Abstract

Author summary

Citation: Salazar Flórez JE, Restrepo BN, Freitas LP, Carabali M, Jaramillo Ramírez GI, Balaguera CG, et al. (2025) Spatio-temporal analysis of the distribution and co-circulation of dengue, chikungunya, and Zika in Medellín, Colombia, from 2013 to 2021. PLoS Negl Trop Dis 19(9): e0013470. https://doi.org/10.1371/journal.pntd.0013470

Editor: Jennifer K. Peterson, University of Delaware, UNITED STATES OF AMERICA

Received: October 31, 2024; Accepted: August 10, 2025; Published: September 5, 2025

Copyright: © 2025 Salazar Flórez 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: The study is based on publicly accessible secondary data sources. Case data for dengue, chikungunya, and Zika can be obtained from the SIVIGILA platform (https://portalsivigila.ins.gov.co/), while population statistics are available through the Colombian National Administrative Department of Statistics (https://www.dane.gov.co/). The processed datasets used in the analyses are openly available at https://github.com/jemilios/Spatiotemporal.

Funding: This work was supported by a grant from the Canadian Institutes of Health Research (https://cihr-irsc.gc.ca/, grant number 428107) to K.Z. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Competing interests: The authors have declared that no competing interests exist.

Introduction

Recently, vector-borne diseases, especially dengue, chikungunya, and Zika, have become a significant global public health concern [1]. Dengue alone accounts for approximately 390 million new cases worldwide each year [2]. However, about 75% of these cases remain asymptomatic and are not reported in the official surveillance records [2]. A recent global meta-analysis estimated that approximately 59% (95% CI: 44–75%) of dengue infections are asymptomatic, with higher proportions during outbreak periods [3,4]. For chikungunya, evidence from systematic reviews and serosurveys indicates that about 25%–40% of infections show no clinically recognizable symptoms [5]. Zika virus infections are also largely silent, with pooled estimates indicating around 59% of infections are asymptomatic, though individual studies range from 33% to 88% [6]. Nearly 96 million infections present symptoms annually, requiring health system intervention [7]. Latin America is one of the hardest-hit regions, representing 14% of all global cases [8].

Zika and chikungunya are less prevalent but have led to significant epidemics, causing lasting impacts in affected regions. Zika virus has been linked to various neurological complications, including microcephaly in children born to individuals infected during pregnancy [9]. There have been reports of locally transmitted cases in 89 countries since its discovery in 1952 [10], with epidemic outbreaks notably in 2013 and 2015 in the Western Pacific [11] and the Americas [12,13], respectively, reporting up to 30,000 cases annually. Currently, 61 countries have reported no cases of the disease despite the continued presence of the Aedes aegypti vector [10].

Chikungunya, similar to Zika, has expanded vastly in recent decades, with a significant increase in Asia, Africa, and America [14–16]. Chikungunya was identified in Cambodia in 1961. Initial outbreaks were recorded in Kenya and the Comoros Islands in 2004 for Africa [15]. It resurfaced in Sri Lanka in 2007 with over 37,000 suspected cases [14]. Europe recorded 205 cases in Italy in 2007 [17]. By 2010, France, too, had local transmission cases [18]. In December 2013, the first outbreaks in the Americas were identified, and by December 2015, nearly one million cases were reported [19].

In Latin America, these arboviruses have had a critical epidemiological impact. Chikungunya, introduced in 2013, peaked in 2015, accounting for nearly one million cases and 7,126 confirmed deaths [20,21]. For Zika, after the first case in the Americas was reported in Chile in March 2014, the virus spread swiftly across the continent, severely affecting Brazil and Colombia, with the highest incidence peaks occurring in 2015 and 2016 [22]. For instance, dengue peaked in 2019 with over 3.1 million cases and approximately 1,534 confirmed deaths [23].

In Colombia, these diseases continue to pose a significant public health challenge. The country ranks as the second-highest in terms of Zika cases in Latin America [24], and dengue is endemic throughout the nation, with an average of over 50,000 reported cases annually [25]. Both Chikungunya and Zika primarily spread from regions along the Atlantic coast and southwest to other parts of the country [26,27]. The arbovirus situation highlights the need to understand their spatial patterns, which will help us better understand their distribution [26,28].

Medellín is Colombia’s second-largest city and one of the most urbanized and densely populated municipalities in the country, with over 2.5 million inhabitants concentrated in 376 km2. Its tropical sub-humid climate, altitude between 1,500 and 1,800 meters, and persistent presence of Aedes aegypti mosquitoes create optimal ecological conditions for arbovirus transmission, including dengue, chikungunya, and Zika [29–31]. Previous studies conducted in Colombian cities have shown that arboviruses such as dengue, chikungunya, and Zika exhibit heterogeneous patterns of transmission at the intra-urban level. In Medellín, the distribution of cases has historically concentrated in neighborhoods with high population density, poor housing conditions, and limited access to public services.

In recent decades, Medellín has experienced cyclical outbreaks of dengue and was one of the earliest urban epicenters for chikungunya (2014) and Zika (2015) introduction in Colombia [25–27,32]. Furthermore, the city’s marked socioeconomic heterogeneity across comunas and neighborhoods allows for the study of health inequities in disease distribution, as lower-income areas often face higher entomological risk due to poor water storage and limited vector control coverage [33,34]. Conducting a fine-scale spatio-temporal analysis in Medellín is relevant not only to guide local interventions but also because the city serves as a model for arboviral dynamics in rapidly urbanizing tropical settings.

Understanding the spatio-temporal dynamics of these arboviruses is paramount for discerning propagation patterns and shaping effective control and prevention strategies [35,36]. Arboviruses are not uniformly distributed in time or space; certain geographical areas may be more susceptible due to environmental factors—such as temperature, rainfall, and urban infrastructure—that favor the proliferation of vector mosquitoes, as well as societal factors like population density and health practices [37–39]. Moreover, distinct temporal transmission patterns exist, with certain times of the year or cycles over multiple years indicating higher disease incidences. Acknowledging these transmission hotspots could enhance future outbreak predictions, enabling targeted resource allocation for prevention and control efforts [26,40].

This study aims to provide a detailed description of the spatio-temporal clustering of dengue, chikungunya, and Zika in Medellín from 2013 to 2021. Rather than seeking generalizable associations or predictive patterns, our objective is to generate fine-scale evidence to support local decision-making and to inform future analytic studies exploring the structural and ecological determinants of arboviral transmission in urban settings.

Methods

Results

Discussion

Our study shows that dengue, chikungunya, and Zika co-circulated between September 2015 and February 2017 in Medellín. We found 5 clusters for dengue that peaked in 2015 and 2016, with evidence cyclical virus. For chikungunya and Zika, we found 4 clusters with peak incidence in 2015 and 2016, respectively. Our results indicate that high-risk clusters were concentrated in the city’s downtown, and northeastern Comunas.

Dengue cases showed no consistent peaks pattern in the visual time series, but exhibited cyclical peaks approximately every two to three years. Between 2013 and 2021, Medellín averaged 137.3 dengue cases per 100,000 inhabitants annually. Another spatio-temporal study in Medellín covering 2007–2017 reported a similar trend, characterized by cyclical dengue outbreaks every 2–3 years and concentrated incidence peaks, consistent with the temporal pattern observed in our analysis [34]. Colombia experienced significant outbreaks in 2010, 2013, and 2015, with around 150,000 cases each year [47,48], and 127,925 cases were reported in 2023, exceeding the 2015 (96.844 cases) epidemic by 32.0% [49]. Other Colombian places, such as Ibague, Cali, and Bucaramanga, also showed significant outbreaks in 2013, 2015, and early 2016 [50–53]. The cases in Medellín mirrors those observed in Colombia and other Latin American countries, such as Brazil, where cities like Rio de Janeiro reported high incidences between 2011–2013 and 2015–2016 [54,55]. In our study, this behavior was evident up to 2016, after which dengue incidence remained low and irregular.

As expected, following its introduction in 2014, Chikungunya exhibited a sharp initial epidemic in 2015, followed by a steep decline in reported cases after 2016 [26]. High Zika incidence was reported in densely populated, lower-altitude municipalities in Colombia with lower weekly rainfall compared to other endemic areas [56]. While Medellín does not have particularly low rainfall, its high population density and favorable ecological conditions for Aedes aegypti may have contributed to the observed transmission. Between 2013 and 2021, Medellín had an average annual chikungunya rate of 5.1 cases per 100,000 inhabitants [26]. A national study reported increased chikungunya and Zika incidence in Colombia’s Andean region between 2014 and 2017 [57], which coincides temporally with the epidemic peaks observed in Medellín. Colombia and Venezuela reported the highest incidence rates in the Andean subregion between 2016 and 2020 [58]. Differences in incidence patterns reported across studies, time periods, and regions may be explained by diagnostic challenges, underreporting, vector adaptability, population immunity, and environmental conditions [26,34,37,55,59–61]. The year 2016 represents a critical point in the analysis, as it corresponds to the highest reported incidence of dengue, chikungunya, and Zika in Medellín, marking the period of greatest co-circulation and overlapping transmission of the three arboviruses.

Vector dynamics, including their density and adaptation to urban conditions, play a key role in shaping arbovirus transmission patterns over time and space [62]. Monitoring vector behavior and assessing the risk of transmission through entomological indices are crucial in this process. In 2022, in the department of Antioquia—where Medellín is located—entomological risk levels for Aedes aegypti based on the household positivity index classified eight municipalities as high or medium risk, while 41 were considered low risk [63]. A study between 2013–2015 in Medellín showed that neighborhoods with a higher incidence of dengue had a significant number of households storing water (OR: 1.69; 95% CI 1.11; 2.57) and more homes with adult mosquitoes (OR: 2.13; 95% CI 1.29; 3.50) [33].

As previously mentioned, dengue incidence in Medellín has historically shown peaks every two to three years. However, a visual inspection of reported case data suggests a decline in incidence from 2017 to 2022, though no formal trend analysis was performed. Other studies have shown a reduction in the incidence of dengue in the city, particularly in 2020 and 2022 [64,65]. This decline could be partially explained by the introduction of Wolbachia into Aedes aegypti mosquitoes, aimed at reducing their ability to transmit dengue and other arboviruses. In Medellín, Wolbachia-infected mosquitoes were released progressively across different comunas between October 2016 and April 2022 [65]. Given that not all areas were covered simultaneously, this intervention may have influenced the spatial distribution and intensity of dengue clusters, contributing to the observed decline in incidence [65]. However, the pandemic may have overshadowed cases and complicated the surveillance of other febrile illnesses [66–68]. However, in 2023 and 2024 an increased number of dengue cases were reported in the region [69].

We identified five dengue clusters that emerged between 2015 and 2016, coinciding with one of the highest peaks in dengue incidence in the time series. Although the scan statistic does not directly assess periodicity, the temporal concentration of these clusters —together with historical outbreak records and visual inspection of incidence trends— suggests a cyclical transmission pattern, with peaks occurring approximately every two to three years. On average, dengue clusters lasted 55 weeks, compared to 10.5 weeks for chikungunya and 34 weeks for Zika. These durations differ from those reported in other settings; for instance, an analysis in the department of Cauca found dengue clusters lasting one to two years [51], while a national study reported average durations of 25 weeks for dengue, 19.5 weeks for chikungunya, and 14 weeks for Zika [26]. Such variation may reflect differences in geographic scale (municipality vs. neighborhood), timing of virus introduction, population immunity, and the unique urban transmission dynamics in Medellín. These comparisons provide valuable context for understanding the intensity and persistence of arboviral clustering in large urban centers.

Our findings indicate that several high-risk clusters occurred in the northeastern comunas of Medellín, areas characterized by high population density and socioeconomic disadvantage. This pattern is consistent with national and local studies showing that arboviruses -whether circulating individually or concurrently- are more prevalent in marginalized urban settings [26]. A previous study conducted between 2008 and 2011 identified the southwestern zone of Medellín, particularly the Belén neighborhood, as a hotspot for dengue outbreaks [70]. However, more recent data suggest a spatial shift toward the northeast, where living conditions remain poor. This shift is supported by recent research highlighting a concentration of arboviral cases in the northeastern comunas [34], in line with the clusters identified in our study and reinforcing the link between socioeconomic vulnerability and arboviral burden in the city [52]. Similarly, a study in Bucaramanga identified four critical clusters, with notable differences in dengue risk between urban core and suburban areas [53]. At the national level, seven clusters with co-circulation of arboviruses were reported, along with 21, 16, and 13 individual clusters for dengue, chikungunya, and Zika, respectively [26].

The co-circulation of dengue, chikungunya, and Zika is a recognized phenomenon in Latin America [36,37,39,54,71,72]. In Medellín, multivariate clusters were concentrated in northeastern comunas, likely influenced by socioeconomic factors such as high population density, poor housing, irregular water access, and limited vector control. Although the three viruses share Aedes aegypti as a common vector, simultaneous clustering was not uniform across the city. This may reflect differences in virus introduction dengue being endemic, while chikungunya and Zika emerged in 2014 and 2015 [24] as well as local variation in immunity, vector density, mobility, and interventions like Wolbachia [65]. These findings suggest that arbovirus clustering is shaped by overlapping social, environmental, and biological factors, rather than occurring at random.

Socioeconomic, environmental, and biological factors appear to shape the co-circulation of arboviruses in Medellín. The viruses primarily emerged in socioeconomically disadvantaged neighborhoods, particularly in the northeastern comunas of the city. Prior studies have shown that the areas identified as high-risk clusters exhibit low living condition indices, often with composite scores below 40 on a 0–100 scale, where lower values denote poorer access to health services, education, housing, and employment opportunities [33,34]. An exception is the Buenos Aires district, where 59% of the population belongs to the upper-middle socioeconomic stratum and the living condition index approaches 50 [73]. However, the presence of arbovirus clusters in this area may be attributed to its high population density and substantial intra-urban mobility, which can facilitate viral transmission even in neighborhoods with relatively better socioeconomic indicators.

The co-circulation of dengue, chikungunya, and Zika in Medellín was predominantly concentrated in northeastern comunas, characterized by high population density, poor housing conditions, and limited public service access. In neighborhoods such as Santa Cruz and La Candelaria, where all three viruses overlapped, the affected areas ranged from 2.2 km2 to 7.36 km2, with population densities reaching up to 447,542.6 inhabitants in Popular [73]. These conditions likely facilitate viral transmission and complicate vector control efforts and healthcare access. Similar patterns have been observed in other Colombian cities —such as Cali— where dengue outbreaks have been linked to socioeconomic and environmental factors like limited piped water, poor waste disposal, and overcrowding [74], and in Bucaramanga, where cluster risk varied across urban and suburban zones [50,51]. Comparable evidence from Fortaleza (Brazil) and Mexico confirms that arboviral transmission disproportionately affects low-income populations with limited access to basic services [34,59].

Another crucial factor is climate variables, such as temperature and rainfall, which have been shown to impact the transmission of dengue, chikungunya, and Zika [37,59,71]. Although this study focuses on an intra-urban setting, and broad climatic conditions may be relatively stable, we acknowledge that Medellín’s complex topography may lead to local microclimatic variations that could influence arbovirus transmission. It’s essential to consider the growing adaptability of the vector to higher altitudes in the Andean region, which may have implications for transmission in mountainous areas of Medellín [58]. It was determined that over fifty years, the city of Medellín experienced climate change, with an increase in the average temperature of 0.8°C, a rise of 1.3°C in the minimum temperature, a 0.5°C increase in the maximum temperature, and a downward trend in relative humidity, with an average decrease of 2.3% [75]. It is important to note that the cited study reports climatic trends in Medellín up to 2010 [75], and conditions have likely changed in the past 15 years due to ongoing urban expansion and climate dynamics. These changes —such as rising temperatures and decreasing humidity— may enhance the adaptability of Aedes aegypti to higher altitudes, potentially expanding its ecological niche and contributing to arbovirus transmission in previously unaffected areas of Medellín [57].

From a public health perspective, identifying high-risk clusters of arbovirus transmission at the intra-urban level enables more efficient allocation of resources for vector control, surveillance, and community engagement [24,60,61,76]. The spatial overlap of multivariate clusters with socioeconomically disadvantaged areas suggests that interventions should be tailored to specific local contexts [28,60]. To enhance the explanatory power and actionability of these findings, future studies should incorporate additional variables such as rainfall, temperature, entomological indices, housing quality, and mobility patterns to model the drivers of clustering and guide integrated control strategies.

A key limitation of this study is the reliance on routine surveillance data, which includes both probable and confirmed cases. Given the overlapping clinical presentations of dengue, chikungunya, and Zika, particularly in the absence of laboratory confirmation, misclassification is likely and may have influenced the spatial and temporal patterns observed. Most cases were identified based on clinical suspicion, with only a small proportion confirmed by ELISA or PCR testing. Additionally, many individuals with mild or asymptomatic infections may not have sought medical care, contributing to underreporting and limiting the representativeness of the dataset, which only reflects those who accessed healthcare services [61]. These limitations are compounded by the absence of seroprevalence studies in Medellín, which restricts our ability to validate findings or estimate the true burden of infection and extent of underreporting.

Part of the data collection also coincided with the COVID-19 pandemic, during which febrile illnesses may have been misattributed to SARS-CoV-2, further complicating accurate diagnosis and surveillance of arboviral infections. While case location was based on residential address rather than place of infection, this georeferencing remains valuable for public health planning, as interventions are typically implemented at the community level.

Methodologically, the use of Kulldorff’s space-time scan statistic introduces additional considerations. This approach assumes a discrete Poisson distribution and circular spatial scanning windows, which may not fully capture irregularly shaped clusters or adjust for potential confounders such as environmental or demographic variables. Cluster detection is also sensitive to the selection of scanning parameters, which may influence the size and significance of identified clusters. Additionally, the study’s ecological design limits causal inference at the individual level, and interpretations of temporal trends and seasonality were based solely on descriptive visual analysis, without formal statistical modeling or seasonal decomposition. Finally, although the observed concentration of clusters in northeastern districts aligns with prior reports of higher vulnerability in these areas, this was not a pre-specified hypothesis in our design and did not arise from our analytical model. We suggest that future studies explicitly investigate the structural and ecological factors behind this apparent spatial inequality.

Nonetheless, these findings provide a valuable overview of the situation of these diseases in Medellín and demonstrate the importance of individualizing their study, enhancing their understanding, and generating insights for their control. The study captured the emergence of dengue, chikungunya, and Zika in Medellín, highlighting the importance of understanding the spatio-temporal patterns of both emerging and endemic diseases. Furthermore, the study analyzed spatio-temporal patterns at a fine scale and neighborhood level, providing valuable insights for understanding disease patterns and effectively targeting interventions. Unlike broader regional studies, our results provide comuna-level evidence of co-circulation patterns and spatial heterogeneity within a single city, offering a finer scale of analysis.

While the present analysis does not include modeling of cluster determinants or forecasting techniques, it provides a high-resolution description of arboviral clustering patterns within a complex urban setting. For chikungunya and Zika, the clusters identified correspond to their respective introduction-driven epidemics and may not be reproducible in the absence of reintroduction. However, for dengue —which remains endemic in Medellín— we observed recurrent clusters over time, suggesting spatial persistence of transmission risk in certain areas. Although these results do not directly predict future outbreaks, they can guide targeted vector control in historically high-risk neighborhoods. Future studies should build on this work by incorporating explanatory variables and evaluating cluster stability across multiple epidemic cycles to improve prediction and prevention strategies.

In conclusion, this study provides a detailed characterization of the spatio-temporal dynamics and co-circulation patterns of dengue, chikungunya, and Zika in Medellín, Colombia, between 2013 and 2021. While the findings are not intended to be extrapolated beyond this specific urban context or to future epidemic scenarios, they offer relevant evidence for local decision-makers to guide vector control and surveillance efforts. The recurrent detection of high-risk clusters for dengue in northeastern districts suggests persistent vulnerabilities that require sustained attention. This localized analysis may also serve as a methodological reference for other hyperendemic cities seeking to better understand and respond to arboviral transmission at the intra-urban scale.

Supporting information

Acknowledgments

We extend our thanks to the Medellín Health Department for their thematic guidance and access to the data.

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