WHONET

WHONET – Getting Started


This tutorial includes the following sections. Click on each seaction to expand the contents:

WHONET is a free software developed by the WHO Collaborating Centre for Surveillance of Antimicrobial Resistance for laboratory-based surveillance of infectious diseases and antimicrobial resistance.

The principal goals of the software are:

  • to enhance local use of laboratory data; and
  • to promote national and international collaboration through the exchange of data.

WHONET can be used by individual laboratories or as part of a national and international surveillance network. At present, the software, available in 17 languages, is used in over 80 countries around the world managing data from over 1000 clinical, public health, veterinary, and food laboratories.

WHONET analytical tools facilitate:

  • the understanding of the local epidemiology of microbial populations;
  • the selection of antimicrobial agents;
  • the identification of hospital and community outbreaks; and
  • the recognition of quality assurance problems in laboratory testing.

Note: At present, WHONET can handle results from the testing of bacteria, fungi, and parasites. WHONET does not yet have virological tests incorporated, but this is a priority area of programming in the upcoming year.

WHONET has three main components.

  • Laboratory configuration: WHONET permits the customization of the software for use in your institution. You can indicate which antimicrobials you test in the laboratory, patient care areas served, data fields that you want to include in the surveillance program, and microbiological alerts of unusual or important organisms and resistance phenotypes.
  • Data entry and clinical reporting: WHONET allows the routine entry of susceptibility test results as well as the retrieval, correction and printing of clinical records. During data entry, WHONET can provide immediate feedback to technicians on important strain phenotypes.
  • Data analysis: WHONET has a user-friendly interface permitting many types of analysis. Options include isolate line-listings and summaries, such as organism frequencies over time, antimicrobial susceptibility test statistics, zone diameter and MIC histograms, antibiotic scatterplots and regression curves, and antibiotic resistance profile line-listings and summaries. WHONET also has a number of alert features which permit the detection of unlikely or important results as well as possible hospital or community outbreaks of bacterial or non-bacterial species.

Examples of some of the WHONET analysis options are shown below.

Figure 1.  What can WHONET do?

Figure 1. Portion of an isolate listing for positive blood cultures. The left portion of the listing includes patient demographic data followed by the antibiotic results. The right portion of the listing includes microbiological alerts about important resistance findings or possible laboratory errors. Then underscore “_” around the patient identifier indicates that the original patient identifiers have been encrypted.

Figure 2.  What can WHONET do?

Figure 2. Distribution of MRSA isolates by department. Only the first isolate per patient is included. The graph depicts the graph for the department of medicine.

Figure 3.  What can WHONET do?

Figure 3. Monthly distribution of patients with Acinetobacter baumannii over a two year period.

Figure 4.  What can WHONET do?

Figure 4. %RIS and test measurement statistics for K. pneumoniae. %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.

Figure 5.  What can WHONET do?

Figure 5. Ciprofloxacin %Resistant results for all Enterobacteriaceae.

Figure 6.  What can WHONET do?

Figure 5.1. 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.

Figure 7.  What can WHONET do?

Figure 6. Resistance profiles. Monthly distribution of patients with isolates of S. aureus of the indicated resistance phenotype. The isolates are non-susceptible to PEN, OXA, CLI, ERY, GEN, AMK, and TCY, but susceptible to CHL and VAN.

Figure 8.  What can WHONET do?

Figure 7. A summary of the microbiological alerts observed in the analyzed data. Categories of alert include “Quality control”, “Important species”, “Important resistance”, “Send to a reference laboratory”, and “Alert the infection control” among others.

Many laboratories in the world already have computer systems for managing microbiological data. Examples include:

1. Simple desktop softwares such as Microsoft Excel, Access, or EpiInfo
2. Laboratory test instruments, such as Vitek, MicroScan, and SensiTitre
3. Commercial or in-house laboratory information systems.

Most of these systems were developed for purposes of clinical reporting, billing, and day-to-day specimen processing needs. Unfortunately, most systems have limited capabilities for analyzing data. This is where WHONET can be a valuable add-on to your existing system.

One way of getting data from your computer system into WHONET is through the manual re-entry of results directly into WHONET. But this is can be a significant waste of valuable staff time and is subject to typing errors during the reentry of results.

To avoid reentering results into WHONET, we have developed the BacLink software. The purpose of the BacLink software is to facilitate the conversion of data from your computer system into WHONET. You could do this interactively on a weekly, monthly, or ad hoc basis. In a number of institutions, it has also been possible to automate and schedule the entire process. BacLink is available free-of-charge from the World Health Organization as part of the WHONET package.

By using BacLink, you can thus avoid the manual entry of results into WHONET. A related benefit in the context of multi-center collaborations is the standardization of data from a number of incompatible data sources into one common structure that can be analyzed with WHONET.

To learn more about BacLink and its use, go through the “BacLink – Getting Started”.

You must install WHONET onto your computer before you can begin using it. WHONET is compatible with all versions of Microsoft Windows from Windows 95 to the most recent.

The installation process is fairly automatic and copies the program files into appropriate locations on your computer, creating menu links and icons which will permit easy access to WHONET.

You can obtain the software

• by download from the web
• on CD-Rom

Installing the software from the web

Go to the site: www.who.int/drugresistance/whonetsoftware

Figure 1.  Installing WHONET and BacLink

Click on the link called “Click here to download the software and manuals”. This will transfer you to an “ftp” site (File Transfer Protocol) where you can find the software.

Figure 2.  Installing WHONET and BacLink

Note: In some institutions, access to ftp sites is disabled in order to protect your computer against viruses. If clicking on the link does not work, first try using “Ctrl”+Click. (If the problem is that your computer is blocking “Pop-Up” screens, then “Ctrl”+Click should fix the problem). If that doesn’t work, you could try downloading the software again from a different computer. If you continue to have problems accessing the ftp site or downloading the software, contact your system administrator for assistance.

Click on “1.Software.”

Figure 3.  Installing WHONET and BacLink

Double-click on the file whonet54setup.exe. You should get a screen asking whether you would like to “Run” or “Save” the file. Choose “Run”. After the software is downloaded, the installation program will begin automatically.

Figure 4.  Installing WHONET and BacLink

Note: Alternatively, if you would like to install WHONET onto computers that have no internet access, it may be more convenient to “Save” the file onto your computer, for example on the Desktop. Then you can copy the file to the other computers for installation. After you save the file, double-click on the filename whonet54setup.exe to initiate the installation program.

On some computers, you will also get a security warning. Click on “Run”.

Figure 5.  Installing WHONET and BacLink

After whonet54setup.exe has downloaded, the program “WinZip Self-Extractor” will run. Click on “Unzip” to decompress whonet54setup.exe.

Figure 6.  Installing WHONET and BacLink

If the decompression works properly, you will get a confirmation that the program “unzipped” successfully.

Figure 7.  Installing WHONET and BacLink

Click “OK”. After clicking “OK”, the WHONET installation program will start. Continue with the instructions below on “Running the installation program.

Installing the software from a CD

In most cases, the WHONET installation program will begin automatically when you put the CD into the CD drive after a delay of five to twenty seconds. In case the installation program does not begin automatically, look for a file called SETUP.EXE on the CD or a file called whonet54setup.exe, and double-click on the file. When the installation program begins, proceed with the instructions below on “Running the installation program”. If the installation program does not begin, ask for assistance from the individual who prepared the CD-ROM.

Running the installation program

After the installation program begins, follow the instructions on the screen. In most cases, you will simply click “Next”, “Next”, “Next”, “Next”, “Finish”. On some computers, you will be asked to reboot the computer to complete the installation.

Figure 8.  Installing WHONET and BacLink

After you install WHONET, you will see icons for WHONET and BacLink on your desktop. You will also have links to the softwares and documentation (manuals and tutorials) from your Windows “Start” menu under “Programs”, “WHONET 5.4”.

Figure 9.  Installing WHONET and BacLink

If your computer is part of a hospital network and if you have difficulties installing WHONET, a frequent explanation is that many computer system administrators disable the ability of typical computer users to install new softwares. They do this to help protect the computers from viruses or other accidental modifications. In this situation, please ask your computer administrator to install the software for you. If you continue to have difficulties with installation, please write to John Stelling at jstelling@rics.bwh.harvard.edu for additional assistance.

Double-click on the WHONET icon to begin the software. You will see the following screen.

Figure 1.  Running WHONET

On this screen, you will see a list of all laboratory configurations present on your computer. Initially, you will only have the one sample laboratory called “WHO Test Hospital”.

From this screen, you have the option to choose the language used by WHONET. By default, WHONET begins in English. If you wish to change this, click on “Select language”, choose the desired language, and click OK. The software will then switch to the selected language. At present, the available languages are: Bulgaria, Chinese (Simplified), English, Estonian, French, German, Greek, Indonesian, Italian, Japanese, Norwegian (Bokmål), Norwegian (Nynorsk), Polish, Portuguese, Russian, Spanish, and Thai.

Figure 2.  Running WHONET

In the above example, Spanish is selected. After you click “OK”, all of the WHONET menus and messages will change to Spanish.

Figure 3. Running WHONET

Now that you have installed WHONET, you are ready for the next steps.

If you plan on using WHONET for manual data entry, proceed with the WHONET tutorial on “Laboratory Configuration” followed by the tutorial on “Data Entry”.

If you want to download and convert data from an existing computer system, then it would be useful to continue with “BacLink – Getting Started”.

If you want to explore WHONET’s data analysis features using the sample data that comes with WHONET or if you already have some WHONET data of your own, you may wish to skip directly to the tutorial “Data Analysis 1”.

Laboratory Configuration #back to top


The purpose of laboratory configuration is to describe to WHONET details about your institution and your laboratory test practices. This tutorial describes how to create a “new laboratory” from the very beginning. Note: If you will be using BacLink, there is a short-cut to accomplish most of the following steps. See the BacLink tutorials for more information. The short-cut feature is called “Create a laboratory from a data file”, and can be found under the WHONET “File” menu option.

Double-click on the WHONET icon on your desktop to begin WHONET. You will see a list of laboratory configurations currently defined on your computer. Click on “New Laboratory” to begin.

Figure 1.  Describing your laboratory

Figure 1. List of WHONET laboratory configurations. Select “New laboratory”.

In this tutorial, you will create an institution in the special “country” World Health Organization called “WHONET Tutorial Hospital”. So for country, select “World Health Organization”, and for the laboratory name, type “WHONET Tutorial Hospital”. For the laboratory code, put “WTH”. Your screen should look like the below.

Figure 2.  Describing your laboratory

Figure 2. WHONET laboratory configuration screen. Enter the country, name, and code of your laboratory.

The only part of laboratory configuration which is required is indicating which antimicrobials you are testing in your laboratory. To do this, click on “Antibiotics” to get the following screen. You will see a long list of antibiotics to your left – this is the WHONET list. On the right is the list of antibiotic tests used in your laboratory. At the beginning this list is empty.

Figure 1.  Selecting your antibiotics

To indicate the tests that you are using, you should indicate three things: 1. the reference guidelines (for example CLSI, SFM, DIN, etc.); 2. the test method (disk, MIC, or Etest); and 3. the name of the antibiotic and, for disk diffusion testing, the disk potency.

In this tutorial, indicate that the method is CLSI, and you will choose a few drugs tested by disk diffusion and a few tested by Etest. To select an antibiotic, double-click on the antibiotic to move it to the right side of the screen or single-click on the antibiotic and hit the “–>” button.

Find the following antibiotics, and move them to the right side of the screen.

Disk diffusion, ampicillin 10ug
Disk diffusion, cefoxitin 30ug
Disk diffusion, ceftriaxone 30ug
Disk diffusion, ciprofloxacin 5ug
Disk diffusion, erythromycin 15ug
Disk diffusion, gentamicin 10ug
Disk diffusion, imipenem, 10ug
Disk diffusion, penicillin G 10units
Disk diffusion, trimethoprim/
sulfamethoxazole 1.25ug/23.75ug
Disk diffusion, vancomycin, 30ug

WHONET assigns a code to each antibiotic test, for example AMP_ND10 indicates a test of ampicillin (“AMP”) by CLSI (“N”, formerly NCCLS) methods by disk diffusion (“D”) with a 10ug disk (“10”).

Now enter a few drugs tested by Etest. Click on the option labeled “Etest” and select the following drugs. Since the disk potency is not relevant for Etests, it does not matter which ”ceftriaxone” you select from the WHONET list.

Etest, ceftiaxone
Etest, penicillin G
Etest, vancomycin

The corresponding test code for the ceftriaxone Etest done by CLSI (formerly NCCLS) methods would be CRO_NE. After making these selections, you should have the following.

Figure 2.  Selecting your antibiotics

Figure 3. Antibiotic configuration screen. Select from the list of antibiotics shown to the left of the screen. The antibiotic tests used in your laboratory appear to the right of the screen.

If you would like to change the sequence of antibiotics, you can use the “Move up” and “Move down” options. Or you can use the left arrow button “<–“ to remove a drug from the list.

After you complete the above steps, it is possible for you to proceed directly with data entry if you would like. There are, however, a number of additional features described in Parts 3 through 6 which may be useful.

The following steps are not required, but may be useful to you.

Antibiotic breakpoints: When you select antibiotic tests, WHONET automatically sets up the correct official breakpoints according to the reference body that you indicate. In most cases, there will be no need for you to change these yourself. However, if there are no official breakpoints for the antibiotic that you selected or if you disagree with the breakpoints used by WHONET, then you may wish to make some manual modifications.

Note: Accurate breakpoints are essential if you are entering quantitative test measurements into WHONET (for example, disk diffusion zone diameters or MIC/Etest values). On the other hand, if you will only be entering test interpretations (“resistant”, “intermediate”, or “susceptible”), then WHONET does not use the breakpoint values. WHONET does not require the use of test measurements, but for good quality microbiological testing and the most valuable analyses, it is strongly recommended.

In this tutorial, we will not change any of the default breakpoints, but to see the values suggested by WHONET, click on “Breakpoints”.

Figure 1.  Configuring your antibiotics

Figure 4. Antibiotic breakpoint configuration.

You can then view any of the disk diffusion or MIC/Etest breakpoints. WHONET distinguishes between “General” breakpoints used for most bacterial species and “Species-specific” breakpoints for species in which the recommended breakpoint is different. After reviewing the breakpoints, select “OK”, “OK” to return to the antibiotic configuration screen.

Figure 2.  Configuring your antibiotics

Figure 5. General and species-specific antibiotic breakpoints

Antibiotic panels: If you will enter results manually into WHONET, it would be useful to the data entry person if you indicate which antibiotics are tested for which organism groups. For example for S. aureus, the software should request results from drugs used in Gram-positive infections, while for E. coli in urine samples, a different set of antimicrobials would be appropriate.

From the Antibiotic configuration screen, click on “Panels”. You will see all of the antibiotics that you have selected in the rows, and a list of various organism groupings in the columns. Place a check mark to indicate which drugs are usually tested for each organism.

For this tutorial, put check marks for the following organisms and antibiotics.

“Staphylococcus”: cefoxitin, erythromycin, penicillin, trimethoprim/ sulfamethoxazole, and vancomycin

“S. pneumoniae”: erythromycin, trimethoprim/ sulfamethoxazole, vancomycin, penicillin-Etest, and ceftiaxone-Etest

“Gram-negative”. ampicillin, ceftriaxone, ciprofloxacin, gentamicin, imipenem, and trimethoprim/sulfamethoxazole

If there is a drug that you test infrequently, for example imipenem for E. coli isolates, there is no need to include it in the panel. The user will be able to enter results for either “panel” antibiotics or “all antibiotics” at the time of data entry.

Figure 3.  Configuring your antibiotics

Figure 6. Antibiotic panel configuration. Indicate which antibiotics you test for each organism group.

Antibiotic resistance profiles: This feature is used in the data analysis option called “Resistance profiles”. In this analysis bacteria are classified according to their multi-resistance phenotype. This is a very valuable analysis for infection control staff when searching for outbreaks of multi-resistant organisms in the hospital setting. Use and interpretation of this feature is described in the tutorial Data Analysis 2.

In this part of laboratory configuration, you can indicate which drugs should be used to construct the resistant profile.

Figure 4.  Configuring your antibiotics

Figure 7. Antibiotic resistance profile configuration. Indicate the drugs to be used in the study of multi-resistance patterns.

The following steps are not required, but may be useful to you.

If you entry data manually into WHONET, it would be useful to enter a list of the most common patient locations from which you get clinical isolates.

Note: If you work in a public health, veterinary, or food laboratory setting, you can use the “Location” field to refer to whatever location would be of most relevance for your work – hospital, city, farm, abattoir, restaurant, market, etc. You can leave the “Department” and “Institution” columns empty if they are not relevant to your work.

Enter the following locations and values for the columns “Location”, “Code”, “Department”, “Institution”, and “Location type”.

Neurology neuro wth med inx
Cardiac Surgery csurg wth sur inx
Neonatal ICU nicu wth neo icu
Diabetes clinic diab wth med out
Health Center #5 hc5 oth out out

Note: “med” = medicine, “sur” = surgery, “inx” = Inpatient (non-ICU), ICU = intensitve care unit, “out” = outpatient.

You can use the “Edit” buttons to change the list of institutions and departments to match the needs of your institution. When you finish the configuration of your locations, click on “OK” to return to the main configuration screen.

Figure 1.  Patient locations

Figure 8. WHONET location configuration. Indicate the locations from which you obtain your samples.

From the main configuration screen, click on “Data fields”. You will see the default list of WHONET data fields. This list includes questions about the patient (identification number, age, date of birth, sex), patient location (location, department, institution, location type), specimen (number, date, type), and microbiological results (organism, serotype, beta-lactamase, ESBL).

Figure 1.  Data fields

Figure 9. WHONET data field configuration. Indicate and modify the data fields that you want to use in WHONET.

For most laboratories, this list is adequate for routine surveillance purposes and does not need to be edited. However for many laboratories, modifications to this list can be very useful.

Adding or removing fields: You can add additional fields to the list or remove fields that you do not need for your work. Click on “Modify list”. On the left, you will see various categories of questions and suggested fields from you to choose from. If you cannot find the field that you need, you may define a “User-defined field”.

For this tutorial, click on “Clinical information” as the data category and “Diagnosis” in the “Data fields” list. Use the right-arrow key to pass “Diagnosis” to your laboratory’s field list.

Now click on “Microbiology” as the data category, and double-click on “D-Test (ERY, CLI)” to add this test to your list. Then click “OK” to return to the previous screen.

Figure 2.  Data fields

Figure 10. Add additional fields or remove fields from the list of fields for your laboratory. In this figure, you can see a number of additional microbiological questions from which to choose. You can also select “User-defined” if the field you would like does not appear in the WHONET lists.

Changing field lengths: WHONET assigns a default length for each data field, but the length of most fields can be changed by the user. For example, the location code by default is at most six characters in length. However, for many laboratories, six letters may not be sufficient. To change the length, click on “Location”, and change the length on the right side of the screen from 6 to a larger value, for example 20. For this tutorial, you can leave these settings unchanged.

Appearance of the data entry screen and isolate listings: You can use “Move up” and “Move down” to change the order of the questions appearing on the data entry screen. You can indicate whether a question applies to humans, animals, or food. You can also indicate which “box” the question appears in during data entry, for example “Location”, “Microbiology”, “Specimen”, etc. You can indicate that a question is hidden from the user by selecting “Hidden”, or whether to include a certain column in the default isolate listing by clicking on “Isolate listing”. For this tutorial, you can leave these settings unchanged.

Code lists: If you add some additional fields to your list, you may also wish to create a list of codes to use for these fields. For this tutorial, click on the item “Diagnosis” that you added above. Now click on “Code list”. To enter a list of valid codes, click on “Use codes from the table below”. Then put in the following entries under the “Description” and “Code” columns: “pneumonia”=”pneumo”, “urinary tract infection”=”uti”, “meningitis”=”mening”. When you finish, click “OK” to return to the previous screen.

You do not need to enter an exhaustive list. Just indicate the most common or important responses for purposes of standardizing data entry.

Figure 3.  Data fields

Figure 11. Defining a list of valid responses for the Diagnosis field.

From the main configuration screen, click on “Alerts”. You will see a long list of microbiological alerts suggested by WHONET – alerts about possible laboratory errors, important results that should be confirmed at the local or national level, and findings that should be communicated to other groups, such as the infection control team. You can easily activate or deactivate the rules suggested by WHONET.

You can also use “New rule” to define additional alerts specific to your institution or country. When you finish reviewing or defining rules, click on “OK” to return to the main configuration screen.

These features are described in greater detail in the tutorial “Expert System”.

Figure 1.  Isolate alerts

Figure 12. List of microbiological alerts for your laboratory. In addition to the pre-defined WHONET alerts, you can also define your own alerts with “New”.

You have now finished your laboratory configuration. Click on “Save” to save all of the laboratory details into a “laboratory configuration file. The name of the file has the form “labxxx.yyy” where “xxx” refers to the country code and “yyy” refers to the laboratory code. For example, in this tutorial, the laboratory configuration will have the name “labwho.wth”.

Figure 1.  Finishing laboratory configuration

You can return to laboratory configuration to make additional changes at any time by selecting “Modify laboratory”.

Now that you have finished configuration of your laboratory, you can now continue with the tutorial on Data Entry.


Data Entry #back to top


In this tutorial, you will learn how to enter results into WHONET data files, how to edit isolate results, and how to print clinical reports.

Begin WHONET, and select the laboratory “WHO Tutorial Hospital” that you created in the tutorial on laboratory configuration. If you did not do this tutorial, then select any of the laboratories available on your computer. Click on “Open laboratory”.

At the top of the screen, you will see the main “Data entry” menu. If you select this menu, you will see a number of options. To begin a new data file, select “New data file”. If you would like to continue working with a data file that already exists, click on “Open data file”. For this tutorial, select “New data file”.

Figure 1.  Creating a new data file

Figure 1. Main WHONET menu with the Data entry options selected.

Every file on a computer needs: 1) a name; and 2) a location. By default, the location of WHONET files is c:\whonet5\data on your computer’s hard drive, but you can put the file wherever is most convenient for you, for example on a central server accessible to many computers.

For the file name, WHONET suggests a name indicating the year of the data, the country code, and the laboratory code, for example w06who.wth. For the tutorial, change the option to “Month/Year”, and WHONET will suggest a name such as w0606who.wth for June 2006. If the data are from a different month, indicate the correct month. For this tutorial, change the file name to w0106who.wth to indicate that you will enter data from January 2006 from the country “WHO” from the “WTH” laboratory. Then click “OK”.

Figure 2.  Creating a new data file

Figure 2. Indicate the name of the new WHONET data file.

WHONET will proceed to data entry. In this step, you will enter results from three clinical isolates and one quality control strain. For the first isolate, enter the following patient information.

First isolate

  • Identification number = 12345
  • Last name = Smith
  • First name = John
  • Sex = Male = m
  • Date of Birth = 1/1/80
  • Diagnosis = Pneumonia = pneumo
  • Location = neuro
  • Specimen number = 1111
  • Specimen date = 10/12/05
  • Specimen type = Blood = bl
  • Organism = S. aureus = sau

Antibiotic results

  • Beta-lactamase = Positive = +
  • Cefoxitin = 20
  • Erythromycin = 18
  • Penicillin G = 12
  • Trimethoprim/
  • sulfamethoxazole = 19
  • Vancomycin = 17

When you finish, your screen should look like the following. As you put in the antibiotic measurements, WHONET will automatically determine and display the interpretation.

Figure 1.  Data entry

Figure 3. Data entry screen after the entry of the first isolate.

Note: For date formats, WHONET uses the defaults set up for your computer. For example, if you type 10/12/05 on a computer outside of the United States, WHONET will probably (depending on your computer) interpret this as 10-Dec-05. On the other hand, if you are in the United States, WHONET will probably interpret this as 12-Oct-05. When WHONET displays the date back to you as “10-Dec-05” or “12-Oct-05”, you will see whether WHONET correctly interprets your intention.

Note: In WHONET, you can enter either quantitative measurements (disk diffusion zone diameters or MIC values in ug/ml) or test interpretations (resistance, intermediate, susceptible). However, we strongly recommend that you enter the test measurements for several reaons:

1. It is the correct way to do the test, and the only way to be certain that measurements and interpretations were done correctly, rather than “eye-balling” the result.

2. Interpretative breakpoints can change over time. If there is a change in breakpoints, you will not be able to compare new statistics with your older statistics if you do not record the test measurements.

3. By reviewing the distribution histograms of test results, you can assess the quality of routine test practices and the reliability of results; and

4. By reviewing the test measurement, you can learn a lot about the mechanisms of resistance and the epidemiology of distinct resistant clones – useful both for research studies and infection control investigations of possible outbreaks.

After you enter all of the results, click on “Save isolate”. From the choices given, select “Save the isolate and continue with the same specimen.”

Figure 2.  Data entry

Figure 4. Save the isolate and continue with the same specimen

Now enter a second bacterial isolate for the same blood specimen with the following results.

Second isolate

  • Organism = E. coli = eco
  • Ampicillin = 6
  • Ceftriaxone = 10

As soon as you put the ceftriaxone result, WHONET will display some alerts in the lower right-hand corner of the screen indicating that this organism may be an ESBL-producing organism. WHONET has many alerts that warn you of possible typing or laboratory testing errors or of important results that should be confirmed and reported to responsible authorities, such as the infection control team or a national reference center.

Continue entering antimicrobial results:

  • Ciprofloxacin = 22
  • Gentamicin = 13
  • Imipenem = 12

As soon as you put the results for imipenem, you will get the following “High priority” alert about carbapenem non-susceptible results.

Figure 3.  Data entry

Figure 5. High-priority alert for Enterobacteriaceae non-susceptible to carbapenems.

Now click on “Save isolate” to see the following screen. The top part of the screen is unchanged from before, but below appears a summary of the isolate alerts.

Figure 4.  Data entry

Figure 6. Saving the results with a summary of the microbiologicial alerts for this isolate.

Save the isolate, and continue with the next isolate. Enter the following results.

  • Identification number = 67890
  • Last name = Jones
  • First name = Mary
  • Sex = Female = f
  • Date of Birth = 3 January 2006
  • Diagnosis = Meningitis = mening
  • Location = nicu
  • Specimen number = 2222
  • Specimen date = 27 January 2006
  • Specimen type = Blood = bl
  • Organism = S. pneumoniae = spn
  • Serotype = Streptococcus pneumoniae serotype 23F
  • Erythromycin = 18
  • Trimethoprim/sulfamethoxazole = 7
  • Vancomycin = 17
  • Penicillin Etest = 8ug/ml = 8
  • Ceftiaxone Etest = 8

To enter the Etest results, click on “Etest”.

If you need to enter a result for an antibiotic test that does not appear on the panel for the organism you enter, change “Antibiotic panel” to “All antibiotics”. If the antibiotic test you want still doesn’t appear, you will need to go back to Laboratory configuration and add the additional tests to your antibiotic list.

Save the isolate as before by clicking on “Save isolate” and “OK”.

Fourth isolate

  • Identification number = atcc25922
  • Last name = atcc25922
  • First name = atcc25922
  • Location = lab
  • Specimen number = 3333
  • Specimen date = 15 January 2006
  • Specimen type = Quality control = qc
  • Organism = E. coli = eco
  • Ampicillin = 16
  • Ceftriaxone = 22
  • Ciprofloxacin = 18
  • Imipenem = 15

When you leave the imipenem result, you will see that the result gets an asterisk “!”. To see why there is an asterisk, return to the imipenem box. On the right side of the screen, you will see the comment “The result is out of the acceptable QC range.”

Figure 5.  Data entry

Save the isolate as before by clicking on “Save isolate” and “OK”.

You have now entered the results for four strains into WHONET. To see these results, click on “View the database” to get the following screen listing all of the results.

Figure 1.  Viewing the database

Figure 7. Viewing the database in table format.

From this screen, you have a number of options:

Sorting the results: If you click on any column heading, WHONET will sort the database by that column. This can help you to find results from a certain patient or with a certain organism. It can also help find errors in data entry, for example in the specimen date column.

Edit the isolate: If there is a mistake in the database or if you have additional information to add, click on “Edit the isolate” to edit the isolate on the main data entry screen. When you finish, click on “Save isolate”.

Edit the table: You can also edit the table directly. Click on “Edit the table” and you can make changes directly to the table.

Delete: Use this button to delete a record.

Search: Use this button to search for records, for example certain patients, specimen numbers, or organisms.

Print: This feature is described further in the next step.

When finished reviewing these features, click on “Continue” to return to the main Data entry screen

Some laboratories use WHONET to report laboratory results back to clinicians. WHONET still has some limitations in this regard, but it has worked reasonably for many institutions.
To print out clinical reports or logbook isolate listings, click on “Print” from either the main Data entry screen or from the “View database” screen.

Figure 1. Clinical reports

Figure 8. Print clinical reports and isolate listings

You have the choice between printing isolate listings (for example fifty isolates per page) or individual patient reports (one to three reports per page). You also have the option of choosing to print only the current isolate selected or a number of isolates with criteria that you specific (date of data entry, specimen number, etc.).
For this tutorial, you will print clinical reports and an isolate listing for the four isolates entered above.
1. Click on “Clinical reports”. Choose “Select isolates”. The default is to print out all isolates entered today (“Date of data entry” = today’s date). Click on “Print”, and then “Print” on the following screen. WHONET will now print the individual clinical reports, two per page.

Figure 2.  Clinical reports

2. Click on “Isolate listing”. Leave the other selections unchanged, and click on “Print”, and then “Print” again. WHONET will now print out the isolate listing.

Figure 3.  Clinical reports Figure 4.  Clinical reports

If you would like to change the format of the clinical report, you can choose the option “Modify clinical report” to make a number of changes. Among other options, you can indicate how many results to print per page, which fields should be included in the print, the fonts for the printout, and whether to include a standard page header or footer.

Figure 5.  Clinical reports

Figure 9. Editing the clinical report.

After you finish exploring the Data entry program, click on “Exit” to return to the main WHONET menu.
In the above steps, you saw how to create a new data file in WHONET and entered results for four isolates. You will now see how to return to open a data file which already exists. Click on “Data entry”, and you will see the following choices.

Figure 1.  Finishing up

Figure 10. The main WHONET screen with the most recently opened data file highlighted.
You will notice that the data file w0106who.wth appears at the bottom of the list. WHONET shows you the list of the most recently open files. Click on “w0106who.wth” to open the file. Alternatively, you could use “Open data file” to open any data file.
You are now back in the data entry program where you can enter results for additional isolates or edit or print results from existing isolates.
When you finish reviewing data entry, select “Exit” from the data entry screen to return to the main WHONET menu.

The following additional features are not essential, but are useful to many users. For purposes of this tutorial, look at the screens that are described, but there is no need to run any of the features. When you finish, select “File”, “Exit” to leave WHONET completely.
Combining data files: In the above example, you created a data file for January 2006. If you continue in this way, you will have twelve monthly files at the end of the year. Many users find it convenient at the end of the year to combine the twelve files into a single larger monthly file.
To use this feature, click on “Data entry” from the main WHONET screen. Choose “Combine or export data files”. Indicate the data files that you want to combine and the name of the new file that you want to create. Then click on “Combine”. When WHONET finishes, the original data files will be unchanged, but you will now have a new large data file which includes all of the results from the original files.

Figure 1.  Other options for managing data files

Figure 11. Combining WHONET data files.

Encryption: If you want to share your data files with other institutions, you may wish to protect the confidentiality of patients with this feature. When you use this option, WHONET will create a copy of your data file but with patient and specimen information either removed or encrypted. WHONET uses a uni-directional encryption, so subsequent “decryption” of the results is not possible.
To use this feature, click on “Data entry” from the main WHONET screen. Choose “Encrypt data files”. Indicate the data file that you want to encrypt and the name of the new file that you want to create. Then click on “Encrypt”. When WHONET finishes, the original data file will be unchanged, but you will now how a new data file in which the patient and sample information has either been removed or encrypted.

Figure 2.  Other options for managing data files

Figure 12. Encrypting patient information.
Data file locations: When you install WHONET, by default, all data files will be saved into the c:\whonet5\data folder. For people using WHONET on a single computer not connected to a network, this is a practical location. However, for computers connected into a network, it if often more convenient to put the data files onto a central common computer where multiple users can have access to the same data files. In this way, data entry and data analysis can be done with the same data files by several individuals using different computers.
If you save your data files on a network computer, it would be convenient for users if you change the default location for WHONET data files. To do this, go to the main WHONET menu, and select “File”, “File locations”. To change the location of the data files, you can type in the desired location or use the Browse option to find the appropriate folder.

Figure 3.  Other options for managing data files

Figure 13. Changing the default file locations.
After checking this option, click on “OK” to return to the main WHONET menu. Click on “File”, “Exit” to completely leave the WHONET program.
Backing up files: As is true for any important document that you have on your computer, you should have a strategy for backing up your WHONET data files. This is important in the case of computer damage, theft, viruses, or accidental modifications. You can back files up by copying your WHONET files onto another computer, CD-ROM, USB-memory stick, or diskettes.
To make copies of your WHONET data files, go to c:\whonet5\data (or other location that you have selected), and find the files that you want to backup. Select these files and choose “Edit” from the main Windows screen and “Copy”. (Alternatively, you can use Ctrl-C or right-click on the file and select “Copy”.)
Then go to the location where you want to back up the files and select “Edit”, “Paste”. (Or Ctrl-V or right-click on the location and select “Paste.”)

Figure 4.  Other options for managing data files

Figure 14. Contents of the folder c:\whonet5\data. The WHONET data file w0106who.wth created in this tutorial is highlighted.
In addition to backing up your WHONET data files, you should also backup your WHONET laboratory configuration file. In this tutorial, the name of this file is labwho.wth. The file is in your c:\whonet5 folder. Go to this file, and copy and paste the file to the backup location.

Figure 5.  Other options for managing data files

Figure 15. Contents of the folder c:\whonet5. The WHONET laboratory configuration file labwho.wth created in this tutorial is highlighted.

Data analysis 1 #back to top


This tutorial will illustrate some of the most important features of the WHONET data analysis program. Applications of these analyses include:


- continuous quality improvement: assessing laboratory test practices and utilization of laboratory services by clinical departments
- describing trends in the epidemiology of microbial populations and antimicrobial resistance
- characterizing the molecular epidemiology of antimicrobial resistance trains
- guiding antimicrobial therapy recommendations and policy
- supporting infection control interventions, in particular the early identification of hospital and community outbreaks


This tutorial focuses on two of the most commonly used analysis options: 1. %RIS and test measurements; and 2. Isolate listing and summary.

Double-click on the WHONET icon on your desktop to begin the software. You will see a screen similar to the following. For purposes of this tutorial, select the laboratory called “WHO Test Hospital”, and click on “Open laboratory”.

Figure 1.  Getting started Figure 1. Laboratory selection.

From the main WHONET screen, click on “Data analysis” and “Data analysis” again. You will now see the main WHONET analysis screen. From this screen, you will be able to tell WHONET the type of analysis you want to perform.

Figure 2.  Getting started

Figure 2. The WHONET data analysis screen.

In the main analysis screen, there are three sections on the left that you must answer: Analysis type, Organisms, and Data files. On the right, there are some additional options that may be useful to you.
Analysis type: First, you must indicate the kind of analysis that you want WHONET to perform. To do this, click on “Analysis type”. You will see several analysis options. For this first analysis, select the option “%RIS and test measurements”. Click “OK” to return to the main analysis screen.

Figure 1.  Setting up an analysis

Figure 3. Analysis type: Select the kind of analysis you want to run, as well as the format of the output – graphs, tables, listings, summaries, etc.
Organisms: Click on Organisms. On this screen, as in many of the WHONET screens, you will see the options available to you on the left side of the screen. On the right side of the screen, you will put your selections.
On the left-hand side, you will first of all see a list of relatively common bacteria and fungi. Choose two organisms for this first analysis: E. coli (eco) and S. aureus (sau). You can select an organism in several possible ways: double-click on the organism or single-click on the organism and hit the right-arrow button “–>” or type the three-letter code and hit ``. Your screen should look like the following.

Figure 2. Setting up an analysis

Figure 4. Organism: Select the organisms or organism groups that you want to analyze.
There are some other useful options on this screen as well.
Extended list: Initially, WHONET shows you the list of relatively common organisms. To see the complete list, click on “Extended list”. You can use the “Search” box to quickly find an organism.
Organism groups: If you click on “Organism groups”, you will see that WHONET permits you to analyze groups of microorganisms such as “All organisms”, “All Enterobacteriaceae”, and “All Salmonella”.
Analyze as one organism: WHONET generally will analyze each organism selected separately. If you would like WHONET to average results together from multiple organisms (for example “Klebsiella pneumoniae”, “Klebsiella oxytoca” and “Klebsiella sp.”), then click on the option “Analyze as one organism”.
When you finish looking at the available options, click “OK” to return to the main analysis screen.
Data files: Click on “Data files” to select the data files to include in the analysis. For this tutorial, select the file w0195who.tst”. You can do this by double-clicking on the file or by single-clicking and using the right-arrow button “–>”. After selecting the file, click on “OK” to return to the main analysis screen.

Figure 3.  Setting up an analysis

Figure 5. Data files: Select the data files to include in the analysis. Files to be analyzed should appear on the right side of the screen.

After making all of the above selections, your screen should look like the following:

Figure 4.  Setting up an analysis

Figure 6. WHONET analysis screen. WHONET will run a “%RIS and test measurement” analysis on E. coli and S. aureus from the file w0195who.tst.

Now that you have given WHONET the details of the analysis to perform, click on “Begin analysis”. If you have answered the questions correctly, WHONET will then read and analyze the data file, and should soon show the following screen.

Figure 1.  Running the analysis

Figure 7. WHONET output screen for the %RIS and test measurement analysis with E. coli.

On the top of this screen, you see a table with the antimicrobial susceptibility test statistics for each of the antimicrobials tested. If you want to sort the table alphabetically or numerically, click on the heading for the column on which you want to sort.

For the E. coli, the output tells you how many isolates in total were found (86 isolates) and which antimicrobials were tested. When you review results such as these, you should evaluate whether the antimicrobials tested are appropriate and whether the laboratory can optimize their test practices by adding, removing, or changing the antimicrobials tested. The results may also suggested typing errors in data entry (for example if there are vancomycin results tabulated for E. coli).

You should also look at the column “Number” to see how often each antimicrobial was tested. This will give you an idea of the laboratory’s testing practices – which antimicrobials are tested in all isolates and which are tested only in urine or highly resistant isolates. If the number of tests per antibiotic is very irregular, this may suggest a problem with antimicrobial disk availability in the laboratory.

For example, in the data presented in this example, one could conclude that the laboratory staff is most likely testing antimicrobials in the following way:

Tested for all isolates: AMP, ATM, CTX, CXM, CEP, GEN, IPM, SXT (9 drugs) Tested for urine isolates: AMC, NIT, NOR (3 drugs) Tested for non-urine isolates: FOX, CIP, PIP (3 drugs) Tested for organisms resistant to first-line agents: AMK, CAZ, TOB (3 drugs)

In the other words, there is a urine panel which includes 12 antimicrobials (as one 15cm plate or two 9cm plates), a non-urine panel with 12 antimicrobials, and three additional drugs used in second-testing.

Additional columns indicate the antimicrobial breakpoints used, the percent of isolates resistant (including a 95% confidence interval), intermediate, and susceptible, as well as the distribution of zone diameters of MIC values.

The lower part of the screen shows some of the same data presented in the table, but in graphical format. For example, click on the options for “Number tested” and “%Resistant”.

Figure 2.  Running the analysis

Figure 8. Results from the %RIS analysis. The number of isolates tested for each antimicrobial is indicated to the left, while the percent of isolates resistant to each antimicrobial is depicted to the right.

Now click on some of the antimicrobials listed in the lower panel, for example ampicillin and trimethoprim/sulfamethoxazole. WHONET will display the zone diameter or MIC distribution of the selected drug. The red lines in the graph represent the interpretative breakpoints. For disk diffusion results, susceptible bacteria will appear to the right of the red lines; resistant isolates are to the left; and intermediate results are between the two lines. For MIC data, the susceptible bacteria will appear to the left and resistant bacteria to the right.

Figure 3.  Running the analysis

Figure 9. Zone diameter histograms for ampicillin and trimethoprim/sulfamethoxazole for E. coli isolates.

For most antimicrobials and organisms, the susceptible bacteria should form a fairly “normal” Gaussian distribution. You can see this for the E. coli histograms, even for those antibiotics with very few test results. Deviations from this pattern are common for some organisms and antimicrobials, but can also suggest test problems in laboratory practices – for example poor reagent quality (disks or test medium), inoculum preparation, or result measurement (for example number preference).

The ampicillin histogram suggests three principal bacterial subpopulations: 1. the wild-type susceptible population with large zone diameters; 2. a group with high-level resistance to ampicillin (zone diameter = 6mm = no inhibition); and 3. a group with low-level resistance (zone diameters 11 and 12mm). The latter two groups presumably possess different resistance genes – an observation not only useful for molecular research, but also in the investigation and characterization of outbreak-associated strains.

The second histogram depicts results for trimethoprim/sulfamethoxazole and illustrates two distint populations that lie in the susceptible category: one population with the “wild-type” phenotype with relatively large zone diameters and a second population with “decreased susceptibility” with diminished zone diameters.

After you finish reviewing results from the E. coli, click on “Continue” to proceed to the S. aureus results. Review the results shown in the table and histograms.
The WHONET results that you see on the screen can easily be transferred to other softwares such as Microsoft Excel, Word, or PowerPoint. You can do this either by using “Copy” and “Paste” or by saving the results as a file.
Copy and Paste: Click on “Copy table”. Now open Microsoft Excel, for example by clicking on your Windows “Start”, “All Programs” menus and looking for Microsoft Excel. (Alternatively, if you want to immediately go to your Windows Desktop, click on the “Windows” key on your keyboard and hit the letter D, in other words “Windows”-D.)
After you have Excel open, go to “Edit”, “Paste”. The WHONET results are now in Excel. You can now use Excel to edit, correct, format, or graph your results.
Now return to WHONET (for example, by clicking on the WHONET icon on the bottom of your screen). Click on “Copy graph”. Go back to Excel, find an empty part of the spreadsheet, and again choose “Edit”, “Paste”.

Figure 1.  Transferring WHONET

Figure 10. Copying and pasting results to Excel using “Copy table” and “Copy graph” from WHONET.

Save the file: WHONET also has an option for saving the results directly to a file. Because “Copy” and “Paste” works well and is usually very fast, there is often no need to do this, but there are a few situations where saving the results as a table can be useful. 1. For “isolate listings” or “resistance profile listings” with thousands of rows, the “Copy” and “Paste” approach can be very slow. In this case, saving the results as an Excel or as a text file would be much faster. 2. When you save the table as an Excel file, WHONET does some automatic formatting of the results and automatically makes a number of Excel graphs. So by using the “Save table” option, this may save you some time formatting the data in Excel.

To save the tables and graphs as an Excel file, click on “File”. Give a name to the file, for example “S. aureus RIS results.xls”. For type of file, select “Excel”. Notice that the default location for this file is c:\whonet5\output. Then click ‘OK’.

Figure 2.  Transferring WHONET

Figure 11. Saving results from WHONET to an Excel file.

Now go back to Excel and select “File”, “Open”. Look in the folder c:\whonet5\output for the file that you just created, and open it up. You will see something the following.

Figure 3.  Transferring WHONET

Figure 12. A formatted Excel file created from WHONET.

Then return to WHONET and click “Continue” to return to the main analysis screen.

In the previous analysis, WHONET analyzed first the E. coli and then the S. aureus. For clinicians and policy makers, it would be useful to prepare a summary report with many species on the same page. With WHONET, this is easy to do.

Click on “Analysis type”. In the middle of the screen, you will see two options: 1. %RIS and test measurements, and 2. Summary. The first of these is the detailed report presented earlier. For this example, select “Summary”.

For the columns, the default selection is %Susceptible (which is often preferred by clinicians and pharmacists). You can change this to %Resistant or %Non-susceptible (which is often preferred by microbiologists and epidemiologists). For the rows, the default selection is “Organism”. In other words, the results from each species will be summarized in a separate row row in the output. Click on “OK” to select the options.

Click on “Organisms”. Click on “Clear list” to remove E. coli and S. aureus from the list of selections. Click on “Organism groups” and double-click on “All Enterobacteriaeceae”. Click “OK” to accept the modifications. Your screen should match the following.

Figure 1.  %Susceptible Summary

Figure 13. Susceptibility summary for all Enterobacteriaceae.

Click on “Begin analysis”, and you should get the following output giving a summary of the susceptibility statistics for all Enterobacteriaceae. If you wish, you can then copy and paste these results to Excel for further editing of the results for distribution to clinical staff. When you finish reviewing the results, click on “OK” to return to the main analysis screen.

Figure 2.  %Susceptible Summary

Figure 14. %S Summary for Enterobacteriacae. The graph for E. coli results is displayed below.

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.

Figure 1.  Isolate listing and summary

Figure 15. Isolate listing of Enterobacteriacae. The most important fields are displayed. To view additional columns, click on “Show hidden columns”.

This listing shows some of the most important data fields: identification number, location, specimen date, specimen type, organism, and antibiotic results (in this example, with disk diffusion zone diameters).

Note: You can configure the fields which appear in this isolate listing. To do so, you would have to go back to laboratory configuration “Modify laboratory”, “Data fields”. For the data fields that you want to appear in the list, make sure that the box for “Isolate listing” is checked.

If you click on the box “Show hidden columns”, WHONET will show you all of the available fields. As in other parts of WHONET, you can click on a column heading to sort the database by that column. This could be useful, for example, to find errors in the entry of specimen dates.

When you finish looking at the isolate listing, select “Continue”. WHONET will proceed to display the summary of the isolate listing. As mentioned earlier, this summary is comparing “Organism” and “Specimen date” (by day). But by changing the analysis parameters, you can summarize any WHONET variable by any other variable.

The tables present the day-by-day trend (number of patients per day) in the isolation of each species, while the graph displays the same information in graphic format.

Figure 1.  Isolate listing and summary

Figure 16. Summary of the Enterobacteriaceae isolate listing. The daily distribution of E. coli isolates is displayed in the graph.

Click on an organism name in the lower right-hand corner to see the distribution of that organism over time, or click on one of the days to see the distribution of organisms for that day. When you finish reviewing the results, click on “OK” to return to the main analysis screen.

Now that you have completed this tutorial, you can exit WHONET completely or continue with Data analysis 2. If you want to leave the software completely, click on “Exit” to leave the data analysis program, and then “File”, “Exit” to leave WHONET.

Data analysis 2 #back to top


The tutorial Data Analysis 1 introduced the WHONET data analysis program and illustrated some of the most common analyses performed with WHONET: 1. %RIS and test measurements; and 2. isolate listings and summaries. In this tutorial, you will see how to select patients or isolates that meet certain criteria, options for handling multiple organism isolates per patient, and two additional analysis features.


For information on the following analysis options, refer to the appropriate tutorials:

  • Expert system
  • Macros and Excel reports.doc
  • Cluster detection with SaTScan


If WHONET is not currently running, double-click on the WHONET icon on your desktop to begin the software. From the list of available laboratories, select the laboratory called “WHO Test Hospital”, and click on “Open laboratory”. From the main WHONET screen, click on “Data analysis” and “Data analysis” again. You will now see the main WHONET analysis screen.
For Analysis type, select “%RIS and test measurement” and for Report Format, also choose “%RIS and test measurement.
For Organism, select S. aureus = sau.
For Isolates, there should be no selection criteria defined.
For Data Files, select w0195who.tst.
If you have done these steps properly, you should see the following screen

Figure 1.  Getting started and review

Figure 1. %RIS and test measurements with S. aureus.

Then click on “Begin Analysis” to get the results. On the output screen, notice that oxacillin was tested 85 times, and 10.6% of the isolates were resistant. After reviewing the rest of the results, click on “Continue” to return to the main analysis screen.

In the preceding analysis, WHONET included results from all S. aureus isolates in the analysis (except for laboratory and quality control isolates). For some analyses, such as isolate listings, including results from all isolates is appropriate.
However, for calculations of %Resistant or %Susceptible, it is usually recommended to make an adjustment to account for the fact that some patients have multiple culture results for the analyzed species. Patients who remain a long time in the hospital or patients with complicated clinical courses may have multiple isolates of the species in question, but outpatients and patients with simple clinical histories may only have a single isolation. If no adjustment is made to the calculation, the statistics will be biased towards the results of the patients with multiple isolates, frequently a subset with higher rates of resistance than other patients.
The U.S. Clinical and Laboratory Standards Institute (CLSI) has published a document “M39 – Analysis and Presentation of Cumulative Antimicrobial Susceptibility Test Statistics”, and this document recommends that laboratories use the first isolate per species for the analyzed time period when calculating susceptibility and resistance proportions for purposes of developing guidelines for empiric therapy.
WHONET offers several strategies for handling multiple patient isolates, including the CLSI recommendation of “first isolate per patient”. To see these options, click on “One-per-patient”. At the top of the screen, choose “By patient”. Then choose “First isolate only”.

Figure 1. One-per-patient options

Figure 2. One-per-patient options. The CLSI recommendation is to use the first isolate per species in the analyzed time period.

Click “OK”, and then “Begin analysis” to get the following results. You will notice now that WHONET is displaying results of 57 patients with S. aureus tested for oxacillin, and 14.0% of the first isolates were resistant to oxacillin (In most analyses of hospital pathogens, the “by isolate” approach wield yield a higher estimate of %resistance than the “by patient” approaches, but at this example demonstrates, this is not always the case.)

When finished reviewing the other results, click “Continue” again to return to the main analysis screen.

Figure 1.  One-per-patient options

Figure 3. %RIS for S. aureus using the first isolate of S. aureus per patient.


After you return to the main screen, click “One-per-patient”, and set the option back to “By isolate”, and click “OK” to return to the main analysis screen.

In the above analyses we analyzed all clinical isolates of S. aureus. (By default, WHONET automatically excludes quality control and other laboratory isolates). In many cases, users would like to select a subset of isolates or patients that meet certain criteria: for example blood isolates from the neonatal intensive care unit or imipenem-resistant Enterobacteriaceae.
To define selection criteria, click on “Isolates”. You may choose among any of the patient, location, sample, or microbiological/antibiotic fields available.

Figure 1.  Isolate selection criteria

Figure 4. Isolate selection criteria. The “Specimen type” field is selected.

For example, double-click on “Specimen type” (or single-click on “Specimen type” and then click on “Define criteria”). Double-click on “Blood” to select this option, and click “OK”.

Figure 2.  Isolate selection criteria

Figure 5. Defining selection criteria for “Specimen type”. You can “Include” or “Exclude” isolates with the criteria defined.

Now find “Oxacillin-Disk” on the list, and double-click. Choose “Resistant”, and “OK”.

There are a few other options on this screen that you should leave unchanged for this tutorial:

Exclude laboratory samples: To avoid mixing clinical from non-clinical isolates in your institution’s summary statistics, WHONET by default does not include the isolates in which the specimen type is equal to “qc” (quality control), “la” (laboratory sample), or “ex” (external quality control) or if the department is equal to “lab”. If you would like to include these results in your analyses, remove the check in this box.

Include isolates that satisfy all of the selection criteria / Include isolates that satisfy at least one of the selection criteria: If you choose the first of these options, WHONET will search for isolates that meet all of the selection criteria. In this example, WHONET will find results in which the isolate is from blood and is also resistant to oxacillin.

If you choose the second option, WHONET will search for isolates that meet at least one of the criteria. This would not be very useful in this example, but a more interesting example would be to ask for Enterobacteriaceae that are resistant to cefotaxime or to ceftazidime (or to both agents).

Delete this criteria / Delete all criteria. If you select these options, you can remove the selection criteria that you have selected.

After selecting the criteria “Specimen type = Blood” and “Erythromycin= Resistant”, click on “OK” to return to the main analysis screen. (Generally, it would be more interesting to study oxacillin-resistant strains than erythromycin-resistant ones, but in this small data set, there were no blood isolates of MRSA isolates.)

Figure 3.  Isolate selection criteria

Figure 6. %RIS and test measurements for S. aureus with two isolate criteria defined: Specimen type = Blood and Erythromycin-Disk = Resistant.

Click on “Begin analysis” to repeat the %RIS analysis performed earlier, but using the selection criteria indicated here. The new output will show the %RIS statistics for blood isolates of erythromycin-resistant S. aureus (8 isolates in the small dataset). When you finish reviewing the results, click “Continue” to return to the main analysis screen.

Figure 4.  Isolate selection criteria

Figure 7. %RIS and test measurement results for S. aureus with two isolate criteria defined: Specimen type = Blood and Erythromycin-Disk = Resistant.

Before you leave this section, remove the selection criteria that you defined. To do this, click on “Isolates” and “Delete all criteria”. You will be asked to confirm your choice, so answer “Yes”.

Figure 5.  Isolate selection criteria

There are several additional options which permit small adjustments in the presentation of the results. To see these, click on “Options”, and review the options available to you. For this tutorial, make the following small change to the %RIS analysis.
For “%RIS and histograms”, change the option “Percent of isolates” to “Number of isolates”. Then click on “OK”, and “Begin Analysis”. In the output, you will see the number of isolates resistant, intermediate, and susceptible, rather than the percentages seen in the earlier analysis.
Click on “OK” to proceed to return to the main analysis screen.

Figure 1.  Other options

Figure 9. Additional analysis options.

In Data Analysis 1, you saw how to do isolate listings, summaries, and %RIS statistics. In this section, you will see how to compare the results of two antibiotic tests to each other.

Click on “Analysis type”, and select “Scatterplot”. In the lower part of the screen, you will select to antibiotic tests to compare. For the first example, put the Penicillin-Disk test on the X axis and the Oxacillin-Disk test on the Y axis. Then click “OK” and “Begin analysis” to get the following graph.

Figure 1.  Scatterplots

This graph shows the zone diameter distribution of isolates tested against both penicillin and oxacillin. Numbers in the figure represent percentage of isolates, and the red lines indicate the interpretative breakpoints.

For example, in the upper right-hand corner of the graph, there are a number of isolates with large zone diameters for penicillin (≥30mm) and large zone diameters for oxacillin (≥13mm). These isolates are susceptible to both agents – this is the traditional wild-type phenotype for S. aureus. The lower left-hand quadrant represents isolates resistant to both drugs; these would be the MRSA isolates. The greatest number of isolates is in the upper left-hand section of the graph. Such isolates are resistant to penicillin (to the left of the red line), but susceptible to oxacillin (above the red line). This is the classical phenotype for beta-lactamase (penicillinase) producing S. aureus.

Fortunately, there are no isolates in the lower right-hand quadrant. Such isolates would have the phenotype penicillin-susceptible and oxacillin-resistant. Microbiologically, such results would be exceedingly rare, and most likely attributable to an error in the laboratory (poor quality reagents, test performance, measurement, transcription, etc.)

Thus a scatterplot can be useful both in the description of molecular mechanisms of resistance, as well as in the detection of unusual or impossible phenotypes suggestive of possible errors. Click on “Continue” to return to the main data analysis screen.

To obtain the scatterplot that you just reviewed, you will need quantitative data (zone diameters and/or MIC values). If you do not have these measurements, you can still do a this kind of comparison, but using the test interpretations rather than the measurements.

Click on “Analysis type”. In the middle of the screen, the current select is “Test measurements”. Click on “Test interpretations”. Click on “OK” and “Begin analysis”.

Figure 2.  Scatterplots

In this output, you see the same kind of results seen in the quantitative scatterplot, but using the R, I, S categories. You will again observe the three major subtypes of S. aureus in this chart. 21.2% of the isolates have the wild-type phenotype (PEN-S, OXA-S), 68.2% have the penicillinase-producer phenotype (PEN-R, OXA-S), and 10.6% have the MRSA phenotype (PEN-R, OXA-R). Click on “Continue” to return to the data analysis screen.

Click on “Analysis type”, and choose the following scatterplot options: X-Axis = Oxacillin-Disk and Y-Axis = Ciprofloxacin Disk. Do this scatterplot both by Test measurements and by Test interpretation to get the following two graphs.

Figure 3.  Scatterplots

In the previous example, the two drugs selected (penicillin and oxacillin) were from the same class of drugs (beta-lactams). Such a comparison is useful for studying mechanisms of resistance and quality assurance (finding unlikely resistance phenotypes). In this example, the antibiotics oxacillin and ciprofloxacin are from two different classes of drugs with distinct mechanisms of resistance, so the graphs give information about cross-resistance and genetic linkages between classes. For example, in this case you see that most MRSA isolates (oxacillin-resistant) are also resistant to ciprofloxacin, a commonly observed epidemiological finding in many institutions.

Besides their value in studies of molecular epidemiology, studies of cross-resistance are useful to pharmacists and clinicians in developing policies for first-line and second-line treatment alternatives and to infection control staff in describing distinct clones causing hospital-acquired infections.

The final analysis that covered in this tutorial is the study of multi-resistance patterns using the analysis “Resistance profiles”. Click on “Analysis type”, and select “Resistant profiles”. Because you are analyzing only one month of data, change the option “Month” in the middle of the screen to “Day”.

Figure 1.  Antimicrobial resistance profiles

Then “OK” and “Begin analysis”. The following isolate listing shows the bottom portion of the output.

Figure 2.  Antimicrobial resistance profiles

This listing is very similar to the one you did in Data analysis 1 with the analysis option “Isolate listing and summary”. But there are two additional columns: “Profile” (using one-letter antibiotic codes) and “Resistance profile” (using three-letter antibiotic codes). These columns indicate the multi-resistance pattern of the isolates. The profiles indicate the drugs to which the isolate is either resistant or intermediate (i.e. non-susceptible). For example “PE” = “PEN ERY” = isolates non-susceptible to penicillin and erythromycin, but susceptible to the other drugs requested.

Completely susceptible isolates appear at the top of the listing, followed by isolates non-susceptible to one drug, then to two drugs, etc. Multi-resistant strains appear at the bottom of the listing. This analysis thus categorizes all of the observed isolates according to resistance phenotype. If a patient has multiple isolates, you can see whether the isolates have the same resistance phenotype, or whether the phenotype changes over time, for example accumulating mutations, resistance genes, and plasmids. By examining the dates and the room numbers, you may also detect possible outbreaks of certain strains of S. aureus as defined by their multi-resistance pattern.

Click on “Continue” to see a summary of this list. Figure 3.  Antimicrobial resistance profiles

This output summarizes findings for all resistance phenotypes observed in the database. In this sample database, you will see that the most common phenotype is pan-susceptible (susceptible to all drugs requested) followed by “PEN” (non-susceptible to penicillin). Among MRSA isolates, the most common phenotype is “PEN OXA ERY CLI GEN SXT CIP”, in other words non-susceptible to all drugs requested with the exception of vancomycin. The day-by-day distribution of this MRSA phenotype is shown in the graph.

Click on “Continue” to return to the main menu.

In this analysis, WHONET did not analyze results for all of the drugs tested again S. aureus. Instead, WHONET used the drugs indicated in the laboratory configuration. To see and modify the drugs used for this analysis, click on “Analysis type” and “Edit profiles”.

Figure 4.  Antimicrobial resistance profiles

This list indicates which antimicrobials will be used, by default, for each organism group. For the item “Staphylococcus”, click on “Edit”.

Figure 5.  Antimicrobial resistance profiles

On this screen, you can select the drugs to use for the resistance profiles. Drugs in the box “Profile antibiotics” will be used to define the resistance phenotype. Drugs appearing under “Supplementary antibiotics” will appear in the line-listing, but are not used to define the resistance phenotype.

Note: Any modifications that you make to the profile antibiotics while you are in the Data analysis area of WHONET will be forgotten as soon as you leave WHONET. Any edits that you do here are temporary. To save the changes permanently for future use, you will need to use the WHONET configuration program. To do this, you will need to go back to the main WHONET screen and select “Modify laboratory” and “Antibiotics”. You will see a button called “Profiles”. After you change the profile antibiotics, click on “Save” to save them into your laboratory configuration.

In the tutorials Data analysis 1 and Data analysis 2, you learned about the most commonly used WHONET analysis options and features. There are additional useful features covered in the following tutorials:
Expert System
Macros and Excel Reports
Cluster Detection with SaTScan (not activated yet, pending publication)

Expert system #back to top


The WHONET 5.4 Expert System consists of a number of components:
Part 1. Isolate alerts - Microbiological alerts - Statistical alerts
Part 2. Expert antimicrobial interpretation rules
Part 3. Selective antimicrobial reporting

WHONET now permits the user to take advantage of pre-defined or user-defined expert rules that can benefit the user in data entry and in clinical reporting. An additional unique feature of the WHONET expert system is the integrated use of expert rules in data analysis.
At present, WHONET 5.4 includes approximately 200 microbiological rules. In this first version of the expert system, pre-defined expert rules cannot be edited, but individual rules can be turned on or off by the user. In addition, users are also free to develop their own expert rules for reporting and analysis.

Rules are flagged according to the following alert categories.

- Quality assurance
  • Unlikely resistance
  • Unlikely susceptible
  • Unlikely phenotype
  • Disk diffusion is not recommended for this organism and antibiotic
  • Other problem
- Microbiological alerts
  • Important microbial species
  • Important antimicrobial resistance
  • Save the isolate
  • Send the isolate to a reference laboratory
  • Other alert
- Clinical alerts
  • Alert the infection control team
  • Therapy comment
- Priority
  • High priority
  • Medium priority
  • Low priority

1A. Configuration of microbiological alerts

Begin WHONET, select your laboratory, and click on “Modify Laboratory”. You will see a new button on the screen for “Alerts”. Click on this button, and you will see the following screen.

Figure 1.  Isolate alerts

Predefined alerts

In the example, a rule for Enterobacteriaceae non-susceptible to carbapenems has been selected. Details of the rule appear below. The software customizes the rules depending on the antimicrobials which you test in your laboratory. You can click on “Active rule” to activate or deactivate the rule. At the top of the screen, you can decide whether you want to view all rules, or only rules of a particular type, for example Quality control rules.

There is also a button called “Select pre-defined alerts”. At present, there is only one set of expert rules defined in WHONET, but it is anticipated that in the future, some countries or projects may wish to create their own pre-defined sets for use in the surveillance network.

User-defined alerts

Click on “New”, and a screen similar to the following will appear. To define a rule, first give a name to the rule, for example “S. aureus and spa typing”. You can indicate whether this is a high, medium, or low priority rule. In the area “Define the selection criteria”, use the “Organisms” and “Isolates” buttons in the same way that you would in WHONET data analysis to select the organism/isolate criteria for the alert.

Figure 2.  Isolate alerts

Now that you have defined the criteria which will trigger the alert, you can indicate that details of the alert back to the user. Use “Alerts” to indicate that category and type of alert, and select “Messages” to enter any messages you wish to display back to the microbiologist or to the clinician. If you click “Alert”, you will get the following screen:

Figure 3.  Isolate alerts

Indicate the flags which you wish to apply to the new alert, and click “OK”.
If you click on “Messages”, you will get the following. Indicate any messages you wish to send to the microbiologist or clinician, and click “OK”. When you complete all details of your new alert, you can return to the main configuration screen to save your modifications.

Figure 4.  Isolate alerts

1B. Alerts and Data entry

Alerts are a significant enhancement to the data entry program. They can assist in the identification of typing errors, prompt notification of resistance results, and educational information on recommended laboratory testing practices.

Go to the Data Entry program, and process with normal entry of information. As you begin to enter results, any alerts triggered will appear automatically in the lower right-hand corner of the screen, as in the figure below.

Figure 5. Isolate alerts

If there is a “High priority” alert, you will receive an alert similar to the following.

Figure 6.  Isolate alerts

When you save the isolate, you will get a summary of all of the alert messages.

Figure 7.  Isolate alerts

1C. Alerts and Data analysis

One of the powerful features of the expert system is the integration of microbiological alerts into analysis tools. This will facilitate a quick review of large amounts of data, highlighting possible laboratory errors or important resistance findings. For national data managers, this feature can facilitate the prompt feedback to laboratory participants and further identification of problems identified.

In Data Analysis, microbiological alerts are integrated into a two main areas: 1. isolate listings and 2. BacTrack – Isolate alerts. To test out the new features, you may use the WHO Test Hospital sample database or your own. The following screens were prepared with the WHO Test Hospital data.

Isolate listings: Go to Data Analysis, and choose “Analysis Type”. Click on “Isolate listing and summary”. Click on the new option: “Include isolate alerts”.

Figure  8.Isolate alerts

Click on “Alerts” to see additional options. As you can see in the below screen, you can include all alerts in the analysis, or only certain categories of alerts of interest to you. By default, WHONET will include all High and Medium priority isolate alerts from all alert types. Indicate the alerts that you want included in your analysis. Then click “OK”, and then “OK” again to return to the main analysis screen.

Figure 9.  Isolate alerts

For “Organisms”, select “ALL” organisms. For “Data files”, select “w0195who.tst”. Then “Begin analysis”.

The left portion of the screen will look like the below. This is unchanged from earlier versions of WHONET. WHONET will display test interpretations for this analysis rather than zone diameters of MIC values.

Figure 10.  Isolate alerts

The right portion of the screen looks like the following.

Figure 11.  Isolate alerts

The usual line-listing from earlier versions of WHONET has now been supplemented with microbiological comments about potentially incorrect or important results. By clicking on any column heaing, the results table can be sorted by that column. In this way, it would be easy to see a list of isolates that should perhaps be repeated and sent to a reference laboratory if necessary.

BacTrack – Isolate alerts

In the isolate listing and summary, this user view results from all isolates, many of which may have alert comments. In the “Isolate alerts” feature, only strains with alerts are presented to the user. Alerts include a combination of microbiological rules, as described above, as well as statistical alerts for isolates occurring in low frequency according to the historical data of that laboratory.

To take advantage of the statistical “low frequency” alerts, you should first create a BacTrack reference dictionary with historical data from this laboratory – for example, the 2005 data file. You will then compare your new data file against this historical data. Alternatively, you could create the BacTrack dictionary using the new data file.

For this example, choose “BacTrack – Isolate alerts” and “Create dictionary”. Then click “OK”. For Organisms, WHONET will automatically include “ALL” isolates. For data files, select “w0195who.tst”. Then “Begin Analysis”. When the analysis is finished, you will receive a message “BacTrack has completed the dictionary.”

Figure 12.  Isolate alerts

Now return to “Analysis Type” and select “BacTrack – Isolate alerts”, “Isolate alerts”. As earlier, you can click on “Alerts” to select those alerts you would like included in the analysis. You may also set the percent of isolates to be used as a threshold for the determination of “infrequent” results. The default is 5% for each option. To increase the number of flagged isolates, you can increase this percentage. To decrease the number of flagged isolates, then lower the percentage. You can put the percentage at 0% if you want to turn a particular feature off.

Figure 13.  Isolate alerts

When finished your selections, click “OK” to return to the main analysis screen, and “Begin analysis”.

Figure 14.  Isolate alerts

Every isolate included in this printout has at least one alert flag. Statistical “low frequency alerts” are found to the left of the listing, and are marked by a special symbol: 1. “*” – the observed resistance is infrequent, based on the hospital’s local data; 2. “#” – the observed susceptible result is infrequent, based on the hospitals’ data; and 3. “+” – the antibiotic indicated is not frequently tested for this organism, based on the hospital’s data.
In this particular example, examples of “infrequent” results include: E. coli resistant to gentamicin; Enterococcus spp. susceptible to clindamycin; H. influenzae resistant to trimethoprim/sulfamethoxazole; P. aeruginosa resistant to amikacin; P. aeruginosa resistant to tobramycin; and P. mirabilis resistant to ampicillin. While such findings may be common in other institutions, the alerts indicate that these findings are rare (<5%) for the results of organisms in this laboratory. Findings of low frequency may perhaps be due to laboratory error, so should be confirmed; or they may reflect important new resistant strains still present at low levels in the institution.
In contrast to the fixed, pre-defined, globally relevant microbiological expert rules described earlier, a great advantage of the “low frequency” alerts is that alerts are automatically adjusted to the past experience of this particular laboratory for all tested organisms and antibiotics.
After viewing the isolate alert listing, click “Continue” to proceed to the isolate alert summary. The summary tabulates every alert that was encountered in the scanned data. Totals are provided, as well as the type of alert – “quality assurance”, “send to a reference laboratory”, etc. If results from more than one laboratory are scanned, the summary also includes the breakdown of alerts by laboratory, as illustrated in the screen below.

Figure 15.  Isolate alerts

The microbiological rules described above provide alerts of various sorts to the user. These rules do not change the antimicrobial test interpretation. There are a few additional rules which actually do change test interpretations given certain findings, for example, an isolate of MRSA should be considered resistant to all beta-lactam agents, irrespective of the in vitro test measurements.
To review the current expert interpretation rules, choose “Modify laboratory” to enter the configuration area, “Antibiotics”, “Breakpoints”. You will see the following screen. Click on “Expert interpretation rules.

Figure 1.  Expert interpretation rules
Figure 2.  Expert interpretation rules

You will see the five expert interpretation rules currently defined, adapted from CLSI recommendations: 1. methicillin-resistant Staphylococcus; 2. confirmed ESBL-producing E. coli, K. pneumoniae, K. oxytoca, or P. mirabilis; 3. probable ESBL-producing E. coli, K. pneumoniae, K. oxytoca, or P. mirabilis; 4. beta-lactamase negative ampicillin-resistant H. influenzae; and 5. DTest positive strains of Staphylococcus and Streptococcus.

At the present time, users cannot create new interpretation rules or edit existing ones. Rules can be activated or deactivated by the user.

It is important to understand when WHONET applies these expert rules. For Data Entry and clinical reporting, these rules are always applied (unless specifically deactivated by the user). In Data Analysis, these rules are are never applied until the option is turned on by the user.

In the Data Analysis program, if you want to apply these expert interpretation rules, go to “Options” and click on “Use expert interpretation rules”. It is the first option listed on the screen.

Figure 3.  Expert interpretation rules

For laboratories using WHONET as a clinical reporting system, the ability to selectively report or suppress certain antimicrobials can be important in supporting rational drug use and guiding clinical therapy decisions.

To configure the selective reporting rules, click on “Modify laboratory”, “Antibiotics”, “Panels”, and click on “Conditional antibiotic reporting”.

Figure 1.  Selective antimicrobial reporting

In the screen below, you can indicate your standard First-line agents, which should typically be reported for all isolates. You can indicate Second-line agents, which will be included in the clinical report under certain conditions (if the result itself is resistant or if the isolate is resistant to multiple First-line agents). For drugs that are principally used only for organism identification (optochin, novobiocin, etc.), you can choode “Do not print” to exclude these isolates from clinical reports.

Figure 2.  Selective antimicrobial reporting

In addition to the results described on this screen, you can enter “Additional rules” to define additional reporting criteria.

The responses that you enter in these screens will set the default behavior for clinical reporting. During data entry, you can change these selections manually by including or excluding additional antimicrobials by using the F8 and F9 keys. In the below screens, antibiotics appearing in gray to not appear in the clinical report.

Figure 3.  Selective antimicrobial reporting

Macros and Excel Reports #back to top


Macros and Reports are valuable features which can be used to facilitate the preparation of standard outputs for use within the laboratory or for distribution to other services. In WHONET, a Macro is a small file which remembers the details of one of your analysis requests, and a Report is a collection of multiple macros. Reports can be viewed on the screen, but are more usefully saved as formatted Excel files for later viewing.

For someone who knows WHONET well, macros and reports can be a significant time saver. For users new to WHONET or to microbiology, the use of WHONET standard reports or locally prepared reports is learned easily, and provides access to focused, important information with minimal effort.

In addition to their value in interactive WHONET use, Macros and Reports can be used to automate analyses or to integrate WHONET into an internet page or other development package.

A macro is a small file which remembers the details of one of your analysis requests. You can save a macro at any time during Data Analysis, and then call up this macro again easily at any time in the future.

As an example, go to WHONET, find the “WHO Test Hospital” and “Open Laboratory”. Enter the Data Analysis program. Enter a simple analysis with the following selections: Analysis Type = %RIS and test measurements, Organisms = E. coli and S. aureus. Data file = w0195who.tst. Begin Analysis. Review the analysis results, and select Continue twice to return to the main analysis screen.

Figure 1.  Creating and using Macros

To save these analysis parameters as a macro, click on “Macros”, and you will see the following.

Figure 2. Creating and using Macros

Click on “New” to define a new macro. Give a name to the macro, for example “eco and sau RIS results”.

Figure 3.  Creating and using Macros

After entering a name, click on “Save” to save the macro. Windows will ask you to give a name to the macro file. By default, WHONET will use the macro name plus the letters “.mcr”. Macros by default are saved in the c:\whonet5\macros, but could be saved in any other folder as well.

Figure 4.  Creating and using Macros

Click on “Save” and “Exit” to return to the main analysis screen. Next, leave WHONET completely.

Then restart WHONET, select the WHO Test Hospital, and go to Data Analysis. In Data Analysis, click on “Macros”. Select the macro which you have just created, and then click “Load”. WHONET will then load all of the options which you had previously selected. You could then “Begin Analysis” immediately to view the analysis results, or you could make modifications to the options loaded from the macro prior to starting the analysis.

As a second example, try to create a macro with the following details. Give the macro the name “MRSA listing and ward summary”. Run the macro to ensure that it works correctly.

  • Analysis type = Isolate listing and summary, Row=Location, Column=Specimen Date
  • Organism = S. aureus
  • Isolates: Oxacillin = Resistant
  • Data file = w0195who.tst

The value of macros and reports has been significantly enhanced through improvements in the formatting of Excel files prepared by WHONET. To see these modifications, load up the macro created in Part 1 and run the analysis. You will see the following screen for E. coli.

Figure 1.  Saving analysis results as an Excel file

The click on “File”, “Save table”. For the file name, enter “eco RIS results.xls”. For the question “Save as type”, select Excel.

Figure 2.  Saving analysis results as an Excel file

WHONET will save the analysis results as an Excel file. Note that by default, WHONET will save the results in the c:\whonet5\output folder.

Now go to Excel and open the file: c:\whonet5\output\eco RIS results.xls. Two parts of the Excel spreadsheet are shown below.

Figure 3.  Saving analysis results as an Excel file Figure 4.  Saving analysis results as an Excel file

Quick Analysis is a new analysis area in WHONET. The intent is to provide much of the benefit of the WHONET interactive analysis program, but with minimal time and effort. Users can choose from a few Standard Reports offered by WHONET or they may create their own reports for use within the laboratory or by clinical services in other hospital areas, such as infection control or pharmacy.

For this example, begin WHONET, open the “WHO Test Hospital”, go to “Analysis” and select “Quick Analysis”.

Figure 1.  Quick Analysis

Select “WHONET Standard report”, and choose the w0195who.tst data file. Click on “Begin Analysis”.

WHONET will perform multiple analyses on the selected data file(s), and prepare a multi-part overview of key results. A few of the sections are depicted below. (Note: The formatting and presentation of the standard report on the screen has not been optimized. This will be completed in the near future.)

Figure 2.  Quick Analysis
Figure 3.  Quick Analysis
Figure 4.  Quick Analysis

Part 3 illustrated the use of a multi-part analysis to provide various types of information to the user. In this part, the creation of a new report format by the user is described. To take advantage of this option, you will need to create one or macros, as described earlier in Part 1.

In the Quick Analysis screen, click on “New”. Give a name to the new report, for example “Weekly infection control report”. On the left side of the screen, you will see the macros that you created earlier in Part 1. Select these macros over to the right side of the screen.

A report typically consists of multiple macros, but a report can also include other reports. In this way, you can build up more complete reports from smaller subreports.

Figure 1.  Quick Analysis and User-defined Reports

After you have selected the macros and reports to include in this report, click on Save. By default the name of this file will be “Weekly infection control report.rpt”, and the file will be saved in c:\whonet5\macros. After you save the report file, click on “Exit” to return to the main Quick Analysis screen.

Figure 2.  Quick Analysis and User-defined Reports

Choose the new report that you have just created. Choose the w0195who.tst data file. Change the “Output” destination to “Excel”. WHONET will give the default name: “C:\whonet5\Output\Weekly infection control report-2006-06-02.xls” to the file, i.e. the name of the report plus the date of creation.

Begin the analysis. When the analysis is completed you will be asked if you want to view the new Excel file. Click “Yes”.

Figure 3.  Quick Analysis and User-defined Reports

WHONET will now open Excel. If it does not pop up on the screen in front of you, check the list of open programs at the bottom of the screen to see if Excel is open. If so, click on Excel to see your results file.

Below is a portion of the Excel report created by WHONET. You will notice that the file has four worksheets. These correspond to the following four pages generated by the two macros selected for the report: 1. eco - %RIS, 2. sau - %RIS, 3. MRSA – Isolate listing, and 4. MRSA – Location summary.

Figure 4.  Quick Analysis and User-defined Reports

With the use of macros and reports, WHONET analyses can be accessed from the Windows command line, Windows Task Scheduler, other softwares developed by programmers involved in public health surveillance, or Internet pages. The syntax is simple. Simply write the name of the macro or report after the program name – whonet.exe. An example of a command to automatically call WHONET using one of the above macros would be: c:\whonet5\whonet.exe “eco and sau RIS results.mcr”

Note – if the macro name includes spaces, you must enclose the macro name in quotation marks. If the macro is in the default macros folder (usually c:\whonet5\macros), then you do not need to indicate the macros location. Otherwise, you should include it in the command.

The Windows Task Scheduler The Window Task Scheduler is a standard feature in Windows computers, and is often used to automate repetitive tasks, such as virus checking or software backups.

Note: In the absence an automated BacLink download, a scheduled WHONET analysis will be of little benefit for most users. In the future, as automated BacLink setups become more common, then automated analyses with WHONET and automatic e-mailing of reports to relevant hospital staff will become much more valuable.

You can access the “Task Scheduler” either from the Windows Control Panel or from “All Programs”, “Accessories”, “System Tools”, “Scheduled Tasks”. Click on “Add Scheduled Task”. From the list of softwares on your computer, select WHONET 5.4.

Figure 1.  Macros, Reports, and Automation

Indicate the desired scheduling, for example “Weekly” or “One time only”. The below example sets up an automated analysis every Monday morning at 6am. Click Next. If requested, provide your Windows password.

Figure 2.  Macros, Reports, and Automation

You will then see the final screen of the basic setup.

Figure 3.  Macros, Reports, and Automation

You are not quite finished yet. If you click “Finish” now, WHONET will run at 6am on Monday, but it will simply open and not perform any analyses. We need to tell the system which macro or report we want WHONET to run.

To do this, click on the box labeled “Open advanced properties for the task when I click Finish”. After putting a checkbox there, click on Finish to proceed to the advanced properties. Under “Run”, the system will just have “c:\whonet5\whonet.exe”. To this you need to add the name of your macro or report, for example “eco and sau RIS results.mcr” in the below screen. Click OK to finalize the task.

Figure 4.  Macros, Reports, and Automation

Click “OK” to finalize the task. You will be returned to the Scheduled Tasks folder. The default name of the task is “WHONET 5”, but you can change this to a more meaningful name. To view all details of the task, click on “View”, “Details”.

Figure 5.  Macros, Reports, and Automation

Calling WHONET from another program

Here is an example from an early version of the new ABC Calc software under development at the State Serum Institute in Copenhagen. The focus of ABC Calc is the management of antimicrobial consumption data, but ABC Calc will also have an integration tool allowing for the simultaneous analysis, presentation, and correlation of antimicrobial resistance data (from WHONET) and consumption data (from ABC Calc).

In the below screen, the user selects their analysis options from an interface similar to WHONET. When the user clicks on “Load WHONET data”, ABC Calc prepares a WHONET macro with the user selections, which it sends to WHONET for analysis. WHONET runs the analysis, and saves the results in a simple text file. ABC Calc waits for WHONET to finish and then reads and displays the text file back to the user, for example on a graph which also displays antimicrobial consumption statistics.

Figure 6.  Macros, Reports, and Automation

Cluster Detection with SaTScan™ #back to top


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, 2006.

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.

In WHONET 5.4, SaTScan statistics have been integrated into two standard analysis features: 1. Isolate listing summaries and 2. Resistance profile summaries. Two new analysis options specific to SaTScan have also been added: 1. SaTScan – Cluster detection in Data Analysis and 2. SaTScan – Space-and-Time cluster detection in Quick Analysis.

Open the WHO Test Hospital, and go to Data Analysis. Go to Analysis Type, and select Isolate listing and summary. At the bottom of the screen, click on the option “Include SaTScan alerts”. By doing this, the SaTScan statistics will be integrated directly into the standard Isolate Listing Summary output.

Figure 1.  SaTScan and Isolate listing summaries

Note: In the above example, the column variable has been set to “Specimen date” by “Day”. In most cases, you should probably leave this option set to “Month” or “Week”. But for purposes of this tutorial, we have set the option to “Day” because the sample dataset only includes one month of data.

To see the details of the SaTScan analysis, click on “SaTScan” to see the below screen.

Figure 1.  SaTScan and Isolate listing summaries

On this screen, you will see a small minority of all of the parameter options available in SaTScan. The use of SaTScan to study microbiological laboratory data and hospital infections data is very new, and will be a major focus of the 5-year NIH grant. As we gain more experience with the use of SaTScan for microbiology data, the number of options included in WHONET will increased and the suggested default parameter values will change to reflect optimal use of the program by microbiologists, infection control, and clinical staff.

In the above example, the user has access to two SaTScan variables.

Analysis type: Retrospective vs. Prospective. Retrospective analysis looks for infectious disease clusters at any time during the data analysis time period – both old clusters and new clusters. This option would be very useful in a retrospective look at available data for any possible outbreak. Prospective analysis only looks for clusters that potentially are still ongoing. This option is appropriate for the prospective detection of outbreaks in the new data.

Maximum cluster length: Indicate the number of days for the greatest length of a possible outbreak. At present, the default is set to 15 days. In other words, SaTScan will look for clusters that are anywhere from 1 day to 15 days in length. If an outbreak is longer than this period, SaTScan possibly may not detect it or possibly may detect only part of it. To find the greatest possible number of potential clusters, you can put a large value for the Maximum cluster length. A long period can slow SaTScan down considerably, so you can experiment to see what impact this value has on 1) the number of detected clusters and 2) the time period needed for the analysis.

Note: In SaTScan, the largest possible value of the Maximum cluster length is half the analysis time period. For example, if you have one year (365 days) of data to scan, the largest value that SaTScan will accept is 182 days. It is not a problem if you enter a higher value into WHONET. WHONET will dynamically adjust the value before it sends the analysis parameters to SaTScan.

Location options: In WHONET so far, we are not yet taking advantage of SaTScan’s ability to handle geographic data. For outpatients, such variables could include zip code or street address GPS latitude and longitude. For inpatients, it is possible describe to SaTScan the geographic (hospital physical location) or functional (clinical care service) relationship between patient care units. So at the present time, WHONET does an automatic configuration of patient locations, treating each ward as a separate “island” of care, unconnected to any other wards.

In the future, it will be possible for WHONET users to describe the ward structure of hospital units in a SaTScan “coordinate file” in a simple user interface. If a user does take the time to describe the geography of their hospital to WHONET, this option will permit the user to select the coordinated file created.

After you select the desired features, click “OK” to return to the main analysis screen.

Then click on “One per patient”. Select the options “By patient”, “First isolate only”.

Note: It would be probably more useful for cluster detection to put the option “By time interval or resistance phenotype”, for example with a 30 day window between isolates. This option does exist for %RIS calculation, but unfortunately, this option is not yet ready for other analyses, such as isolate listings and resistance profiles. This will be addressed in the near future.

Figure 3.  SaTScan and Isolate listing summaries

Note: We do not yet know what criteria would be most effective in detecting real infectious disease outbreaks, and whether the criteria should differ for different organisms. SaTScan does an excellent job of finding statistically defined “clusters” of events, but the clinical interpretation of these clusters will depend on the experience and insight of infection control and clinical staff. With more testing on real datasets, we will aim to provide tested and validated recommendations for setting the cluster detection parameters.

Finally, click “OK” and Begin Analysis. First you will see the standard isolate listing. (SaTScan makes no changes to the isolate listing. If you do not wish to see the listing, you should choose “Summary” as the Report format rather than “Both”.)

When you click Begin Analysis, WHONET will read the data files, and prepare the files needed by SaTScan to operate. WHONET will then send this information to SaTScan. A small icon will appear at the bottom of the screen to tell you that SaTScan is running in the background. When SaTScan is finished, this icon will disappear automatically.

After SaTScan is finished analyzing the data, WHONET will read the SaTScan results, and integrate the statistics into the normal WHONET output, as in the below screen.

Figure 4.  SaTScan and Isolate listing summaries

In addition to the typical columns for Isolate listing summaries, you see several additional columns in this output related to the clusters detected by SaTScan.

In the sample dataset with one month of data, WHONET found 39 bacterial species. SaTScan identified possible clusters in 7 of these species. Cluster number 1 is the cluster of greatest statistical significance (smallest p-value), etc. Only one of the identified clusters has a small p-value:

  • Organism Klebsiella pneumoniae
  • Cluster dates January 28-30
  • Observed 8 patients
  • Expected 1.75 patients
  • p-value 0.065

This particular organism is depicted in the below graph, confirming that there does indeed seem to be a rise in the number of patients with K. pneumoniae at the end of the month.

Figure 5.  SaTScan and Isolate listing summaries

In Part 1, we saw how SaTScan statistics can be applied to organism frequency data. In this section, we will see how the same statistics can be applied to resistance profile data. For the output columns, put “Specimen date” by “Day”. (As above, we are selecting “Day” in this tutorial because there is only one month of data.)

Go to “Analysis Type”, and select “Resistance profiles”. Check on the box for “Include SaTScan alerts”.

For “One per patient”, put “By patient”, “First isolate only”. For “Organisms”, select S. aureus. Then begin the analysis. WHONET will first show you the Resistance profile listing. This is not affected by the SaTScan analysis. Hit Continue to proceed to the Resistance profile summary.

Figure 1.  SaTScan and Resistance profile summaries

WHONET found 60 isolates of S. aureus, which cluster into 16 different resistance phenotypes. (The results “-” and “---” indicated that the indicated antimicrobials were not tested). From the 16 resistance phenotypes, SaTScan identified 4 possible clusters. Cluster number 1 has the following characteristics.

  • Resistance profile PEN
  • CIP (non-susceptible only to PEN and CIP)
  • Cluster dates January 29-30
  • Observed 2 patients
  • Expected 0.21 patients
  • p-value 0.53

The graph for this resistance profile is given above. Even though the number of isolates is very small, and the p-value is not, this cluster may still be of interest. In the entire month of January, this resistance profile was only seen three times, all at the end of month – once on January 26 (not detected by SaTScan), January 29, and January 30. In a further investigation, it would be useful to look at the patient locations. If you refer back to the Resistance profile listing, you will notice that the three isolates came respectively from location “xx = Unknown”, “er = Emergency Room”, and “op = Outpatient”. So there is no epidemiologic link between these three patients with the available data, but one possibly would be revealed with further investigation of the patient medical records.

In parts 1 and 2, we saw how SaTScan results can be integrated with standard WHONET analyses. In the next two parts, we will focus only on the information generated by SaTScan. In “Analysis type”, select “SaTScan – Cluster detection”. At the bottom of the screen, click on “SaTScan” to see additional options. In all above analyses, we used a Retrospective analysis. For this example, choose Prospective analysis.

For organisms, put “All organisms”. For One per patient, put “By patient”, “First isolate only”. Begin the analysis.

Figure 1.  SaTScan – Cluster detection (Data Analysis)

In Part 1, we saw that January had 39 bacterial species. Of the 39 species, SaTScan has identified 18 possible “ongoing” clusters, in other words clusters that potentially could include January 31, the final date of the analysis period. Of the 18 clusters, only one has a small p-value

  • Organism Klebsiella pneumoniae
  • Cluster dates January 28-31
  • Observed 8 patients
  • Expected 2.36 patients
  • p-value 0.057

This is the same cluster detected in Part 1 of this tutorial.

Now exit from the usual Data analysis program, and select “Quick analysis”.

Figure 1.  SaTScan – Space-and-Time cluster detection (Quick Analysis)

Choose the option “SaTScan – Space-and-Time cluster detection”. If you click on “Edit”, you will see the same SaTScan options menu which we saw in Data analysis.

For Data files, choose the w0195who.tst data file. Click on Begin analysis.

WHONET will display for you a two-part output. Part A – SaTScan report is the actual report prepared by the SaTScan software summarizing the details of the analysis performed and all statistical findings. This output begins with a brief summary of the analysis performed and the data summarized.

It then continues with a list of all of the identified clusters in order of decreasing statistical significance. Finally at the bottom of the output, you will see the detailed parameter settings used for the analysis.

Figure 2.  SaTScan – Space-and-Time cluster detection (Quick Analysis)

If you continue with Part B – SaTScan summary, you will see that WHONET has extracted the most important pieces of information for display to the user in a concise format. (Note: in this first version of WHONET 5.4, the formatting of the Quick Analysis results has not been optimized. This will be improved in the near future.)

Figure 3.  SaTScan – Space-and-Time cluster detection (Quick Analysis)

How to run Antibiogram? #back to top


From the main WHONET screen after you have opened your Laboratory: 1) Go to Data analysis – Data analysis Figure 1.  How to run Antibiogram You will then see the following screen: Figure 2.  How to run Antibiogram 2) Click on “Analysis type” You will then see the following screen: Figure 3.  How to run Antibiogram

In the middle of the screen, you will see two options: 1. %RIS and test measurements, and 2. Summary.

Select “Summary”

For the columns, the default selection is %Susceptible (which is often preferred by clinicians and pharmacists). You can change this to %Resistant or %Non-susceptible (which is often preferred by microbiologists and epidemiologists). For the rows, the default selection is “Organism”. In other words, the results from each species will be summarized in a separate row row in the output.

Click on “OK” in the bottom right to select the options.

You will now be at the main Data Analysis screen again:

Click on “Organisms”.

You will then see the following screen:

Figure 4.  How to run Antibiogram

Click on “Organism groups” and double-click on “All Enterobacteriaeceae”. Click “OK” to accept the modifications.

You will again be at the main Data Analysis screen.

Next click on “Data Files”

You will see the following screen:

Figure 5.  How to run Antibiogram

Navigate to your data file and select “OK”

You will then be back at the Data Analysis Screen

If you would like to remove repeat isolates, you can do this by clicking on “One Per Patient” in the upper right hand side of the screen.

You will then see this screen:

Figure 6.  How to run Antibiogram

Choose “By patient” and then select “OK”

You will now be at the main Data analysis screen again.

If you would like to choose isolates such as specimen, location, etc. Click on “Isolates”

You will then see the following screen.

Figure 7.  How to run Antibiogram

Double Click on the isolate you would like and put in the information required, then click on “OK”

You will now be on the main Data analysis screen.

Figure 8.  How to run Antibiogram

You should next choose where you would like the output. In the bottom right corner you will see a drop down for “Output to”. Choose “Screen”.

Click on “Begin analysis”. If you wish, you can then copy and paste these results to Excel for further editing of the results for distribution to clinical staff. When you finish reviewing the results, click on “OK” to return to the main analysis screen.

Transferring WHONET results to Excel and other softwares

The WHONET results that you see on the screen can easily be transferred to other softwares such as Microsoft Excel, Word, or PowerPoint. You can do this either by using “Copy” and “Paste” or by saving the results as a file.

Copy and Paste: Click on “Copy table”. Now open Microsoft Excel, for example by clicking on your Windows “Start”, “All Programs” menus and looking for Microsoft Excel. (Alternatively, if you want to immediately go to your Windows Desktop, click on the “Windows” key on your keyboard and hit the letter D, in other words “Windows”-D.)

After you have Excel open, go to “Edit”, “Paste”. The WHONET results are now in Excel. You can now use Excel to edit, correct, format, or graph your results.

Now return to WHONET (for example, by clicking on the WHONET icon on the bottom of your screen). Click on “Copy graph”. Go back to Excel, find an empty part of the spreadsheet, and again choose “Edit”, “Paste”.

Figure 9. How to run Antibiogram

Figure 10. Copying and pasting results to Excel using “Copy table” and “Copy graph” from WHONET.

Save the file: WHONET also has an option for saving the results directly to a file. Because “Copy” and “Paste” works well and is usually very fast, there is often no need to do this, but there are a few situations where saving the results as a table can be useful. 1. For “isolate listings” or “resistance profile listings” with thousands of rows, the “Copy” and “Paste” approach can be very slow. In this case, saving the results as an Excel or as a text file would be much faster. 2. When you save the table as an Excel file, WHONET does some automatic formatting of the results and automatically makes a number of Excel graphs. So by using the “Save table” option, this may save you some time formatting the data in Excel.

To save the tables and graphs as an Excel file, click on “File”. Give a name to the file, for example “S. aureus RIS results.xls”. For type of file, select “Excel”. Notice that the default location for this file is c:\whonet5\output. Then click ‘OK’.

Figure 10. How to run Antibiogram

Figure 11. Saving results from WHONET to an Excel file.

Now go back to Excel and select “File”, “Open”. Look in the folder c:\whonet5\output for the file that you just created, and open it up. You will see something the following.

Figure 11.  How to run Antibiogram

Figure 12. A formatted Excel file created from WHONET.

Then return to WHONET and click “Continue” to return to the main analysis screen.