[Maturing] Used to produce summary output either internally in regional_epinow or externally.

regional_summary(
  regional_output = NULL,
  reported_cases,
  results_dir = NULL,
  summary_dir = NULL,
  target_date = NULL,
  region_scale = "Region",
  all_regions = TRUE,
  return_output = FALSE,
  max_plot = 10,
  ...
)

Arguments

regional_output

A list of output as produced by regional_epinow and stored in the regional list.

reported_cases

A data frame of confirmed cases (confirm) by date (date), and region (region).

results_dir

An optional character string indicating the location of the results directory to extract results from.

summary_dir

A character string giving the directory in which to store summary of results.

target_date

A character string giving the target date for which to extract results (in the format "yyyy-mm-dd"). Defaults to latest available estimates.

region_scale

A character string indicating the name to give the regions being summarised.

all_regions

Logical, defaults to TRUE. Should summary plots for all regions be returned rather than just regions of interest.

return_output

Logical, defaults to FALSE. Should output be returned, this automatically updates to TRUE if no directory for saving is specified.

max_plot

Numeric, defaults to 10. A multiplicative upper bound on the number of cases shown on the plot. Based on the maximum number of reported cases.

...

Additional arguments passed to report_plots.

Value

A list of summary measures and plots

See also

regional_epinow

Examples

# \donttest{
# example delays
generation_time <- get_generation_time(disease = "SARS-CoV-2", source = "ganyani")
incubation_period <- get_incubation_period(disease = "SARS-CoV-2", source = "lauer")
reporting_delay <- estimate_delay(rlnorm(100, log(6), 1), max_value = 30)

# example case vector from EpiSoon
cases <- example_confirmed[1:30]
cases <- data.table::rbindlist(list(
  data.table::copy(cases)[, region := "testland"],
  cases[, region := "realland"]
))

# run basic nowcasting pipeline
out <- regional_epinow(
  reported_cases = cases,
  generation_time = generation_time,
  delays = delay_opts(incubation_period, reporting_delay),
  output = "region",
  rt = NULL
)
#> INFO [2022-03-28 04:11:45] Producing following optional outputs: regions
#> Logging threshold set at INFO for the EpiNow2 logger
#> Writing EpiNow2 logs to the console and: /var/folders/24/8k48jl6d249_n_qfxwsl6xvm0000gn/T//RtmpqbXERq/regional-epinow/2020-03-22.log
#> Logging threshold set at INFO for the EpiNow2.epinow logger
#> Writing EpiNow2.epinow logs to: /var/folders/24/8k48jl6d249_n_qfxwsl6xvm0000gn/T//RtmpqbXERq/epinow/2020-03-22.log
#> INFO [2022-03-28 04:11:45] Reporting estimates using data up to: 2020-03-22
#> INFO [2022-03-28 04:11:45] No target directory specified so returning output
#> INFO [2022-03-28 04:11:45] Producing estimates for: testland, realland
#> INFO [2022-03-28 04:11:45] Regions excluded: none
#> INFO [2022-03-28 04:12:24] Completed estimates for: testland
#> INFO [2022-03-28 04:13:03] Completed estimates for: realland
#> INFO [2022-03-28 04:13:03] Completed regional estimates
#> INFO [2022-03-28 04:13:03] Regions with estimates: 2
#> INFO [2022-03-28 04:13:03] Regions with runtime errors: 0
#> INFO [2022-03-28 04:13:03] No target directory specified so returning timings

regional_summary(
  regional_output = out$regional,
  reported_cases = cases
)
#> INFO [2022-03-28 04:13:03] No summary directory specified so returning summary output
#> $latest_date
#> [1] "2020-03-22"
#> 
#> $results
#> $results$estimates
#> $results$estimates$summarised
#>        region       date                 variable strat     type       median
#>   1: testland 2020-02-22                        R  <NA> estimate    1.6322468
#>   2: testland 2020-02-23                        R  <NA> estimate    1.6359159
#>   3: testland 2020-02-24                        R  <NA> estimate    1.5754194
#>   4: testland 2020-02-25                        R  <NA> estimate    1.5465078
#>   5: testland 2020-02-26                        R  <NA> estimate    1.5483517
#>  ---                                                                         
#> 422: realland 2020-03-26           reported_cases  <NA> forecast  991.5000000
#> 423: realland 2020-03-27           reported_cases  <NA> forecast 1239.5000000
#> 424: realland 2020-03-28           reported_cases  <NA> forecast  985.0000000
#> 425: realland 2020-03-29           reported_cases  <NA> forecast 1118.5000000
#> 426: realland       <NA> reporting_overdispersion  <NA>     <NA>    0.9963241
#>             mean           sd   lower_90    lower_50    lower_20    upper_20
#>   1:    1.639706 1.119347e-01  1.4638326   1.5687936   1.6079753    1.658615
#>   2:    1.641193 1.058096e-01  1.4750018   1.5740327   1.6129870    1.660551
#>   3:    1.579606 9.872186e-02  1.4237893   1.5164624   1.5525069    1.597319
#>   4:    1.549736 9.252992e-02  1.4037361   1.4895356   1.5245174    1.566864
#>   5:    1.550685 8.904673e-02  1.4111612   1.4926670   1.5262397    1.567475
#>  ---                                                                        
#> 422: 1693.269000 2.136052e+03 54.0000000 393.7500000 716.8000000 1322.800000
#> 423: 1907.321000 2.091694e+03 70.0000000 492.0000000 894.6000000 1638.200000
#> 424: 1607.507000 1.889484e+03 72.0000000 426.7500000 743.0000000 1311.000000
#> 425: 1858.927500 2.144206e+03 71.9500000 477.0000000 859.6000000 1534.400000
#> 426:    1.065823 4.027978e-01  0.5345241   0.7764879   0.9159032    1.087634
#>         upper_50    upper_90
#>   1:    1.701449    1.832920
#>   2:    1.701318    1.816132
#>   3:    1.636689    1.748143
#>   4:    1.603731    1.702294
#>   5:    1.601691    1.697571
#>  ---                        
#> 422: 2189.750000 5534.150000
#> 423: 2608.250000 5927.200000
#> 424: 2083.250000 5196.400000
#> 425: 2506.250000 6005.000000
#> 426:    1.274299    1.845573
#> 
#> 
#> 
#> $summarised_results
#> $summarised_results$table
#>      Region New confirmed cases by infection date
#> 1: realland                    1019 (950 -- 1145)
#> 2: testland                    1020 (943 -- 1136)
#>    Expected change in daily cases Effective reproduction no.
#> 1:                     Decreasing        0.79 (0.74 -- 0.84)
#> 2:                     Decreasing        0.79 (0.75 -- 0.84)
#>               Rate of growth Doubling/halving time (days)
#> 1: -0.057 (-0.074 -- -0.049)            -12 (-14 -- -9.3)
#> 2: -0.057 (-0.074 -- -0.049)            -12 (-14 -- -9.4)
#> 
#> $summarised_results$data
#>      region            estimate  median    mean     sd lower_90 lower_50
#> 1: testland  1020 (943 -- 1136) 1020.00 1029.00 59.000   943.00  1003.00
#> 2: realland  1019 (950 -- 1145) 1019.00 1030.00 64.000   950.00  1004.00
#> 3: realland 0.79 (0.74 -- 0.84)    0.79    0.79  0.030     0.74     0.78
#> 4: testland 0.79 (0.75 -- 0.84)    0.79    0.79  0.029     0.75     0.77
#>    lower_20 upper_20 upper_50 upper_90                                metric
#> 1:  1015.00   1027.0  1048.00  1136.00 New confirmed cases by infection date
#> 2:  1016.00   1026.0  1046.00  1145.00 New confirmed cases by infection date
#> 3:     0.79      0.8     0.81     0.84            Effective reproduction no.
#> 4:     0.79      0.8     0.81     0.84            Effective reproduction no.
#>    Expected change in daily cases prob_control
#> 1:                     Decreasing            1
#> 2:                     Decreasing            1
#> 3:                     Decreasing            1
#> 4:                     Decreasing            1
#> 
#> $summarised_results$regions_by_inc
#> [1] "testland" "realland"
#> 
#> 
#> $summary_plot

#> 
#> $summarised_measures
#> $summarised_measures$rt
#>       region       date strat                           type    median
#>  1: realland 2020-02-22  <NA>                       estimate 1.6287134
#>  2: realland 2020-02-23  <NA>                       estimate 1.6329677
#>  3: realland 2020-02-24  <NA>                       estimate 1.5726155
#>  4: realland 2020-02-25  <NA>                       estimate 1.5442543
#>  5: realland 2020-02-26  <NA>                       estimate 1.5462150
#>  6: realland 2020-02-27  <NA>                       estimate 1.5490782
#>  7: realland 2020-02-28  <NA>                       estimate 1.5319744
#>  8: realland 2020-02-29  <NA>                       estimate 1.3096630
#>  9: realland 2020-03-01  <NA>                       estimate 1.1617002
#> 10: realland 2020-03-02  <NA>                       estimate 1.0840952
#> 11: realland 2020-03-03  <NA>                       estimate 1.0000881
#> 12: realland 2020-03-04  <NA>                       estimate 0.9316281
#> 13: realland 2020-03-05  <NA>                       estimate 0.8828817
#> 14: realland 2020-03-06  <NA>                       estimate 0.8202715
#> 15: realland 2020-03-07  <NA> estimate based on partial data 0.8926061
#> 16: realland 2020-03-08  <NA> estimate based on partial data 0.8674781
#> 17: realland 2020-03-09  <NA> estimate based on partial data 0.8484259
#> 18: realland 2020-03-10  <NA> estimate based on partial data 0.8335932
#> 19: realland 2020-03-11  <NA> estimate based on partial data 0.8220869
#> 20: realland 2020-03-12  <NA> estimate based on partial data 0.8136868
#> 21: realland 2020-03-13  <NA> estimate based on partial data 0.8077592
#> 22: realland 2020-03-14  <NA> estimate based on partial data 0.8034974
#> 23: realland 2020-03-15  <NA> estimate based on partial data 0.8003446
#> 24: realland 2020-03-16  <NA> estimate based on partial data 0.7980612
#> 25: realland 2020-03-17  <NA> estimate based on partial data 0.7968367
#> 26: realland 2020-03-18  <NA> estimate based on partial data 0.7952001
#> 27: realland 2020-03-19  <NA> estimate based on partial data 0.7949698
#> 28: realland 2020-03-20  <NA> estimate based on partial data 0.7936882
#> 29: realland 2020-03-21  <NA> estimate based on partial data 0.7937895
#> 30: realland 2020-03-22  <NA> estimate based on partial data 0.7933397
#> 31: realland 2020-03-23  <NA>                       forecast 0.7926788
#> 32: realland 2020-03-24  <NA>                       forecast 0.7923490
#> 33: realland 2020-03-25  <NA>                       forecast 0.7928867
#> 34: realland 2020-03-26  <NA>                       forecast 0.7921127
#> 35: realland 2020-03-27  <NA>                       forecast 0.7918682
#> 36: realland 2020-03-28  <NA>                       forecast 0.7919460
#> 37: realland 2020-03-29  <NA>                       forecast 0.7921023
#> 38: testland 2020-02-22  <NA>                       estimate 1.6322468
#> 39: testland 2020-02-23  <NA>                       estimate 1.6359159
#> 40: testland 2020-02-24  <NA>                       estimate 1.5754194
#> 41: testland 2020-02-25  <NA>                       estimate 1.5465078
#> 42: testland 2020-02-26  <NA>                       estimate 1.5483517
#> 43: testland 2020-02-27  <NA>                       estimate 1.5506804
#> 44: testland 2020-02-28  <NA>                       estimate 1.5330400
#> 45: testland 2020-02-29  <NA>                       estimate 1.3095249
#> 46: testland 2020-03-01  <NA>                       estimate 1.1619420
#> 47: testland 2020-03-02  <NA>                       estimate 1.0838066
#> 48: testland 2020-03-03  <NA>                       estimate 0.9991528
#> 49: testland 2020-03-04  <NA>                       estimate 0.9307315
#> 50: testland 2020-03-05  <NA>                       estimate 0.8817289
#> 51: testland 2020-03-06  <NA>                       estimate 0.8193897
#> 52: testland 2020-03-07  <NA> estimate based on partial data 0.8916053
#> 53: testland 2020-03-08  <NA> estimate based on partial data 0.8671506
#> 54: testland 2020-03-09  <NA> estimate based on partial data 0.8476947
#> 55: testland 2020-03-10  <NA> estimate based on partial data 0.8326889
#> 56: testland 2020-03-11  <NA> estimate based on partial data 0.8209244
#> 57: testland 2020-03-12  <NA> estimate based on partial data 0.8123660
#> 58: testland 2020-03-13  <NA> estimate based on partial data 0.8062731
#> 59: testland 2020-03-14  <NA> estimate based on partial data 0.8024139
#> 60: testland 2020-03-15  <NA> estimate based on partial data 0.7992736
#> 61: testland 2020-03-16  <NA> estimate based on partial data 0.7969624
#> 62: testland 2020-03-17  <NA> estimate based on partial data 0.7955352
#> 63: testland 2020-03-18  <NA> estimate based on partial data 0.7939984
#> 64: testland 2020-03-19  <NA> estimate based on partial data 0.7935635
#> 65: testland 2020-03-20  <NA> estimate based on partial data 0.7928701
#> 66: testland 2020-03-21  <NA> estimate based on partial data 0.7926409
#> 67: testland 2020-03-22  <NA> estimate based on partial data 0.7918547
#> 68: testland 2020-03-23  <NA>                       forecast 0.7913393
#> 69: testland 2020-03-24  <NA>                       forecast 0.7913447
#> 70: testland 2020-03-25  <NA>                       forecast 0.7922151
#> 71: testland 2020-03-26  <NA>                       forecast 0.7919235
#> 72: testland 2020-03-27  <NA>                       forecast 0.7916873
#> 73: testland 2020-03-28  <NA>                       forecast 0.7914714
#> 74: testland 2020-03-29  <NA>                       forecast 0.7921955
#>       region       date strat                           type    median
#>          mean         sd  lower_90  lower_50  lower_20  upper_20  upper_50
#>  1: 1.6380433 0.10731668 1.4747270 1.5690102 1.6060754 1.6545537 1.6985437
#>  2: 1.6399855 0.10164597 1.4822246 1.5754015 1.6117729 1.6574189 1.6976464
#>  3: 1.5788365 0.09501183 1.4319868 1.5174511 1.5523487 1.5957501 1.6336407
#>  4: 1.5493642 0.08924175 1.4101669 1.4912402 1.5248900 1.5656104 1.6016651
#>  5: 1.5506112 0.08600446 1.4174875 1.4942648 1.5268486 1.5667853 1.6009277
#>  6: 1.5539990 0.08459462 1.4231414 1.4983986 1.5300107 1.5697540 1.6028739
#>  7: 1.5367946 0.08325389 1.4088383 1.4824572 1.5122852 1.5505560 1.5858630
#>  8: 1.3131424 0.07044417 1.2044543 1.2676226 1.2923460 1.3242525 1.3551243
#>  9: 1.1633193 0.05538936 1.0760323 1.1281461 1.1481005 1.1745451 1.1968170
#> 10: 1.0860498 0.04581124 1.0124926 1.0562886 1.0743901 1.0951809 1.1144038
#> 11: 1.0018282 0.03796571 0.9422676 0.9783000 0.9918687 1.0084245 1.0243354
#> 12: 0.9337750 0.03228445 0.8865086 0.9129127 0.9250665 0.9380600 0.9511637
#> 13: 0.8846208 0.02889339 0.8424136 0.8673499 0.8769805 0.8883090 0.8985084
#> 14: 0.8213549 0.02623011 0.7823059 0.8066602 0.8153856 0.8248063 0.8329084
#> 15: 0.8927027 0.02984613 0.8473128 0.8759652 0.8866563 0.8973947 0.9066197
#> 16: 0.8693160 0.02698277 0.8307711 0.8548605 0.8628132 0.8722305 0.8814585
#> 17: 0.8503074 0.02622664 0.8136082 0.8356749 0.8436254 0.8530068 0.8630403
#> 18: 0.8350566 0.02617563 0.7977208 0.8202844 0.8285794 0.8386926 0.8492111
#> 19: 0.8233153 0.02660293 0.7835137 0.8077821 0.8166715 0.8276146 0.8376099
#> 20: 0.8143565 0.02725455 0.7725083 0.7981205 0.8078239 0.8194293 0.8295292
#> 21: 0.8082838 0.02791664 0.7634349 0.7914057 0.8020167 0.8136675 0.8247266
#> 22: 0.8037754 0.02840786 0.7569770 0.7865342 0.7972164 0.8095381 0.8212349
#> 23: 0.8006288 0.02867375 0.7547094 0.7830847 0.7939589 0.8070443 0.8185852
#> 24: 0.7982170 0.02890950 0.7507699 0.7806108 0.7916763 0.8048241 0.8158267
#> 25: 0.7965334 0.02913916 0.7480646 0.7789205 0.7896690 0.8032044 0.8143052
#> 26: 0.7950809 0.02932829 0.7474087 0.7775736 0.7884007 0.8021790 0.8130276
#> 27: 0.7944665 0.02957755 0.7472920 0.7768067 0.7876880 0.8016536 0.8130034
#> 28: 0.7933554 0.02983785 0.7452073 0.7757691 0.7867039 0.7999711 0.8119550
#> 29: 0.7933466 0.03015885 0.7437312 0.7758412 0.7868185 0.8002418 0.8122478
#> 30: 0.7928749 0.03047096 0.7431321 0.7752042 0.7862780 0.7997065 0.8120304
#> 31: 0.7926228 0.03051766 0.7430431 0.7742399 0.7860250 0.7993957 0.8114806
#> 32: 0.7922913 0.03045273 0.7416240 0.7738875 0.7857614 0.7986386 0.8109084
#> 33: 0.7929569 0.03031271 0.7430241 0.7743443 0.7863482 0.7991991 0.8115878
#> 34: 0.7927958 0.03002340 0.7430351 0.7743703 0.7860963 0.7986934 0.8113241
#> 35: 0.7930069 0.02969333 0.7439575 0.7747871 0.7859091 0.7990674 0.8116110
#> 36: 0.7926435 0.02934115 0.7436005 0.7749144 0.7853810 0.7986861 0.8111253
#> 37: 0.7930429 0.02907999 0.7448974 0.7754533 0.7856249 0.7989824 0.8111845
#> 38: 1.6397059 0.11193470 1.4638326 1.5687936 1.6079753 1.6586147 1.7014489
#> 39: 1.6411930 0.10580957 1.4750018 1.5740327 1.6129870 1.6605515 1.7013177
#> 40: 1.5796062 0.09872186 1.4237893 1.5164624 1.5525069 1.5973185 1.6366893
#> 41: 1.5497355 0.09252992 1.4037361 1.4895356 1.5245174 1.5668638 1.6037309
#> 42: 1.5506850 0.08904673 1.4111612 1.4926670 1.5262397 1.5674753 1.6016914
#> 43: 1.5538682 0.08765745 1.4188061 1.4966364 1.5290965 1.5704817 1.6034459
#> 44: 1.5366277 0.08655287 1.4051525 1.4803388 1.5115405 1.5528599 1.5842656
#> 45: 1.3129845 0.07347246 1.2020639 1.2651160 1.2912188 1.3256130 1.3539020
#> 46: 1.1627800 0.05731698 1.0733690 1.1258980 1.1481453 1.1736574 1.1971788
#> 47: 1.0849697 0.04692940 1.0078244 1.0558865 1.0739938 1.0948116 1.1134247
#> 48: 1.0004482 0.03896088 0.9393237 0.9765626 0.9914137 1.0081618 1.0223868
#> 49: 0.9323659 0.03310620 0.8835933 0.9117044 0.9245309 0.9380540 0.9499826
#> 50: 0.8832667 0.02947470 0.8422345 0.8659908 0.8763586 0.8876984 0.8977096
#> 51: 0.8201283 0.02647054 0.7824273 0.8056458 0.8143778 0.8243887 0.8321533
#> 52: 0.8914345 0.02968794 0.8465603 0.8748196 0.8855525 0.8968234 0.9058582
#> 53: 0.8682951 0.02593505 0.8310481 0.8540416 0.8622806 0.8713141 0.8802976
#> 54: 0.8496038 0.02452649 0.8146404 0.8352283 0.8431781 0.8519562 0.8622458
#> 55: 0.8345961 0.02419267 0.7989296 0.8197314 0.8276059 0.8376411 0.8475147
#> 56: 0.8229510 0.02456227 0.7863434 0.8074571 0.8156003 0.8265377 0.8366944
#> 57: 0.8141027 0.02536570 0.7766721 0.7973141 0.8064430 0.8184525 0.8288848
#> 58: 0.8081356 0.02629484 0.7683104 0.7908025 0.8005480 0.8133098 0.8235302
#> 59: 0.8037240 0.02710016 0.7624542 0.7857932 0.7962987 0.8090089 0.8200751
#> 60: 0.8006524 0.02766806 0.7580015 0.7825553 0.7930091 0.8061062 0.8175969
#> 61: 0.7982811 0.02812393 0.7547150 0.7799831 0.7908281 0.8038772 0.8156585
#> 62: 0.7966033 0.02845783 0.7530994 0.7781263 0.7894867 0.8023732 0.8137170
#> 63: 0.7951288 0.02863473 0.7523248 0.7767438 0.7881132 0.8007709 0.8127893
#> 64: 0.7944719 0.02877555 0.7515725 0.7763958 0.7873612 0.8005544 0.8123946
#> 65: 0.7933076 0.02887779 0.7493775 0.7754628 0.7859908 0.7993823 0.8114733
#> 66: 0.7932453 0.02905416 0.7487090 0.7752386 0.7859159 0.7990142 0.8117816
#> 67: 0.7927293 0.02929146 0.7479722 0.7746065 0.7852546 0.7985854 0.8113017
#> 68: 0.7924530 0.02938803 0.7479095 0.7743261 0.7850775 0.7985621 0.8103664
#> 69: 0.7921196 0.02951435 0.7470859 0.7737067 0.7846508 0.7980650 0.8105738
#> 70: 0.7928055 0.02970294 0.7478623 0.7747289 0.7850501 0.7988416 0.8110303
#> 71: 0.7926868 0.02984685 0.7486045 0.7743384 0.7849988 0.7987736 0.8106812
#> 72: 0.7929573 0.03000271 0.7482573 0.7746620 0.7852625 0.7992195 0.8112733
#> 73: 0.7926621 0.03012012 0.7484052 0.7741659 0.7846449 0.7987758 0.8115867
#> 74: 0.7931293 0.03024958 0.7480739 0.7741972 0.7851838 0.7992595 0.8122724
#>          mean         sd  lower_90  lower_50  lower_20  upper_20  upper_50
#>      upper_90
#>  1: 1.8212265
#>  2: 1.8135475
#>  3: 1.7390201
#>  4: 1.6980564
#>  5: 1.6927822
#>  6: 1.6942818
#>  7: 1.6741462
#>  8: 1.4295287
#>  9: 1.2548865
#> 10: 1.1620916
#> 11: 1.0675546
#> 12: 0.9890602
#> 13: 0.9355675
#> 14: 0.8664468
#> 15: 0.9435970
#> 16: 0.9151955
#> 17: 0.8930346
#> 18: 0.8769624
#> 19: 0.8658018
#> 20: 0.8571191
#> 21: 0.8521743
#> 22: 0.8497203
#> 23: 0.8475227
#> 24: 0.8449439
#> 25: 0.8431614
#> 26: 0.8414513
#> 27: 0.8407910
#> 28: 0.8397064
#> 29: 0.8414035
#> 30: 0.8415769
#> 31: 0.8409005
#> 32: 0.8403171
#> 33: 0.8408514
#> 34: 0.8406670
#> 35: 0.8406123
#> 36: 0.8400169
#> 37: 0.8397399
#> 38: 1.8329196
#> 39: 1.8161321
#> 40: 1.7481430
#> 41: 1.7022939
#> 42: 1.6975710
#> 43: 1.6997360
#> 44: 1.6842825
#> 45: 1.4397871
#> 46: 1.2543140
#> 47: 1.1581395
#> 48: 1.0624003
#> 49: 0.9849970
#> 50: 0.9311381
#> 51: 0.8621833
#> 52: 0.9379101
#> 53: 0.9106242
#> 54: 0.8904856
#> 55: 0.8763264
#> 56: 0.8664992
#> 57: 0.8576175
#> 58: 0.8533785
#> 59: 0.8505473
#> 60: 0.8493344
#> 61: 0.8462909
#> 62: 0.8443542
#> 63: 0.8423259
#> 64: 0.8425316
#> 65: 0.8411789
#> 66: 0.8413629
#> 67: 0.8410591
#> 68: 0.8408014
#> 69: 0.8409095
#> 70: 0.8414818
#> 71: 0.8416032
#> 72: 0.8426234
#> 73: 0.8438992
#> 74: 0.8437577
#>      upper_90
#> 
#> $summarised_measures$growth_rate
#>       region       date strat                           type        median
#>  1: realland 2020-02-22  <NA>                       estimate  1.575462e-01
#>  2: realland 2020-02-23  <NA>                       estimate  1.588251e-01
#>  3: realland 2020-02-24  <NA>                       estimate  1.446278e-01
#>  4: realland 2020-02-25  <NA>                       estimate  1.381169e-01
#>  5: realland 2020-02-26  <NA>                       estimate  1.383001e-01
#>  6: realland 2020-02-27  <NA>                       estimate  1.391017e-01
#>  7: realland 2020-02-28  <NA>                       estimate  1.349743e-01
#>  8: realland 2020-02-29  <NA>                       estimate  8.064985e-02
#>  9: realland 2020-03-01  <NA>                       estimate  4.343481e-02
#> 10: realland 2020-03-02  <NA>                       estimate  2.314296e-02
#> 11: realland 2020-03-03  <NA>                       estimate  2.001439e-05
#> 12: realland 2020-03-04  <NA>                       estimate -1.925108e-02
#> 13: realland 2020-03-05  <NA>                       estimate -3.323086e-02
#> 14: realland 2020-03-06  <NA>                       estimate -5.136976e-02
#> 15: realland 2020-03-07  <NA> estimate based on partial data -3.132148e-02
#> 16: realland 2020-03-08  <NA> estimate based on partial data -3.760878e-02
#> 17: realland 2020-03-09  <NA> estimate based on partial data -4.237653e-02
#> 18: realland 2020-03-10  <NA> estimate based on partial data -4.644200e-02
#> 19: realland 2020-03-11  <NA> estimate based on partial data -4.967111e-02
#> 20: realland 2020-03-12  <NA> estimate based on partial data -5.201373e-02
#> 21: realland 2020-03-13  <NA> estimate based on partial data -5.370508e-02
#> 22: realland 2020-03-14  <NA> estimate based on partial data -5.485896e-02
#> 23: realland 2020-03-15  <NA> estimate based on partial data -5.565055e-02
#> 24: realland 2020-03-16  <NA> estimate based on partial data -5.630208e-02
#> 25: realland 2020-03-17  <NA> estimate based on partial data -5.662788e-02
#> 26: realland 2020-03-18  <NA> estimate based on partial data -5.704186e-02
#> 27: realland 2020-03-19  <NA> estimate based on partial data -5.713477e-02
#> 28: realland 2020-03-20  <NA> estimate based on partial data -5.737854e-02
#> 29: realland 2020-03-21  <NA> estimate based on partial data -5.738123e-02
#> 30: realland 2020-03-22  <NA> estimate based on partial data -5.749809e-02
#> 31: realland 2020-03-23  <NA>                       forecast -5.758261e-02
#> 32: realland 2020-03-24  <NA>                       forecast -5.769667e-02
#> 33: realland 2020-03-25  <NA>                       forecast -5.751280e-02
#> 34: realland 2020-03-26  <NA>                       forecast -5.762181e-02
#> 35: realland 2020-03-27  <NA>                       forecast -5.759345e-02
#> 36: realland 2020-03-28  <NA>                       forecast -5.780140e-02
#> 37: realland 2020-03-29  <NA>                       forecast -5.760798e-02
#> 38: testland 2020-02-22  <NA>                       estimate  1.563979e-01
#> 39: testland 2020-02-23  <NA>                       estimate  1.575085e-01
#> 40: testland 2020-02-24  <NA>                       estimate  1.430748e-01
#> 41: testland 2020-02-25  <NA>                       estimate  1.363474e-01
#> 42: testland 2020-02-26  <NA>                       estimate  1.367364e-01
#> 43: testland 2020-02-27  <NA>                       estimate  1.375877e-01
#> 44: testland 2020-02-28  <NA>                       estimate  1.333328e-01
#> 45: testland 2020-02-29  <NA>                       estimate  8.016316e-02
#> 46: testland 2020-03-01  <NA>                       estimate  4.341660e-02
#> 47: testland 2020-03-02  <NA>                       estimate  2.299287e-02
#> 48: testland 2020-03-03  <NA>                       estimate -2.095528e-04
#> 49: testland 2020-03-04  <NA>                       estimate -1.949756e-02
#> 50: testland 2020-03-05  <NA>                       estimate -3.355912e-02
#> 51: testland 2020-03-06  <NA>                       estimate -5.165495e-02
#> 52: testland 2020-03-07  <NA> estimate based on partial data -3.148245e-02
#> 53: testland 2020-03-08  <NA> estimate based on partial data -3.769117e-02
#> 54: testland 2020-03-09  <NA> estimate based on partial data -4.242752e-02
#> 55: testland 2020-03-10  <NA> estimate based on partial data -4.649727e-02
#> 56: testland 2020-03-11  <NA> estimate based on partial data -4.956944e-02
#> 57: testland 2020-03-12  <NA> estimate based on partial data -5.192920e-02
#> 58: testland 2020-03-13  <NA> estimate based on partial data -5.348856e-02
#> 59: testland 2020-03-14  <NA> estimate based on partial data -5.456972e-02
#> 60: testland 2020-03-15  <NA> estimate based on partial data -5.537124e-02
#> 61: testland 2020-03-16  <NA> estimate based on partial data -5.606901e-02
#> 62: testland 2020-03-17  <NA> estimate based on partial data -5.640661e-02
#> 63: testland 2020-03-18  <NA> estimate based on partial data -5.678623e-02
#> 64: testland 2020-03-19  <NA> estimate based on partial data -5.682055e-02
#> 65: testland 2020-03-20  <NA> estimate based on partial data -5.718895e-02
#> 66: testland 2020-03-21  <NA> estimate based on partial data -5.709995e-02
#> 67: testland 2020-03-22  <NA> estimate based on partial data -5.723812e-02
#> 68: testland 2020-03-23  <NA>                       forecast -5.744422e-02
#> 69: testland 2020-03-24  <NA>                       forecast -5.752912e-02
#> 70: testland 2020-03-25  <NA>                       forecast -5.739810e-02
#> 71: testland 2020-03-26  <NA>                       forecast -5.740797e-02
#> 72: testland 2020-03-27  <NA>                       forecast -5.732514e-02
#> 73: testland 2020-03-28  <NA>                       forecast -5.742998e-02
#> 74: testland 2020-03-29  <NA>                       forecast -5.739097e-02
#>       region       date strat                           type        median
#>              mean          sd     lower_90     lower_50     lower_20
#>  1:  0.1815941092 0.221521149  0.130848310  0.142020409  0.149876628
#>  2:  0.1835819424 0.241156013  0.129254671  0.141418406  0.150206318
#>  3:  0.1646265288 0.174357693  0.118334389  0.129549560  0.137021132
#>  4:  0.1562627687 0.156165277  0.112258922  0.123174444  0.130731612
#>  5:  0.1571776950 0.165489060  0.111771459  0.123162025  0.131103457
#>  6:  0.1583454696 0.173663391  0.112855149  0.123934225  0.131803032
#>  7:  0.1529951540 0.160564588  0.110197003  0.120316485  0.127984441
#>  8:  0.0866982540 0.040453311  0.063635474  0.073963725  0.077764943
#>  9:  0.0449318167 0.018668994  0.023844151  0.036769001  0.040803224
#> 10:  0.0237462338 0.014255120  0.003641038  0.016339768  0.020573899
#> 11:  0.0000182915 0.011249628 -0.017834477 -0.006444107 -0.002201962
#> 12: -0.0192760701 0.010323323 -0.035933431 -0.025543679 -0.021467518
#> 13: -0.0332549539 0.009835409 -0.048377784 -0.039455439 -0.035433484
#> 14: -0.0515511057 0.010231534 -0.067817197 -0.057741205 -0.053606187
#> 15: -0.0302613545 0.007478512 -0.040246097 -0.034501403 -0.032602218
#> 16: -0.0371122360 0.007545292 -0.048436351 -0.040596004 -0.038638590
#> 17: -0.0426250440 0.007848504 -0.055378300 -0.046227082 -0.043736093
#> 18: -0.0470190225 0.007989403 -0.060627786 -0.050809600 -0.047962146
#> 19: -0.0503798137 0.008036011 -0.064215821 -0.054298076 -0.051143313
#> 20: -0.0529331700 0.008072241 -0.067228710 -0.056932795 -0.053583229
#> 21: -0.0546535520 0.008093715 -0.069305234 -0.058545623 -0.055280827
#> 22: -0.0559322761 0.008112906 -0.070945610 -0.059936498 -0.056609145
#> 23: -0.0568281027 0.008108680 -0.071663024 -0.060832384 -0.057517428
#> 24: -0.0575137291 0.008113937 -0.072624059 -0.061567075 -0.058148528
#> 25: -0.0579901282 0.008130125 -0.073215425 -0.062100686 -0.058615692
#> 26: -0.0584050150 0.008162361 -0.073400213 -0.062588218 -0.058882441
#> 27: -0.0585757505 0.008204692 -0.073559745 -0.062957705 -0.059012310
#> 28: -0.0588951500 0.008281319 -0.074262514 -0.063325776 -0.059352455
#> 29: -0.0588903374 0.008347621 -0.074514021 -0.063396491 -0.059232166
#> 30: -0.0590212103 0.008433360 -0.074439545 -0.063495337 -0.059413226
#> 31: -0.0590971178 0.008464202 -0.074755375 -0.063581765 -0.059617683
#> 32: -0.0591962624 0.008459218 -0.074683473 -0.063517759 -0.059947004
#> 33: -0.0590012153 0.008402770 -0.074670605 -0.063210232 -0.059644048
#> 34: -0.0590512849 0.008336777 -0.074326135 -0.063278713 -0.059833202
#> 35: -0.0589915184 0.008242239 -0.074579710 -0.062998068 -0.059650011
#> 36: -0.0591014756 0.008156423 -0.074548981 -0.063068571 -0.059669268
#> 37: -0.0589859573 0.008067291 -0.074305643 -0.062854173 -0.059555471
#> 38:  0.1823859050 0.130673407  0.131087704  0.141265978  0.149524049
#> 39:  0.1841454928 0.137474696  0.129331427  0.140837351  0.149965593
#> 40:  0.1651444321 0.106606351  0.118196670  0.129083034  0.136761632
#> 41:  0.1565933170 0.095816241  0.111770566  0.123030089  0.130092754
#> 42:  0.1572719752 0.096832871  0.111870829  0.122885334  0.130098885
#> 43:  0.1582103395 0.096853636  0.112579829  0.123410900  0.130725140
#> 44:  0.1527548403 0.088451006  0.110097022  0.120014466  0.126896133
#> 45:  0.0866030154 0.030585218  0.062232523  0.073184889  0.077426417
#> 46:  0.0447035804 0.016811013  0.023004849  0.036170905  0.040773508
#> 47:  0.0234060340 0.013770920  0.002559406  0.015823862  0.020524387
#> 48: -0.0003748580 0.011487466 -0.019436896 -0.006900047 -0.002461986
#> 49: -0.0196444633 0.010595564 -0.037255700 -0.026029152 -0.021879100
#> 50: -0.0335747910 0.009992944 -0.049262107 -0.039838100 -0.035882399
#> 51: -0.0517877271 0.010219636 -0.067812045 -0.058243352 -0.054154398
#> 52: -0.0305412243 0.007460018 -0.039791196 -0.034587258 -0.032714464
#> 53: -0.0373058144 0.007213024 -0.047363863 -0.041020220 -0.038621651
#> 54: -0.0427176328 0.007378830 -0.053890350 -0.046496553 -0.043705363
#> 55: -0.0470344601 0.007479408 -0.059049780 -0.050946448 -0.047966010
#> 56: -0.0503597809 0.007503816 -0.063171666 -0.054258568 -0.051169265
#> 57: -0.0528750322 0.007574691 -0.066090123 -0.056761772 -0.053477108
#> 58: -0.0545615072 0.007673324 -0.067673578 -0.058496695 -0.055068207
#> 59: -0.0558107853 0.007794211 -0.069317278 -0.059771415 -0.056213048
#> 60: -0.0566847614 0.007889271 -0.070325684 -0.060542669 -0.056910918
#> 61: -0.0573579268 0.007964122 -0.071728224 -0.061166091 -0.057574893
#> 62: -0.0578307963 0.008006215 -0.072079502 -0.061694359 -0.058076234
#> 63: -0.0582485237 0.008019340 -0.072920184 -0.062212777 -0.058625482
#> 64: -0.0584267917 0.008005156 -0.073025695 -0.062442816 -0.058699399
#> 65: -0.0587543353 0.008003017 -0.073552948 -0.062786335 -0.059085423
#> 66: -0.0587573284 0.007988773 -0.073225081 -0.062701648 -0.059092602
#> 67: -0.0588916208 0.008010594 -0.073646683 -0.062965388 -0.059197067
#> 68: -0.0589654281 0.008007278 -0.073728675 -0.063022489 -0.059294023
#> 69: -0.0590558808 0.008006966 -0.073476136 -0.063176699 -0.059403023
#> 70: -0.0588471206 0.007996884 -0.073467234 -0.062868914 -0.059338556
#> 71: -0.0588766345 0.008009832 -0.073496175 -0.063089304 -0.059392638
#> 72: -0.0587925271 0.008015377 -0.073428768 -0.062925781 -0.059313284
#> 73: -0.0588756627 0.008029071 -0.073374236 -0.062976800 -0.059462222
#> 74: -0.0587350412 0.008023904 -0.073129821 -0.062790899 -0.059362671
#>              mean          sd     lower_90     lower_50     lower_20
#>         upper_20     upper_50     upper_90
#>  1:  0.166819361  0.188205236  0.285114215
#>  2:  0.168230544  0.191355588  0.292074092
#>  3:  0.152708753  0.172412822  0.258470821
#>  4:  0.145545094  0.164058860  0.243038799
#>  5:  0.146240243  0.165368485  0.245478888
#>  6:  0.147508235  0.166120250  0.246819201
#>  7:  0.142698906  0.160640937  0.235689848
#>  8:  0.083654544  0.091704200  0.125221152
#>  9:  0.046169933  0.050957188  0.069071426
#> 10:  0.025687991  0.030364694  0.044948886
#> 11:  0.002335683  0.006385167  0.016999844
#> 12: -0.017035365 -0.013106767 -0.002931006
#> 13: -0.031385654 -0.027468206 -0.016950706
#> 14: -0.049303151 -0.045279827 -0.035328771
#> 15: -0.029947681 -0.026954575 -0.017127193
#> 16: -0.036430655 -0.033816638 -0.024901185
#> 17: -0.041293797 -0.039081742 -0.030455374
#> 18: -0.045174108 -0.043183992 -0.035198989
#> 19: -0.048200979 -0.046229781 -0.038673613
#> 20: -0.050490580 -0.048530768 -0.041812328
#> 21: -0.052048351 -0.050113613 -0.043388603
#> 22: -0.053218533 -0.051143658 -0.044895074
#> 23: -0.053928111 -0.051855266 -0.045893797
#> 24: -0.054538039 -0.052431178 -0.046682028
#> 25: -0.054932224 -0.052752276 -0.047439030
#> 26: -0.055338071 -0.053150002 -0.047743160
#> 27: -0.055438044 -0.053281666 -0.047846017
#> 28: -0.055653813 -0.053402789 -0.048168245
#> 29: -0.055612651 -0.053291129 -0.048379141
#> 30: -0.055767036 -0.053329221 -0.048593126
#> 31: -0.055771690 -0.053357224 -0.048536703
#> 32: -0.055898599 -0.053439598 -0.048490801
#> 33: -0.055790201 -0.053346186 -0.048497525
#> 34: -0.055868609 -0.053363021 -0.048588345
#> 35: -0.055855906 -0.053338649 -0.048546373
#> 36: -0.056027348 -0.053511837 -0.048850330
#> 37: -0.055899900 -0.053459750 -0.048878023
#> 38:  0.165950595  0.186371775  0.296950952
#> 39:  0.167298791  0.188966688  0.304381920
#> 40:  0.151529080  0.169940708  0.270677585
#> 41:  0.144236598  0.162260762  0.255829795
#> 42:  0.144623183  0.163231737  0.259049475
#> 43:  0.145293212  0.164419041  0.258991880
#> 44:  0.140657701  0.159044605  0.246529670
#> 45:  0.083351459  0.091198483  0.128872946
#> 46:  0.045958959  0.050708245  0.070090695
#> 47:  0.025608691  0.029863588  0.043667126
#> 48:  0.002154091  0.006020141  0.016136190
#> 49: -0.017195910 -0.013400714 -0.003908225
#> 50: -0.031459527 -0.027719654 -0.018036554
#> 51: -0.049441971 -0.045474089 -0.036129388
#> 52: -0.030162242 -0.027369330 -0.018077355
#> 53: -0.036510115 -0.034335200 -0.025948312
#> 54: -0.041333903 -0.039174880 -0.032030681
#> 55: -0.045258611 -0.043275024 -0.036361106
#> 56: -0.048306514 -0.046163817 -0.039616352
#> 57: -0.050435984 -0.048495616 -0.042575938
#> 58: -0.051854907 -0.049951920 -0.044398069
#> 59: -0.053010065 -0.050986050 -0.045359964
#> 60: -0.053962558 -0.051741129 -0.046458818
#> 61: -0.054570493 -0.052316783 -0.047241985
#> 62: -0.055013052 -0.052724746 -0.047797386
#> 63: -0.055367375 -0.053023907 -0.048202297
#> 64: -0.055526833 -0.053133329 -0.048346377
#> 65: -0.055702187 -0.053349803 -0.048929225
#> 66: -0.055611342 -0.053285255 -0.049098575
#> 67: -0.055745457 -0.053380351 -0.049216964
#> 68: -0.055848031 -0.053456292 -0.049201126
#> 69: -0.055933188 -0.053608283 -0.049207632
#> 70: -0.055707872 -0.053479699 -0.048876367
#> 71: -0.055684648 -0.053612800 -0.048845849
#> 72: -0.055677359 -0.053465005 -0.048774319
#> 73: -0.055775698 -0.053626188 -0.048952880
#> 74: -0.055664848 -0.053455992 -0.048806180
#>         upper_20     upper_50     upper_90
#> 
#> $summarised_measures$cases_by_infection
#>       region       date strat                           type median   mean
#>  1: realland 2020-02-22  <NA>                       estimate 1584.5 1564.8
#>  2: realland 2020-02-23  <NA>                       estimate 1845.3 1824.5
#>  3: realland 2020-02-24  <NA>                       estimate 2063.4 2043.5
#>  4: realland 2020-02-25  <NA>                       estimate 2322.8 2304.7
#>  5: realland 2020-02-26  <NA>                       estimate 2649.5 2633.2
#>  6: realland 2020-02-27  <NA>                       estimate 3023.0 3011.0
#>  7: realland 2020-02-28  <NA>                       estimate 3403.6 3398.5
#>  8: realland 2020-02-29  <NA>                       estimate 3300.8 3303.4
#>  9: realland 2020-03-01  <NA>                       estimate 3173.5 3184.6
#> 10: realland 2020-03-02  <NA>                       estimate 3106.5 3125.2
#> 11: realland 2020-03-03  <NA>                       estimate 2943.0 2967.0
#> 12: realland 2020-03-04  <NA>                       estimate 2755.5 2784.0
#> 13: realland 2020-03-05  <NA>                       estimate 2577.0 2606.2
#> 14: realland 2020-03-06  <NA>                       estimate 2328.0 2357.5
#> 15: realland 2020-03-07  <NA> estimate based on partial data 2419.7 2453.6
#> 16: realland 2020-03-08  <NA> estimate based on partial data 2285.7 2320.3
#> 17: realland 2020-03-09  <NA> estimate based on partial data 2157.5 2192.9
#> 18: realland 2020-03-10  <NA> estimate based on partial data 2037.4 2071.5
#> 19: realland 2020-03-11  <NA> estimate based on partial data 1923.4 1956.4
#> 20: realland 2020-03-12  <NA> estimate based on partial data 1814.6 1846.8
#> 21: realland 2020-03-13  <NA> estimate based on partial data 1713.7 1743.8
#> 22: realland 2020-03-14  <NA> estimate based on partial data 1618.2 1645.6
#> 23: realland 2020-03-15  <NA> estimate based on partial data 1527.1 1552.3
#> 24: realland 2020-03-16  <NA> estimate based on partial data 1441.5 1464.1
#> 25: realland 2020-03-17  <NA> estimate based on partial data 1360.7 1380.9
#> 26: realland 2020-03-18  <NA> estimate based on partial data 1284.0 1302.0
#> 27: realland 2020-03-19  <NA> estimate based on partial data 1212.6 1228.3
#> 28: realland 2020-03-20  <NA> estimate based on partial data 1144.1 1157.9
#> 29: realland 2020-03-21  <NA> estimate based on partial data 1080.4 1092.7
#> 30: realland 2020-03-22  <NA> estimate based on partial data 1019.6 1030.7
#> 31: realland 2020-03-23  <NA>                       forecast  962.3  972.0
#> 32: realland 2020-03-24  <NA>                       forecast  907.8  916.5
#> 33: realland 2020-03-25  <NA>                       forecast  857.4  865.1
#> 34: realland 2020-03-26  <NA>                       forecast  809.3  815.9
#> 35: realland 2020-03-27  <NA>                       forecast  764.6  769.9
#> 36: realland 2020-03-28  <NA>                       forecast  721.3  725.9
#> 37: realland 2020-03-29  <NA>                       forecast  680.8  685.0
#> 38: testland 2020-02-22  <NA>                       estimate 1585.8 1570.2
#> 39: testland 2020-02-23  <NA>                       estimate 1846.5 1830.2
#> 40: testland 2020-02-24  <NA>                       estimate 2064.8 2049.0
#> 41: testland 2020-02-25  <NA>                       estimate 2324.3 2309.8
#> 42: testland 2020-02-26  <NA>                       estimate 2648.7 2637.8
#> 43: testland 2020-02-27  <NA>                       estimate 3023.3 3014.6
#> 44: testland 2020-02-28  <NA>                       estimate 3403.3 3400.8
#> 45: testland 2020-02-29  <NA>                       estimate 3300.8 3303.9
#> 46: testland 2020-03-01  <NA>                       estimate 3173.6 3183.5
#> 47: testland 2020-03-02  <NA>                       estimate 3107.7 3122.8
#> 48: testland 2020-03-03  <NA>                       estimate 2944.1 2963.5
#> 49: testland 2020-03-04  <NA>                       estimate 2756.5 2779.7
#> 50: testland 2020-03-05  <NA>                       estimate 2575.8 2601.5
#> 51: testland 2020-03-06  <NA>                       estimate 2326.8 2352.7
#> 52: testland 2020-03-07  <NA> estimate based on partial data 2418.4 2448.2
#> 53: testland 2020-03-08  <NA> estimate based on partial data 2284.6 2315.0
#> 54: testland 2020-03-09  <NA> estimate based on partial data 2157.6 2187.7
#> 55: testland 2020-03-10  <NA> estimate based on partial data 2037.8 2066.6
#> 56: testland 2020-03-11  <NA> estimate based on partial data 1925.1 1951.9
#> 57: testland 2020-03-12  <NA> estimate based on partial data 1817.6 1842.6
#> 58: testland 2020-03-13  <NA> estimate based on partial data 1716.4 1740.0
#> 59: testland 2020-03-14  <NA> estimate based on partial data 1620.1 1642.1
#> 60: testland 2020-03-15  <NA> estimate based on partial data 1528.9 1549.2
#> 61: testland 2020-03-16  <NA> estimate based on partial data 1443.0 1461.2
#> 62: testland 2020-03-17  <NA> estimate based on partial data 1361.7 1378.4
#> 63: testland 2020-03-18  <NA> estimate based on partial data 1284.8 1299.7
#> 64: testland 2020-03-19  <NA> estimate based on partial data 1212.8 1226.2
#> 65: testland 2020-03-20  <NA> estimate based on partial data 1144.0 1155.9
#> 66: testland 2020-03-21  <NA> estimate based on partial data 1080.6 1090.9
#> 67: testland 2020-03-22  <NA> estimate based on partial data 1020.2 1029.1
#> 68: testland 2020-03-23  <NA>                       forecast  962.3  970.5
#> 69: testland 2020-03-24  <NA>                       forecast  908.1  915.1
#> 70: testland 2020-03-25  <NA>                       forecast  857.8  863.9
#> 71: testland 2020-03-26  <NA>                       forecast  809.2  814.8
#> 72: testland 2020-03-27  <NA>                       forecast  764.1  768.9
#> 73: testland 2020-03-28  <NA>                       forecast  721.0  725.2
#> 74: testland 2020-03-29  <NA>                       forecast  680.9  684.5
#>       region       date strat                           type median   mean
#>        sd lower_90 lower_50 lower_20 upper_20 upper_50 upper_90
#>  1:  96.8   1386.4   1532.6   1570.1   1592.3   1607.3   1681.7
#>  2: 110.1   1620.8   1789.1   1830.1   1853.8   1871.4   1960.7
#>  3: 119.9   1833.2   2003.9   2048.7   2072.4   2093.3   2198.6
#>  4: 131.3   2074.6   2260.6   2308.5   2332.9   2358.7   2484.6
#>  5: 145.7   2380.6   2580.6   2634.0   2660.0   2687.0   2836.3
#>  6: 162.4   2744.1   2947.9   3006.5   3034.4   3066.9   3253.0
#>  7: 179.8   3108.0   3328.3   3387.9   3416.3   3460.8   3676.3
#>  8: 172.9   3040.2   3235.0   3286.3   3314.3   3359.8   3575.3
#>  9: 166.7   2940.2   3117.1   3163.0   3190.4   3237.6   3458.1
#> 10: 165.4   2888.9   3057.1   3095.6   3125.4   3176.0   3409.1
#> 11: 160.2   2753.2   2899.3   2932.4   2961.5   3014.1   3255.9
#> 12: 154.4   2587.4   2718.1   2746.0   2775.4   2828.2   3068.9
#> 13: 149.0   2420.4   2541.6   2565.7   2594.8   2646.6   2882.5
#> 14: 139.0   2184.1   2296.0   2316.5   2345.3   2391.9   2624.3
#> 15: 149.0   2273.6   2386.1   2407.0   2439.8   2491.4   2740.2
#> 16: 144.7   2151.5   2254.8   2273.0   2304.4   2357.8   2599.2
#> 17: 140.0   2031.6   2127.9   2146.2   2176.8   2229.5   2461.0
#> 18: 134.8   1915.4   2009.4   2026.2   2054.7   2108.6   2324.9
#> 19: 129.4   1805.4   1895.9   1913.0   1939.9   1991.4   2190.0
#> 20: 123.6   1706.2   1790.6   1805.7   1830.8   1881.0   2071.7
#> 21: 117.6   1608.2   1691.3   1705.3   1729.4   1774.9   1957.2
#> 22: 111.4   1514.5   1596.6   1610.1   1632.8   1674.3   1843.2
#> 23: 105.1   1423.9   1507.1   1520.0   1540.2   1578.2   1737.8
#> 24:  98.7   1340.8   1422.5   1435.0   1454.3   1489.0   1642.4
#> 25:  92.4   1268.3   1342.6   1354.7   1372.4   1404.7   1555.8
#> 26:  86.2   1195.0   1266.6   1278.8   1294.2   1323.7   1459.6
#> 27:  80.3   1129.0   1195.9   1207.6   1221.7   1246.8   1373.8
#> 28:  74.7   1066.7   1128.1   1139.6   1152.6   1174.8   1295.1
#> 29:  69.5   1007.3   1065.2   1076.4   1088.5   1108.5   1217.9
#> 30:  64.6    950.9   1004.7   1016.3   1026.9   1046.1   1145.9
#> 31:  60.2    896.5    947.5    958.9    968.7    987.3   1077.0
#> 32:  56.0    845.4    893.0    904.7    913.8    932.6   1014.6
#> 33:  52.2    796.0    843.8    854.4    862.9    880.9    958.2
#> 34:  48.6    749.0    796.1    806.2    814.9    831.2    899.5
#> 35:  45.2    707.8    751.3    761.4    769.5    784.6    847.5
#> 36:  41.9    667.6    708.8    718.3    726.2    739.4    795.9
#> 37:  38.8    630.7    668.9    678.4    685.4    697.7    748.8
#> 38:  87.6   1409.7   1541.7   1572.6   1593.4   1610.3   1684.6
#> 39: 100.4   1647.4   1797.8   1831.7   1854.9   1875.2   1968.1
#> 40: 110.4   1852.3   2012.5   2048.4   2074.2   2096.5   2206.6
#> 41: 122.3   2096.7   2266.5   2307.8   2333.4   2358.9   2487.6
#> 42: 137.3   2401.5   2586.2   2633.5   2660.4   2690.0   2849.0
#> 43: 154.8   2752.4   2955.3   3005.4   3035.2   3071.0   3261.2
#> 44: 173.4   3117.4   3333.1   3386.2   3418.3   3462.0   3686.7
#> 45: 168.4   3049.6   3234.9   3284.6   3315.1   3363.5   3572.7
#> 46: 163.8   2936.2   3114.7   3160.3   3188.8   3237.4   3452.4
#> 47: 163.6   2880.9   3053.1   3094.5   3123.9   3174.6   3392.5
#> 48: 159.3   2741.2   2895.2   2932.1   2962.3   3010.6   3233.3
#> 49: 153.9   2577.2   2712.6   2745.0   2775.6   2823.5   3048.2
#> 50: 148.6   2414.1   2536.4   2564.5   2594.7   2641.5   2867.1
#> 51: 138.3   2179.8   2290.6   2315.3   2344.5   2389.7   2597.6
#> 52: 147.4   2268.5   2382.9   2405.7   2437.7   2486.6   2710.3
#> 53: 141.9   2144.0   2252.7   2271.6   2303.0   2352.1   2572.3
#> 54: 135.6   2024.6   2127.8   2145.3   2175.2   2220.7   2435.8
#> 55: 128.7   1916.3   2008.4   2025.8   2054.4   2098.9   2312.3
#> 56: 121.5   1811.1   1896.5   1912.6   1941.5   1981.1   2183.8
#> 57: 114.3   1712.6   1789.7   1805.6   1832.7   1872.7   2055.9
#> 58: 107.3   1617.4   1690.4   1705.9   1730.2   1767.5   1930.0
#> 59: 100.7   1524.1   1596.4   1610.2   1633.8   1669.0   1820.2
#> 60:  94.4   1437.9   1505.8   1519.9   1542.8   1575.2   1717.6
#> 61:  88.6   1353.6   1419.7   1434.6   1455.8   1484.9   1621.2
#> 62:  83.1   1273.5   1340.5   1354.5   1373.8   1401.1   1530.1
#> 63:  77.9   1197.6   1264.5   1278.5   1295.4   1321.5   1437.1
#> 64:  73.0   1127.5   1194.0   1207.3   1222.4   1246.9   1356.0
#> 65:  68.3   1061.1   1125.7   1139.0   1153.0   1175.4   1278.6
#> 66:  63.9   1000.6   1063.1   1076.0   1089.0   1110.3   1203.3
#> 67:  59.7    944.0   1003.0   1015.6   1027.1   1048.2   1136.9
#> 68:  55.7    893.4    946.1    958.3    969.4    988.9   1071.2
#> 69:  51.9    842.6    893.0    903.9    914.2    932.2   1007.9
#> 70:  48.4    796.6    843.1    853.9    863.9    880.0    951.2
#> 71:  45.0    751.2    795.6    806.1    814.9    829.6    893.6
#> 72:  41.9    709.9    751.5    761.0    769.4    782.8    841.9
#> 73:  39.0    671.0    708.9    718.1    725.9    738.1    790.8
#> 74:  36.3    633.0    669.8    678.3    685.2    696.2    746.4
#>        sd lower_90 lower_50 lower_20 upper_20 upper_50 upper_90
#> 
#> $summarised_measures$cases_by_report
#>       region       date strat                           type median   mean
#>  1: realland 2020-02-22  <NA>                       estimate  202.0  325.4
#>  2: realland 2020-02-23  <NA>                       estimate  295.0  463.2
#>  3: realland 2020-02-24  <NA>                       estimate  222.5  363.3
#>  4: realland 2020-02-25  <NA>                       estimate  303.5  471.7
#>  5: realland 2020-02-26  <NA>                       estimate  314.0  514.2
#>  6: realland 2020-02-27  <NA>                       estimate  481.5  756.9
#>  7: realland 2020-02-28  <NA>                       estimate  653.0  996.7
#>  8: realland 2020-02-29  <NA>                       estimate  666.0 1033.2
#>  9: realland 2020-03-01  <NA>                       estimate  970.5 1456.2
#> 10: realland 2020-03-02  <NA>                       estimate  668.0 1046.5
#> 11: realland 2020-03-03  <NA>                       estimate  809.5 1354.3
#> 12: realland 2020-03-04  <NA>                       estimate  786.5 1293.0
#> 13: realland 2020-03-05  <NA>                       estimate 1215.5 1886.7
#> 14: realland 2020-03-06  <NA>                       estimate 1569.5 2493.4
#> 15: realland 2020-03-07  <NA> estimate based on partial data 1411.5 2348.0
#> 16: realland 2020-03-08  <NA> estimate based on partial data 1955.5 2937.4
#> 17: realland 2020-03-09  <NA> estimate based on partial data 1093.5 1815.8
#> 18: realland 2020-03-10  <NA> estimate based on partial data 1319.0 2145.5
#> 19: realland 2020-03-11  <NA> estimate based on partial data 1159.5 1798.0
#> 20: realland 2020-03-12  <NA> estimate based on partial data 1515.0 2431.7
#> 21: realland 2020-03-13  <NA> estimate based on partial data 1902.0 2931.4
#> 22: realland 2020-03-14  <NA> estimate based on partial data 1578.0 2550.9
#> 23: realland 2020-03-15  <NA> estimate based on partial data 1885.0 2997.7
#> 24: realland 2020-03-16  <NA> estimate based on partial data 1109.5 1839.8
#> 25: realland 2020-03-17  <NA> estimate based on partial data 1232.0 1945.2
#> 26: realland 2020-03-18  <NA> estimate based on partial data 1035.5 1696.2
#> 27: realland 2020-03-19  <NA> estimate based on partial data 1240.5 2094.5
#> 28: realland 2020-03-20  <NA> estimate based on partial data 1546.5 2470.6
#> 29: realland 2020-03-21  <NA> estimate based on partial data 1383.5 2212.1
#> 30: realland 2020-03-22  <NA> estimate based on partial data 1544.5 2478.7
#> 31: realland 2020-03-23  <NA>                       forecast  895.5 1459.6
#> 32: realland 2020-03-24  <NA>                       forecast 1042.5 1606.7
#> 33: realland 2020-03-25  <NA>                       forecast  812.0 1343.5
#> 34: realland 2020-03-26  <NA>                       forecast  991.5 1693.3
#> 35: realland 2020-03-27  <NA>                       forecast 1239.5 1907.3
#> 36: realland 2020-03-28  <NA>                       forecast  985.0 1607.5
#> 37: realland 2020-03-29  <NA>                       forecast 1118.5 1858.9
#> 38: testland 2020-02-22  <NA>                       estimate  214.0  331.4
#> 39: testland 2020-02-23  <NA>                       estimate  309.0  466.4
#> 40: testland 2020-02-24  <NA>                       estimate  213.0  362.1
#> 41: testland 2020-02-25  <NA>                       estimate  323.0  493.9
#> 42: testland 2020-02-26  <NA>                       estimate  291.0  504.2
#> 43: testland 2020-02-27  <NA>                       estimate  466.5  754.8
#> 44: testland 2020-02-28  <NA>                       estimate  670.0 1038.0
#> 45: testland 2020-02-29  <NA>                       estimate  699.0 1108.1
#> 46: testland 2020-03-01  <NA>                       estimate  976.5 1495.7
#> 47: testland 2020-03-02  <NA>                       estimate  656.5 1038.8
#> 48: testland 2020-03-03  <NA>                       estimate  830.5 1390.8
#> 49: testland 2020-03-04  <NA>                       estimate  839.5 1300.2
#> 50: testland 2020-03-05  <NA>                       estimate 1178.5 1892.8
#> 51: testland 2020-03-06  <NA>                       estimate 1566.5 2436.6
#> 52: testland 2020-03-07  <NA> estimate based on partial data 1558.0 2341.3
#> 53: testland 2020-03-08  <NA> estimate based on partial data 1896.5 2950.5
#> 54: testland 2020-03-09  <NA> estimate based on partial data 1153.0 1832.4
#> 55: testland 2020-03-10  <NA> estimate based on partial data 1404.5 2264.2
#> 56: testland 2020-03-11  <NA> estimate based on partial data 1157.0 1879.4
#> 57: testland 2020-03-12  <NA> estimate based on partial data 1499.0 2418.9
#> 58: testland 2020-03-13  <NA> estimate based on partial data 1829.5 2967.5
#> 59: testland 2020-03-14  <NA> estimate based on partial data 1627.5 2632.7
#> 60: testland 2020-03-15  <NA> estimate based on partial data 1947.0 2902.9
#> 61: testland 2020-03-16  <NA> estimate based on partial data 1106.0 1777.2
#> 62: testland 2020-03-17  <NA> estimate based on partial data 1327.5 2124.3
#> 63: testland 2020-03-18  <NA> estimate based on partial data 1081.5 1722.6
#> 64: testland 2020-03-19  <NA> estimate based on partial data 1358.5 2166.3
#> 65: testland 2020-03-20  <NA> estimate based on partial data 1535.0 2503.8
#> 66: testland 2020-03-21  <NA> estimate based on partial data 1384.5 2209.3
#> 67: testland 2020-03-22  <NA> estimate based on partial data 1591.5 2485.0
#> 68: testland 2020-03-23  <NA>                       forecast  907.0 1484.7
#> 69: testland 2020-03-24  <NA>                       forecast 1003.5 1574.5
#> 70: testland 2020-03-25  <NA>                       forecast  879.0 1363.6
#> 71: testland 2020-03-26  <NA>                       forecast 1071.0 1681.0
#> 72: testland 2020-03-27  <NA>                       forecast 1199.5 1847.0
#> 73: testland 2020-03-28  <NA>                       forecast 1048.0 1702.3
#> 74: testland 2020-03-29  <NA>                       forecast 1201.0 1848.9
#>       region       date strat                           type median   mean
#>         sd lower_90 lower_50 lower_20 upper_20 upper_50 upper_90
#>  1:  380.2     14.0     82.8    148.0    278.4    432.0   1014.7
#>  2:  513.7     18.0    123.0    216.6    405.0    628.8   1474.0
#>  3:  456.9     13.0     92.0    161.6    297.4    455.0   1171.4
#>  4:  541.1     20.0    118.0    214.6    409.4    628.5   1487.7
#>  5:  642.7     19.0    119.0    224.0    429.0    662.0   1730.1
#>  6:  870.9     27.0    190.0    349.6    659.8   1021.2   2338.2
#>  7: 1077.0     40.0    271.0    481.6    859.0   1375.0   3191.1
#>  8: 1122.4     43.0    277.8    488.2    879.4   1431.2   3246.1
#>  9: 1670.8     67.0    389.8    700.4   1286.8   1917.2   4339.3
#> 10: 1358.3     38.9    258.0    469.0    868.8   1325.0   3379.2
#> 11: 1702.3     51.0    321.0    579.0   1103.2   1797.0   4292.7
#> 12: 1589.2     53.0    307.0    554.8   1061.4   1693.0   4099.1
#> 13: 2189.7     74.9    494.8    903.6   1607.0   2413.8   5952.3
#> 14: 2884.8     97.9    641.5   1131.8   2082.2   3275.0   8349.2
#> 15: 2702.2     86.9    588.5   1023.8   1952.6   3116.2   7700.6
#> 16: 3321.0    145.8    728.2   1354.8   2572.4   3956.0   9374.6
#> 17: 2137.8     70.9    467.2    800.2   1520.8   2361.5   5926.4
#> 18: 2642.5     98.9    520.2    927.8   1783.4   2752.5   7104.7
#> 19: 1971.8     88.9    468.0    840.0   1572.8   2443.2   5622.2
#> 20: 2747.5    121.9    617.8   1133.8   2053.0   3153.5   8106.9
#> 21: 3230.9    117.9    749.5   1426.6   2485.4   3904.0   9186.1
#> 22: 3071.6    106.9    631.0   1151.6   2121.4   3320.2   8319.2
#> 23: 3422.4    153.0    782.2   1392.8   2567.4   3931.5   9475.2
#> 24: 2205.2     88.0    455.5    828.6   1460.2   2446.0   6162.6
#> 25: 2175.0     78.9    482.0    877.8   1634.0   2661.2   6193.5
#> 26: 2012.6     81.9    425.5    780.6   1381.8   2225.8   5684.3
#> 27: 2616.1     84.0    516.0    932.6   1720.0   2720.5   6532.9
#> 28: 2933.9     85.0    624.5   1132.0   2023.4   3212.2   7958.6
#> 29: 2635.1     79.9    555.2   1023.6   1862.2   2897.5   7008.4
#> 30: 2766.5     90.9    623.8   1126.4   2101.2   3331.2   7905.0
#> 31: 1725.0     71.0    363.8    646.6   1183.2   1931.2   4826.6
#> 32: 1845.0     70.0    393.8    760.6   1376.4   2118.5   5082.6
#> 33: 1649.5     54.0    325.5    610.2   1082.0   1742.2   4376.2
#> 34: 2136.1     54.0    393.8    716.8   1322.8   2189.8   5534.1
#> 35: 2091.7     70.0    492.0    894.6   1638.2   2608.2   5927.2
#> 36: 1889.5     72.0    426.8    743.0   1311.0   2083.2   5196.4
#> 37: 2144.2     71.9    477.0    859.6   1534.4   2506.2   6005.0
#> 38:  374.3     15.0     89.0    156.0    281.0    435.2   1072.2
#> 39:  514.0     18.0    119.0    220.6    412.4    635.0   1417.3
#> 40:  437.7     12.0     89.8    155.0    279.0    467.0   1258.0
#> 41:  538.4     22.9    133.8    240.0    424.8    658.0   1576.1
#> 42:  698.6     20.0    120.0    216.0    381.0    627.0   1637.5
#> 43:  910.0     29.0    180.5    340.0    634.0    996.0   2467.8
#> 44: 1172.6     52.0    265.0    489.6    896.0   1365.2   3364.1
#> 45: 1291.5     49.0    284.5    511.6    922.0   1425.8   3697.1
#> 46: 1573.5     55.9    391.5    749.6   1298.6   2080.5   4552.2
#> 47: 1187.9     42.9    266.8    480.6    871.4   1433.8   3308.5
#> 48: 2008.4     50.8    339.8    590.2   1127.0   1794.0   4573.2
#> 49: 1478.6     54.9    313.8    597.0   1090.8   1735.2   4211.0
#> 50: 2234.5     68.0    434.2    832.6   1574.0   2493.2   6461.0
#> 51: 2932.6     96.0    607.0   1156.8   2076.2   3192.2   7945.1
#> 52: 2580.5     97.9    569.0   1109.8   2026.4   3182.0   7412.3
#> 53: 3340.9    138.9    777.0   1396.6   2499.4   3871.5   9405.8
#> 54: 2287.3     76.9    478.8    873.6   1497.4   2268.2   5719.7
#> 55: 2630.0    102.8    586.0   1045.2   1871.4   2967.2   7310.0
#> 56: 2225.3     90.9    480.8    853.8   1569.2   2489.2   5950.9
#> 57: 2998.1     94.9    597.0   1065.0   1960.2   3133.2   7912.2
#> 58: 3361.2    148.0    795.5   1352.8   2451.6   3839.0   9787.1
#> 59: 3126.1     88.0    641.0   1191.6   2232.2   3506.5   8491.0
#> 60: 3141.2    108.9    749.0   1401.2   2590.8   3899.2   8996.3
#> 61: 2097.5     69.0    436.8    801.6   1486.4   2301.8   5556.9
#> 62: 2747.9     86.0    532.8    941.6   1767.6   2758.0   7134.3
#> 63: 2075.4     59.9    411.5    758.8   1417.8   2197.0   5573.0
#> 64: 2467.8     77.9    548.5    967.6   1880.8   2861.5   7138.1
#> 65: 2879.2    105.9    599.0   1122.4   2091.4   3288.0   8825.1
#> 66: 2688.3     92.0    534.8    963.6   1802.0   2868.8   7000.1
#> 67: 2819.8     73.0    615.2   1139.8   2192.0   3305.5   8063.8
#> 68: 1796.9     58.0    376.0    675.0   1228.4   1884.8   4942.0
#> 69: 1799.6     58.9    391.8    706.0   1324.6   2091.0   5065.1
#> 70: 1502.1     64.9    360.5    637.6   1171.4   1806.0   4376.4
#> 71: 1950.1     56.9    431.8    772.0   1414.4   2215.2   5332.5
#> 72: 2096.6     68.9    447.0    845.6   1614.4   2476.5   5741.6
#> 73: 2121.4     70.0    417.8    756.2   1440.0   2188.8   5553.8
#> 74: 2011.6     77.9    459.0    829.4   1615.8   2500.0   5914.3
#>         sd lower_90 lower_50 lower_20 upper_20 upper_50 upper_90
#> 
#> 
#> $reported_cases
#>           date confirm   region
#>  1: 2020-02-22      14 testland
#>  2: 2020-02-23      62 testland
#>  3: 2020-02-24      53 testland
#>  4: 2020-02-25      97 testland
#>  5: 2020-02-26      93 testland
#>  6: 2020-02-27      78 testland
#>  7: 2020-02-28     250 testland
#>  8: 2020-02-29     238 testland
#>  9: 2020-03-01     240 testland
#> 10: 2020-03-02     561 testland
#> 11: 2020-03-03     347 testland
#> 12: 2020-03-04     466 testland
#> 13: 2020-03-05     587 testland
#> 14: 2020-03-06     769 testland
#> 15: 2020-03-07     778 testland
#> 16: 2020-03-08    1247 testland
#> 17: 2020-03-09    1492 testland
#> 18: 2020-03-10    1797 testland
#> 19: 2020-03-11     977 testland
#> 20: 2020-03-12    2313 testland
#> 21: 2020-03-13    2651 testland
#> 22: 2020-03-14    2547 testland
#> 23: 2020-03-15    3497 testland
#> 24: 2020-03-16    2823 testland
#> 25: 2020-03-17    4000 testland
#> 26: 2020-03-18    3526 testland
#> 27: 2020-03-19    4207 testland
#> 28: 2020-03-20    5322 testland
#> 29: 2020-03-21    5986 testland
#> 30: 2020-03-22    6557 testland
#> 31: 2020-02-22      14 realland
#> 32: 2020-02-23      62 realland
#> 33: 2020-02-24      53 realland
#> 34: 2020-02-25      97 realland
#> 35: 2020-02-26      93 realland
#> 36: 2020-02-27      78 realland
#> 37: 2020-02-28     250 realland
#> 38: 2020-02-29     238 realland
#> 39: 2020-03-01     240 realland
#> 40: 2020-03-02     561 realland
#> 41: 2020-03-03     347 realland
#> 42: 2020-03-04     466 realland
#> 43: 2020-03-05     587 realland
#> 44: 2020-03-06     769 realland
#> 45: 2020-03-07     778 realland
#> 46: 2020-03-08    1247 realland
#> 47: 2020-03-09    1492 realland
#> 48: 2020-03-10    1797 realland
#> 49: 2020-03-11     977 realland
#> 50: 2020-03-12    2313 realland
#> 51: 2020-03-13    2651 realland
#> 52: 2020-03-14    2547 realland
#> 53: 2020-03-15    3497 realland
#> 54: 2020-03-16    2823 realland
#> 55: 2020-03-17    4000 realland
#> 56: 2020-03-18    3526 realland
#> 57: 2020-03-19    4207 realland
#> 58: 2020-03-20    5322 realland
#> 59: 2020-03-21    5986 realland
#> 60: 2020-03-22    6557 realland
#>           date confirm   region
#> 
#> $high_plots
#> $high_plots$infections

#> 
#> $high_plots$reports

#> 
#> $high_plots$R

#> 
#> $high_plots$growth_rate

#> 
#> 
#> $plots
#> $plots$infections

#> 
#> $plots$reports

#> 
#> $plots$R

#> 
#> $plots$growth_rate

#> 
#> 
# }