Emergence and spread of Aedes albopictus in northern Iran with risk assessment and habitat hotspot analysis in Mazandaran Province

Abstract

Diverse ecosystems, trade and travel create favorable conditions for the spread and establishment of invasive Aedes species in different geographical areas and the diseases they transmit. To maximize the effect of vector control and preventive interventions, it is crucial to detect the presence of invasive Aedes mosquitoes through entomological surveillance and map their larval habitats, hence, this study aimed to search for invasive Aedes mosquitoes as well as identify potential larval habitats and assess the risk of invasive Aedes dispersal in Mazandaran Province. This study was conducted in Mazandaran Province, characterized by diverse ecosystems favorable for mosquito breeding. “Enhanced surveillance efforts” to identify invasive Aedes mosquitoes were conducted from early 2024 through mid-August 2025. Sampling methods include ovitraping, larval collection, and Human Landing Catches (HLC), conducted biweekly across selected counties. In the summer of the same year, an exploratory field study was conducted to identify potential larval habitats of invasive Aedes mosquitoes. Environmental parameters, along with demographic data, were recorded to assess their impact on potential larval habitat abundance. Descriptive statistics, chi-square, cluster analysis (K-means algorithm), Getis-Ord Gi, Geographically Weighted Regression (GWR), and Generalized Estimating Equations (GEE) were applied using SPSS version 25 and ArcGIS version 10.5 for data analysis. Aedes albopictus was first identified at a Hotel in Ramsar County in western Mazandaran on July 8, 2024. Subsequent detections were made at 26 sites in Ramsar and 23 sites in Tonekabon, among others. A total of 80 potential larval habitat types were identified, with disposable plastic containers being the most abundant (2271, 28.2% of total). The highest abundance of potential habitats was noted in Chalus, followed by Babolsar and Amol. Risk assessment categorized counties into three clusters based on the environmental conditions, habitat diversity and risk levels. Nur County exhibited low risk, while Amol, Babolsar, Fereydunkenar and Mahmoodabad were classified as moderate risk. Chalus, Ramsar, Tonekabon, Abbasabad, and Nowshahr counties showed a high risk profile. Spatial clustering analysis using the Getis-Ord Gi* statistic identified three out of ten cities as significant hotspots for potential Ae. albopictus larval habitats, with Z-scores ranging from 0.086 to 0.220 (p < 0.05). Apart from reporting the first record of Aedes albopictus in Mazandaran, Iran, this study provides critical insights into the spatial distribution of invasive Aedes habitats, highlighting areas of high risk and informing targeted vector control interventions. The findings contribute to public health strategies aimed at mitigating the spread of mosquito-borne diseases in northern Iran as well as contingency measures for vector control in the case of epidemics.

Introduction

Dengue, chikungunya, and Zika are rapidly expanding arboviral diseases of major global public health concern. These diseases are transmitted mainly by Aedes aegypti and Aedes albopictus. Although Ae. aegypti is considered the more efficient vector, Ae. albopictus plays a major role in transmission in areas where Ae. aegypti is absent or occurs at low densities¹. Both species commonly breed in small natural and, more importantly, artificial water-holding containers in domestic and peri-domestic environments, such as plastic tanks, flower pots, water storage jars, and discarded containers². The International trade of goods, particularly used tires containing desiccation-resistant eggs, has facilitated the global spread of these invasive mosquitoes. Over recent decades, Ae. aegypti and Ae. albopictus have rapidly spread in the Eastern Mediterranean region and Southwestern Asia³.

In Iran, Ae. albopictus was first observed in Chabahar, Sistan and Baluchestan Province⁴ in very low population but a widespread massive entomological surveillance failed to reproduce the findings in later years. Aedes aegypti was first found in Bandar Lengeh, Hormozgan Province, southern Iran^5,6. Aedes albopictus was detected in Gilan Province in North of Iran⁷ that swept many northern and northwestern provinces of the country. Considering the presence of these invasive Aedes species in Iran, coupled with reported cases of dengue fever⁸, concerns have raised regarding the establishment of these vectors the potential for local transmission of arboviral diseases in the country. Some health experts in Iran project that a dengue epidemic surge may impact the country in the upcoming years⁹.

Climate variability, environmental change, and human activities play a central role in shaping the distribution, establishment, and population dynamics of Aedes mosquitoes by influencing the availability and persistence of suitable larval habitats¹⁰. Both climatic factors and anthropogenic conditions—such as urbanization patterns and water-holding artificial containers—determine where these vectors can successfully breed and spread. Insufficient attention to mosquito biogeography, combined with an overreliance on insecticides and limited understanding of vector ecology and susceptibility, has contributed to the limited effectiveness of many urban mosquito control programs¹¹. In this context, identifying and mapping the spatial distribution of potential larval habitats is a key component of evidence-based vector management¹¹. Such information supports targeted surveillance, improves the efficiency of larval source management, and strengthens preparedness for arboviral disease transmission, particularly in areas with high human mobility and points of entry that may facilitate the introduction and spread of invasive Aedes species.

Geographic Information Systems (GIS) have been recognized as a powerful tool for analyzing the relevant information in health sciences and disease epidemiology¹². Utilizing this robust tool allows for the study of the spatial and temporal distribution of vectors, vector-borne diseases, and their breeding habitats, enabling the design of effective prevention and control strategies through the creation of thematic maps and determining associated risks¹². In recent years, GIS has been applied in medical entomology in Iran, particularly in relation to vector-borne diseases^3,13–15.

Mazandaran Province in northern Iran presents climatic and ecological conditions favorable for the development and diversity of mosquito vectors^16,17. The province is characterized by a humid subtropical climate, moderate temperatures, high rainfall, and diverse landscapes ranging from coastal plains along the Caspian Sea to forested mountainous areas. These environments, combined with dense human settlements, provide numerous natural and artificial larval habitats consistent with the ecological preferences of Ae. albopictus¹⁸. In addition, Mazandaran is a major tourist destination with substantial seasonal human movement. The presence of active seaports connected to international trade routes, along with an international airport, further increases the risk of introduction of invasive mosquitoes, particularly given the documented presence of Aedes species in connected regions^19,20.

Considering these local ecological and anthropogenic features, the present study was designed to conduct enhanced entomological surveillance aimed at detecting invasive Aedes mosquitoes in Mazandaran Province, northern Iran, and to identify their potential larval habitats. In addition, spatial and environmental analyses were performed to assess the risk of invasion and to determine habitat hotspot zones using Geographic Information Systems (GIS) and spatial modeling techniques. The findings of this study are expected to provide baseline data for improving integrated vector control strategies, guiding surveillance efforts, and supporting public health preparedness against possible outbreaks of arboviral diseases transmitted by invasive Aedes mosquitoes in northern Iran.

Materials and methods

Study area

The study was conducted in Mazandaran Province, northern Iran including counties of Ramsar, Tonekabon, Abbasabad, Chalous, Nowshahr, Nour, Amol, Mahmoodabad, Fereydunkenar, and Babolsar. The province has moderate and subtropical climate with average summer temperature of 25 °C and winter of about 8 °C, with a population of 3,283,582 and an area of 23,842 km². The latitude and longitude of the province are 36.5656^◦ N and 53.0588^◦ E. It is bounded by Gilan Province in the West, Golestan Provinces in the East, Tehran and Semnan Provinces in the South and the Caspian Sea in the North. It has common trade borders with Russia in the North, the Republic of Azerbaijan in the West, and Turkmenistan and Kazakhstan in the East of the Caspian Sea. The west of the province features diverse ecosystems, including beaches, forests and wetlands, creating favorable conditions for the breeding of Aedes mosquitoes. These areas are popular tourist destinations, frequently hosting both domestic and international visitors, which can significantly impact mosquito population dynamics and the spread of mosquito-borne diseases.

Sampling efforts to detect invasive Aedes mosquitoes

Sampling efforts to detect invasive Aedes mosquitoes were planned and performed biweekly throughout 2024 in Mazandaran Province, northern Iran, as part of " Intensified surveillance efforts” following previous studies¹⁴. These efforts have also continued into 2025. In each city, points of entry (port and airport) and transportation routes were monitored according to Iran CDC surveillance guideline for invasive Aedes vectors²¹. Three main sampling methods were employed: (1) Ovitraps: these black plastic buckets of about 1.5 L containing 10% hay infusion water and a coarse paper as a substrate for egg laying were bimonthly placed (once in the first half of the month and once in the second half of the month) both indoors and outdoors at heights of less than 1.5 m at selected points (totally 100 ovitraps), visited 72 h later. The suspected papers were collected and transferred to the laboratory for counting the eggs and species identification after keeping for 2–3 days at room temperature before hatching to the 4th instar larvae. (2) Larval Collection: a comprehensive range of natural and artificial breeding habitats were surveyed for the presence of Aedes larvae. Larvae were collected using dippers and pipettes and preserved for further analysis. Sampling efforts were always conducted by the same individual in the morning (0800–1200 h) or afternoon (1400–1800 h) for about 30 min at each larval habitat. (3) Human Landing Catch (HLC): Adult Aedes mosquitoes were collected using the Human Landing Catch (HLC) method, where trained personnel exposed their lower limbs to attract host-seeking female mosquitoes, which were then captured using mouth aspirators or sweep nets²². Care was taken to collect probing mosquitoes before biting to prevent risk to the human baits. The study protocol was approved by the Ethical Committee of Mazandaran University of Medical Sciences (Ethics code: IR.MAZUMS.REC.1403.385) and was performed according to the Iran CDC surveillance guideline for invasive Aedes vectors²¹. All participants involved in HLC provided informed consent prior to participation. In addition, appropriate personal protective measures were implemented, including the use of protective clothing and net jackets on areas where landing was not taking place, and close supervision to minimize the risk of mosquito bites and potential pathogen exposure All collected specimens were morphologically identified to species level using standard taxonomic keys²³. Environmental parameters, including temperature, humidity, precipitation and wind speed, were recorded by portable digital thermo-hygrometers and Meteorological department of Mazandaran Province during each sampling event to assess their influence on the abundance and distribution of invasive Aedes mosquitoes.

Searching efforts to identify potential larval habitats

In the summer of 2024, an exploratory field study was conducted to identify potential larval habitats of invasive Aedes mosquitoes in the above-mentioned counties of Mazandaran Province, northern Iran. This section of study aimed to uncover breeding sites that may facilitate the proliferation of these vectors (Fig. 1). In each selected county, three blocks were chosen for monitoring based on the following inclusion criteria: (1) high movement of passengers and goods between the province of Gilan and the southern provinces where the presence of invasive Aedes species has been documented, (2) designation as tourist areas, (3) higher population density, and (4) prioritization for the control and prevention program of invasive Aedes species. This strategic selection aimed to maximize the likelihood of finding potential larval habitats associated with human activities. To undertake the study, three teams of two trained personnel were formed. Each team underwent specialized training to ensure they were equipped with the necessary skills for effective potential larval habitat identification and sampling. Additionally, information regarding the characteristics of potential larval habitats, along with demographic and climatic data were systematically recorded in the relevant forms for each county. This data was crucial for understanding the ecological conditions that favor Aedes mosquito breeding.

Fig. 1.

Potential habitat diversity of invasive Aedes mosquitoes in Mazandaran Province. The asterisk “*” indicates the most abundant habitats. The original photograph was taken by the first author.

Data analyses

Statistical software SPSS version 25 and ArcMap version 10.8 were used to perform all the analyses. Descriptive statistics were used to summarize the frequency and distribution of larval habitats across sampling sites. Differences in habitat types among counties were tested using the chi-square test. Clustering analysis (K-means) was performed to classify counties into low-, moderate-, and high-risk groups based on environmental variables, habitat diversity, and population density. To analyze the spatial distribution of potential larval habitats, geographic coordinates of sampling locations were extracted using GPS software. These coordinates were then imported into Excel in KML format, converted into shape files, and subsequently transferred to ArcMap GIS version 10.5 for further analysis.

To investigate the relationship between environmental variables influencing the spatial distribution of potential habitats, such as temperature, relative humidity and precipitation, Geographic Weighted Regression (GWR) was employed using ArcGIS version 10.5, as it accounts for spatial non-stationarity—allowing the strength and direction of relationships to vary across geographic locations rather than assuming uniform effects throughout the study area. This approach provided a more detailed understanding of how climatic and ecological variables influence the local abundance and spatial distribution of invasive Aedes mosquitoes. In this analysis, the spatial distribution of potential habitats was treated as the dependent variable, while annual average temperature, relative humidity and precipitation served as independent variables²⁴. Furthermore, due to the spatial correlation among the variables, the Generalized Estimating Equations (GEE) method with linear link function was applied using SPSS version 25, with a significance level set at 0.05.

Hot spot analysis

Additionally, the study utilized clustering methods based on Getis-Ord Gi* statistics to identify major hot spots and areas conducive to the establishment of Aedes aegypti and Aedes albopictus. This statistical tool identifies significant spatial clusters with high (hot spots) and low (cold spots) values. The Getis-Ord Gi statistic provides a Z-score, where a higher Z-score indicates a stronger hot spot clustering, while a lower Z-score suggests a more pronounced cold spot clustering^25,26.

Results

First record of Ae. albopictus in Mazandaran Province

Aedes albopictus was first identified in the yard of a Hotel in Ramsar County on June 27, 2024, with a total of 7 specimens (both larvae and adults) during the invasive Aedes mosquito surveillance program. The species was collected using larval collection and landing catch methods, specifically in a preferred habitat of tree trunk hole. Detailed morphological characteristics of both adult and larval specimens were recorded to confirm the identification of the species. Adult specimens exhibited characteristics including a scutum with a narrow median longitudinal white stripe extending from the anterior margin to the prescutellar area; posterior dorsocentral white stripes that are narrow and short, not reaching the middle of the scutum; scales on the wing veins that are all dark except for a small spot of white scales at the base of the costa (C); the anterior portion of the midfemur without a longitudinal white stripe; a clypeus without white scale-patches; palps with white scales on the apical half; a mesepimeron with connected white scale-patches forming a V-shaped white patch; and abdominal terga with complete basal white bands (Fig. 2).

Fig. 2.

Morphological characteristic used to distinguish between adult female of Aedes albopictus and other Aedes spp. caught in Mazandaran Province, northern Iran, 2025. (A) General view- scutum, (B) wing, (C) mid femur, (D) palp and clypeus, (E) mesepimeron, (F) abdomen. The original photograph was taken by the first author.

Larval specimens also had features including a single antennal seta (1-A); a siphonal tuft (1-S) with 2–4 branches, inserted slightly beyond the middle of the siphon, distal to the pecten; comb scales without subapical spines; a saddle seta (1-X) usually with 2 branches, at least one of them distinctly longer than the saddle; seta 4-X with 4 pairs of setae, each single; and basal tubercle(s) of setae 9-12-M, T with only small denticles (Fig. 3).

Fig. 3.

Morphological characteristic used to distinguish between larvae of Aedes albopictus and other Aedes spp. caught in Mazandaran Province, northern Iran, 2025. (A-1) Head and antenna, (A-2) Seta 1-A, (B) Seta 1-S, 1-X and 4-X, (C) Pecten teeth, (D) Comb scale, (E) Annal papillae, (F-1,2) Basal tubercules and seta of 9–12-M, thorax. The original photograph was taken by the first author.

Following this initial detection, Aedes albopictus was subsequently found at 26 sites in Ramsar, 23 sites in Tonekabon, 10 sites in Abbasabad, 9 sites in Chalus, 14 sites in Nowshahr, 12 sites in Nur, and 5 sites in Mahmoudabad counties. Notably, all samples, with the exception of those from Abbasabad County, were obtained from outdoor places (Table 1). In continued intensified surveillance until mid-2025, most parameters remained consistent with those recorded in 2024, with a few exceptions. Specifically, in Abbasabad, samples were collected from both indoor and outdoor locations, unlike in other counties. Ovitraps were positive across all surveyed sites. Additionally, Aedes albopictus was detected in both Babolsar and Fereydunkenar counties during this period (Table 1). Figure 4 shows spatial distribution of Ae. albopictus during the “intensified surveillance” program in Mazandaran Province.

Table 1.

Positive foci, collection sites, types of centers, and trapping methods in selected counties of Mazandaran Province during intensified surveillance from 2024 to mid-2025.

Year	City	Positive foci	Coordinates		Place of collection		Type of center		Collection methods
			Latitude	Longitude	Outdoor	Indoor	Urban	Rural	Ovitrap	Larvae collection	Human Landing Catch
2024	Ramsar	1	36.538120	50.425050	+		+			+	+
		2	36.567770	50.382190	+		+				+
		3	36.528850	50.447310	+		+				+
		4	36.574990	50.360500	+			+			+
		5	36.527340	50.454850	+			+			+
		6	36.551760	50.383730	+		+				+
		7	36.570400	50.369050	+			+			+
		8	36.568410	50.370860	+			+			+
		9	36.541120	50.412310	+		+				+
		10	36.545750	50.394940	+		+				+
		11	36.548270	50.401710	+		+				+
		12	36.530712	50.420787	+		+			+	+
		13	36.885146	50.738662	+		+			+	+
		14	36.541120	50.413310	+			+		+	+
		15	36.574961	50.360526	+		+			+	+
		16	36.555360	50.3915930	+			+			+
		17	36.566100	50.399290	+		+				+
		18	36.537120	50.4227870	+		+				+
		19	36.537120	50.427870	+		+				+
		20	36.371120	50.4227870	+		+				+
		21	36.066600	50.434041	+		+			+	+
		22	36.066600	50.434045	+		+			+	+
		23	36.334000	50.419670	+		+				+
		24	36.545180	50.395990	+		+				+
		25	36.552200	50.401790	+		+				+
		26	36.558900	50.536260	+			+			+
	Tonekabon	1	36.867833	50.779389	+			+			+
		2	36.863156	50.784299	+			+			+
		3	36.852718	50.807704	+		+				+
		4	36.76633	50.98719	+			+			+
		5	36.782832	50.945911	+			+			+
		6	36.736038	51.056321	+			+			+
		7	36.771611	50.801484	+			+			+
		8	36.857921	50.784858	+			+			+
		9	36.852846	50.803736	+		+				+
		10	36.740915	51.034889	+		+				+
		11	36.746062	51.043582	+		+				+
		12	36.717687	50.995625	+			+			+
		13	36.816876	50.886069	+		+				+
		14	36.806023	50.879393	+		+				+
		15	36.78983	50.923571	+			+			+
		16	36.807674	50.880203	+		+				+
		17	36.815149	50.838687	+			+			+
		18	36.803756	50.875555	+		+				+
		19	36.822747	50.875086	+		+				+
		20	36.846149	50.799534	+			+			+
		21	36.85323	50.803505	+		+				+
		22	36.754881	51.013199	+		+				+
		23	36.817883	50.874121	+		+				+
	Abasabad	1	36.729855	51.103459		+	+			+	+
		2	36.729775	51.101006		+	+				+
		3	36.729855	51.103459		+	+				+
		4	36.7372379	51.0743622		+	+				+
		5	36.714163	51.173145		+		+			+
		6	36.7292908	51.1043295		+	+				+
		7	36.69909	51.267362		+	+				+
		8	36.7043227	51.2330102		+	+				+
		9	36.733653	51.084072		+	+				+
		10	36.6949872	51.1979480		+	+				+
	Chalus	1	36.66438	51.3112451	+		+				+
		2	36.6405833	51.3631667	+			+			+
		3	36.6155278	51.3893611	+			+			+
		4	36.651412	51.450341	+		+				+
		5	36.6851223	51.3456572	+			+			+
		6	36.688491	51.322844	+			+			+
		7	36.648128	51.4109421		+		+			+
		8	36.646889	51.426444	+		+				+
		9	36.6468626	51.4260953	+		+				+
	Nowshahr	1	36.565237	51.83047	+			+			+
		2	36.642733	51.540047	+		+				+
		3	36.652552	51.453883	+			+			+
		4	36.656139	51.484468	+		+				+
		5	36.653243	51.457471	+		+				+
		6	36.657130	51.487996	+		+				+
		7	36.659055	51.473558	+		+				+
		8	36.6562047	51.4883779	+		+				+
		9	36.559661	51.8607580	+			+			+
		10	36.647099	51.495387	+		+				+
		11	36.658255	51.480184	+		+				+
		12	36.626603	51.502446	+			+			+
		13	36.652243	51.498052	+		+				+
		14	36.654998	51.495955	+		+				+
	Nur	1	36.573333	51.988333	+		+				+
		2	36.573333	51.988333	+		+				+
		3	36.573333	51.988333	+		+				+
		4	36.5586	52.60766	+		+				+
		5	36.573333	51.988333	+		+				+
		6	36.573333	51.988333	+		+				+
		7	36.573333	51.988333	+		+				+
		8	36.573333	51.988333	+		+				+
		9	36.573333	51.988333	+		+				+
		10	36.573333	51.988333	+		+				+
		11	36.573333	51.988333	+		+	+			+
		12	36.573333	51.988333	+		+				+
	Mahmudabad	1	36.37973032	52.15241	+		+				+
		2	36.37978032	52.15282	+		+				+
		3	36.37973034	52.15241	+		+				+
		4	36.36848031	52.1144	+			+			+
		5	36.38530032	52.17377	+		+				+
Mid-2025	All cities in 2024	*	*		*, in addition, Abbasabad City, includes both indoor and outdoor		*		*, in addition, ovitraps were also positive at all sites
	Babolsar	1	36.419090	52.355650	+		+		+
		2	36.421530	52.358900	+		+				+
		3	36.417170	52.357250	+		+				+
		4	36.427170	52.357250	+		+		+
	Fereydunkenar	1	36.694900	52.555800	+		+		+		+

*All items are consistent with 2024.

Fig. 4.

Spatial distribution of Ae. albopictus during the intensified surveillance program in Mazandaran Province, northern Iran from 2024 to mid-2025. The map was generated by the first author using ArcGIS version 10.5 (https://www.esri.com/en-us/arcgis/products/arcgis-desktop/overview).

Identification of potential larval habitat

During the monitoring of potential larval habitats, a total of 80 habitat types with 607 occurrence times were identified across 10 counties in Mazandaran Province, with the spatial distribution of these occurrences illustrated in Fig. 5. Among these, statistical comparison revealed that 33 habitat types exhibited significant differences in their distribution among the surveyed counties (p < 0.05) (Table 2). For a clearer interpretation, the identified habitats were grouped by frequency: high (> 5%), moderate (1–5%), and low (< 1%). The most common habitat types observed were disposable plastic containers, with an abundance of 2271 (28.2% of the total), predominantly found in Chalus (754 /2271, 33.20%; χ²= 1360.55, p < 0.001). Following this, plastic caps (2166, 26.9% of the total) and plastic bags (518, 6.44% of the total) were also the most abundant in Chalus (754 out of 2,166, 34.81%; χ²=929.36 and 123 out of 518, 23.74%; χ²=306.98, p < 0.001, respectively). Habitat types such as animal troughs, air conditioner bases, and concrete power poles exhibited the lowest frequencies across all counties.

Fig. 5.

Map showing the distribution of the number of occurrences of potential larval habitats in selected counties of Mazandaran Province, northern Iran. The map was generated by the first author using ArcGIS version 10.5 (https://www.esri.com/en-us/arcgis/products/arcgis-desktop/overview).

Table 2.

Potential larval habitats identified in the selected counties of Mazandaran Province, 2024.

Type of habitat*	Counties
	Occurrence	Amol	Babolsar	Chalos	Ramsar	Tonekabon	Abasabad	Fereydunkenar	Mahmudabad	Nur	Nowshahr	Total	χ²	P
		N(%)	N(%)	N(%)	N(%)	N(%)	N(%)	N(%)	N(%)	N(%)	N(%)	N(%)
Frequency group: high > %5
10	39	241(24.35)	351(32.2)	566(29.15)	129(20.87)	122(22.1)	135(29.41)	49(9.37)	213(39.4)	237(31.9)	123(20.9)	2166(26. 9)	929.36	p < 0.001
35	30	70(7.1)	117(10.75)	123(6.34)	3(0.49)	49(8.86)	6(1.3)	28(5.35)	31(5.74)	64(8.61)	27(4.58)	518(6.44)	306.98	p < 0.001
38	34	348(35.15)	212(19.5)	754(38.8)	51(8.25)	154(27.85)	135(29.41)	126(24.1)		266(35.8)	225(38.2)	2271(28.2)	1360.55	p < 0.001
Frequency group: moderate, %1–5
8	28	7(0.7)	14(1.29)	44(2.27)	17(2.75)	12(2.17)	7(1.53)	15(2.87)	8(1.48)	4(0.54)	13(2.21)	141(1.75)	81.48	p < 0.001
9	17	33(3.33)		18(0.93)	119 (19.25)	8(1.45)	5(1.09)	6(1.15)	95(17.6)		20(3.4)	304(3.78)	357.15	p < 0.001
13	28	68(6.9)	9(0.82)	71(3.66)	44(7.12)	9(1.63)	14(3.05)	26(4.97)	46(8.52)	14(1.88)	21(3.57)	322(4)	155.88	p < 0.001
15	12	88(8.9)	6(0.55)	13(0.67)	21(3.4)		5(1.09)	6(1.15)	6(1.11)			145(1.8)	264.71	p < 0.001
18	25	9(0.91)	10 (0.92)	21(1.08)	21(3.4)	11(1.99)	6(1.3)	19(3.63)	11(2.04)	6(0.81)	4(0.68)	118(1.47)	30.64	p < 0.001
19	12		33(3.03)	18(0.93)	22(3.56)	12(2.17)	6(1.3)	5(0.96)		5(0.67)		101(1.26)	46.41	p < 0.001
27	16		24 (2.2)	24(1.24)	13(2.1)	6(1.08)	6(1.3)	18(3.44)		2(0.27)	6(1.02)	99(1.23)	42.98	p < 0.001
28	19	8(0.8)		16(0.83)	16(2.59)		18(3.92)	7(1.34)	4(0.74)	7(0.94)	14(2.38)	90(1.12)	17.55	0.01
29	28	27(2.72)	32(2.94)	53(2.73)	19(3.07)	14(2.53)	24(5.23)	7(1.34)	12(2.22)	67(9.02)	9(1.53)	264(3.28)	132.13	p < 0.001
36	11		41(3.77)	7(0.36)	10(1.62)	10(1.81)		16(3.06)				84(1.04)	46.11	p < 0.001
43	16	7(0.7)	29(2.66)	44(2.27)			8(1.74)	6(1.15)	10(1.85)	12(1.62)	10(1.7)	126(1.57)	81.61	p < 0.001
Frequency group: low, < %1
1	1										2(034)	2 (0.02)	-	-
2	1					4(0.72)						4(0.05)	-	-
3	12	5(0.5)		1(0.05)	6(0.97)	6(1.08)		6(1.15)	10(1.85)	9(1.21)	6(1.02)	49(0.61)	8.3	0.3
4	5			4(0.2)		4(0.72)		2(0.38)		4(0.54)		14(0.17)	0.85	0.83
5	4			1(0.05)	5(0.81)					6(0.81)	4(0.68)	16(0.2)	3.5	0.3
6	15	1(0.1)	19(1.75)	6(0.31)	5(0.81)	14(2.53)	6(1.3)		3(0.56)	3(0.4)		57(0.71)	37.45	p < 0.001
11	2				3(0.49)			4(0.76)				7(0.09)	0.143	0.7
12	4		10(0.92)		3(0.49)	3(0.54)		8(1.53)				24(0.3)	6.33	0.09
14	5			1(0.05)	3(0.49)	3(0.54)			4(0.74)		2(0.34)	13(0.16)	2	0.73
17	4		5(0.46)		10(1.62)			2(0.38)				17(0.21)	5.76	0.05
20	2	3(0.3)						5(0.96)				8(0.1)	0.5	0.48
21	9	12(1.22)		4(0.21)	3(0.49)	2(0.36)		9(1.72)	4(0.74)			34(0.42)	13.64	0.01
22	7	11(1.11)		6(0.31)	28(4.53)			25(4.78)				70(0.87)	19.48	p < 0.001
23	1				5(0.81)							5(0.06)	-	-
24	6			8(0.41)	5(0.81)	7(1.27)						20(0.25)	0.7	0.7
25	8			8(0.41)	5(0.81)	9(1.63)	2(0.44)	4(0.76)		1(0.13)	3(0.51)	32(0.4)	11.75	0.06
26	3			6(0.31)	4(0.65)							10(0.12)	0.4	0.52
30	8			9(0.47)	9(1.45)		39(8.5)	9(1.72)			2(0.34)	68(0.85)	132.13	p < 0.001
31	9	4(0.4)				5(0.9)		9(1.72)	8(1.48)		3(0.51)	29(0.36)	4.62	0.32
32	3		21(1.93)			2(0.36)						23(0.29)	15.69	0.23
33	13	3(0.3)	5(0.46)	19(0.98)	16(2.59)	16(2.89)					7(1.19)	66(0.82)	20.90	0.001
34	10		4(0.37)	31(1.6)		24(4.34)	4(0.87)	8(1.53)	4(0.74)	3(0.4)		78(0.97)	70.79	p < 0.001
37	7	3(0.3)			1(0.16)	2(0.36)	6(1.3)	8(1.53)		2(0.27)		22(0.27)	10.18	0.07
39	7		1(0.09)	3(0.15)			2(0.44)			1(0.13)	22(3.74)	29(0.36)	57.03	p < 0.001
40	2					3(0.54)		4(0.76)				7(0.09)	0.14	0.70
41	8			2(0.1)	9(1.45)	11(1.99)			4(0.74)	1(0.13)	5(0.85)	32(0.4)	14.5	0.01
42	6		4(0.36)	9(0.46)	5(0.81)	4(0.72)		6(1.15)				28(0.35)	3.07	0.54
44	2			1(0.05)					2(0.37)			3(0.04)	0.33	0.56
45	8		9(0.83)	7(0.36)			2(0.44)			1(0.13)	4(0.68)	23(0.29)	9.82	0.04
46	1	5(0.5)										5(0.06)	-	-
47	6			6(0.31)	3(0.49)	3(0.54)		3(0.57)			1(0.17)	16(0.2)	4	0.4
48	10	3(0.3)	27(2.48)	13(0.67)	4(0.64)			5(0.96)		7(0.94)	2(0.34)	61(0.76)	53.86	p < 0.001
49	10	10(1)		15(0.77)		3(0.54)			6(1.11)	4(0.54)	9(1.53)	47(0.58)	12.61	0.02
50	3					6(1.08)	2(0.44)	3(0.57)				11(0.14)	2.36	0.3
51	3					2(0.36)				1(0.13)	4(0.6)	7(0.09)	2	0.36
52	8		2(0.18)			9(1.63)		15(2.87)		1(0.13)		27(0.34)	19.07	p < 0.001
53	1					2(0.36)						2(0.02)	-	-
54	12	4(0.4)	1(0.09)	2(0.1)		2(0.36)	7(1.53)			6(0.81)	2(0.34)	24(0.3)	9.25	0.16
55	1						2(0.44)					2(0.02)	-	-
56	10	1(0.1)		6(0.31)			10(2.18)	3(0.57)	3(0.56)		5(0.85)	28(0.35)	10.57	0.06
57	5			1(0.05)			2(0.44)	4(0.76)			8(1.3)	15(0.19)	7.66	0.05
58	2		39(3.58)								7(1.19)	46(0.57)	22.26	p < 0.001
59	1										3(0.51)	3(0.04)	-	-
60	1										3(0.51)	3(0.04)	-	-
61	1										5(0.85)	5(0.6)	-	-
62	2							4(0.76)			3(0.51)	7(0.09)	0.14	0.7
64	2							4(0.76)			4(0.68)	8(0.1)	-	-
65	8	10(1)	29(2.66)					6(1.15)		4(0.54)		49(0.61)	32.06	p < 0.001
66	1									2(0.27)		2(0.02)	-	-
67	3							3(0.57)	4(0.74)	2(0.27)		9(0.11)	0.66	0.71
68	8	3(0.3)	1(0.09)					9(1.72)	5(0.93)	1(0.13)		19(0.24)	11.78	0.01
69	2							3(0.57)	3(0.56)			6(0.07)	-	-
70	5		9(0.83)					18(3.44)	43(7.96)			70(0.87)	26	p < 0.001
72	1	4(0.4)										4(0.05)	-	-
73	2	2(0.2)										2(0.02)	-	-
75	1		6(0.55)									6(0.07)	-	-
76	1		5(0.46)									5(0.06)	-	-
77	1		3(0.28)									3(0.04)	-	-
78	1		6(0.55)									6(0.07)	-	-
79	1		2(0.18)									2(0.02)	-	-
80	1		2(0.18)									2(0.02)	-	-
Others**	5		1(0.09)	1(0.05)	1(0.16)				1(0.19)		1(0.17)	5(0.06)	-	-
Total	607	990(100)	1089(100)	1942(100)	618(100)	553(100)	459(100)	523(100)	540(100)	743(100)	589(100)	8046

The asterisk (*) indicates potential larval habitats in the western province, including: (1) Under Cooler, (2) Animal Drinking Trough / Bird Feeder, (3) Black Rubber Builders Bucket, (4) Boat, (5) Water Barrel, (6) Concrete Water Basin, (7) Sewage Well, (8) Concrete Drainage Channel, (9) Water Fountains, (10) plastic caps, 11. Hole in Block Wall, 12. Clay Pots, 13. Dirt Hole, 14. Plastic pot, 15. Tree Trunk Hole, 16. Wooden Cart, 17. Concrete Pipe, 18. Discarded Tire, 19. Pit on Paved Street, 20. Concrete Block, 21. Metal Trash Can, 22. Disposable Spoon, 23. Watermelon Rind, 24. Groove/Hole in Stone, 25. Riverbank Edge, 26. Concrete pot, 27. Water Accumulated by Street Curb, 28. Canned Food Container, 29. Glass Containers, 30. Groove on Concrete, 31. Construction Debris, 32. Snail Shell, 33. Concrete/Cement Pit, 34. Leaf, 35. Plastic Bag, 36. Metal Pipe Under Asphalt, 37. Clay Pot, 38. Disposable Plastic Container, 39. Worn-out Banner, 40. Plastic Sewer Cover, 41. Scrap Metal, 42. Plant saucer, 43. Eggshell, 44. Tarpaulin Cover, 45. Walnut Shell, 46. Oak Tree Bark, 47. Concrete Hole, 48. Pit on Asphalt, 49. Earthen Ditch, 50. Light Bulb, 51. Water Well, 52. Dripping Water from Cooler, 53. Water on Steps, 54. Water pit next to human drinking trough, 55. Car wheel track, 56. Plastic Pipe, 57. Zinc Watering Can, 58. Pit under irrigation tap, 59. Wheelbarrow, 60. Uonolit, 61. Plastic Water Tank, 62. Metal door, 63. Concrete power Poles, 64. Plastic Water Pool, 65. Metal Cap, 66. Metal Water Tank, 67. Children’s Playground Flooring, 68. Metal Pipe, 69. Wooden Container, 70. Plastic bucket ,71 .Animal Troughs ,72 .Marsh ,73 .Vehicle Flooring ,74 .Cooler Stand ,75 .Drainpipe ,76 .Hole on Speed Bump ,77 .Sewage Channel with Metal Lid ,78 .Metal Bottle ,79 .Garbage Dump ,80 .Go-Kart Track.

**Rare habitat (7,16,63,71,74).

The highest overall number of habitats among the selected counties was observed in Chalus (1942), Babolsar (1089), and Amol (990). In Chalus and Amol, disposable plastic containers were the dominant habitat types, while in Babolsar, plastic caps showed the highest frequency (Table 2).

Risk assessment

The risk assessment of potential larval habitats across the selected counties of Mazandaran Province, using K-means clustering based on environmental variables (Table 3), identified three distinct clusters of counties, indicating different levels of risk.

Table 3.

The identified risk clusters along with their characteristics in the selected counties of Mazandaran Province, 2024.

Cluster	Counties (occurrence)	Type of habitats (occurrence)	Number		Temperature		Rainfall		Humidity		Wind speed		population		Station
			Mean	Std. Deviation	Mean	Std. Deviation	Mean	Std. Deviation	Mean	Std. Deviation	Mean	Std. Deviation	Mean	Std. Deviation	Mean	Std. Deviation
1*	Nur (62)	3(3),4(1),5(1),6(2),8(2),10(6),13(3),18(1),19(1), 25(1), 27(1), 28(2), 29(4), 34(1), 35(6), 37(1),38(6), 39(1), 41(1), 43(3),45(1), 48(1), 49(1), 51(1), 52(1), 54(5), 65(2),66(1), 67(1), 68(1)	12.02	20.65	12.10	0.00	205.5	0.000	52	0.00	23	0.00	121.53	0.000	3.87	1.79
2**	Amol (55), Babolsar (58), Fereydunkenar(64), Mahmudabad (34)	3(4),4(1),6(4),8(10),9(5),10(10),11(1),12(2),13(10),14(1),15(6),17(2),18(9),19(3),20(2), 21(5), 22(4), 25(1), 27(4),28(5), 29(10), 30(2), 31(6), 32(2), 33(2), 34(3), 35(12), 36(4), 37(3),38(10), 39(1), 40(1), 41(1), 42(2), 43(6), 44(1), 45(2), 46(1), 47(1),48(4), 49(2), 50(1), 52(3), 54(2),56(3), 57(1), 58(1), 62(1), 64(1),65(6), 67(2), 68(7), 69(2), 70(5),71(1), 72(1), 73(2), 74(1), 75(1),76(1), 77(1), 78(1), 79(1), 80(1)	13.71	25.21	18.41	0.97	998.06	127.34	73.53	2.43	20.32	0.73	175.91	137.359	2.15	1.02
3***	Chalus (98), Ramsar (57), Tonekabon(79) Abasabad (46), Nowshahr (54)	1(1),2(1),3(5),4(3),5(3),6(9),7(1),8(16),9(12), 10(21),11(1),12(2),13(15),14(4),15(6),16(1),17(2), 18(15),19(8), 21(4), 22(3),23(1), 24(6), 25(6), 26(3), 27(11), 28(12),29(14), 30(6), 31(3), 32(1), 33(11), 34(6),35(12), 36(7), 37(3), 38(17), 39(5), 40(1),41(6), 42(4), 43(7), 44(1), 45(5), 47(5),48(5), 49(7), 50(2), 51(2), 52(4), 53(1), 54(5),55(1), 56(7), 57(4), 58(1), 60(1),61(1), 62(1), 63(1), 64(1)	10.49	19.234	17.78	0.78	1596.24	92.58	76.48	0.72	24.23	0.72	115.87	39.31	2.89	1.57

*3. Plastic Bucket, 4. Boat, 5. Water Barrel, 6. Concrete Water Basin, 8. Concrete Drainage Channel, 10. plastic caps, 13. Dirt Hole, 18. Discarded Tire, 19. Pit on Paved 25. Riverbank Edge, 27. Water Accumulated by Street Curb, 28. Canned Food Container, 29. Glass Containers 34. Leaf, 35. Plastic Bag, 37. Clay Pot, 38. Disposable Plastic Container, 39. Worn-out Banner, 40. Plastic Sewer Cover, 41. Scrap Metal, 43. Eggshell, 45. Walnut Shell, 48. Pit on Asphalt, 49. Earthen Ditch, 51. Water Well, 52. Dripping Water from Cooler, 54. Water pit next to human drinking trough, 65. Metal Cap, 66. Metal Water Tank, 67. Children’s Playground Flooring, 68. Metal Pipe.

**3. Black Rubber Builders Bucket, 4. Boat, 6. Concrete Water Basin, 8. Concrete Drainage Channel, 9. Water Fountains, 10. plastic caps, 11. Hole in Block Wall, 12. Clay Pots, 13. Dirt Hole, 14. Plastic pot, 15. Tree Trunk Hole, 17. Concrete Pipe, 18. Discarded Tire, 19. Pit on Paved Street, 20. Concrete Block, 21. Metal Trash Can, 22. Disposable Spoon, 25. Riverbank Edge, 27. Water Accumulated by Street Curb, 28. Canned Food Container, 29. Glass Containers, 30. Groove on Concrete, 31. Construction Debris, 32. Snail Shell, 33. Concrete/Cement Pit, 34. Leaf, 35. Plastic Bag, 36. Metal Pipe Under Asphalt, 37. Clay Pot, 38. Disposable Plastic Container, 39. Worn-out Banner, 40. Plastic Sewer Cover, 41. Scrap Metal, 42. Plant saucer, 43. Eggshell, 44. Tarpaulin Cover, 45. Walnut Shell, 46. Oak Tree Bark, 47. Concrete Hole, 48. Pit on Asphalt, 49. Earthen Ditch, 50. Light Bulb, 52. Dripping Water from Cooler, 54. Water pit next to human drinking trough, 56. Plastic Pipe, 57. Zinc Watering Can, 58. Pit under irrigation tap, 62. Metal door, 64. Plastic Water Basin, 65. Metal Cap, 67. Children’s Playground Flooring, 68. Metal Pipe, 69. Wooden Container, 70. Plastic bucket ,71 .Animal Troughs ,72 .Marsh ,73 .Vehicle Flooring ,74 .Cooler Stand ,75 .Drainpipe ,76 .Hole on Speed Bump ,77 .Sewage Channel with Metal Lid ,78 .Metal Bottle ,79 .Garbage Dump ,80 .Go-Kart Track.

***1. Under Cooler, 2. Animal Drinking Trough / Bird Feeder, 3. Black Rubber Builders Bucket, 4. Boat, 5. Water Barrel, 6. Concrete Water Basin, 7. Sewage Well, 8. Concrete Drainage Channel, 9. Water Fountains, 10. Plastic caps, 11. Hole in Block Wall, 12. Clay Pots, 13. Dirt Hole, 14. Plastic pot, 15. Tree Trunk Hole, 16. Wooden Cart, 17. Concrete Pipe, 18. Discarded Tire, 19. Pit on Paved Street, 21. Metal Trash Can, 22. Disposable Spoon, 23. Watermelon Rind, 24. Groove/Hole in Stone, 25. Riverbank Edge, 26. Concrete pot, 27. Water Accumulated by Street Curb, 28. Canned Food Container, 29. Glass Containers, 30. Groove on Concrete, 31. Construction Debris, 32. Snail Shell, 33. Concrete/Cement Pit, 34. Leaf, 35. Plastic Bag, 36. Metal Pipe Under Asphalt, 37. Clay Pot, 38. Disposable Plastic Container, 39. Worn-out Banner, 40. Plastic Sewer Cover, 41. Scrap Metal, 42. Plant saucer, 43. Eggshell, 44. Tarpaulin Cover, 45. Walnut Shell, 47. Concrete Hole, 48. Pit on Asphalt, 49. Earthen Ditch, 50. Light Bulb, 51. Water Well, 52. Dripping Water from Cooler, 53. Water on Steps, 54. Water pit next to human drinking trough, 55. Car wheel track, 56. Plastic Pipe, 57. Zinc Watering Can, 58. Metal Butter Can, 60. Uonolit, 61. Plastic Water Tank, 62. Metal door, 63. Concrete power poles, 64. Plastic Water pool.

Cluster 1 consists of Nur County. The recorded environmental metrics indicate a mean temperature of 12.1 °C, humidity 52% and rainfall 205 mm. Wind speed and population metrics showed similarly low variance, indicating stable conditions. The aggregated environmental data suggest that the habitats in this cluster are less conducive to the proliferation of invasive species, thereby categorizing them as low risk (Table 3).

The second cluster, representing Amol, Babolsar, Fereydunkenar and Mahmudabad counties, recorded a higher count of occurrences across a diverse range of habitat types (13.71). Environmental parameters included a mean temperature (18.41 °C), Humidity (73.53%) and Rainfall (998.06 mm), accompanied by low wind speed (20.32) and high population (175.91). These create an optimal environmental conditions for the establishment and spread of invasive mosquito species, resulting in a designation of moderate risk (Table 3).

The third cluster includes the counties of Chalus, Ramsar, Tonekabon, Abasabad, and Nowshahr. This group exhibited a high risk profile along with several characteristics, as detailed in Table 3.

The Generalized Estimating Equations analysis identified several significant positive predictors affecting the number of occurrences of potential larval habitats of invasive Aedes mosquitoes in Mazandaran Province. Population size exhibited a positive association (B = 0.00001098, Wald χ² = 20.087, p < 0.001), indicating that areas with higher human population densities are more likely to have increased occurrences of suitable larval habitats. Similarly, rainfall showed a significant positive effect (B = 0.002, Wald χ² = 13.300, p < 0.001), suggesting that higher precipitation levels contribute to a greater number of potential larval habitat occurrences (Table 4).

Table 4.

Results of generalized estimating equations showing significant predictors affecting the number of occurrences of potential larval habitats of invasive Aedes mosquitoes in Mazandaran Province, Northern Iran.

	B	Std. error	95% Wald confidence interval			Hypothesis test
			Lower	Upper		Wald Chi-square	df	Sig.
(Intercept)	13.805	3.3304	3.3304	7.278		20.333	17.183	˂0.001
Wind speed	-0.448	0.1038	0.1038	-0.651		-0.244	18.619	˂0.001
Population	0.00001098	2.4489E-06	2.4489E-06	6.176E-06		1.578E-05	20.087	˂0.001
Temperature	-0.441	0.1102	0.1102	-0.657		-0.225	15.978	˂0.001
Rainfall	0.002	0.0006	0.0006	0.001		0.003	13.300	˂0.001
(Scale)	1.585

Hot spot analysis

The results of hotspot clustering analysis in Mazandaran Province, using the Getis-Ord Gi* statistics, identified Chalus, Babolsar, and Amol counties as significant hotspots for potential Aedes albopictus larval habitats. These areas showed the highest Z-scores, ranging from 0.086001 to 0.220000, P < 0.05 indicating statistically significant spatial clustering of larval habitats. The positive Z-scores from the Getis-Ord Gi* analysis suggest these locations have a notably greater concentration of suitable larval habitats compared to other regions in the province, and should be prioritized for vector control interventions (Fig. 6).

Fig. 6.

Spatial hot spot analysis (Getis-Ord Gi*) of potential larval habitats for invasive Aedes mosquitoes in Mazandaran Province, northern Iran. The map was generated by the first author using ArcGIS version 10.5 (https://www.esri.com/en-us/arcgis/products/arcgis-desktop/overview).

Discussion

A total of 33 species of mosquitoes have been documented in the checklist for Mazandaran Province, with six species belonging to the genus Aedes³⁰. Notably, Aedes albopictus has been added as a new species to this list.

The discovery of Ae. albopictus in West Mazandaran Province is of significant public health concern. This invasive mosquito is a competent vector for several arboviruses including dengue, chikungunya, Zika and yellow fever². While autochthonous transmission of these viruses has not yet been reported by this species in Iran, the presence of Ae. albopictus increases the risk of future outbreaks, especially given the high volume of travel to and from endemic areas. The detection of Ae. albopictus in Mazandaran Province, aligns with global trends of expanding ranges for invasive mosquito species, driven by climate change and human activities³¹, represents a northward expansion of this invasive species within Iran. Previously, the species was observed for the first time from the Sistan & Baluchestan Province in the southeast of the country bordering Pakistan in 2016 ⁴. However, subsequent intensive entomological monitoring failed to detect the establishment of the species in southern provinces of Iran⁹. The suitable climate and habitat in Mazandaran has likely facilitated this spread. The province has a humid subtropical climate with warm summers and mild winters, which matches the preferred climate of Ae. albopictus.

To address the challenges posed by this invasive species, comprehensive and integrated vector control strategies should be developed and implemented. These include community engagement and public education to eliminate standing water, the promotion of environmentally sustainable source reduction practices, the incorporation of biological control methods, and the judicious use of insecticides. Continuous entomological surveillance is also essential to monitor the distribution and population dynamics of Ae. albopictus and to support timely, evidence-based interventions³².

It is important to note that resistance to insecticides has developed at an alarming rate in invasive Aedes species^33–35, and new techniques need optimization, cost-effectiveness and environmental safety³⁶. Habitat management as a long-term approach in response to the ecological characteristics of the vector, plays an important role in controlling invasive Aedes species and reducing the burden of diseases transmitted by them²⁷.

In the present study, the searching efforts for the detection of potential habitat types across different counties revealed significant variations in occurrences, distributions and abundance. The overall distribution of habitat types demonstrates that some habitats are more widespread than others, with types like disposable plastic containers, plastic caps and plastic bags being significantly more common compared to others. This finding aligns with previous studies that have highlighted the detrimental impact of urban waste on mosquito proliferation, particularly in areas where waste management practices are inadequate^28,29,37,38. This regional consistency indicates the ecological and public health relevance of our findings and the need for targeted management of diverse habitat types.

Overall, 61.54% of the identified potential larval habitats were associated with household and urban waste in our study. The prevalence of these habitats suggests that urban environments in western Mazandaran may be particularly vulnerable to invasive Aedes mosquito infestations due to the accumulation of litter. The survey conducted under normal municipal solid waste management practices further emphasizes this concern, as the presence of such load of wastes indicates sub-standard usage of waste collection bins near human settlements, careless disposal of and negligence of citizens regarding the management of household wastes. Contributing factors such as natural phenomena, including wind and water accumulation from heavy rains, may also prolong their presence in these environments and transform these types of habitats into potential larval breeding places, contributing to higher mosquito populations.

Moreover, aside from natural phenomena, indiscriminate wastage of water, particularly from municipal supplies, significantly contributes to water accumulation in household wastes, thus enhancing the suitability of these habitats for Aedes breeding³⁹. The link between household waste, socioeconomic factors, and disease prevalence underscores the necessity for raising awareness among communities regarding proper waste disposal⁴⁰.

The fact is that the persistent use of plastic and poor waste management practices result in a prolonged lifecycle for these materials, which in turn perpetuates the breeding of invasive Aedes mosquitoes and increases the risk of diseases such as dengue^40,41. Therefore, it is essential for communities to be oriented towards the potential risks associated with improperly managed wastes.

Improved waste management strategies and further research into effective management practices⁴² are crucial to minimize invasive Aedes populations in Mazandaran and similar urban areas where household waste significantly contributes to breeding sites. If not adequately addressed, the management of these household and urban wastes poses a continued risk for increased breeding of mosquitoes, particularly those of the Aedes genus. Therefore, targeted interventions to mitigate the effects of household waste on mosquito populations are imperative in tropical countries.

The analysis of the clusters reveals varying degrees of risk associated with potential larval habitats based on environmental conditions. Clusters 1, 2, and 3 highlight the necessity for targeted interventions, with particular attention required in high-risk areas i.e. Amol, babolsar, fereydunkenar, mahmoudabad where conditions are highly favorable for the proliferation of invasive mosquito species. The findings of Generalized Estimating Equations (GEE) analysis to elucidate the key determinants affecting the occurrence of potential larval habitats of invasive Aedes mosquitoes demonstrate that larval habitats in Mazandaran Province are likely influenced by synergistic interactions between human population density and rainfall patterns. These results extend the established ecological framework of container-breeding mosquito proliferation by quantifying the relative contributions of socio-environmental factors in northern Iran’s unique climate. These patterns align with findings from Barrera et al., which emphasize the combined effects of urbanization and rainfall in shaping the distribution and abundance of Aedes larval habitats and highlight the importance of environmental management in vector control efforts⁴³. The positive population density effect reflects progressive urbanization’s role in creating artificial aquatic habitats through water storage practices and infrastructure gaps. As human settlements expand, the accumulation of plastic containers, construction debris, and poorly maintained drainage systems generates microhabitats that bypass natural limitations on larval carrying capacity⁴⁴. Rainfall similarly enhances larval habitat availability by creating and sustaining temporary aquatic sites essential for mosquito oviposition and larval development⁴⁵. Notably, the observed negative temperature correlation (β=-0.441) implies potential thermal exclusion during peak summer months, however, it should be noted that although high temperatures, especially in the warm seasons, generally reduce the availability of larval habitats, in urban environments, artificial containers such as water tanks, plastic containers, discarded tires, and plant pots serve as microhabitats that moderate temperature fluctuations. These containers create thermal buffering by maintaining more stable and cooler internal microclimates compared to the external environment, thereby protecting larvae from lethal heat stress. This thermal buffering effect is particularly important during the hottest periods and enables the persistence and proliferation of Aedes mosquitoes in urban cores despite unfavorable ambient temperatures^43,46.

The hotspot analysis using the Getis-Ord Gi* statistic further substantiates the spatial heterogeneity of potential Aedes albopictus larval habitats across Mazandaran province. The identification of Chalus, Babolsar, and Amol counties as significant hotspots with statistically significant Z-scores (p < 0.05) underscores the elevated risk in these specific areas (Fig. 6). These findings complement the cluster analysis by emphasizing that varying environmental conditions contribute to localized increases in larval habitat suitability. This spatial consistency between the hotspot analysis and the risk clustering results further supports the validity of the identified high-risk areas. Both approaches highlighted Chalus, Babolsar, and Amol as priority counties, indicating that environmental and spatial factors jointly contribute to the elevated risk of Aedes proliferation in these regions. Such convergence between the two methods enhances confidence in the robustness of the risk assessment framework and provides a solid basis for targeted vector control planning. To mitigate the risks associated with these invasive species and reduce the burden of Aedes-borne diseases in the future in each clusters, it is crucial for provincial health authorities to implement targeted interventions aimed at reducing potential larval habitats. This can be achieved by measures as follows:

• Implement a Clean Mazandaran Campaign: Launch a focused campaign aimed at promoting cleanliness and reducing potential Aedes breeding sites across the province.

• Organize Orientation Sessions for Intra- and Inter-sectoral Collaborations: Holding regular meetings with clear agenda and outcomes to enhance communication and cooperation among various organizations, to foster a unified approach to mosquito control efforts.

Promote public awareness and education: Developing educational programs to inform the public about the importance of eliminating stagnant water and maintaining clean environment to will help prevent Aedes breeding. Increased awareness can lead to proactive community behavior.

• Perform Regular Surveillance: Establish a continuous entomological surveillance system to track the dynamics of invasive Aedes populations and quickly identify new breeding sites.

• Promote water storage practices: Ensuring water supply system that eliminate the need for storing water in open containers that helps reduce breeding habitats. This can be achieved through water infrastructure development as well as public education on efficient water use.

• Implement Community Participation Programs: Educate residents on the importance of eliminating stagnant water and appropriate waste disposal methods to minimize potential breeding sites for mosquitoes.

• Enhance Waste Management Practices: Develop strategies for effective municipal waste management, with an emphasis on the removal of disposable plastic containers and other debris that can collect water.

• Adopt Integrated Vector Management (IVM): through a rational decision-making process encouraging optimal use of resources for efficient, cost-effective and sustainable Aedes vector control in line with the Global Vector Control Response 2017–2030 (GVCR) that provides a new strategy to strengthen vector control worldwide through increased capacity, improved surveillance, better coordination and integrated actions.

• Strengthen Collaboration with Local Stakeholders: Involve local businesses and community groups in vector control initiatives to promote shared responsibility in managing potential larval habitats.

• Implement Policy and Regulatory Measures: Developing and enforcing policies that mandate the removal of potential breeding sites in public spaces and residential areas is essential. Regular inspections should be conducted to ensure compliance with these regulations.

By prioritizing these recommendations and fostering collaboration among relevant organizations, it will be possible to create a more sustainable approach to vector control that addresses both immediate challenges and long-term ecological balance.

Limitations of the study

Despite the strengths of this study, several limitations should be acknowledged. First, the assessment of potential larval habitats was conducted only in ten selected counties, prioritizing areas with high human mobility, tourism, or trade activity. Although this targeted design increased the likelihood of detecting invasive Aedes habitats, it inherently limits the province-wide representativeness of the findings. Counties not included in the survey may host additional habitat types or different ecological patterns that were not captured in this study. Second, the survey of larval habitats was cross-sectional and limited to the summer season, which may not reflect seasonal fluctuations in container availability, rainfall-driven habitat formation, or human behaviors influencing habitat dynamics. Continuous or year-round monitoring would be necessary to better characterize temporal variations in habitat productivity.

Finally, larval productivity of habitat types was not evaluated, meaning that while occurrence and distribution of potential habitats were mapped, their actual contribution to Ae. albopictus population dynamics could not be quantified. Future studies incorporating larval density measurements and longitudinal sampling would help clarify the epidemiological significance of each habitat category.

Conclusion

This is the first report of the presence of Aedes albopictus in Mazandaran, northern Iran, serving as a clear call to action for researchers and public health officials to address the multifaceted challenges posed by this invasive mosquito species. This exploratory field study provides a comprehensive assessment of potential larval habitats of invasive Aedes mosquitoes in western Mazandaran. Disposable plastic containers, water caps and plastic bags were observed with high abundance across the studies counties. The observed abundance of potential larval habitats suggests that certain environmental and waste-related conditions may support the proliferation of invasive Aedes species. These findings highlight the importance of integrating habitat management strategies into ongoing vector surveillance programs. In this context, community participation—particularly in improving household waste disposal practices and reducing water-holding containers—can play a supportive role in enhancing the effectiveness of local vector control efforts. The baseline data generated in this exploratory study may provide useful initial insights that complement future, more comprehensive surveillance efforts. While the current findings provide preliminary information on the distribution and characteristics of potential larval habitats, broader longitudinal studies are needed to confirm these patterns. Nevertheless, these early data can support the refinement of local vector management plans and contribute to more informed prioritization of resource allocation within integrated vector control programs.

Author contributions

Conceptualization, A.A.E, M.Z and S.H.N.; Methodology, S.H.N, A.C and M.F.D.; Formal analysis, S.H.N and J.Y.C; Investigation, S.H.N.; Resources: S.H.N.; Data curation, S.H.N.; Writing—original draft, S.H.N; Writing—review and editing, A.A.E; Visualization, A.A.E., M.Z and S.H.N; Supervision, A.A.E and S.H.N.; Project administration, A.A.E and S.H.N.; Validation, A.A.E and S.H.N.; Funding acquisition, S.H.N. All authors have read and agreed to the published version of the manuscript.

Funding

This work was supported by the Mazandaran University of Medical Sciences [grant numbers 22669].

Data availability

The datasets generated and/or analyzed during the current study are presented in the manuscript and also are available from the corresponding author on reasonable request.

Declarations

Competing interests

The authors declare no competing interests.

Ethics statement

The study was designed according to the national ethical rules and regulations and approved by Ethic Committees of Mazandaran University of Medical Sciences (with Ethics codes: IR.MAZUMS.REC.1403.385).