Medical Meteorological Forecast For Three Weather Sensitive Diseases In Shijiazhuang

In the context of global climate change,extreme weather events occur frequently,and the impact on human health is more significant,performs to induce or intensify related diseases by direct or indirect route.Studies in epidemiology and statistics show that among those health events that caused by high temperature and heat wave and heavy pollution weather,the occurrence and death of cardiovascular and cerebrovascular and respiratory diseases account for a large proportion.In recent years,lots of studies about cardiovascular and cerebrovascular and respiratory diseases show that,the characteristics are various in seasons,and correlated with meteorological elements.Further more,according to the analysis of details between different diseases,it also have a seasonal difference.Therefore,it’s important for the prevention and control of disease to investigate the relationship between meteorological elements and cardiovascular and cerebrovascular and respiratory diseases,and to carry out the key indicators of early warning research of the impact of extreme weather on human health,and then establish the weather prediction model for human health risk.In this study,the meteorological data of last 53 years of Shijiazhuang area were used to obtain the climate characteristics,and analyze the relationship between the chronic obstructive pulmonary disease(COPD),coronary heart disease(CHD),cerebral infarction(CI)and meteorological factors.According to the incidence trends of these three common diseases,the corresponding prediction model for different seasons were set up respectively,and the main conclusions are as followings:1.The mean temperature of recent 53 years in Shijiazhuang performs a rising trend.And since1980’s,it rose significantly.The mean annual maximum temperature and minimum temperature also show an upward trend,especially the mean annual minimum temperature,with an average increase rate of 0.594 ℃ / 10 a.For different seasons,it’s more significant in winter.2.The COPD occurrence has obvious seasonal characteristics.It presents a high incidence in autumn and winter,followed by spring,and the least in summer.Meteorological factors played a comprehensive effect on the occurrence of COPD.The 24 hours diurnal temperature variations,daily minimum temperature and diurnal temperature range are three major temperature indicators for COPD.In autumn and winter,with small change in air temperature,the atmospheric stratification turns stable,air pollution is the main impacting factor;In spring,it’s coming warm,diurnal temperature range becomes larger with a mean value of 10 degrees.Moreover,the more activity bacteria becomes the major effecting factor.In summer,high temperature and low air pressure(991.7hPa)lead to the relapse.In order to reduce the occurrence and provide reference,prediction model were established for different seasons.Furthermore,results show that male patients with COPD for adult accounted for 56.4%,those 60 years old accounted for 51.2%,therefore,the prevention of COPD may need more focus on elderly.3.The incidence of CHD is various in different months and seasons.It presents least in summer and most in autumn.,and it’s higher in winter and autumn than the mean.There’s a positive correlation between CHD disease numbers and the win speed change and air pressure change,but a negative correlation with the vapor pressure,mean temperature,mean maximum temperature and the mean minimum temperature.From spring to summer,the air temperature increased,the CHD incidence show a downward trend,and is turns to be opposite from summer to autumn.In summer,the air temperature becomes highest,and the CHD incidence is least.It is the positive response mechanism between The CHD incidence and wind speed/air pressure.Using vapor pressure and wind speed change,to set up the prediction model for CHD incidence.After testing,it’s accuracy rate is 77 percents,and can present the trends of CHD incidence almostly.4.The incidence of CI also performs different monthly and seasonal characteristics.The CI incidence show a similar performance in other seasons but least in winter.There’s a positive correlation between CI disease numbers and air pressure in summer,and it’s the same to other seasons between CI incident numbers and relative humidity and its change,mean temperature,mean maximum temperature and mean minimum temperature,but a positive correlation with air pressure.On the basis of this to set up the prediction model of CI disease numbers for different seasons.After testing,with the 82 percents accuracy rate a for summer,and 76 percents accuracy rate for winter.It can present the trends of CI disease numbers almostly.5.Developed a health-weather business platform to achieve business applications.