diff --git a/analysis_scripts/create_main_plots.jl b/analysis_scripts/create_main_plots.jl index 9ccb11c..6daa750 100644 --- a/analysis_scripts/create_main_plots.jl +++ b/analysis_scripts/create_main_plots.jl @@ -70,11 +70,12 @@ plot!(PCR_plt,(1+3):(length(kenya_pos_mv_av)+3),kenya_pos_mv_av, # plot!(PCR_plt,(n_1+1):(size(linelist_data.cases,1)-3),weekly_mv_av(sum(linelist_data.cases,dims = 2)[:])[(n_1+1):end],color = :red,lw = 3,lab = "Daily cases: Kenyan MoH (7 day mv-av)") smooth_cases_lookahead = weekly_mv_av(sum(linelist_data.cases[(n_1-2):end,:],dims = 2)[:]) plot!(PCR_plt,(length(kenya_pos_mv_av)+4):(length(kenya_pos_mv_av)+3+length(smooth_cases_lookahead)),smooth_cases_lookahead, - color = :red,lw = 3, + color = :black,lw = 3,ls = :dash, lab = "Daily cases: 7 day mv-av (not used in fitting)") plot!(PCR_plt,4:(n-3),kenya_pcr_forecast_mv_av,ribbon = 9*sqrt.(kenya_pcr_forecast_mv_av_var), - color = :green, lw = 5, ls = :dot,lab = "Model fit and forecast (7 day mv-av)") + color = :red, lw = 3,lab = "Model fit and forecast (7 day mv-av)", + fillalpha = 0.4) # savefig(PCR_plt,"plots/kenya_cases.png") @@ -141,8 +142,8 @@ plot!(deaths_plt,4:(n-3),cumsum(kenya_deaths_forecast_mv_av), ## Kenya Serology plot -plotlyjs() -# gr() +# plotlyjs() +gr() xticktimes = [((Date(2020,2,1) + Month(k))- Date(2020,2,24)).value for k = 1:18 ] xticklabs = [monthname(k)[1:3]*"/20" for k = 3:12] xticklabs = vcat(xticklabs,[monthname(k)[1:3]*"/21" for k = 1:8]) @@ -228,14 +229,14 @@ scatter!(plt_sero,xs_mondays[seroidxs.*rnd3_idxs],kenya_weekly_sero_pos_rnd3[ser lab = "Weekly KNBTS: round 3 (not used in fitting)") plot!(plt_sero,kenya_serology_forecast_nw,lw = 2,color = :green, ribbon = 3*sqrt.(var_kenya_serology_forecast), - lab = "Model fit: seroposivity (adjusted, no seroreversion)" ) + lab = "Model fit: seropositivity (test weighted, no seroreversion)" ) plot!(plt_sero,test_weighted_kenya_serology_forecast,lw = 2,ls = :dash,color = :green, - lab = "Model fit: seroposivity (adjusted, with seroreversion)" ) + lab = "Model fit: seropositivity (test weighted, with seroreversion)" ) plot!(plt_sero,kenya_infections_forecast./sum(N_kenya), ribbon = 9*sqrt.(var_kenya_infections_forecast)./sum(N_kenya), - lab = "Model fit: Overall Kenyan population exposure (unadjusted)", + lab = "Model fit: Overall Kenyan population exposure", color = :red) # savefig(plt_sero,"plots/kenya_sero.png") diff --git a/plots/kenya_cases.png b/plots/kenya_cases.png index d45c77e..d7f5ad1 100644 Binary files a/plots/kenya_cases.png and b/plots/kenya_cases.png differ diff --git a/plots/kenya_sero.png b/plots/kenya_sero.png index 82620af..bf2c46b 100644 Binary files a/plots/kenya_sero.png and b/plots/kenya_sero.png differ diff --git a/sensitivity_analysis/model_selection.jl b/sensitivity_analysis/model_selection.jl index 44a51c6..ed77990 100644 --- a/sensitivity_analysis/model_selection.jl +++ b/sensitivity_analysis/model_selection.jl @@ -99,7 +99,7 @@ include("../analysis_scripts/plotting_methods.jl") ct_fitted = EM_steps[end][1] N = sum(N_kenya[:,"Nairobi"]) -plot(ct_fitted) +ct_plt = plot_ct(ct_fitted) ##Calculate predictions diff --git a/supplementary_info/Explaining the 3 waves in Kenya_supporting_information.docx b/supplementary_info/Explaining the 3 waves in Kenya_supporting_information.docx deleted file mode 100644 index d2537e7..0000000 Binary files a/supplementary_info/Explaining the 3 waves in Kenya_supporting_information.docx and /dev/null differ