# Covid 19 Contagion Dynamics

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breed [humans human] breed [statistic_agents statistic_agent] globals [ age_group_0_9 age_group_10_19 age_group_20_29 age_group_30_39 age_group_40_49 age_group_50_59 age_group_60_69 age_group_70_79 age_group_80 elapsed-day-hours medical_care_used number_of_deaths death_list city_area_patches roads_area_patches change_lockdown_condition? cumulative_infected last_cumulative cumulative_aware_of_infection last_cumulative_aware_of_infection logged_transmitters R0_global ] humans-own [ infected? infection-length aggravated_symptoms_day age-group ontreatment? gotinfection? contagion-chance death-chance ongoing-infection-hours symptoms_delay aware_of_infection? infectedby ] statistic_agents-own [ age-group recovered deaths ] patches-own [ original_map_color ] to-report calculate_R0 let list_of_transmitters remove-duplicates logged_transmitters let current_case 0 let sum_repetitions 0 foreach list_of_transmitters [ patient -> set current_case patient let transmitter_repeated length filter [ i -> i = current_case] logged_transmitters set sum_repetitions sum_repetitions + transmitter_repeated ] ifelse length list_of_transmitters > 0 [ report sum_repetitions / ( length list_of_transmitters ) ] [ report 0 ] end ;;;;;;;;;;;;;;;;;;;;;;;;;;; HUMANS PROCEDURES ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;; ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;; ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;; to-report moore-neighborhood report humans at-points [[-1 1] [1 1] [-1 -1] [-1 0] [1 0] [0 1] [0 0] [0 -1] [1 -1]] end to infection_exposure if (not gotinfection?) [ let people_around moore-neighborhood let infected_around people_around with [infected? = true and not ontreatment? and ( ongoing-infection-hours > (average_days_for_contagion * 24)) ] let number_of_infected_around count infected_around if number_of_infected_around > 0 [ let within_contagion_distance (random(metres_per_patch * 2 + 1)) ;; Assuming each patch represents up to metres_per_patch distance units (meters) set within_contagion_distance within_contagion_distance + random-float ( keep_social_distancing ) ;; Assuming the ordered social distance is not followed accurately but more randomly and proportionate to the ordered distance ;;;;;;;;; Chance of Contagion according to age group: if (contagion-chance >= (random(100) + 1) and within_contagion_distance <= maximum_contagion_distance) [ let transmitter_person nobody ask one-of infected_around [ set transmitter_person who ] set logged_transmitters lput transmitter_person logged_transmitters if length ( logged_transmitters ) > 800 [ ;;Do not allow the list to grow without end, delete older elements. set logged_transmitters but-first logged_transmitters ] get_infected ] ] ] end to get_infected set color red set size 3 set infected? true set gotinfection? true set infection-length 24 * ( random-normal average_infection_length 5.0 ) ;; mean of infection length and standard-deviation multiplied by 24 hours set aggravated_symptoms_day round (infection-length / 2.5) ;; Aggravated infection may happen after the first week set symptoms_delay 24 * ( random-normal average-symptoms-show 4.0 ) set ongoing-infection-hours 0 set cumulative_infected cumulative_infected + 1 end to get-healthy set infected? false set gotinfection? true set infection-length 0 set ongoing-infection-hours 0 set aggravated_symptoms_day 0 if ontreatment? [ free-medical-care set ontreatment? false] set color green set size 1 set aware_of_infection? false update-recovered-statistics age-group end to check_health_state if infected? [ if ongoing-infection-hours >= ( symptoms_delay + random(diagnosis_delay) ) and not ontreatment? [ if not aware_of_infection? [ set aware_of_infection? true set cumulative_aware_of_infection cumulative_aware_of_infection + 1 ] ifelse prioritise_elderly? [ ifelse age-group >= age_group_60_69 [ if get-medical-care = true [ set ontreatment? true ] ] [ if %medical-care-availability >= 25 [ ;;If not an elderly person then only take medical care if availability >= 25% if get-medical-care = true [ set ontreatment? true ] ] ] ] [ if get-medical-care = true [ set ontreatment? true ] ] ] if (ongoing-infection-hours = aggravated_symptoms_day) ;;Check if patient is going to die [ ;;;;;;;;;; Decide if patient survived or not the infection: let chance_to_die 0 let severity_factor 1 if ( ( chance_of_severe_infection * 1000 ) >= random(100000) ) [ ;;Patient got a severe infection increasing the death chance by a severity factor set severity_factor severity_death_chance_multiplier ] ifelse (ontreatment?) [ set chance_to_die ((death-chance * 1000) * severity_factor) * 0.5 ;; Death chance is reduced to 50%, Survival chance is increased by 50% ] [ set chance_to_die (death-chance * 1000) * severity_factor ] if (chance_to_die >= (random(100000) + 1)) [ update-death-statistics age-group set number_of_deaths number_of_deaths + 1 delete-person ] ] ifelse (ongoing-infection-hours >= infection-length) [ set ongoing-infection-hours 0 get-healthy ] [ set ongoing-infection-hours ongoing-infection-hours + 1 ] ] end to move [ #speed ] if not ontreatment? [ rt random-float 360 let next_patch_color white ask patch-ahead 1 [ set next_patch_color original_map_color ] if (next_patch_color = white ) [ fd #speed ] ] end to delete-person if ontreatment? [ free-medical-care ] die end ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;; SETUP PROCEDURES ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;; ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;; ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;; to draw_road_lines let rows 1 repeat 8 [ ask patches with [pxcor > -260 and pxcor < 260 and pycor = -250 + (rows * 60) and pcolor = white ][set pcolor yellow] let roads 1 repeat 3 [ ask patches with [pxcor = -260 + (rows * 60) + roads and pycor > -250 and pycor < 260 and pcolor = white ][set pcolor yellow] set roads roads + 1 ] set rows rows + 1 ] end to create_city_map ask patches with [pxcor > -270 and pxcor < 270 and pycor > -270 and pycor < 260 ] [ set pcolor white ] let rows 1 repeat 8 [ ask patches with [pxcor > -260 and pxcor < 260 and pycor = -250 + (rows * 60) ][set pcolor yellow] let roads 1 repeat 3 [ ask patches with [pxcor = -260 + (rows * 60) + roads and pycor > -250 and pycor < 260 ][set pcolor yellow] set roads roads + 1 ] set rows rows + 1 ] end to setup-globals ifelse load_city_map? [ import-pcolors "Argentina_outline.png" draw_road_lines ] [ create_city_map ] ask patches [ set original_map_color pcolor ] set age_group_0_9 9 set age_group_10_19 19 set age_group_20_29 29 set age_group_30_39 39 set age_group_40_49 49 set age_group_50_59 59 set age_group_60_69 69 set age_group_70_79 79 set age_group_80 80 set elapsed-day-hours 0 set medical_care_used 0 set number_of_deaths 0 set cumulative_infected 0 set last_cumulative 0 set city_area_patches patches with [ pcolor != black ] set roads_area_patches patches with [ pcolor = yellow ] set complete_lockdown? false set change_lockdown_condition? false set prioritise_elderly? false set partial_lockdown? false set cumulative_aware_of_infection 0 set last_cumulative_aware_of_infection 0 set logged_transmitters[] set R0_global 0 end to setup_statistic_agent [ #age-group ] create-statistic_agents 1 [ set age-group #age-group set recovered 0 set deaths 0 ht ] end to setup-people [#number #age-group] create-humans #number [ let random_x 0 let random_y 0 ask one-of city_area_patches [ set random_x pxcor set random_y pycor ] setxy random_x random_y set shape "circle" set infected? false set aggravated_symptoms_day 0 set ongoing-infection-hours 0 set color green set age-group #age-group set ontreatment? false set gotinfection? false set symptoms_delay 0 set aware_of_infection? false set infectedby nobody ifelse age-group <= age_group_0_9 [ set contagion-chance chance_of_infection_0-9 set death-chance chance_of_death_0-9 ] [ ifelse age-group <= age_group_10_19 [ set contagion-chance chance_of_infection_10-19 set death-chance chance_of_death_10-19 ] [ ifelse age-group <= age_group_20_29 [ set contagion-chance chance_of_infection_20-29 set death-chance chance_of_death_20-29 ] [ ifelse age-group <= age_group_30_39 [ set contagion-chance chance_of_infection_30-39 set death-chance chance_of_death_30-39 ] [ ifelse age-group <= age_group_40_49 [ set contagion-chance chance_of_infection_40-49 set death-chance chance_of_death_40-49 ] [ ifelse age-group <= age_group_50_59 [ set contagion-chance chance_of_infection_50-59 set death-chance chance_of_death_50-59 ] [ ifelse age-group <= age_group_60_69 [ set contagion-chance chance_of_infection_60-69 set death-chance chance_of_death_60-69 ] [ ifelse age-group <= age_group_70_79 [ set contagion-chance chance_of_infection_70-79 set death-chance chance_of_death_70-79 ] [ set contagion-chance chance_of_infection_80 set death-chance chance_of_death_80 ] ] ] ] ] ] ] ] ] end to setup clear-all ;random-seed 25000000 setup-globals setup-people population_0-9 age_group_0_9 setup-people population_10-19 age_group_10_19 setup-people population_20-29 age_group_20_29 setup-people population_30-39 age_group_30_39 setup-people population_40-49 age_group_40_49 setup-people population_50-59 age_group_50_59 setup-people population_60-69 age_group_60_69 setup-people population_70-79 age_group_70_79 setup-people population_80 age_group_80 let affected_number round (count humans * (initial_infected_population / 100)) infect_people affected_number setup_statistic_agent age_group_0_9 setup_statistic_agent age_group_10_19 setup_statistic_agent age_group_20_29 setup_statistic_agent age_group_30_39 setup_statistic_agent age_group_40_49 setup_statistic_agent age_group_50_59 setup_statistic_agent age_group_60_69 setup_statistic_agent age_group_70_79 setup_statistic_agent age_group_80 reset-ticks end ;;;;;;;;;;;;;;;;;;;;;;;;; ENVIRONMENT - STATISTIC_AGENTS PROCEDURES ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;; ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;; ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;; to update-recovered-statistics [ #age-group ] ask statistic_agents with [ age-group = #age-group ] [ set recovered recovered + 1 ] end to update-death-statistics [ #age-group ] ask statistic_agents with [ age-group = #age-group ] [ set deaths deaths + 1 ] end ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;; ENVIRONMENT - HUMAN PROCEDURES ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;; ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;; ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;; to infect_people [#affected_number] ask n-of #affected_number humans with [ not gotinfection? ] [ get_infected ] end to-report get-medical-care if medical_care_used < medical_care_capacity [ set medical_care_used medical_care_used + 1 report true ] report false end to-report %medical-care-availability report ( (medical_care_capacity - medical_care_used) / medical_care_capacity ) * 100 end to free-medical-care set medical_care_used medical_care_used - 1 end to people-enter-city [#people_entering #percentage_entering_infected_population] let entering_per_age_group #people_entering / 9 setup-people entering_per_age_group age_group_0_9 setup-people entering_per_age_group age_group_10_19 setup-people entering_per_age_group age_group_20_29 setup-people entering_per_age_group age_group_30_39 setup-people entering_per_age_group age_group_40_49 setup-people entering_per_age_group age_group_50_59 setup-people entering_per_age_group age_group_60_69 setup-people entering_per_age_group age_group_70_79 setup-people entering_per_age_group age_group_80 infect_people #people_entering * #percentage_entering_infected_population / 100 end to people-leave-city [#people_leaving] ask n-of #people_leaving humans with [not ontreatment?] [ delete-person ] end ;;;;;;;;;;;;;;;;;;;;;;;;;;; SOCIAL INTERACTIONS - HUMANS PROCEDURES ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;; ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;; ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;; to gather_in_schools if partial_lockdown? [ stop ] let gatherings_size 200 ;Students per school 200 repeat active_schools [ let place_x 0 let place_y 0 ask one-of city_area_patches [ set place_x pxcor set place_y pycor] ask up-to-n-of gatherings_size humans with [ ( age-group = age_group_0_9 or age-group = age_group_10_19 ) and not aware_of_infection? ][set xcor place_x - 4 + random(8) set ycor place_y - 4 + random(8) ] ] end to gather_in_colleges if partial_lockdown? [ stop ] let gatherings_size 300 ;Students per college repeat active_colleges [ let place_x 0 let place_y 0 ask one-of city_area_patches [ set place_x pxcor set place_y pycor] ask up-to-n-of gatherings_size humans with [ age-group = age_group_20_29 and not aware_of_infection? ][set xcor place_x - 4 + random(8) set ycor place_y - 4 + random(8) ] ] end to gather_in_hosp_venues if partial_lockdown? [ stop ] let gatherings_size 40 ;40 people per venue repeat active_hosp_venues [ let place_x 0 let place_y 0 ask one-of city_area_patches [ set place_x pxcor set place_y pycor] ask up-to-n-of gatherings_size humans with [ not aware_of_infection? ][set xcor place_x - 2 + random(3) set ycor place_y - 2 + random(3) ] ] end to gather_in_public_transport_lines if partial_lockdown? [ stop ] let gatherings_size 60 ;60 people per bus/tram line repeat active_public_transport_lines [ let place_x 0 let place_y 0 ask one-of roads_area_patches [ set place_x pxcor set place_y pycor] ask up-to-n-of gatherings_size humans with [ not aware_of_infection? ][set xcor place_x - 2 + random(3) set ycor place_y - 4 + random(10) ] ] end to gather_in_adult_venues if partial_lockdown? [ stop ] let gatherings_size 40 ; 40 people per venue repeat active_adult_venues [ let place_x 0 let place_y 0 ask one-of city_area_patches [ set place_x pxcor set place_y pycor] ask up-to-n-of gatherings_size humans with [ ( age-group != age_group_0_9 and age-group != age_group_10_19 ) and not aware_of_infection? ][set xcor place_x - 2 + random(3) set ycor place_y - 2 + random(3) ] ] end to gather_in_senior_venues if partial_lockdown? [ stop ] let gatherings_size 40 ; 40 people per venue repeat active_adult_venues [ let place_x 0 let place_y 0 ask one-of city_area_patches [ set place_x pxcor set place_y pycor] ask up-to-n-of gatherings_size humans with [ ( age-group = age_group_60_69 or age-group = age_group_70_79 or age-group = age_group_80 ) and not aware_of_infection? ][set xcor place_x - 2 + random(3) set ycor place_y - 2 + random(3) ] ] end to gather_in_food_shops if partial_lockdown? [ stop ] let gatherings_size 50 ; 50 people in a supermarket, bakery, small shop repeat active_adult_venues [ let place_x 0 let place_y 0 ask one-of city_area_patches [ set place_x pxcor set place_y pycor] ask up-to-n-of gatherings_size humans with [ age-group != age_group_0_9 and not aware_of_infection? ][set xcor place_x - 2 + random(4) set ycor place_y - 2 + random(4) ] ] end to go_back_home ask humans with [ not aware_of_infection? ] [ let random_x 0 let random_y 0 ask one-of city_area_patches [ set random_x pxcor set random_y pycor ] setxy random_x random_y ] end ;;;;;;;;;;;;;;;;;;;;;;;;;;; GO PROCEDURE ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;; ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;; ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;; to go ifelse prioritise_elderly? [ foreach sort-on [(- age-group)] humans [ patient -> ask patient [ check_health_state ] ] ] [ ask humans [ check_health_state ] ] ask humans [ ;check_health_state if elapsed-day-hours > 6 [ infection_exposure ] ifelse not complete_lockdown? [ move 1.5 ][ move 0.1 ] ] ifelse elapsed-day-hours >= 24 [ set R0_global calculate_R0 print cumulative_aware_of_infection if log_infection_data? [ ;let delta_cumulative cumulative_infected / (last_cumulative + 1) ;print ( word ceiling (ticks / 24) "," cumulative_infected "," number_of_deaths "," delta_cumulative ) let delta_cumulative cumulative_aware_of_infection / (last_cumulative_aware_of_infection + 1) print ( word ceiling (ticks / 24) "," cumulative_infected "," number_of_deaths "," delta_cumulative ) set last_cumulative_aware_of_infection cumulative_aware_of_infection set last_cumulative cumulative_infected ] set elapsed-day-hours 1 ] [ if not complete_lockdown? [ if elapsed-day-hours mod 7 = 0 [ gather_in_hosp_venues ] ;;3 times a day if elapsed-day-hours mod 10 = 0 [ gather_in_food_shops ] ;;2 times a day if elapsed-day-hours > 6 and elapsed-day-hours mod 2 = 0 [ gather_in_public_transport_lines ] ;; 8 times a day ifelse elapsed-day-hours = 7 [ ;;Rush Hour ;;;;; People enter and leave the city once a day: people-leave-city people_entering_city_per_day; people_leaving_city_per_day people-enter-city people_entering_city_per_day infected_visitors;[#people_entering #percentage_entering_infected_population] ;;;;; Gatherings once a day gather_in_schools gather_in_colleges gather_in_senior_venues ] [ if elapsed-day-hours = 22 [ gather_in_adult_venues ] ] ] set elapsed-day-hours elapsed-day-hours + 1 ] if change_lockdown_condition? != complete_lockdown? [ set change_lockdown_condition? complete_lockdown? go_back_home ] tick end to-report %infected ifelse any? humans [ report (count humans with [infected?] / count humans) * 100 ] [ report 0 ] end

There are 13 versions of this model.

## Attached files

File | Type | Description | Last updated | |
---|---|---|---|---|

Argentina.png | png | Argentina city_map | almost 3 years ago, by Santiago Linares | Download |

Argentina_outline.png | png | Argentina Outline Map | almost 3 years ago, by Cristian Jimenez Romero | Download |

Covid 19 Contagion Dynamics.png | preview | PresentacionArgentina | almost 3 years ago, by Cristian Jimenez Romero | Download |

Covid 19 Contagion Dynamics.png | preview | Presentacion | almost 3 years ago, by Cristian Jimenez Romero | Download |

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Cristian Jimenez Romero

## About the model

The model presented here is a multi-agent simulation that visualises emerging dynamics from the interaction and influence of a small subset of multiple biological and social factors in the development of the covid-19 pandemic. Given the scale of the pandemic, and the complexity of global societal structures, the simulation may not be viewed as a precise model of universal application. The simulation may however be tailored to locales to enable governments to assess strategic interventions and outcomes at local, municipal and regional levels. In facilitating such analysis, variables that play a critical role in the development of the pandemic have been singled out for manipulation in the model.

## Posted almost 3 years ago

Cristian Jimenez Romero

## Download

If you get any trouble downloading or opening the model please contact me and I will be happy to send you the code via email.

## Posted almost 3 years ago

Olufemi Oloba

## Helping with the model

Hi, I am Olufemi, a PhD student who is still learning NetLogo but I would not mind helping out with the model in any little way I can. Similarly, I am interested in modeling the spread of the disease in Nigeria what with our dismal health sector. Kind Regards, Olufemi

## Posted almost 3 years ago

Cristian Jimenez Romero

## Re. Helping with the model

Hi Olufemi, thanks for your message. It would be very interesting to model the spread of the disease in Nigeria. There is some data that the model would require, including: distribution of population per age group, number of hospital beds per 1000 people, density of population, etc. Please write me a private message on cristianjimenez.org Kind Regards, Cristian

## Posted almost 3 years ago

Emiliano Alvarez

## good model (Question)

Very interesting ABM. I would like to apply this kind of model but also looking on economic imbalances on wages, employment, production, etc. I think on the possibilities of merging economic ABM's and contagion dynamics ABM's, in a way to explore the economic consequences of pandemics.

## Posted almost 3 years ago

Cristian Jimenez Romero

## Re. good model

Thanks for your message Emiliano. I you need any help applying or modifying the model for your own applications please let me know. I will be happy to help.

## Posted almost 3 years ago

zhangrong hu

## Basemap request (Question) (Question)

The model is fantastic, I am going to apply it to my city (Tandil, Argentina). I would need the file California_outline_white.png to run the model in a specific area. Can you send it to me. Thank you very much and congratulations, a great contribution.

## Posted almost 3 years ago

iliasse aafir

## request

i'm an engineering student , really i'm interested by the model , but a don't why i didn't work for me , they told me about import-a and fetch

## Posted almost 3 years ago

iliasse aafir

## request

please i need your help this model don't work for me

## Posted almost 3 years ago

iliasse aafir

## request

i need the filname used for the p colors

## Posted almost 3 years ago

Santiago Linares

## request (Question)

Dear iliasse, About you request Argentina city_map I recently uploaded the Argentina.png file, it is the filename used for the p colors. Regards

## Posted almost 3 years ago

Aaron Meyers

## question about # people recovered (Question)

Thank you for the extremely interesting model, it is very helpful. I have a question regarding the "# people recovered" field in the monitors on the top. After the model runs for a while, this number sometimes begins to go down. Can you explain what is happening? How can the total # of recovered people since the simulation started go down? Thank you!

## Posted almost 3 years ago

Cristian Jimenez Romero

## question about # people recovered

Hi Aaron, Thanks for your message and for your question. If you set the slider "people_entering_city_per_day" with a value greater than 0 it will cause that new agents enter in the city every day but also some agents already living in the city (including recovered ones) will go away. It will make the counter "# people recovered" to go down. This is something that needs correction in order to keep a cumulative counting of recovered agents. Thank you for spotting this behaviour and raising the question!

## Posted almost 3 years ago

Asha Mahesh

## downloading the model file (Question)

I am not able to extract the model from downloaded zip file. Can you please send me the model

## Posted over 2 years ago

Jack Du

## can not open the code

Hello Thanks for sharing! This is a really brilliant and interesting model. But I have trouble to open. the error is that it can not unable to open model with current format. Can you share the code with me Thanks

## Posted over 2 years ago

Manuel Mateos GutiĆ©rrez

## Trying to execute the model

Hi, as my colleages I am having issues running the model, it sends a error about the format. I tried to directly use the code but there are some missing variables like average_days_for_contagion Could you update the model for 6.2? (I also tried with 6.1.1 but same issue) Or give us some guidance to run it? I am very interested on creating a COVID model to study it's behaviour and I'd like to use your model as foundation. Thank you in advance.

## Posted about 2 years ago

Iqbal Khatoon

## Trouble while downloading the model. (Question)

Hi, Cristian, Iam really inspired by the model. A lot of appreciation for this amazing work. Bravo!! Iam having an issue while downloading this model, would you like to please send it to iqb.986@gmail.com.

## Posted about 1 year ago