Using PRIME

Note: This documentation is also available as a pdf from the download page

PRIME is a spreadsheet-based tool created in Microsoft Excel, comprising four sheets:

• Country Selection – select a country of interest and load default input values
• Customisation – an opportunity to override the default input values
• Age Data – an opportunity to override default age-related input values
• Output – displays the results of the tool’s analysis as a chart and graph

Navigation between these sheets is via buttons within each sheet, or using the sheet tabs in the bottom left corner:

Sheet navigation tabs

1. Localising Data

On the first sheet titled ‘Localization’, use the drop-down menu:

To select your country of interest:

The fields below will be automatically populated with default information which has been collected from global databases, position papers and publications compiled by WHO and its academic collaborators.

Further information can be found in the scientific publication describing PRIME.

Explanation of input data fields

Field label	Explanation
Cohort size at birth (female)	The number of female newborns in the country in the base year
Cohort size at vaccination age (female)	The number of females in the country at the age at which routine vaccination is given (based on the age in “Target age group”)
Full-dose coverage	The expected proportion of girls in the relevant age group who will receive the full course of the vaccine (either 2 or 3 doses)
Vaccine efficacy vs HPV 16/18	The proportionate reduction in risk of cervical cancers due to HPV 16/18 in vaccinees. This should normally be 100%.
Target age group	The age at which HPV vaccines are normally given. Note that PRIME is only suitable to be used to look at HPV vaccines delivered to girls in the WHO recommended ages of 9-13 years old.
Vaccine price procurement cost per fully vaccinated girl	The procurement cost to purchase enough vaccines (either 2 or 3 doses) to fully vaccinate one girl
Vaccine delivery cost per fully vaccinated girl	The cost of delivering and administering enough vaccines (either 2 or 3 doses) to fully vaccinate one girl
Total vaccine cost per fully vaccinated girl	The total cost to purchase enough vaccines (either 2 or 3 doses) to fully vaccinate on girl. This is automatically calculated as the sum of the procurement and delivery cost
Cancer treatment cost (per episode, over lifetime)	The cost on average to treat a woman with cervical cancer, from diagnosis to death
DALYs for cancer diagnosis	DALYS incurred for a year of life in which cervical cancer is diagnosed. Advice from a health economist is recommended before altering this parameter
DALYs for non-terminal cancer sequelae (per year)	DALYS incurred for a year of life following the year in which cervical cancer is diagnosed, assuming the cancer is non-terminal. This may vary depending on the country. Advice from a health economist is recommended before altering this parameter.
DALYs for terminal cancer	DALYS incurred for a year of life immediately prior to dying from terminal cervical cancer. Advice from a health economist is recommended before altering this parameter.
Discount rate (%)	The rate representing society’s preference for consumption and health gains in the present rather than in the future. WHO recommends a rate of 3% per annum3.
Proportion of cervical cancer cases due to 16/18	The proportion of cervical cancer cases diagnosed in the base year that are caused by HPV 16 or 18 infection.
GDP per capita	The value of all the goods and services produced in the country divided by the total population.

The output of the tool can be viewed directly by going to the ‘output’ sheet using the navigation tab (see Fig. 1), or the ‘output’ button embedded in the sheet:

After you choose the country, the fields in the table in the Country Selection worksheet are automatically populated with data from global databases. These databases may not necessarily contain the most appropriate data from the country you are looking at. If you have access to additional data sources and/or are able to plan further data collection activities, then customisation is strongly recommended. To edit the input values, go to the ‘customization’ sheet, accessible by tab or using the ‘customize’ button:

2. Customise Data

To use different input values, enter them into the ‘override value’ cells on the ‘customize’ sheet:

We recommend that customizing the parameter inputs and any activities to collect suitable data to inform such an exercise is done in discussion with a team of epidemiologists, health economists, clinicians, policy makers and other experts familiar with cervical cancer data sources in the country.

When entering data, please ensure that you are consistent in the use of units (eg. currency), as well as in the population and year that the data represent.

Changes made to these values will be reflected automatically in the output on the final sheet, accessible as before using the output button:

Further improvements to accuracy can be made by editing the age-related profile of the cohort represented by the model, which can be carried out on the ‘age data’ sheet, accessible by the tabs or via the ‘customize age data’ button:

3. Age Data

The ‘Age Data’ sheet offers another opportunity to customize the PRIME tool’s inputs.

For each year of life, from age 0 to 100 years old, the model accepts three parameters, outlined in Table 2.

Age related parameters

Field label	Explanation
Cervical Cancer Incidence	The probability that a case of cervical cancer is diagnosed in any given woman in the corresponding age group in the base year.
Cervical Cancer Mortality	The probability that any given woman dies of cervical cancer in the corresponding age group in the base year.
All-cause Mortality	The probability that any given woman dies of any cause in the corresponding age group in the base year.

The default values are based on information in global databases compiled by WHO, IARC , UNPD and other sources. Further information can be found in the scientific publication describing PRIME.

Any override values entered in the ‘override values’ cells on this sheet will be reflected automatically in the output on the final sheet

4. Understanding the Output

The ‘Output’ sheet contains a table of values and a chart.

Understanding the Chart

The chart includes two output columns, as seen in Figure 3.

Undiscounted values are those which do not have a discount rate applied, i.e. they represent no preference between consumption and health gains occurring today or in the future.

Discounted values are values which incorporate the discount rate from the list of input values, i.e. they represent values after taking into account a preference for consumption and health gains occurring today against similar gains in the future.

Example output chart

Here is more information to aid understanding of the model’s outputs:

Output values explained

Field label	Explanation
Cohort size at birth (female)	The number of female newborns in the country in the base year.
Cohort size at vaccination age (female)	The number of females in the country at the age at which routine vaccination is given (based on the age in “Target age group”).
Cost of Vaccination including delivery costs	The total cost of vaccinating a single age cohort in the base year.
Treatment Costs Saved	The treatment costs eventually averted due to cervical cancer cases prevented by vaccinating a single age cohort in the base year.
Net cost	The net (incremental) cost of vaccinating a single age cohort in the base year. This is equal to the cost of vaccination minus the treatment costs saved.
Cervical cancers prevented	The number of cervical cancers eventually averted by vaccinating a single age cohort in the base year.
Deaths prevented	The number of deaths eventually averted due to cervical cancer cases prevented by vaccinating a single age cohort in the base year.
Life years saved	The number of life year losses eventually averted due to cervical cancer cases prevented by vaccinating a single age cohort in the base year.
Nonfatal DALYs averted	The number of DALY losses eventually averted due to cervical cancer cases prevented by vaccinating a single age cohort in the base year.
Incremental cost per…
… cervical cancer prevented	The net (incremental) cost of vaccination divided by the number of cervical cancers eventually averted by vaccinating a single age cohort in the base year.
… Life saved	The net (incremental) cost of vaccination divided by the number of deaths eventually averted due to cervical cancer cases prevented by vaccinating a single age cohort in the base year
… Life years saved	The net (incremental) cost of vaccination divided by the number of life year losses eventually averted due to cervical cancer cases prevented by vaccinating a single age cohort in the base year
… DALY prevented	The net (incremental) cost of vaccination divided by the number of DALY losses eventually averted due to cervical cancer cases prevented by vaccinating a single age cohort in the base year

Understanding the chart:

The chart shows the reduction of HPV incidence in the vaccinated population with age.

The incidence of cervical cancer that would be expected over the lifetime of an age cohort with and without vaccination is shown.

Example chart

5. Further Investigations

The model underlying PRIME is described in Jit M, Brisson M, Portnoy A, Hutubessy R. Cost-effectiveness of female human papillomavirus vaccination in 179 countries: a PRIME modelling study. Lancet Global Health 2014; 2(7):e406) which is available from The Lancet.

Modellers interested in the exact calculations involved can find these by right-clicking on a sheet’s tab, and selecting ‘unhide…’ to reveal additional sheets. We recommend that this is only done by expert modellers, and are unable to provide any support for modifying the underlying model equations outside of a formal research collaboration that has been agreed to in advance.