, being ‘x’ a specific territory.
Abstract: Here I propose a Mathematical Coefficient to easily analyze Covid-19 incidence and evolution in different territories, allowing fair comparisons. The final goal is to provide a tool to avoid biased and unfair information, showing transparent and easy data in Media and Public Administration.
On October 12, 2020, the UK registered 17.232 new Covid-19 cases. The Spanish region of Aragon notified 357 cases (both data were given on October 13, 2020). At first sight, it seems that Aragon is having much better numbers than the UK, but if we take into consideration the total population of each territory -and we should- that is no longer the case. Aragon comprises 1,328,753 people, while the UK comprises 66,796,807 people, so that may explain the initial difference in the number of positive cases. A good measure to take into consideration the total population is to divide the number of positive cases by the total population:Aragon presented slightly worse numbers than the UK on October 12. However, the total population is not the only parameter we may consider if we want to be fair when analyzing and comparing. PCR tests are another hotspot, as some places are testing more than others. It is clear than the more testing in a territory, the more positive cases. Similar, a good measure to take into account the number of PCR tests done is to divide the total number of positives by the number of PCRs done:Aragon is depicting much worse figures. However, with this other measure we forget about the total population.
My proposal gathers these three different parameters: number of positive cases, total population and testing numbers. Coefficient of Joven-Romero is a number between 0 and 1, in which the closer to 0, the better, while the closer to 1, the worse: 0 ≤ CJR(x) ≤ 1. Note that 1 would mean that all the population in a territory have been tested and all of them have got positive Covid-19 results. On October 12, Aragon had a Coefficient of Joven-Romero of 0.0070606316 and the UK had a Coefficient of Joven-Romero of 0.0045051869. That means that Aragon had a 63.80713731% more Covid-19 impact that day (CJR(UK) / CJR(Aragon)). Public Administration and Medical Experts would establish limits and thresholds in this Coefficient of Joven-Romero in order to declare different Covid-19 impact levels, and subsequently, different measures.
Other parameters like the number of casualties or the ICU units occupied by Covid-19 patients may be considered too. However, they are not easy to establish: there are different criteria for ICU, some Covid-19 deceased patients presented other diseases, additional data are difficult to obtain in some territories, the weight these other factors must have in the final formula is debatable, etc.
The purpose of this coefficient is to easily communicate accurate information that allows fair and precise analysis and comparison. Coefficient of Joven-Romero is not addressed to Mathematicians, Statisticians or even Scientists in general, but to Media and Public Administration in order to avoid the spread of biased or unfair data, and to facilitate easy but accurate information transmission on Covid-19. According to this coefficient and this information, different Covid-19 impact levels and subsequent measures might be established.
Notes:
- I only consider PCR testing as that is currently the only feasible testing method to detect Covid-19.
- At the beginning, I was willing to exemplify the proposed Coefficient of Joven-Romero with data from the UK and Spain. Unfortunately, Spanish official data are incomplete and unclear, and that made impossible such comparison. Then, I decided to use the Aragonese official data, well collected in the below-stated link.
Sources
https://coronavirus.data.gov.uk/ (UK Official Covid-19 Data) [Accessed on October 13]
https://transparencia.aragon.es/COVID19 (Aragon Official Covid-19 Data) [Accessed on October 13]
OpenEdition le sugiere que cite este post de la siguiente manera:
Marco Antonio Joven-Romero (14 de octubre de 2020). Coefficient of Joven-Romero: a fair tool to analyze Covid-19 impact. ESTRICALLA. Recuperado 5 de diciembre de 2024 de https://doi.org/10.58079/ojmg