Coronavirus Calculations Follow-Up

This is just a short follow-up of my previous post, Acceptable Risk, as well as another self-indulgent venture into amateur (irresponsible) statistics and forecasting.

In my previous post I estimated the total number of people that could die from coronavirus in the UK if the entire population was infected. In this post, I will apply the same logic to the world population.

All of the data used is from Worldometer. Certain countries and dependencies are excluded from the calculations because they either have no Coronavirus-related calculations, or they have no information regarding the total number of tests conducted, at least according to Worldometer (a notable example being China). Approximately six billion of the world’s population is included in the calculations, the results of which are then extrapolated to the true population.

According to Worldometer:

  • Of the 183 countries and dependencies sampled, 46,988,838 tests had been conducted (there is no information as to how many individuals have been tested more than once, so let’s assume it’s one test per person) from a sample size of 5,960,273,633 (which includes the people who have died as a result of COVID)
  • This means that approximately 0.8% of the world has been tested
  • Of those tested, there have been 4,031,583 total positive cases
  • If we assume that the sample is perfectly representative of the global population, and that if we tested the entire sample population that the infection rate would be the same, then we can extrapolate and assume that the true total number of cases is 511,383,956
  • We have a rough idea of how many people have died (rough because of potential under-reporting in certain cases, and false attribution of COVID to death in other cases), which is 275,841
  • As a percentage of the “true” total number of cases, this is a mortality rate of approximately 0.054% (however, this is likely to be an underestimation, as this calculation only takes into account deaths that have already occurred, but there are still many active cases where individuals have neither recovered nor died, but we know with almost absolute certainty that they will not all recover, therefore the death rate from the current infected population is likely to be higher)
  • So, if the actual entire global population (including the number of people that have already died as a result of COVID) were to be infected by Coronavirus, and 0.054% were to die as a result, then that would be total death toll of 4,198,585
  • This would make it the third highest cause of mortality in the world, after cardiovascular diseases and cancers, and the greatest communicable cause of death (according to numbers from 2017, released by the Institute for Health Metrics and Evaluation, founded by the Bill and Melinda Gates Foundation)
  • “Flattening the curve” does not mean completely stopping the disease in its tracks, rather, it means preventing needless deaths from hospital overcrowding, but acknowledging that a significant number of people will unavoidably die as a result of the coronavirus, unless a vaccine or some sort of treatment to alleviate the worst symptoms is developed



  • I chose to include countries and dependencies that had zero deaths because, despite this being fairly suspicious in some cases and potentially the result of an imperfect testing and diagnosing infrastructure, there is a possibility that many of these territories are either very remote and are therefore not highly exposed to the virus, or that their populations simply do not suffer as severe symptoms, either due to genetic or lifestyle factors
  • The countries and dependencies that were not included for the previously mentioned reasons were: American Samoa, Cook Islands, Cote d’Ivoire, Guam, Kiribati, Marshall Islands, Lesotho, Micronesia, Nauru, Niue, North Korea, Northern Mariana Islands, Palau, Puerto Rico, Saint Barthelemy, Saint Helena, Samoa, Solomon Islands, Tokelau, Tonga, Turkmenistan, Tuvalu, US Virgin Islands, Vanuatu, Wallis and Futuna, Anguilla, Burkina Faso, Cameroon, Chad, China, Comoros, Democratic Republic of the Congo, Eritrea, French Guiana, Guadeloupe, Guinea, Liberia, Macao, Martinique, Monaco, Nicaragua, Saint Martin, Saint Pierre Miquelon, Seychelles, Sierra Leone, Somalia, St. Barth, Sudan, Syria, Tajikistan, Tanzania, Vatican City, and Western Sahara
  • All data and calculations used can be found here
  • There was no significant correlation found between population density and total number of cases ( Pearson Correlation Coefficient of -0.03311181692)
  • Unnecessary disclaimer: I am not a virologist, epidemiologist, statistician, mathematician, medical professional, or appropriately qualified in any way. I’m just interested

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