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Aktualʹnaâ Infektologiâ
Article . 2019
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The use of mathematical modeling in the epidemiological surveillance of acute intestinal infections

Authors: N.G. Malysh; O.V. Kuzmenko; M.D. Chemych; S.I. Doan;

The use of mathematical modeling in the epidemiological surveillance of acute intestinal infections

Abstract

Background. Acute intestinal infections remain actual diseases for many countries of the world now, especially with middle and low income, in spite of improving sanitary and hygienic conditions of living, drinking water quality. Therefore, the system of epidemiological surveillance of acute intestinal infections needs to be improved. Based on the study of the dynamics of morbidity, risk factors, new ways to improve the epidemiological surveillance of acute intestinal infections were offered. Materials and methods. The paper presents the results of studies on the dynamics of the incidence of schigellosis, salmonellosis, diarrheal escherichiosis, demographic statistics and indicators of sanitary-hygienic monitoring for 2001–2017 in the Sumy region. Epidemiological and statistical methods of research, multivariate analysis were applied. Results. It was found that in the studied period, the incidence rates for shigellosis decreased from 42.3 per 100,000 population to 0.5, salmonellosis — increased from 13.0 to 17.7, diarrheal escherichiosis — varied at 3.70–2.20. At the same time, the population of the region has decreased from 1,317.8 thousand people in 2001 to 1,104.5 in 2017, the population density — from 55.3 (persons per 1 km2) to 46.3, the natural population movement — from –11.1 to –8.6 %, migratory movement — from – 5.2 to –0.7 %, the prevalence of digestive diseases has increased — from 13,004.0 per 100,000 people to 17,124.89. It has been found that in those examined for prophylactic purposes, the frequency of shigella and salmonella isolation decreased from 146.5 and 20.7 per 100,000 population to 0, enteropathogenic colibacilli — from 671.4 to 24.9. Results of sanitary-hygienic monitoring of food and drinking water showed that the frequency of detection of “substandard” water samples was 8.1 %, meat and meat products — 5.2 %, milk and dairy products — 4.3 %, sugar and confectionery products — 5.6 %, eggs — 4.2 %. The frequency of isolation of sanitary and indicative microflora from equipment, the hands of workers in public catering facilities was 4.7 %, food enterprises and enterprises for the production of confectionery with cream — 3.4 and 1.03 %, respectively, dairies — 1.6 %. Statistical analysis conducted with the help of Statistica software package showed the dependence of the morbidity on the influence of risk factors, which can be presented as a linear multivariate regression equation. Using predictive values of risk factors, as well as regression equations, predictive values of morbidity were obtained for the most significant forms of acute intestinal infections. In 2018–2020, an increase in the incidence rate of shigellosis, salmonella, diarrheal escherichiosis is expected. Among the risk factors, the greatest impact will be the increase in population density, the prevalence of digestive diseases, migration of the population, “substandard” microbiological indicators of meat and meat products. Conclusions. Thus, identifying risk factors for unfavorable epidemiological situation and using a mathematical model to predict the development of the epidemic process of acute intestinal infections, taking into account demographic indicators and socio-hygienic monitoring data, can be an important part of the system for improving epidemiological surveillance.

Keywords

diarrheal escherichiosis, salmonellosis, epidemiological surveillance, risk factors, prognosis, Infectious and parasitic diseases, RC109-216, shigellosis

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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