Dengue is the most important and fastest growing arboviral disease world-wide. An estimated 50-100 million people are affected each year 1, and between 1990 and 2020, global burden more than doubled each decade 2. There is no widespread commercially available vaccine for dengue, and so mitigation primarily relies on mosquito control 3. Mosquito control resources are limited, and overuse of insecticides causes resistance, forcing many public health programs to target their control efforts in time and space towards areas with an elevated risk of dengue infection. If dengue outbreaks can be identified in the very early stages, efforts can be well-targeted, significantly reducing infection rates 4. If risk cannot be predicted, control becomes reactive rather than preventative, which can lead to a failure to reduce dengue infection 4. This importance of early detections has incentivized efforts towards creating accurate dengue outbreak models and risk maps.
Despite the strong incentive, dengue risk mapping has achieved variable success5. Dengue is spatially explicit and highly dependent on the environment and the immunological profile of the human population, creating complex transmission persistence and dispersal patterns 6. Therefore, dengue transmission shifts dynamically across space and time, complicating the ability to determine reliable predictors. Spatial scale is also a complicating factor. For example, weather is often a primary predictor in dengue models, yet these parameters are often only measured on a homogenous, city-wide scale.
Human mobility has gained increasing recognition as a driver of fine-scale dengue risk. The primary vector of dengue, Aedes aegypti, is a short-distance flier 7, and so the diffusion and spatial variability of dengue across both short and long distances is mediated by human movement 8. Within a single city, human social networks and daily movement have been shown to predict clusters of dengue infections 9, and in one study, control via tracing social contacts of infected people effectively reduced dengue 10. In another study, distance to a metro station predicted the clustering of dengue cases over two epidemic years in Singapore 11, suggesting that dengue can be tied to hubs of human transport within the space of a city. While lower socioeconomic status has also been tied to dengue incidence in some cases, this effect is highly inconsistent across studies (reviewed in 12 and 13). This suggests that it may not be socioeconomic status itself affecting transmission, but other factors that may result from it.
We analyzed dengue cases in Medellín, Colombia during an eight-year period of rapid development of the city’s Metro system. We explored how the construction of public transit infrastructure targeted towards low socioeconomic status regions and the resulting changes in human mobility affected the fine-scale spatial distribution of dengue incidence. Medellín is a perfect test-case to understand the impacts of growing urban infrastructure and public transit on dengue because 1) seasonality is limited, with a stable climate year-round, minimizing noise from climatic drivers of dengue transmission 14) Medellín has undergone a period of rapid infrastructure growth, including the construction of new public transit lines. This allows for comparison of the spatial structure of dengue before and after the addition of each new line; 3) Medellín has collected probable dengue health care facility case records since 2008, and each case is recorded to the patient’s home address, enabling analysis at a fine spatial scale; 4) Medellín surveyed city-wide human mobility patterns in 2011 and 2016 so we can quantify the use of public transit systems across space to understand its impact on dengue; and 5) Medellin´s neighborhoods are classified based on their socioeconomic strata into six different classes, strata six representing the highest income group, and one the lowest. And there are both areas of high and low socioeconomic status with and without accessible public transit lines throughout the study period.
Medellín is situated in a valley surrounded by mountains. The flat center is primarily industrial and commercial, while more residential neighborhoods are in the steep perimeter. Historically, low socioeconomic status residents of mountainous parts of the city had extremely limited mobility 15, 16, 17. Many residents of the high-elevation, high-socioeconomic status regions can travel by personal vehicle or taxi, but for residents of low socioeconomic status regions without the same resources, accessing a job in the industrial center would have required finding a means to traverse up to 600 meters in elevation gain. To improve the public transportation system of residents in Medellin, particularly in locations where topography limits the way to move, Medellín Metro system was inaugurated in 1994 with a goal of providing mobility to low socioeconomic status residents of mountainous regions 15, 16, 17. The metro system expanded between 1994 and 2016 to become more accessible and increasingly utilized by larger portions of the city. Medellín has a year-round tropical climate with average temperatures between 21°C and 25°C 14, and Ae. aegypti and recently Ae. albopictus have been established across the city18. Medellín is endemic for all four dengue serotypes19. Dengue has been a notifiable disease in Colombia since 2008, and in Medellín, all cases diagnosed by a physician that meet the WHO case definition 3 are reported as probable dengue cases along with each patient’s demographic information and home address (Medellín Secretaría de Salud, pers comm).
We conducted a retrospective geospatial analysis of dengue cases in Medellín between 2008 and 2016 to understand the effects of the construction of public transit infrastructure and resulting changes in human mobility and socioeconomic status on fine-scale spatial heterogeneity in dengue risk while accounting for socioeconomic status. We determined if regions of the city that are closer to public transit lines and that have a higher percentage of public transit ridership had higher dengue incidence and analyzed how this effect is modulated by socioeconomic status.