About
This app visualizes weekly counts of all-cause mortality (all ages) and
per capita weekly COVID-19 vaccine doses by country, and estimates the
association between vaccination and mortality using a distributed lag model (DLM).
An optional toggle allows the DLM outcome to be switched from all-cause deaths
to non-COVID deaths (all-cause deaths minus COVID-19 deaths), enabling exploration
of the hypothesis that any positive association between vaccination and all-cause
mortality is attributable to concurrent COVID-19 death waves rather than a
direct vaccine effect.
Data sources
-
Mortality:
Human Mortality Database (STMF)
— weekly all-cause death counts (all ages, both sexes combined) by country.
-
Vaccination:
Our World in Data — COVID-19 vaccinations
— 7-day average of daily doses administered per million people, multiplied by 7
to obtain an estimated weekly total.
-
COVID-19 deaths:
Our World in Data — COVID-19 deaths
— weekly confirmed COVID-19 deaths by country, used to derive the non-COVID
all-cause death series (all-cause deaths minus COVID-19 deaths).
Weeks with no reported COVID-19 deaths are treated as zero;
weeks outside the OWID coverage window are also set to zero.
Analysis
- Descriptive time-series plots display weekly all-cause deaths alongside
weekly vaccine doses, with optional overlays for COVID-19 deaths and
the derived non-COVID death series.
-
A quasiPoisson distributed lag non-linear model (DLNM; R package
dlnm
) is fitted to estimate the lagged association between
vaccination and mortality over up to four years, adjusting for long-term
trend (optional natural spline) and seasonality (up to four pairs of
sine/cosine harmonics). The DLNM approach is described in:
Gasparrini (2011), Journal of Statistical Software.
-
Testing the COVID-confounding hypothesis:
Because vaccination campaigns often overlapped with large COVID-19 death
waves, a spurious positive association between vaccine doses and all-cause
mortality is plausible at the ecological (country) level.
Toggling the DLM outcome to
non-COVID deaths
(all-cause minus COVID-19 deaths) allows direct examination of whether
any positive association persists once COVID-19 deaths are removed from the
outcome — if the association weakens substantially or reverses, this supports
the confounding-by-COVID-wave hypothesis.
Plots
- Time-series panel: weekly all-cause deaths (black) and vaccine doses
per million (blue). Optional overlays add COVID-19 deaths (dark green)
and non-COVID all-cause deaths (purple dashed). The red dashed horizontal
line marks the numerator dose level used in the association plots.
- Lagged-effect plot: week-by-week count ratios from the DLM, comparing
the selected numerator dose group to zero doses, with 95% confidence bands.
- Cumulative effect plot: the overall one-year-ahead mortality count ratio
(numerator vs zero doses), being the product of the 52 weekly lagged
count ratios shown above.
- Observed vs predicted panel: observed deaths (grey), model-fitted deaths
(red dashed), and the counterfactual trajectory without any vaccination
(blue dot-dash), with 95% prediction intervals. The outcome shown (all-cause
or non-COVID deaths) reflects whichever series was selected for modelling.
Disclaimer
This app is for educational purposes only and does not provide medical advice.
Results represent ecological associations at the country level and should not
be interpreted as individual-level causal effects. Confounding, data quality
variation across countries, and modelling assumptions all limit causal inference.
Please refer to the source links above for full details on data provenance
and methodology.