The microbiology laboratory database software.

WHONET 2018

This is our NEW version of WHONET. It is a modernized version of WHONET 5.6. In addition to the standard WHONET 5.6 features, this version supports 26 languages and includes new features for exporting to the WHO GLASS data structure. Further information on GLASS can be found using this link.

WHONET 2018 is a desktop application written in Visual Studio 2017 with support for 2018 CLSI and EUCAST breakpoints.

Download

WHONET 2018
Online installation (17.5 MB)
Build date: 2018-10-03
Version: 8.3.12

WHONET 2018
Offline installation (133 MB)
Build date: 2018-10-03
Version: 8.3.12

WHONET WEB

This version of WHONET is still in development. In addition to the standard features of the desktop softwares, For U.S. facilities, WHONET WEB also supports monthly reporting to the CDC’s NHSN project MDRO-CDI reporting module.

WHONET WEB is a web application written in Visual Studio 2017, and can be in installed on a facility’s intranet network or the public internet on a server of your choice. The current demonstration version is available in English only, but multilingual support will be added.

Demo

https://whonetdev.net
Username: demo
Password: WHONETdemo
Build date: 2018-02-04


Requirements documentation

WHONET 5.6

This is the version of WHONET used in over 120 countries and 2,300 laboratories around the world. WHONET 5.6 is a desktop application written in Visual Basic 6 with support for 24 languages and 2018 CLSI and EUCAST breakpoints.

Download

WHONET 5.6
Online installation (18.5 MB)
Build date: 2018-08-15

WHONET 5.6
Offline installation (62.5 MB)
Build date: 2018-08-15

WHONET 5.6
Backup installation (32.8 MB)
Backup version: 2016-05

WHONET-SaTScan | Daily, Weekly, Monthly, Annual Reports

Cluster Alerts

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

Isolate listings

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 Statistics

%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.

WHONET Scatterplot

Scatterplot

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.

Custom macros

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.

Automation

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!

Support for WHO-GLASS export

You can find additional information about GLASS below:

  • WHO-GLASS Export
  • Clinical data
  • Laboratory data
  • Epidemiological data

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.

http://www.who.int/glass/

WHO GLASS

Try our support services and let one of our professionals assist you with your setup.