The impact of the COVID-19 vaccination campaign in the US has been hampered by a substantial geographical heterogeneity of the vaccination coverage. Several studies have proposed vaccination hesitancy as a key driver of the vaccination uptake disparities. However, the impact of other important structural determinants such as local disparities in healthcare capacity is virtually unknown. In this cross-sectional study, we conducted causal inference and geospatial analyses to assess the impact of healthcare capacity on the vaccination coverage disparity in the US. We evaluated the causal relationship between the healthcare system capacity of 2417 US counties and their COVID-19 vaccination rate. We also conducted geospatial analyses using spatial scan statistics to identify areas with low vaccination rates. We found a causal effect of the constraints in the healthcare capacity of a county and its low-vaccination uptake. Counties with higher constraints in their healthcare capacity were more probable to have COVID-19 vaccination rates ≤50, with 35% higher constraints in low-vaccinated areas (vaccination rates ≤ 50) compared to high-vaccinated areas (vaccination rates > 50). We also found that COVID-19 vaccination in the US exhibits a distinct spatial structure with defined “vaccination coldspots”. We found that the healthcare capacity of a county is an important determinant of low vaccine uptake. Our study highlights that even in high-income nations, internal disparities in healthcare capacity play an important role in the health outcomes of the nation. Therefore, strengthening the funding and infrastructure of the healthcare system, particularly in rural underserved areas, should be intensified to help vulnerable communities. None.

Background: Despite the identification of some environmental factors linked to the cutaneous leishmaniasis (CL) epidemic, little is known about the impact of environmental disturbances caused by human activities. We assessed the association between socioeconomic and demographic factors with the spatial structure of the CL epidemic in Colombia. Methods: Using data from more than 65 000 CL cases collected across the entire country from publicly available sources, we conducted a spatial clustering analysis to identify high burden areas (clusters) of CL. Associations between CL clusters and socioeconomic variables were investigated. Results: We identified seven statistically significant clusters of CL located across all Colombian biomes. Deforestation and livestock were statistically significantly associated with the spatial clustering of CL. Urbanization, time spent traveling to main cities and water bodies were other factors linked with the clustering of CL. Conclusions: This study found that human activities such as deforestation linked to agriculture, livestock production and mining activities are key drivers of the spatial distribution of the CL epidemic. The intensity of these human activities, which are projected to increase because of social and economic transformations in progress in Colombia, will potentially exacerbate the already growing CL epidemic in the country.

In Colombia, human leptospirosis (HL) is a disease that has had a mandatory notification rule since 2007. Humans usually acquire the infection through water contaminated with animal urine that comes into direct contact with cutaneous lesions, eyes or mucous membranes. To analyze the spatiotemporal variability in the occurrence of HL cases in Colombia between 2007 and 2016, and its relation with the El Niño Southern Oscillation (ENSO) cycle and the consequent anomalies in rainfall in spatiotemporal clusters. An ecological study of the HL cases, aggregated by municipality, and reported between 2007 and 2016, is presented. During the period of study, 9928 cases of HL were reported, and 58.9% of the municipalities reported at least one case of leptospirosis. Six spatiotemporal clusters were identified—five were in the Andean region and one was in the Caribbean region. The assessment of the ENSO cycle and rainfall anomalies suggests the importance of La Niña episodes, and excess rainfall periods in the occurrence of cases of HL. Our results demonstrate the importance of the ENSO cycle, rainfall periods and periods with excess rainfall in the occurrence of cases and outbreaks of HL in Colombia, and suggest the importance of the topography of valleys and flood zones as zones in which the risk of infection is elevated.

Human leptospirosis is an infection that most often affects tropical countries. Since 2007, Colombia requires the notification of disease cases, enabling the observation of an increase in cases in recent years. The objectives of this article were to analyze environmental and socioeconomic variables and to evaluate their relationship with human leptospirosis cases. This is an ecological study on human leptospirosis cases aggregated by municipality and reported between 2007 and 2016. Spatial aggregation assessment was made using the Getis-Ord Gi method, and negative binomial regression was used to evaluate the relationship between environmental and socioeconomic variables with human leptospirosis. During the study period, 9,928 cases of human leptospirosis were reported, and 58.9% of municipalities reported at least one case. Four hotspots of human leptospirosis, including 18 municipalities, were identified. The results of the negative binomial model confirmed the importance of the effects of education, poverty and some climatic variables on the decadal incidence rate of human leptospirosis. Our results confirm the importance of socioeconomic determinants such as social marginality associated with violence and education, as well as ecological variables such as rainfall, height above sea level and forest coverage on the incidence rate of human leptospirosis at municipal scale.

Cutaneous leishmaniasis (CL) is a vector-borne disease that is widely distributed in most tropical regions. Colombia has experienced an important increase in its incidence during the last decade. There are CL transmission foci in the Colombian departments of Santander and Norte de Santander. To identify environmental and socio-economic variables associated with CL incidence in the municipalities of the northeast of Colombia between 2007 and 2016. This was an ecological study of CL cases aggregated by municipality. The cases reported during the study period were analyzed with a negative binomial regression to obtain the adjusted incident rate ratio for environmental and socio-economic variables. During the study period, 10 924 cases of CL were reported, and 110 (86.6%) municipalities reported at least one CL case. The coverages of forest (aIRR 1.05, 95% CI 1.03–1.07), heterogeneous agricultural zones (aIRR 1.04, 95% CI 1.02–1.06) and permanent crops (aIRR 1.07, 95% CI 1.02–1.12) were associated with a higher incidence of CL. Conversely, urban functionality (aIRR 0.95, 95% CI 0.92–0.96), minimal-altitude above sea level (aIRR 0.84, 95% CI 0.79–0.90) and shrub coverage (aIRR 0.98, 95% CI 0.95–1.0) were negatively associated with the incidence of CL in the municipality. Our results confirm the importance of environmental determinants, such as height above sea level, and coverage of forest, permanent crops and heterogeneous agricultural zones, for the occurrence of CL; these findings also suggest the importance of shrub coverage. Furthermore, urban functionality was a socio-economic determinant independently associated with CL incidence.