Modifying impact of environmental factors on the course of an epidemic process

Abstract

Introduction. It is necessary to establish peculiarities and regularities of COVID-19 infection; this task requires further research on how to formalize and build spatial-temporal models of the infection spread. This article focuses on determining non-infectious factors that can modify the epidemic process caused by the COVID-19 coronavirus for further substantiation of integrated solutions that are necessary to ensure sanitary-epidemiological welfare of the RF population. Materials and methods. Our study involved analyzing regularities of regional differentiation in parameters introduced into mathematical models. These models described how the epidemic process developed in RF regions depending on modifying non-infectious factors identified by modelling the dynamics of spread of SARS-CoV-2 delta strain. These modifying factors included anti-epidemic activities; sanitary-epidemiological, sociodemographic, and economic conditions in a region; weather and climate; public healthcare systems and people’s lifestyles in RF regions over 2020-2021. The dynamics of the epidemic process was modelled by using the conventional SIR-model. Relationships between parameters introduced into the model of the epidemic process and modifying regional conditions were examined by using correlation-regression analysis. Results. The modelling made it possible to identify priority risk factors that modified COVID-19 spread authentically (p<0.05) and explained regional differences in intensity of contagion, recovery and lethality. We established that population coverage with vaccination, especially among people aged 31-40 years, had the greatest authentic positive influence on the decline of reproduction index (R0) of the virus (r=-0.37). An increase in monthly average temperatures in autumn and winter as well as over a year made for people moving faster from the susceptible to infected category (r=0.21-0.22). Growing sun insolation over a year, especially in summer, resulted in slower movement of susceptible people into the infected category (r=-0.02-(-0.23)). Next, several sanitary-epidemiological indicators authentically made the infection spread faster; they were improper working conditions (not conforming to the safety standards as per physical indicators) and ambient air quality in settlement not corresponding to the hygienic standards as per chemical indicators and noise (r=0.29-0.24). Recovery took longer in regions where alcohol consumption was comparatively higher (r=-0.32). Limitations. The limitations of the study include modelling the epidemic process using the standard SIR model; limited set of indicators and period of analysis. Conclusions. The existing regional differentiation in development of specific stages in the epidemic process related to the COVID-19 delta strain occurs due to complex interactions and influence exerted by modifying factors that create a certain multi-level and multi-component system. This system is able to transform the epidemic process either potentiating it or slowing it down.