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Online Journal of Public Health Informatics
Article . 2017 . Peer-reviewed
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Online Journal of Public Health Informatics
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PubMed Central
Article . 2017
License: CC BY NC
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Application of GIS for Optimization of Epidemiological Monitoring

Authors: Malakhov, Volodymyr; Zavialkin, Volodymyr; Tarasyuk, Oleksandra; Smolnytska, Valentyna;

Application of GIS for Optimization of Epidemiological Monitoring

Abstract

IntroductionTechnology that combines traditional manipulations with databasesand complete visualization of geographic (spatial) analysis employingmaps has been developed in order to explore the possibilities forGeographical Information Systems (GIS) to be used in sanitaryand epidemiological surveillance system based on the analysis ofmorbidity and identification of influence of hazardous chemicalenvironmental factors on human health.MethodsGraphical analytic method of information processing allowedvisual establishing of mathematically determined cause-and-effectrelationships between levels of air chemical pollution and morbiditylevels for purulent bacterial meningitis.ResultsCalculated average annual contaminations of atmosphere of 20administrative rayons and seven cities of Lviv oblast with carbonoxide, lead, sulfur dioxide, and dust during the period 2006-2014were the objects of the study. During a year, 1,920 air samples werecollected per each ingredient for each rayon and city according tolaboratory data of facilities of the State Sanitary and EpidemiologicalService in Lviv oblast. Average annual levels of the chemicalsubstances were determined within the M.A.C. in all rayons and cities.However, 4-6% of individual samples in the rayons and 8-10% ofindividual samples in the cities exceeded the allowed concentrations,which imposed a real ecological danger.Fig. 1.Levels of carbon oxide air contamination within rayons ofLviv oblastMorbidity intensity rates for purulent bacterial meningitis weredetermined for the same period according to statistical reports oninfectious disease morbidity in Lviv oblast. In different years, humanmorbidity fluctuated from 0.7 to 2.3 per 100 thousand of populationin the oblast.The study found the correlation between the concentrations ofcarbon monoxide, lead, sulfur dioxide, and dust in the air and levels ofincidence of bacterial meningitis in people in the cities of Lviv oblastwith 1,092 thousand inhabitants, which compose 42.3% of all oblastpopulation. Correlation coefficients are r = 0.78 (p<0.001), r = 0.70(p<0.001), r = 0.51 (p<0.005), and r =0.68 (p<0.02), respectively.Fig. 2.Correlation dependencies between air contamination andpopulation morbidity rates for purulent bacterial meningitis withinrayons of Lviv oblast.The search for a correlation between chemical contaminationof atmosphere and the morbidity level the rayon population of theoblast for purulent bacterial meningitis testified the existence of astatistically significant dependence between the level of morbidityfor all population layers and atmosphere contamination with sulfurdioxide, lead, carbon monoxide, and dust. The correlation coefficientsare r = 0.62 (p<0.002), r = 0.52 (p<0.005), r = 0.63 (p<0.005), r = 0.56(p<0.05), correspondingly.The study found the correlation between the concentrationsof sulfur dioxide, and lead in the air of Lviv oblast and levels ofincidence of purulent bacterial meningitis in children. Correlationcoefficients are r = 0.55 (p<0.05) and r = 0.57 (p<0.001), respectively.ConclusionsUsing GIS approach, the study resulted in the development ofmedical-geographical maps of administrative rayons of Lviv oblast.The maps include peculiarities for each year of surveillance. Cause-and-effect relationships between the levels of the anthropogenicpollution of the air basin of Lviv oblast and morbidity levels forpurulent bacterial meningitis for the oblast population have beenspatially and temporally visualized as a study result.

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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
Green
gold