Background

This flexdashboard displays leaflet maps for a counter-factual-based analysis of the impact of the various COVID-19 vaccines up to 2001. Various counter-factuals, e.g. no vaccines, etc. are simulated using Imperial College London’s nimue model. All other epidemic parameters for each country are taken from the fits presented here. The simulated counter-factuals are compared to a simulation generated using these fits that represent what occured in reality (this is referred to as the baseline). The maps show the difference in deaths and infections between these two simulations for each country. Additionally, the individual numbers of deaths and infections or vaccines assigned (in the counter-factual) can also be plotted using the icon in the top right hand corner.

Additional maps with adjustments can be plotted by selecting the relevant tab. Per 10k refers to deaths/infections per 10,000 people in the countries populations and per 1k vaccinations is per 1,000 people vaccinated (with at least one dose) in that country in reality.

Limitations

As a warning this method assumes that vaccination campaign have no impact on any non-vaccine interventions (these are represented by changes in the parameter R_t).This could be unreasonable as, for example, if less vaccines are available for a country then they might stay in a stricter lockdown than in they did in reality. This makes the model’s value of R_t higher than it should be, meaning that for the No Vaccines counter-factual the deaths averted should be viewed as an upper estimate the true deaths averted.

These models are fitted to an excess death estimate, taken from here, and so are dependant on the quality of these estimates. Please also note that the model uncertainity does not account for uncertainting the excess mortality estimates.

Figure 1

Usage

The maps are presented as chloropleths with categorical colouring, a countries exact value can be viewed by hovering over it with your mouse.

Deaths Averted represents an increase in deaths/infections under the selected counter-factual. For example in the No Vaccines counter-factual the UK has a value of 507205 (total) deaths as can be seen in figure 1. This indicates that there would have been 507205 more deaths if there had been no vaccines in the UK. It is useful to think of 507205 as the number of deaths averted by the real-life vaccinations. Additional Deaths Averted presents a decrease in deaths/infections in the counterfactual, so under WHO counterfactual this the number of deaths that could have been avoided if the country had recieved that many vaccinations.

The map tabs for simulated and baseline deaths just show the total or adjusted death counts and by definition are positive numbers. These are both presented on the same colour scale to make comparisons easier.

The map tab for Vaccinated People (1 or 2 doses) show the number of vaccines assigned to that country in the selected counter-factual. For No Vaccines this is 0. Please note that per 1k vaccinations is the number of vaccinations total (in the baseline) whilst this map plots people vaccinated (in the counter factual).

Some small island nations, e.g. the Maldives, are represented by tiny polygons. The best way to view these is to mouse over them whilst zoomed out.

Coverage

This research models all countries with population above 90,000 and several territories and administrative regions. We have excluded mainland China from our results due to its unique position as the origin of the detected epidemic, lack of reported excess mortality, and large population size.