The emergence of autochthonous dengue fever in Iran: a comprehensive analysis of the first major outbreak in Sistan and Baluchestan Province, 2024

Abstract

Background

Dengue fever (DF) is an emerging disease in Iran. The first large-scale local transmission outbreak occurred in southeastern Iran in 2024. This study aimed to investigate the demographic, geographical, and clinical features of this outbreak in Sistan and Baluchestan Province.

Methods

This retrospective cross-sectional study investigated a recent DF outbreak in Chabahar County, Sistan and Baluchestan Province, southeastern Iran. Data from the centers for disease control (CDC) of Iran’s Ministry of Health including socio-demographic factors, travel history to endemic areas, laboratory results, clinical symptoms, hospitalization records, disease severity, and treatment outcomes were analyzed. Statistical analysis was performed using SPSS software.

Results

A total of 871 DF cases were recorded in Sistan and Baluchestan Province in 2024, with the highest burden (98%) reported from Chabahar County. The incidence rate peaked during the last week of October, indicating a seasonal pattern. Patients were predominantly male (59.9%), with a mean age of 33.7 years (SD: 15.4). The most frequent clinical symptoms were fever, headache, and muscle or joint pain, reported in more than 97% of patients. Rapid diagnostic tests (RDT) with Non-Structural Protein 1 (NS1) antigen were used for primary confirmation in 83.3% of cases. Importantly, 4.8% of DF patients were diagnosed with dengue hemorrhagic fever (DHF). Common hematological abnormalities included low hematocrit levels (61.9%), thrombocytopenia (42.6%), and leukopenia (43.5%). Molecular testing identified circulation of DENV-1 and DENV-2 serotypes. Only 8.3% of total patients required hospitalization; all patients recovered fully, and no fatalities related to DF were reported.

Conclusion

This study documents the first large-scale local transmission outbreak of DF in Iran. It provides important information on geographical, demographic, and clinical features of DF in the study areas, which may serve as an effective guide for health systems to control this emerging disease. Importantly, the establishment of Aedes aegypti in southern Iran marks a critical transition toward endemicity, underscoring the need for sustained vector surveillance and control measures.es

Introduction

Dengue fever (DF) is a major emerging and re-emerging arboviral disease, transmitted to humans via the bites of infected Aedes aegypti and Aedes albopictus mosquitoes, which inhabit both urban and rural environments [1, 2]. The causative agent is a single-stranded, positive-sense ribonucleic acid (RNA) virus belonging to the Flaviviridae family, which comprises four distinct serotypes: DENV-1, DENV-2, DENV-3, and DENV-4 [3]. Infection with one serotype confers lifelong immunity only to that serotype; however, subsequent infections with different serotypes increase the risk of severe disease [4].

Approximately 80% of dengue virus infections are asymptomatic. Symptomatic cases present a wide range of nonspecific clinical features, including high fever, localized muscle pain, severe frontal headache, retro-orbital discomfort, bone pain, myalgia, arthralgia, and maculopapular rash. These manifestations often resemble those of other infectious diseases (e.g., influenza, measles, typhoid fever, leptospirosis, typhus fever, and malaria), which complicates diagnosis. Accurate and timely diagnosis is therefore critical for effective management, typically facilitated by dengue rapid diagnostic tests (RDTs) [5, 6]. Currently, no universally approved treatment or vaccine is exists for DF across all age groups., making mosquito bite prevention the most effective strategy for disease control [7, 8]. However, effective prevention and control of DF also depend on the knowledge, attitudes, and practices (KAP) of healthcare professionals. Several studies have highlighted how limited awareness, inadequate attitudes, and poor practices among health service providers can hinder timely diagnosis, case management, and vector control efforts, thereby exacerbating the risk of outbreaks [9–11].

Multiple factors, including socio-economic conditions, urban expansion, international travel, climate change, and population growth, contribute to the rising incidence and global spread of DF [12, 13]. The World Health Organization (WHO) estimates that approximately 390 million dengue infections occur annually, and a significant proportion of the global population remains at risk for DF [14, 15]. The resurgence of the disease has elevated it to a pressing global public health priority, particularly in tropical and subtropical regions [15].

Beyond the global expansion of DF, the Eastern Mediterranean Region (EMR) has experienced a marked escalation in its DF burden over the past two decades, with repeated outbreaks reported in at least nine endemic countries, including Pakistan, Afghanistan, Yemen, Sudan, Oman, Saudi Arabia, Egypt, Somalia, and Djibouti [16–22]. In several of these settings, most notably Pakistan, Yemen, Sudan, and parts of the Arabian Peninsula, large recurrent epidemics have been driven by rapid urbanization, informal water storage, protracted conflict, and climate‑related extreme rainfall, creating highly favorable conditions for Aedes breeding and sustained virus circulation [12, 16–23]. WHO currently classifies the regional DF risk as high, and Ae. aegypti and Ae. albopictus have been documented in most EMR countries, underscoring that Iran is surrounded by an expanding belt of DF transmission along its eastern and southern borders [18, 20, 21, 24]. Given Iran’s extensive travel, trade, and labor migration links with Pakistan, Afghanistan, and Gulf countries, as well as suitable climatic conditions in its southern coastal belt, the country is uniquely vulnerable to the introduction and local amplification of DF once competent Aedes vectors become established [18, 21, 25–27].

Vector presence is a determinant of dengue virus transmission in Iran, and the recent spread of Aedes mosquitoes has fundamentally altered the country’s risk profile [26, 28]. Recent entomological surveillance confirmed Ae. aegypti in southern coastal provinces, with established populations documented in Hormozgan since 2020 and the first detection in Chabahar, Sistan and Baluchestan Province, in late 2023 [25, 29]. This temporal sequence, imported human cases for more than a decade in the absence of sustained local transmission, followed by the confirmed establishment of Ae. aegypti in key port cities strongly suggests that the 2023 detection of Ae. aegypti in Chabahar acted as the primary catalyst enabling autochthonous DF transmission during the 2024 outbreak [24, 27, 30]. In line with WHO’s risk assessment for Iran, the confirmation of local DF transmission in 2024 is considered an “unusual but expected” event, specifically because competent Ae. aegypti are now established in multiple southern and southeastern provinces that sustain intense human mobility with dengue‑endemic countries [31].

In Iran, the first documented case of DF occurred in 2008 in a traveler returning from Southeast Asia [32]. In response, a national human DF surveillance system was established in 2010, followed by the implementation of an entomological surveillance system in 2015 to strengthen vector monitoring and control [33]. All DF cases reported in Iran prior to 2024 were classified as imported infections. In 2024, however, autochthonous transmission was confirmed, involving 12 cases in Bandar Lengeh, Hormozgan Province, followed by a larger-scale outbreak in Sistan and Baluchestan Province, particularly in Chabahar County [31].

Epidemiological and geographical studies are vital for understanding the burden, transmission dynamics, and risk factors associated with DF. This study provides a comprehensive assessment of epidemiological data on DF in Sistan and Baluchestan Province, with the aim of informing policy decisions, guiding future research, and enhancing strategies for the prevention, management, and eventual elimination of this study in Iran and other at-risk regions worldwide.

Materials and methods

Study area

The study was conducted in Sistan and Baluchestan Province located in southeastern Iran. This province is strategically located, bordered by the Sea of Oman to the south and sharing land borders with Pakistan and Afghanistan to the east. Chabahar County, the focal point of this study, is situated in the southern part of the province. It is the only oceanic port in Iran and is equipped with modern infrastructure, including two major ports capable of handling ocean-going container vessels with a combined annual capacity of 8.5 million tons.

The geographical importance of the study area lies in its role as a vital corridor for international trade, facilitating connections between Central Asia and global markets. The port’s strategic location provides the shortest access to international waters for non-coastal Central Asian countries such as Turkmenistan, Uzbekistan, Tajikistan, Kyrgyzstan, and Kazakhstan (Fig. 1).

Fig. 1.

Geographical and topographical map of Chabahar County, southeastern Iran

Climatically, Chabahar County experiences relatively mild conditions compared to other parts of the province. It is characterized by a tropical climate with high humidity and low average annual rainfall, which occurs mainly during the summer months and can lead to flooding. These weather patterns, combined with consistently warm temperatures, create an environment conducive to the transmission of mosquito-borne diseases such as DF.

Human interactions further contribute to the vulnerability of this area to disease transmission. The proximity to Pakistan facilitates substantial cross-border movement of people and goods, increasing the likelihood of disease importation. In addition, socio-economic activities such as trade, tourism, and pilgrimage routes amplify the risk of outbreaks.

Study design and data collection

This retrospective cross-sectional study investigated the recent local transmission outbreak of DF in Chabahar County, Sistan and Baluchestan Province, southeastern Iran (Fig. 1). Data were collected from multiple healthcare facilities, including public and private health centers, hospitals, and laboratories, to ensure a comprehensive dataset of patients with confirmed DF.

Epidemiological investigations were conducted for each case to determine whether the infection was locally transmitted or imported. This classification was based on patient interviews regarding travel to endemic areas within the two-week incubation period. Additionally, assessments were conducted within a 500-meter radius of each patient’s residence and workplace to screen contacts and identify potential DF cases.

Data collection was conducted using a census method, whereby healthcare providers recorded epidemiological characteristics and clinical manifestations of confirmed DF patients. Information was gathered according to a national guideline checklist and registered in the Ministry of Health’s surveillance registry system. For each confirmed case, socio-demographic information (age, gender, residential area, occupation, nationality), travel history, laboratory results, clinical symptoms, hospitalization details, disease severity classification (DF, DHF, DSS), and treatment outcomes were documented.

Dengue case definitions

Confirmed dengue infection is defined as:

• Positive Non-Structural Protein 1 (NS1) antigen test.

• Positive PCR result.

• Seroconversion of Immunoglobulin M (IgM) or Immunoglobulin G (IgG) [34].

• A fourfold increase in IgG titers.

Probable dengue infection was defined as an acute febrile illness (temperature > 38 °C) accompanied by a positive epidemiological history (e.g., travel to endemic areas or mosquito exposure) or positive serology (IgM and/or IgG in a clinical sample), together with at least two clinical symptoms. This included severe headache, retro-orbital pain, gastrointestinal symptoms (nausea or vomiting), myalgia, weakness, fatigue, arthralgia/severe bone pain, maculopapular or morbilliform rash, hemorrhagic manifestations, leukopenia, thrombocytopenia, positive tourniquet test, and hematocrit increase.

Diagnostic protocols and testing algorithm

The national diagnostic protocols for DF in Iran included:

1. Rapid Diagnostic Test (RDT): NS1 antigen and IgM/IgG antibody detection using the Bioline™ Dengue Duo Kit (Abbott Diagnostics Korea Inc., Lot No. 101106). Reported sensitivity: NS1 = 92.4%; IgM/IgG = 94.2%.

2. Enzyme-Linked Immunosorbent Assay (ELISA): Anti-Dengue Virus IgM/IgG antibody test (EuroImmun, Germany), with sensitivity 98.5–100% and specificity 95.7%−100%.

3. Molecular testing: Real-Time RT-PCR for viral genome detection with samples analysed at the Pasteur Institute of Iran.

Viremia typically begins 2–3 days before fever onset and lasts for 4–7 days. During this period, both molecular and antigen tests are expected to yield positive results. Immunoglobulin M antibodies are detectable from days 3–5 of illness, peaking within two weeks, while IgG antibodies appear by the end of the first week and may remain detectable for years.

Serotyping of the dengue virus

As part of the epidemiological study, virological assessments were conducted to determine circulating dengue virus serotypes. A total of 37 blood samples were randomly selected over the course of the outbreak, without specific selection criteria, and analysed using molecular methods at the Pasteur Institute of Iran. This process was essential for identifying circulating strains and informing appropriate public health responses.

Monitoring clinical progression

Three laboratory tests were ordered for all confirmed DF cases to monitor disease progression and guide treatment:

• White Blood Cell Count (WBC): normal range 4,000–10,000 cells/µL.

• Platelet Count (Plt): normal range 150,000–450,000 platelets/µL.

• Hematocrit (Hct): normal range 36–48% (females), 42–54% (males).

Only one-quarter of confirmed patients underwent these supplementary tests, as most declined additional testing. This limited participation may affect the generalizability of findings regarding DF clinical features.

Severity classification framework

The classification of dengue cases in this study was conducted according to the Comprehensive Guidelines for Prevention and Control of Dengue and Dengue Haemorrhagic Fever, Revised and Expanded Edition, published by the WHO Regional Office for South-East Asia (2011). This guideline follows the 1997 WHO classification system, which categorizes cases into DF, DHF (Grades I–IV), and DSS (operationally equivalent to DHF Grades III and IV). Criteria applied were as follows:

• DF: Fever with two of the following: headache, retro-orbital pain, myalgia, arthralgia/bone pain, rash, hemorrhagic manifestations; no evidence of plasma leakage. Laboratory findings: leucopenia (WBC ≤ 5000/mm³), thrombocytopenia (< 150,000/mm³), rising hematocrit (5–10%), no evidence of plasma loss.

• DHF: Including:

  • Grade I: Fever and hemorrhagic manifestation (positive tourniquet test) plus evidence of plasma leakage; laboratory: thrombocytopenia < 100,000/mm³ and hematocrit rise ≥ 20%.
  • Grade II: As in Grade I plus spontaneous bleeding; laboratory: thrombocytopenia < 100,000/mm³ and hematocrit rise ≥ 20%.

• DSS: Including:

  • Grade III: As in Grade I or II plus circulatory failure (weak pulse, narrow pulse pressure ≤ 20 mmHg, hypotension, restlessness); laboratory: thrombocytopenia < 100,000/mm³ and hematocrit rise ≥ 20%.
  • Grade IV: As in Grade III plus profound shock with undetectable blood pressure and pulse; laboratory: thrombocytopenia < 100,000/mm³ and hematocrit rise ≥ 20%.

Data analysis

Data were analysed using IBM SPSS Statistics for Windows, Version 25 (IBM Corp., Armonk, NY, USA). Both qualitative and quantitative variables were assessed. Chi-Square tests were used for categorical data. When assumptions were violated (> 20% of cells with expected frequency < 5), the Fisher-Freeman-Halton exact test with Monte Carlo simulation was applied. Associations between travel history and study months were evaluated using Chi-Square and exact tests. Correlations between dengue cases and climatic variables (temperature, relative humidity, precipitation) were examined using Spearman correlation analysis. Trends in DF cases were analysed and visualized by epidemiological week using Microsoft Excel.

Mapping and spatial analysis

To visualize patient distribution and health center coverage under the CDC of Chabahar University, geographic coordinates of patients and health centers were obtained from Google Maps and validated against recorded addresses. Distribution maps were created using ArcGIS Desktop, Version 10.7 (Esri, Redlands, CA, USA). Base layers were sourced from OpenStreetMap, enabling comprehensive spatial analysis of DF case distribution and health center coverage.

Results

Overview

In 2024, a total of 871 DF cases were confirmed, with the majority concentrated in Chabahar County. 59.9% of cases were male, patients′ ages ranged from 2 to 93 years (median: 33 years; IQR: 21 years; mean ± SD: 33.66 ± 15.40 years; mode: 35 years). The majority of patients (94.8%) resided in urban areas, highlighting the higher prevalence of dengue fever in densely populated regions. Additionally, Iranian nationals made up the largest portion of the sample (92.2%), while Afghan and Pakistani nationals accounted for smaller percentages. Moreover, 93.7% of individuals reported no recent travel to endemic areas (Table 1).

Table 1.

Travel history to endemic areas by demographic factors among dengue fever cases, Chabahar County, Sistan and Baluchestan Province, southeastern Iran, 2024

Demographic factor		Travel history (within the past 15 days)				Total		P-value
		Yes		No
		N.	%	N.	%	N.	%
Gender	Male	39	4.5	483	55.5	522	59.9	0.3
	Female	20	2.3	329	38.8	349	40.1
	Total	59	6.8	812	93.2	871	100
Month	June	2	0.2	0	0	2	0.2	0.001
	July	0	0	1	0.1	1	0.1
	August	4	0.5	43	4.9	47	5.4
	September	15	1.7	32	3.7	47	5.5
	October	21	2.5	204	23.4	225	25.8
	November	10	1.1	391	44.9	401	46.0
	December	7	0.8	141	16.2	148	17.0
	Total	59	6.8	812	93.2	871	100
Occupation	Student	8	0.8	122	14.0	130	14.9	0.001
	Worker	6	0.7	103	11.7	109	12.6
	Self-Employed	17	2.0	191	21.8	208	23.9
	Housewife	17	2.0	241	27.7	258	29.6
	Unemployed	3	0.3	58	6.7	61	7.0
	Farmer	4	0.5	5	0.6	9	1.0
	Governmental	4	0.5	92	10.6	96	11.0
	Total	59	6.8	812	93.2	871	100
Region	Urban	53	6.1	773	88.7	826	94.8	0.1
	Rural	6	0.7	39	4.5	45	5.2
	Total	59	6.8	812	93.2	871	100
Nationality	Iranian	52	6.0	751	86.2	803	92.1	0.1
	Afghan	2	0.2	49	5.6	51	5.9
	Pakistani	5	0.6	12	1.4	17	2.0
	Total	59	6.8	812	93.2	871	100
Travel destination	Not traveled	0	0	812	93.2	812	93.2	0.001
	United Arab Emirates	1	0.1	0	0	1	0.1
	Pakistan	56	6.4	0	0	56	6.4
	Afghanistan	2	0.2	0	0	2	0.2
	Total	59	6.8	812	93.2	871	100

Note: Percentages may not sum to exactly 100 due to rounding. P-values were calculated using Chi-square tests and the Fisher-Freeman-Halton exact test with Monte Carlo simulation

The 30–39 year age group accounted for proportion of DF cases, representing 25.8% of all cases. 23.8% of males and 28.9% of females were affected (Fig. 2). Chi-Square analysis showed no statistically significant association between age group and gender among DF patients (P = 0.07).

Fig. 2.

Distribution of dengue fever cases by gender and age groups in Chabahar County, Sistan and Baluchestan Province, southeastern Iran, 2024

Close contacts

It is important to note that among the identified cases, 104 individuals were confirmed positive for DF among close contacts of patients, accounting for approximately 12% of total cases in the surrounding area.

Temporal analysis

Weekly and monthly analyses revealed a significant rising trend in DF cases. The local transmission outbreak began in June 2024, with the first imported cases reported in epidemiological week 23. This phase marked the beginning of local transmission, which intensified in the subsequent months. In July, only one case was reported. However, the situation changed significantly in August, when cases surged to 47. This upward trajectory continued into September, indicating sustained local transmission. The outbreak peaked in October and November, with the highest weekly frequency observed in week 44, reaching 127 cases (Fig. 3).

Fig. 3.

The weekly temporal trend of dengue fever according to local and imported cases in Chabahar County, Sistan and Baluchestan Province, southeastern Iran, 2024

Travel history

Overall, 6.8% of all DF patients reported recent travel to endemic areas (within the past 15 days). Gender-based analysis of recent travel history revealed, 7.5% of males reported recent travel compared to 5.6% of females. However, these differences were not statistically significant (P-value = 0.3). A temporal pattern was also observed in travel history across different months. In June, all participants (N = 2) reported recent travel, although the small sample size limits generalizability. In contrast, October showed a higher number of travelers (21 individuals, 2.4%), while November and December reflected lower travel rates (1.1% and 0.8%, respectively).

The association between travel history and study months (July–December) was examined using the Chi-square test. The Pearson Chi-square was significant (χ² = 89.811, df = 6, p < 0.001). As several cells had expected counts less than 5, the Fisher-Freeman-Halton exact test with Monte Carlo simulation (10,000 samples) was additionally performed, confirming the statistical significance (p < 0.001). These findings indicate that travel behavior was not uniformly distributed across months, suggesting that external factors such as seasonal changes or socio-economic conditions may significantly influence travel patterns (Table 1).

Dengue fever symptoms

Several symptoms were highly prevalent among the participants. Notably, fever was reported by all age groups, with a prevalence of 100%. Headache and body pain also showed significant prevalence, with rates of 99.6% and 99.3%, respectively. Further analysis revealed that symptoms with a prevalence exceeding 50% included muscle pain, reported by 97.7% of participants, and calf muscle pain, observed in 62% of cases, particularly among middle-aged individuals (63.5%). Vomiting was reported in 23.9% of participants, with a higher prevalence among children (30%). Eye pain and nausea were also prevalent, affecting 20.9% and 18.8% of participants, respectively. In contrast, other symptoms such as diarrhea, sore throat, and itchy rash were less commonly reported, with prevalence rates below 20%. The detailed breakdown of these symptoms, categorized by age group, is presented in Table 2.

Table 2.

Clinical features and outcome of dengue fever by age groups in Chabahar County, Sistan and Baluchestan Province, southeastern Iran, 2024

Category	Sub-Category	Age classification group										Total
		Child		Adolescence		Youth		Middle-aged		Elderly
		N	%	N	%	N	%	N	%	N	%	N	%
Symptom	Fever	10	100	146	100	203	100	455	100	57	100	871	100
	Headache	10	100	145	99.3	203	100	453	99.5	57	100	868	99.6
	Generalized body pain*	10	100	145	99.3	203	100	450	98.9	57	100	865	99.3
	Muscle pain**	10	100	143	97.9	198	97.5	445	97.8	55	96.5	851	97.7
	Calf muscle pain	5	50.0	92	63	119	58.6	289	63.5	35	61.4	540	62
	Vomiting	3	30.0	39	26.8	47	23.1	104	22.9	15	26.3	208	23.9
	Eye pain	1	10.0	33	22.6	48	23.6	89	19.6	11	19.3	182	20.9
	Nausea	4	40.0	34	23.3	37	18.2	79	17.4	10	17.5	164	18.8
	Diarrhea	2	20.0	19	13	26	12.8	56	12.3	7	12.3	110	12.6
	Sore throat	1	10.0	12	8.2	22	10.8	39	8.6	5	8.8	79	9.1
	Itchy rash	1	10.0	5	3.4	11	5.4	16	3.5	1	1.8	34	3.9
	Skin rash	0	0	8	5.5	2	1.0	8	1.8	2	3.5	20	2.3
	Loss of appetite	0	0	4	2.7	5	2.5	6	1.3	0	0	15	1.7
	Neurological disturbance	0	0	1	0.7	0	0	7	1.5	0	0	8	0.9
	Runny nose	0	0	0	0	1	0.5	4	0.9	0	0	5	0.6
	Red eye	0	0	0	0	1	0.5	3	0.7	0	0	4	0.5
	Severe abdominal pain	0	0	1	0.7	0	0	2	0.4	0	0	3	0.3
	Chills	0	0	0	0	0	0	2	0	0	0	2	0.2
	Hypotension	0	0	1	0.7	0	0	1	0.2	0	0	2	0.2
	Joint pain and inflammation	0	0	0	0	0	0	1	0	0	0	1	0.1
	Decreased consciousness	0	0	0	0	0	0	0	0	1	1.7	1	0.1
	Tachycardia	0	0	0	0	0	0	0	0	1	1.7	1	0.1
	Respiratory distress	0	0	1	0.7	0	0	0	0	0	0	1	0.1
	Abdominal pain	0	0	0	0	1	0.5	0	0	0	0	1	0.1
Severity	DF***	10	1.1	143	14.6	191	21.9	432	49.6	53	6.1	829	95.2
	DHF****	0	0	3	0.3	12	1.4	23	2.6	4	0.5	42	4.8
	DSS*****	0	0	0	0	0	0	0	0	0	0	0	0
	Total	10	1.1	146	16.8	203	23.3	455	52.2	57	100	871	100
Hospitalization	Outpatient	10	1.1	134	15.4	188	21.6	417	47.9	50	5.7	799	91.7
	Inpatient	0	0	12	1.4	15	1.7	38	4.4	7	0.8	72	8.3
Outcome	Recovery	10	1.1	146	16.8	203	23.3	455	53.2	57	6.5	871	100
	Death	0	0	0	0	0	0	0	0	0	0	0	0
Total		10	1.1	146	16.8	203	23.3	455	53.2	57	6.5	871	100

Note: Percentages for all reported symptoms are calculated relative to the total study population (N = 871).

*General discomfort throughout the body ** Discomfort localized to muscle groups *** DF: Dengue fever ****DHF: Dengue hemorrhagic fever ***** DSS: Dengue Shock Syndrome

The hospitalization rate among patients was 8.3%, with 9.4% for men and 6.5% for women. Among the three types of DF, 95.2% of the cases were classified as DF, while approximately 4.8% of patients were diagnosed with DHF. The analysis indicated that these conditions did not differ significantly between genders. However, when examining age groups, it was found that 7% of elderly patients experienced DHF, while all pediatric cases were categorized as DF (Table 2).

Dengue fever diagnostic methods

In 83.3% of cases, the NS1 test (alone or in combination) was utilized for initial diagnosis, either as a standalone test or in combination with other tests. In the remaining cases, the diagnostic approach involved the use of IgG and IgM tests. Confirmatory molecular testing, specifically PCR, was conducted for 46.84% of the patients in this study. Among those who underwent PCR testing, an impressive 92.9% tested positive for dengue.

Among 37 samples selected for serotyping, 9 were identified as DENV-2, while the remainder were classified as DENV-1.

Laboratory diagnostic tests

In our study, only 25% of individuals collaborated with healthcare providers for additional laboratory tests, indicating limited engagement with medical services. The status of three critical laboratory tests (WBC, hematocrit, and platelets) was analyzed, and the results are depicted in Fig. 4. Statistical analysis provided additional context to these findings, with the mean recorded at 4.62 ± 2.53, 40.17 ± 21.20 and 157.78 ± 70.04 for WBC, hematocrit and platelets, respectively. The findings reveal that among the tested population, a notable percentage of individuals exhibited non-normal results. Specifically, for the WBC test, 44% were identified as non-normal. In the cases of Hematocrit and Platelets tests, 61.9% and 43% of individuals fell into the low category, respectively (Table 3).

Fig. 4.

The weekly trend of meteorological data and dengue fever cases in Chabahar County, Sistan and Baluchestan Province, southeastern Iran, 2024

Table 3.

Laboratory diagnostic tests and hematological findings among dengue fever cases in Chabahar County, southeastern Iran, 2024

Laboratory diagnostic test			Frequency
			N.	%
Antigen/Antibody test (N = 871)		NS1	559	64.2
		NS1-IGM	109	12.5
		IGG-IGM	99	11.4
		IGM	69	7.9
		NS1-IGG-IGM	29	3.3
		NS1-IGG	6	0.7
		Total	871	100
PCR (N = 408)		Positive	379	92.9
		Negative	29	7.1
		Total	408	100
Serotype (N = 37)		DENV-1	28	75.7
		DENV-2	9	24.3
		Total	37	100
Hematological Parameters	WBC* (N = 223)	Low	97	43.5
		Normal	122	54.7
		High	4	1.8
		Total	223	100
	Plt** (N = 223)	Low	95	42.6
		Normal	128	57.4
		High	0	0
		Total	223	100
	Hct*** (N = 218)	Low	135	61.9
		Normal	82	37.6
		High	1	0.5
		Total	218	100

*WBC: White Blood Cell (4,000–10,000 cells per microliter; normal range) **Plt: Platelet (150,000–450,000 platelets per microliter; normal range) ***Hct: Hematocrit (Female: 36% − 48%; Male: 42% − 54%)

Dengue fever and meteorological data

Figure 4 illustrates the weekly epidemiological trends of dengue cases alongside meteorological data, including average temperature, average relative humidity, and total precipitation. Spearman’s correlation analysis revealed did not find a statistically significant positive association between dengue cases and both average temperature (r = − 0.806, p < 0.001) and average relative humidity (r = − 0.486, p = 0.006). Additionally, a weaker but significant negative correlation was observed between dengue cases and precipitation (r = − 0.367, p = 0.046). These findings suggest that higher temperature and humidity levels may be inversely associated with dengue incidence in the study area.

Patient spatial distribution

The data presented in Fig. 5 illustrates a clear disparity in the incidence of DF cases between urban and rural health centers. In urban healthcare facilities, DF incidence rate ranged from 45.4 to 106.7 cases per 10,000 population. In contrast, the incidence in rural healthcare centers was significantly lower, falling within the 0–10 per 10,000 population range. The analysis of patient distribution across health centers revealed significant disparities in the frequency of patients. The Sayyid al-Shuhada center recorded the highest number of patients, representing 36.5% of the total patients. Following closely, the Imam Ali center accounted for 20.9%, and the Hazrat Mohhammad center contributed 13.2%. In contrast, several centers including Ramin, Baluchi Dervish, and Pirsahraab reported minimal patient numbers, each with fewer than five cases.

Fig. 5.

Dengue fever prevalence per 10,000 populations in health centers of Chabahar County, Sistan and Baluchestan Province, southeastern Iran, 2024

Discussion

Dengue fever is a deadly emerging and re-emerging arbovirus disease which is transmitted by invasive Aedes mosquitoes and distributed in tropical and subtropical environments around the world [35–37]. Over the past 30 years, the burden of DF has increased alarmingly, especially in Asia [38–40]. The dynamics of the disease outbreaks are influenced by the complex interaction among the agent (various serotypes of dengue virus), vectors (invasive Aedes mosquitoes), and environmental conditions, including social, cultural, economic, and geographical factors [23].

Sistan and Baluchestan Province located in the Indo-Malayan zone shares a long land border with Afghanistan and Pakistan, which are endemic foci of DF, and outbreaks of the disease have been reported from these countries [20, 40, 41]. Population movements between Sistan and Baluchestan Province and these two infected countries facilitate disease transmission across borders, because viremic patients, as the main reservoir of the disease, enter this province legally and illegally. Consequently, outbreaks occur in high-risk areas, where invasive Aedes are present.

A modeling study in Iran indicated that Sistan and Baluchestan Province has favorable climatic condition for the presence of invasive Aedes mosquitoes, the main vectors of DF [42]. In 2016, Ae. albopictus was reported for the first time from Chabahar, Nikshar, and Sarbaz Counties, located in the southern part of this province. However, since this species was not caught in subsequent surveys, the evidence suggests that, Ae. albopictus entered the province but failed to establish itself; therefore, this species is currently absent in the study area [26, 43].

In recent years, following the establishment and geographical distribution of Ae. aegypti in southern areas of Iran, particularly in Hormozgan Province, the distribution range of this species has extended to the south eastern regions of the country, including Sistan and Baluchestan Province [25, 28, 44, 45]. The combination of these factors led to the first large-scale local transmission outbreak of DF in southeastern Iran. During this outbreak, 871 cases of the disease were reported of which, about 98% of the cases were from Chabahar County.

Despite the known role of temperature in accelerating the Aedes mosquito life cycle and the viral Extrinsic Incubation Period (EIP), our Spearman correlation analysis did not find a statistically significant positive association between mean temperature or relative humidity and local dengue incidence. Therefore, the role of imported cases is probably a more compelling mechanism for the epidemic pattern observed during October and November in the study area. Our data show an increase in the number of imported cases approximately two to three weeks prior to the main local peaks. This timing is highly suggestive of a direct seeding effect. Imported cases introduce a continuous source of viremic individuals into the community, which, if an Aedes vector population is present (regardless of optimal or suboptimal temperature), serves as the critical ignition point for local transmission. Therefore, the role of imported reservoirs in the increase of disease cases in the region is significant.

Dengue fever is usually more common in urban and semi-urban areas and due to the challenges related to house sanitation, environmental health and municipal services, the uncontrolled expansion of cities leads to increase in mosquitoes breeding habitats and subsequently disease outbreaks [40, 46–49]. In the present study about 95% of cases were reported from urban areas especially in populated regions that is similar to studies conducted in Pakistan, Bangladesh, India, Colombia, and Brazil that showed the higher incidence of disease in urban than rural areas so, urban areas with high population density, inadequate infrastructure, and poor sanitation facilitate Aedes breeding and therefore, environmental improvement, provision of piped drinking water to prevent water storage in containers, and improvement of sanitation infrastructure can play an important role in controlling the vector population and controlling dengue fever cases in such areas [36, 50–53].

Gender is another factor that can affect infection rates, influencing access to healthcare, susceptibility, clothing, health-seeking behavior, occupation, and exposure to vectors [36, 54]. During this outbreak, although ‘Housewives’ constituted the largest single occupational group (29.6%), indicating significant transmission within domestic and peri-domestic environments by Ae. aegypti, the combined percentage of self-employee and laborers (predominantly male) reached 36%. These aggregate data suggest that occupational and outdoor exposure remains the main driver of the higher infection rates observed in men. Consequently, vector control programs must prioritize both domestic spaces and outdoor/work environments. This finding is justified by the higher prevalence of the disease in men compared to women, which is consistent with the findings of many studies conducted in various Asian regions, including Pakistan, Afghanistan, India, and Bangladesh [36, 55–65]. However, contrasting results have also been reported in America, where the prevalence of disease in females was equal or higher than in men [66–68]. Possibly, the reason for this difference is the cultural, social, and behavioral differences between the inhabitants of these continents. In some parts of Asia especially Middle East women wear full covered clothes that protect them against mosquito bite and also, they are more restricted to houses than men and also health care seeking in women is lesser than men for religious and cultural reasons [36, 55, 69].

In addition to gender, age groups can influence the occupations of individuals. According to Min Du et al.; globally, the highest incidence of DF belongs to age group of 10-25 years [70]. In the present study, similar to studies conducted in Asia, the incidence of DF in active age groups that spend more time outdoors are more than the other groups [20, 53, 55, 71, 72].

Some of these active individuals travel to endemic areas for recreation or business, in infected, enter to non-endemic areas as disease reservoirs. In this study, about 6.8% of patients had a history of traveling to infected countries including Pakistan, Afghanistan, and the United Arab Emirates. Considering that Ae. aegypti often feeds on multiple hosts during each gonotrophic cycle therefore, disease outbreaks occur in the presence of the viremic reservoirs in high risk areas [73]. So, in the study area, imported cases of the disease played a significant role in the initiation and continuation of the recent outbreak.

However, DF is an emerging disease in Iran, and the first cases of local transmission on a very small scale, 12 people infected, were reported in 2024 from Hormozgan Province and controlled immediately [29]. Therefore, it seems that limited serotypes of dengue virus are circulating in Iran. Initial infection with a single dengue virus serotype (DENV) confers lifelong homologous immunity. However, subsequent exposure to a heterologous serotype can lead to an inefficient immune response, wherein pre-existing IgG antibodies, instead of neutralizing the virus, exacerbate the infection via the mechanism of antibody-dependent enhancement (ADE) [74]. This phenomenon is partially explained by original antigenic sin (OAS), where the antibody titers associated with the primary infection remain dominant in circulation, hindering an effective antibody response against the newly invading serotype [75–77].

Given these immunological foundations, the introduction of any new serotype (such as DENV-3 or DENV-4) into regions previously dominated only by DENV-1 and DENV-2 (like Iran) poses a significant risk of increased severe illness, hospitalization, and mortality. The recent experience in Nepal, where the introduction of the DENV-3 serotype resulted in the largest dengue outbreak in that Country strongly underscores the necessity for vigilance and preparedness in the health system against the co-circulation of multiple serotypes in Iran [78].

Studies have shown that the case fatality rate for secondary dengue infections with heterologous serotypes increases the risk of DHF, especially when the interval between the primary and secondary infection exceeds two years [79]. For example, during the first major outbreak of DF in Pakistan in 1994, serotype DENV₁ and DENV₂ were documented but subsequently DENV3 was introduced in 2005 and caused a sharp rise in DHF. A similar finding was observed in Afghanistan, with no deaths reported during the first outbreak in 2019, but two deaths were reported during subsequent waves of the disease in 2021 and 2023 [20, 40, 55]. As mentioned above, DF is an emerging disease in Iran, and limited serotypes of the virus exist in this country and so health care systems should pay special attention to future outbreaks with new DF cases, especially for individuals with a history of previous dengue infection, particularly if their initial diagnosis was more than two years prior. Therefore, it is expected that future outbreaks in the southeast of Iran will lead to a higher number of DHF cases. So, environmental improvement, especially establishing a daily garbage collection system and provision of piped drinking water in areas such as Sistan and Baluchestan, where a large number of people store water in containers, can have a significant impact on reducing the frequency of Ae. aegypti and preventing explosive outbreaks of the disease. Aadditionally, public health education about vector biology and ecology and its control methods, and also increased medical infrastructure for disease management seem is essential.

Clinical and laboratory data are crucial in disease diagnosis, monitoring and management [80]. In this study fever along with headache, body pain, and muscle pain were the most common symptoms of the disease which coincides with the studies conducted in Afghanistan, Bangladesh, and also Iran [29, 71, 72]. Similarly in Pakistan and Colombia, fever and headache were reported in most patients [55, 65, 81]. However, clinical symptoms vary in different forms of DF, and in mild forms, as seen in the recent outbreak, flu-like symptoms are usually seen [20].

Therefore, it may be challenging to distinguish mild types of DF from other diseases with similar presentation, so valid laboratory tests are essential for correct diagnosis and subsequently managements of the patients [82]. In this study PCR performed for 46.84% of patients and was positive in 93% of tested cases. Although, PCR test is the gold standard for detecting dengue virus in patient samples within the first days of symptom onset so it is not essential for all patients, NS1 can be diagnosed up to 10 days of infection but IgM and IgG is preferred after the first weeks of DF clinical signs. Therefore, serological tests were mostly used during this out break for patients diagnosis [82].

One of the limitations of this study was the non-participation of a large percentage of patients for hematology tests. This is due to anxiety about the outcome, social withdrawal, and social stigma. Subsequently, these factors can hinder patient management and disease control [83, 84]. This limited participation may have affected the representativeness of the laboratory findings and introduced potential bias into the analysis. Patients who consented to testing might differ clinically or demographically from those who did not, which could skew hematological or biochemical results. Future studies with a higher and more balanced inclusion of participants in laboratory assessments are recommended to minimize this bias and strengthen the validity of the findings.

However, in this study the most common abnormality hematological tests were low hematocrit (61.9%), platelet, and WBC (both between 42 and 44%).

According to Ojha et al., thrombocytopenia (low platelet count) and leukopenia (low WBC count) can be common clinical manifestations of mild forms of DF [85]. Coincide with the present study leukopenia was reported in patients from Bangladesh, Afghanistan, and Iran [29, 71, 72]. Thrombocytopenia was observed in many patients in Bangladesh, Pakistan, Saudi Arabia, Afghanistan, and Iran and it is may be due to bone marrow depression during DF [29, 71, 72, 86–89]. However given the substantially elevated prevalence of thalassemia in Iran’s southern provinces, particularly those bordering the Persian Gulf, which significantly exceeds global rates, it is hypothesized that the high background endemicity of this hematological disorder may serve as a contributing factor to the pronounced decreases in hematocrit observed among patients concurrently afflicted with dengue fever [90].

Many parts of Iran have suitable climatic conditions for the establishment of invasive Aedes and these mosquitoes have currently been reported from the northern and southern provinces of the country [91–93]. Chabahar County, as the most important oceanic port of Iran, is the place where a large amount of goods is unloaded and distributed throughout the country. In addition, due to its natural attractions, is one of the important tourist areas. Therefore, an outbreak of DF in Chabahar County, could lead to widespread outbreaks of the disease in the other areas. Therefore, to prevent the spread of DF in the country, it is necessary to attract the participation of relevant governmental and non-governmental organizations.

Iran’s largest ocean port is located in Sistan and Baluchestan Province. DF is now endemic in this region so, the present study aimed to investigate the demographic and clinical features of DF in this region. The results of this research can be effective for health care systems in diagnosing and controlling the disease. Given that vector control is one of the basic methods for controlling vector-borne diseases, it is recommended that studies be conducted on vector ecology in this new focus of DF.

Conclusion

The first large-scale local transmission outbreak in southeastern Iran occurred in 2024 in Chabahar County which is the most oceanic port of the country. According to the results, imported cases played an important role in increasing the incidence of local transmission of the disease.

During this outbreak, it was identified that males, active age groups, lack of access to piped water, and regular garbage collection system especially in densely populated urban areas, are key factors associated with the disease outbreak. The recent study is the first epidemiological study on local transmission of DF in Iran. Therefore, the results of this study can guide health systems in controlling this emerging disease in Iran.

Policy implications

To effectively enhance public health intervention efficacy, future operational strategies must converge on six critical pillars: To effectively enhance the efficacy of public health interventions, future operational strategies must converge on six critical pillars: Targeted Vector Control, using effective insecticides such as Malathion and deltamethrin in the infected foci of the disease; Rapid Household Reservoir Identification, necessitating an immediate screening protocol involving rapid sampling of all household members and close neighbors following any confirmed case to swiftly break transmission chains; Enhanced Symptomatic Surveillance for High-Risk Groups, by using symptoms of fever, headache, and myalgia (muscle pain) as an early warning index and mandating urgent screening for the hemorrhagic form; Dedicated Research into Severe Forms, strongly recommending that a case-control study be conducted to precisely identify the risk factors escalating severe dengue; Countering Social Stigma and Improving Diagnostic Compliance, through the formulation of a clear policy utilizing community engagement and educational programs to address85% refusal rate for testing reluctance reported due to social stigma; and finally, Data Monitoring, and Cross-Border Surveillance, which involves strengthening the surveillance system through the digitization of entomological data and establishing formal cross-border monitoring with neighboring countries such as Pakistan and Afghanistan to anticipate the arrival of new strains or potential disease waves.

Limitation

Due to insufficient financial resources, it was not possible to perform serotyping on all samples. With increased funding and a larger sample size, it is possible that results could indicate the presence of more than two serotypes. One of the main shortcomings of this study was that only one-quarter (25%) of the intended laboratories participated. This low participation rate likely resulted in the preferential sampling of sicker and more severely ill patients. Consequently, our findings regarding hematological abnormalities may overestimate the true prevalence (a phenomenon known as severity bias). Furthermore, to determine whether a patient was autochthonous (local to the area), we relied solely on the patient’s self-reported travel history. Since human memory can be fallible, this method makes the patient classification susceptible to recall bias and therefore compromises accuracy. Future studies with a higher and more balanced inclusion of participants in laboratory assessments are recommended to minimize this bias and strengthen the validity of the findings.

Abbreviations

RDT

Rapid diagnostic tests

ELISA

Enzyme-linked immunosorbent assay

NS1

Non-structural protein 1

CDC

Centers for Disease Control

DF

Dengue fever

DHF

Dengue hemorrhagic fever

DSS

Dengue shock syndrome

Ae

Aedes

RNA

Ribonucleic acid

WHO

World Health Organization

IgG

Immunoglobulin G

IgM

Immunoglobulin M

PCR

Polymerase chain reaction

WBC

White blood cell

Plt

Platelet

Hct

Hematocrit

epi week

Epidemiological week

SPSS

Statistical package for the social sciences

GIS

Geographic information system

Prec. (mm)

Precipitation (millimeters)

RH (%)

Relative humidity (percent)

Temp (°C)

Temperature (degrees Celsius)

Author contributions

Madineh Abbasi managed the project, wrote method and results, Mahasti Alizadeh, Fatemeh Nikpour and Ahmad Koosha conducted the original idea and rewrote the article. Ahmad Raeisi and Abdolreza Mirolyaie rewrote the article. Omid Dehghan, Faramarz Mobaraki, Ehsan Sheykh Noori supported field study, and article writing. Saideh Yousefi wrote two sections of the manuscript. All authors discussed the results and contributed to the final manuscript.

Funding

This study had no financial support.

Data availability

The surveillance dataset underlying this study cannot be shared publicly due to governmental restrictions. De‑identified data may be made available from the corresponding author upon reasonable request and with appropriate institutional approvals.

Declarations

Ethical approval

This study was conducted in accordance with the declaration of Helsinki. The protocol was reviewed and approved by the Ethics Committee of Tabriz University of Medical Sciences (Approval Code: IR.TBZMED.REC.1404.283). As this was a retrospective surveillance study using anonymized data provided by the Ministry of Health, the requirement for individual informed consent was formally waived by the Ethics Committee of Tabriz University of Medical Sciences, in accordance with national regulations for communicable disease surveillance.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.