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geseir_forecast.m
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geseir_forecast.m
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% seir_forecast() forecasts a generalized SEIR model n days.
% Based on E. Cheynet's work [1].
%
% References:
% [1] https://www.mathworks.com/matlabcentral/fileexchange/74545-generalized-seir-epidemic-model-fitting-and-computation
%
% Version: 001
% Date: 2020/04/02
% Author: Rodrigo Gonzalez <rodralez@frm.utn.edu.ar>
% URL: https://github.com/rodralez/covid-19
%
% The fitting is here more challenging than in Example 1 because the term
% "Confirmed patient" used in the database does not precise whether they have
% been quarantined or not. In a previous version of the submision (version <1.5)
% , the infectious cases were erroneously used instead of the quarantined cases.
if (~exist('ITERATIVE','var')), ITERATIVE = 'OFF'; end
if strcmp( ITERATIVE, 'OFF' )
clear
close all
clc
if (~exist('ITERATIVE','var')), ITERATIVE = 'OFF'; end
end
if (~exist('ENGLISH','var')), ENGLISH = 'OFF'; end
if (~exist('PEAK','var')), PEAK = 'OFF'; end
addpath ./
addpath /home/rodralez/my/investigacion/work-in-progress/covid-19/matlab/
addpath ./num2sip/
%% Cases
% S(t): susceptible cases,
% P(t): insusceptible cases,
% E(t): exposed cases(infected but not yet be infectious, in a latent period),
% I(t): infectious cases(with infectious capacity and not yet be quarantined),
% Q(t): quarantinedcases(confirmed and infected),
% R(t): recovered cases and
% D(t): % closed cases(or death
%% Rates
% alpha: protection rate,
% beta: infection rate,
% gamma: average latent time,
% delta: average quarantine time,
% lambda: cure rate, and
% kappa: mortalityrate, separately
%% COUNTRY
Province = '';
% Province = 'CABA';
% Country = 'Argentina';
% Country = 'Ecuador';
% Country = 'Brazil';
Country = 'Chile';
% Country = 'Uruguay';
% Country = 'United Kingdom';
% Country = 'Spain';
% Country = 'Italy';
% Country = 'US';
% Country = 'Sweden';
% Country = 'Norway';
% Country = 'France';
% Country = 'Belgium';
% Country = 'Germany';
% Country = 'Turkey';
% Country = 'Singapore';
% Country = 'Korea, South';
% Country = 'China';
% Province = 'Hubei';
%% SIMULATION CONFIG
if strcmp( ITERATIVE, 'OFF' )
FIT_UNTIL = datetime(2020, 5, 5);
FIT_FROM = FIT_UNTIL - 14;
% % FIT_FROM = datetime(2020, 3, 1);
FORECAST_DAYS = 15; % DAYS TO FORECAST
% FORECAST_DAYS = 90; % DAYS TO FORECAST
% PEAK = 'ON'
% MODEL_EVAL = 'ON';
% FIT_FROM = datetime(2020, X, X);
% FIT_UNTIL = FIT_FROM + 14;
% FIT_UNTIL = datetime(2020, 5, 2);
% FIT_FROM = FIT_UNTIL - 24;
% FORECAST_DAYS = days (datetime(2020, 5, 1) - FIT_UNTIL );
end
% ENGLISH = 'ON'
source = 'HOPKINS';
% source = 'MINSAL';
% source_input = 'online' ;
source_input = 'offline' ;
if (~exist('MODEL_EVAL','var')), MODEL_EVAL = 'OFF'; end
%% GET DATA JH
[tableConfirmed_jh,tableDeaths_jh,tableRecovered_jh,time_jh] = get_covid_global_hopkins ( source_input, './hopkins/' );
% [tableConfirmed,tableDeaths,tableRecovered,time] = get_covid_us_hopkins ( source, './hopkins/' );
% FIND COUNTRY
[indC, indR, indD, Npop] = find_country (tableConfirmed_jh,tableRecovered_jh,tableDeaths_jh, Country, Province);
Confirmed_jh = table2array(tableConfirmed_jh(indC, 4:end));
Deaths_jh = table2array(tableDeaths_jh(indD, 4:end));
if ~isempty(tableRecovered_jh)
Recovered_jh = table2array(tableRecovered_jh(indR, 4:end));
end
%% GET DATA MINSAL
if strcmp(Country, 'Argentina')
[tableConfirmed_ar,tableDeaths_ar,tableRecovered_ar,time_ar] = get_covid_argentina( source_input, './csv/', Recovered_jh );
% FIND COUNTRY
[indC_ar, indR_ar, indD_ar, Npop_ar] = find_country (tableConfirmed_ar,tableRecovered_ar,tableDeaths_ar, Country, Province);
compare_hopkins_minsal(tableConfirmed_jh,tableRecovered_jh,tableDeaths_jh, time_jh, tableConfirmed_ar,tableRecovered_ar,tableDeaths_ar, time_ar)
Confirmed_ar = table2array(tableConfirmed_ar(indC_ar, 4:end));
Deaths_ar = table2array(tableDeaths_ar(indD_ar, 4:end));
if ~isempty(tableRecovered_jh)
Recovered_ar = table2array(tableRecovered_ar(indR_ar, 4:end));
end
minNum = 50;
time_ar(Confirmed_ar <= minNum)= [];
if ~isempty(tableRecovered_ar)
Recovered_ar(Confirmed_ar <= minNum)=[];
end
Deaths_ar(Confirmed_ar <= minNum)=[];
Confirmed_ar(Confirmed_ar <= minNum)=[];
end
% FIND FIRST 50 CASES
% If the number of confirmed Confirmed cases is small, it is difficult to know whether
% the quarantine has been rigorously applied or not. In addition, this
% suggests that the number of infectious is much larger than the number of
% confirmed cases
minNum = 50;
time_jh(Confirmed_jh <= minNum)= [];
if ~isempty(tableRecovered_jh)
Recovered_jh(Confirmed_jh <= minNum)=[];
end
Deaths_jh(Confirmed_jh <= minNum)=[];
Confirmed_jh(Confirmed_jh <= minNum)=[];
%% CHOOSE DATASET
if strcmp(source, 'HOPKINS')
Confirmed = Confirmed_jh;
Recovered = Recovered_jh;
Deaths = Deaths_jh;
time = time_jh;
source_str = sprintf( 'Johns Hopkins CSSE');
elseif strcmp(source, 'MINSAL')
Confirmed = Confirmed_ar;
Recovered = Recovered_ar;
Deaths = Deaths_ar;
time = time_ar;
source_str = sprintf( 'Ministerio de Salud');
else
error('No data source selected!')
end
%% FITTING
tidx = datefind( FIT_FROM, time);
tfdx = datefind( FIT_UNTIL, time);
tfit = time >= FIT_FROM;
tfit = time <= FIT_UNTIL & tfit;
% Initial conditions
C0 = Confirmed(tfit);
E0 = C0(1) ; % Initial number of exposed cases. Unknown but unlikely to be zero.
I0 = C0(1) ; % Initial number of infectious cases. Unknown but unlikely to be zero.
param_fit = my_fit_SEIQRDP(Confirmed(tfit), Recovered(tfit), Deaths(tfit), Npop, E0, I0, time(tfit));
Active = Confirmed - Recovered - Deaths;
FIT_DAYS = length(time(tfit));
%% FORECAST Simulate the epidemy outbreak based on the fitted parameters
% Initial conditions
C0 = Confirmed(tfit);
E0 = C0(1) ; % Initial number of exposed cases. Unknown but unlikely to be zero.
I0 = C0(1) ; % Initial number of infectious cases. Unknown but unlikely to be zero.
R0 = Recovered(tfit);
D0 = Deaths(tfit);
R0 = R0(1);
D0 = D0(1);
Q0 = C0(1)- R0 - D0;
dt = 1/24; % time step, 1 hour
time_adj = time(tfit);
time_sim = datetime( time_adj(1) ): dt : datetime( time_adj(end) + FORECAST_DAYS );
[S1,E1,I1,Q1,R1,D1,P1] = my_SEIQRDP(param_fit, Npop, E0, I0, Q0, R0, D0, time_sim, dt);
C1 = Q1 + R1 + D1 ;
%% DOUBLING ANALYSYS
% fdx = find ( c1 <= ceil( C1(end) / 2 ), 1, 'last');
fdx = find ( Q1 >= floor( Q1(end) / 2 ), 1, 'first');
doubling_q = round( datenum ( time_sim(end)- time_sim(fdx) ) );
fdx = find ( D1 >= floor( D1(end) / 2 ), 1, 'first');
doubling_d = round( datenum ( time_sim(end)- time_sim(fdx) ) );
if isempty(doubling_q | doubling_d)
warning ('doubling is empty.')
end
%% PRINT
if strcmp( ITERATIVE, 'OFF' )
fprintf(' *** Country: %s ***\n\n', Country );
fprintf(' Fiting time series starts on %s. \n', datestr(time(1)) );
fprintf(' Fiting time series stops on %s. \n' , datestr(time(end)) );
fprintf(' Forecasting time series stops on %s. \n', datestr(time_sim(end)) );
fprintf(' Forecasting days are %d.\n', FORECAST_DAYS );
if strcmp (ENGLISH, 'ON')
model_str = sprintf( 'It is forecasted on %s:', datestr( time_sim(end), 'mmmm dd' ) );
c_fore_str = sprintf( '%d confirmed cases (%+d)', round( C1(end) ) , round( C1(end) - Confirmed(end) ) );
q_fore_str = sprintf( '%d active cases (%+d)', round( Q1(end) ) , round( Q1(end) - Active(end) ) );
r_fore_str = sprintf( '%d recoveries (%+d)', round( R1(end) ) , round( R1(end) - Recovered(end) ) );
d_fore_str = sprintf( '%d deaths (%+d)', round( D1(end) ) , round( D1(end) - Deaths(end) ) );
double_q_str = sprintf( 'Active cases are doubled in %d days', doubling_q );
double_d_str = sprintf( 'Deaths are doubled in %d days', doubling_d );
else
model_str = sprintf( 'Se proyecta para el %s:', datestr( time_sim(end), 'dd/mm/yy' ) );
c_fore_str = sprintf( '%d casos confirmados (%+d)', round( C1(end) ) , round( C1(end) - Confirmed(end) ) );
q_fore_str = sprintf( '%d casos activos (%+d)', round( Q1(end) ) , round( Q1(end) - Active(end) ) );
r_fore_str = sprintf( '%d recuperados (%+d)', round( R1(end) ) , round( R1(end) - Recovered(end) ) );
d_fore_str = sprintf( '%d fallecidos (%+d)', round( D1(end) ) , round( D1(end) - Deaths(end) ) );
double_q_str = sprintf( 'Activos se duplican cada %d días', doubling_q );
double_d_str = sprintf( 'Fallecidos se duplican cada %d días', doubling_d );
end
i_fore_str = sprintf( '%d potential active cases', round( Q1(end) + I1(end) ) );
Q_fore_str = sprintf( 'Models predicts %d active cases on %s', round( ( Q1(end)) ), datestr( time_sim(end) ) );
N_fore_str = sprintf( 'Models predicts new %d active cases on %s', round( ( Q1(end) ) - Active(end) ), datestr( time_sim(end) ) );
I_fore_str = sprintf( 'Models predicts %d infected on %s', round( I1(end) ), datestr( time_sim(end) ) );
% ro_str = sprintf( 'Ro: %.2f', BRN );
alpha_str = sprintf( 'alpha : %.2f', param_fit.alpha );
beta_str = sprintf( 'beta: %.2f', param_fit.beta );
gamma_str = sprintf( 'gamma^-1: %.1f days', 1/param_fit.gamma);
delta_str = sprintf( 'delta^-1: %.1f days', 1/param_fit.delta);
lambda_str = sprintf( 'Recovery rate: [%f %f]', param_fit.lambda(1), param_fit.lambda(2) );
kappa_str = sprintf( 'Death rate: [%f %f]', param_fit.kappa(1), param_fit.kappa(2) );
fprintf( '\n %s \n', Q_fore_str );
fprintf( ' %s \n', I_fore_str );
fprintf( ' %s \n', N_fore_str );
% fprintf( ' %s \n', ro_str );
fprintf( ' %s \n', alpha_str );
fprintf( ' %s \n', beta_str );
fprintf( ' %s \n', gamma_str );
fprintf( ' %s \n', delta_str );
fprintf( ' %s \n', lambda_str );
fprintf( ' %s \n', kappa_str );
fprintf( ' %s \n', double_q_str );
fprintf( ' %s \n', double_d_str );
end
%% PLOT
%--------------------------------------------------------------------------
% COLORS
%--------------------------------------------------------------------------
blue = [0, 0.4470, 0.7410];
orange = [0.8500, 0.3250, 0.0980];
yellow = [0.9290, 0.6940, 0.1250] ;
purple = [0.4940, 0.1840, 0.5560];
green = [0.4660, 0.6740, 0.1880];
blue_light = [0.3010, 0.7450, 0.9330] ;
gray = ones(1,3) * 0.5;
red_dark = [0.6350, 0.0780, 0.1840] ;
red = [1 0 0];
%--------------------------------------------------------------------------
% FONT SIZE, LINE WIDTH, POINT WIDTH
%--------------------------------------------------------------------------
font_title = 23;
font_label = 20;
font_tick = 17;
font_legend = 15;
font_point = 13;
line_width = 2.5;
line_width_pt= 2;
mks = 9;
%--------------------------------------------------------------------------
% VECTOR INDEX FOR FIGURE
%--------------------------------------------------------------------------
fodx = time_sim > FIT_UNTIL;
fopx = contains( cellstr( datestr( time_sim ) ), '00:00:00') & fodx';
fidx = time_sim <= FIT_UNTIL;
time_fore_pt = time_sim (fopx);
c_fore_pt = C1 (fopx);
q_fore_pt = Q1 (fopx);
r_fore_pt = R1 (fopx);
d_fore_pt = D1 (fopx);
if strcmp( ITERATIVE, 'OFF' )
%--------------------------------------------------------------------------
figure
%--------------------------------------------------------------------------
% FITING, LINES
%--------------------------------------------------------------------------
% c1 = semilogy(time_sim (fidx), C1 (fidx), 'color', green, 'LineWidth', line_width);
q1 = semilogy(time_sim (fidx), Q1 (fidx), 'color', red_dark, 'LineWidth', line_width);
hold on
r1 = semilogy(time_sim (fidx), R1 (fidx), 'color', blue, 'LineWidth', line_width);
d1 = semilogy(time_sim (fidx), D1 (fidx), 'k', 'LineWidth', line_width);
%--------------------------------------------------------------------------
% PEAK LINE
%--------------------------------------------------------------------------
if strcmp (PEAK, 'ON')
qdx = find (Q1 == max(Q1));
adx = find (Active == max(Active));
if max(Q1) > max(Active )
peak_max = max(Q1);
peak_time = time_sim (qdx);
else
peak_max = max(Active);
peak_time = time (adx);
end
line([peak_time peak_time], [1 peak_max], 'color', red, 'linewidth', line_width, 'LineStyle', '--');
semilogy(peak_time, peak_max, 'color', red, 'Marker','d', 'LineStyle', 'none', 'LineWidth', line_width_pt,'MarkerSize', mks+3);
if strcmp (ENGLISH, 'OFF')
peak_str = sprintf( 'Pico el %s con %s casos activos', datestr( peak_time, 'dd/mm' ), num2sip(round( peak_max ) , 3) ) ;
else
peak_str = sprintf( 'Peak with %s active cases on %s', num2sip(round( peak_max ) , 3), datestr( peak_time, 'mmmm dd' ) ) ;
end
fprintf(' %s \n', peak_str )
end
%--------------------------------------------------------------------------
%--------------------------------------------------------------------------
% FORECASTING, POINTS
%--------------------------------------------------------------------------
% cp = semilogy(time_sim (fopx), C1(fopx), 'color', green, 'Marker','x', 'LineStyle', 'none', 'LineWidth', line_width_pt,'MarkerSize', mks);
qp = semilogy(time_sim (fopx), Q1(fopx), 'color', red_dark, 'Marker','x', 'LineStyle', 'none', 'LineWidth', line_width_pt,'MarkerSize', mks);
rp = semilogy(time_sim (fopx), R1(fopx), 'color', blue, 'Marker','x', 'LineStyle', 'none', 'LineWidth', line_width_pt,'MarkerSize', mks);
dp = semilogy(time_sim (fopx), D1(fopx), 'color', 'black', 'Marker','x', 'LineStyle', 'none', 'LineWidth', line_width_pt,'MarkerSize', mks);
% cr = semilogy(time, Confirmed, 'color', green, 'Marker', 'o', 'LineStyle', 'none', 'LineWidth', line_width_pt, 'MarkerSize', mks);
qr = semilogy(time, Active, 'color', red_dark, 'Marker', 'o', 'LineStyle', 'none', 'LineWidth', line_width_pt, 'MarkerSize', mks);
rr = semilogy(time, Recovered, 'color', blue, 'Marker', 'o', 'LineStyle', 'none', 'LineWidth', line_width_pt, 'MarkerSize', mks);
dr = semilogy(time, Deaths, 'color', 'black', 'Marker', 'o', 'LineStyle', 'none', 'LineWidth', line_width_pt, 'MarkerSize', mks);
grid on
%--------------------------------------------------------------------------
%--------------------------------------------------------------------------
% AXES PROPIETIES
%--------------------------------------------------------------------------
if strcmp (ENGLISH, 'ON')
yl = ylabel('Number of cases');
xl = xlabel('Time (days)');
else
yl = ylabel('Número de casos');
xl = xlabel('Tiempo (días)');
end
set(gcf,'color','w')
% set(gca,'yscale','lin')
set(gca,'yscale','log')
xlim([ time(1) time_sim(end) ])
if max(R1) > max(Q1)
ylim([ 1 max(R1)*3 ]);
else
ylim([ 1 max(Q1)*3 ]);
end
set(gca, 'XTickMode', 'manual', 'YTickMode', 'auto', 'XTick', time(1):4:time_sim(end), 'FontSize', font_tick, 'XTickLabelRotation', 45);
%--------------------------------------------------------------------------
%--------------------------------------------------------------------------
% TITLE
%--------------------------------------------------------------------------
if (strcmp(Province, ''))
country_str = Country;
else
country_str = [Province,' (',Country,')'];
end
if strcmp (ENGLISH, 'ON')
date_str = datestr(time(tfdx), 'mmmm dd');
if strcmp (MODEL_EVAL, 'OFF')
title_type = 'GeSEIR model for COVID-19 forecasting';
else
title_type = 'GeSEIR model for COVID-19 evaluation';
end
sub_title_srt = ['\fontsize{20}\color{gray}\rm Source: ', source_str, '.'];
switch (country_str)
case 'Korea, South', country_str = 'South Korea'; Country = 'South Korea';
end
title_srt = sprintf('%s, %s.\nFitted with %d days, forecasted %d days from %s.', ...
country_str, title_type, FIT_DAYS, FORECAST_DAYS, date_str );
else
date_str = datestr(time(tfdx), 'dd/mm/yy');
switch (country_str)
case 'Spain', country_str = 'España';
case 'Italy', country_str = 'Italia';
case 'US', country_str = 'EE.UU.';
case 'Korea, South', country_str = 'Corea del Sur'; Country = 'South Korea';
end
if strcmp (MODEL_EVAL, 'OFF')
title_type = 'Modelo GeSEIR para la predicción de COVID-19';
else
title_type = 'Evaluación del modelo GeSEIR para la predicción de COVID-19';
end
sub_title_srt = ['\fontsize{20}\color{gray}\rm Fuente: ', source_str, '.'];
title_srt = sprintf('%s, %s.\nAjuste con %d días, proyección de %d días desde %s.', ...
country_str, title_type, FIT_DAYS, FORECAST_DAYS, date_str );
end
tl = title( { title_srt ; sub_title_srt } );
%--------------------------------------------------------------------------
%--------------------------------------------------------------------------
% Points with value labels
%--------------------------------------------------------------------------
if FORECAST_DAYS < 30
P = 5;
else
P = 7;
end
hght = 1.75;
delay = 0; % -1/2
if strcmp (MODEL_EVAL, 'OFF')
for i = 1 : P : size(Active, 2)
text( time(i)+delay , Active(i)*hght , sprintf('%s', num2sip( Active(i) , 3)), 'FontSize', font_point, 'color', red_dark ) ;
end
for i = 1 : P : size(Recovered, 2)
text( time(i)+delay, Recovered(i)/hght , sprintf('%s', num2sip(Recovered(i) , 3)), 'FontSize', font_point, 'color', blue );
end
for i = 1 : P : size(Deaths, 2)
text( time(i)+delay, Deaths(i)/hght , sprintf('%s', num2sip(Deaths(i) , 3)), 'FontSize', font_point, 'color', 'black' );
end
S = P;
for i = S : P : size(time_fore_pt, 2)
text( time_fore_pt(i)+delay, q_fore_pt(i)*hght , sprintf('%s', num2sip(round( q_fore_pt(i)) , 3)), 'FontSize', font_point, 'Color', red_dark);
end
for i = S : P : size(time_fore_pt, 2)
text(time_fore_pt(i)+delay, r_fore_pt(i)/hght , sprintf('%s', num2sip(round( r_fore_pt(i)) , 3)), 'FontSize', font_point, 'Color', blue);
end
for i = S : P : size(time_fore_pt, 2)
text(time_fore_pt(i)+delay, d_fore_pt(i)/hght , sprintf('%s', num2sip(round( d_fore_pt(i)) , 3)), 'FontSize', font_point, 'Color', 'black');
end
% Print last vector element
text( time_fore_pt(end)+delay, q_fore_pt(end)*hght , sprintf('%s', num2sip(round( q_fore_pt(end)) , 3)), 'FontSize', font_point, 'Color', red_dark);
text( time_fore_pt(end)+delay, r_fore_pt(end)/hght , sprintf('%s', num2sip(round( r_fore_pt(end)) , 3)), 'FontSize', font_point, 'Color', blue);
text( time_fore_pt(end)+delay, d_fore_pt(end)/hght , sprintf('%s', num2sip(round( d_fore_pt(end)) , 3)), 'FontSize', font_point, 'Color', 'black');
else
%--------------------------------------------------------------------------
% Points with errors percent labels
%--------------------------------------------------------------------------
P = 2;
for i = 1 : P : size(q_fore_pt, 2)
if ( tfdx+i <= size (Active, 2))
error = (round(q_fore_pt(i)) - Active(tfdx+i)) / Active(tfdx+i) * 100;
text( time_fore_pt(i)+delay, q_fore_pt(i)*hght , sprintf('%.0f%%', error) , 'FontSize', font_point, 'color', red_dark ) ;
end
end
for i = 1 : P : size(r_fore_pt, 2)
if ( tfdx+i <= size (Recovered, 2))
error = (round(r_fore_pt(i)) - Recovered(tfdx+i)) / Recovered(tfdx+i) * 100;
text( time_fore_pt(i)+delay, r_fore_pt(i)/hght , sprintf('%.0f%%', error) , 'FontSize', font_point, 'color', blue );
end
end
for i = 1 : P : size(d_fore_pt, 2)
if ( tfdx+i <= size (Deaths, 2))
error = (round(d_fore_pt(i)) - Deaths(tfdx+i)) / Deaths(tfdx+i) * 100;
text( time_fore_pt(i)+delay, d_fore_pt(i)/hght , sprintf('%.0f%%', error) , 'FontSize', font_point, 'color', 'black' );
end
end
end
%--------------------------------------------------------------------------
%--------------------------------------------------------------------------
% LEGEND
%--------------------------------------------------------------------------
if strcmp (ENGLISH, 'ON')
leg = {
'Active (fitted)', ...
'Recoveries (fitted)',...
'Deaths (fitted)',...
'Active (reported)', ...
'Recoveries (reported)',...
'Deaths (reported)'};
else
leg = {
'Activos (ajustado)', ...
'Recuperados (ajustado)',...
'Fallecidos (ajustado)',...
'Activos (reportados)', ...
'Recuperados (reportados)',...
'Fallecidos (reportados)'};
end
ll = legend( [q1, r1, d1, qr, rr, dr], leg{:}, 'Location','SouthEast' ); % NorthWest
set(ll,'color','none');
%--------------------------------------------------------------------------
%--------------------------------------------------------------------------
% TEXT BOX
%--------------------------------------------------------------------------
if strcmp (PEAK, 'OFF')
text_box = sprintf('%s\n * %s.\n * %s.\n * %s.\n * %s.\n * %s.', model_str, ...
q_fore_str, r_fore_str, d_fore_str, double_q_str, double_d_str);
else
text_box = sprintf('%s\n * %s.\n * %s.\n * %s.\n * %s.', model_str, ...
q_fore_str, r_fore_str, d_fore_str, peak_str);
end
al = annotation('textbox', [0.42, 0.26, 0.1, 0.1], 'string', text_box, ...
'LineStyle','-',...
'FontSize', font_legend,...
'FontName','Arial', ...
'FaceAlpha', 0.5, ...
'BackgroundColor', 'white');
% 'FontWeight','bold',...
%--------------------------------------------------------------------------
% SIGNATURE
%--------------------------------------------------------------------------
% Create textbox
annotation('textbox', [0.14 0.79 0.35 0.05],...
'Color', ones(1,3) * 0.50 ,...
'String',{'Rodrigo Gonzalez (Twitter @RGonzalez\_PhD)'},...
'LineStyle','none',...
'FontSize', font_legend ,...
'FontName','Arial', ...
'FaceAlpha', 0.5, ...
'BackgroundColor', 'white');
%--------------------------------------------------------------------------
%--------------------------------------------------------------------------
% WATERMARK
%--------------------------------------------------------------------------
for i=1:3
x = 0.14 + i*0.15;
y = 0.79 - i*0.145;
annotation('textbox', [x y 0.35 0.05],...
'Color', ones(1,3) * 0.875 , ...
'String',{'Rodrigo Gonzalez (Twitter @RGonzalez\_PhD)'},...
'LineStyle','none',...
'FontSize', font_legend ,...
'FontName','Arial', ...
'FaceAlpha', 0.05, ...
'BackgroundColor', 'white');
end
%--------------------------------------------------------------------------
set(tl,'FontSize', font_title, 'FontName','Arial');
set(xl,'FontSize', font_label, 'FontName','Arial');
set(yl,'FontSize', font_label, 'FontName','Arial');
set(ll,'FontSize', font_legend, 'FontName','Arial');
set(al,'FontSize', font_legend, 'FontName','Arial');
hold off
%% SAVE FIGURE TO PNG FILE
Country = regexprep(Country, ' ', '_');
date_str = datestr( FIT_UNTIL , 'yyyy-mm-dd');
if strcmp (MODEL_EVAL, 'OFF')
file_name = sprintf('%s_covid-19_forecast_%s', Country, date_str );
else
file_name = sprintf('%s_covid-19_eval_%s', Country, date_str );
end
if strcmp (PEAK, 'ON')
file_name = [file_name,'_peak'];
end
file_str = sprintf('./png/%s.png', file_name );
set(gcf, 'Units', 'Normalized', 'OuterPosition', [0 0 1 1]);
saveas(gcf,file_str)
%% INFECTED FIGURE
%% PLOT INFECTED AND EXPOSED
% figure
%
% q1 = semilogy(time_sim (fidx), I1 (fidx), 'color', red_dark, 'LineWidth', line_width);
% hold on
% r1 = semilogy(time_sim (fidx), E1 (fidx), 'color', blue, 'LineWidth', line_width);
%
% grid on
%
% legend('INFECTED', 'EXPOSED')
%
% hold off
%% SAVE DATA TO CSV FILE
%--------------------------------------------------------------------------
% FITTING AND FORECASTING
%--------------------------------------------------------------------------
% lambda_str = sprintf( 'Recovery rate: [%f %f]', param_fit.lambda(1), param_fit.lambda(2) );
% kappa_str = sprintf( 'Death rate: [%f %f]', param_fit.kappa(1), param_fit.kappa(2) );
t = 0:size(time_sim, 2);
lambda = param_fit.lambda(1) * (1-exp(- param_fit.lambda(2) .* t));
kappa = param_fit.kappa(1) * exp(- param_fit.kappa(1) .* t);
file_str = sprintf('./csv/%s.csv', file_name );
fid = fopen(file_str, 'w');
fprintf(fid, '%s, %s, %s, %s, %s, %s, %s,\n', 'Date', 'Active', 'Recoveries', 'Deaths', 'Active+Infected', 'lambda', 'kappa') ; % Print the time string
for idx = 1:size(time_sim, 2) % Loop through each time/value row size(qq, 1)
fprintf(fid, '%s,', datestr ( time_sim(:, idx) , 31 ) ) ; % date
fprintf(fid, '%12.5f,', Q1(idx) ) ; %
fprintf(fid, '%12.5f,', R1(idx) ) ; %
fprintf(fid, '%12.5f,', D1(idx) ) ; %
fprintf(fid, '%12.5f,', Q1(idx)+I1(idx) ) ; %
fprintf(fid, '%12.5f,', lambda(idx) ) ; %
fprintf(fid, '%12.5f,', kappa(idx) ) ; %
fprintf(fid, '\n' ) ; % active
end
fclose(fid) ;
%--------------------------------------------------------------------------
% FITTING AND FORECASTING, LASTEST
%--------------------------------------------------------------------------
if strcmp (MODEL_EVAL, 'OFF')
cp_command = sprintf('cp %s ./csv/%s_covid-19_forecast_lastest.csv', file_str, Country );
ret = system(cp_command);
if ret ~= 0
error('cp error!');
end
end
%--------------------------------------------------------------------------
% REPORTED
%--------------------------------------------------------------------------
if strcmp (MODEL_EVAL, 'OFF')
file_name = sprintf('%s_covid-19_reported_%s', Country, date_str );
else
file_name = sprintf('%s_covid-19_reported_eval_%s', Country, date_str );
end
file_str = sprintf('./csv/%s.csv', file_name);
fid = fopen(file_str, 'w');
fprintf(fid, '%s, %s, %s, %s,\n', 'Date', 'Active', 'Recoveries', 'Deaths') ; % Print the time string
for idx = 1:size(time, 2) % Loop through each time/value row size(qq, 1)
fprintf(fid, '%s,', datestr ( time(1, idx) , 31 ) ) ; % date
fprintf(fid, '%12.5f,', Active(idx) ) ; % active
fprintf(fid, '%12.5f,', Recovered(idx) ) ; % active
fprintf(fid, '%12.5f,', Deaths(idx) ) ; % active
fprintf(fid, '\n' ) ; % active
end
%--------------------------------------------------------------------------
% REPORTED, LASTEST
%--------------------------------------------------------------------------
if strcmp (MODEL_EVAL, 'OFF')
cp_command = sprintf('cp %s ./csv/%s_covid-19_reported_lastest.csv', file_str, Country );
ret = system(cp_command);
if ret ~= 0
error('cp error!');
end
end
end