Mathematical Model for Forecasting the Influence of Atmospheric Pollution on Population Morbidity in Stara Zagora Municipality (Bulgaria)

Abstract

AIM:This paper aims to create a mathematical model for forecasting the morbidity of the population in the Republic of Bulgaria and the Stara Zagora Municipality in particular as a consequence of the atmospheric pollution.SUBJECTS AND METHODS:This model is based on a formula which determines the correlation between the average annual concentrations of atmospheric pollutants SO2, PM10, Pb aerosols, NO2 and H2S) and the morbidity of the population based on the number of people who visited their GPs in a relation with a chronic health problem or emergency condition and the number of hospitalisations in two age groups (newborn to 17 years olds and 18 and older) as well as for the entire population in the period 2009-2013, making it possible to predict morbidity levels.RESULTS:The expected morbidity level predictions based on the number of people who visited their GPs in Municipality are lower, while hospitalisation level predictions are higher. This model has been created and tested and is applicable in all residential areas.CONCLUSIONS:A new, very sensitive, mathematical model has been created and tested (average margin of error from 0.61% to 2.59%) and is applicable in all residential areas.

Short-term effects of air pollution on hospital admissions for cardiovascular diseases and diabetes mellitus in Sofia, Bulgaria (2009–2018)

“…To our knowledge, this is the first study in Bulgaria to model short-term associations between air pollution and IHD, CI, and T2DM hospitalisations that covers such a long period of ten years. In their reports of short-term associations between air pollution and cardiovascular diseases, earlier studies in the country relied on bivariate analyses, which are not ideally suited for modelling count data and which ignore time trends and autocorrelations in time series (19)(20)(21).…”

“…Against this backdrop, the lack of robust studies in Bulgaria is surprising. To our knowledge, earlier time-series research used suboptimal analytical approaches and covered relatively short periods of time (19)(20)(21).…”