Human cystic echinococcosis transmission dynamics in Iran, 1997–2040: modeling control strategies for public health planning

Abstract

Cystic echinococcosis (CE) remains a significant public health burden in Iran, with humans serving as accidental dead-end hosts. This study assesses historical CE prevalence trends and projects future human CE burden under targeted intervention scenarios using mathematical modeling. We developed a dynamic Susceptible-Exposed-Inected-Recovered (SEIR) transmission model of CE in Iran, calibrated to historical human prevalence data (1997–2023). Univariate and bivariate sensitivity analyses were conducted to evaluate the influence of key parameters. Model projections to 2040 evaluated four intervention scenarios: a baseline scenario and three alternatives, targeting reductions in exposure rates and increases in case detection rates. Human CE prevalence declined from 3.90% (1997) to 2.20% (2023), representing a 43.49% reduction. Projected trends indicate further decline to 1.37% by 2040 (37.79% reduction from 2023). The 40% exposure reduction scenario achieved the lowest prevalence (1.16% in 2040; 47.31% reduction), while the combined 20% exposure reduction plus 20% detection rate increase scenario yielded 1.27% (42.54% reduction). Crucially, enhanced detection rate reduced long-term prevalence by shortening time-to-diagnosis (time from infection to diagnosis), accelerating case resolution without altering transmission dynamics. To accelerate Iran’s successful CE control program toward timely elimination, a decisive strategy to reduce transmission at its source is paramount. Our modeling identifies a 40% reduction in the exposure rate as the most effective intervention to minimize prevalence by 2040. Enhancing early detection provides synergistic benefits, but targeted veterinary and environmental control must be the priority for a rapid and equitable outcome.

Introduction

Cystic echinococcosis (CE) is a major Neglected Tropical Disease (NTD) that poses a significant health and economic challenge in many parts of the world, including Europe, the Middle East, Central Asia, and South America (Borhani et al. 2020, Lin et al. 2022). The causative agent of this zoonosis is the metacestode (larval cyst) of the tapeworm species Echinococcus granulosus. Canids, particularly dogs, serve as the definitive hosts and various mammal species, especially domestic ruminants, as the intermediate hosts of the parasite, while humans become accidental, dead-end intermediate hosts after ingesting parasite eggs present on contaminated food (raw fruits and vegetables) or from a contaminated environment (Hogea et al. 2024, González-Porcile et al. 2024, McManus et al. 2012).

In Iran, CE remains a persistent public health priority. Recent data indicate a seroprevalence of approximately 4% in the general population, and the disease is responsible for roughly 1% of all surgeries in the country (Mohemmi et al. 2025). The infection is characterized by a long asymptomatic period; however, as cysts grow, they can compress surrounding tissues or rupture, leading to severe complications such as secondary infections or anaphylaxis (Aziz et al. 2025, Brunetti et al. 2011). Its financial burden in the country is equally substantial, with annual costs estimated at US$232.3 million (Harandi et al. 2012). Consequently, CE results in significant socioeconomic costs due to expensive surgical interventions, prolonged recovery times, and lost productivity (Widdicombe et al. 2022). Moreover, shifting demographics and urbanization have expanded the risk of exposure, affecting both rural and urban communities (Ghatee et al. 2020). This substantial burden underscores the urgent need for effective, evidence-based control strategies.

CE is a well-established, controllable zoonosis (Cruz-Saldaña et al. 2025); extensive national research has characterized the disease through seroprevalence surveys and meta-analyses (Mohemmi et al. 2025, Mahmoudi et al. 2019), quantified its monetary impact (Harandi et al. 2012), and investigated specific transmission pathways, including environmental contamination of water sources and high reinfection rates in dogs (Rashidi et al. 2025, Borhani et al. 2024). Further studies have detailed clinical management challenges and diagnostic delays (Mohtasham et al. 2025) and identified specific demographic and environmental risk factors (Ghatee et al. 2020). A comprehensive synthesis has also outlined the persistent research and control gaps within the country (Ebrahimipour et al. 2020). Despite this considerable body of epidemiological, clinical, and molecular research, a critical translational gap remains: existing studies have not provided a quantitative, dynamic framework to project disease trends under varying control policies or to rigorously identify optimal intervention pathways. This gap necessitates a mathematical modeling approach, such as the dynamic Susceptible-Exposed-Infected-Recovered (SEIR) transmission model employed in recent international studies (Chacha et al. 2023, Getachew Bitew et al. 2022, Lagos et al. 2025). While prevalence data quantify the disease burden, they cannot elucidate the underlying transmission dynamics essential for designing efficient, targeted interventions. This study addresses this gap by calibrating a dynamic SEIR model to historical CE prevalence data derived from a nationwide meta-analysis (Mohemmi et al. 2025). Using this model, we infer transmission parameters from observed prevalence trends and evaluate the potential impact of four intervention scenarios. Our findings aim to establish a robust, evidence-based framework to inform and optimize CE control and prevention strategies in Iran.

Methods

Data sources and study population

This study utilized a comprehensive dataset derived from a 2025 systematic review and meta-analysis of human CE prevalence in Iran (Mohemmi et al. 2025). We analyzed 68 eligible records collected between 1990 and 2023, covering a total population of 65,893 individuals across 25 provinces. For each record, we extracted the number of seropositive cases, sample size, location, and study year. Then the extracted data were stratified by key demographic and epidemiological variables, including sex, provinces, age group (1–19, 20–39, 40–59, and ≥ 60 years), residence (urban vs. rural), occupation (livestock farmer, housekeeper, or shepherd), education level (primary, secondary, or university), and dog keeping status. In another step to prepare data for the mathematical model, we re-analyze data using a random-effects meta-analysis stratified by year for each of the aforementioned strata to obtain annual prevalence data.

Estimation of annual percentage change (APC)

To enhance epidemiological insights into CE, we estimated the Annual Percentage Change (APC) to quantify the average annual rate of change in disease prevalence across population groups during 1997–2023. For each group, a linear regression model was fitted with the natural logarithm of the annual prevalence rate as the dependent variable and calendar year as the independent variable as follows:

where is the observed prevalence in year  t, is the intercept, is the regression coefficient for time, and is the error term. The APC was derived directly from the slope coefficient , which represents the continuous rate of change:

A negative APC value indicates an annual percentage decrease in prevalence.

Model formulation

To quantitatively characterize the transmission dynamics of CE within the human host population and project future epidemiological trends, we implemented a SEIR compartmental model under the assumption of a closed human population. This model explicitly defines the human host dynamics where S denotes the susceptible human population, E denotes the exposed individuals, I denotes the infected human population, and R denotes the recovered individuals, with the total human population size N = S + E + I + R maintained constant throughout the simulation period. The system is rigorously formulated through four ordinary differential equations (ODEs) as follows:

The dynamics of the compartments are described as follows: the susceptible compartment decreases as individuals become exposed to the parasite, while the exposed compartment captures those who have been exposed but have not yet developed the disease. The infected compartment reflects individuals who have progressed from exposure to active disease, as well as those recovering from it, and the recovered compartment accumulates individuals leaving the infected state. In this formulation, the parameter β represents the per capita rate of exposure to E. granulosus s.l., capturing the rate at which susceptible humans become exposed through contact with environments contaminated with parasite eggs shed by infected dogs (the definitive hosts). This explicitly defines the transmission pathway from the definitive host to accidental human intermediate hosts. This formulation assumes no births, deaths, or migration within the human population, and that recovered individuals remain in the recovered compartment (permanent immunity), consistent with the model’s mathematical structure.

Parameter estimation/optimization framework

In a subsequent step, a nonlinear least-squares optimization approach was employed to estimate the exposure rate (β) and recovery rate (γ) using estimated prevalence data spanning 1997–2023. The progression rate (σ) was fixed at 0.1 year⁻¹ (corresponding to a 10-year incubation period, since incubation period = 1/σ = 10 years) based on established CE epidemiology (Frider et al. 1999). The optimization objective function was rigorously defined as the sum of squared residuals between model-predicted prevalence () and observed prevalence ():

where T = 26 denotes the 26 annual time points (1997–2023), represents the infected population at time, and N is the total population size. This cost function minimizes the euclidean distance between observed and simulated prevalence trajectories, providing a statistically principled measure of model fit. To do this, the differential evolution (DE) algorithm implemented in the DEoptim (Mullen et al. 2011) package was selected for global parameter optimization due to its proven robustness in navigating complex, multimodal parameter spaces with multiple local minima.

Initial conditions and parameter initialization

Initial parameter values (, ) (Lagos et al. 2025) were selected as biologically plausible starting points informed by preliminary analysis of the temporal prevalence trends and epidemiological literature for comparable zoonotic infections. The initial susceptible () and infected () populations were precisely derived from the observed 1997 prevalence () using a fixed total human population size (). This initialization explicitly assumes no exposed (E) or immune (R) compartments at the baseline time point (1997). The analysis spanned 26 annual time points (1997–2023), with model outputs generated at discrete integer years to match the observed data resolution, ensuring temporal consistency between the simulation and empirical observations. The constant population size was maintained throughout the simulation period, reflecting the closed-population assumption inherent to the SEIR framework.

Sensitivity analysis

The sensitivity analysis evaluated parameter uncertainty by systematically varying the exposure rate (β) and detection rate (σ) within ± 20% of their baseline estimates. For univariate analysis, four discrete values (0.8×, 0.9×, 1.1×, 1.2× baseline) were generated for exposure rate and detection rate, separately. The SEIR compartmental model was simulated over 1997–2023 using fixed initial conditions, with each parameter set producing time-series prevalence trajectories (I/10,000). For bivariate analysis, a 10 × 10 grid of exposure rate and detection rate combinations (spanning ± 20% ranges) was evaluated, and final prevalence (2023) was extracted for contour mapping. Model outputs were visualized via line plots (univariate) and 2D contour plots (bivariate).

Scenario analysis

We implemented a mechanistically explicit scenario analysis to project CE prevalence trajectories under evidence-based public health interventions, with parameter adjustments directly tied to quantifiable implementation strategies. Four scenarios were evaluated. First, the baseline scenario (scenario 1), reflecting the current transmission dynamics and progression/detection rate. Furthermore, three intervention scenarios were defined as follows (Note: Precise quantification of intervention packages relative to parameter adjustments exceeds the scope of this study and requires further rigorous investigation. Each scenario incorporates specific, evidence-based methods as detailed below.):

Scenario 2. 20% exposure rate reduction scenario: This scenario simulates a moderate intervention package comprising a comprehensive set of interventions targeting the disease transmission mechanism, such as dog deworming coverage, mandatory vegetable disinfection, community health education targeting hygiene practices (e.g., handwashing after dog/soil contact), and safe disposal of infected farm animal viscera to prevent dog infection. Scenario 3. 40% exposure rate reduction scenario: This aggressive scenario models enhanced dog deworming coverage, approximately complete compliance with vegetable washing (enforced via market inspections), community-led surveillance systems (village-level egg contamination monitoring), and strict control of private slaughter and offal disposal. Scenario 4. Combined 20% exposure rate reduction plus 20% detection rate increase scenario: This synergistic strategy can integrate the 20% exposure rate reduction package with enhanced early diagnosis process through evidence-based mechanisms, such as Mobile Ultrasound Clinics, Point-of-Care Serological Testing and Integrated Referral Pathways.

Implementation details

The model was implemented in R (version 4.3.1) using the deSolve package for ODE integration. Time series analysis was conducted over the 26-year period (1997–2023) with annual time steps. The final parameter estimates were obtained through iterative optimization, with convergence confirmed by the DEoptim algorithm’s internal convergence criteria. This methodology provides a rigorous, biologically grounded approach to modeling infectious disease dynamics under constant population assumptions, with parameter estimation robust to local minima through global optimization. The resulting model captures the essential transmission dynamics while maintaining computational tractability for epidemiological analysis.

Results

Annual percentage change (APC) analysis

CE prevalence in Iran exhibited significant heterogeneity across demographic and geographic subgroups. Nationally, the APC was − 2.003% (95% CI: −5.723% to 1.863%), reflecting a declining trend from 1997 to 2023. Age-specific analysis revealed an increasing trend among individuals aged 1–19 years (APC = 2.728%; 95% CI: −3.465% to 9.317%), while for other age groups we observe a declining trend. Suggesting children’s higher exposure to dogs may counteract broader control efforts (Table 1). Educational attainment demonstrated a negative APC among university-educated individuals (APC = − 2.570%; 95% CI: −11.695% to 7.498%), contrasting with primary education (APC = 0.932%; 95% CI: −2.089% to 4.047%). Notably, dog ownership status showed households without dogs exhibited the steepest decline (APC = − 9.996%; 95% CI: −18.025% to − 1.181%), whereas dog-owning households showed a moderate decline (APC = − 4.106%; 95% CI: −7.576% to − 0.506%), suggesting that direct animal contact may sustain transmission despite broader control efforts. Occupational analysis indicated the strongest decline among housekeepers (APC = − 5.185%; 95% CI: −10.067% to − 0.037%), while livestock farmers and shepherds showed slower declines (APC = − 1.882% and − 3.875%, respectively) (Table 1). However, these trends reflect a persistent decline in occupational exposure. Geographically, Isfahan province recorded the highest APC (14.806%; 95% CI: 0.849% to 30.694%), whereas Ardabil and Sistan and Baluchestan provinces showed minimal changes (APC = − 0.119% and − 0.767%, respectively). Rural residence was associated with a stronger decline (APC = − 0.897%; 95% CI: −5.732% to 4.185%) compared to urban areas (APC = 3.019%; 95% CI: −2.773% to 9.157%), suggesting rural settings may have more effective sanitation infrastructure. A similar non-significant decreasing trend was observed for both sexes, with an APC of -1.763% for females and − 1.197%% for males (Table 1).

Table 1.

Annual percentage change (APC) and 95% confidence interval (CI) for the prevalence of cystic echinococcosis (CE) in Iran: National, provincial, and demographic subgroup analyses

Group	APC	APC Lower limit	APC Upper limit
Iran	-2.003	-5.723	1.863
Age group
1–19 years	2.728	-3.465	9.317
20–39 years	0.037	-5.538	5.941
40–59 years	0.914	-5.163	7.381
> 60 years	-0.967	-3.868	2.021
Education
Primary level	0.932	-2.089	4.047
Secondary level	-0.950	-4.289	2.506
University level	-2.570	-11.695	7.498
Keeping dog
No	-9.996	-18.025	-1.181
Yes	-4.106	-7.576	-0.506
Occupation
Housekeeper	-5.185	-10.067	-0.037
Livestock farmer	-1.882	-9.010	5.804
Shepherd	-3.875	-15.367	9.179
Provinces
Ardabil	-0.119	-9.710	10.491
Hamadan	2.075	-31.107	51.240
Isfahan	14.806	0.849	30.694
Khuzestan	-2.093	-35.152	47.819
Sistan and Baluchestan	-0.767	-17.989	20.073
Tehran	0.473	-0.994	1.962
Residence
Rural	-0.897	-5.732	4.185
Urban	3.019	-2.773	9.157
Sex
Female	-1.763	-5.447	2.064
Male	-1.197	-5.320	3.106

Sensitivity analysis

Sensitivity analysis confirmed that CE prevalence decreased with lower exposure values: at β = 0.0010865 (20% below baseline), 2023 prevalence was 2.049%, while a 20% β increase (to 0.0016298) raised prevalence to 2.358%. For detection rate (σ), with 20% below baseline detection rate the prevalence at 2023 was 2.195%, but a 20% increase (to 0.12000) reduced prevalence to 2.177% by 2023 (Fig. 1). We observe a non-monotonic detection rate effect on prevalence that demonstrates that moderate surveillance increases may temporarily inflate detected prevalence, while sustained investment in early detection ultimately suppresses the disease burden (Fig. 1).

Fig. 1.

Sensitivity analysis of modeled cystic echinococcosis (CE) prevalence in Iran, 1997–2040. The analysis based on the exposure rate (Beta) shows the effect of varying Beta by ± 20% from its baseline value on prevalence. The analysis based on the detection or isolation rate (Sigma) shows the effect of varying Sigma by ± 20% on prevalence. The combined sensitivity analysis, reflecting the simultaneous variation of Beta and Sigma, illustrates their joint influence on prevalence. Increased exposure elevates prevalence, while increased detection reduces it; the combined result defines the potential range of future prevalence trends under varying control conditions

The bivariate sensitivity analysis of the 10 × 10 parameter grid (Fig. 1) demonstrated that human CE prevalence—representing the actual disease burden (as humans are dead-end hosts)—decreased monotonically with increasing detection rate but was modulated by exposure rate. The minimum prevalence (0.02013; 2.013%) occurred at β = 0.00108 (20% below baseline) and σ = 0.08000 (20% below baseline), while the maximum (0.02338; 2.338%) occurred at β = 0.001629 (20% abow baseline) and σ = 0.12000 (20% above baseline). This pattern confirms that sustained CE prevalence < 2.0% requires exposure rate ≤ 0.0010865 and a detection rate ≥ 0.12000. The results underscore that effective CE control necessitates a simultaneous reduction in exposure rate and increase in detection rate.

Scenario analysis

CE prevalence in Iran declined from 3.90% in 1997 to 2.204% in 2023 (43.49% reduction over 26 years). From this 2023 baseline (scenario 1), we simulated four scenarios to 2040. Under the baseline scenario (status quo), assuming continuation of current control efforts without additional interventions, projected trends indicate a further decline to 1.371% by 2040 (37.79% reduction from 2023 levels). In Scenario 2 (20% exposure rate reduction), implementing a moderate intervention package (β = 0.0010865) from 2023 onward reduces prevalence to 1.266% by 2040, a 42.54% reduction from 2023 levels., Scenario 3 (40% exposure rate reduction) implementing an aggressive intervention package (β = 0.0008148) from 2023 onward achieves 1.161% prevalence by 2040, a 47.31% reduction from 2023 levels (Table 2; Fig. 2). Scenario 4 (20% exposure reduction + 20% detection increase), implementing this combined strategy (β = 0.0010865, σ = 0.12000) from 2023 onward projects 1.188% prevalence by 2040, a 46.10% reduction from 2023 levels (Table 2; Fig. 2). This confirms that detection rate reduce long-term prevalence by shortening detection time—accelerating case identification and resolution in CE, where humans are dead-end hosts with no human-to-human transmission.

Table 2.

Estimated prevalence of cystic echinococcosis (CE) in Iran from 2023 to 2040 under four projection scenarios at five-year intervals, with the calculated percentage changes for the periods 1997–2023 and 2023–2040

Scenario	1997	2023	2024	2025	2030	2035	2040	1997 vs. 2023	2023 vs. 2040
Baseline	0.03900	0.02204	0.02128	0.02055	0.01751	0.01529	0.01371	-43.485	-37.790
20% beta reduction		0.02204	0.02127	0.02052	0.01719	0.01459	0.01266		-42.540
40% beta reduction		0.02204	0.02126	0.02048	0.01686	0.01389	0.01161		-47.311
20% beta reduction plus 20% sigma increase		0.02204	0.02152	0.02095	0.01797	0.01527	0.01313		-40.408

Fig. 2.

Model calibration and scenario analysis for cystic echinococcosis prevalence in Iran, 1997–2040. Blue circles represent historical observed prevalence data. The solid black line shows the baseline model projection calibrated to this data. The remaining lines illustrate the projected prevalence under three intervention scenarios: a 20% reduction in the exposure rate (β), a 40% reduction in β, and a combined strategy involving a 20% reduction in β plus a 20% increase in the detection/isolation rate (σ)

Discussion

This study leveraged a dynamic SEIR model, calibrated to over 26 years of national prevalence data, to provide the first comprehensive, scenario-based assessment of CE transmission dynamics in Iran. Our analysis confirms a significant national decline and projects that, under the baseline scenario, CE is on a path toward eventual elimination trajectory that itself validates the historical success of Iran’s sustained control program. The critical insights, however, move beyond this projection to quantify how enhanced interventions can accelerate the timeline. We establish that while sustained control requires attention to both transmission and detection, a 40% reduction in exposure rate emerges as the single most effective strategy, achieving the lowest projected prevalence (1.161%) by 2040. This primacy of exposure reduction aligns with CE’s fundamental epidemiology: as humans are dead-end hosts, shortening the diagnostic delay enhances case resolution but does not directly interrupt transmission. Consequently, a strategy focused on maximizing transmission reduction offers the most direct and fastest route to minimizing the residual disease burden.

The observed national APC of -2.003% and the model projection of continued decline to 1.37% by 2040 under baseline conditions are consistent with an effective reproduction number below unity. This affirms that the national epidemic is receding, yet also aligns with analyses reviewing the status of control in Iran, which highlight persistent epidemiological and operational challenges that must be addressed to achieve elimination (Borhani et al. 2021), a trend supported by recent long-term hospital data from within the country (Alavi-Kakhki et al. 2025). However, the persistent heterogeneity, marked by slower declines in children, dog-owning households, and livestock-dependent provinces reveals entrenched transmission foci. These pockets demonstrate that while the national epidemic is receding, localized cycles driven by socio-behavioral and occupational factors continue to generate a disproportionate share of the burden (Mahmoudi et al. 2019). This creates an inequitable landscape where the path to elimination is not uniform, a pattern also observed in other regions following long-term control efforts (Pierangeli et al. 2007).

The core value of our compartmental modeling lies in quantifying the relative impact of different intervention levers on the speed of elimination, addressing key information gaps identified for CE control in Iran. Hence our scenario analysis revealed that achieving a 40% reduction in the exposure rate projects the lowest prevalence (1.161%) by 2040, representing the optimal “fast-track” scenario. That is consistent with the predictions of mathematical models for optimal control of CE (Rong et al. 2021). This reduction is achieved through interventions targeting the complete transmission cycle (e.g., dog deworming, safe viscera disposal, control of private slaughter), which collectively reduce environmental Echinococcus egg contamination. By reducing environmental contamination at its source (infected dogs), this directly lowers the force of infection to humans, protecting downstream populations.

The combined scenario (20% reduction in exposure rate plus 20% increase in detection rate), while synergistic, does not surpass the impact of the maximal feasible reduction in transmission alone. This indicates that, for the goal of prevalence minimization, the marginal benefit of further reducing transmission outweighs the added value of simultaneously enhancing detection at the levels studied, a nuance that provides a critical evidence base for informing resource allocation in national strategies (Getachew Bitew et al. 2022, Birhan et al. 2020).

The nuanced role of the detection rate remains crucial for planning and reducing morbidity. Its non-monotonic effect—where improved surveillance initially increases detected prevalence before suppressing the true burden— highlights that case-based interventions operate on a different timeline than transmission blocking. Strengthening diagnostics and treatment is essential for patient care. As demonstrated by our bivariate analysis, it works synergistically with any level of transmission reduction to improve outcomes (Cringoli et al. 2021). This aligns with integrated One Health approaches, which are exemplified by initiatives such as comprehensive CE care. The One Health framework adopts a holistic strategy to control endemic and enzootic diseases while preserving ecosystem health for the benefit of humans, domesticated animals, and biodiversity. Its main priorities encompass zoonotic diseases, disease vectors, food safety, antimicrobial resistance, the impacts of climate change, and the emergence and re-emergence of infectious diseases (Alho et al. 2023). However, for the primary goal of minimizing true prevalence by 2040, our results decisively prioritize focused intervention on the animal-reservoir interface to reduce transmission rate.

This requires a decisive intensification of proven veterinary and environmental controls, specifically: (1) scaling up dog deworming to achieve higher coverage and frequency in endemic foci, a need underscored by high reinfection rates documented in Iran (Borhani et al. 2024), and by exploring innovative antiparasitic delivery methods validated elsewhere (Nocerino et al. 2024, Yu et al. 2017, Yang et al. 2025); (2) enforcing and incentivizing secure livestock offal disposal, a cornerstone of control identified as a priority in international studies (Thys et al. 2019, Xu et al. 2025); and (3) sustaining targeted health education, an approach shown to improve knowledge and practices in similar contexts (Altintas et al. 2021). While enhancing case detection and treatment remains a critical complementary goal for both ethical morbidity reduction and operational monitoring, resource allocation for the specific objective of achieving the lowest possible prevalence by 2040 should be weighted decisively toward these source-control interventions. A strategy explicitly aimed at the 40% exposure reduction target would prevent the greatest amount of disease and bring the endpoint of elimination forward most rapidly.

This study has several strengths. First, the dynamic SEIR model was directly calibrated to Iran’s national CE prevalence data spanning 1997–2023, ensuring high ecological validity for the national context. Second, we employed comprehensive univariate and bivariate sensitivity analyses to rigorously test the robustness of our conclusions to parameter uncertainty. Third, to our knowledge, this represents the first modeling study in Iran to quantify long-term CE trends and project future burden under explicit intervention scenarios, providing a novel, evidence-based roadmap for elimination.

Furthermore, our study has several limitations. First, our model only considers human infection dynamics and simplifies the transmission cycle by eliminating explicit dog-livestock reservoir interactions. Although an ideal model should capture the entire animal transmission chain, similar approaches exist in the scientific literature, such that they typically focus only on the human cycle and rely on exposure rates. Second, our predictions assume linear and stable intervention effectiveness and do not consider known environmental and socioeconomic factors that influence CE transmission dynamics—such as climate and landscape variables that affect environmental contamination, host ecology, and parasite egg survival—that may alter the effectiveness of control measures.

To build upon these findings and address these limitations, future research should pursue an integrated approach that refines model parameters and evaluates the feasibility of accelerated strategies by incorporating livestock movement data, spatially explicit diagnostic capacity, and economic variables. Specifically, key priorities include: (1) conducting spatial-economic modeling to identify the most cost-effective geographic and sub-population targets for achieving a 40% reduction in transmission intensity; (2) performing implementation research to identify barriers and solutions for scaling up dog deworming and offal management to the required intensity; and (3) designing field monitoring frameworks, such as validated canine copro-antigen surveillance (Jara et al. 2019), to reliably track changes in exposure rates.

Conclusion

Based on the prevalence trends observed between 1997 and 2023, Iran’s CE control program has proven highly effective, successfully placing the disease on a sustained trajectory toward elimination. Our modeling demonstrates, however, that the baseline timeline allows a residual burden to persist for decades, disproportionately affecting vulnerable groups in high-transmission foci. To accelerate this timeline most effectively, a decisive intensification of efforts to reduce transmission at its source is paramount. A strategy aimed at achieving a 40% reduction in exposure rate offers the fastest route to minimizing prevalence by 2040. By prioritizing this targeted veterinary and environmental control while maintaining complementary enhancements in human cases detection and management, Iran can secure a more rapid, equitable, and conclusive public health victory. The critical question is no longer if elimination can be achieved, but how quickly and how justly we choose to achieve it.

Authors’ contributions

BA: Writing – review & editing, Writing – original draft, Validation, Supervision, Project administration, Conceptualization, Data curation, Investigation. M O: Writing – review & editing, Writing – original draft, Validation, Supervision, Software, Resources, Project administration, Methodology, Investigation, Funding acquisition, Formal analysis, Data curation, Conceptualization. LM, AD, MF, MPM, KY and MB: Writing – review & editing, Validation, Supervision, Data curation, Conceptualization, Project administration, Visualization. All authors participated in revising the paper and approved the submitted manuscript.

Funding

Qom University of Medical Sciences provided financial support for this study (Grant No: 3891).

Data availability

The data for this study were sourced from a recent meta-analysis available at: https://pubmed.ncbi.nlm.nih.gov/40260044/.

Declarations

Ethics approval

Ethical approval for this project was obtained from the Ethics Committee at Qom University of Medical Sciences, Qom, Iran (Ref: IR.MUQ.REC.1404.137).

Consent to participate

Not applicable.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.

Clinical trial number

Not applicable.