET in our FAQ section.
%RIS and test measurement statistics for Staph. aureus, E. coli, K. pneumoniae, and more. %Resistant results are shown to the left for all antimicrobials, including the 95% confidence interval. The graph to the right depicts the distribution of disk diffusion zone diameters around the gentamicin disk.
You can read more about WHONET in our FAQ section.
Scatterplot comparison of gentamicin and amikacin results for K. pneumoniae. To the left is a comparison of the disk diffusion zone diameter results. To the right is the comparison using the test interpretations – resistance, intermediate, and susceptible.
The software permits a number of algorithms for the detection of event clusters. Options include retrospective or prospective cluster detection; purely temporal, pure spatial, or space-time clusters; and flexible parameter selection for space and time variables.
In this first version of an integrated WHONET-SaTScan package, WHONET is using a space-time permutation probability model, using Monte Carlo simulations. In collaboration with Dr. Kulldorf in a five-year NIH project entitled “Modeling Infectious Disease Agent Study” (MIDAS), we will test out a number of additional algorithms, models, and parameters, and these optimized routines will eventually be offered through the WHONET user interface.
Cluster detection for the Infection Preventionist or Quality Departments! Automated daily data extractions from your system into WHONET. WHONET-SaTScan uses the space and time poisson modal to statistically detect potential cluster signals for the Infection Preventionists review and follow up.
Was this signal something you wanted to know? You may never know...Real time outbreak detection is possible with WHONET. Let us set it up for you!
You can find additional information about GLASS below:
GLASS aims to combine clinical, laboratory and epidemiological data on pathogens that pose the greatest threats to health globally. The GLASS manual details the proposed approach for the early implementation of the surveillance system, that will focus on antibiotic-resistant bacteria, and outlines the flexible and incremental development of the system over time that will incorporate lessons learned from the early implementation phase.
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