Introduction

Leishmaniasis, a vector-borne parasitic disease, presents clinical manifestations which range from self-healing primary skin infections, in the case of cutaneous leishmaniasis, to incurable Kala-Azar, in the case of visceral leishmaniasis [1]. Leishmania parasites are mainly transmitted through zoonotic or anthroponotic routes, i.e. by bites of phlebotomine sandfly species [2]. Difficulties in leishmaniasis elimination and its control are rooted in poor vector (sandfly) management, the fact that there is no vaccine available, and the lack of new effective treatments [3].

The wide diversity of Leishmania species in 98 countries around the world has been documented. The scientific literature shows that about 350 million people worldwide are at risk of leishmaniasis, and an annual incidence of 700,000 to 1 million has been reported [4,5,6,7]. Although the actual number of human cases of cutaneous and visceral leishmaniasis is unknown, both have been expanding during the last decades [8,9,10]. Leishmaniasis shows a rising prevalence with a high incidence, especially in Mediterranean countries and across Europe [11]. As an example, the population of Barcelona (Spain) experienced a growing trend of leishmaniasis from 1996 to 2019, which was statistically significant between 2016 and 2019 [12]. Some researchers suggest that this obvious increase of vector borne diseases, such as leishmaniasis, might be due to climate change [13, 14]. Human health is affected by various environmental factors, especially in places of residence, so that it should be considered that most health issues have a spatial dimension [15]. In addition, some research has shown the influence of climate change on vector populations and, consequently, on the incidence of vector borne diseases, such as malaria, chikungunya, dengue, yellow fever, and zika [16, 17].

Geographic Information Systems (GIS) consist of hardware, software, geographic data, human resources, as well as other layers that display the results in the form of maps which can be analyzed for ecological and epidemiological aims [18]. Preparing a map of the occurrence of the disease at a particular point or region based on GIS, does not only protect communities of risk factors, but also influences the strategy of healthcare management [19]. Delimiting the risk of outbreaks and identifying critical areas by epidemiologists can open up new lines for healthcare authorities to create plans to prevent the spread of a disease [20]. WHO has recommended the use of GIS as an ideal tool to predict the future evolution of a disease in various areas and to analyse the relation between geographic health problems in communities and their natural environment [19].

The aims of this research are the following:

  • to study the climatic conditions in the areas that are the centres of visceral and cutaneous leishmaniasis in Iran during the years 1999-2021;

  • to identify climatic factors that increase the risk of an area turning into a hotspot region of cutaneous and visceral leishmaniasis; and to establish the association between the main species of Leishmania (L. major, L. tropica, L. infantum) dispersion and climatic variables.

Materials and Methods

Study Site

This study was conducted at a national scale in Iran, located in west Asia, covering a land mass of 1,648,195 km2, bordering the Caspian Sea in the north as well as the Persian Gulf and the Oman Sea in the south, and having borders with Afghanistan, Armenia, Azerbaijan, Iraq, Pakistan, Turkey and Turkmenistan [21].

Data Collection

Parasitological data consisted of all molecular-based reports of leishmaniasis in Iran from 1999 to 2021, which were gathered from reliable medical sources. For the purpose of the current study, articles that report the number, type and geographical distribution of human leishmaniasis cases in Iran through molecular tests from 1999 to 2019 were collected based on a literature review previously published by our colleagues in 2021 [22]. We followed their method and added 11 new articles which were published from 2020 to 2021 to the database. To separate the reported data based on the cities located in each province, material and methods and results of all 168 articles were reviewed, and the results of 106 cities were recorded.

Meteorological Data

The data of 382 meteorological stations around the whole country from 1999 to July 2021, including air temperature, soil temperature, annual rainfall and humidity, were obtained from the Iranian Climatological Research Centre.

All the above-mentioned data were arranged in a geodatabase for further application in ArcGIS.

Mapping and Statistical Analysis

All the information available concerning the species distribution in Iran and climatic conditions during these 22 years was transported to maps through raster layers using ArcGIS 10.4.1. The maps generated were used for the proposed hypotheses concerning Leishmania spp. spatial epidemiology.

As the data were reported for certain locations only, the Inverse Distance Weighting (IDW) interpolation method was used to generate raster maps to estimate cutoff points for optimum climatic parameters, with the aim to predict the transmission risk in the regions of the country for which parasitological and climatic data were not available.

The relationship between Leishmania spp. foci and climatic models was statistically examined to determine the normal or abnormal distribution of data and quantitative data, which were then ranked to be selected for appropriate statistical analysis.

The relationship between parasitological data (dependent variable) and climatic models was examined with SPSS software version 20 using the ANOVA statistical test. A P value < 0.05 was considered statistically significant. Climatic conditions were grouped if necessary. Groups of ecological parameters in and out of the endemic area were estimated and the limits of statistical relationship with species distribution were investigated and recorded. The cut-off grouped boundaries were entered in the GIS project and the maps of high-risk areas were generated. For this purpose, changes were made in the grouping or some low-impact variables were basically omitted to obtain the optimal conditions that had the most geographical similarity with the reported conditions.

Results

New molecular-based reports of the three main human Leishmania species in Iran from 2020 to 2021 are shown in Table 1, which were used, together with the previous reports from 1999 to 2019 [22], as part of the geodatabase in the GIS.

Table 1 Molecular-based reports of the three main human Leishmania species in Iran from 2020 to 2021
Full size table

For a better definition of the climatic conditions of the different parts of Iran at district resolution, meteorological data collected by synoptic stations were processed using the IDW prediction model in ArcGIS 10.4.1 software. Figure 1 shows the climatic conditions of the districts in Iran.

Fig. 1
figure 1

Interpolation at district resolution in Iran during the 1999–2021 period of: A annual rainfall (mm/year) (areas with brown colour and green colour have the lowest and highest annual rainfall, respectively); B soil temperature (℃) (red areas have the warmest and blue areas the coldest mean soil temperature); C relative humidity (%); D mean air temperature (℃) (red areas have the warmest and blue areas the coldest mean air temperature) (colour figure online)

Full size image

The data of the three Leishmania species reported at national scale from several locations were gathered and located on the maps (Fig. 2). The interpolation of these data was done by IDW showing the pattern of L. major, L. tropica and L. infantum (Fig. 3).

Fig. 2
figure 2

Geographical distribution recorded between 1999 and 2021 in Iranian cities of: A Leishmania major in 71 cities; B Leishmania tropica in 57 cities; C Leishmania infantum in 30 cities

Full size image
Fig. 3
figure 3

Distribution, using the IDW prediction model, in Iranian cities of: A Leishmania major; B Leishmania tropica; (C) Leishmania infantum

Full size image

The climatic conditions of the high prevalence areas of the three Leishmania species were statistically analysed (Supplementary Table 1, 2 and 3; Supplementary Figs. 1, 2 and 3). The results show that some climatic parameters do not have an important impact on the parasite distribution and therefore do not contribute to the epidemiology of leishmaniasis; consequently, they were not considered in the prediction models.

In the next step, suitable climatic conditions were arranged in lower and higher groups; these cutoff conditions were tested using ANOVA in SPSS software. A correlation with a P value < 0.05 was assumed as statistical difference to omit some climatic parameters.

The distribution of L. major in Iran is significantly related to: the annual rainfall (P value = 0.004), with the optimum for its distribution being about 175 to 225 mm per year; the soil temperature (P value < 0.0001), with the optimum being about 8 to 11 ℃; the relative humidity (P value < 0.0001), with the optimum being about 37 to 40%; and the mean-minimum and maximum air temperature (P value < 0.05), with the mean optimum being about 15 to 18 ℃.

The distribution of L. tropica significantly related to: the annual rainfall (P value = 0.003), with the optimum for its distribution being about 150 to 200 mm per year; and the relative humidity (P value = 0.008), with the optimum being about 37 to 40%.

The distribution of L. infantum in Iran is significantly related to: the annual rainfall (P value < 0.0001), with the optimum for its distribution being about 250 to 350 mm per year; the soil temperature (P value < 0.0001), with the optimum being about 7 to 8 ℃; and the mean-minimum and maximum air temperature (P value < 0.05), with the optimum being about 13 to 15 ℃.

Suitable climatic conditions of ecological niches of the three main Leishmania species in Iran are:

  • 95-325 mm of annual rainfall, 5–16 ℃ of soil temperature, 31–50% of relative humidity, 15–27 ℃ of mean temperature, 21–34 ℃ of maximum temperature, and 8–19 ℃ of minimum temperature, in the case of L. major;

  • 95–210 mm of annual rainfall, and 25–47% or relative humidity, in the case of L. tropica;

  • 250–350 mm of annual rainfall, 4–8 ℃ of soil temperature, and 520 of mean temperature, in the case of L. infantum.

These critical conditions were assumed, and predictive maps were generated for each species. The maps show the transmission of leishmaniasis predicted by the climatic models for L. major, L. tropica and L. infantum (Fig. 4). Unfortunately, the L. infantum prediction map could not be developed in more detail as for the other two species due to its more reduced area of distribution and data were only recorded in 30 cities of Iran.

Fig. 4
figure 4

Transmission predicted by the climatic model of: A Leishmania major; B Leishmania tropica; C Leishmania infantum

Full size image

Discussion

Leishmaniasis is well established in Iran and almost all reports to health centres reflect the local disease scenario, with the exception of the capital city, Tehran. Cases diagnosed and reported in Tehran are not of local transmission and in prediction of the ecological niche of parasites this epidemiological item was considered a correction.

It is notable that other epidemiological parameters are stand-alone factors in the distribution of leishmaniasis, for instance, an urban area for L. tropica or the presence of dogs for the distribution of L. infantum.

Leishmania major is the species whose distribution has been most closely related to climatic factors. All ecological variables examined in the study were significantly associated with L. major distribution in Iran. Surprisingly, mapping of L. major cases according to molecular reports during 1999–2021 shows that their geographic distribution is limited, stretching from the northeast of Iran to the centre and to the southwest of the country. The main reservoir of L. major in the northeast and centre of Iran is the rhombic rat, Rhombus opimus, and the secondary reservoir in these areas is the Libyan jird, Meriones libycus, while the main reservoir in the southwest of Iran is the Indian gerbil, Tatera indica [34, 35]. As the rodent reservoir and the parasite distributions are largely coincident, it can be concluded that L. major is indirectly affected by climate factors. This conclusion is highly in agreement with its life cycle and its transmission route which is mainly dependent on the rodent population [36]. In contrast, L. tropica prevalence is only related to humidity and annual rainfall. This lack of dependence on air and soil temperatures might be an important reason for its geographical distribution, which has spread throughout the country except for a small area in the northwest. It is obvious that the complete independence of L. tropica from air and soil temperatures may lead to an easy outbreak, and therefore, the best way for its control and management seems to be the early diagnosis and treatment of patients. In the case of L. infantum, its prevalence is related to all climatic variables considered with the exception of humidity. In comparison to L. major, L. infantum prevalence tends to be more closely linked to colder and rainier geographical regions, i.e. to cold and rainy locations.

Periodical examination of dogs for visceral leishmaniasis seems to be unavoidable. Obviously, given the fatal complications of visceral leishmaniasis, if sufficient attention is not paid to the early diagnosis and treatment of dogs, the main reservoir of this zoonotic disease, in areas with a suitable climate, the consequences will be costly to both animal and human health.

Conclusions

The current results of the 1999–2021 study period confirm the association between climatic conditions and Leishmania species distribution in Iran, especially in the case of L. major and L. infantum, whilst being less significant in the case of L. tropica. Consequently, the relationship between climatic conditions and the geographical distribution of Leishmania species as well as the use of GIS as an essential tool to better understand the spatial epidemiology of leishmaniasis have been reaffirmed.