EpiMundi

FMD outbreaks in Africa

Descriptive stats

$numeric_summary
        variable       min        max      mean  median
1       latitude 26.798000   37.27370 35.762338 36.1480
2      longitude -9.540806   13.48826  4.767517  4.7506
3      sumAtRisk  1.000000 2370.00000 89.957447 20.0000
4       sumCases  1.000000  663.00000 12.372340  4.0000
5      sumDeaths  0.000000  326.00000  4.623602  0.0000
6   sumDestroyed  0.000000  424.00000  3.132500  0.0000
7 sumSlaughtered  0.000000 1005.00000 11.787599  2.0000

$speciesDescription
# A tibble: 17 × 2
   speciesDescription                                                      Freq
   <chr>                                                                  <int>
 1 domestic, cattle                                                         510
 2 domestic, sheep                                                          126
 3 domestic, goat, domestic, sheep                                           96
 4 domestic, cattle, domestic, sheep                                         90
 5 domestic, cattle, domestic, goat, domestic, sheep                         40
 6 domestic, sheep, domestic, goat                                           19
 7 domestic, sheep, domestic, cattle                                         16
 8 domestic, cattle, domestic, sheep, domestic, goat                         11
 9 domestic, cattle, domestic, goat/sheep                                    10
10 domestic, goat                                                             9
11 domestic, cattle, domestic, goat                                           5
12 domestic, sheep, domestic, cattle, domestic, goat                          4
13 domestic, goat, domestic, cattle, domestic, sheep                          2
14 domestic, goat, domestic, sheep, domestic, cattle                          2
15 domestic, sheep, domestic, goat, domestic, cattle                          2
16 domestic, cattle, domestic, goat, domestic, sheep, domestic, camelidae     1
17 domestic, goat, domestic, cattle                                           1

$serotypes
# A tibble: 5 × 2
  serotypes      Freq
  <chr>         <int>
1 O               927
2 Not Specified     8
3 A                 7
4 A, O              1
5 <NA>              1

No humans affected as expected since FMD is non-zoonotic.

# A tibble: 3 × 5
  country events total_cases total_deaths avg_reporting_delay_days
  <fct>    <int>       <dbl>        <dbl>                    <dbl>
1 Algeria    727        9465         3209                    47.3 
2 Tunisia    159        1317           22                    17.8 
3 Morocco     40         113            3                     7.52

Spatial analysis

Figure 1 - Study areas

1. Map the outbreak intensity per country

2. Test different techniques for spatial distribution of disease outbreaks

`summarise()` has grouped output by 'country'. You can override using the
`.groups` argument.

Scale on map varies by more than 10%, scale bar may be inaccurate
Scale on map varies by more than 10%, scale bar may be inaccurate
Scale on map varies by more than 10%, scale bar may be inaccurate

3. Check lag between outbreak and reporting

Timeseries of date of outbreak and date of reporting lag (black for outbreak dates and red for reporting)

#END#