How Reliable Are These Numbers?

1. Why Risk Numbers Disagree

Three factors drive disagreement between sources:

1. Numerator uncertainty: Death attribution varies by coding system (ICD-10 codes, verbal autopsy, hospital records)
2. Denominator uncertainty: How many people were exposed? A “deaths per year” figure means nothing without knowing the exposure population
3. Temporal and geographic aggregation: A global annual average hides enormous regional and seasonal variation

Our inclusion criteria: traceable numerator + defined denominator + reproducible calculation. We reject risks where we cannot identify both the death count and the population at risk.

2. The Confidence System

Every entry in atomic_risks() carries a confidence tier:

3. Geographic and Health Profile Conditioning

Geography is the biggest source of variation in risk data — the same snake bite ranges from 0.5 mm (US, with antivenom) to 18.5 mm (rural sub-Saharan Africa) �� a 37x difference. Health profile conditioning shows similar magnitude: a bee sting is 0.03 mm for the general population but 31 mm for someone with a known allergy (1,000x).

For the full analysis of how geography and demographics reshuffle risk rankings, including disease mortality by country (IHME GBD data) and age-conditioned confounders (bed falls, anaesthesia), see the Confounding Variables vignette.

The common_risks() function supports profile-based filtering:

# Default: returns high-income, all-ages estimates
common_risks()

# Geographic and health profile conditioning
common_risks(profile = list(country = "NG"))
common_risks(profile = list(health_profile = "allergic"))

4. Cross-Validation Methods

We use five methods to assess data reliability:

5. Worked Example: Animal Risks from OWID

Our World in Data reports annual deaths by animal. Converting to per-encounter micromorts requires:

$$\text{micromorts} = \frac{\text{deaths per year}}{\text{encounters per year}} \times 10^6$$

Mosquito, crocodile, and elephant fail our inclusion criteria: there is no defensible per-encounter denominator. Mosquito bites are ubiquitous in endemic regions, making a per-bite risk meaningless. We cite OWID for context but do not include these as micromort entries.

6. Estimate Ranges

For wildlife entries, we document plausible ranges reflecting source disagreement:

The range reflects uncertainty in both the numerator (death counts vary by year and reporting) and denominator (exposure estimates are often rough). The point estimate is our best central value; the range brackets the plausible minimum and maximum.

7. What You Can Contribute

If you find a better source for an existing entry, or want to propose a new risk: open an issue at github.com/johngavin/micromort with:

1. Numerator: Death count and source citation
2. Denominator: Exposure count and source citation
3. Geography/condition: Does the estimate apply globally, or to a specific population?
4. Time period: When was the data collected?

Entries start at validation_status = "single_source" and get upgraded as more sources confirm them.

Reproducibility

sessionInfo()
R version 4.5.2 (2025-10-31)
Platform: aarch64-apple-darwin24.6.0
Running under: macOS Tahoe 26.4.1

Matrix products: default
BLAS:   /nix/store/gf17x1bj3m732n39jznn6kz69szbr5rb-blas-3/lib/libblas.dylib 
LAPACK: /nix/store/5kg4z5bffhr8nry8bl8l5wlxvpy54dm2-openblas-0.3.30/lib/libopenblasp-r0.3.30.dylib;  LAPACK version 3.12.0

locale:
[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8

time zone: Europe/Belfast
tzcode source: internal

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
[1] dplyr_1.1.4     micromort_0.2.0 testthat_3.3.1 

loaded via a namespace (and not attached):
 [1] generics_0.1.4     digest_0.6.39      magrittr_2.0.4     evaluate_1.0.5    
 [5] grid_4.5.2         RColorBrewer_1.1-3 pkgload_1.4.1      fastmap_1.2.0     
 [9] rprojroot_2.1.1    jsonlite_2.0.0     processx_3.8.6     pkgbuild_1.4.8    
[13] backports_1.5.0    brio_1.1.5         secretbase_1.0.5   ps_1.9.1          
[17] purrr_1.2.0        scales_1.4.0       codetools_0.2-20   cli_3.6.5         
[21] rlang_1.1.6        units_1.0-0        bit64_4.6.0-1      withr_3.0.2       
[25] yaml_2.3.12        otel_0.2.0         tools_4.5.2        checkmate_2.3.3   
[29] base64url_1.4      ggplot2_4.0.1      credentials_2.0.3  assertthat_0.2.1  
[33] vctrs_0.6.5        R6_2.6.1           lifecycle_1.0.4    fs_1.6.6          
[37] bit_4.6.0          usethis_3.2.1      targets_1.11.4     arrow_22.0.0      
[41] callr_3.7.6        pkgconfig_2.0.3    desc_1.4.3         pillar_1.11.1     
[45] gtable_0.3.6       data.table_1.18.0  glue_1.8.0         Rcpp_1.1.0        
[49] gert_2.2.0         xfun_0.55          tibble_3.3.0       tidyselect_1.2.1  
[53] sys_3.4.3          knitr_1.51         farver_2.1.2       igraph_2.2.1      
[57] htmltools_0.5.9    rmarkdown_2.30     compiler_4.5.2     prettyunits_1.2.0 
[61] S7_0.2.1           askpass_1.2.1      openssl_2.3.4     

micromort 0.1.0 | Git 94d93d2 | R 4.5.2 | Built 2026-04-18 12:20:56