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Myagkov Sergey Vladimirovich, Deputy Director Hydrometeorological Research Institute E-mail: [email protected] Tillakhodjaeva Zukhrakhon Djakhongirovna, senior researcher, Hydrometeorological Research Institute, Uzhydromet E-mail: [email protected]; [email protected]
RISK ASSESSMENT OF DISEASES IN THE CONDITIONS OF CLIMATE CHANGE
Abstract. In this article proposed methods which are included in the early warning system, that allows the timely development of adaptation measures to climate change in the health care system.
Keywords: climate change, risk assessment, Tashkent region, the spread of diseases, adaptation.
incision, since one part of the population see a doctor immediately, some only on the second or third day, and some only when a critical condition occurs.
To determine the statistical dependencies between the number of diseases and weather changes, we propose to use the expression:
N
(1)
Many studies on climate change focus on the sharp and anomalous rise in air temperature and changes in precipitation. Global climate change has led not only to an increase in air temperature, but also to the "imbalance" of climate systems. This means that, against the background of mild changes in the averaged characteristic (air temperature, precipitation), there is an increase in the number of extreme events. Precipitation begins to fall in the form of heavy rain, but then a long drought occurs. Thus, changes in climatic or averaged values are poorly expressed, but at the same time, an increase in the number of extreme (maximum and minimum) weather phenomena during the same period of instrumental observations is pronounced. These processes are most vividly observed in Central Asia, where the continental climate is preserved and, at the same time, an increase in the number of extreme weather events is observed.
Medical research confirms that in the state of public health there is also a great dependence on sudden changes in weather characteristics, especially for meteosensitive or weakened by chronic human diseases.
To adapt the health system to climate change, it is necessary to develop an early warning system for the risk of disease, depending on the dynamics of weather and climate factors in a particular region. The system of observation ofvarious types of diseases currently does not correspond to the system of instrumental observations of hydrometeorological parameters.
If hydrometeorological observations are carried out regularly and continuously, according to certain methods and standards, the medical statistics are based on the cases of the diseased. In some cases, the diseases are not fixed, since patients often prefer to self-medicate and acquire the appropriate medications in pharmacies without a prescription and without going to a doctor.
In this regard, the following approach is proposed as a definition of the dependence of incidence on weather factors.
Due to the fact that it is almost impossible to detect an increase in the number or spread of morbidity in the daily
Y =11+i - >
j=i
where Y is the weather characteristic (air temperature, atmospheric pressure, pressure difference per day, etc.), X. - is some "weather" factor from the set i e N - some set of meteorological observations, N - is the number of observations.
Thus, the dependence of the number of diseases is some function or:
¥j = f {Y},, (2)
where ^ . - type of disease from the set j eQ.
In addition, it is a priori known that several weather factors can have a significant effect on the increase in the number of diseases at the same time, for example, a sharp change in air temperature and atmospheric pressure. In this case, it is possible to use multifactor regression analysis to identify meaningful links:
V = i<*,Y,, (3)
i=1
where y - is the type of disease, a, - is the coefficient, F - is the number of parameters taken into account.
The average, maximum and minimum air temperatures per day, the values of atmospheric pressure and its change per day and others were taken as weather factors.
A set of detectable diseases - a disease characterized by elevated blood pressure, diseases of the circulatory system, and diseases of the respiratory organs - was taken as the types of morbidity.
Thus, it turns out some summary analytical table of the risk of growth in the number and distribution of the type of morbidity of the population depending on weather and climatic factors in the form of a certain dependence of morbidity
on the weather, with a corresponding multiple regression coefficient and approximation reliability value.
Table 1 shows the matrix of the magnitude of the accuracy of the approximation for certain types of diseases and weather characteristics of the Tashkent region of Uzbekistan for the period 2005-2015. Of course, the accuracy of the approximation is not great for all cases, but it can still be used to assess
the risk of increasing incidence, especially depending on the dynamics of weather factors. In case of extreme changes in weather and climatic factors, to warn different categories of users in a timely manner - from the level of the Ministry of Health to attending physicians and risk groups themselves.
The magnitude of the accuracy of the approximation serves as a probabilistic characteristic of the dependence of the type of morbidity on the weather factor and can serve as a measure of the risk, in terms of its probabilistic excess over the norm, since it varies from 0 to 1.
It should be noted that in this case only the weather factor is taken into account, which is secondary, if unhealthy
Table 1.- The matrix of the magnitude for certain types of diseases
lifestyles, unbalanced nutrition, stressful situations, constant psycho-emotional stress, hypodynamia, elevated blood cholesterol, arterial hypertension and tons are taken as primary factors.
According to the weather forecast, it is possible to make a prediction of the risk of an increase in the number or spread of morbidity with a predetermined degree of probability corresponding to the magnitude of the approximation reliability for a particular area.
The World Health Organization (WHO) project, jointly carried out by experts from Uzhydromet and the Ministry of Health, developed an early warning system for disease risk, which uses the proposed approach to develop recommendations for various groups of users.
The system is designed to prevent risks for various categories of users and to apply various response measures developed in advance by specialists.
At the state level - for timely prevention and warning of the population by appropriate means of warning.
of the accuracy of the approximation and weather characteristics
Type of disease Atmospheric pressure Differential Atmospheric Pressure per day Temperature air, average per day Delta temperatures of air per day
acute rheumatic fever 0.0001 0.0668 0.0238 0.0016
chronic rheumatic heart disease 0.0055 0.0282 0.0088 0.0635
rheumatic heart disease 0.0570 0.0019 0.0312 0.0790
disease characterized by high blood pressure 0.0141 0.2163 0.0027 0.0040
coronary heart disease 0.0146 0.0230 0.0094 0.0221
angina pectoris 0.1720 0.2463 0.3288 0.4280
acute myocardial infarction 0.0661 0.4262 0.2520 0.3488
acute myocardial infarction 0.0395 0.2290 0.2024 0.2108
chronic ischemic heart disease chronic diseases of tonsils and adenoids, peritonsular abscess 0.0979 0.1972 0.1469 0.2212
pneumonia 0.0300 0.0957 0.1149 0.0864
For early warning, recommendations will be made on the categories of patients, including not only chronic, but also group - children, the elderly, women, and chronic patients.
For pharmacology - the degree of use of drugs and drugs for the prevention of diseases.
The system is placed on a special website www.meteomed. uz, which provides access to all blocks of users who are at a distance, does not require the development and use of special communication lines between different users, ensures efficiency, which is important in extreme cases.
The system contains its own database, which allows you to enter data on morbidity, to carry out their graphical and tabular control, if necessary, correct and correct the input data. Risk calculation programs use the entered data and put it on a special page. The analytical group of health workers monitors the calculation results and issues the appropriate recommendations in accordance with previously developed action plans and risk criteria.
The system consists of separate blocks. Block receipt and entry information. Baseline information for statistical pro-
cessing comes from the SES of the Ministry of Health - the number of diseases per decade. Directly on the page, you can
enter, analyze the entered data in tabular and graphical form, thus avoiding technical errors (Figure 1).
Figure 1. Graph of the decade progress comparing the number of recorded acute intestinal diseases and average air temperature
The system of equations calculates the parameters of the statistical dependence of the number of diseases on weather and climatic factors.
In (Figure 2) the calculated equation with the coefficient of approximation and the dependence graph are given. The coefficients of the calculated equations of multiple regression are entered in the appropriate calculation unit. According to hydrometeorological data, which are substituted into the appropriate equations, the estimated number of diseases is calculated. The calculation results are placed in a special table with the appropriate values of the accuracy of the approximation, which are analyzed by the relevant group of experts of the Ministry of Health.
For widespread use, an approach can be used in which three criteria of excess over the norm are applied - 75%, 90%, above 100% -when extreme values of the used weather factors are used. For treating physicians appropriate action plans.
For the convenience ofthe analytical group, the system provides GIS processing of database materials. In (Fig. 3) shows an example of displaying the results in cartographic form for the districts of the Tashkent region in a predetermined time interval.
Using the nosogeographic maps built in the GIS system, it becomes possible to analyze the territorial distribution of the disease. For example, in (Fig. 3) clearly visible territorial intensity of the spread of acute intestinal infections, depending on the location in the direction of the flow of watercourses.
This is explained by the increase in the concentration of pollution as a result of not only polluted water entering the watercourses, but also pollution from the slopes of the foothills. What subsequently leads to an increase in the concentration of water pollution along river flows downstream.
In this case, the analytical group may focus on individual territories most affected by not only weather and climate factors, but also distribution throughout the region.
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4-::
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:::
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fif - 0.5004-
■F
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■* -r * r
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Figure 2. Dependence of the number of acute intestinal diseases for a month on the average air temperature in the previous month
Figure 3. A zoological map of the spread of acute intestinal infections Tashkent region for the period 2005-2015
An analytical approach has been developed for comparing average decadal (monthly averages) data on morbidity and average daily meteorological data to obtain quantitative values of prognostic equations.
The location of the system on a special site allows prompt entry of source information, without the use of special communication tools, calculation, output of calculation results into a special (password-protected) page for medical analysis.
The analytical group will make the appropriate decision and promptly disseminate the results of the analysis in the form of appropriate, previously developed action plans for various categories of users.
This approach can be used for various territories at the global level, taking into account national specificity in the choice of morbidity risk criteria and climatic factors. To develop response measures for critical values of weather variability and climate change.
References:
1. Chub V E., Myagkov S. V., Klimov S. I. Climate change and public health. Ecological Herald.- Tashkent, 2010.- No. 11.13 p.
2. Myagkov S. V., Klimov S. I. Climate change and sensitivity to acute intestinal diseases Ecological Bulletin. - Tashkent, 2011.-No. 2.- 49 p.
3. Myagkov S. V Ecology of the Tashkent Canals Ecological Bulletin - Tashkent, 2009.- No. 8.- 22 p.
4. Myagkov S. Fresh drinking water resources in Kyzyl- Kum desert. Management and Governance of Groundwater in Arid and Semi- Arid Countries. International Workshop, 2005. Cairo, Egypt.- P. 65-70.
5. Tillyakhodjaeva Z. D. "Risk assessment of the population relating to the pollution of the environment" 2nd International Conference on Arid lands Studies / Innovations for sustainability and food security in arid semiarid lands. - Samarkand. Uzbekistan, 2014.- P. 153-154.
