J Arthropod-Borne Dis, December 2015, 9(2): 148–160 MR Shirzadi et al.: Dynamic Relations … 148 Original Article Dynamic Relations between Incidence of Zoonotic Cutaneous Leishmaniasis and Climatic Factors in Golestan Province, Iran Mohammad Reza Shirzadi 1, *Abolfazl Mollalo 2, Mohammad Reza Yaghoobi-Ershadi 3 1Communicable Diseases Management Center, Ministry of Health and Medical Education, Tehran, Iran 2Department of Geo-spatial Information System (GIS), Center of Excellence in GIS, K. N. Toosi University of Technology, Tehran, Iran 3Department of Medical Entomology and Vector Control, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran (Received 14 June 2014; accepted 1 Oct 2014) Abstract Background: Zoonotic Cutaneous Leishmaniasis (ZCL), an important public health problem in Iran, is sensitive to climate conditions. This study aimed to examine dynamic relations between the climate factors and incidence of ZCL in Golestan Province, northern Iran during 2010–2012. Methods: Data of monthly climatic factors, including temperature variables, relative humidity variables, evapora- tion, total rainfall, and number of freezing and rainy days together with monthly ZCL incidence were used. Spear- man rank correlation was carried out to explain associations between the monthly ZCL incidence rate and climate factors at 0, 1, 2, 3 and 4 months lagged periods. Pearson’s correlation analysis was conducted to examine the type and strength of relationships between the spatially averaged climate factors and ZCL incidence rate in district level. Stepwise multiple regression was used to find the best combination of independent climatic variables, which predict the ZCL incidence. Results: Spearman correlation analysis indicated that the highest correlations between climate factors and monthly ZCL incidence were established when the climate time-series lagged the ZCL incidence series, especially two month prior to disease incidence. Based on the results of the both Spearman rank correlation and Pearson correlation analy- ses, ZCL incidences in Golestan Province tend to be more prevalent in areas with higher temperature, lower relative humidity, lower total rainfall, higher evaporation and lower number of rainy days. The results of stepwise regression analysis indicated that minimum temperature, mean humidity, and rainfall had considerable effect on ZCL incidence. Conclusion: Climate factors are major determinants of ZCL incidence rate in Golestan Province and such climate conditions provide favourable conditions for propagation and transmission of ZCL in this endemic area. Keywords: Zoonotic Cutaneous Leishmaniasis (ZCL), Climate factors, Correlation analysis, GIS, Iran Introduction Leishmaniasis is an environmental de- pendent disease affected by a variety of fac- tors, amongst which climate factors are con- sidered to play major role in frequency of the disease (Patz et al. 2005). It represents significant socio-economic burden to society and psychological disfiguring effect on pa- tients with permanent scars, predominantly in developing countries including Iran (Yag- hoobi-Ershadi et al. 2013). The disease is one of the most important health problems in Iran and its prevention and surveillance is one of the WHO priorities (WHA 2007). Leishmaniasis in Iran has mainly three clinical forms in- cluding cutaneous leishmaniasis (CL), vis- ceral leishmaniasis (VL) and mucocutaneous leishmaniasis (MCL), amongst which CL is the most common form of leishmaniasis. Although, CL can be seen in Zoonotic (ZCL) and Anthroponotic (ACL) forms, about 80 % of cases reported in the country are of ZCL form (Yaghoobi-Ershadi 2012). Zoonotic Cu- *Corresponding author: Mr Abolfazl Mollalo, Email: a_mollalo@yahoo.com http://jad.tums.ac.ir Published Online: March 11, 2015 J Arthropod-Borne Dis, December 2015, 9(2): 148–160 MR Shirzadi et al.: Dynamic Relations … 149 taneous Leishmaniasis due to Leishmania major is still a great and increasing public health problem in many rural areas of 17 out of 31 provinces of Iran (Akhavan et al. 2010). According to the published statistics by the WHO, number of CL cases in this country during the period of 1998 to 2009 generally increased from 18,560 to 24,586 patients (WHO 2012). Fig. 1 shows fre- quency of CL occurrence in Iran, during the period of 1998–2009. Although ZCL yearly afflicts considerable numbers of people from different parts of Iran, inadequate attention has been paid to monitoring and surveillance of the disease. Golestan Province, an endemic province of ZCL in Iran, with several significant spa- tial and spatio-temporal hotspots of ZCL especially in northern and northeastern parts, is constantly at risk of infection (Mollalo et al. 2015). Previous entomological studies carried out in this province proved that ZCL is caused by the Leishmania major (Yaki- moff and Schokhor) (Kinetoplastida: Try- panosomatidae), the main vector is Phle- botomus papatasi Scopoli (Diptera: Psy- chodidae) also the main reservoir host is Rhombomys opimus (great gerbil) (Rassi et al. 2008, Sharbatkhori et al. 2014). Climate is one of the most significant factors that might affect the spatial distribu- tion of many infectious diseases including leishmaniasis. It affects through control on host or vector physiology and behaviour di- rectly (e.g. effect of rainfall on parasite de- velopment and vector competence) or indi- rectly (e.g. effect of temperature on the range and abundance of the sand fly species that act as vectors or through socio-economic changes that affect the amount of human contacts with the transmission cycle) (Ready 2008). Climate would be expected to modify the spatial and temporal distribution of the leishmaniasis (Kelly-Hope and Thomson 2008). New methodological advances, such as Geographic Information System (GIS) over last 30 years has provided an ability to better understand the etiology of the diseases in shorter time and less costs. GIS is a worth- while tool in studying infectious diseases (Moore and Carpenter 1999). In spite of broad studies on the association between climate variables and incidences of different kinds of infectious diseases throughout the world, very little researches in regards of leishmaniasis has been reported from Iran. Several studies in various parts of the world had linked different forms of leishmaniasis to environmental factors. In the study region, Mollalo et al. (2014), linked the normalized difference vegetation index (NDVI), as a general proxy indicator of climate changes (Including temperature, humidity and rain- fall), with incidence of CL and demonstrated that most of cases were occurred in non- vegetative or low-density vegetation areas. During 1991–2001 in Costa Rica, Chaves and Pascual (2006) studied monthly CL inci- dence by using mathematical models. They showed that CL has cycles of about three years related to temperature and indices of the El Niño Southern Oscillation. Using such a model, they could predict the incidence of CL up to 12 months ahead with an accuracy of between 72 % and 77 % depending on pre- diction time. In central Tunisia, Toumi et al. (2012), investigated temporal dynamics and impacts of climate factors (Including rain- fall, temperature and humidity) on incidence of ZCL. Their results showed seasonality during the same epidemiologic year so that ZCL incidence raised by 1.8 % when there was 1 mm increase in the rainfall lagged by 12 to 14 months and by 5.0 % when there was a 1 % increase in humidity from July to September in the same epidemiologic year. To the best of our knowledge, this is the first attempt in terms of assessing the rela- tionship between climate factors and ZCL incidence in quantitative manner in surveyed area. Development of low-cost and efficient management tools for effective control of the http://jad.tums.ac.ir Published Online: March 11, 2015 J Arthropod-Borne Dis, December 2015, 9(2): 148–160 MR Shirzadi et al.: Dynamic Relations … 150 ZCL is an important objective, which requires comprehensive efforts and studies including the ecology of the disease and role of the climate change. For this purpose, this study was designed to investigate the relations between the climate factors and incidence of ZCL to gain deeper insight into the possible interactions between climate conditions and ZCL incidence in Golestan Province of Iran. Materials and Methods Study area Golestan Province consists of 14 counties with 60 districts located in north-east of Iran (36° 30’ to 38° 8’ N and 53° 57’ to 56° 22’ E) bounded on the north by Turkmenistan country, on the west by Mazandaran Prov- ince and the Caspian Sea, on the south by Semnan Province, and on the east by North- ern-Khorasan Province. The geographical po- sition of this province provides a unique area with very diverse climate. As northern re- gions are located in the arid and semi-arid climate, southern regions represent a moun- tainous climate, and central and southern west regions are located in a moderate Mediterranean climate. Based on the cli- matic conditions of the region during the study period, the monthly maximum and minimum temperature were 30.7 °C and 5.09 °C in July 2011 and February 2012, respectively. The total annual rainfall was a minimum of 0 mm in July 2010 and its maxi- mum of 124.18 mm in October 2011. The minimum monthly relative humidity was 51.78 % (June 2010) and the maximum was 79.64 % (March 2010) (Golestan Province Meteorological Center, unpublished data). Data Collection The Iranian primary health care (PHC) sys- tem was well founded especially in rural areas. More than 16,000 health houses over the country cover almost 95 % of the rural areas. Health workers are responsible to de- liver primary healthcare and to keep health records of people to the Center for Disease Control and Prevention (CDC) of their study area. Monthly ZCL incidence records over the period of January 2010 to December 2012 (36 months) were considered for analysis of their temporal correlations and lagged effects. During the study period a total of 2,893 ZCL cases, diagnosed by direct smear examination, were officially reported by CDC of Golestan Province. The data were checked in a meticu- lous manner to prevent any possible mis- takes and were mapped at district level using ArcGIS Desktop software version 9.3 (ESRI Inc, Redlands, CA). Fig. 3 shows the annual ZCL incidence rate at district level. Climate data Data of climate factors were obtained from Golestan Province Meteorological Center. The data were collected from synoptic sta- tions in Golestan Province and synoptic sta- tions in adjacent provinces including North- ern-Khorasan and Semnan during September 2009 to December 2012 (40 months) for more accurate interpolation. Climatic factors, in- cluding the minimum, maximum and mean temperature (°C), minimum, maximum and mean relative humidity (%), mean evapo- ration (mm), total rainfall (mm), and number of freezing and rainy days were calculated for each district based on the observation of synoptic stations in mentioned provinces. After collection of climate data, they were entered into GIS environment for further analyses. This has been done through the following procedure: 1) The monthly average of measurements of the above factors for each synoptic station was calculated. 2) A point layer was created for observation stations and the monthly averages of factors associated with their related points. 3) For any of the factors, using inverse dis- tance weighting (IDW) method, a raster was created by interpolating the monthly average http://jad.tums.ac.ir Published Online: March 11, 2015 J Arthropod-Borne Dis, December 2015, 9(2): 148–160 MR Shirzadi et al.: Dynamic Relations … 151 values of those factors between stations. 4) For each factors, its raster was overlaid with the polygon layer of the district boundaries. For each district, the average of the raster cells inside district polygon was assumed as the value of the factor in that district and analyzed to recognize possible relationships with ZCL incidence. Fig. 2 shows maps of climatic factors at district level in Golestan using IDW method. Geographic Information System was used in conjunction with statistical analytical meth- ods to analyze the relations between ZCL inci- dence and climate factors in the study area. Spatial statistics analyses To assess the correlation between climate factors and ZCL incidence rate, the monthly ZCL incidence was regarded as the depend- ent variable, while climate variables were considered as independent variables. A four- stage approach was adopted to describe and analyze the possible relations of the climatic variables on the incidence of ZCL. Firstly, the monthly and annual ZCL incidences of each district were calculated and mapped. Secondly, Spearman rank correlation was used to examine the association between the cli- mate factors and ZCL incidence rate. In this regard, Cross correlation was performed to detect the lagged effect of climate factors on ZCL incidence rates at global (province) level at 0, 1, 2, 3 and 4 months lagged peri- ods. Thirdly, Pearson’s correlation analysis at local (district) level was conducted to exam- ine the type and strength of relations be- tween the spatially averaged of climate vari- ables and annual ZCL incidence rates in districts. Finally, multivariate stepwise re- gression was used to establish the models to determine the contribution rate of all the climatic factors. Results The monthly trend of climate factors and ZCL incidence rate is shown in Fig. 4. With regard to the lagged effects, it can be visu- ally seen positive associations between aver- age temperature and evaporation with in- crease of ZCL incidence rate, and negative associations between relative humidity, and rainfall with increase of ZCL incidence rate. However, statistical analyses needs to for- mally test whether the results are statistically significant or not. Associations between monthly ZCL inci- dence rate and climate factors were observed at global (province) level at 0, 1, 2, 3 and 4 months lagged periods. Besides, local cor- relation at district level between ZCL inci- dence rate and climate factors was observed using the Pearson correlation analysis. Based on the results of the Spearman rank corre- lation at the province level, positive associa- tions were observed between the monthly ZCL incidence rates with all temperature variables and evaporation. In addition, nega- tive correlations were seen between the monthly ZCL incidence rates with all hu- midity variables, rainfall, number of rainy days and number of freezing days. The time lag(s) of climatic factors preceding ZCL in- cidence at which the series showed that the strongest correlation were obtained by cross- correlation analysis of monthly ZCL inci- dence series and monthly climatic data time- series. Among ten climate factors used in this study, except minimum humidity and rain- fall, highest correlations were found with 2- months lagged period. Moreover, lowest correlations were found 0-month (for all temperature variables, evaporation, rainfall and number of freezing days) and 4-month (for all humidity variables and number of rainy days). Among the climate factors, tem- perature variables showed the highest cor- relation with the monthly ZCL incidence rate whereas rainfall showed the least cor- relations with the monthly ZCL incidence rates. Detailed information of the results of Spearman rank correlation between the http://jad.tums.ac.ir Published Online: March 11, 2015 J Arthropod-Borne Dis, December 2015, 9(2): 148–160 MR Shirzadi et al.: Dynamic Relations … 152 monthly ZCL incidence rates and climate factors at 0, 1, 2, 3 and 4 months lagged pe- riods has presented in Table 1. Pearson’s correlation analyses revealed that positive associations were observed between annual ZCL incidence rates in all 60 districts of province with all temperature variables, evaporation, and number of freezing days. While negative associations were observed with all relative humidity variables, rainfall and number of rainy days. These results indicate that ZCL incidences in Golestan Province tend to be more prevalent in districts with the lowest average relative humidity values as an indicator of drought. However, all the variables except number of freezing days showed similar signs in both analyses. Among the climate factors, relative humidity showed the highest correlation, while minimum temperature showed the least correlations with ZCL incidence rates. Table 2 represents results of the Pearson correlation between the monthly ZCL incidence rates and climate factors. Results of the multivariate stepwise re- gression showed the best model among others, with highest R, R2, and lowest standard error, was the regression model with equation Y= 4.015+0.739* (minimum temperature)-0.841* (mean humidity)-0.7631* (rainfall) (Table 3). The multiple regression showed 0.536 changes of monthly ZCL incidence contributed to the average monthly minimum temperature, mean humidity, and total rainfall. Table 1. Spearman rank correlation between the monthly ZCL incidence rates and climate factors at 0, 1, 2, 3 and 4 months lagged periods, between September 2009 and December 2012 Monthly ZCL Incidence Temperature Min. Temperature Max. Temperature Relative Humidity Min. Relative Humidity 0-Month .403* .399* .368* -.505** -.492** 1-Month .735** .695** .723** -.764** -.712** 2- Month .895** .858** .854** -.776** -.649** 3-Month .800** .780** .749** -.625** -.445** 4-Month .472** .502** .398* -0.278 -0.088 Monthly ZCL Incidence Max. Relative Humidity Evaporation Rainfall No. Rainy Days No. Freezing Days 0-Month -.514** 0.314 -0.166 -.493** -0.306 1-Month -.736** .695** -.383* -.604** -.540** 2- Month -.759** .893** -.497** -.611** -.670** 3-Month -.636** .853** -.551** -.469** -.646** 4-Month -.411* .574** -.336* -0.138 -.451** **.Correlation is significant at the 0.01 level *.Correlation is significant at the 0.05 level Table 2. Results of Pearson correlation analysis between climate factors and ZCL incidences in 60 districts of Golestan Province, Iran, between September 2009 and December 2012 Monthly ZCL Incidence Temperature Min. Temperature Max. Temperature Relative Humidity Min. Relative Humidity Yearly ZCL incidence .150 .035 .106 -.326** -.272* Monthly ZCL Incidence Max. Relative Humidity Evaporation Rainfall No. Rainy Days No. Freezing Days Yearly ZCL incidence -.320** .249 -.210 -.128 .122 **.Correlation is significant at the 0.01 level *.Correlation is significant at the 0.05 level http://jad.tums.ac.ir Published Online: March 11, 2015 J Arthropod-Borne Dis, December 2015, 9(2): 148–160 MR Shirzadi et al.: Dynamic Relations … 153 Fig. 1. Frequency of CL cases in Iran, between 1998 and 2009 Fig. 2. Climatic maps of Golestan Province during 2010–2012, generated by IDW method http://jad.tums.ac.ir Published Online: March 11, 2015 J Arthropod-Borne Dis, December 2015, 9(2): 148–160 MR Shirzadi et al.: Dynamic Relations … 154 Fig. 3. Annual ZCL incidence rate at the district level per 100,000 individuals in Golestan Province, Iran, 2010–2012 http://jad.tums.ac.ir Published Online: March 11, 2015 J Arthropod-Borne Dis, December 2015, 9(2): 148–160 MR Shirzadi et al.: Dynamic Relations … 155 http://jad.tums.ac.ir Published Online: March 11, 2015 J Arthropod-Borne Dis, December 2015, 9(2): 148–160 MR Shirzadi et al.: Dynamic Relations … 156 Fig. 4. Temporal trend of ZCL cases incidence (per 100, 000) concerning mean of climate factors, Golestan Province, Iran, 2010–2012 Table 3. The results of stepwise regression analysis in which 3 out of 10 climate factors were selected Model R R-square Adjusted R2 P-value 6 0.732 0.536 0.534 <0.01 Final regression model: Y=4.015+0.739*(minimum temperature)-0.841*(mean humidity)-0.7631*(rainfall) http://jad.tums.ac.ir Published Online: March 11, 2015 J Arthropod-Borne Dis, December 2015, 9(2): 148–160 MR Shirzadi et al.: Dynamic Relations … 157 Discussion The results of this study both support and extend the findings of previous works where temporal series of climate variables had as- sociated with other vector-borne infectious diseases such as Malaria (Nath and Mwchahary 2012, Zhao et al. 2014) and dengue fever (Goto et al. 2013). Examining of correlations showed statistically significant association between climate factors behind ZCL inci- dence time series by Spearman rank correla- tion. According to results of the Spearman rank correlation, monthly climate factors dy- namically correlated with monthly ZCL in- cidence rate during three years period of study. However, climate factors generally did not show strong correlation with ZCL inci- dence rates in the same months. The best correlations between the climate factors and monthly ZCL incidence rates were observed when climate factors time-series were lagged the ZCL incidence rates. This indicates that climate change prior to the disease active period is an important influencing factor and at least one-month time is needed for climate factors to effect on occurrence of ZCL in humans. It should be noted that the above temporal relationship might vary by different geo- graphic areas due to different seasonal pat- terns in different ecological zones. Previous studies have debated the association between leishmaniasis epidemic and climatic factors in some areas of Iran. Comparison the results of correlation analysis between incidence of cutaneous leishmaniasis and climate factors with studies of Yazdanpanah and Rostamianpur (2013) in Ilam Province, west of Iran, and Mozafari and Bakhshizadeh-Kolooche (2011) in Yazd-Ardakan plain in central part of Iran, indicates that although positive correlation between the average temperature and CL incidence was observed in Ilam, this relation was negative in Yazd. In contrast, both of the studies reported that the association be- tween CL epidemic and relative humidity was not significant, while in our analyses in both local (district) and global (province) levels, relative humidity appeared to be the most significant factor. Therefore, results of this study are not valid for other study areas of Iran. Moreover, results of our study were consistent with findings of other researchers around the world including Roger et al. (2013) in French Guiana located in South America, and Sing (1999) in Rajasthan, In- dia. Both of the studies showed that inci- dence of disease increased with rise of tem- perature and decreased with decline of rain- fall, and relative humidity, respectively. The results of this study are also consis- tent with the previous findings of Mollalo et al. (2014), at the same study area, who ob- served significant association between vege- tation cover and CL incidence in Golestan Province. Because low vegetation covers almost accompanies by higher temperature, evaporation, lower rainfall, and relative hu- midity. Moreover, it is clear from Fig. 3 that districts with high incidence rate of ZCL were almost located at northern parts of the province with arid and semi-arid climate conditions indicating that such climate con- ditions provide favorable circumstances for ZCL transmission in this province. The main limitations of this study are re- lated to current surveillance system in Iran, which yearly loses considerable numbers of the cases. Official reports are probably un- derestimated due to many reasons such as the not reported, not diagnosed or misdiag- nosed cases. Therefore, it is possible that incidence of the disease is underestimated in this study. However, there are few published empirical evaluations of reported and under- estimated CL cases, the degree of underre- porting CL cases in Iran was found to be 2.8 to 4.6 fold (Alvar et al. 2012). Since the reg- istration system is uniform throughout the http://jad.tums.ac.ir Published Online: March 11, 2015 J Arthropod-Borne Dis, December 2015, 9(2): 148–160 MR Shirzadi et al.: Dynamic Relations … 158 Iran, these errors are evenly distributed. In addition, short period of this study (three years) may not lead to robust and reliable results. Besides, it should be noted that this study examined only climate factors on ZCL epidemics, without taking socio-economic conditions, and other elements influencing the number of new cases, such as herd im- munity or individual factors influencing the number of asymptomatic carriers into ac- count. Therefore, it is necessary to perform further studies to other environmental factors (such as construction of roads, building dams, etc.) and even culture and life style of people in the study area, which might influ- ence on disease pattern. Since the geographical and seasonal dis- tributions of ZCL is closely linked to the climate conditions, using climate factors to- gether with the other influencing factors as predictive indicators can be used to establish early warning systems (EWSs) to forecast ZCL incidence in managing the next epi- demic. Conclusion Climate factors have been greatly caused or affected on the spatial distribution of ZCL in Golestan Province, so that areas with higher temperature and evaporation, and in con- trast lower humidity, rainfall, and num- ber of rainy days were more susceptible to disease occurrence. These findings can pro- vide essential guidelines for public health policy makers to monitor and predict the disease based on the climate factors for fu- ture control measures. This means that the budget, personnel, and resources can be al- located more efficiently by concentrating on major determinants of ZCL epidemic in Golestan Province. Acknowledgments We would like to express our sincere thanks and appreciations both to the authorities of the Golestan Center for Disease Control and Prevention (CDC) for providing ZCL data, and Golestan, Semnan and Northern-Khorasan Provinces Meteorological Centers for supply- ing the climate data used in this study. 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World Health Assembly (2007) The World http://jad.tums.ac.ir Published Online: March 11, 2015 J Arthropod-Borne Dis, December 2015, 9(2): 148–160 MR Shirzadi et al.: Dynamic Relations … 160 Health Assembly Resolution (WHA 60.13) on the “Control of Leishma- niasis”. Geneva, Switzerland. Available at: http://www.who.int/neglected_ diseasesmediacentre/WHA_60.13_Eng .pdf. WHO (2012) Available at: http://gis.emro. Who. int/leishmanya/atlas.html. http://jad.tums.ac.ir Published Online: March 11, 2015