This study was aimed to investigate the air pollutants impact on heart patient’s hospital admission rates in Yazd for the first time. Modeling was done by time series, multivariate linear regression, and artificial neural network (ANN). During 5 years, the mean concentrations of PM(10), SO(2), O(3), NO(2), and CO were 98.48 μg m(-3), 8.57 ppm, 19.66 ppm, 18.14 ppm, and 4.07 ppm, respectively. The total number of cardiovascular disease (CD) patients was 12,491, of which 57% and 43% were related to men and women, respectively. The maximum correlation of air pollutants was observed between CO and PM(10) (R = 0.62). The presence of SO(2) and NO(2) can be dependent on meteorological parameters (R = 0.48). Despite there was a positive correlation between age and CD (p = 0.001), the highest correlation was detected between SO(2) and CD (R = 0.4). The annual variation trend of SO(2), NO(2), and CO concentrations was more similar to the variations trend in meteorological parameters. Moreover, the temperature had also been an effective factor in the O(3) variation rate at lag = 0. On the other hand, SO(2) has been the most effective contaminant in CD patient admissions in hospitals (R = 0.45). In the monthly database classification, SO(2) and NO(2) were the most prominent factors in the CD (R = 0.5). The multivariate linear regression model also showed that CO and SO(2) were significant contaminants in the number of hospital admissions (R = 0.46, p = 0.001) that both pollutants were a function of air temperature (p = 0.002). In the ANN nonlinear model, the 14, 12, 10, and 13 neurons in the hidden layer were formed the best structure for PM, NO(2), O(3), and SO(2), respectively. Thus, the R(all) rate for these structures was 0.78-0.83. In these structures, according to the autocorrelation of error in lag = 0, the series are stationary, which makes it possible to predict using this model. According to the results, the artificial neural network had a good ability to predict the relationship between the effect of air pollutants on the CD in a 5 years’ time series.
BACKGROUND: Although scorpionism is recorded worldwide, some regions such as Iran present a higher incidence. Due to the great prevalence of scorpion stings in Khuzestan province, southwestern Iran, the present study examined the relationship between different climate parameters and the scorpion sting rate in this area from April 2010 to March 2015. METHODS: In this cross-sectional descriptive-analytical study, we considered all scorpion sting cases recorded in the Department of Infectious Diseases, Ahvaz Jundishapur University of Medical Sciences. Data were analyzed using statistics, frequency distribution and Pearson’s correlation coefficient. RESULTS: A total of 104,197 cases of scorpion stings was recorded from 2010 to 2015. The cumulative incidence of scorpion sting was 2.23%. The spatial distribution of scorpion stings showed that most cases occurred in the Dehdez district (4,504 scorpion stings/100,000 inhabitants) and the Masjed Soleyman county (4,069 scorpion stings/100,000 inhabitants). A significant association was found between climate factors (temperature, evaporation rate, sunshine duration, humidity, and precipitation) and the scorpion sting rate. An increase in rainfall and humidity coincided with a reduction in scorpion stings whereas an increase in temperature, evaporation, and sunshine duration was accompanied by a growth of scorpion stings. No significant correlation was found between wind velocity/direction and the incidence rate of stings. Moreover, the seasonal peak incidence of scorpion stings was recorded in summer (an average of 8,838 cases) and the lowest incidence was recorded during winter (an average of 1,286 cases). The annual trend of scorpion sting cases decreased during the period from 2010 to 2015. CONCLUSION: Climate variables can be a good index for predicting the incidence of scorpion stings in endemic regions. Since they occur mostly in the hot season, designing preventive measures in the counties and districts with a high incidence of scorpion stings such as Dehdez and Masjed Soleyman can minimize mortality and other burdens.
Cotton is one of the important crops that play an important role in creating a livelihood for rural people in many parts of Iran. Cotton production necessitates a large amount of resources (e.g., fossil energy and agrochemicals, all of which have the potential to damage the environment in various ways). The purpose of the current study was to evaluate the environmental effects of cotton production in the South Khorasan Province of Iran. For this purpose, life cycle assessment (LCA) and data envelopment analysis (DEA) techniques have been applied to investigate the environmental impacts of cotton production. LCA is a practical method to evaluate the environment on the product flow, in which all aspects of the product life cycle are examined by a comprehensive approach. Furthermore, combining the LCA method with other managerial strategies such as DEA could allow researchers to provide decision-makers with more practical and interpretable data. The findings of the efficiency test showed that the average technical efficiency, pure technical efficiency, and scale efficiency were 0.81, 0.92, and 0.87, respectively. Respiratory inorganics (i.e., respiratory effects resulting from winter smog caused by emissions of dust, sulfur, and nitrogen oxides to air) posed the greatest environmental burden in cotton production, followed by non-renewable energy, carcinogens, and global warming. In addition, the highest effects were on human health, and then, on resources and climate change. Energy, on-system pollution, and waste played a crucial role in the environmental impacts of cotton processing. This study suggests improving farmers’ knowledge toward the optimum application of chemical fertilizers, or their substitution with green fertilizers, which reduces the environmental effect of growing cotton in the area.
BACKGROUND: Asthma is a chronic respiratory disease resulting from a complex interaction between genetic and environmental factors. Among environmental factors, climatic and geographical variations have an important role in increasing asthma hospitalization. The current study aimed to investigate the effect of geoclimatic factors on the occurrence of childhood asthma hospitalization in Fars province, southwest Iran. METHOD: We mapped the addresses of 211 hospitalized patients with childhood asthma (2016-2019) and investigated the effects of different temperature models, mean annual rainfall and humidity, number of frosty and rainy days, evaporation, slope, and land covers on the occurrence of childhood asthma hospitalization using a geographical information system. The Kriging and Spline methods have been used for generating interpolated models. Data were analyzed using logistic regression. RESULTS: In the multivariate model, urban setting was recognized as the most important childhood asthma hospitalization predictor (p < 0.001, odds ration [OR] = 35.044, confidence interval [CI] = 9.096-135.018). The slope was considered the determinant of childhood asthma hospitalization when analyzed independently and its increase was associated with decreased childhood asthma hospitalization (p = 0.01, OR = 0.914, CI = 0.849-0.984). CONCLUSION: In the current study, the urban setting was the most important risk factor associated with increased childhood asthma hospitalization.
Climate change has increased the exposure risk of workers to occupational health risk factors and diseases. This study aims to investigate the impacts of climate change on the occupational health indicators at the workplaces in Iran. This study was conducted during 2021 in three climatic regions of Iran. Required data was collected from Health Deputies of Medical Universities and Iran Meteorological Organization. Stepwise linear regression model used for data analysis and predictions were done based on three scenarios of SSP1-2.6, SSP3-7.0, and SSP5-8.5 during the period of 2021-2100. This indicated 2.6 and 2.9 times higher percentage of workers who were exposed to heat stress and Ultra Violet (UV) radiation, respectively, in the provinces understudy. This study suggests a holistic approach to address potential impacts of climate change on workers’ health and safety that would benefit in making decisions on climate-related planning and developing the adaptation strategies at workplaces.
OBJECTIVE: Brucellosis is a zoonosis almost chronic disease. Brucellosis bacteria can remain in the environment for a long time. Thus, climate irregularities could pave the way for the survival of the bacterium brucellosis. Brucellosis is more common in men 25 to 29 years of age, in the western provinces, and in the spring months. The aim of this study is to investigate the effect of climatic factors as well as predicting the incidence of brucellosis in Qazvin province using the Markov switching model (MSM). This study is a secondary study of data collected from 2010 to 2019 in Qazvin province. The data include brucellosis cases and climatic parameters. Two state MSM with time lags of 0, 1 and 2 was fitted to the data. The Bayesian information criterion (BIC) was used to evaluate the models. RESULTS: According to the BIC, the two-state MSM with a 1-month lag is a suitable model. The month, the average-wind-speed, the minimum-temperature have a positive effect on the number of brucellosis, the age and rainfall have a negative effect. The results show that the probability of an outbreak for the third month of 2019 is 0.30%.
This study focused on the measurement of BTEX (benzene, toluene, ethylbenzene and xylene) concentrations in the air of various regions and indoor-outdoor environments in Bandar Abbas, Iran. Air samples were taken actively and analyzed by gas chromatography-mass spectrometry (GC-MS) during two one-month periods i.e., Feb 2020 (period I) and Sep/Oct 2020 (period II). The mean air temperature and the levels of all BTEX compounds were higher in period II. The highest total BTEX (t-BTEX) levels (median [min-max]) were found in the urban region (18.00 [5.21-67.24] μg m(-3)), followed by industrial region (7.00 [2.05-14.76] μg m(-3)) and rural region (2.81 [ND-7.38] μg m(-3)). The significant positive correlations between all BTEX compounds and T/B ratio >1 indicated the vehicular traffic as the main source of emission. At 95th percentile probability, the non-cancer risk of t-BTEX in urban region was only less than one order of magnitude below the threshold level of unity (1.91E-01) and the cancer risk of benzene exceeded the recommended level of 1.0E-06 by U.S. EPA in urban (7.69E-06) and industrial (2.97E-06) regions. It was found that the indoor/outdoor ratio of BTEX concentration in beauty salon and hospital was greater than 1. Overall, the current levels of BTEX in the ambient air of study area, especially near urban roadside and in some indoor environments, should not be overlooked and appropriate mitigation actions should be undertaken.
The generation and emission of volatile organic compounds (VOCs) affects the environment and air quality, playing an important role in global warming, depletion of atmospheric ozone and emission of unpleasant odors, but also directly affect human health. This study investigated the health risks of benzene, toluene, ethylbenzene, xylene (BTEX) compounds and biogas released in and around the municipal landfill. Sampling of the VOCs was carried out by the 1501NIOSH method from 8 points over 5 months. The samples were analyzed for BTEX in the ambient air of the landfill, resulting in 0.03-18.09 ppm concentrations, while for biogases a 0.08-25.2 ppm range was found. Assessment of definite health and potential risks showed that the lifetime cancer risk (LCR) for benzene and hazard quotient (HQ) for the BTEX components in all studied sampling sites are higher than the acceptable standard. The high concentration of benzene measured in ambient air indicated that petroleum compounds containing benzene and its derivatives have the highest value in the category of BTEX compounds among all emissions. Therefore, high concentrations of volatile compounds derived from VOCs, especially benzene, should be reduced at the site with control engineering measures.
Climate change affects human health, and severe acute respiratory syndrome (SARS) incidence is one of the health impacts of climate change. This study is a retrospective cohort study. Data have been collected from the Iranian Ministry of Health and Medical Education between 17 February 2016 and17 February 2018. The Neural Network Model has been used to predict SARS infection. Based on the results of the multivariate Poisson regression and the analysis of the coexistence of the variables, the minimum daily temperature was positively associated with the risk of SARS in men and women. The risk of SARS has increased in women and men with increasing daily rainfall. According to the result, by changes in bioclimatic parameters, the number of SARS patients will be increased in cities of Iran. Our study has shown a significant relationship between SARS and the climatic variables by the type of climate and gender. The estimates suggest that hospital admissions for climate-related respiratory diseases in Iran will increase by 36% from 2020 to 2050. This study demonstrates one of the health impacts of climate change. Policymakers can control the risks of climate change by mitigation and adaptation strategists.
BACKGROUND: Cutaneous leishmaniasis (CL) has been reported in recent years in South Khorasan Province, a desert region of eastern Iran, where the main species is Leishmania tropica. Little is known of the influence of geography and climate on its distribution, and so this study was conducted to determine geo-climatic factors by using geographic information system. METHODS: The home addresses of patients with CL patients who were diagnosed and notified from 2009 to 2017 were retrieved from the provincial health center and registered on the village/town/city point layer. The effects of mean annual rainfall (MAR) and mean annual humidity (MAH), mean annual temperature (MAT), maximum annual temperature (MaxMAT), minimum annual temperature (MinMAT), mean annual number of high-velocity wind days (MAWD), mean annual frosty days (MAFD) and snowy days (MASD), elevation, soil type and land cover on CL distribution were examined. The geographical analysis was done using ArcMap software, and univariate and multivariate binary logistic regression were applied to determine the factors associated with CL. RESULTS: A total of 332 CL patients were identified: 197 (59.3%) male and 135 (40.7%) female. Their mean age was 29.3 ± 2.1 years, with age ranging from 10 months to 98 years. CL patients came from a total of 86 villages/towns/cities. By multivariate analysis, the independent factors associated with increased CL were urban setting (OR = 52.102), agricultural land cover (OR = 3.048), and MAWD (OR = 1.004). Elevation was a protective factor only in the univariate analysis (OR = 0.999). Soil type, MAH, MAT, MinMAT, MaxMAT, and MAFD did not influence CL distribution in eastern Iran. CONCLUSIONS: The major risk zones for CL in eastern Iran were urban and agricultural areas with a higher number of windy days at lower altitudes. Control strategies to reduce human vector contact should be focused in these settings.
BACKGROUND/OBJECTIVE: Natural disasters (NDs) are calamitous phenomena that can increase the risk of infections in disaster-affected regions. This study aimed to evaluate the frequency of malaria and cutaneous leishmaniasis (CL) before and after earthquakes, floods, and droughts during the past four decades in Iran. METHODS: Malaria and CL data were obtained from the reports of the Ministry of Health and Medical Education in Iran for the years 1983 through 2017. The data of NDs were extracted from the Centre for Research on the Epidemiology of Disasters (CRED). Interrupted time series analysis with linear regression modeling was used to estimate time trends of mentioned diseases in pre- and post-disaster conditions. RESULTS: For the periods preceding the disasters drought and flood, a decreasing time trend for malaria and CL was found over time. The time trend of malaria rate preceding the 1990 earthquake was stable, a downward trend was found after 1990 disaster until 1997 (β coefficient: -10.7; P = .001), and this declining trend was continued after 1997 disaster (β coefficient: -2.7; P = .001). The time trend of CL rate preceding the 1990 earthquake had a declining trend, an upward trend was found after 1990 earthquake until 1999 (β coefficient: +8.7; P = .293), and a slight upward trend had also appeared after 1999 earthquake (β coefficient: +0.75; P = .839). CONCLUSION: The results of the current study indicated the occurrence of earthquakes, floods, and droughts has no significant effect on the frequency of malaria and CL in Iran.
Evidence shows that climate change may have adverse effects on human health. The purpose of this study was to investigate the relation between Physiologically Equivalent Temperature (PET) and cardiovascular hospital admissions in Ahvaz. Distributed Lag Non-linear Models (DLNM) combined with quasi-Poisson regression models were used to investigate the effect of PET on hospital admissions. Low PET values (6.4 °C, 9.9 °C and 16.9 °C) in all lags, except lag 0-30, significantly decreased the risk of hospital admissions for total cardiovascular diseases, hypertension, ischemic heart diseases, and cardiovascular admissions in men, women and ≤65 years. But, low PET (6.4 °C) in lags 0 and 0-2 significantly increased the risk of hospital admissions for cerebrovascular diseases; and high PET values increased the risk of ischemic heart diseases and in men. Both cold and hot stress are involved in cardiovascular hospital admissions.
Background: There are few epidemiological studies on the relation between temperature changes and adverse pregnancy outcomes. The purpose of this study was to determine the relation between Physiological Equivalent Temperature (PET) with adverse pregnancy outcomes including stillbirth, low birth weight (LBW), preterm labor (PTL), spontaneous abortion (SA), preeclampsia and hypertension in Ahvaz, Iran. Methods: Distributed Lag Non-linear Models (DLNM) combined with quasi-Poisson regression were used to investigate the effect of PET on adverse pregnancy outcomes. In this study the effect of time trend, air pollutants (NO2, SO2 and PM10), and weekdays were adjusted. Results: High PET (45.4 C°, lag = 0) caused a significant increase in risk of stillbirth. Also, high levels of PET (45.4, 43.6, 42.5 C°, lag = 0–6) and low levels of PET (9.9, 16.9 C°, lags = 0, 0–13, 0–21) significantly increased the risk of LBW. But, low levels of PET (6.4, 9.9, 16.9 C°, lags = 0–6, 0–13) reduced the risk of gestational hypertension. Conclusion: The results of this study showed that hot and cold thermal stress may be associated with increased risk of stillbirth, and LBW in Ahvaz.
Excessive ambient air temperature due to global warming and climate change is capable of imposing heat stress on outdoor workers. This study had a quantitative, secondary, and analytical design. The present study aimed at modelling the trend of climate change by Hadley atmosphere-ocean general circulation model (HadCM) and Long Ashton Climate Generator (LARS) to predict future climate change trends, and determining heat stress in exposed farmworkers with high working energy demand who work full time in the unsheltered farm area. In this study, the data of the three synoptic metrological monitoring stations (located at the cities of Dezful (32.3831 degrees N, 48.4236 degrees E), Ahvaz (31.3183 degrees N, 48.6706 degrees E), and Dehdez (31.7011 degrees N, 50.2946 degrees E)) in a 30 years duration (1986-2016) was used. To predict the future trend of air temperature, HadCM and LARS were applied. Also, the Wet-Bulb Globe Temperature (WBGT) index was used to determine heat stress. The results showed that the temperature will increase throughout the coming years in the 3 cities (Ahvaz, Dezful, and Dehdez). The determination coefficient (R-2) ranges from 0.91 to 0.96 for the results. The rise of temperature rate between the time duration of 2011-2040 and 2041-2070 will be about 5 degrees C, and the WBGT indexes in June, July, and August were obtained as very hot (danger; > 28 degrees C). And the rate of increase in air temperature in the city of Ahvaz will be higher than in the other two cities. According to the results, it was revealed that heat stress coincidence with global warming will increase and exposure to heat for farmworkers will be much more severe.
BACKGROUND: Disaster planning and management pose a serious challenge to most countries. These challenges point to insufficient planning to deal with these events. Therefore, it is necessary to pay attention to the methods and characteristics of the decision-making approaches in these events. In this study, we tried to identify most appropriate approaches for the Iranian health system by studying disaster planning approaches. MATERIALS AND METHODS: This study was conducted using mixed methods in 2020-2021 in two phases: qualitative and quantitative. First, we reviewed at the research literature. Our goal was to identify studies that suggested approaches to disaster planning. The next step in this study was a qualitative study using semi-structured interviews. Participants in qualitative phase included managers and employees from different parts of the Iranian health system from the provinces of Golestan, Fars, Khuzestan, Lorestan, Kerman, Sistan, and Baluchestan. RESULTS: By combining approaches taken from literature reviews and qualitative study, four main approaches were identified. The results of our study have shown that disaster response planning approaches include function, risk assessment, capability, and futuristic base. CONCLUSION: This study provides complete overview of disaster planning approaches that enable health professionals to use them to develop response plans. Our findings indicate that in complex and large-scale events such as floods and pandemics, it is necessary to combine the introduced methods for operational planning.
BACKGROUND: Malaria is the third most important infectious disease in the world. WHO propose programs for controlling and elimination of the disease. Malaria elimination program has begun in first phase in Iran from 2010. Climate factors play an important role in transmission and occurrence of malaria infection. The main goal is to investigate the spatial distribution of incidence of malaria during April 2011 to March 2018 in Hormozgan Province and its association with climate covariates. METHODS: The data included 882 confirmed cases gathered from CDC in Hormozgan University of Medical Sciences. A Poisson-Gamma Random field model with Bayesian approach was used for modeling the data and produces the smoothed standardized incidence rate (SIR). RESULTS: The SIR for malaria ranged from 0 (Abu Musa and Haji Abad districts) to 280.57 (Bandar-e-Jask). Based on model, temperature (RR= 2.29; 95% credible interval: (1.92-2.78)) and humidity (RR= 1.04; 95% credible interval: (1.03-1.06)) had positive effect on malaria incidence, but rainfall (RR= 0.92; 95% credible interval: (0.90-0.95)) had negative impact. Also, smoothed map represent hot spots in the east of the province and in Qeshm Island. CONCLUSION: Based on the analysis of the study results, it was found that the ecological conditions of the region (temperature, humidity and rainfall) and population displacement play an important role in the incidence of malaria. Therefore, the malaria surveillance system should continue to be active in the region, focusing on high-risk areas of malaria.
Flash-flooding affected Iran in March 2019 causing the displacement of thousands of people. Social workers established a Child Friendly Space (CFS) and applied comprehensive case management to provide psychosocial support for people who were affected by flooding (PWAF) (n = 565) in a community in Poldokhtar, covering a period of 3 months. Outreach services, involving community-volunteers, providing counseling, establishing CFS, training PWAF for reducing violence, and preventing child abuse were essential social work post-disaster interventions to support vulnerable populations. The article reflects upon the often-neglected role of social workers in post-disaster settings, and brings new material for discussion from the unexplored field of Iranian social workers.
Flood hazard characteristics play a key role in flood-induced mortality. Therefore, it is crucial to evaluate the associations between these factors and flood fatalities. This case-control study was performed in the flood-prone regions of Iran with recorded flood-induced mortality rates during 2005-2018. In total, 369 subjects completed the survey (123 cases and 246 controls); they were selected from 12 provinces and 30 cities. In this study, descriptive and analytical analyses were carried out to measure flood hazard characteristics. Afterward, the correlation of flood hazard characteristics with flood-induced mortality was measured. According to the descriptive analysis, most deaths occurred in summer, during hours of darkness, in areas with one- and five-year flood return periods, and in floods with short rainfall durations. In addition, the spatial analysis demonstrated that most deaths occurred in flash floods, floods accompanied by bad weather, and floods with floating debris. The results of Chi-square and Fisher’s exact test also indicated significant correlations between darkness, flood return periods, flood behavior, floods with floating debris, bad weather, other hazards, and flood discharge with flood-induced mortality. According to the regression analysis, the variables of flood discharge over 500 m3/s, flash floods, nighttime floods, and floods with floating debris increased the risk of flood-induced mortality 3.64, 1.62, 3.34, and 1.06 times, respectively. Although changing flood hazard characteristics seems to be impossible, damages caused by floods can be decreased and the lives of people can be protected through appropriate preventive and managerial solutions, planning, training, promotion of preparedness, and timely warnings.
BACKGROUND: In recent years, the prevalence of dust events has increased in the region and the world. According to the Meteorological Organization, the most frequent days with dust events are on stations located in Khuzestan province. Objective: Assessment of the effects of dust events and meteorological elements on stroke morbidity in health in Iran: a health promotion approach. MATERIALS AND METHODS: The present study was a retrospective cohort study 2020 and 2013 provided between based on ecological data-based on population. Information about patients with stroke was obtained from the hospital. Information on the dust events and meteorological elements was also from the data center of the Meteorological Organization of Iran. Using STATA the correlation between the diseases and the, 14 statistical software version occurrence of dust events and changes in meteorological elements was obtained and the statistical model (Spearman correlation coefficient) individually estigate the equation was used inv modified by Poisson regression simultaneous effect of variables. RESULTS: the results of adjusted statistical models show that increasing the severity of dust event increases the risk of stroke in males (lag 0-21 confidence interval [CI] 95% = 1.496-1.0067 relative risk [RR] = 1.03 P = 0.01). Increasing the average wind speed also increases the risk of stroke in males (lag 0-3 CI 95% = 1.0491-0.9996 RR = 1.02 P = 0.05). Increased rainfall and average relative humidity increase the risk of stroke in people under 60 years (lag 0-7 CI 95% = 1.0012-0.9058 RR = 1.95 P = 0.05). Increasing the average daily temperature reduces the risk of stroke in males (lag 0-3 CI 95% = 0.9874-0.9254 RR = 0.51 P < 0.001). CONCLUSION: Increasing the intensity of dust storms along with meteorological elements has increased the risk of stroke. However, increasing the average temperature has had a protective effect on the risk of stroke.
Sexual violence is largely absent from studies on violence against women in disasters. The role of men in perpetrating violence against women is overlooked or excused and women are usually blamed in both countries. A review of 2 studies of men’s violence against women after floods and earthquakes in Iran and bushfires in Australia show remarkable similarities. Although cultural contexts and the way gender inequality is established and demonstrated are different, these studies reveal unexpected parallels. The context of disaster lays it bare. Participants of both studies were disaster-affected people in Iran and Australia who revealed the taboos that prevent women speaking of violence that is exacerbated in a disaster context. Men play important roles in preventing and responding to violence against women as the result of their responsibilities and positions at the household and community levels. The objective of this paper was to compare the findings from these studies and consider the difficulties faced in conducting studies related to the roles of men and women roles during and after disaster events.
BACKGROUND: Outbreaks of infectious diseases are the major concern after flooding. Flood makes people displacement which would be more complicated with inadequate sanitation. Settling in crowded shelters in absence of clean water and inaccessibility to health care services makes people more vulnerable to get infection. This review aimed to discuss about potential undesirable outcomes of flooding occurred in 2019 in Iran. METHODS: A comprehensive search was carried out in databases including PubMed, Google scholar, Scopus, Science Direct, Iran medex, Magiran and SID (Scientific information database) from 2000 to 2019. All original descriptive articles on flood were concerned. Related articles on flood disturbance were considered. Also, publication of red cross society was considered as only reliable reference in evaluation of consequences of flood occurred in 2019 in Iran. RESULTS: Flooding in Iran, was started in March 2019 and lasted to April 2019. Flood affected 31 provinces and 140 rivers burst their banks, and southwestern Iran being hit most severely. According the reports of international federation of red cross society, 3800 cities and villages were affected by the floods with 65,000 destroyed houses and 114,000 houses partially damaged. Also 70 hospitals or health care centers with 1200 schools were damaged along with many infrastructures including 159 main roads and 700 bridges. CONCLUSIONS: Considering 365,000 displaced persons and estimation of mentioned damages, it was one of the greatest natural disaster during the last 20 years. Various risk factors in favor of infectious diseases such as overcrowding, disruption of sewage disposal, poor standards of hygiene, poor nutrition, negligible sanitation and human contact among refugees provide suitable conditions for increased incidence of infectious diseases after flooding and also cause epidemics.More attention is needed to provide hygienic situation for people after natural disasters including flood.
PURPOSE: Salmonella is one of the main causes of gastroenteritis, and its incidence may be affected by meteorological variables. This is the first study about the effect of climatic factors on salmonella incidence in Kermanshah, Iran. METHODS: Data about salmonellosis cases in Kermanshah were inquired from Center for Communicable Disease Control, at the Ministry of Health and Medical Education of Iran, for the 2008 to 2018 time-frame. Meteorological variables including maximum, minimum and mean of temperature and humidity, sunshine hours and rainfall were inquired for the same time frame. Negative binomial generalized linear models (GLM) were used to assess the effect of meteorological variables on the weekly incidence of salmonellosis. RESULTS: During the years under study, 569 confirmed cases were registered in Kermanshah province. Study results showed a 3?% increase in salmonellosis incidence, after 1?% increase in minimum humidity in the week before (incidence rate ratio (IRR): 1.03; 95?% confidence interval (CI):1.02-1.05) and also a 4?% increase in incidence for 1 °C increase in mean temperature in the same week (IRR: 1.04; 95?% CI:1.02-1.06). CONCLUSIONS: Increase in minimum humidity and mean temperature may have a role in increasing the incidence of salmonellosis in Iran.
The study was conducted to determine thermal stress and its trend in Iran. The atmospheric variables of 304 synoptic stations, including mean temperature, relative humidity, wind speed and cloudiness, for the period 1961-2010, were used to identify the thermal stress conditions in Iran. These data were prepared on a daily basis from the Iran Meteorological Organization. Physiologically equivalent temperature (PET) and standard effective temperature (SET*) were used to identify thermal stress. Also, thermal stress was studied with a simple linear regression method and at a 95% confidence level. The results of the study revealed that in Iran each location can experience different types of environmental conditions throughout the year. At a specified time, thermal stresses of different intensities can be seen. The other results showed that the mountainous regions, especially the highlands of the northwest, along with the Zagros and Alborz mountains, had the highest co-efficient of variability (> 50%). Also, the southern regions of Iran have both monthly and annual scales with the least co-efficient of variability (< 20%) in bioclimatic conditions. In general, a diversity of bioclimatic conditions is evident in Iran both temporally and spatially. The other part of the study determined that heat and cold stress and heat comfort had a positive trend (fewer than 60 stations) in parts of Iran, a negative trend in some other parts (more than 50 stations), and no specific trend in the remaining parts (more than 250 stations). Most of the northern stations, especially on the Caspian coast, have been shown to have a positive trend in the event of cold stress. Indeed, extreme bioclimatic conditions (very cold and hot conditions) have been rising in both the southern and northern latitudes of the country. Even in southern parts, a positive trend of cold and very cold conditions can be observed at some stations.
Visceral leishmaniasis (VL) as a vector-borne disease, is an endemic in the northwest and south of Iran and sporadic in other areas in the country. This study was performed to investigate the Granger causality analysis of the impacts of climatic factors on VL in northwestern Iran throughout the period from 1995 to 2019. In a longitudinal study, the epidemiological data of patients suffering from VL were collected from the health centers and hospitals in Meshkinshahr County, Ardabil province, between 1995 and 2019. Moreover, the environmental and climatic data of each location, such as temperature, humidity, rainfall, the number of frost and warm days in the year, were obtained from the meteorological center of the county and put into the Excel software. The incidence rate of VL was modeled by time series analysis and to compare its relationship with other time series covariates, the Granger causality analysis was used. The results of Granger causality analysis showed that some climatic variables including daily mean temperature, absolute minimum temperature, maximum and minimum temperature and maximum humidity were the main factors affecting the prevalence of VL in northwestern Iran. The findings greatly demonstrated that the potential of Granger causality in epidemiologic status of VL in northwestern Iran. Moreover, the results suggest that in addition to patient-related and biological factors, environmental and climatic factors such as temperature and humidity also play a major role in completing the transmittance cycle of VL in an endemic focus.
In recent years, there have been considerable changes in the distribution of diseases that are potentially tied to ongoing climate variability. The aim of this study was to investigate the association between the incidence of cutaneous leishmaniasis (CL) and climatic factors in an Iranian city (Isfahan), which had the highest incidence of CL in the country. CL incidence and meteorological data were acquired from April 2010 to March 2017 (108 months) for Isfahan City. Univariate and multivariate seasonal autoregressive integrated moving average (SARIMA), generalized additive models (GAM), and generalized additive mixed models (GAMM) were used to identify the association between CL cases and meteorological variables, and forecast CL incidence. AIC, BIC, and residual tests were used to test the goodness of fit of SARIMA models; and R(2) was used for GAM/GAMM. 6798 CL cases were recorded during this time. The incidence had a seasonal pattern and the highest number of cases was recorded from August to October. In univariate SARIMA, (1,0,1) (0,1,1)(12) was the best fit for predicting CL incidence (AIC=8.09, BIC=8.32). Time series regression (1,0,1) (0,1,1)(12) showed that monthly mean humidity after 4-month lag was inversely related to CL incidence (AIC=8.53, BIC=8.66). GAMM results showed that average temperature with 2-month lag, average relative humidity with 3-month lag, monthly cumulative rainfall with 1-month lag, and monthly sunshine hours with 1-month lag were related to CL incidence (R(2)=0.94). The impact of meteorological variables on the incidence of CL is not linear and GAM models that include non-linear structures are a better fit for prediction. In Isfahan, Iran, meteorological variables can greatly predict the incidence of CL, and these variables can be used for predicting outbreaks.
PURPOSE: The aim of the present study was to investigate the effect of short-term exposure to ambient black carbon (BC) on daily cause-specific mortality, including mortality due to respiratory, cardiovascular, ischemic heart and cerebrovascular diseases in Tehran, Iran. MATERIALS AND METHODS: Daily non-accidental death counts, meteorological data and hourly concentrations of air pollutants from 2014 to 2017 were collected in Tehran. A distributed lag non-linear model was used to assess the association between exposure to BC and daily mortality. RESULTS: The mean daily BC concentration during the study period was 3.96?±?1.19 µg/m(3). The results indicated that BC was significantly associated with cardiovascular, ischemic heart disease, and cerebrovascular mortality, but not with respiratory mortality. In first model, each 10 µg/m(3) increase in at lag 3, lag 4 and lag 5 were associated with cardiovascular mortality in 16-65 year age group with the relative risks (RRs) of 1.17 (95?% CI: 1.02-1.33), 1.17 (95?% CI: 1.04-1.31) and 1.12 (95?% CI: 1.02-1.24), respectively. The highest mortality rate per 10 µg/m(3) increase in exposure was found for ischemic heart diseases with RR of 3.98 (95?% CI: 1.04-1.81, lag 01) for 16-65 age group. Cerebrovascular mortality was associated with 10 µg/m(3) increases in non-cumulative exposure with RR of 1.17 (95?% 1.009-1.35, lag 5) in the age group ? 65 years. In the second model for a 10 µg/m(3) increase in BC, cardiovascular mortality at specific lag days (5 and 6 days) in the age group ? 16 years were associated with RR of 1.34 (95?% CI 1.08-1.66) and 1.35(95?% CI 1.02-1.77), respectively. CONCLUSIONS: This study in Tehran found significant effects of BC exposure on daily mortality for cardiovascular, ischemic heart disease, cerebrovascular disease. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s40201-021-00659-0.
Climate change may be associated with human morbidity and mortality through direct and indirect effects. Ahvaz is one of the hottest cities in the world. The aim of this study was to investigate the relation between physiological Equivalent Temperature (PET) and non-accidental, cardiovascular and respiratory disease mortality in Ahvaz, Iran. Distributed Lag Non-linear Models (DLNM) combined with quasi-Poisson regression were used to investigate the effect of PET on death. The effect of time trend, air pollutants (NO(2), SO(2) and PM(10)), and weekdays were adjusted.The results showed that in cold stress [1st percentile of PET (2.7 °C) relative to 25th percentile (11.9 °C)] the risk of total respiratory mortality, respiratory mortality in men, and mortality in people under 65 year olds, significantly decreased in the cumulative lags of 0-2, 0-6 and 0-13; but the risk of respiratory mortality increased in the elderly and in the final lags. In contrast, heat stress [99th percentile of PET (44.9 °C) relative to 75th percentile (43.4 °C)] significantly increased the risk of total cardiovascular mortality (CVD), cardiovascular mortality in men, ischemic heart disease and cerebrovascular disease mortality in lags 0 and 0-2. It seems that high PET values increase the risk of cardiovascular mortality, while low PET values increase respiratory mortality only among the elderly in Ahvaz.
Although Ahvaz is considered as one of the warmest cities around the world, few epidemiological studies have been conducted on the adverse effects of temperature on human health using thermal indices in this city. This study investigates the relation between physiologically equivalent temperature (PET) and respiratory hospital admissions in Ahvaz. Distributed lag non-linear models (DLNMs) combined with quasi-Poisson regression models were used to investigate the relation between PET and respiratory disease hospital admissions, adjusted for the effect of time trend, air pollutants (NO(2), SO(2), and PM(10)), and weekdays. The analysis was performed by utilizing R software. Low PET values significantly decreased the risk of hospital admissions for total respiratory diseases, respiratory diseases in men and women, chronic obstructive pulmonary diseases (COPD), and bronchiectasis. However, low PET (16.9°C) in all lags except lag 0-30 significantly increased the risk of hospital admissions for asthma. The results indicate that in Ahvaz, which has a warm climate, cold weather decreased overall respiratory hospital admissions, except for asthma.
This study aimed to estimate morbidity risk/number attributed to air extreme temperatures using time-stratified case crossover study and distributed lag non-linear model in a region of Iran during 2015-2019. A time-stratified case crossover design based on aggregated exposure data was used in this study. In order to have no overlap bias in the estimations, a fixed and disjointed window by using 1-month strata was used in the design. A conditional Poisson regression model allowing for over dispersion (Quasi-Poisson) was applied into Distributed Lag Non-linear Model (DLNM). Different approaches were applied to estimate Optimum Temperature (OT). In the model, the interaction effect between temperature and humidity was assessed to see if the impact of heat or cold on Hospital Admissions (HAs) are different between different levels of humidity. The cumulative effect of heat during 21 days was not significant and it was the cold that had significant cumulative adverse effect on all groups. While the number of HAs attributed to any ranges of heat, including medium, high, extreme, and even all values were negligible, but a large number was attributable to cold values; about 10000 HAs were attributable to all values of cold temperature, of which about 9000 were attributed to medium range and about 1000 and less than 500 were attributed to high and extreme values of cold, respectively. This study highlights the need for interventions in cold seasons by policymakers. The results inform researchers as well as policy makers to address both men and women and elderly when any plan or preventive program is developed in the area under study.
This study was conducted in order to explore the effect of thermal comfort on all-cause mortality using three indices in different lag times, in a semi-arid to dry region of Iran. Three thermal comfort indices based on the energy balance of the human body including physiologically equivalent temperature (PET), predicted mean vote (PMV), and standard effective temperature (SET) were used to assess the effects of thermal comfort on mortality. Distributed lag non-linear models were used to assess the relation. The natural cubic spline was chosen as the basis function for the space of predictors and lags, with 4 degrees of freedom. All three indices showed the same pattern in general, but the relative risk for PMV values were more than the other indices in different lags. For all three indices, lag 0 had the highest relative risk of mortality in warm and hot indices. The relative risk for warm and hot values was more than cool and cold values in lag 0, and for the PMV index, it was larger than the two other indices. These results were different in lags 5 to 8, and the relative risks for cool and cold values were more than warm and hot values. This study showed that heat stress has a stronger and more immediate adverse effect on mortality than cold stress. Also, the elderly and females are more vulnerable than others. The most apparent effect was seen in lags 0-12.
Arid and semi-arid climates, including that of Iran, are more susceptible to environmental changes due to their special ecological structure than other climates. Therefore, climate change in these areas appears to have significant effects on agricultural and food production systems. The present study explores the effect of climatic changes on total horticultural production and food security in agro-ecological zones of Iran. The study was conducted in two steps. In the first step, the effects of climatic parameters on total horticultural production were investigated using time series data (1985-2017) and a regression model. In the second step, due to the important role of horticultural products in per capita food consumption in Iran, the effect of climate parameters on food security was also examined. Results revealed that total horticultural production was influenced by temperature, evapotranspiration, and wind speed at the 0.05 level. With the increase in temperature (at a rate of one unit), total horticultural production is reduced to 0.01 million tons. Evapotranspiration and wind speed have had a negative effect on total horticultural production, and with increasing evapotranspiration and wind speed, total horticultural production was 0.029 and 0.008 million, respectively, tons decreased. Also, food security was influenced by temperature, precipitation, and wind speed.
Objective: To determine the significance of temperature, rainfall and humidity in the seasonal abundance of Anopheles stephensi in southern Iran. Methods: Data on the monthly abundance of Anopheles stephensi larvae and adults were gathered from earlier studies conducted between 2002 and 2019 in malaria prone areas of southeastern Iran. Climatic data for the studied counties were obtained from climatology stations. Generalized estimating equations method was used for cluster correlation of data for each study site in different years. Results: A significant relationship was found between monthly density of adult and larvae of Anopheles stephensi and precipitation, max temperature and mean temperature, both with simple and multiple generalized estimating equations analysis (P<0.05). But when analysis was done with one month lag, only relationship between monthly density of adults and larvae of Anopheles stephensi and max temperature was significant (P<0.05). Conclusions: This study provides a basis for developing multivariate time series models, which can be used to develop improved appropriate epidemic prediction systems for these areas. Long-term entomological study in the studied sites by expert teams is recommended to compare the abundance of malaria vectors in the different areas and their association with climatic variables.
BACKGROUND: The Crimean-Congo Hemorrhagic fever (CCHF) is endemic in Iran and has a high fatality rate. The aim of this study was to investigate the association between CCHF incidence and meteorological variables in Zahedan district, which has a high incidence of this disease. METHODS: Data about meteorological variables and CCHF incidence was inquired from 2010 to 2017 for Zahedan district. The analysis was performed using univariate and multivariate Seasonal Autoregressive Integrated Moving Average (SARIMA) models and Generalized Additive Models (GAM) using R software. AIC, BIC and residual tests were used to test the goodness of fit of SARIMA models, and R(2) was used to select the best model in GAM/GAMM. RESULTS: During the years under study, 190 confirmed cases of CCHF were identified in Zahedan district. The fatality rate of the disease was 8.42%. The disease trend followed a seasonal pattern. The results of multivariate SARIMA showed the (0,1,1) (0,1,1)(12) model with maximum monthly temperature lagged 5?months, forecasted the disease better than other models. In the GAM, monthly average temperature lagged 5?months, and the monthly minimum of relative humidity and total monthly rainfall without lag, had a nonlinear relation with the incidence of CCHF. CONCLUSIONS: Meteorological variables can affect CCHF occurrence.
OBJECTIVE: By studying the effect of environmental factors on health, it is clear that geographical, climatic and environmental factors have a significant impact on human health. This study, based on the data of the patients with breast cancer in Iran since 2010 to 2014 and using the statistical methods has determined the effect of geographical features of Iran (solar radiation status, radiation angle) on the frequency and distribution of this disease. RESULTS: The maximum amount of total solar radiation occurs in the vicinity (surrounding) of the tropic of cancer, which covers some parts of the south of Iran and in the atmosphere of the northern latitudes of Iran. The amount of humidity and cloudiness is more than the southern latitudes, which causes more reflection of short waves of the sun during the day. Findings showed that the rate of breast cancer in low latitudes is higher than high latitudes. It was also found that with increasing longitude, the rate of cancer increases significantly due to the high thickness of the atmosphere and receiving more sunlight in the electromagnetic spectrum, as well as dry air and low water vapor in low altitude areas of eastern and southeastern Iran.
Few studies have investigated the different extreme temperature effects (heat-cold) of one geographical location at the same time in Iran. This study was conducted to assess the impact of heat and cold waves on mortality in Urmia city, which has a cold and mountainous climate. Distributed Lag Non-linear Models combined with a quasi-Poisson regression were used to assess the impact of heat (HW) and cold waves (CW) on mortality in subgroups, controlled for potential confounders such as long-term trend of daily mortality, day of week effect, holidays, mean temperature, humidity, wind speed and air pollutants. The heat/cold effect was divided into two general categories A-main effect (the effect caused by temperature), B-added effect (the effect caused by persistence of extreme temperature). Results show that there was no relation between HW and respiratory and cardiovascular death, but in main effects, HW(H1) significantly increased, the risk of Non-Accidental Death (NAD) in lag 0 (Cumulative Excess Risk (CER) (NAD) = 31(CI; 4-65)). Also in added effects, HW had a significant effect on NAD (CER (H1; NAD; lag;0-2) = 31(CI; 5, 51), CER (H2; NAD; lag;0-2) = 26(CI; 6, 48)). There was no relation between CW and respiratory death and cardiovascular death, but in added effects, CW((C1)) significantly decreased, the risk of non-accidental death in initial lags (CER (C1; NAD; lag;0-2) = 19 (CI; 35, 2)). It seems that high temperatures and heat waves increase the risk of non-accidental mortality in northwest of Iran.
BACKGROUND: Risk perception is an important predictor to mitigate climate change effects which can produce mental health consequences such as anxiety and depression. For developing policies of climate risk adaptation, awareness of public attitudes, beliefs, and perception is essential. At this study, researchers tried to focus on the often “unseen” psychological aspects of climate change. MATERIALS AND METHODS: A qualitative approach was done with a consistent content analysis method. The study consisted of 33 participants including ordinary people and experts in disasters and climate change. Purposeful sampling was adopted until data saturation. The data collection was performed through in-depth and semi-structured interviews. All interviews were transcribed after listening again and again and reading several times to catch an overall understanding of the interviews. RESULTS: The main theme of the study was “Complexity nature of climate change risk perception” and related categories including “the Mental health dimension,” “the Cognitive dimension” and “Interaction of imposed components.” The structure of the research community strongly reflected effects of cultural and religious factors in all aspects of community life. Participants’ life experiences of extreme events were associated to their perception of climate change. CONCLUSIONS: Risk perception is multifactorial and complicate and should clearly be understood to improve community participation to manage climate change-related risks. We propose that authorities and related managers should pay attention to it as a priority. This may assist in developing research on public mental health practices.
BACKGROUND: The prevalence of Acute Myocardial Infarction (AMI) varies from region to region caused by seasonal climate changes and temperature variation. This study aimed to assess the relationship between changing meteorological conditions and incidence of AMI in Iran. METHODS: This retrospective prevalence study was based on medical records of the heart center of Mazandaran Province on all patients diagnosed with AMI in Mazandaran, northern Iran between 2013 and 2015. Patients’ sex and the day, month, year and time of hospital admission were extracted from patients’ records. Moreover, the meteorological reports were gathered. RESULTS: A statistically significant difference was found between the distributions of AMI cases across 12 months of the year (P < 0.01). Fuzzy clustering analysis using 16 different climatic variables showed that March, April, and May were in the same cluster together. The other 9 months were in different clusters. CONCLUSION: Significant increase in AMI was seen in March, April and May (cold to hot weather).
BACKGROUND: Estimating the effects of climate change on human health can help health policy makers plan for the future. In Iran, there are few studies, about investigating the effects of climate change on mortality. This study aimed to project the effect of low (cold) and high (heat) temperature on mortality in a dry region of Iran, Kerman. METHODS: Mortality attributed to temperature was projected by estimating the temperature-mortality relation for the observed data, projection of future temperatures by the statistical downscaling model (SDSM), and quantifying the attributable fraction by applying the observed temperature-mortality relation on the projected temperature. Climate change projection was done by three climate scenarios base on Representative Concentration Pathways (RCP2.6, RCP4.5 and RCP8.5). Adaptation was considered by using different minimum mortality temperatures (MMT) and risk reduction approaches. The current decade (2010-19) was considered as the reference period. RESULTS: All three climate change scenarios, showed that the mean of temperature will rise about 1 °C, by 2050 in Kerman. The number of deaths attributed to heat were obviously higher than cold in all periods. Assuming no adaptation, over 3700 deaths attributed to temperature will happen in each decade (2020s, 2030s and 2040s) in the future, in which over 3000 deaths will be due to heat and over 450 due to cold. In the predictions, as Minimum Mortality Temperature (MMT) went up, the contribution of heat to mortality slightly decreased, and cold temperature played a more important role. By considering the risk reduction due to adaptation, the contribution of heat in mortality slightly and insignificantly decreased. CONCLUSION: The results showed that although low temperatures will contribute to temperature-related mortality in the future, but heat will be a stronger risk factor for mortality, especially if adaptation is low.
Background: Iran is a disaster-prone country, and many flood events occur in its provinces annually. The unprecedented amount of rainfall in the northern region of Iran (from March 17 to 22, 2019) led to flash flooding of the Golestan Province. Objectives: This study assessed the challenges and strengths of health-related needs in the first 10 days after the great flood in Golestan; via interviews with experts. Methods: This cross-sectional and qualitative study was carried out in Gonbad-e-Kavoos, Anbar Alum, Aq-Qala, Simin Shahr, and Gomishan cities of the flood-hit province of Golestan from March 21, to April 13 in 2019. The data were collected using the researcher’s field observations and interviews with 26 experts and policymakers. Results: The findings were categorized into 10 main groups namely mental health, environmental health, health education, maternal, infant, and child health, nutrition, epidemics, drugs, mobile hospitals, non-communicable diseases, and management. Environmental health issues were faced with a wide range of challenges. Conclusion: Due to the insufficient development of many health infrastructures in underdeveloped and developing countries, health policymakers and disaster management experts should collaborate before and after the disaster to detect and resolve the flaws. This could help reduce health problems and challenges when a natural disaster occurs, particularly by diminishing the number of morbidities and mortalities.
OBJECTIVES: This study investigated the modification of temperature effects on cardiovascular and respiratory mortality by air pollutants (particulate matter less than 2.5 and 10 µm in diameter [respectively], ozone, nitrogen dioxide, carbon monoxide, and sulfur dioxide). METHODS: Poisson additive models with a penalized distributed lag non-linear model were used to assess the association of air temperature with the daily number of deaths from cardiovascular and respiratory diseases in Ahvaz, Iran from March 21, 2014 to March 20, 2018, controlling for day of the week, holidays, relative humidity, wind speed, air pollutants, and seasonal and long-term trends. Subgroup analyses were conducted to evaluate the effect modification for sex and age group. To assess the modification of air pollutants on temperature effects, the level of each pollutant was categorized as either greater than the median value or less than/equal to the median value. RESULTS: We found no significant associations between temperature and cardiovascular and respiratory mortality. In the subgroup analyses, however, high temperatures were significantly associated with an increased risk of cardiovascular mortality among those 75 years old and older, with the strongest effect observed on day 0 relative to exposure. The results revealed a lack of interactive effects between temperature and air pollutants on cardiovascular and respiratory mortality. CONCLUSIONS: A weak but significant association was found between high temperature and cardiovascular mortality, but only in elderly people. Air pollution did not significantly modify the effect of ambient temperature on cardiovascular and respiratory mortality.
Investigation of temperature extremes is very important as one of the most important climate parameters in different parts. If exposed to enough heat, humans will suffer from extreme heat. Maximum temperature and heat can adversely affect many living organisms. The effects of extreme heat on people with chronic lung disease, including asthma and emphysema, are greater; even for people with healthy lungs, outdoor activities are not recommended during high ozone levels. The purpose of this study is to monitor and analyze the effects of atmospheric temperature extreme and extreme heat on human health in Central Iran. Therefore, the minimum and maximum data of 15 synoptic stations in the study area for the period (1988-2018) using hybrid artificial neural network (HANN) and adaptive neuro-fuzzy inference system (ANFIS) models were used. Finally, multi-criteria decision-making (MCDM) models TOSIS and SAW were used to prioritize the areas exposed to rising temperature. The results showed that according to ANFIS modelling for predicting extreme temperatures, the lowest mean training error and the mean error of validation for the minimum temperature were equal to 0.10 for the Yazd Station and 1.66% for the Damghan station. The lowest mean training error and the mean error of validation for the maximum extreme temperature obtained 0.016 for the Garmsar station and 9.39% for the Shahroud station. The maximum extreme temperature of two stations of Garmsar and Bafgh (1 and 0.9689, respectively) was more exposed to extreme temperatures based on the TOPSIS model. Garmsar and Salafchegan Stations (1 and 0.9873, respectively) were more exposed to extreme temperatures based on the SAW model. Climate change is fundamentally changing the Earth’s climate system in a way that directly and indirectly endangers human physical and mental health. Severe increase in temperature is directly associated with death from cardiovascular and respiratory diseases, especially in the elderly. Also in the study area, the house is a place for peace and comfort for every human being. Climatic and weather conditions have a direct impact on creating a sense of comfort in any architectural space. Proper heating and air conditioning in the interior of the building is another case of architecture that will not be easy because this architectural issue is related to the comfort or non-comfort of man, and the concepts of heat or cold are mostly due to the natural feeling of man and his physiological conditions. The rising trend of thermal stresses in the studied stations increases the need to pay attention to the issue of thermal stresses and the spread of diseases (heat attack, syncope, and muscle cramps) in terms of crisis planning and management.
SARS CoV-2 (COVID-19) Coronavirus cases are confirmed throughout the world and millions of people are being put into quarantine. A better understanding of the effective parameters in infection spreading can bring about a logical measurement toward COVID-19. The effect of climatic factors on spreading of COVID-19 can play an important role in the new Coronavirus outbreak. In this study, the main parameters, including the number of infected people with COVID-19, population density, intra-provincial movement, and infection days to end of the study period, average temperature, average precipitation, humidity, wind speed, and average solar radiation investigated to understand how can these parameters effects on COVID-19 spreading in Iran? The Partial correlation coefficient (PCC) and Sobol’-Jansen methods are used for analyzing the effect and correlation of variables with the COVID-19 spreading rate. The result of sensitivity analysis shows that the population density, intra-provincial movement have a direct relationship with the infection outbreak. Conversely, areas with low values of wind speed, humidity, and solar radiation exposure to a high rate of infection that support the virus’s survival. The provinces such as Tehran, Mazandaran, Alborz, Gilan, and Qom are more susceptible to infection because of high population density, intra-provincial movements and high humidity rate in comparison with Southern provinces.
BACKGROUND: Cutaneous leishmaniasis (CL) is a dermal and parasitic disease.. The aim of this study was to determine the effect of environmental and climate factors on spatial distribution of CL in northeastern Iran by utilizing remote sensing from 20 March 2016 to 19 March 2017. METHODS: In this ecological study, the data were divided into two parts: The descriptive data on human CL cases were gathered from Communicable Diseases center of Iran. The remote sensing techniques and satellite imagery data (TRMM, MODIS-Aqua, MODIS-Terra and AMSR-2 with spatial resolution 0.25°, 0.05°, 5600m and 10km) of environmental and climate factors were used to determine the spatial pattern changes of cutaneous leishmaniasis incidence. RESULTS: The incidence of CL in North Khorasan, Razavi Khorasan, and South Khorasan was 35.80 per 100,000 people (309/863092), 34.14 per 100,000 people (2197/6,434,501) and 7.67 per 100,000 people (59/768,898), respectively. The incidence of CL had the highest correlation with soil moisture and evapotranspiration. Moreover, the incidence of disease was significantly correlated with Normalized Difference Vegetation Index (NDVI) and air humidity while it had the lowest correlation with rainfall. Furthermore, the CL incidence had an indirect correlation relation with the air temperature meaning that with an increase in the temperature, the incidence of disease decreased. CONCLUSION: As such, the incidence of disease was also higher in the northern regions; most areas of North Khorasan and northern regions of Razavi Khorasan; where the rainfall, vegetation, specific humidity, evapotranspiration, and soil moisture was higher than the southern areas.
BACKGROUND: Ensuring public health is crucial in any policy debate on climate change. Paris Agreement on climate change is a global contract, through which countries have committed themselves to a public health treaty. The agreement has laid the foundation for mitigation and adaptation. This study was conducted to provide an evidence-based framework for policy-making in the health system of Iran in order to reduce the adverse effects of climate change on public health and to increase the adaptation of the health system as a result. METHODS: This is a qualitative study. We first used Delphi method to extract the components of Paris Agreement on climate change that were related to the functions and policymaking of health system in Iran. Twenty-three experts in health and climate change were identified purposefully and through snowball sampling as participants in Delphi. Data collection instrument was a structured questionnaire. We used SPSS software version 25 for data analysis based on the descriptive indices including the mean, the percentage of consensus above 75%, and the Kendall coordination coefficient. RESULTS: Seventy-nine components classified within nine categories were extracted. The most important examples of the implementation of Paris Agreement on climate change in the health system of Iran were: participation in the formulation of strategies for mitigation and adaptation, identifying vulnerable groups, assessing vulnerability, increasing the capacity of health services delivery during extreme events, using early warning systems, using new technologies to increase the adaptation, evaluation of interventions, financial support, increasing the number of researches, increasing the knowledge and skills of staff, and finally public awareness. CONCLUSIONS: Evidence-based policy-making is pivotal to develop effective programs to control the health effects of climate change. This research provided policy translation and customization of micro and macro provisions of Paris Agreement on climate change, in line with the political context of health system in Iran. Our finding will pave the ground, we envisage, for further steps towards capacity building and enhancement of resiliency of the health system, adaptation interventions, and evaluation, identification of barriers and facilitators for adaptation and decreasing the adverse health effects caused by the climate change, in Iran and perhaps beyond.
Objective: To establish a spatial geo-database for scorpions in Iran, and to identify the suitable ecological niches for the most dangerous scorpion species under different climate change scenarios. Methods: The spatial distribution of six poisonous scorpion species of Iran were modeled: Hemiscorpius lepturus, Androctonus crassicauda, Mesobuthus eupeus, Hottentotta saulcyi, Hottentotta zagrosensis, and Odontobuthus (O.) doriae, under RCP2.6 and RCP8.5 climate change scenarios. The MaxEnt ecological niche model was used to predict climate suitability for these scorpion species in the 2030s and 2050s, and the data were compared with environmental suitability under the current bioclimatic data. Results: A total of 73 species and subspecies of scorpions belonging to 19 genera in Iran were recorded. Khuzestan Province has the highest species diversity with 34 species and subspecies. The most poisonous scorpion species of Iran are scattered in the semi-arid climates, at an altitudinal range between 11 m and 2 954 m above sea level. It is projected that O. doriae, Androctonus crassicauda and Mesobuthus eupeus species would be widely distributed in most parts of the country, whereas the most suitable ecological niches for the other species would be limited to the west and/or southwestern part of Iran. Conclusions: Although the environmental suitability for all the species would change under the two climate change scenarios, the change would be more significant for O. doriae under RCP8.5 in the 2050s. These findings can be used as basis for future studies in the areas with the highest environmental suitability for the most dangerous scorpion species to fill the gaps in the ecology of scorpion species in these areas.
