A spi_field_guide() result computed on synth_surveillance, with all
five STEPS components and the neighbour, seasonal and detection context
supplied. This lets spi_field_guide_help(), the
spi_field_guide_table() examples, and tests run without refitting the model.
It was produced by spi_adjacency() -> spi_index() (no covariates) at
district-year and district-month levels -> spi_compare_npafp() ->
spi_field_guide().
Format
An object of class spi_field_guide; see the Value section
of spi_field_guide() for its contents. The review year is 2024, the SPI
cutoff is 1, and the NPAFP target is 3 per 100,000 under-15 person-years.
Reproducibility
Regenerate with Rscript data-raw/synth_field_guide.R (needs INLA). The
generator uses set.seed(20260710) and the fit's seed = 42L.
Examples
print(synth_field_guide)
#>
#> ── SPI field guide ─────────────────────────────────────────────────────────────
#> Review year: 2024 | STEPS applied below SPI 1 (median rule) | priority for
#> review: 90% CrI below 1, with extent or persistence
#> Available components and additional findings: "timeliness", "extent",
#> "adequacy", "surroundings", "seasonal", "detect_afp", and "detect_es"
#>
#> ── Review labels for 2024 ──
#>
#> # A tibble: 3 × 3
#> verdict n pct
#> <chr> <int> <dbl>
#> 1 Priority for review 60 25.4
#> 2 Monitor 71 30.1
#> 3 No SPI indication 105 44.5
#> ── Districts with priority for review (top 10 by size of shortfall) ──
#>
#> # A tibble: 60 × 11
#> district obs exp spi cri npafp extent persist transport adequacy
#> <chr> <int> <dbl> <dbl> <chr> <dbl> <lgl> <lgl> <dbl> <dbl>
#> 1 Khandor 0 2.4 0 0.00-0.00 0 TRUE TRUE NA NA
#> 2 Arddor 0 1.7 0 0.00-0.00 0 TRUE TRUE NA NA
#> 3 Ardor 0 1.2 0 0.00-0.00 0 TRUE TRUE NA NA
#> 4 Doloth 0 1.1 0 0.00-0.00 0 TRUE TRUE NA NA
#> 5 Raenan 0 1 0 0.00-0.00 0 TRUE TRUE NA NA
#> 6 Chakis 0 1.9 0 0.00-0.00 0 TRUE TRUE NA NA
#> 7 Kiroth 0 1.5 0 0.00-0.00 0 TRUE FALSE NA NA
#> 8 Vashoth 0 2.3 0 0.00-0.00 0 TRUE TRUE NA NA
#> 9 Suzil 1 8.1 0.13 0.10-0.17 1.6 FALSE TRUE 100 100
#> 10 Nentha 2 14.5 0.14 0.11-0.18 2 TRUE FALSE 100 100
#> # ℹ 50 more rows
#> # ℹ 1 more variable: verdict <chr>
#> ℹ See `spi_field_guide_help()` for worked examples, `spi_field_guide_table()` to render it.
head(as_tibble(synth_field_guide))
#> # A tibble: 6 × 60
#> adm0_name adm1_name adm2_name adm2_guid year observed expected_total
#> <chr> <chr> <chr> <chr> <dbl> <int> <dbl>
#> 1 Harad Gartha Khandor {01325AA0-BEA1-66… 2015 1 1.55
#> 2 Harad Gartha Khandor {01325AA0-BEA1-66… 2016 2 1.87
#> 3 Harad Gartha Khandor {01325AA0-BEA1-66… 2017 0 1.90
#> 4 Harad Gartha Khandor {01325AA0-BEA1-66… 2018 2 2.11
#> 5 Harad Gartha Khandor {01325AA0-BEA1-66… 2019 5 2.49
#> 6 Harad Gartha Khandor {01325AA0-BEA1-66… 2020 2 1.39
#> # ℹ 53 more variables: spi_median <dbl>, spi_q05 <dbl>, spi_q95 <dbl>,
#> # count_annual <int>, pop_u15 <dbl>, npafp_rate <dbl>, npafp_adequate <lgl>,
#> # spi_below_threshold <lgl>, spi_pass <lgl>, category <fct>,
#> # conventional_pass <lgl>, spi_below <lgl>, noise_tail <dbl>,
#> # noise_plausible <lgl>, cri_excludes_1 <lgl>, gate_pass <lgl>,
#> # s1_discordance <lgl>, spi_previous <dbl>, persistence_concern <lgl>,
#> # national_pct <dbl>, extent_others <int>, extent_others_below <int>, …