The years for which we show the data. The meaning of the year depends on the plot
The type of vaccination program - routine or
The countries for which we show the data.
Disease / Vaccine
The vaccines for which we show the data. Use the 'Aggregate all diseases'
checkbox to show data aggregated across all diseases and vaccines to exclude double-counting.
The touchstone for which we show the data. This
should usually be set to the latest touchstone, and selecting multiple touchstone is usually
Gavi vs non-Gavi vaccination programs
Explanation of methods
This method shows the impact by calendar year, e.g. the number of people who would have died in a
given year but whose deaths were averted due to vaccination given at any previous time. This is also
known as "cross-sectional impact". While the resulting estimates are intuitively easy to understand,
they fail to represent the long-term future impact of vaccination on individual disease risk. In
addition, the impact estimates cannot be linked to specific vaccination activities.
Year of birth
This method shows the impact for each birth cohort, e.g. the number of deaths prevented in a cohort
born in a given year, over the course of their lifetime. We calculate impact for birth cohorts from
2000 to 2030, and consider the lifetime up to 2100. This is also known as "lifetime impact" or
"cohort impact". This approach is appropriate for capturing the direct effects of vaccination in
protecting the immunised individual. However, indirect effects of vaccination (acting via herd
immunity) play out across the whole population.
Year of Vaccination
This is the approach used by VIMC to estimate vaccine impact by year of vaccination. It can be used
to easily determine the efficacy of a particular vaccination campaign.
Uncertainty is approximate when multiple diseases are selected and the plot is stratified by any
than disease. This is because uncertainty is summed across each selected disease, which may result
double-counting of some metrics. To see calculated uncertainty across all disease, select
'Aggregate all diseases' in the Disease filter.