About the Numbers
Numbers matter. It has been said, “If you can’t make a number out of it, you don’t understand it.” Science is based on evidence and numbers are the evidence. They matter on a large and small scale. If a scientist makes a discovery that saves only a few lives, and it affects you, there is ample cause for family and friends to rejoice.
Numbers matter on a large scale as well. In the book, Scientists Greater than Einstein,
Prior to our website, humans have tended to count the number of deaths far more often than the number of lives saved. There is logic to this. By focusing on deaths, scientists know what diseases need further research. However, we miss a key point by not counting lives saved as well. Many people believe living a long and healthy life is simply a matter of luck or fate due to not getting an infectious disease or having good genetics. Few people realize the true power of science that has overcome disease and even genetic proclivity. We believe that if more people knew what science has accomplished, perhaps health care research would become a priority leading to more saved lives. Then the half million Americans who die before age 65 each year due to disease might make it into old age.
We obtained the numbers from the best sources available, including the Centers for Disease Control (CDC) and the World Health Organization (WHO), but often good data was lacking. So our numbers are not exact, but they are reliable estimates and when we have erred, it is on the conservative side.
Reflect on the numbers and the progress heroic scientists have made. If you are an indefatigable statistics whiz, join our numbers committee. Join us as we celebrate both individual lives saved and millions of lives saved.
Before 1900 lifesaving statistics were not reliably kept. We refer to scientists of this era as ScienceHero Legends. We cannot directly count the numbers of lives these scientists saved, but we do pay tribute to their awesome insights, their everlasting contributions to humanity, and honor the lives they lived by providing profile pages for them without numbers.Determining the Number of Lives Saved
By Amy R. Pearce, PhD
As this project’s statistician, my task was to delineate figures that were in all practicality impossible to pinpoint. Consequently, each number represents a conservative estimate of lives saved for each of the ‘life savers’ based on the best available data and a common sense approach.
Whenever possible, I employed a consistent and logical multistep process. Both aggregated and disaggregated world population figures from the 20th century and beyond were used to gather the potential beneficiaries from each discovery and a timeline was established from its invention and first widespread use through 2008. I calculated lives saved based on published data from the most reputable, corroborative, and accessible evidence and resources (WHO, CDC, NIH, UNICEF and medical databases such as Medline, Lexus Nexus and PubMed), yet on occasion, these yielded insufficient data and alternate sources such as Internet websites and a variety of nonacademic literature were also considered. Software programs such as Excel and SPSS were used for calculations and graphics.
I found population data for countries with ready access to the “new” cure, and also mortality and morbidity statistics for targeted illnesses, then determined a percentage of this population that would logically have died without the intervention. For the most part, the information for the developed world (North America, Western Europe, parts of South America, Southeast Asia and certain other countries) was most accessible and reliable, and so the majority of calculations were extrapolated from these figures.
Statistics from the developing world were scarce, and if figures were not available, or could not be credibly inferred, they were not included in extrapolated figures. Hence, while many lives saved totals are astoundingly high, I believe each result is wholly conservative and likely underestimates the true number of beneficiaries.
"An approximate answer to the right problem is worth a good deal more than an exact answer to an approximate problem."
--John Tukey, PhD and statistician