Figures
Abstract
Background
Aedes-borne diseases pose escalating public health challenges globally, influenced not only by ecological and biological factors but critically by social determinants of health (SDH). In Iran, emerging local transmission of dengue highlights these diseases as effective proxies to examine the impact of social and environmental factors on health equity. However, evidence on context-specific drivers and effective responses remains scarce. This study aimed to identify key SDH and propose prioritized interventions to inform evidence-based policymaking.
Methods
This mixed-method study included a two scoping review on SDH of Aedes-Borne Diseases and SDH-focused interventions, complemented by qualitative data from in-depth interviews with 21 national and provincial health experts in Iran. Data were analyzed using an inductive content analysis approach and MAXQDA 25 software was used throughout the analysis. The identified interventions were prioritized through a multi-criteria decision analysis, incorporating expert input via an online checklist and digital platform, based on four key criteria: effectiveness, feasibility, social acceptability, and political support.
Results
Findings reveal that socioeconomic inequalities, weak community awareness, and limited health system capacity substantially drive disease risk. Notably, the local emergence and spread of dengue serve as a sensitive indicator reflecting broader social vulnerabilities affecting health outcomes. Integrated multisectoral strategies—encompassing health education, environmental management, digital surveillance, and cross-sector collaboration—are vital for effective control. Priority actions include healthcare worker training, embedding disease prevention within educational curricula, and tailored communication leveraging native languages and trusted community leaders.
Conclusion
The study underscores that Aedes-borne diseases are not only biological threats but also reflections of underlying social and structural inequities. By framing dengue and related diseases as sentinel indicators of SDH, policymakers can better design integrated and equity-oriented strategies. Controlling Aedes-borne diseases requires a shift from disease-centric approaches toward comprehensive, SDH-informed strategies that strengthen community engagement, improve environmental and health infrastructure, and enhance cross-sector coordination. The prioritized interventions identified in this study provide a practical roadmap for strengthening preparedness and response in Iran and similar settings.
Author summary
Aedes mosquitoes, which can spread dengue and other viral infections, are now appearing in several provinces of Iran. We wanted to understand how social and economic conditions, local environments, and the health system together shape the risk of these diseases and the success of control efforts. To do this, we reviewed international evidence and spoke with national and provincial health experts across affected regions in Iran. We then used a structured ranking process to identify which social factors and policy actions should be prioritized. Our findings show that poverty, poor housing and water management, limited public awareness, and gaps in health services all increase the risk of Aedes borne diseases. We also highlight practical, high priority actions, e.g., training health workers, integrating mosquito borne disease prevention into school curricula, and using local languages and trusted community leaders for communication. These results can help health authorities design fairer and more effective strategies to prevent future outbreaks in Iran and similar settings.
Citation: Mohamadi E, Jafarzadeh J, Mohamadi F, Mostafavi H, Bakhtiari A, Moradi G, et al. (2025) Understanding the social determinants of Aedes-borne diseases in Iran: A qualitative exploration of challenges and policy solutions. PLoS Negl Trop Dis 19(12): e0013850. https://doi.org/10.1371/journal.pntd.0013850
Editor: Anna Giné-March, Anesvad Foundation, SPAIN
Received: October 1, 2025; Accepted: December 10, 2025; Published: December 22, 2025
Copyright: © 2025 Mohamadi et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: All datasets used and analyzed in this study are included in the accompanying supplementary materials.
Funding: The author(s) received no specific funding for this work.
Competing interests: The authors have declared that no competing interests exist.
Introduction
Aedes-borne diseases, i.e., dengue, chikungunya, and Zika have emerged as growing public health threats, particularly in tropical and subtropical regions [1]. Their rapid spread is driven by climate change, urbanization, global travel and trade, and broader social and economic factors [2,3]. According to the World Health Organization (WHO), by 2024, over 90 countries were affected by these diseases, with more than 7.6 million dengue cases and 3,000 related deaths reported, a significant increase compared to previous years [4,5]. The highest burdens have been observed in South American nations and Pacific island countries [5,6]. Data from the European Medicines Agency in the same year estimate a global case count of 13 million, with 8,500 deaths, most notably 11 million cases and 6,000 deaths reported from the PAHO region. Brazil alone accounted for over 9.5 million infections in 2024, followed by Argentina, Mexico, Paraguay, and Colombia [7]. These trends have been attributed to climate shifts, viral evolution, prolonged warm seasons, weaknesses in health systems, and increasing human and goods mobility.
A growing body of evidence indicates that Aedes-borne diseases are significantly influenced by social determinants of health (SDH). These include economic status, access to healthcare services, educational attainment, and overall living conditions [8–10]. Low health literacy, inadequate public education, and limited awareness about mosquito bite prevention and disease control measures are associated with increased vulnerability to Aedes-borne infections [11–14]. Populations living in areas with poor sanitation infrastructure,i.e., lack of access to safe drinking water and adequate hygiene facilities, are at heightened risk [15–17]. Furthermore, stagnant water, which serves as an ideal breeding ground for Aedes mosquitoes, is more frequently found in low-income and underserved communities [18–20].
In Iran, Aedes-borne diseases have been reported in at least nine provinces to date, with the majority of confirmed cases concentrated in the southern and southeastern regions, particularly in Sistan and Baluchestan, Hormozgan, and Kerman, mainly within urban and peri-urban setting [21]. Although current reports indicate a limited number of cases, early evidence suggests that these diseases hold significant potential for expansion across southern provinces. Factors, i.e., climate suitability, proximity to international transmission hotspots, and inadequate health and environmental infrastructure place these areas at heightened risk. Despite this growing concern, there remains a lack of comprehensive research in Iran exploring the social determinants that influence the prevention, control, and spread of Aedes-borne diseases.
Given the complex interplay of social determinants and the diverse contextual drivers of Aedes-borne diseases across regions [22–24], current evidence strongly highlights the need for comprehensive, multisectoral approaches to improve understanding and inform effective control strategies. In Iran, the rising number of reported cases in southern provinces, coupled with limited localized data, underscores a critical need to contextualize global insights and adapt successful international interventions to local conditions. This study addresses the significant knowledge gaps regarding how social determinants shape the transmission and control of Aedes-related diseases across different Iranian regions.
This study aims to identify the key social determinants affecting the prevention, control, and spread of Aedes-borne diseases in Iran and to develop context-specific, evidence-based policy recommendations. It synthesizes global and national findings, prioritizes effective SDH-focused interventions based on impact and feasibility, and assesses the infrastructure needed for successful, multisectoral implementation. This research is guided by the underlying theoretical framework that variations in social determinants, i.e., economic, environmental, and health system factors, significantly influence the risk and control feasibility of Aedes-borne diseases in Iran. This implicit hypothesis informed the design, analysis, and interpretation of our findings.
Method
Ethics statement
This study involved human participants. The qualitative component included in-depth interviews, for which Written informed consent was obtained from all participants prior to their participation in the study. Participants also provided consent for the publication of their interview content in a fully anonymized form, with all personally identifying information removed. Confidentiality was strictly maintained, and participants reviewed and confirmed their interview transcripts. The study protocol was approved by the Ethics Committee of Tehran University of Medical Sciences (Approval Code: IR.TUMS.SPH.REC.1403.255).
This study is a mixed-methods applied research project in the field of health systems, designed and implemented in three sequential phases (Fig 1).
Phase I: Scoping review to identify social determinants of health and related interventions
Study design.
The first phase of this research was conducted using a scoping review methodology, following the framework proposed by Arksey and O’Malley [25]. This phase aimed to identify key social determinants influencing the spread, prevention, and control of Aedes-borne diseases (including dengue, chikungunya, and Zika), as well as relevant interventions applied globally. To address the objectives, two distinct scoping reviews were conducted, each guided by a specific research question:
- What are the key social determinants of health SDH associated with the transmission, prevention, and control of Aedes-borne diseases (dengue, chikungunya, and Zika)?
- What types of socioeconomically-driven interventions have been implemented to control Aedes-borne diseases and their vectors?
Data sources and search strategy.
The literature search was conducted across three major electronic databases; PubMed, Cochrane Library, and Scopus. In addition, the websites of key international organizations, i.e., the WHO were reviewed to retrieve relevant guidelines. Search terms were developed using controlled vocabulary (e.g., MeSH terms) and keyword combinations related to SDH, vector-borne diseases, and intervention strategies (Table 1).
Inclusion criteria.
Studies were included if they met the following criteria: (1) published in English; (2) explicitly focused on the role of SDHs in the transmission, prevention, and control of Aedes-borne diseases; (3) addressed the design or implementation of policy and programmatic interventions based on SDH; (4) published between 2005 and December 30, 2024; (5) had full-text availability; and (6) included various study types, i.e., primary research, reviews, and guidelines.
Exclusion Criteria: Studies were excluded if they (1) were not written in English; (2) were letters to the editor or commentary pieces; (3) did not provide access to the full text; or (4) referred to interventions or their impacts in an unclear or non-transparent manner during the screening process.
Screening Process of Studies: The literature screening process was conducted in accordance with PRISMA guidelines [26]. A comprehensive search was performed in databases, i.e., PubMed, Scopus, and Web of Science using keywords related to Aedes-borne diseases and social determinants of health. After removing duplicates, titles and abstracts were independently screened by two reviewers based on predefined inclusion and exclusion criteria. Full-text articles were then assessed, and any disagreements were resolved through discussion or consultation with a third reviewer. The entire process was documented using a PRISMA flow diagram. During this stage, EndNote software was used to organize and manage the references.
Phase II: Identification of social determinants of health (qualitative study)
Study design.
The qualitative component of this study was specifically designed to capture the perspectives of national and provincial health policymakers, managers, and technical experts. The aim was to explore the key SDHs influencing the transmission, prevention, and control of Aedes-borne diseases in Iran from the standpoint of those responsible for decision-making, program implementation, and policy development at systemic levels.
Participants.
Participants were selected through purposive sampling and included 21 key informants and experts. These comprised national-level policymakers from the Ministry of Health and Medical Education (MOHME), operational managers and field specialists from medical universities in affected provinces, and academic professionals. The range of expertise spanned public health specialists, i.e., epidemiologists, disease control officers, and environmental health experts, i.e., as well as entomologists, social psychologists, sociologists (focused on behavioral and cultural aspects of disease prevention), infectious disease specialists, family physicians directly involved in patient care, and researchers engaged in SDH-focused work across provinces.
Data collection tool.
Data were collected through semi-structured qualitative interviews guided by an interview protocol developed after the completion of Phase I. This guide was designed to ensure comprehensive coverage of the study’s core questions. To develop the interview framework, the research team first reviewed the study objectives and the key themes and indicators identified during the scoping review. A draft version of the interview guide was then created and refined based on input from academic advisors affiliated with the project (S1 Appendix). The finalized guide was used in all interviews to facilitate consistency and thematic depth.
Data collection.
Data were collected through semi-structured interviews. Given the geographic distribution of participants, interviews were conducted both in person and virtually. Prior to each interview, participants were contacted to provide a general overview of the research team, the study objectives, and the expected contribution of the participant. Following this, interviews were scheduled based on the participant’s preferred time and format. At the beginning of each session, the study’s goals were reiterated, and verbal consent for recording was obtained. After each interview, transcripts were prepared verbatim and shared with participants for verification and approval before inclusion in the analysis. The semi-structured format allowed participants ample space to express their perspectives freely. All interviews were audio-recorded, and supplementary notes were taken during each session. We conducted 12 individual in depth interviews and two focus group discussions comprising health managers, disease control specialists, and representatives from provincial health departments. The overall sample size (n = 21) was determined through purposive sampling and finalized at thematic saturation, whereby no new themes emerged from additional interviews or group discussions. Focus group composition allowed for interactive exchange of perspectives among experienced professionals, complementing individual interview insights”.
Data analysis.
Data were analyzed using an inductive content analysis approach, following the conventional content analysis method as proposed by Graneheim and Lundman [27]. Transcription and preliminary coding began immediately after each interview was completed and approved by the interviewee. To immerse in the data, transcripts were read multiple times, and meaning units—words, phrases, or paragraphs relevant to the study topic—were identified. These units were then condensed and labeled with appropriate codes. As coding progressed, similar codes were grouped into subcategories through constant comparison. These subcategories were further reviewed, compared conceptually, and organized into broader main categories. The coding and categorization processes were iterative and conducted by three members of the research team to ensure accuracy and analytical depth. To manage and organize the coding process, MAXQDA 25 software was used throughout the analysis. Themes were identified through systematic comparison and reflection on the categories, ensuring conceptual coherence and robustness of the final findings.
Phase III: Contextualization and prioritization of SDH-based interventions
Study design.
This phase adopted a mixed-methods design grounded in participatory policy analysis and guided by a multi-criteria decision analysis (MCDA) approach [28,29]. The objective was to contextualize and prioritize SDH-oriented policy interventions for the prevention and control of Aedes-borne diseases, aligned with the national and provincial contexts of the affected regions.
Participants.
A total of 9 experts were engaged, including entomologists, public health officials, epidemiologists, community representatives, Non-Governmental Organization (NGO) delegates, and health professionals from relevant institutions, i.e., MOHME, provincial municipalities, universities, and provincial health departments.
Data collection.
Interventions identified through the systematic review and expert interviews in earlier phases were consolidated and categorized. These interventions were then evaluated using four criteria: effectiveness, feasibility of implementation, social acceptability, and political support. To collect expert opinions, an online checklist was developed and distributed via a digital platform (S2 Appendix and S1 File). Experts were asked to assess each proposed intervention against the four criteria and assign weighted scores (from 1 to 10) based on the perceived importance of each dimension.
Data analysis.
The data collected in this phase were analyzed using a two-step quantitative approach to prioritize the SDH-based interventions. First, the Shannon Entropy Method [30] was applied to calculate the objective weights of the four predefined evaluation criteria: effectiveness, feasibility, social acceptability, and political support. We selected this method for criterion weighting as it enables an objective, data-driven assessment of dispersion and significance among expert responses, without the introduction of subjective biases that may occur with preference based approaches, i.e., the Analytic Hierarchy Process (AHP). Shannon Entropy is particularly suitable where the aim is to minimize subjective influence and to reflect the intrinsic diversity and informational content of available quantitative data. This enhances transparency and strengthens the reproducibility of the weighting procedure in our multi-criteria decision analysis framework. This method enabled the assignment of weights based on the dispersion of expert scores, ensuring minimal subjectivity in the weighting process. Subsequently, the Simple Weighted Average Method [31,32] was used to compute a composite score for each intervention, by multiplying the score of each intervention under each criterion by its respective weight and summing the results. This process provided a final ranked list of prioritized interventions tailored to the contextual needs of the country and the affected provinces. All calculations were performed using Microsoft Excel for entropy-based weight determination and SPSS version 26 for validation and descriptive analysis. Detailed scoring matrices, entropy values, and final ranking outputs are provided in S1 File.
Results
Key SDHs influencing Aedes-Borne diseases
A total of 206 records were initially retrieved through a comprehensive database search. After removing duplicates, non-English publications, and irrelevant or inaccessible studies, 99 articles met the inclusion criteria and were selected for full-text review and analysis (see PRISMA diagram in S3 Appendix). These studies [1–3,8–12,14–16,18–20,22,33–115] focused primarily on dengue (n = 54), Aedes mosquitoes in general (n = 28), Zika virus (n = 14), and chikungunya virus (n = 3), and were conducted across diverse geographic settings, with the highest contributions from Brazil, the United States, India, and Saudi Arabia. Most articles were published between 2015 and 2024 and employed cross-sectional, spatial (GIS), or review methodologies, reflecting the increasing global attention to Aedes-borne diseases.
A comparative analysis of the frequency of SDHs associated with the spread, prevention, and control of Aedes-borne diseases identified three major contributing factors. The most frequently cited determinant was income, a subcomponent of the broader poverty and related socioeconomic indicators, mentioned in 48 studies. The second key factor was access to urban services and the lack of adequate infrastructure, part of the broader category of urban infrastructure and social support, noted in 40 studies. The third significant determinant was housing quality, falling under the broader housing and environmental conditions domain, referenced in 37 studies (Fig 2). Detailed findings and frequency distributions of the identified determinants are presented in the S4 Appendix.
Policy recommendations derived from the scoping review on SDHs
As part of the identification of SDH-focused interventions, 4,944 English-language articles (2000–2024) were retrieved from major databases, along with 10 relevant WHO reports. After removing 583 duplicates, titles and abstracts were screened based on predefined inclusion criteria. Following full-text review, 71 studies and global documents were included in the final synthesis; (see PRISMA diagram in S5 Appendix) [12,116–185]. Most articles were published between 2019 and 2024 and covered dengue (n = 54), general Aedes-related issues (n = 28), Zika virus (n = 14), and chikungunya (n = 3). The studies originated from diverse settings, with the highest representation from Brazil, the U.S., India, Saudi Arabia, and international collaborations. Methodologies included original research (n = 41), reviews (n = 20), policy papers, and one protocol.
Findings indicate that combining multi-level strategies with intersectoral collaboration can significantly reduce the transmission of Aedes-borne diseases. However, the selection and effectiveness of interventions largely depend on the contextual and socio-environmental characteristics of the target setting. None of the reviewed studies identified a single “gold standard” intervention; rather, a combination of approaches across different domains proved more effective in enhancing both impact and sustainability. These strategies also included more advanced measures, i.e., regular monitoring of mosquito habitats, targeted spraying, and the use of innovative technologies for environmental management. Regional and international cooperation, i.e., data sharing and harmonized cross-border strategies, was emphasized as a critical element in preventing transnational disease spread. Overall, these interventions, through an integrated approach involving preventive and control actions, infrastructure improvements, and public awareness, provide a comprehensive foundation for sustainable and effective management of Aedes-borne diseases. Details of this finding provided in S6 Appendix.
SDH-Driven determinants and interventions for Aedes-Borne diseases in Iran
A total of 21 participants were interviewed, including 12 individual in-depth interviews and two focus group discussions. The participants were selected with maximum variation in terms of organizational affiliation, educational level, professional role, gender, and years of experience (Table 2 and S7 Appendix).
Thematic analysis of the qualitative interviews revealed that the complexity of Aedes-borne diseases arises from a multifaceted interplay of social, economic, environmental, and entomological factors. Through this analysis, five main themes were identified: environmental factors, social factors, economic factors, health system infrastructure, and mosquito species characteristics. These primary themes encompassed 18 sub-themes (Tables 3). The full transcripts of the interviews are provided in S2 File.
The spread of Aedes-borne diseases in Iran is shaped by the interaction of environmental, social, economic, health system, and entomological factors. Climate variability, water scarcity, and humidity foster mosquito breeding, while social and economic inequities, i.e., low health literacy, overcrowding, and poor access to healthcare, intensify vulnerability and delay disease control. Structural gaps in diagnostic capacity, surveillance, and trained personnel, especially in the southern provinces, further constrain timely response. Entomological data reveal that Aedes aegypti dominates arid southern regions, relying on human hosts and artificial habitats, whereas Aedes albopictus prevails in humid northern zones with broader ecological adaptability. (Table 3).
Policy strategies targeting SDHs for the prevention and control of Aedes-Borne diseases in Iran
Interventions, i.e., public education and management of both artificial and natural breeding sites were ranked as high priority due to their direct role in reducing larval habitats and preventing disease transmission. In contrast, measures with more indirect but nonetheless important effects, i.e., the use of local media and multicultural communication programs, were classified as medium priority. The analysis emphasized that understanding the biological variations of Aedes species and aligning intervention programs with the cultural and social context of each region are critical for effective implementation. A summary of key policy strategies addressing social determinants for Aedes-borne disease prevention and control is provided in Table 4, with detailed thematic breakdowns available in S8 Appendix.
The intervention prioritization analysis revealed varying scores across the four criteria: effectiveness (mean range: 6.25–9.13), feasibility (3.5–8.38), social acceptability (5.38–8.75), and political acceptability (4.75–8.13). Among these, feasibility showed the greatest variability, while social and political acceptability demonstrated moderate variation. Based on weighted average scores, the top three prioritized interventions were: (1) specialized training for healthcare workers to enhance disease identification and control skills (8.05); (2) integration of Aedes-borne disease prevention into the national education curriculum (7.56); and (3) use of local media and native languages for effective health communication (7.51). Similarly, Shannon entropy analysis yielded comparable but not identical priorities. This method highlighted: (1) training healthcare staff (8.19), (2) using local media and native languages (7.52), and (3) engaging local and religious leaders to promote preventive action (7.37) as the top-ranked interventions (Fig 3 and S9 Appendix).
Discussion
This qualitative study explored the social determinants influencing the transmission, prevention, and control of Aedes-borne diseases in Iran. The findings revealed that environmental, economic, social, and health system factors play a critical role in the spread of dengue, chikungunya, and Zika. These results align with international evidence, highlighting the need for a multisectoral approach to effectively manage these diseases.
Environmental determinants, particularly climate variability, temperature, rainfall, and the presence of stagnant water, emerged as key contributors to the proliferation of Aedes mosquitoes. Higher temperatures and humidity accelerate mosquito development and expand their geographic range, consistent with findings from Brazil and Thailand, where a 1–2°C increase significantly raised mosquito density and disease transmission [2]. Similarly, rainfall contributes to ideal breeding conditions, as evidenced in Malaysia and Indonesia, where higher precipitation correlates with increased dengue incidence [33]. In Iran, participants from southern provinces, i.e., Hormozgan, Bushehr, and Sistan and Baluchestan reported that sudden downpours, coupled with poor surface water management, have intensified mosquito proliferation in those regions.
International studies have shown that economic deprivation and social inequalities have a direct impact on the incidence and control of Aedes-borne diseases [150]. In low-income countries, lack of access to basic health infrastructure, inadequate waste management, and high population density in impoverished areas have contributed to the increased transmission of dengue and chikungunya [97]. Consistent with these findings, the present study revealed that in Iran, low-income and underserved regions experience the highest exposure to Aedes-borne diseases. In these areas, poor waste collection, absence of proper sewage systems, and limited access to safe water create favorable conditions for mosquito breeding. These findings underscore the need to complement health interventions with broader social and economic measures, i.e., improving urban infrastructure and addressing economic disparities, to achieve effective disease control.
This study highlights the critical role of public awareness and community engagement in the success of Aedes-borne disease control programs. In countries, i.e., Singapore, large-scale educational campaigns have led to a significant decline in disease incidence [144]. However, in Iran, the absence of structured educational programs and low public awareness remain major barriers. Interviewees noted limited knowledge among the general population about disease risks and preventive practices, i.e., eliminating stagnant water and using protective screens. These findings align with global evidence that school-based programs, mosque outreach, social media, and national broadcasting can effectively enhance public engagement [22,36,144,145]. Countries like Malaysia, Brazil, and Cuba have also demonstrated the value of community-based approaches, including the active involvement of women and families in vector control [22,36,123,171]. While Iran has a broad network of mosques and schools offering strong outreach potential, the lack of sustained programming and insufficient funding hinder progress. Unlike Singapore, where health education is embedded in curricula, Iran has yet to establish a nationwide framework for Aedes-focused public education.
The study also highlighted weaknesses in the health system, including delays in disease detection and a shortage of diagnostic tools, as major challenges in Iran’s vector control efforts. This is consistent with findings from Malaysia and the Philippines, where inadequate surveillance systems, late case detection, and limited trained personnel have been linked to increased transmission and reduced effectiveness of control strategies [48]. In Iran, the shortage of trained medical entomologists, lack of coordination across health sectors, and financial constraints in procuring diagnostic equipment and insecticides were among the main operational challenges identified. Evidences suggest that the establishment of digital surveillance systems, strengthening of local health networks, and increased investment in diagnostic infrastructure can significantly reduce the incidence of Aedes-borne diseases [131,132]. Accordingly, reinforcing Iran’s health system infrastructure and developing robust disease monitoring and surveillance mechanisms should be considered key priorities for effective vector control.
Waste management and environmental sanitation are also essential components of Aedes control. In Brazil, strict regulations on tire disposal and scrap yard oversight have proven effective, while urban drainage programs in Mexico have contributed significantly to dengue prevention [2]. In Iran, similar interventions, i.e., community cleanup campaigns and improved waste management systems, were prioritized, but implementation remains hindered by inadequate municipal coordination, limited funding, and insufficient public participation. Unlike Brazil and Mexico [41,111], where incentive-based mechanisms promote community engagement, Iran has yet to operationalize such tools effectively.
Advanced surveillance and early warning systems are critical for anticipating outbreaks. Malaysia and Thailand have employed satellite data, artificial intelligence, and biosensors to forecast Aedes activity and identify high-risk zones [48]. These tools enable preemptive health responses. Additionally, rapid diagnostic testing (RDT) has enhanced early case detection in several countries. In contrast, Iran lacks a robust environmental surveillance and early warning system. While prioritized, implementation is constrained by limited technological infrastructure and budget. The use of locally developed digital platforms could offer a cost-effective solution.
Cross-sectoral collaboration is another key enabler of effective disease control. In Brazil, ministries of health, environment, and local governments coordinate efforts through an integrated governance structure [103]. In Cuba, civil society organizations, volunteers, and local health workers collaborate through unified networks [171]. In Iran, while intersectoral coordination is recognized as a high-priority intervention, it remains a major challenge. Fragmentation among ministries and agencies, particularly the lack of cooperation between the MOHME, municipalities, and the Department of Environment, undermines the consistency and effectiveness of intervention programs. Establishing formal coordination structures and joint policy frameworks is essential for enhancing implementation outcomes.
Studies from Brazil have emphasized the critical role of coordinated action among governmental and non-governmental bodies, intersectoral collaboration, and unified policy implementation in curbing the spread of Aedes-borne diseases [103]. Similarly, this study identified a lack of coordination among key institutions in Iran as a major barrier to effective program implementation. These findings highlight the necessity of establishing integrated management structures, enhancing intersectoral collaboration, and formulating cohesive policies. Global experiences demonstrate that successful strategies typically combine public education, environmental infrastructure development, health system strengthening, and cross-sector partnerships. Iran’s prioritized interventions, developed through expert consultation and scientific criteria, generally align with these approaches. However, challenges related to implementation capacity, institutional coordination, investment levels, and limited adoption of digital tools reveal the need for tailored, context-specific adaptation of global best practices.
This study offers a novel social perspective on the emergence and spread of Aedes-borne diseases in Iran for the first time, combining evidence from global literature with insights from diverse national stakeholders. A key strength lies in the integration of qualitative interviews with provincial managers and experts, enhancing the contextual relevance and depth of the findings. The study also employed flexible communication methods and leveraged existing networks within the MOHME and NGOs to overcome challenges in reaching key informants. However, a key limitation of this study is the absence of direct community level representation among participants. While our sample included national and provincial health experts, policymakers, and field specialists to capture policy and structural perspectives, community members and affected populations were not directly engaged in data collection. This omission may limit insights into grassroots determinants and the lived experiences of those most affected by Aedes-borne diseases. To mitigate this, the study relied on expert input from provincial representatives. Future research should incorporate community stakeholders to enable richer triangulation of social determinants and to better inform context-appropriate policy interventions. We acknowledge that the purposive expert sampling approach entails inherent limitations, including potential selection bias and constrained transferability of findings. This methodological choice was intended to capture in depth insights from experienced professionals, aligning with the study’s policy focused objectives. Nevertheless, while the results provide valuable contextual evidence, their application in other settings should be approached with caution and adapted to local social, environmental, and institutional conditions.
Conclusion
This study highlights the multifaceted nature of Aedes-borne diseases, i.e., dengue, chikungunya, and Zika, in Iran, shaped by a complex interplay of social, economic, environmental, and health system factors. It convincingly links socioeconomic inequality, low health literacy, and limited health infrastructure with increased risk of Aedes-borne diseases in Iran. Importantly, the multi-criteria prioritization quantitatively highlights that socioeconomic factors carry the greatest relative weight, followed by health system capacity and environmental determinants. This evidence underscores the need to focus interventions on socioeconomic improvements alongside health system strengthening to effectively mitigate disease risk.
Public awareness and community engagement emerged as central to effective prevention. In Iran, leveraging schools, mosques, and local media, alongside improved collaboration between communities and public institutions, are crucial. Without behavioral change and health literacy, other interventions face limited impact. Additionally, upgrading environmental and health infrastructure, i.e., waste management, water systems, and diagnostic capacity, is vital for vector control. Strengthening health surveillance systems and intersectoral coordination between the MOHME, municipalities, environmental agencies, and civil society is critical. Lessons from countries like Brazil and Malaysia demonstrate the value of aligning health policies with environmental and development agendas. Based on the findings, the study recommends that policymakers focus on three key pillars:
- Expanding public education and awareness campaigns through schools, mass media, and digital platforms.
- Improving environmental infrastructure, with emphasis on water management, waste reduction, and efficient environmental monitoring.
- Strengthening the health system through broader service access, rapid diagnostic tools, and enhanced disease surveillance.
Future research should explore the effectiveness of localized control models, assess the role of community participation, analyze the climate-related dynamics of Aedes spread in Iran, and examine innovative monitoring and vector control strategies.
Supporting information
S1 Appendix. Topic guide for qualitative phase.
https://doi.org/10.1371/journal.pntd.0013850.s001
(DOCX)
S2 Appendix. Prioritization form for SDH-oriented interventions and strategies for Aedes-Borne diseases in the Islamic Republic of Iran.
https://doi.org/10.1371/journal.pntd.0013850.s002
(DOCX)
S3 Appendix. PRISMA flow diagram – Search, screening, and selection of articles on key Social Determinants of Health (SDHs) influencing Aedes-Borne diseases.
https://doi.org/10.1371/journal.pntd.0013850.s003
(DOCX)
S4 Appendix. Frequency of Social Determinants of Health (SDHs) for Aedes-Borne diseases based on reviewed studies.
https://doi.org/10.1371/journal.pntd.0013850.s004
(DOCX)
S5 Appendix. PRISMA flow diagram – Search, screening, and selection of studies on SDH-based interventions related to aedes disease control.
https://doi.org/10.1371/journal.pntd.0013850.s005
(DOCX)
S6 Appendix. Interventions identified from the literature categorized by social and economic factors.
https://doi.org/10.1371/journal.pntd.0013850.s006
(DOCX)
S7 Appendix. Profile of participants in the qualitative component of the study.
https://doi.org/10.1371/journal.pntd.0013850.s007
(DOCX)
S8 Appendix. Policy strategies targeting SDHs for the prevention and control of Aedes-Borne diseases in Iran.
https://doi.org/10.1371/journal.pntd.0013850.s008
(DOCX)
S9 Appendix. Prioritization of identified interventions based on defined criteria.
https://doi.org/10.1371/journal.pntd.0013850.s009
(DOCX)
S1 File. Details of interventions’ prioritization.
https://doi.org/10.1371/journal.pntd.0013850.s010
(XLSX)
S2 File. Full transcripts of qualitative interviews with key informants, including provincial and national stakeholders.
https://doi.org/10.1371/journal.pntd.0013850.s011
(DOCX)
References
- 1. Morgan J, Strode C, Salcedo-Sora JE. Climatic and socio-economic factors supporting the co-circulation of dengue, Zika and chikungunya in three different ecosystems in Colombia. PLoS Negl Trop Dis. 2021;15(3):e0009259. pmid:33705409
- 2. Coalson JE, Richard DM, Hayden MH, Townsend J, Damian D, Smith K, et al. Aedes aegypti abundance in urban neighborhoods of Maricopa County, Arizona, is linked to increasing socioeconomic status and tree cover. Parasit Vectors. 2023;16(1):351. pmid:37807069
- 3. Babu AN, Niehaus E, Shah S, Unnithan C, Ramkumar PS, Shah J, et al. Smartphone geospatial apps for dengue control, prevention, prediction, and education: MOSapp, DISapp, and the mosquito perception index (MPI). Environ Monit Assess. 2019;191(Suppl 2):393. pmid:31254076
- 4.
Dengue and severe dengue [Internet]. Who.int. [cited 2025 Nov 15]. Available from: https://www.who.int/news-room/questions-and-answers/item/dengue-and-severe-dengue
- 5.
Dengue - global situation [Internet]. Who.int. [cited 2025 Nov 15]. Available from: https://www.who.int/emergencies/disease-outbreak-news/item/2024-DON518
- 6. Zheng J, Tong H, Chen M, Duan L, Song P, Sun J, et al. Global burden of dengue from 1990 to 2021: a systematic analysis from the Global Burden of Disease study 2021. Infect Dis Poverty. 2025;14(1):105. doi: https://doi.org/10.1186/s40249-025-01365-x pmid:41094559
- 7.
Dengue worldwide overview [Internet]. European Centre for Disease Prevention and Control; 2025 [cited 2025 Nov 15]. Available from: https://www.ecdc.europa.eu/en/dengue-monthly
- 8. Ashmore P, Lindahl JF, Colón-González FJ, Sinh Nam V, Quang Tan D, Medley GF. Spatiotemporal and socioeconomic risk factors for dengue at the province level in Vietnam, 2013-2015: clustering analysis and regression model. Trop Med Infect Dis. 2020;5(2).
- 9. Aziz AT, Al-Shami SA, Mahyoub JA, Hatabbi M, Ahmad AH, Md Rawi CS. Promoting health education and public awareness about dengue and its mosquito vector in Saudi Arabia. Parasit Vectors. 2014;7:487. pmid:25403705
- 10. de Jesús Crespo R, Rogers RE. Habitat segregation patterns of container breeding mosquitos: the role of urban heat islands, vegetation cover, and income disparity in cemeteries of New Orleans. Int J Environ Res Public Health. 2021;19(1):245. pmid:35010505
- 11. Dias ÍKR, Martins RMG, Sobreira CL da S, Rocha RMGS, Lopes M do SV. Education-based Aedes Aegypti control actions: an integrative review. Cien Saude Colet. 2022;27(1):231–42. pmid:35043902
- 12. Jency PJ, Rishla KE, Jabir MM, Vijayakumar B, Dinesh RJ, Dhanalakshmi R. Anti-dengue sanitation practices: a health education approach for municipal sanitary workers in Puducherry, India. Cureus. 2024;16(7).
- 13. Joyce AL, Alvarez FS, Hernandez E. Forest coverage and socioeconomic factors associated with dengue in El Salvador, 2011-2013. Vector Borne Zoonotic Dis. 2021;21(8):602–13.
- 14. Whiteman A, Mejia A, Hernandez I, Loaiza JR. Socioeconomic and demographic predictors of resident knowledge, attitude, and practice regarding arthropod-borne viruses in Panama. BMC Public Health. 2018;18(1):1261. pmid:30428861
- 15. Bonifay T, Douine M, Bonnefoy C, Hurpeau B, Nacher M, Djossou F, et al. Poverty and arbovirus outbreaks: when chikungunya virus hits more precarious populations than dengue virus in French Guiana. Open Forum Infect Dis. 2017;4(4):ofx247. pmid:29308403
- 16. Alkhaldy I, Barnett P. Evaluation of neighborhood socio-economic status, as measured by the Delphi Method, on dengue fever distribution in Jeddah City, Saudi Arabia. Int J Environ Res Public Health. 2021;18(12):6407. pmid:34199216
- 17. Kumar S, Katyal R, Kumar K, Patel S, Kamal S, Bora D. An observation on contribution of breeding of Aedes aegpti vector of Dengue and Chikungunya by different income group communities of Varanasi city, Uttar Pradesh, India. J Commun Dis. 2009;41(2):133–6. pmid:22010503
- 18. Cunha HS, Sclauser BS, Wildemberg PF, Fernandes EAM, Dos Santos JA, Lage M de O, et al. Water tank and swimming pool detection based on remote sensing and deep learning: relationship with socioeconomic level and applications in dengue control. PLoS One. 2021;16(12):e0258681. pmid:34882711
- 19. Shams N, Amjad S, Yousaf N, Ahmed W, Seetlani NK, Farhat S. Dengue knowledge in indoor dengue patients from low socioeconomic class; aetiology, symptoms, mode of transmission and prevention. J Ayub Med Coll Abbottabad. 2018;30(1):40–4. pmid:29504327
- 20. Dhar-Chowdhury P, Haque CE, Lindsay R, Hossain S. Socioeconomic and ecological factors influencing Aedes aegypti prevalence, abundance, and distribution in Dhaka, Bangladesh. Am J Trop Med Hyg. 2016;94(6):1223–33. pmid:27022149
- 21. Hosseiniara R, Mohammadi-Shahrokhi V, Zarei S, Dehghani R. Aedes mosquito and dengue fever in Iran and worldwide: medical significance, prevention, and control. Feyz Med Sci J. 2024;28(3):324–34.
- 22. Chaves M de O, Evangelista M do SN, Fernandes FM de C. Health education in Aedes aegypti: case study. Rev Bras Enferm. 2020;73(3):e20180487. pmid:32267416
- 23. Allen T, Crouch A, Topp SM. Community participation and empowerment approaches to Aedes mosquito management in high-income countries: a scoping review. Health Promot Int. 2021;36(2):505–23. pmid:32647879
- 24. De Azevedo TS, Bourke BP, Piovezan R, Sallum MAM. The influence of urban heat islands and socioeconomic factors on the spatial distribution of Aedes aegypti larval habitats. Geospat Health. 2018;13(1):623. pmid:29772891
- 25. Arksey H, O’Malley L. Scoping studies: towards a methodological framework. Int J Soc Res Methodol. 2005;8(1):19–32.
- 26. Moher D, Altman DG, Liberati A, Tetzlaff J. PRISMA statement. Epidemiology. 2011;22(1):128; author reply 128. pmid:21150360
- 27. Graneheim UH, Lundman B. Qualitative content analysis in nursing research: concepts, procedures and measures to achieve trustworthiness. Nurse Educ Today. 2004;24(2):105–12. pmid:14769454
- 28. Mobinizadeh M, Mohamadi E, Arman H, Nasiripour A, Olyaeemanesh A, Mohamadi S. Topic selection for health technology assessment: an approach combining multiple attribute decision making and decision rules. Med J Islam Repub Iran. 2021;35:40. pmid:34211942
- 29. Wang Y-M, Elhag TMS. Fuzzy TOPSIS method based on alpha level sets with an application to bridge risk assessment. Expert Syst Appl. 2006;31(2):309–19.
- 30. Shanon CE. A mathematical theory of communication. BSTJ. 1948;27:623–56.
- 31.
Tzeng GH, Huang JJ. Multiple attribute decision making: methods and applications. CRC Press; 2011.
- 32.
Mohamadi E, Tabatabaei SM, Olyaeemanesh A, Sagha SF, Zanganeh M, Davari M. Coverage decision-making for orthopedics interventions in the health transformation program in Iran: a multiple criteria decision analysis (MCDA). 2016.
- 33. Abdul Rahman FK, Binti Wan Puteh SE, Bin Zainuddin MA. E-dengue system insights: exploring the factors influencing dengue-related deaths in an urbanized state in a Low-Middle Income Country (LMIC). BMC Public Health. 2024;24(1):3055. pmid:39501241
- 34. Abu Bakar A, Sulaiman S, Omar B, Mat Ali R. Evaluation of Melaleuca cajuputi (Family: Myrtaceae) essential oil in aerosol spray cans against dengue vectors in low cost housing flats. J Arthropod Borne Dis. 2012;6(1):28–35. pmid:23293776
- 35. Aguiar-Santos M, Mendes LG da C, Passos DFD, Santos TG da S, Lins RHFB, Monte ACP do. Spatial analysis of Chikungunya fever incidence and the associated socioeconomic, demographic, and vector infestation factors in municipalities of Pernambuco, Brazil, 2015-2021. Rev Bras Epidemiol. 2023;26:e230018. pmid:36820755
- 36. AhbiRami R, Zuharah WF. School-based health education for dengue control in Kelantan, Malaysia: impact on knowledge, attitude and practice. PLoS Negl Trop Dis. 2020;14(3):e0008075. pmid:32218580
- 37. Anno S, Imaoka K, Tadono T, Igarashi T, Sivaganesh S, Kannathasan S, et al. Space-time clustering characteristics of dengue based on ecological, socio-economic and demographic factors in northern Sri Lanka. Geospat Health. 2015;10(2):376. pmid:26618322
- 38. Barrera R, Harris A, Hemme RR, Felix G, Nazario N, Muñoz-Jordan JL, et al. Citywide control of Aedes aegypti (Diptera: Culicidae) during the 2016 Zika epidemic by integrating community awareness, education, source reduction, larvicides, and mass mosquito trapping. J Med Entomol. 2019;56(4):1033–46. pmid:30753539
- 39. Bavia L, Melanda FN, de Arruda TB, Mosimann ALP, Silveira GF, Aoki MN, et al. Epidemiological study on dengue in southern Brazil under the perspective of climate and poverty. Sci Rep. 2020;10(1):2127. pmid:32034173
- 40. Blanton RE, Silva LK, Morato VG, Parrado AR, Dias JP, Melo PRS, et al. Genetic ancestry and income are associated with dengue hemorrhagic fever in a highly admixed population. Eur J Hum Genet. 2008;16(6):762–5. pmid:18270538
- 41. Cançado MSM, Barbosa MA, Teixeira RAG, Oliveira ESF de. Perceptions of representatives of a committee against dengue in the health education actions, Goiás, Brazil. Rev Esc Enferm USP. 2014;48 Spec No. 2:94–9. pmid:25830742
- 42. Carabali M, Harper S, Lima Neto AS, Dos Santos de Sousa G, Caprara A, Restrepo BN, et al. Spatiotemporal distribution and socioeconomic disparities of dengue, chikungunya and Zika in two Latin American cities from 2007 to 2017. Trop Med Int Health. 2021;26(3):301–15. pmid:33219561
- 43. Chiaravalloti-Neto F, da Silva RA, Zini N, da Silva GCD, da Silva NS, Parra MCP, et al. Seroprevalence for dengue virus in a hyperendemic area and associated socioeconomic and demographic factors using a cross-sectional design and a geostatistical approach, state of São Paulo, Brazil. BMC Infect Dis. 2019;19(1):441. pmid:31109295
- 44. Dapari R, Muniandy K, Fattah Azman AZ, Abu Bakar S, Mohd Desa MN, Hwa LC, et al. Effectiveness of the Integrated Dengue Education and Learning (iDEAL) module in improving the knowledge, attitude, practice, environmental cleanliness index, and dengue index among schoolchildren: a randomised controlled trial protocol. PLoS One. 2024;19(4):e0302736. pmid:38687755
- 45. David MR, Lourenço-de-Oliveira R, Freitas RM de. Container productivity, daily survival rates and dispersal of Aedes aegypti mosquitoes in a high income dengue epidemic neighbourhood of Rio de Janeiro: presumed influence of differential urban structure on mosquito biology. Mem Inst Oswaldo Cruz. 2009;104(6):927–32. pmid:19876569
- 46. de Amorin Vilharba BL, Yamamura M, de Azevedo MV, Fernandes W de S, Santos-Pinto CDB, de Oliveira EF. Disease burden of congenital Zika virus syndrome in Brazil and its association with socioeconomic data. Sci Rep. 2023;13(1):11882. pmid:37482558
- 47. de Jesús Crespo R, Harrison M, Rogers R, Vaeth R. Mosquito vector production across socio-economic divides in Baton Rouge, Louisiana. Int J Environ Res Public Health. 2021;18(4):1420. pmid:33546458
- 48. Dey SK, Rahman MM, Howlader A, Siddiqi UR, Uddin KMM, Borhan R, et al. Prediction of dengue incidents using hospitalized patients, metrological and socio-economic data in Bangladesh: a machine learning approach. PLoS One. 2022;17(7):e0270933. pmid:35857776
- 49. Diaz-Quijano FA, Martínez-Vega RA, Rodriguez-Morales AJ, Rojas-Calero RA, Luna-González ML, Díaz-Quijano RG. Association between the level of education and knowledge, attitudes and practices regarding dengue in the Caribbean region of Colombia. BMC Public Health. 2018;18(1):143. pmid:29338712
- 50. Dowling Z, Armbruster P, LaDeau SL, DeCotiis M, Mottley J, Leisnham PT. Linking mosquito infestation to resident socioeconomic status, knowledge, and source reduction practices in suburban Washington, DC. Ecohealth. 2013;10(1):36–47. pmid:23377982
- 51. Dowling Z, Ladeau SL, Armbruster P, Biehler D, Leisnham PT. Socioeconomic status affects mosquito (Diptera: Culicidae) larval habitat type availability and infestation level. J Med Entomol. 2013;50(4):764–72. pmid:23926774
- 52. Durrance-Bagale A, Hoe N, Lai J, Liew JWK, Clapham H, Howard N. Dengue vector control in high-income, city settings: a scoping review of approaches and methods. PLoS Negl Trop Dis. 2024;18(4):e0012081. pmid:38630673
- 53. Freitas LP, Schmidt AM, Cossich W, Cruz OG, Carvalho MS. Spatio-temporal modelling of the first Chikungunya epidemic in an intra-urban setting: the role of socioeconomic status, environment and temperature. PLoS Negl Trop Dis. 2021;15(6):e0009537. pmid:34143771
- 54. Gamboa LF, Rodriguez Lesmes P. The fertility-inhibiting effect of mosquitoes: socio-economic differences in response to the Zika crisis in Colombia. Econ Hum Biol. 2019;35:63–72. pmid:31154121
- 55. Gardini Sanches Palasio R, Marques Moralejo Bermudi P, Luiz de Lima Macedo F, Reis Santana LM, Chiaravalloti-Neto F. Zika, chikungunya and co-occurrence in Brazil: space-time clusters and associated environmental-socioeconomic factors. Sci Rep. 2023;13(1):18026. pmid:37865641
- 56. Gurevitz JM, Antman JG, Laneri K, Morales JM. Temperature, traveling, slums, and housing drive dengue transmission in a non-endemic metropolis. PLoS Negl Trop Dis. 2021;15(6).
- 57. Hagenlocher M, Delmelle E, Casas I, Kienberger S. Assessing socioeconomic vulnerability to dengue fever in Cali, Colombia: statistical vs expert-based modeling. Int J Health Geogr. 2013;12:36. pmid:23945265
- 58. Healy K, Hamilton G, Crepeau T, Healy S, Unlu I, Farajollahi A, et al. Integrating the public in mosquito management: active education by community peers can lead to significant reduction in peridomestic container mosquito habitats. PLoS One. 2014;9(9):e108504. pmid:25255027
- 59. Jain R, Sontisirikit S, Iamsirithaworn S, Prendinger H. Prediction of dengue outbreaks based on disease surveillance, meteorological and socio-economic data. BMC Infect Dis. 2019;19(1):272. pmid:30898092
- 60. Joshi V, Sharma RC, Sharma Y, Adha S, Sharma K, Singh H, et al. Importance of socioeconomic status and tree holes in distribution of Aedes mosquitoes (Diptera: Culicidae) in Jodhpur, Rajasthan, India. J Med Entomol. 2006;43(2):330–6. pmid:16619619
- 61. Kellemen M, Ye J, Moreno-Madriñan MJ. Exploring for municipality-level socioeconomic variables related to Zika virus incidence in Colombia. Int J Environ Res Public Health. 2021;18(4):1831. pmid:33668584
- 62. Kellner AWA. Heavy metals partitioning in the Rodrigo de Freitas lagoon; larvicidal potential of a new essential oil against Aedes aegypti; and the socioeconomic impact of tourism due to wild dolphins provisioning. An Acad Bras Cienc. 2013;85(4):1215–6. pmid:24346790
- 63. Khormi HM, Kumar L. Assessing the risk for dengue fever based on socioeconomic and environmental variables in a geographical information system environment. Geospat Health. 2012;6(2):171–6. pmid:22639119
- 64. Khun S, Manderson L. Community and school-based health education for dengue control in rural Cambodia: a process evaluation. PLoS Negl Trop Dis. 2007;1(3):e143. pmid:18160981
- 65. Khun S, Manderson L. Poverty, user fees and ability to pay for health care for children with suspected dengue in rural Cambodia. Int J Equity Health. 2008;7:10. pmid:18439268
- 66. Kienberger S, Hagenlocher M, Delmelle E, Casas I. A WebGIS tool for visualizing and exploring socioeconomic vulnerability to dengue fever in Cali, Colombia. Geospat Health. 2013;8(1):313–6. pmid:24258905
- 67. Kikuti M, Cunha GM, Paploski IAD, Kasper AM, Silva MMO, Tavares AS, et al. Spatial distribution of dengue in a Brazilian urban slum setting: role of socioeconomic gradient in disease risk. PLoS Negl Trop Dis. 2015;9(7):e0003937. pmid:26196686
- 68. Kua KP, Lee SWH. Randomized trials of housing interventions to prevent malaria and Aedes-transmitted diseases: a systematic review and meta-analysis. PLoS One. 2021;16(1):e0244284. pmid:33417600
- 69. Kumar CJ, Baboo CA, Krishnan BU, Kumar A, Joy S, Jose T, et al. The socioeconomic impact of the chikungunya viral epidemic in India. Open Med. 2007;1(3):e150-2. pmid:21673944
- 70. Kuper H, Smythe T, Duttine A. Reflections on health promotion and disability in low and middle-income countries: case study of parent-support programmes for children with congenital Zika syndrome. Int J Environ Res Public Health. 2018;15(3):514. pmid:29538291
- 71. Lefebvre B, Karki R, Misslin R, Nakhapakorn K, Daudé E, Paul RE. Importance of public transport networks for reconciling the spatial distribution of dengue and the association of socio-economic factors with dengue risk in Bangkok, Thailand. Int J Environ Res Public Health. 2022;19(16):10123. pmid:36011755
- 72. Lin CH, Schiøler KL, Jepsen MR, Ho CK, Li SH, Konradsen F. Dengue outbreaks in high-income area, Kaohsiung City, Taiwan, 2003-2009. Emerg Infect Dis. 2012;18(10):1603–11.
- 73. Lobkowicz L, Power GM, De Souza WV, Montarroyos UR, Martelli CMT, de Araùjo TVB, et al. Neighbourhood-level income and Zika virus infection during pregnancy in Recife, Pernambuco, Brazil: an ecological perspective, 2015-2017. BMJ Global Health. 2021;6(12).
- 74. Lorenz C, Azevedo TS, Virginio F, Aguiar BS, Chiaravalloti-Neto F, Suesdek L. Impact of environmental factors on neglected emerging arboviral diseases. PLoS Negl Trop Dis. 2017;11(9):e0005959. pmid:28953892
- 75. Madeira NG, Macharelli CA, Pedras JF, Delfino MCN. Education in primary school as a strategy to control dengue. Rev Soc Bras Med Trop. 2002;35(3):221–6. pmid:12045814
- 76. McQuade L, Rao M, Miller R, Zhou W, Deol R, Sato B. Understanding patterns of socioeconomic and demographic factors along with health services provider availability for Zika outbreak in South Florida. Disaster Med Public Health Prep. 2018;12(4):455–9. pmid:29041992
- 77. Mohamed MA, Hassan NY, Osman MM, Gedi S, Maalin BAA, Sultan KM, et al. Epidemiological investigation of dengue fever outbreak and its socioeconomic determinants in Banadir region, Somalia. BMC Infect Dis. 2024;24(1):393. pmid:38605362
- 78. Mulligan K, Dixon J, Sinn C-LJ, Elliott SJ. Is dengue a disease of poverty? A systematic review. Pathog Glob Health. 2015;109(1):10–8. pmid:25546339
- 79. Padilla-Pozo Á, Bartumeus F, Montalvo T, Sanpera-Calbet I, Valsecchi A, Palmer JRB. Assessing and correcting neighborhood socioeconomic spatial sampling biases in citizen science mosquito data collection. Sci Rep. 2024;14(1):22462. pmid:39341898
- 80. Paixão ES, Fernandes QHRF, Cardim LL, Pescarini JM, Costa MCN, Falcão IR, et al. Socioeconomic risk markers of congenital Zika syndrome: a nationwide, registry-based study in Brazil. BMJ Glob Health. 2022;7(9):e009600. pmid:36175039
- 81. Paixão ES, Harron K, Andrade K, Teixeira MG, Fiaccone RL, Costa M da CN, et al. Evaluation of record linkage of two large administrative databases in a middle income country: stillbirths and notifications of dengue during pregnancy in Brazil. BMC Med Inform Decis Mak. 2017;17(1):108. pmid:28716074
- 82. Parker C, Garcia F, Menocal O, Jeer D, Alto B. A mosquito workshop and community intervention: a pilot education campaign to identify risk factors associated with container mosquitoes in San Pedro Sula, Honduras. Int J Environ Res Public Health. 2019;16(13).
- 83. Paulson W, Kodali NK, Balasubramani K, Dixit R, Chellappan S, Behera SK, et al. Social and housing indicators of dengue and chikungunya in Indian adults aged 45 and above: analysis of a nationally representative survey (2017-18). Arch Public Health. 2022;80(1):125.
- 84. Pedro RS, Carvalho MS, Girianelli VR, Damasceno LS, Leal I, Cunha DC da, et al. A populational-based birth cohort study in a low-income urban area in Rio de Janeiro, Brazil: implementation and description of the characteristics of the study. Cad Saude Publica. 2019;35(5):e00023918. pmid:31141024
- 85. Power GM, Francis SC, Sanchez Clemente N, Vasconcelos Z, Brasil P, Nielsen-Saines K, et al. Examining the association of socioeconomic position with microcephaly and delayed childhood neurodevelopment among children with prenatal Zika virus exposure. Viruses. 2020;12(11):1342. pmid:33238584
- 86. Qi X, Wang Y, Li Y, Meng Y, Chen Q, Ma J. The effects of socioeconomic and environmental factors on the incidence of dengue fever in the Pearl River Delta, China, 2013. PLoS Negl Trop Dis. 2015;9(10).
- 87. Queiroz ER da S, Medronho R de A. Spatial analysis of the incidence of Dengue, Zika and Chikungunya and socioeconomic determinants in the city of Rio de Janeiro, Brazil. Epidemiol Infect. 2021;149:e188. pmid:34338179
- 88. Quintero J, Carrasquilla G, Suárez R, González C, Olano VA. An ecosystemic approach to evaluating ecological, socioeconomic and group dynamics affecting the prevalence of Aedes aegypti in two Colombian towns. Cad Saude Publica. 2009;25 Suppl 1:S93-103. pmid:19287871
- 89. Radhika NML, Gunathilaka N, Udayanga L, Kasturiratne A, Abeyewickreme W. Level of awareness of dengue disease among school children in Gampaha District, Sri Lanka, and effect of school-based health education programmes on improving knowledge and practices. Biomed Res Int. 2019;2019:3092073. pmid:31321232
- 90. Ramisetty-Mikler S, Boyce L. Communicating the risk of contracting Zika virus to low income underserved pregnant Latinas: a clinic-based study. PLoS One. 2020;15(11):e0241675. pmid:33216763
- 91. Raza FA, Ashraf S, Hasnain S, Ahmad J, Iqbal M. Dengue seroprevalence and its socioeconomic determinants in Faisalabad, Pakistan: a cross-sectional study. Rev Soc Bras Med Trop. 2018;51(4):503–7. pmid:30133634
- 92. Rosado LEP, Aquino EC de, Brickley EB, França DD da S, Silva FPA, Silva VL da, et al. Socioeconomic disparities associated with symptomatic Zika virus infections in pregnancy and congenital microcephaly: a spatiotemporal analysis from Goiânia, Brazil (2016 to 2020). PLoS Negl Trop Dis. 2022;16(6):e0010457. pmid:35714146
- 93. Rothman SE, Jones JA, LaDeau SL, Leisnham PT. Higher west nile virus infection in Aedes albopictus (Diptera: Culicidae) and Culex (Diptera: Culicidae) mosquitoes from lower income neighborhoods in Urban Baltimore, MD. J Med Entomol. 2021;58(3):1424–8. pmid:33257956
- 94. Salim KU, Álvarez FS, Chan-Golston AM, Naughton CC, Cisneros R, Joyce A. Socioeconomic and environmental factors associated with dengue fever incidence in Guatemala: rising temperatures increase dengue risk. PLoS One. 2024;19(8):e0308271. pmid:39088578
- 95. Sallam MF, Fizer C, Pilant AN, Whung P-Y. Systematic review: land cover, meteorological, and socioeconomic determinants of Aedes mosquito habitat for risk mapping. Int J Environ Res Public Health. 2017;14(10):1230. pmid:29035317
- 96. Seposo X, Valenzuela S, Apostol GL. Socio-economic factors and its influence on the association between temperature and dengue incidence in 61 provinces of the Philippines, 2010-2019. PLoS Negl Trop Dis. 2023;17(10).
- 97. Shafique M, Mukhtar M, Areesantichai C, Perngparn U. Effectiveness of positive deviance, an asset-based behavior change approach, to improve knowledge, attitudes, and practices regarding dengue in low-income communities (Slums) of Islamabad, Pakistan: a mixed-method study. Insects. 2022;13(1):71. pmid:35055914
- 98. Shragai T, Harrington LC. Aedes albopictus (Diptera: Culicidae) on an invasive edge: abundance, spatial distribution, and habitat usage of larvae and pupae across urban and socioeconomic environmental gradients. J Med Entomol. 2019;56(2):472–82. pmid:30566612
- 99. Souza RL, Nazare RJ, Argibay HD, Pellizzaro M, Anjos RO, Portilho MM, et al. Density of Aedes aegypti (Diptera: Culicidae) in a low-income Brazilian urban community where dengue, Zika, and chikungunya viruses co-circulate. Parasit Vectors. 2023;16(1):159. pmid:37149611
- 100. Stefopoulou Α, Balatsos G, Petraki A, LaDeau SL, Papachristos D, Michaelakis Α. Reducing Aedes albopictus breeding sites through education: a study in urban area. PLoS One. 2018;13(11):e0202451. pmid:30408031
- 101. Suwantika AA, Kautsar AP, Supadmi W, Zakiyah N, Abdulah R, Ali M, et al. Cost-effectiveness of dengue vaccination in Indonesia: considering integrated programs with wolbachia-infected mosquitos and health education. Int J Environ Res Public Health. 2020;17(12):4217. pmid:32545688
- 102. Swaddiwudhipong W, Chaovakiratipong C, Nguntra P, Koonchote S, Khumklam P, Lerdlukanavonge P. Effect of health education on community participation in control of dengue hemorrhagic fever in an urban area of Thailand. Southeast Asian J Trop Med Public Health. 1992;23(2):200–6. pmid:1439971
- 103. Teurlai M, Menkès CE, Cavarero V, Degallier N, Descloux E, Grangeon J-P, et al. Socio-economic and climate factors associated with dengue fever spatial heterogeneity: a worked example in New Caledonia. PLoS Negl Trop Dis. 2015;9(12):e0004211. pmid:26624008
- 104. Towers VS, Goldsmith M, Goldsmith P. Zika virus: patient education recommendations. Adv Neonatal Care. 2018;18(5):360–5. pmid:30239404
- 105. Udayanga L, Gunathilaka N, Iqbal MCM, Lakmal K, Amarasinghe US, Abeyewickreme W. Comprehensive evaluation of demographic, socio-economic and other associated risk factors affecting the occurrence of dengue incidence among Colombo and Kandy Districts of Sri Lanka: a cross-sectional study. Parasit Vectors. 2018;11(1):478. pmid:30143051
- 106. Usman HB, AlSahafi A, Abdulrashid O, Mandoura N, Al Sharif K, Ibrahim A. Effect of health education on dengue fever: a comparison of knowledge, attitude, and practices in public and private high school children of Jeddah. Cureus. 2018;10(12).
- 107. Vazquez-Prokopec GM, Lenhart A, Manrique-Saide P. Housing improvement: a novel paradigm for urban vector-borne disease control? Trans R Soc Trop Med Hyg. 2016;110(10):567–9. pmid:27864518
- 108. Vernal S, Nahas AK, Chiaravalloti Neto F, Prete Junior CA, Cortez AL, Sabino EC, et al. Geoclimatic, demographic and socioeconomic characteristics related to dengue outbreaks in Southeastern Brazil: an annual spatial and spatiotemporal risk model over a 12-year period. Rev Inst Med Trop Sao Paulo. 2021;63:e70. pmid:34586304
- 109. Viennet E, Ritchie SA, Faddy HM, Williams CR, Harley D. Epidemiology of dengue in a high-income country: a case study in Queensland, Australia. Parasit Vectors. 2014;7:379. pmid:25138897
- 110. Viennet E, Ritchie SA, Williams CR, Faddy HM, Harley D. Public health responses to and challenges for the control of dengue transmission in high-income countries: four case studies. PLoS Negl Trop Dis. 2016;10(9):e0004943. pmid:27643596
- 111. Walker KR, Williamson D, Carrière Y, Reyes-Castro PA, Haenchen S, Hayden MH, et al. Socioeconomic and human behavioral factors associated with Aedes aegypti (Diptera: Culicidae) immature habitat in Tucson, AZ. J Med Entomol. 2018;55(4):955–63. pmid:29471405
- 112. Whiteman A, Delmelle E, Rapp T, Chen S, Chen G, Dulin M. A novel sampling method to measure socioeconomic drivers of Aedes albopictus distribution in Mecklenburg County, North Carolina. Int J Environ Res Public Health. 2018;15(10).
- 113. Wijayanti SPM, Porphyre T, Chase-Topping M, Rainey SM, McFarlane M, Schnettler E, et al. The importance of socio-economic versus environmental risk factors for reported dengue cases in Java, Indonesia. PLoS Negl Trop Dis. 2016;10(9):e0004964. pmid:27603137
- 114. Yalwala S, Kollars JW, Kasembeli G, Barasa C, Senessie C, Kollars PG, et al. Preliminary report on the reduction of adult mosquitoes in housing compounds in Western Kenya using the ProVector flower and Entobac bait pads containing Bacillus thuringiensis israelensis with honey bait. J Med Entomol. 2016;53(5):1242–4. pmid:27282815
- 115. Zellweger RM, Cano J, Mangeas M, Taglioni F, Mercier A, Despinoy M, et al. Socioeconomic and environmental determinants of dengue transmission in an urban setting: an ecological study in Nouméa, New Caledonia. PLoS Negl Trop Dis. 2017;11(4):e0005471. pmid:28369149
- 116. Abbas A, Abbas RZ, Khan JA, Iqbal Z, Hayat Bhatti MM, Sindhu Z-D. Integrated strategies for the control and prevention of dengue vectors with particular reference to Aedes aegypti. Pak Vet J. 2014;34(1).
- 117. Al-Abri SS, Kurup PJ, Al Manji A, Al Kindi H, Al Wahaibi A, Al Jardani A, et al. Control of the 2018-2019 dengue fever outbreak in Oman: a country previously without local transmission. Int J Infect Dis. 2020;90:97–103. pmid:31639520
- 118. Aldridge RL, Kline J, Coburn JM, Britch SC, Boardman L, Hahn DA, et al. Gamma-irradiation reduces survivorship, feeding behavior, and oviposition of female Aedes aegypti. J Am Mosq Control Assoc. 2020;36(3):152–60. pmid:33600583
- 119. Alfonso-Sierra E, Basso C, Beltrán-Ayala E, Mitchell-Foster K, Quintero J, Cortés S, et al. Innovative dengue vector control interventions in Latin America: what do they cost? Pathog Glob Health. 2016;110(1):14–24. pmid:26924235
- 120. Alvarado-Moreno MS, Laguna-Aguilar M, Rodriguez OSS, Sanchez-Casas RM, Ramirez-Jimenez R, Zarate-Nahón EA, et al. Potential community-based control by use of plastic film to block Aedes aegypti(L.) egg adhesion. Southwest Entomol. 2013;38(4):605–14.
- 121. Arduino M d B, Serpa LLN, Rangel O, Santos GV d. Evaluation of superabsorbent polymer (SAP) in oviposition traps used in the integrated control of Aedes aegypti (Linnaeus, 1762) and Aedes albopictus (Skuse, 1894) (Diptera: Culicidae). Rev Soc Bras Med Trop. 2023;56.
- 122. Aziz AT, Al-Shami SA, Mahyoub JA, Hatabbi M, Ahmad AH, Md Rawi CS. Promoting health education and public awareness about dengue and its mosquito vector in Saudi Arabia. Parasit Vectors. 2014;7:1–2.
- 123. Basso C, García da Rosa E, Romero S, González C, Lairihoy R, Roche I, et al. Improved dengue fever prevention through innovative intervention methods in the city of Salto, Uruguay. Trans R Soc Trop Med Hyg. 2015;109(2):134–42. pmid:25604764
- 124. Beech CJ, Vasan S, Quinlan MM, Capurro ML, Alphey L, Bayard V, et al. Deployment of innovative genetic vector control strategies: progress on regulatory and biosafety aspects, capacity building and development of best-practice guidance. Asia-Pac J Mol Biol Biotechnol. 2009;17(3):75–85.
- 125. Bouzid M, Brainard J, Hooper L, Hunter PR. Public health interventions for aedes control in the time of Zikavirus- a meta-review on effectiveness of vector control strategies. PLoS Negl Trop Dis. 2016;10(12):e0005176. pmid:27926934
- 126. Bowman LR, Donegan S, McCall PJ. Is dengue vector control deficient in effectiveness or evidence?: Systematic review and meta-analysis. PLoS Negl Trop Dis. 2016;10(3):e0004551. pmid:26986468
- 127. Cazola LH d O, Tamaki EM, Pontes ERJC, Andrade SMO d. The incorporation of activities to control dengue by community health agents. Rev Saúde Pública. 2014;48.
- 128. Chippaux J-P, Chippaux A. Yellow fever in Africa and the Americas: a historical and epidemiological perspective. J Venom Anim Toxins Incl Trop Dis. 2018;24:20. pmid:30158957
- 129. Claypool AL, Brandeau ML, Goldhaber-Fiebert JD. Prevention and control of dengue and chikungunya in Colombia: a cost-effectiveness analysis. PLoS Negl Trop Dis. 2021;15(12):e0010086. pmid:34965277
- 130. Coalson JE, Richard DM, Hayden MH, Townsend J, Damian D, Smith K, et al. Aedes aegypti abundance in urban neighborhoods of Maricopa County, Arizona, is linked to increasing socioeconomic status and tree cover. Parasit Vectors. 2023;16(1):351. pmid:37807069
- 131. Codeço CT, Lima AWS, Araújo SC, Lima JBP, Maciel-de-Freitas R, Honório NA, et al. Surveillance of Aedes aegypti: comparison of house index with four alternative traps. PLoS Negl Trop Dis. 2015;9(2):e0003475. pmid:25668559
- 132. Côrtes N, Lira A, Prates-Syed W, Dinis Silva J, Vuitika L, Cabral-Miranda W, et al. Integrated control strategies for dengue, Zika, and Chikungunya virus infections. Front Immunol. 2023;14:1281667. pmid:38196945
- 133. Dambach P, Louis VR, Standley CJ, Montenegro-Quiñonez CA. Beyond top-down: community co-creation approaches for sustainable dengue vector control. Glob Health Action. 2024;17(1):2426348. pmid:39514564
- 134. Dantés HG, Manrique-Saide P, Vazquez-Prokopec G, Morales FC, Siqueira Junior JB, Pimenta F, et al. Prevention and control of Aedes transmitted infections in the post-pandemic scenario of COVID-19: challenges and opportunities for the region of the Americas. Mem Inst Oswaldo Cruz. 2020;115:e200284. pmid:32785481
- 135. Dapari R, Muniandy K, Fattah Azman AZ, Abu Bakar S, Mohd Desa MN, Hwa LC, et al. Effectiveness of the Integrated Dengue Education and Learning (iDEAL) module in improving the knowledge, attitude, practice, environmental cleanliness index, and dengue index among schoolchildren: a randomised controlled trial protocol. PLoS One. 2024;19(4):e0302736. pmid:38687755
- 136. Diallo M, Dia I, Diallo D, Diagne CT, Ba Y, Yactayo S. Perspectives and challenges in entomological risk assessment and vector control of chikungunya. J Infect Dis. 2016;214(suppl 5):S459–65. pmid:27920174
- 137. Dusfour I, Vontas J, David J-P, Weetman D, Fonseca DM, Corbel V, et al. Management of insecticide resistance in the major Aedes vectors of arboviruses: advances and challenges. PLoS Negl Trop Dis. 2019;13(10):e0007615. pmid:31600206
- 138. Erlanger TE, Keiser J, Utzinger J. Effect of dengue vector control interventions on entomological parameters in developing countries: a systematic review and meta-analysis. Med Vet Entomol. 2008;22(3):203–21. pmid:18816269
- 139. Feng X, Jiang N, Zheng J, Zhu Z, Chen J, Duan L, et al. Advancing knowledge of One Health in China: lessons for One Health from China’s dengue control and prevention programs. Sci One Health. 2024;3:100087. pmid:39641122
- 140. Gunning CE, Okamoto KW, Astete H, Vasquez GM, Erhardt E, Del Aguila C, et al. Efficacy of Aedes aegypti control by indoor Ultra Low Volume (ULV) insecticide spraying in Iquitos, Peru. PLoS Negl Trop Dis. 2018;12(4):e0006378. pmid:29624581
- 141. Heinz S, Kolimenakis A, Horstick O, Yakob L, Michaelakis A, Lowery Wilson M. Systematic review: yellow fever control through environmental management mechanisms. Trop Med Int Health. 2021;26(11):1411–8. pmid:34455664
- 142. Hermann LL, Gupta SB, Manoff SB, Kalayanarooj S, Gibbons RV, Coller B-AG. Advances in the understanding, management, and prevention of dengue. J Clin Virol. 2015;64:153–9. pmid:25453329
- 143. Hladish TJ, Pearson CAB, Toh KB, Rojas DP, Manrique-Saide P, Vazquez-Prokopec GM, et al. Designing effective control of dengue with combined interventions. Proc Natl Acad Sci U S A. 2020;117(6):3319–25. pmid:31974303
- 144. Ho SH, Lim JT, Ong J, Hapuarachchi HC, Sim S, Ng LC. Singapore’s 5 decades of dengue prevention and control-Implications for global dengue control. PLoS Negl Trop Dis. 2023;17(6):e0011400. pmid:37347767
- 145. Kittayapong P, Thongyuan S, Olanratmanee P, Aumchareoun W, Koyadun S, Kittayapong R, et al. Application of eco-friendly tools and eco-bio-social strategies to control dengue vectors in urban and peri-urban settings in Thailand. Pathog Glob Health. 2012;106(8):446–54. pmid:23318236
- 146. Kurniawan W, Suwandono A, Widjanarko B, Suwondo A, Artama WT, Shaluhiyah Z, et al. The effectiveness of the One Health SMART approach on dengue vector control in Majalengka, Indonesia. JHR. 2020;35(1):63–75.
- 147. Lusno MFD, Haksama S, Yudhastuti R, Zubaidah S, Al Mamun A, Tarawally A, et al. The need for active and integrated involvement of the community and health professionals in the prevention and control of dengue hemorrhagic fever in Indonesia. Pan Afr Med J. 2024;47:185. pmid:39092020
- 148. Magalhães RC da S, Maio MC. The “Good Neighbor Policy for yellow fever”: cold war, the Aedes aegypti eradication program of the United States and international cooperation in health in the Americas. História. 2022;41.
- 149. Malijan RPB, Angeles JR, Apilado AMA, Ammugauan MAT, Salazar FV. Insecticide resistance in Aedes aegypti from the National Capital Region of the Philippines. Insects. 2024;15(10):782. pmid:39452358
- 150. Martinez-Cruz C, Arenas-Monreal L, Gomez-Dantes H, Villegas-Chim J, Gloria AB-F, Maria ET-R, et al. Educational intervention for the control of Aedes aegypti with Wolbachia in Yucatan, Mexico. Eval Program Plann. 2023;97.
- 151. McGregor BL, Connelly CR. A review of the control of Aedes aegypti (Diptera: Culicidae) in the continental United States. J Med Entomol. 2021;58(1):10–25. pmid:32829398
- 152. Mitchell-Foster K, Ayala EB, Breilh J, Spiegel J, Wilches AA, Leon TO, et al. Integrating participatory community mobilization processes to improve dengue prevention: an eco-bio-social scaling up of local success in Machala, Ecuador. Trans R Soc Trop Med Hyg. 2015;109(2):126–33. pmid:25604763
- 153. Mulderij-Jansen V, Pundir P, Grillet ME, Lakiang T, Gerstenbluth I, Duits A, et al. Effectiveness of Aedes-borne infectious disease control in Latin America and the Caribbean region: a scoping review. PLoS One. 2022;17(11):e0277038. pmid:36322603
- 154. Nikookar SH, Fazeli-Dinan M, Zaim M, Enayati A. Prevention and control policies of dengue vectors (Aedes aegypti and albopictus) in Iran. J Mazandaran Univ Med Sci. 2023;33(227):381–96.
- 155. Okunromade OF, Lokossou VK, Anya I, Dada AO, Njidda AM, Disu YO, et al. Performance of the public health system during a full-scale yellow fever simulation exercise in Lagos State, Nigeria, in 2018: how prepared are we for the next outbreak? Health Secur. 2019;17(6):485–94. pmid:31859573
- 156.
Pan American Health Organization. Technical document for the implementation of interventions based on generic operational scenarios for Aedes aegypti control. Washington (DC): PAHO; 2019.
- 157.
World Health Organization. Global strategy for dengue prevention and control 2012-2020. 2012.
- 158.
World Health Organization; UNICEF. Global vector control response 2017-2030. 2017.
- 159. Paploski IAD, Rodrigues MS, Mugabe VA, Kikuti M, Tavares AS, Reis MG, et al. Storm drains as larval development and adult resting sites for Aedes aegypti and Aedes albopictus in Salvador, Brazil. Parasit Vectors. 2016;9(1):419. pmid:27464886
- 160.
Parks W, Lloyd L, Nathan M, Hosein E, Odugleh A, Clark G, et al. International experiences in social mobilization and communication for dengue prevention and control. 2004.
- 161. Pollett S, Fauver JR, Maljkovic Berry I, Melendrez M, Morrison A, Gillis LD, et al. Genomic epidemiology as a public health tool to combat mosquito-borne virus outbreaks. J Infect Dis. 2020;221(Suppl 3):S308–18. pmid:31711190
- 162. Quintero J, Ronderos Pulido N, Logan J, Ant T, Bruce J, Carrasquilla G. Effectiveness of an intervention for Aedes aegypti control scaled-up under an inter-sectoral approach in a Colombian city hyper-endemic for dengue virus. PLoS One. 2020;15(4):e0230486. pmid:32236142
- 163. Rather IA, Kumar S, Bajpai VK, Lim J, Park Y-H. Prevention and control strategies to counter ZIKA epidemic. Front Microbiol. 2017;8:305. pmid:28293228
- 164. Reno E, Quan NG, Franco-Paredes C, Chastain DB, Chauhan L, Rodriguez-Morales AJ, et al. Prevention of yellow fever in travellers: an update. Lancet Infect Dis. 2020;20(6):e129–37. pmid:32386609
- 165. Ritchie SA, van den Hurk AF, Smout MJ, Staunton KM, Hoffmann AA. Mission accomplished? We need a guide to the “post release” world of wolbachia for Aedes-borne disease control. Trends Parasitol. 2018;34(3):217–26. pmid:29396201
- 166. Roiz D, Wilson AL, Scott TW, Fonseca DM, Jourdain F, Müller P, et al. Integrated Aedes management for the control of Aedes-borne diseases. PLoS Negl Trop Dis. 2018;12(12):e0006845. pmid:30521524
- 167. Ross PA. Designing effective Wolbachia release programs for mosquito and arbovirus control. Acta Trop. 2021;222:106045. pmid:34273308
- 168. Ruggerio CA, Querejeta GA, Conicelli KB, Lombardo RJ. Integration of municipal state, society and university efforts for sanitary risk prevention associated with Aedes aegypti mosquito in the metropolitan area of Buenos Aires, Argentina. Trop Med Int Health. 2021;26(7):789–99. pmid:33813766
- 169. Ryan PA, Turley AP, Wilson G, Hurst TP, Retzki K, Brown-Kenyon J. Establishment of wMel Wolbachia in Aedes aegypti mosquitoes and reduction of local dengue transmission in Cairns and surrounding locations in northern Queensland, Australia. Gates Open Res. 2019;3.
- 170. Saadatian-Elahi M, Alexander N, Möhlmann T, Langlois-Jacques C, Suer R, Ahmad NW, et al. Measuring the effectiveness of integrated vector management with targeted outdoor residual spraying and autodissemination devices on the incidence of dengue in urban Malaysia in the iDEM trial (intervention for Dengue Epidemiology in Malaysia): study protocol for a cluster randomized controlled trial. Trials. 2021;22(1):374. pmid:34053466
- 171. Sanchez L, Perez D, Cruz G, Castro M, Kourí G, Shkedy Z, et al. Intersectoral coordination, community empowerment and dengue prevention: six years of controlled interventions in Playa Municipality, Havana, Cuba. Trop Med Int Health. 2009;14(11):1356–64. pmid:19840350
- 172. Sim S, Ng LC, Lindsay SW, Wilson AL. A greener vision for vector control: The example of the Singapore dengue control programme. PLoS Negl Trop Dis. 2020;14(8):e0008428. pmid:32853197
- 173. Staunton KM, Yeeles P, Townsend M, Nowrouzi S, Paton CJ, Trewin B, et al. Trap location and premises condition influences on Aedes aegypti (Diptera: Culicidae) catches using biogents sentinel traps during a “rear and release” program: implications for designing surveillance programs. J Med Entomol. 2019;56(4):1102–11. pmid:30817823
- 174. Stone CM, Schwab SR, Fonseca DM, Fefferman NH. Human movement, cooperation and the effectiveness of coordinated vector control strategies. J R Soc Interface. 2017;14(133):20170336. pmid:28855386
- 175. Tabachnick WJ. Climate change and the arboviruses: lessons from the evolution of the dengue and yellow fever viruses. Annu Rev Virol. 2016;3(1):125–45. pmid:27482902
- 176. Taborda A, Chamorro C, Quintero J, Carrasquilla G, Londoño D. Cost-effectiveness of a dengue vector control intervention in Colombia. Am J Trop Med Hyg. 2022;107(1):180.
- 177. Tambo E, El Dessouky AG, Khater EIM. Innovative preventive and resilience approaches against aedes-linked vector-borne arboviral diseases threat and epidemics burden in gulf council countries. Oman Med J. 2019;34(5):391–6. pmid:31555414
- 178. Tissera H, Pannila-Hetti N, Samaraweera P, Weeraman J, Palihawadana P, Amarasinghe A. Sustainable dengue prevention and control through a comprehensive integrated approach: the Sri Lankan perspective. WHO South East Asia J Public Health. 2016;5(2):106–12. pmid:28607237
- 179. Toledo ME, Rodriguez A, Valdés L, Carrión R, Cabrera G, Banderas D, et al. Evidence on impact of community-based environmental management on dengue transmission in Santiago de Cuba. Trop Med Int Health. 2011;16(6):744–7. pmid:21418448
- 180. Trewin BJ, Montgomery BL, Hurst TP, Gilmore JS, Endersby-Harshman NM, Crisp GJ. Extensive public health initiatives drive the elimination of Aedes aegypti (Diptera, Culicidae) from a town in regional Queensland: a case study from Gin Gin, Australia. PLoS Negl Trop Dis. 2022;16(4):e0010243. pmid:35395009
- 181. Uchenna Emeribe A, Nasir Abdullahi I, O R Ajagbe O, Egede Ugwu C, Oloche Onoja S, Dahiru Abubakar S, et al. Incidence, drivers and global health implications of the 2019/2020 yellow fever sporadic outbreaks in Sub-Saharan Africa. Pathog Dis. 2021;79(4):ftab017. pmid:33739369
- 182. Ulibarri G, Betanzos A, Betanzos M, Rojas JJ. Preliminary results on the control of Aedes spp. in a remote Guatemalan community vulnerable to dengue, chikungunya and Zika virus: community participation and use of low-cost ecological ovillantas for mosquito control. F1000Research. 2016;5:598. pmid:28105304
- 183. Umoke PCI, Umoke M, Eyo N, Ugwu Mbbs A, Okeke E, Nwalieji CA, et al. Delay in health-seeking behaviour: implication to yellow fever outcome in the 2019 outbreak in Nigeria. Health Soc Care Community. 2021;29(3):703–11. pmid:33761167
- 184. Wilder-Smith A, Tissera H, AbuBakar S, Kittayapong P, Logan J, Neumayr A, et al. Novel tools for the surveillance and control of dengue: findings by the DengueTools research consortium. Glob Health Action. 2018;11(1):1549930. pmid:30560735
- 185. Xue L, Ren X, Magpantay F, Sun W, Zhu H. Optimal control of mitigation strategies for dengue virus transmission. Bull Math Biol. 2021;83(2):8. pmid:33404917