Open AccessNovel Indicator to Ascertain the Status and Trend of COVID-19 Spread: Modeling Study
Author(s) -
Takashi Nakano,
Yoichi Ikeda
Publication year - 2020
Publication title -
jmir. journal of medical internet research/journal of medical internet research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.446
H-Index - 142
eISSN - 1439-4456
pISSN - 1438-8871
DOI - 10.2196/20144
Subject(s) - gompertz function , covid-19 , statistics , mathematics , econometrics , pandemic , logarithm , value (mathematics) , demography , constant (computer programming) , demographic economics , economics , computer science , medicine , mathematical analysis , sociology , disease , pathology , infectious disease (medical specialty) , programming language
Background In the fight against the pandemic of COVID-19, it is important to ascertain the status and trend of the infection spread quickly and accurately. Objective The purpose of our study is to formulate a new and simple indicator that represents the COVID-19 spread rate by using publicly available data. Methods The new indicator K is a backward difference approximation of the logarithmic derivative of the cumulative number of cases with a time interval of 7 days. It is calculated as a ratio of the number of newly confirmed cases in a week to the total number of cases. Results The analysis of the current status of COVID-19 spreading over countries showed an approximate linear decrease in the time evolution of the K value. The slope of the linear decrease differed from country to country. In addition, it was steeper for East and Southeast Asian countries than for European countries. The regional difference in the slope seems to reflect both social and immunological circumstances for each country. Conclusions The approximate linear decrease of the K value indicates that the COVID-19 spread does not grow exponentially but starts to attenuate from the early stage. The K trajectory in a wide range was successfully reproduced by a phenomenological model with the constant attenuation assumption, indicating that the total number of the infected people follows the Gompertz curve. Focusing on the change in the value of K will help to improve and refine epidemiological models of COVID-19.