cbbad60b-89e5-4578-9130-b1e9bca5acae
isee systems, inc.
0
365
16
people/person/day
EUR/(person-year)
USD/jobs
USD/(worker-mo)
jobs/(worker-mo)
mo/yr
SIR
Economy
Economical Impact
0
Policy Interventions
Life and Death
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
government_support_to_mitigate_daily_economic_impact
Pound Sterling
IF TIME < 90 THEN 0
ELSE
daily_lost_income
*"%_covered_by_government_support"
Pound Sterling/day
"%_normal_FTE"
*Base_Full_Time_Equivalent_employment
unitless
140
Pound Sterling/day/people
= total workforce
33e6
unitless
<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.0//EN" "http://www.w3.org/TR/REC-html40/strict.dtd">
<html><head><meta name="qrichtext" content="1" /><style type="text/css">
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(Base_Full_Time_Equivalent_employment
-Full_Time_Equivalent_employment)
people
<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.0//EN" "http://www.w3.org/TR/REC-html40/strict.dtd">
<html><head><meta name="qrichtext" content="1" /><style type="text/css">
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<p style=" margin-top:0px; margin-bottom:0px; margin-left:0px; margin-right:0px; -qt-block-indent:0; text-indent:0px;"><span style=" font-family:'Arial'; font-size:12pt; color:#000000;">decreased number of hours by 17% to 877 million hours</span></p>
<p style=" margin-top:0px; margin-bottom:0px; margin-left:0px; margin-right:0px; -qt-block-indent:0; text-indent:0px;"><span style=" font-family:'Arial'; font-size:12pt; color:#000000;">over 3 months</span></p>
<p style="-qt-paragraph-type:empty; margin-top:0px; margin-bottom:0px; margin-left:0px; margin-right:0px; -qt-block-indent:0; text-indent:0px; font-family:'Arial'; font-size:12pt; color:#000000;"><br /></p>
<p style="-qt-paragraph-type:empty; margin-top:0px; margin-bottom:0px; margin-left:0px; margin-right:0px; -qt-block-indent:0; text-indent:0px; font-family:'Arial'; font-size:12pt; color:#000000;"><br /></p></body></html>
1-
(0.25*
(1-"Hygiene_&_social_distancing_effect_v(t)")
)
unitless
2.0
unitless
0
incurring_debt
pounds sterling
government_support_to_mitigate_daily_economic_impact
Pound Sterling/day
extra_unemployment
*average_daily_income
Pound Sterling/day
60/100
unitless
0
daily_lost_spending_power
pounds sterling
(1-"%_covered_by_government_support")
*daily_lost_income
*"knock-on_effect"
Pound Sterling/day
TIME
0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0
unitless
Government_debt + Lost_Spending_Power
Pound Sterling
Total_Economic_Impact-(247e9-294e6+887e3-1.8e6+25.5e3)
Pound Sterling
Full_Time_Equivalent_employment
extra_unemployment
average_daily_income
daily_lost_income
Base_Full_Time_Equivalent_employment
extra_unemployment
extra_unemployment
daily_lost_income
"%_normal_FTE"
Full_Time_Equivalent_employment
Base_Full_Time_Equivalent_employment
Full_Time_Equivalent_employment
government_support_to_mitigate_daily_economic_impact
incurring_debt
daily_lost_income
government_support_to_mitigate_daily_economic_impact
"%_covered_by_government_support"
government_support_to_mitigate_daily_economic_impact
daily_lost_income
daily_lost_spending_power
"%_covered_by_government_support"
daily_lost_spending_power
"knock-on_effect"
daily_lost_spending_power
"Hygiene_&_social_distancing_effect_v(t)"
"%_normal_FTE"
Total_Economic_Impact
Change_in_Economic_Impact
"initial_susceptible_population_(is)"
immunity_loss
"infection_rate_(ir)"
People
0
"infection_rate_(ir)"
new_cases_arrival
incubation_rate
iau_recovering
iau_screening
People
0
incubation_rate
isu_testing
isu_dying
isu_recovering
isu_worsening
People
0
isu_testing
iau_screening
ID_disease_progression_rate
id_dying
ID_recovering
People
0
ID_disease_progression_rate
isuh_testing
h_dying
h_worsening
h_recovering
People
0
h_worsening
admission_directly_to_C
recovering
c_dying
People
0
recovering
ID_recovering
h_recovering
isu_recovering
iau_recovering
immnity_gain
People
0
immnity_gain
immunity_loss
People
"contact_rate_(cr)"
*infectivity
*"Susceptible_(S)"
*fraction_of_population_infectious
*"Hygiene_&_social_distancing_effect_v(t)"
people/day
"fraction_developing_symptoms_(fs)"[Age]
*"Infectious_Asymptomatic_Undiagnosed_(IAU)"
/time_for_iau_to_develop_symptoms
people/day
<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.0//EN" "http://www.w3.org/TR/REC-html40/strict.dtd">
<html><head><meta name="qrichtext" content="1" /><style type="text/css">
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</style></head><body style=" font-family:'.AppleSystemUIFont'; font-size:13pt; font-weight:400; font-style:normal;">
<p style=" margin-top:0px; margin-bottom:0px; margin-left:0px; margin-right:0px; -qt-block-indent:0; text-indent:0px;"><span style=" font-family:'Arial'; font-size:12pt; color:#000000;">https://www.iseesystems.com/store/products/publishing-options.aspx</span></p>
<p style="-qt-paragraph-type:empty; margin-top:0px; margin-bottom:0px; margin-left:0px; margin-right:0px; -qt-block-indent:0; text-indent:0px; font-family:'Arial'; font-size:12pt; color:#000000;"><br /></p></body></html>
MIN(normal_ISU_testing, testing_capcity)
people/day
MIN(testing_capcity, normal_IAU_testing)
people/day
(1-"fr._ID_to_c")
*fraction_id_becoming_serious
*"Infectious_Diagnosed_(ID)"
/time_for_id_to_get_serious
people/day
0
isu_dying
id_dying
h_dying
c_dying
People
global_death_multiplier
*fraction_isu_dying
*"Infectious_Symptomatic_Undiagnosed_(ISU)"
/time_for_isu_to_die
people/day
global_death_multiplier
*fraction_id_dying
*"Infectious_Diagnosed_(ID)"
/time_for_id_to_die
people/day
global_death_multiplier
*fraction_h_dying
*"Severe_&_hospitalized_(H)"
/time_for_h_to_die
people/day
"fraction_to_become_critical(fc)"
*"Severe_&_hospitalized_(H)"
/time_for_h_to_worsen
people/day
fraction_critical_to_recover
*"Critical_(C)"
/time_for_c_to_recover
people/day
fraction_id_recovering
*"Infectious_Diagnosed_(ID)"
/time_for_id_to_recover
people/day
fraction_h_recovering
*"Severe_&_hospitalized_(H)"
/time_for_h_to_recover
people/day
fraction_isu_recovering
*"Infectious_Symptomatic_Undiagnosed_(ISU)"
/time_for_isu_to_recover
people/day
fraction_iau_recovering
*"Infectious_Asymptomatic_Undiagnosed_(IAU)"
/time_for_iau_to_recover
people/day
"Recovered_(R)"
/time_to_test_for_immunity
people/day
COVID19-KS_4.stmx model
temporary_immunity
*"Immune_(I)"
/time_to_lose_immunity
people/day
"base_infectivity_(p)"
*infectivity_multiplier
unitless
<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.0//EN" "http://www.w3.org/TR/REC-html40/strict.dtd">
<html><head><meta name="qrichtext" content="1" /><style type="text/css">
p, li { white-space: pre-wrap; }
</style></head><body style=" font-family:'.AppleSystemUIFont'; font-size:13pt; font-weight:400; font-style:normal;">
<p style=" margin-top:12px; margin-bottom:12px; margin-left:0px; margin-right:0px; -qt-block-indent:0; text-indent:0px;"><span style=" font-family:'Calibri'; font-size:11pt;">Base infectivity, 0.015, </span><span style=" font-family:'.SF NS Text';">Table 1, p.9 </span></p>
<p style=" margin-top:12px; margin-bottom:12px; margin-left:0px; margin-right:0px; -qt-block-indent:0; text-indent:0px;"><span style=" font-family:'.SF NS Text';">Venkateswaran, J., & Damani, O. (2020). Effectiveness of Testing, Tracing, Social Distancing and Hygiene in Tackling Covid-19 in India: A System Dynamics Model. </span><span style=" font-family:'.SF NS Text'; font-style:italic;">ArXiv:2004.08859 [q-Bio]</span><span style=" font-family:'.SF NS Text';">. </span><a href="http://arxiv.org/abs/2004.08859"><span style=" font-family:'.SF NS Text'; text-decoration: underline; color:#0000ff;">http://arxiv.org/abs/2004.08859</span></a><span style=" font-family:'.SF NS Text';"> </span></p>
<p style="-qt-paragraph-type:empty; margin-top:12px; margin-bottom:12px; margin-left:0px; margin-right:0px; -qt-block-indent:0; text-indent:0px; font-family:'.SF NS Text';"><br /></p></body></html>
0.015
unitless
SUM("Infectious_Asymptomatic_Undiagnosed_(IAU)"[*, *]) + SUM("Infectious_Symptomatic_Undiagnosed_(ISU)"[*, *])
People
"stratified_population_(SN)"
-initial_infectious_population
-"Immune_(I)"
people
67886011
People
0.059
.062
0.058
0.055
.063
0.068
0.067
0.066
0.060
0.068
0.070
0.065
0.055
0.051
0.049
0.034
0.025
0.015
0.009
unitless
"population_fraction_by_age_and_region_(g)"
*"Total_Initial_Population_(N)"
people
10
people
Fraction developing symptoms, 0.8 , Table 1, p.9
Venkateswaran, J., & Damani, O. (2020). Effectiveness of Testing, Tracing, Social Distancing and Hygiene in Tackling Covid-19 in India: A System Dynamics Model. ArXiv:2004.08859 [q-Bio]. http://arxiv.org/abs/2004.08859
age_multiplier*"base_fraction_developing_symptoms_(fs)"
unitless
Avg. time to develop symptoms, 2 days, Table 1, p.9
Venkateswaran, J., & Damani, O. (2020). Effectiveness of Testing, Tracing, Social Distancing and Hygiene in Tackling Covid-19 in India: A System Dynamics Model. ArXiv:2004.08859 [q-Bio]. http://arxiv.org/abs/2004.08859
9
Days
effect_of_age_on_contact_rate[Age]*"base_contact_rate(bcr)"[Age]
*fraction_exposed
*age_specific_exposure_profile
1/Day
Avg. time for asymptomatics to recover, 11 days, Table 1, p.9
Venkateswaran, J., & Damani, O. (2020)
11
days
SUM("Susceptible_(S)"[*, *])
people
SUM("Recovered_(R)"[*, *])
people
SUM("Death(D)"[*, *])
people
100*Total_Deaths/"Total_Initial_Population_(N)"
dimensionless
SUM("Immune_(I)"[*, *])
People
Base_Reproduction_Rate_R0*Total_Susceptible/"Total_Initial_Population_(N)"
unitless
"contact_rate_(cr)"
*infectivity
*Average_Duration_of_Illness_d
unitless
The average length of time that a person is infectious.
Day
7
day
Fraction developing symptoms, Table 1, p.9
Venkateswaran, J., & Damani, O. (2020). Effectiveness of Testing, Tracing, Social Distancing and Hygiene in Tackling Covid-19 in India: A System Dynamics Model. ArXiv:2004.08859 [q-Bio]. http://arxiv.org/abs/2004.08859
0.025
unitless
5.6
Days
Avg. time for infectious Symptomatics to recover, 14 days , table 1, p.9
Venkateswaran, J., & Damani, O. (2020)
14
Days
fraction dying, , Table 1, p.9
Venkateswaran, J., & Damani, O. (2020)
0.15
0.2
0.25
0.3
0.35
0.4
0.45
0.5
0.55
0.65
0.7
0.75
0.8
0.85
0.9
0.9
0.9
0.9
0.9
unitless
sum of days to get worse ( 5 days) and time from critical to die (5 days)
Table 1, p.9
Venkateswaran, J., & Damani, O. (2020)
5
day
Avg. time for infectious hospitalized to recover, 14 days , table 1, p.9
Venkateswaran, J., & Damani, O. (2020)
14
Days
fraction to ecobming critical, Table 1, p.9
Venkateswaran, J., & Damani, O. (2020)
0
0
0
0
0
0
0.14
0.14
0.14
0.14
0.23
0.24
0.24
0.28
0.32
0.38
0.45
0.5
0.6
unitless
Avg. time for infectious worsening, 5 days , table 1, p.9
Venkateswaran, J., & Damani, O. (2020)
7
Days
Avg. time for critical to recover, 14 days , table 1, p.9
Venkateswaran, J., & Damani, O. (2020)
7
Days
h_recovery_multiplier
*base_fraction_h_recovering
unitless
14
Days
global_death_multiplier
*fraction_c_dying
*"Critical_(C)"
/time_for_c_to_die
people/day
Avg. time for critical to die, 14 days , table 1, p.9
Venkateswaran, J., & Damani, O. (2020)
3
Days
c_recovery_multiplier
*base_fraction_h_recovering
unitless
500
days
Total_Critical + Total_Immune + Total_Infected_undiagnosed + Total_Infectious_Diagnosed + Total_Recovered + Total_Hospitalized_not_critical + Total_Susceptible
People
One infectious individual arrives every 50 days.
People
1
People/day
SUM(Reproduction_Rate_R[*, *])
unitless
1
unitless
compared to ventilator beds in the Uk
SUM("Critical_(C)"[*, *])
People
SUM("ISU_hospitalized_(ISUH)"[*, *]) + SUM("Severe_&_hospitalized_(H)"[*,*])
People
SUM("Infectious_Asymptomatic_Undiagnosed_(IAU)"[*, *])
People
SUM("Infectious_Symptomatic_Undiagnosed_(ISU)"[*, *])
People
SUM("Infectious_Diagnosed_(ID)"[*, *])
People
0
infecting
People
total_infection_rate
people/day
SUM("infection_rate_(ir)"[*, *])
People/day
The values reflect susceptibility only
1
1
1
1
1
1
1
1
1
1
1
1
1.5
2
2.5
3
3.5
4
4.5
unitless
1.5
1/Day
SUM("stratified_population_(SN)"[*, *])
people
SUM("Death(D)"[a_80_to_84:a_90_plus, *])
People
Total_Immune/Total_Population
unitless
0
diagnosing
People
total_iau_screening
+total_isu_testing
+total_isuh_testing
people/day
IF Confirmed_Cases=0 THEN 0
ELSE (Total_Deaths/Confirmed_Cases)*100
unitless
Total_Infected_undiagnosed/"stratified_population_(SN)"
unitless
SUM(new_cases_arrival[*, *])
people/day
STEP(initial_cases,1)-STEP(initial_cases,10)
people/day
MIN((daily_cases_approx/age_group_factor)
, (daily_confirmed_cases_data/age_group_factor))\
testing capacity as defined in the model is a substitute for the number confirmed cases per day resulting from actual test capacity. The model currently by definition considers all tested cases to be positive.
Data used to approximate this is based on daily confirmed cases not daily tested people.
In the future, we need to add testing the suscpitable population where we will need to add a % of people tested positive.
the more test capacity UK have the more IAU and Sus will be tested.
daily_cases_approx/age_group_factor
people/day
isu_recovery_multiplier
*base_fraction_h_recovering
unitless
0.012
unitless
c_death_multiplier
*base_fraction_c_dying
unitless
TIME
1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1
unitless
<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.0//EN" "http://www.w3.org/TR/REC-html40/strict.dtd">
<html><head><meta name="qrichtext" content="1" /><style type="text/css">
p, li { white-space: pre-wrap; }
</style></head><body style=" font-family:'.AppleSystemUIFont'; font-size:13pt; font-weight:400; font-style:normal;">
<p style=" margin-top:0px; margin-bottom:0px; margin-left:0px; margin-right:0px; -qt-block-indent:0; text-indent:0px;"><span style=" font-family:'Arial'; font-size:12pt; color:#000000;">data source: https://ourworldindata.org/coronavirus</span></p></body></html>
TIME
0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,2,2,3,7,7,9,10,28,43,65,81,115,158,194,250,285,359,508,694,877,1161,1455,1669,2043,2425,3095,3747,4461,5221,5865,6433,7471,8505,9608,10760,11599,12285,13029,14073,14915,15944,16879,17994,18492,19051,20223,21060,21787,22792,23635,24055,24393,25302,26097,26771,27510,28131,28446,28734,29427,30076,30615,31241,31587,31855,32065,32692,33186,33614,33998,34466,34636,34796,35341,35704,36042,36393,36675,36793,36914,37048,37460,37837,38161,38376,38489,39045,39369,39728,39904,40261,40465,40542,40597,40883,41128,41279,41481,41662,41698,41736,41969,42153,42288,42461,42589,42632,42647,42927,43081,43230,43414,43514,43550,43575,43730,43906,43995,44131,44198,44220,44236,44391,44517,44602,44650,44798,44819,44830,44968,45053
People
<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.0//EN" "http://www.w3.org/TR/REC-html40/strict.dtd">
<html><head><meta name="qrichtext" content="1" /><style type="text/css">
p, li { white-space: pre-wrap; }
</style></head><body style=" font-family:'.AppleSystemUIFont'; font-size:13pt; font-weight:400; font-style:normal;">
<p style=" margin-top:0px; margin-bottom:0px; margin-left:0px; margin-right:0px; -qt-block-indent:0; text-indent:0px;"><span style=" font-family:'Arial'; font-size:12pt; color:#000000;">data source:</span></p>
<p style=" margin-top:0px; margin-bottom:0px; margin-left:0px; margin-right:0px; -qt-block-indent:0; text-indent:0px;"><span style=" font-family:'Arial'; font-size:12pt; color:#000000;">https://ourworldindata.org/coronavirus</span></p></body></html>
TIME
0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,2,2,2,2,2,2,3,3,3,4,8,8,9,9,9,9,9,9,9,9,9,9,9,13,13,13,13,16,20,23,36,39,51,89,118,167,210,277,323,373,460,594,802,1144,1395,1547,1954,2630,3277,3983,5018,5018,5687,6654,8081,9533,11662,14547,17093,19526,22145,25154,29478,33722,38172,41907,47810,51612,55246,60737,65081,70276,78995,84283,88625,93877,98480,103097,108696,114221,120071,124747,129048,133499,138082,143468,148381,152844,157153,161149,165225,171257,177458,182264,186603,190588,194994,201205,206719,211368,215264,219187,223064,226467,229709,233155,236715,240165,243699,246410,248822,248297,250912,254199,257158,259563,261188,265231,267244,269131,271226,272830,274766,276336,277989,279860,281665,283315,284872,286198,287403,289144,290147,291413,292954,294379,295893,296861,298140,299255,300473,301819,303114,304335,305293,306214,306866,307984,309360,310250,311151,311965,312654,313483,283757,284276,284900,285416,285768,286349,286979,287621,288133,288953,289603,290133,291373,291911
People
data source: https://ourworldindata.org/coronavirus
TIME
0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0,1,4,0,2,1,18,15,22,16,34,43,36,56,35,74,149,186,183,284,294,214,374,382,670,652,714,760,644,568,1038,1034,1103,1152,839,686,744,1044,842,1029,935,1115,498,559,1172,837,727,1005,843,420,338,909,795,674,739,621,315,288,693,649,539,626,346,268,210,627,494,428,384,468,170,160,545,363,338,351,282,118,121,134,412,377,324,215,113,556,324,359,176,357,204,77,55,286,245,151,202,181,36,38,233,184,135,173,128,43,15,280,154,149,184,100,36,25,155,176,89,136,67,22,16,155,126,85,48,148,21,11,138,85
People/day
<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.0//EN" "http://www.w3.org/TR/REC-html40/strict.dtd">
<html><head><meta name="qrichtext" content="1" /><style type="text/css">
p, li { white-space: pre-wrap; }
</style></head><body style=" font-family:'.AppleSystemUIFont'; font-size:13pt; font-weight:400; font-style:normal;">
<p style=" margin-top:0px; margin-bottom:0px; margin-left:0px; margin-right:0px; -qt-block-indent:0; text-indent:0px;"><span style=" font-family:'Arial'; font-size:12pt; color:#000000;">data source: https://ourworldindata.org/coronavirus</span></p></body></html>
TIME
0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,2,0,0,0,0,0,1,0,0,1,4,0,1,0,0,0,0,0,0,0,0,0,0,4,0,0,0,3,4,3,13,3,12,38,29,49,43,67,46,50,87,134,208,342,251,152,407,676,647,706,1035,0,669,967,1427,1452,2129,2885,2546,2433,2619,3009,4324,4244,4450,3735,5903,3802,3634,5491,4344,5195,8719,5288,4342,5252,4603,4617,5599,5525,5850,4676,4301,4451,4583,5386,4913,4463,4309,3996,4076,6032,6201,4806,4339,3985,4406,6211,5514,4649,3896,3923,3877,3403,3242,3446,3560,3450,3534,2711,2412,-525,2615,3287,2959,2405,1625,4043,2013,1887,2095,1604,1936,1570,1653,1871,1805,1650,1557,1326,1205,1741,1003,1266,1541,1425,1514,968,1279,1115,1218,1346,1295,1221,958,921,652,1118,1380,890,901,814,689,829,-29726,519,624,516,352,581,630,642,512,820,650,530,1240,538
People/day
31.1+31.1/2
unitless
1
unitless
Fraction developing symptoms, 0.8 , Table 1, p.9
Venkateswaran, J., & Damani, O. (2020). Effectiveness of Testing, Tracing, Social Distancing and Hygiene in Tackling Covid-19 in India: A System Dynamics Model. ArXiv:2004.08859 [q-Bio]. http://arxiv.org/abs/2004.08859
0.0
0.01
0.03
0.05
0.08
0.11
0.15
0.2
0.25
0.3
0.35
0.38
0.4
0.4
0.4
0.4
0.4
0.4
0.4
unitless
a proxy for an EXPOSED stock
0.5
unitless
1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1
1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1
1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1
1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1
1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1
1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1
1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1
1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1
1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1
1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1
1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1
1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1
1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1
1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1
1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1
1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1
1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1
1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1
1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1
TIME
unitless
0.513
unitless
"fraction_ISU_accurately_tested_(ft)"
*"Infectious_Symptomatic_Undiagnosed_(ISU)"
/time_for_isu_testing
People/day
TIME
0,0.000411587379072635,0,0,0,0,0,280,730,2500,6000,6000,6000
people/day
Fraction developing symptoms, Table 1, p.9
Venkateswaran, J., & Damani, O. (2020). Effectiveness of Testing, Tracing, Social Distancing and Hygiene in Tackling Covid-19 in India: A System Dynamics Model. ArXiv:2004.08859 [q-Bio]. http://arxiv.org/abs/2004.08859
0.025
unitless
"Infectious_Asymptomatic_Undiagnosed_(IAU)"
*"fraction_IAU_accurately_screened_(ft)"
/time_for_iau_screening
People/day
4.6
Days
SUM(isu_testing)
People/day
SUM(iau_screening)
People/day
sum of days to get worse ( 5 days) and time from critical to die (5 days)
Table 1, p.9
Venkateswaran, J., & Damani, O. (2020)
7
day
sum of days to get worse ( 5 days) and time from critical to die (5 days)
Table 1, p.9
Venkateswaran, J., & Damani, O. (2020)
5
day
0
daily_deaths
People
total_isu_dying
+total_id_dying
+total_h_dying
+total_c_dying
people/day
SUM(isu_dying)
People/day
SUM(id_dying)
People/day
SUM(h_dying)
People/day
SUM(c_dying)
People/day
fraction dying, , Table 1, p.9
Venkateswaran, J., & Damani, O. (2020)
0
0
0
0.02
0.06
0.06
0.06
0.06
0.06
0.11
0.11
0.11
0.25
0.25
0.26
0.26
0.3
0.3
0.3
unitless
isu_death_multiplier
*base_fraction_isu_dying
unitless
fraction dying, , Table 1, p.9
Venkateswaran, J., & Damani, O. (2020)
0
0
0
0.02
0.06
0.06
0.06
0.06
0.06
0.11
0.11
0.11
0.25
0.25
0.26
0.26
0.3
0.3
0.3
unitless
id_death_multiplier
*base_fraction_id_dying
unitless
Fraction becoming serious, Table 1, p.9
Venkateswaran, J., & Damani, O. (2020)
0.02
0.02
0.02
0.02
0.17
0.17
0.17
0.17
0.17
0.28
0.28
0.27
0.27
0.4
0.4
0.47
0.47
0.47
0.47
unitless
base_fraction_id_becoming_serious
*ID_worse_multiplier
unitless
Avg. time for infectious Symptomatics to become serious/ hospitalise, Table 1, p.9
Venkateswaran, J., & Damani, O. (2020)
2
Days
fraction dying, , Table 1, p.9
Venkateswaran, J., & Damani, O. (2020)
0.002
0.002
0.002
0.002
0.06
0.06
0.06
0.06
0.06
0.1
0.12
0.15
0.25
0.3
0.5
0.6
0.7
0.7
0.7
unitless
h_death_multiplier
*base_fraction_h_dying
unitless
fraction to ecobming critical, Table 1, p.9
Venkateswaran, J., & Damani, O. (2020)
"base_fraction_to_become_critical(fc)"
*h_worsening_multiplier
unitless
Total_Critical + Total_Infectious_Diagnosed + Total_Hospitalized_not_critical
People
0
admissions
People
total_id_progression
+total_isu_worsening
+total_admissions_directly_to_C
people/day
SUM(ID_disease_progression_rate)
people/day
compared to 120,000 hospitalization in the UK (100KEngland +25% approx)
Total_Critical + Total_Hospitalized_not_critical
People
1
unitless
0.012
unitless
0.0012
unitless
0.0012
unitless
starts decline day on day 80 ( in mid of March)
to the lowest value around day 150 end of April
TIME
1,1,1,1,1,1,1,1,1,0.5,0.39,0.33,0.303,0.283,0.279,0.277,0.277,0.277,0.277,0.277,0.277,0.277,0.277,0.277,0.277
unitless
1
unitless
14
Days
iau_recovery_multiplier
*base_fraction_h_recovering
unitless
0
dc
People
daily_confirmed_cases_data
people/day
0
dh
People
daily_admissions_data
people/day
(1-"fr._isu_to_c")
*"fraction_becoming_isu_serious_(fh)"
*"Infectious_Symptomatic_Undiagnosed_(ISU)"
/time_for_isu_to_get_serious
people/day
Fraction becoming serious, Table 1, p.9
Venkateswaran, J., & Damani, O. (2020)
base_isu_fraction_becoming_serious
*isu_worse_multiplier
unitless
Avg. time for infectious Symptomatics to become serious/ hospitalise, Table 1, p.9
Venkateswaran, J., & Damani, O. (2020)
5
Days
0.182
unitless
Fraction becoming serious, Table 1, p.9
Venkateswaran, J., & Damani, O. (2020)
0.02
0.02
0.02
0.02
0.17
0.17
0.17
0.17
0.17
0.28
0.28
0.27
0.27
0.4
0.4
0.47
0.47
0.47
0.47
unitless
0
isu_worsening
isuh_testing
People
(1-"fr._isuh_to_c")
*"ISU_hospitalized_(ISUH)"
/time_for_isuh_testing
people/day
1
day
SUM(isuh_testing)
People/day
SUM(isu_worsening)
people/day
<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.0//EN" "http://www.w3.org/TR/REC-html40/strict.dtd">
<html><head><meta name="qrichtext" content="1" /><style type="text/css">
p, li { white-space: pre-wrap; }
</style></head><body style=" font-family:'.AppleSystemUIFont'; font-size:13pt; font-weight:400; font-style:normal;">
<p style=" margin-top:0px; margin-bottom:0px; margin-left:0px; margin-right:0px; -qt-block-indent:0; text-indent:0px;"><span style=" font-family:'Arial'; font-size:12pt; color:#000000;">source: source: https://coronavirus-staging.data.gov.uk/healthcare</span></p></body></html>
TIME
0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1741,1989,2032,2284,2245,2589,3184,2912,3561,3477,2990,3045,2978,3050,3212,3115,2777,2579,2314,2079,2251,2191,1903,2146,2003,1795,1782,1789,1805,1640,1616,1580,1430,1465,1578,1621,1645,1506,1387,1220,1304,1269,1217,1295,1246,989,1023,944,1080,1068,1000,987,938,853,870,897,943,928,894,826,646,666,626,731,785,745,694,617,591,645,678,658,640,549,443,451,460,508,536,469,441,394,443,446,485,477,441,369,308,314,423,376,377,361,315,298,231,224,237,306,217,210,186,212,215,200,206,201,179
people/day
source: https://coronavirus-staging.data.gov.uk/healthcare
TIME
0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,205,1788,2357,2869,3406,3821,4639,5881,7044,8020,9238,10732,12204,13111,13265,14748,16606,17801,18280,18980,19361,19524,19648,19518,19872,19397,19257,18552,18277,17320,17462,17476,17356,17098,16522,15957,15339,14799,14695,14788,14113,13851,13475,13051,12766,12607,12493,12152,11682,11161,10689,10701,10432,10659,10343,10088,9702,9497,9105,9124,9095,8914,8512,8268,8233,7867,7871,7895,7800,7474,7211,6909,6619,6587,6635,6451,6254,5996,5841,5631,5430,5409,5230,4972,4732,4662,4520,4519,4489,4490,4348,4217,4078,3926,3898,3961,3841,3730,3584,3361,3284,3308,3490,3144,2963,2842,2720,2588,2549,2495,2392,2251,2172,2088,1941,1951,1960,1865
People
<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.0//EN" "http://www.w3.org/TR/REC-html40/strict.dtd">
<html><head><meta name="qrichtext" content="1" /><style type="text/css">
p, li { white-space: pre-wrap; }
</style></head><body style=" font-family:'.AppleSystemUIFont'; font-size:13pt; font-weight:400; font-style:normal;">
<p style=" margin-top:0px; margin-bottom:0px; margin-left:0px; margin-right:0px; -qt-block-indent:0; text-indent:0px;"><span style=" font-family:'Arial'; font-size:12pt; color:#000000;">source: https://coronavirus-staging.data.gov.uk/healthcare</span></p></body></html>
TIME
0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,5166,6944,9092,11084,13387,15663,18216,21498,24407,28051,31408,34424,37403,40367,43514,46754,49810,52525,55081,57331,59461,61703,63858,65836,67939,70000,71718,73460,75292,77104,78693,80205,81742,82997,84385,85987,87523,89015,90475,91714,92885,94083,95333,96478,97703,98887,99800,100742,101667,102692,103683,104647,105567,106427,107258,108066,108948,109864,110714,111585,112323,112963,113566,114189,114944,115676,116417,117047,117630,118183,118812,119490,120137,120751,121234,121658,122081,122525,123032,123542,124003,124421,124802,125176,125659,126130,126578,126979,127347,127621,127941,128353,128737,123273,123577,123890,124167,124367,124580,124858,125117,125313,125513,125720,125913,126097,126303,126498,126684
People
TIME
0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1813,2120,2309,2469,2644,2864,2967,2963,3228,3274,3301,3277,3234,3228,3222,3162,3247,3176,3130,3036,2964,2867,2703,2702,2580,2454,2347,2286,2224,2178,2068,2009,1936,1874,1802,1685,1641,1585,1538,1485,1414,1342,1314,1302,1234,1196,1141,1106,1034,1008,964,926,886,863,847,783,751,719,704,679,652,636,602,571,554,540,515,509,491,439,390,393,390,393,385,378,357,352,330,315,310,340,311,316,276,268,270,270,262,279,259,239,231,220,217,209,197,185,188,191,168,159,162,145,153
people
0
Flow_3
People
daily_confirmed_deaths_data
people/day
Fraction becoming serious, Table 1, p.9
Venkateswaran, J., & Damani, O. (2020)
0.999
0.999
0.998
0.997
0.996
0.995
0.99
0.98
0.96
0.28
0.94
0.92
0.9
0.88
0.85
0.8
0.75
0.7
0.6
unitless
base_fraction_id_recovering
*ID_recovery_multiplier
unitless
1
unitless
Fraction becoming serious, Table 1, p.9
Venkateswaran, J., & Damani, O. (2020)
0.999
0.999
0.998
0.997
0.996
0.995
0.99
0.98
0.96
0.28
0.94
0.92
0.9
0.88
0.85
0.8
0.75
0.7
0.6
unitless
1
unitless
SUM(h_recovering[*, *])
people/day
SUM("Severe_&_hospitalized_(H)"[*, *])
people
isu_to_c
+ID_to_c
+isuh_to_c
people/day
0.5
unitless
"fr._isu_to_c"
*"fraction_becoming_isu_serious_(fh)"
/time_for_isu_to_get_serious
people/day
0.5
unitless
"fr._ID_to_c"
*fraction_id_becoming_serious
/time_for_id_to_get_serious
people/day
0.5
unitless
"fr._isuh_to_c"
*fraction_h_dying
/time_for_h_to_die
people/day
SUM(isu_to_c[*, *])
People/day
SUM(isuh_to_c[*, *])
people/day
SUM(ID_to_c[*, *])
people/day
SUM(h_worsening[*, *])
people/day
total_admissions_directly_to_C + total_h_worsening
people/day
total_ID_to_c + total_isu_to_c + total_isuh_to_c
people/day
1
unitless
1
unitless
1
unitless
0
ad
d
r
People
daily_admissions_data
people/day
daily_confirmed_deaths_data
people/day
fr_r
*H_1
/t_to_r
people/day
0.5
unitless
14
Days
SUM(recovering)
+SUM(h_recovering)
people/day
IF TIME < hospital_data_time THEN
missing_cumulative_admissions_data
ELSE cumulative_admissions_data
People
98
days
TIME
0,4.97166019142435,9.73457529119953,15.4602552626431,26.6198548307808,25,89.1379147137104,159.008711154864,272.918932934654,446.589920236149,442,1007.56756652629,1374.57931963743,1745.94722405114,3500,5990,9770,16000,22400,32700,42000
People
IF TIME <=critical_data_time THEN
0
ELSE SUM("Critical_(C)")
People
92.43
days
77.9
days
IF TIME <=hospitalization_data_time THEN
0
ELSE Total_Current_Hospitalization
People
TIME
0.999933071490757,0.999820137900379,0.999525741268224,0.998807970779779,0.9973105857863,0.995,0.9926894142137,0.991192029220221,0.990474258731776,0.990179862099621,0.990066928509243
unitless
SUM("ISU_hospitalized_(ISUH)"[*, *])
People
Total_ISUH
/MAX(total_isuh_testing, 0.1)
average_isuh_time_before_diagnosis + time_for_h_to_worsen
days
average_isuh_time_before_diagnosis + time_for_h_to_die
days
average_isuh_time_before_diagnosis + time_for_h_to_recover
days
SUM("Death(D)"[a_0_to_4, *]) + SUM("Death(D)"[a_10_to_14, *]) + SUM("Death(D)"[a_15_to_19, *]) + SUM("Death(D)"[a_5_to_9, *])
SUM("Death(D)"[a_20_to_24, *]) + SUM("Death(D)"[a_25_to_29, *]) + SUM("Death(D)"[a_30_to_34, *]) + SUM("Death(D)"[a_35_to_39, *]) + SUM("Death(D)"[a_40_to_44, *]) + SUM("Death(D)"[a_45_to_49, *]) + SUM("Death(D)"[a_50_to_54, *]) + SUM("Death(D)"[a_55_to_59, *])
SUM("Death(D)"[a_60_to_64,*]) + SUM("Death(D)"[a_65_to_69,*]) + SUM("Death(D)"[a_70_to_74, *]) + SUM("Death(D)"[a_75_to_79, *]) + SUM("Death(D)"[a_80_to_84, *]) + SUM("Death(D)"[a_85_to_89, *]) + SUM("Death(D)"[a_90_plus, *])
SUM("Death(D)"[a_70_to_74, *]) + SUM("Death(D)"[a_75_to_79, *]) + SUM("Death(D)"[a_80_to_84, *]) + SUM("Death(D)"[a_85_to_89, *]) + SUM("Death(D)"[a_90_plus, *])
SUM("Death(D)"[a_80_to_84, *]) + SUM("Death(D)"[a_85_to_89, *]) + SUM("Death(D)"[a_90_plus, *])
Confirmed_Cases
("Death(D)"[a_0_to_4,UK]*2.5
+"Death(D)"[a_5_to_9,UK]*7.5
+"Death(D)"[a_10_to_14,UK]*12.5
+"Death(D)"[a_15_to_19,UK]*17.5
+"Death(D)"[a_20_to_24,UK]*22.5
+"Death(D)"[a_25_to_29,UK]*37.5
+"Death(D)"[a_30_to_34,UK]*32.5
+"Death(D)"[a_35_to_39,UK]*37.5
+"Death(D)"[a_40_to_44,UK]*42.5
+"Death(D)"[a_45_to_49,UK]*47.5
+"Death(D)"[a_50_to_54,UK]*52.5
+"Death(D)"[a_55_to_59,UK]*57.5
+"Death(D)"[a_60_to_64,UK]*62.5
+"Death(D)"[a_65_to_69,UK]*67.5
+"Death(D)"[a_70_to_74,UK]*72.5
+"Death(D)"[a_75_to_79,UK]*77.5
+"Death(D)"[a_80_to_84,UK]*82.5
+"Death(D)"[a_85_to_89,UK]*87.5
+"Death(D)"[a_90_plus,UK]*95)/MAX(1, Confirmed_Deaths)
Years
100
*Deaths_under_20
/MAX(1, Confirmed_Deaths)
unitless
100
*"Deaths_20-60"
/MAX(1, Confirmed_Deaths)
100
*Deaths_over_60
/MAX(1, Confirmed_Deaths)
100
*Deaths_over_70
/MAX(1, Confirmed_Deaths)
100
*Deaths_over_80
/MAX(1, Confirmed_Deaths)
SUM("Death(D)"[a_0_to_4, *]) + SUM("Death(D)"[a_10_to_14, *]) + SUM("Death(D)"[a_15_to_19, *]) + SUM("Death(D)"[a_20_to_24,*]) + SUM("Death(D)"[a_25_to_29,*]) + SUM("Death(D)"[a_30_to_34,*]) + SUM("Death(D)"[a_35_to_39,*]) + SUM("Death(D)"[a_40_to_44,*]) + SUM("Death(D)"[a_45_to_49,*]) + SUM("Death(D)"[a_5_to_9, *])
100
*Deaths_under_50
/MAX(1, Confirmed_Deaths)
Total_Deaths-(47.6e3+668+36)
people
(average_age_of_death_in_the_UK
-average_age_of_death_due_to_Covid
)
*Total_Deaths
People years
81.4
Years
years_of_life_lost_to_Covid-(45.8e3-13.8+23.e3+16.2)
(Month-1)*(365/12)+Day
7
12
"Susceptible_(S)"
"infection_rate_(ir)"
"Infectious_Asymptomatic_Undiagnosed_(IAU)"
incubation_rate
"Infectious_Asymptomatic_Undiagnosed_(IAU)"
normal_IAU_testing
"Infectious_Symptomatic_Undiagnosed_(ISU)"
normal_ISU_testing
"Infectious_Diagnosed_(ID)"
ID_disease_progression_rate
"Severe_&_hospitalized_(H)"
h_dying
"Infectious_Diagnosed_(ID)"
id_dying
"Severe_&_hospitalized_(H)"
h_worsening
"Recovered_(R)"
immnity_gain
infectivity
"infection_rate_(ir)"
"base_infectivity_(p)"
infectivity
"Total_Initial_Population_(N)"
"stratified_population_(SN)"
"stratified_population_(SN)"
"initial_susceptible_population_(is)"
"initial_susceptible_population_(is)"
initial_infectious_population
"initial_susceptible_population_(is)"
"population_fraction_by_age_and_region_(g)"
"stratified_population_(SN)"
"Infectious_Asymptomatic_Undiagnosed_(IAU)"
iau_recovering
"fraction_developing_symptoms_(fs)"
incubation_rate
time_for_iau_to_develop_symptoms
incubation_rate
"contact_rate_(cr)"
"infection_rate_(ir)"
time_for_iau_to_recover
iau_recovering
Total_Deaths
deaths_in_percent
fraction_of_population_infectious
"Total_Initial_Population_(N)"
deaths_in_percent
Base_Reproduction_Rate_R0
Reproduction_Rate_R
Average_Duration_of_Illness_d
Base_Reproduction_Rate_R0
Base_Reproduction_Rate_R0
"Total_Initial_Population_(N)"
Reproduction_Rate_R
Total_Susceptible
Reproduction_Rate_R
"fraction_ISU_accurately_tested_(ft)"
normal_ISU_testing
time_for_isu_testing
normal_ISU_testing
"Infectious_Symptomatic_Undiagnosed_(ISU)"
isu_recovering
time_for_isu_to_recover
isu_recovering
time_for_isu_to_die
isu_dying
ID_recovering
"Severe_&_hospitalized_(H)"
h_recovering
time_for_h_to_recover
h_recovering
time_for_h_to_worsen
h_worsening
"Critical_(C)"
recovering
time_for_c_to_recover
recovering
fraction_h_recovering
h_recovering
time_to_test_for_immunity
immnity_gain
"Critical_(C)"
c_dying
time_for_c_to_die
c_dying
fraction_critical_to_recover
recovering
"Immune_(I)"
immunity_loss
time_to_lose_immunity
immunity_loss
Base_Reproduction_Rate_R0
temporary_immunity
immunity_loss
total_infection_rate
infecting
fraction_of_population_infectious
effect_of_age_on_contact_rate
"contact_rate_(cr)"
"base_contact_rate(bcr)"
"contact_rate_(cr)"
LTCF_deaths
Total_Immune
herd_immunity
Total_Population
herd_immunity
Total_Deaths
CFR
Confirmed_Cases
CFR
fraction_of_population_infectious
"infection_rate_(ir)"
initial_cases
new_cases_arrival
testing_capcity
isu_testing
testing_capcity
iau_screening
fraction_isu_recovering
isu_recovering
fraction_c_dying
c_dying
base_fraction_c_dying
fraction_c_dying
c_death_multiplier
fraction_c_dying
"base_fraction_developing_symptoms_(fs)"
"fraction_developing_symptoms_(fs)"
age_multiplier
"fraction_developing_symptoms_(fs)"
fraction_exposed
"contact_rate_(cr)"
age_specific_exposure_profile
"contact_rate_(cr)"
infectivity_multiplier
infectivity
normal_ISU_testing
isu_testing
age_group_factor
testing_capcity
daily_cases_approx
testing_capcity
normal_IAU_testing
iau_screening
"fraction_IAU_accurately_screened_(ft)"
normal_IAU_testing
time_for_iau_screening
normal_IAU_testing
total_iau_screening
total_isu_testing
total_iau_screening
diagnosing
total_isu_testing
diagnosing
time_for_h_to_die
h_dying
time_for_id_to_die
id_dying
total_isu_dying
total_id_dying
total_h_dying
total_c_dying
total_isu_dying
daily_deaths
total_id_dying
daily_deaths
total_h_dying
daily_deaths
total_c_dying
daily_deaths
base_fraction_isu_dying
fraction_isu_dying
fraction_isu_dying
isu_dying
"Infectious_Symptomatic_Undiagnosed_(ISU)"
isu_dying
base_fraction_id_dying
fraction_id_dying
fraction_id_dying
id_dying
base_fraction_id_becoming_serious
fraction_id_becoming_serious
fraction_id_becoming_serious
ID_disease_progression_rate
time_for_id_to_get_serious
ID_disease_progression_rate
base_fraction_h_dying
fraction_h_dying
fraction_h_dying
h_dying
"base_fraction_to_become_critical(fc)"
"fraction_to_become_critical(fc)"
"fraction_to_become_critical(fc)"
h_worsening
total_id_progression
total_id_progression
admissions
ID_worse_multiplier
fraction_id_becoming_serious
h_death_multiplier
fraction_h_dying
isu_death_multiplier
fraction_isu_dying
id_death_multiplier
fraction_id_dying
"Hygiene_&_social_distancing_effect_v(t)"
"infection_rate_(ir)"
h_worsening_multiplier
"fraction_to_become_critical(fc)"
time_for_id_to_recover
ID_recovering
fraction_iau_recovering
iau_recovering
dc
"fraction_becoming_isu_serious_(fh)"
isu_worsening
time_for_isu_to_get_serious
isu_worsening
isu_worse_multiplier
"fraction_becoming_isu_serious_(fh)"
base_isu_fraction_becoming_serious
"fraction_becoming_isu_serious_(fh)"
"Infectious_Symptomatic_Undiagnosed_(ISU)"
isu_worsening
"ISU_hospitalized_(ISUH)"
isuh_testing
time_for_isuh_testing
isuh_testing
total_isuh_testing
total_isuh_testing
diagnosing
total_isu_worsening
total_isu_worsening
admissions
dh
Flow_3
base_fraction_id_recovering
fraction_id_recovering
ID_recovery_multiplier
fraction_id_recovering
fraction_id_recovering
ID_recovering
h_recovery_multiplier
fraction_h_recovering
base_fraction_h_recovering
fraction_h_recovering
"fr._isu_to_c"
isu_to_c
isu_to_c
admission_directly_to_C
"fr._ID_to_c"
ID_to_c
ID_to_c
admission_directly_to_C
"fr._isuh_to_c"
isuh_to_c
isuh_to_c
admission_directly_to_C
isu_worsening
isuh_testing
ID_disease_progression_rate
admissions
c_recovery_multiplier
fraction_critical_to_recover
fraction_critical_to_recover
fraction_iau_recovering
iau_recovery_multiplier
fraction_iau_recovering
fraction_isu_recovering
isu_recovery_multiplier
fraction_isu_recovering
ad
d
H_1
r
fr_r
r
t_to_r
r
daily_recovery_from_hospitals
daily_recovery_from_hospitals
hospital_data_time
new_cumulative_admissions_data
missing_cumulative_admissions_data
new_cumulative_admissions_data
critical_april_forward
critical_data_time
critical_april_forward
new_cumulative_admissions_data
hospitalization_March_forward
hospitalization_data_time
hospitalization_March_forward
isu_to_c
isu_to_c
isuh_to_c
isuh_to_c
ID_to_c
ID_to_c
global_death_multiplier
isu_dying
id_dying
c_dying
h_dying
Notes: 13.7
1. Updating the cases and death data up to July 16, 2020
Total_ISUH
average_isuh_time_before_diagnosis
total_isuh_testing
average_isuh_time_before_diagnosis
average_age_of_death_due_to_Covid
average_age_of_death_due_to_Covid
"%_deaths_under_20"
Deaths_under_20
"%_deaths_under_20"
"Deaths_20-60"
"%_deaths_20-60"
"%_deaths_20-60"
"%_deaths_over_60"
Deaths_over_60
"%_deaths_over_60"
Deaths_over_70
"%_deaths_over_70"
"%_deaths_over_70"
"%_deaths_over_80"
Deaths_over_80
"%_deaths_over_80"
Deaths_under_50
"%_deaths_under_50"
"%_deaths_under_50"
Total_Deaths
Change_in_Total_Deaths
average_age_of_death_due_to_Covid
years_of_life_lost_to_Covid
average_age_of_death_in_the_UK
years_of_life_lost_to_Covid
years_of_life_lost_to_Covid
years_of_life_lost_to_Covid
change_in_years_of_life_lost_to_Covid
Month
Model_day
Day
Model_day
"Immune_(I)"
"stratified_population_(SN)"
Total_Infected_undiagnosed
infectivity
"Infectious_Diagnosed_(ID)"
"contact_rate_(cr)"
"Death(D)"
isu_testing
iau_screening
isu_dying
id_dying
h_dying
c_dying
ID_disease_progression_rate
daily_confirmed_cases_data
isuh_testing
isu_worsening
daily_admissions_data
daily_confirmed_deaths_data
"fr._isu_to_c"
"fr._isuh_to_c"
"fr._ID_to_c"
total_admissions_directly_to_C
base_fraction_h_recovering
base_fraction_h_recovering
base_fraction_h_recovering
daily_admissions_data
daily_confirmed_deaths_data
recovering
h_recovering
"Critical_(C)"
cumulative_admissions_data
Total_Current_Hospitalization
"fraction_becoming_isu_serious_(fh)"
time_for_isu_to_get_serious
fraction_h_dying
time_for_h_to_die
fraction_id_becoming_serious
time_for_id_to_get_serious
global_death_multiplier
global_death_multiplier
global_death_multiplier
Confirmed_Deaths
"Death(D)"
Total_Deaths
0
new_missed_cases
Flow_1
0
Flow_1
Flow_2
0
Flow_2
Flow_3
0
0
0
Flow_3
0
normal_rate_of_missed_cases*
"%_of_new"
0
0
normal_rate_of_missed_cases
new_missed_cases
"%_of_new"
new_missed_cases
0,10,20,30,40,50,60,70,80,90,100,110,120,130,140,150,160,170,180,190,200,210,220,230,240
1,1,1,1,1,1,1,1,1,0.5,0.39,0.33,0.303,0.283,0.279,0.3,0.35,0.4,0.5,0.5,0.5,0.5,0.5,0.5,0.5