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Our Published Predications

We’re using the models listed below with their formulas and tracking.

We’ll publish against data that we get updated as actuals to predict for USA and other regions.

Updated every few weeks typically.

Model Formulas
  • $new_infected = round(max(0, (min(($remaining_population – $unkillable_elite_in_bunkers – $total_infected), ($old_new_infected * (($infection_rate – ($current_day / $incubation_days) * $burnout_rate)))))));
  • $new_deaths = round(min($remaining_population,($new_infected * $mortality_rate) + ($old_new_infected * $mortality_complicator)));
  • $total_infected = min($remaining_population – $unkillable_elite_in_bunkers, ($new_infected + ($total_infected – $new_deaths)));
  • $remaining_population = max($unkillable_elite_in_bunkers,($remaining_population – $new_deaths));

Spread Prediction

Historical Data 

Spread Summary

Historical Pandemic

New Infected Deaths

New Infected & New Hospitalizations

Total Infected Deaths

Workforce Disruption

Disease Severity

Death By Age Group

Disease Symptom Types

Population Decline

Total Deaths

Spread Prediction

Used to display a table of estimated spreading of a viral pandemic. You can use the following shortcode parameters:

  1. ‘starting_population’ => The population to start the equation with. Default:’7727439400′
  2. ‘unkillable_elite_in_bunkers’ => The population that will not die because they are immune or hidden from the disease. Default:’50000′
  3. ‘start_date’ => The date when the pandemic starts. Default:’01-01-2020′
  4. ‘initial_infections’ => The count of the initially infected people. Default:’2′
  5. ‘infection_rate’ => The rate of infection – how many newly infected people each infected will generate. Default:’2.45′
  6. ‘incubation_days’ => The incubation period of the disease (in days). Default:’10’
  7. ‘mortality_rate’ => The mortality rate of the disease (in percentage). Default:’3′
  8. ‘mortality_complicator’ => The mortality complicator of the disease (in percentage). This kicks in when many new infected are being generated in a short period of time (no more free space in hospitals). Default:’10’
  9. ‘burnout_rate’ => The rate after which the disease will be stopped (cured or self contained) – (in percentage). Default:’4′
  10. ‘iteration_count’ => The number of iterations to display. Default:’50’
  11. ‘date_format’ => The format of the date. Default:’Y-m-d’
Historical Data Prediction

To display a table of estimated spreading of a viral pandemic. The data is based on historical data from JHU, based on which, we’ll estimate a future outcome for the pandemic. 

  1. ‘target_location’ => Select the starting location of the simulation. List of possible locations are from here: https://coronadatascraper.com/#timeseries-byLocation.json – Default is:’ITA’
  2. ‘unkillable_elite_in_bunkers’ => The population that will not die because they are immune or hidden from the disease. Default:’50000′
  3. ‘infection_rate’ => The rate of infection – how many newly infected people each infected will generate. Default:’1.3′
  4. ‘mortality_rate’ => The mortality rate of the disease (in percentage). Default:’2′
  5. ‘mortality_complicator’ => The mortality complicator of the disease (in percentage). This kicks in when many new infected are being generated in a short period of time (no more free space in hospitals). Default:’2′
  6. ‘burnout_rate’ => The rate after which the disease will be stopped (cured or self contained) – (in percentage). Default:’3.5′
  7. ‘iteration_count’ => The number of iterations to display. Default:’50’
Spread summary

To display a table of summaries of outcome (and initial input) of a viral pandemic.

  1. ‘starting_population’ => The population to start the equation with. Default:’7727439400′
  2. ‘unkillable_elite_in_bunkers’ => The population that will not die because they are immune or hidden from the disease. Default:’50000′
  3. ‘start_date’ => The date when the pandemic starts. Default:’01-01-2020′
  4. ‘initial_infections’ => The count of the initially infected people. Default:’2′
  5. ‘infection_rate’ => The rate of infection – how many newly infected people each infected will generate. Default:’2.45′
  6. ‘incubation_days’ => The incubation period of the disease (in days). Default:’10’
  7. ‘mortality_rate’ => The mortality rate of the disease (in percentage). Default:’3′
  8. ‘mortality_complicator’ => The mortality complicator of the disease (in percentage). This kicks in when many new infected are being generated in a short period of time (no more free space in hospitals). Default:’10’
  9. ‘burnout_rate’ => The rate after which the disease will be stopped (cured or self contained) – (in percentage). Default:’4′
  10. ‘include_init_data’ => Do you want to display initial (input) date in the table? Default:’true’
  11. ‘init_data_header_texts’ => A comma separated list of header texts for the table. Default:’Starting Population,Immune Population,Start Date,Initial Infections,Infection Rate,Incubation Days,Mortality Rate,Mortality Complicator,Burnout Rate,Iteration Count’
  12. ‘include_final_data’ => Do you want to display final (resulting) date in the table? Default:’true’
  13. ‘final_data_header_texts’ => A comma separated list of header texts for the table. Default:’Population At Risk,Total Infected,Total Recovered,Total Deaths,Total Uninfected,Population Alive’
  14. ‘date_format’ => The format of the date. Default:’Y-m-d’
Historical Pandemic prediction

To display a chart to show and compare values for estimated cases (new infected, total infected, new deaths, total deaths, population decline) based on the historical data from JHU, of the COVID-19 viral pandemic.

  1. ‘target_location’ => Select the starting location of the simulation. Lst of possible locations are from here: https://coronadatascraper.com/#timeseries-byLocation.json – Default is:’ITA’
  2. ‘chart_type’ => Select the type of chart to show. Possible values are: newinfected, newdead, totalinfected, totaldead, remainingpopulation. Default:’newinfected’
  3. ‘unkillable_elite_in_bunkers’ => The population that will not die because they are immune or hidden from the disease. Default:’50000′
  4. ‘infection_rate’ => The rate of infection – how many newly infected people each infected will generate. Default:’1.3′
  5. ‘mortality_rate’ => The mortality rate of the disease (in percentage). Default:’2′
  6. ‘mortality_complicator’ => The mortality complicator of the disease (in percentage). This kicks in when many new infected are being generated in a short period of time (no more free space in hospitals). Default:’2′
  7. ‘burnout_rate’ => The rate after which the disease will be stopped (cured or self contained) – (in percentage). Default:’3.5′
  8. ‘iteration_count’ => The number of iterations to display. Default:’50’
  9. ‘date_format’ => The format of the date. Default:’Y-m-d’
New Infected Deaths

To display a chart to show and compare values for estimated new infected cases and new deaths for a time period, of a viral pandemic.

  1. ‘starting_population’ => The population to start the equation with. Default:’7727439400′
  2. ‘unkillable_elite_in_bunkers’ => The population that will not die because they are immune or hidden from the disease. Default:’50000′
  3. ‘start_date’ => The date when the pandemic starts. Default:’01-01-2020′
  4. ‘initial_infections’ => The count of the initially infected people. Default:’2′
  5. ‘infection_rate’ => The rate of infection – how many newly infected people each infected will generate. Default:’2.45′
  6. ‘incubation_days’ => The incubation period of the disease (in days). Default:’10’
  7. ‘mortality_rate’ => The mortality rate of the disease (in percentage). Default:’3′
  8. ‘mortality_complicator’ => The mortality complicator of the disease (in percentage). This kicks in when many new infected are being generated in a short period of time (no more free space in hospitals). Default:’10’
  9. ‘burnout_rate’ => The rate after which the disease will be stopped (cured or self contained) – (in percentage). Default:’4′
New Infected Hospitalizations

To display a chart to show and compare values for estimated new infected cases and new hospitalized patients for a time period, of a viral pandemic. 

  1. ‘starting_population’ => The population to start the equation with. Default:’7727439400′
  2. ‘hospitalization_rate’ => The hospitalization rate of the disease (in percentage). Default:’20’
  3. ‘unkillable_elite_in_bunkers’ => The population that will not die because they are immune or hidden from the disease. Default:’50000′
  4. ‘start_date’ => The date when the pandemic starts. Default:’01-01-2020′
  5. ‘initial_infections’ => The count of the initially infected people. Default:’2′
  6. ‘infection_rate’ => The rate of infection – how many newly infected people each infected will generate. Default:’2.45′
  7. ‘incubation_days’ => The incubation period of the disease (in days). Default:’10’
  8. ‘mortality_rate’ => The mortality rate of the disease (in percentage). Default:’3′
  9. ‘mortality_complicator’ => The mortality complicator of the disease (in percentage). This kicks in when many new infected are being generated in a short period of time (no more free space in hospitals). Default:’10’
  10. ‘burnout_rate’ => The rate after which the disease will be stopped (cured or self contained) – (in percentage). Default:’4′
  11. ‘iteration_count’ => The number of iterations to display. Default:’50’
  12. ‘date_format’ => The format of the date. Default:’Y-m-d’
Total Infected Deaths

To display a chart to show and compare values for estimated total infected cases and total deaths for a time period, of a viral pandemic. 

  1. ‘starting_population’ => The population to start the equation with. Default:’7727439400′
  2. ‘unkillable_elite_in_bunkers’ => The population that will not die because they are immune or hidden from the disease. Default:’50000′
  3. ‘start_date’ => The date when the pandemic starts. Default:’01-01-2020′
  4. ‘initial_infections’ => The count of the initially infected people. Default:’2′
  5. ‘infection_rate’ => The rate of infection – how many newly infected people each infected will generate. Default:’2.45′
  6. ‘incubation_days’ => The incubation period of the disease (in days). Default:’10’
  7. ‘mortality_rate’ => The mortality rate of the disease (in percentage). Default:’3′
  8. ‘mortality_complicator’ => The mortality complicator of the disease (in percentage). This kicks in when many new infected are being generated in a short period of time (no more free space in hospitals). Default:’10’
  9. ‘burnout_rate’ => The rate after which the disease will be stopped (cured or self contained) – (in percentage). Default:’4′
  10. ‘iteration_count’ => The number of iterations to display. Default:’50’
  11. ‘date_format’ => The format of the date. Default:’Y-m-d’
Total Workforce Disruption

To display a chart to show the disruption of the workforce, caused by people getting sick and not being able to work.

  1. ‘starting_population’ => The population to start the equation with. Default:’7727439400′
  2. ‘workforce_percentage’ => The percentage of the population that is in the active workforce. Default:’60’
  3. ‘unkillable_elite_in_bunkers’ => The population that will not die because they are immune or hidden from the disease. Default:’50000′
  4. ‘start_date’ => The date when the pandemic starts. Default:’01-01-2020′
  5. ‘initial_infections’ => The count of the initially infected people. Default:’2′
  6. ‘infection_rate’ => The rate of infection – how many newly infected people each infected will generate. Default:’2.45′
  7. ‘incubation_days’ => The incubation period of the disease (in days). Default:’10’
  8. ‘mortality_rate’ => The mortality rate of the disease (in percentage). Default:’3′
  9. ‘mortality_complicator’ => The mortality complicator of the disease (in percentage). This kicks in when many new infected are being generated in a short period of time (no more free space in hospitals). Default:’10’
  10. ‘burnout_rate’ => The rate after which the disease will be stopped (cured or self contained) – (in percentage). Default:’4′
  11. ‘iteration_count’ => The number of iterations to display. Default:’50’
  12. ‘date_format’ => The format of the date. Default:’Y-m-d’
Disease Severity

To display a chart to show the number of asymptomatic, severe and critical cases of the disease. 

  1. ‘starting_population’ => The population to start the equation with. Default:’7727439400′
  2. ‘unkillable_elite_in_bunkers’ => The population that will not die because they are immune or hidden from the disease. Default:’50000′
  3. ‘start_date’ => The date when the pandemic starts. Default:’01-01-2020′
  4. ‘initial_infections’ => The count of the initially infected people. Default:’2′
  5. ‘infection_rate’ => The rate of infection – how many newly infected people each infected will generate. Default:’2.45′
  6. ‘incubation_days’ => The incubation period of the disease (in days). Default:’10’
  7. ‘mortality_rate’ => The mortality rate of the disease (in percentage). Default:’3′
  8. ‘mortality_complicator’ => The mortality complicator of the disease (in percentage). This kicks in when many new infected are being generated in a short period of time (no more free space in hospitals). Default:’10’
  9. ‘burnout_rate’ => The rate after which the disease will be stopped (cured or self contained) – (in percentage). Default:’4′
  10. ‘iteration_count’ => The number of iterations to display. Default:’50’
  11. ‘date_format’ => The format of the date. Default:’Y-m-d’
Deaths By Age Group

To display a chart to show the number of deaths, by each age group.

  1. ‘starting_population’ => The population to start the equation with. Default:’7727439400′
  2. ‘unkillable_elite_in_bunkers’ => The population that will not die because they are immune or hidden from the disease. Default:’50000′
  3. ‘start_date’ => The date when the pandemic starts. Default:’01-01-2020′
  4. ‘initial_infections’ => The count of the initially infected people. Default:’2′
  5. ‘infection_rate’ => The rate of infection – how many newly infected people each infected will generate. Default:’2.45′
  6. ‘incubation_days’ => The incubation period of the disease (in days). Default:’10’
  7. ‘mortality_rate’ => The mortality rate of the disease (in percentage). Default:’3′
  8. ‘mortality_complicator’ => The mortality complicator of the disease (in percentage). This kicks in when many new infected are being generated in a short period of time (no more free space in hospitals). Default:’10’
  9. ‘burnout_rate’ => The rate after which the disease will be stopped (cured or self contained) – (in percentage). Default:’4′
  10. ‘iteration_count’ => The number of iterations to display. Default:’50’
  11. ‘date_format’ => The format of the date. Default:’Y-m-d’
Disease Symptom Types

To display a chart to show the number of people having different symptoms for the COVID-19 disease. 

  1. ‘starting_population’ => The population to start the equation with. Default:’7727439400′
  2. ‘unkillable_elite_in_bunkers’ => The population that will not die because they are immune or hidden from the disease. Default:’50000′
  3. ‘start_date’ => The date when the pandemic starts. Default:’01-01-2020′
  4. ‘initial_infections’ => The count of the initially infected people. Default:’2′
  5. ‘infection_rate’ => The rate of infection – how many newly infected people each infected will generate. Default:’2.45′
  6. ‘incubation_days’ => The incubation period of the disease (in days). Default:’10’
  7. ‘mortality_rate’ => The mortality rate of the disease (in percentage). Default:’3′
  8. ‘mortality_complicator’ => The mortality complicator of the disease (in percentage). This kicks in when many new infected are being generated in a short period of time (no more free space in hospitals). Default:’10’
  9. ‘burnout_rate’ => The rate after which the disease will be stopped (cured or self contained) – (in percentage). Default:’4′
  10. ‘iteration_count’ => The number of iterations to display. Default:’50’
  11. ‘date_format’ => The format of the date. Default:’Y-m-d’
Population Decline

To display a chart to show the amount of population decline, for a time period, in case of a viral pandemic.

  1. ‘starting_population’ => The population to start the equation with. Default:’7727439400′
  2. ‘unkillable_elite_in_bunkers’ => The population that will not die because they are immune or hidden from the disease. Default:’50000′
  3. ‘start_date’ => The date when the pandemic starts. Default:’01-01-2020′
  4. ‘initial_infections’ => The count of the initially infected people. Default:’2′
  5. ‘infection_rate’ => The rate of infection – how many newly infected people each infected will generate. Default:’2.45′
  6. ‘incubation_days’ => The incubation period of the disease (in days). Default:’10’
  7. ‘mortality_rate’ => The mortality rate of the disease (in percentage). Default:’3′
  8. ‘mortality_complicator’ => The mortality complicator of the disease (in percentage). This kicks in when many new infected are being generated in a short period of time (no more free space in hospitals). Default:’10’
  9. ‘burnout_rate’ => The rate after which the disease will be stopped (cured or self contained) – (in percentage). Default:’4′
  10. ‘iteration_count’ => The number of iterations to display. Default:’50’
  11. ‘date_format’ => The format of the date. Default:’Y-m-d’
Total Deaths

To display a chart to show the amount of total deaths count, for a time period, in case of a viral pandemic. 

  1. ‘starting_population’ => The population to start the equation with. Default:’7727439400′
  2. ‘unkillable_elite_in_bunkers’ => The population that will not die because they are immune or hidden from the disease. Default:’50000′
  3. ‘start_date’ => The date when the pandemic starts. Default:’01-01-2020′
  4. ‘initial_infections’ => The count of the initially infected people. Default:’2′
  5. ‘infection_rate’ => The rate of infection – how many newly infected people each infected will generate. Default:’2.45′
  6. ‘incubation_days’ => The incubation period of the disease (in days). Default:’10’
  7. ‘mortality_rate’ => The mortality rate of the disease (in percentage). Default:’3′
  8. ‘mortality_complicator’ => The mortality complicator of the disease (in percentage). This kicks in when many new infected are being generated in a short period of time (no more free space in hospitals). Default:’10’
  9. ‘burnout_rate’ => The rate after which the disease will be stopped (cured or self contained) – (in percentage). Default:’4′
  10. ‘iteration_count’ => The number of iterations to display. Default:’50’
  11. ‘date_format’ => The format of the date. Default:’Y-m-d’
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