Landscapes of healthcare utilization during a dengue fever outbreak in an urban environment of Colombia

Casas, Irene; Delmelle, Eric

doi:10.1007/s10661-019-7415-2

Cited by 10 publications

(6 citation statements)

References 47 publications

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“…Several articles examining patterns of DENF in Colombia have recognized outdated population census being a critical issue that could affect the findings of their research. [73][74][75][76][77][78] Until more recent census are available, different population growth models could address this issue, or relying on disaggregated population projection, using dasymetric mapping. 79,80 Third, including vector surveillance data (presence/absence) in each neighborhood would improve the accuracy of the relative risk estimates.…”

Section: Discussionmentioning

confidence: 99%

Space–Time Conditional Autoregressive Modeling to Estimate Neighborhood-Level Risks for Dengue Fever in Cali, Colombia

Desjardins

Eastin

Paul

et al. 2020

The American Journal of Tropical Medicine and Hygiene

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Vector-borne diseases affect more than 1 billion people a year worldwide, causing more than 1 million deaths, and cost hundreds of billions of dollars in societal costs. Mosquitoes are the most common vectors responsible for transmitting a variety of arboviruses. Dengue fever (DENF) has been responsible for nearly 400 million infections annually. Dengue fever is primarily transmitted by female Aedes aegypti and Aedes albopictus mosquitoes. Because both Aedes species are peri-domestic and container-breeding mosquitoes, dengue surveillance should begin at the local level-where a variety of local factors may increase the risk of transmission. Dengue has been endemic in Colombia for decades and is notably hyperendemic in the city of Cali. For this study, we use weekly cases of DENF in Cali, Colombia, from 2015 to 2016 and develop space-time conditional autoregressive models to quantify how DENF risk is influenced by socioeconomic, environmental, and accessibility risk factors, and lagged weather variables. Our models identify high-risk neighborhoods for DENF throughout Cali. Statistical inference is drawn under Bayesian paradigm using Markov chain Monte Carlo techniques. The results provide detailed insight about the spatial heterogeneity of DENF risk and the associated risk factors (such as weather, proximity to Aedes habitats, and socioeconomic classification) at a fine level, informing public health officials to motivate at-risk neighborhoods to take an active role in vector surveillance and control, and improving educational and surveillance resources throughout the city of Cali.

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Section: Discussionmentioning

confidence: 99%

Space–Time Conditional Autoregressive Modeling to Estimate Neighborhood-Level Risks for Dengue Fever in Cali, Colombia

Desjardins

Eastin

Paul

et al. 2020

The American Journal of Tropical Medicine and Hygiene

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“…43 Improvements in access to hospitals might encourage dengue patients to seek care, a trend observed in Cali, Colombia. 44,45 In recent years, Colombia has improved its transportation system throughout the country, and crime and violence have gone down, causing Colombia's tourism to increase and potentially the spread of dengue. 46,47 In Asia, Tien et al demonstrated increased air travel playing a large role in the dispersal of dengue virus, and similar conclusions were found in Brazil, which also demonstrated the additional role of the development of roads around a city.…”

Section: Discussionmentioning

confidence: 99%

Surveillance and Epidemiology of Dengue in Medellín, Colombia from 2009 to 2017

Warnes

Santacruz-Sanmartín

Carrillo

et al. 2021

The American Journal of Tropical Medicine and Hygiene

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Dengue is the most prevalent arthropod-borne viral disease in humans, primarily transmitted by the Aedes aegypti mosquito. We conducted a descriptive analysis of dengue cases from 2009 to 2017 in Medellín, Colombia, using data available from the Secretariat of Health. We analyzed the burden of outbreak years on the healthcare system, risk of cases exhibiting severe illness, potential disease surveillance problems, gender and age as risk factors, and spatiotemporal patterns of disease occurrence. Our data consisted of 50,083 cases, separated based on whether they were diagnostic test negative, diagnostic test positive (primarily IgM ELISA), clinically confirmed, epidemiologically linked, or probable. We used dengue incidence to analyze epidemiological trends between our study years, related to human movement patterns, between gender and age-groups, and spatiotemporally. We used risk to analyze the severity of dengue cases between the study years. We identified human movement could contributed to dengue spread, and male individuals (incidence rate: 0.86; 95% CI: 0.76–0.96) and individuals younger than 15 years (incidence rate: 1.24; 95% CI: 1.13–1.34) have higher incidence of dengue and located critical parts of the city where dengue incidence was high. Analysis was limited by participant diagnostic information, data concerning circulating strains, and a lack of phylogenetic information. Understanding the characteristics of dengue is a fundamental part of improving the health outcomes of at-risk populations. This analysis will be useful to support studies and initiatives to counteract dengue and provide context to the surveillance data collected by the health authorities in Medellín.

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“…While global assessments of healthcare access and quality have been developed [22], implementing these principles at a local level, for multiple countries simultaneously, has not been addressed. Furthermore, the quantified travel times are not always the actual traveled route to care, as persons may pursue alternative paths to access a health facility, including cross-border travel [58], or chose an alternate facility aside from the closest facility [59, 60], particularly during emergencies [61]. In some instances, while a facility may be available, individuals could already be too ill to travel and are treated at home, or seek non-facility-based forms of healthcare provisioning such as traditional healers [62].…”

Section: Discussionmentioning

confidence: 99%

Travel time to health facilities in areas of outbreak potential: maps for guiding local preparedness and response

Hulland

Wiens

Shirude

et al. 2019

BMC Med

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BackgroundRepeated outbreaks of emerging pathogens underscore the need for preparedness plans to prevent, detect, and respond. As countries develop and improve National Action Plans for Health Security, addressing subnational variation in preparedness is increasingly important. One facet of preparedness and mitigating disease transmission is health facility accessibility, linking infected persons with health systems and vice versa. Where potential patients can access care, local facilities must ensure they can appropriately diagnose, treat, and contain disease spread to prevent secondary transmission; where patients cannot readily access facilities, alternate plans must be developed. Here, we use travel time to link facilities and populations at risk of viral hemorrhagic fevers (VHFs) and identify spatial variation in these respective preparedness demands.Methods and findingsWe used geospatial resources of travel friction, pathogen environmental suitability, and health facilities to determine facility accessibility of any at-risk location within a country. We considered in-country and cross-border movements of exposed populations and highlighted vulnerable populations where current facilities are inaccessible and new infrastructure would reduce travel times. We developed profiles for 43 African countries. Resulting maps demonstrate gaps in health facility accessibility and highlight facilities closest to areas at risk for VHF spillover. For instance, in the Central African Republic, we identified travel times of over 24 h to access a health facility. Some countries had more uniformly short travel times, such as Nigeria, although regional disparities exist. For some populations, including many in Botswana, access to areas at risk for VHF nationally was low but proximity to suitable spillover areas in bordering countries was high. Additional analyses provide insights for considering future resource allocation. We provide a contemporary use case for these analyses for the ongoing Ebola outbreak.ConclusionsThese maps demonstrate the use of geospatial analytics for subnational preparedness, identifying facilities close to at-risk populations for prioritizing readiness to detect, treat, and respond to cases and highlighting where gaps in health facility accessibility exist. We identified cross-border threats for VHF exposure and demonstrate an opportunity to improve preparedness activities through the use of precision public health methods and data-driven insights for resource allocation as part of a country’s preparedness plans.

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Landscapes of healthcare utilization during a dengue fever outbreak in an urban environment of Colombia

Cited by 10 publications

References 47 publications

Space–Time Conditional Autoregressive Modeling to Estimate Neighborhood-Level Risks for Dengue Fever in Cali, Colombia

Space–Time Conditional Autoregressive Modeling to Estimate Neighborhood-Level Risks for Dengue Fever in Cali, Colombia

Surveillance and Epidemiology of Dengue in Medellín, Colombia from 2009 to 2017

Travel time to health facilities in areas of outbreak potential: maps for guiding local preparedness and response

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