| Issue |
ITM Web Conf.
Volume 31, 2020
International Conference “Mathematical Modelling in Biomedicine” 2019
|
|
|---|---|---|
| Article Number | 03002 | |
| Number of page(s) | 6 | |
| Section | Epidemiology | |
| DOI | https://doi.org/10.1051/itmconf/20203103002 | |
| Published online | 09 March 2020 | |
Analyzing the spatial distribution of individuals predisposed to arterial hypertension in Saint Petersburg using synthetic populations
ITMO University, 49 Kronverksky Pr., St. Petersburg, 197101, Russia
∗ e-mail: vnleonenko@yandex.ru
Arterial hypertension (AH) is one of the most common cardiovascular diseases, and it can lead to serious complications. To optimize the delivery of patients exposed to AH to medical institutions and thus to curtail mortality in Russian cities caused by the consequences of hypertension, it is necessary to estimate the number of potential patients, along with their spatial distribution. This paper presents a method which uses synthetic population data to assess the spatial distribution of individuals potentially prone to arterial hypertension. The risk of arterial hypertension of an individual is calculated based on its demographic characteristics (age and gender). Using Saint Petersburg as a case study, we demonstrate that the mentioned approach makes it possible to perform predictions of AH cases distribution in absence of real data on hypertension status of the individuals. The results of the study will be used to assess the input flows of patients to healthcare facilities and optimize their workflow.
© The Authors, published by EDP Sciences, 2020
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.