Main Article Content
The study of epidemiological models are important because they help researchers to understand and propose possible strategies to combat any epidemic virus. Most of the research in those models, however, focuses on the response variable, modeling how it varies as a function of epidemiological parameters. In this paper, on the other hand, we focus on the explanatory variable ”time,” examining the critical points of the logistic model curve. These are: the maximum acceleration point(map), inflection point(ip), maximum deceleration point(mdp), and asymptotic deceleration point(adp). We first estimated a time series of the cases of people infected by COVID 19 as a function of time, and then used the cumulative estimates of the time series to fit a reparameterization of the logistic model. Data from China and Italy were used as an example, reporting the economic and political factors within each interval between the estimated critical points. The estimates of each critical point for China and Italy were respectively (map:34.93-50.92, ip:41.68-65.53;mdp:48.43-80.14;adp:57-94). This
methodology adds to the literature and shows researchers how the social, political, economic, and sanitary factors that were adopted in each of the countries influenced the difference of the intervals between the critical points in each country.
This work is licensed under a Creative Commons Attribution 4.0 International License.
Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).