Carvalho, C.S. Temporal Analysis of Vaccine Adverse Effects for Causation Inference. Preprints2023, 2023121385. https://doi.org/10.20944/preprints202312.1385.v1
APA Style
Carvalho, C.S. (2023). Temporal Analysis of Vaccine Adverse Effects for Causation Inference. Preprints. https://doi.org/10.20944/preprints202312.1385.v1
Chicago/Turabian Style
Carvalho, C.S. 2023 "Temporal Analysis of Vaccine Adverse Effects for Causation Inference" Preprints. https://doi.org/10.20944/preprints202312.1385.v1
Abstract
We present a formalism to assess the safety of the COVID19 vaccines and infer a causal relation between vaccine administration and adverse effects, in particular death. We use data on adverse effects from VAERS covering the time interval [01-10-2020, 31-12-2021] (downloaded on 1 Feb 2022). We measure a vaccine fatality rate of order 0.01 for all vaccine manufacturers and identify a strong heterogeneity in the vaccine toxicity across vaccine lots, spanning up to four orders of magnitude. We compute the correlation between vaccination dates and death dates, and produce an estimate of the time lag that maximises the correlation, finding that the onset of adverse effects happened statistically (i.e. 32-41 percentiles) within one day after the vaccine administration and that death happened statistically (i.e. 22-50 percentiles) within about two weeks after the vaccine administration. These results provide data-based insights that can guide public health measures and health insurance policies.
Keywords
vaccine fatality rate; causation inference
Subject
Computer Science and Mathematics, Probability and Statistics
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
