![[Maturing]](figures/lifecycle-maturing.svg)
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_epinowand stored in theregionallist.- 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
#>
#>
# }