2018
DOI: 10.1371/journal.pone.0203673
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Malaria intensity in Colombia by regions and populations

Abstract: Determining the distribution of disease prevalence among heterogeneous populations at the national scale is fundamental for epidemiology and public health. Here, we use a combination of methods (spatial scan statistic, topological data analysis and epidemic profile) to study measurable differences in malaria intensity by regions and populations of Colombia. This study explores three main questions: What are the regions of Colombia where malaria is epidemic? What are the regions and populations in Colombia wher… Show more

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Cited by 36 publications
(53 citation statements)
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References 87 publications
(116 reference statements)
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“…In Brazilian municipalities where mining is a central economic activity, malaria appeared as an occupational disease especially in young men [34]. In Colombia, 89.3% of malaria cases originated from the six regions with the highest gold mining activity [5,35]. In Peru, until 2015, health facilities located in areas of intense illegal gold mining (Madre de Dios region) reported 30 times more malaria cases than those in non-mining areas [13,36].…”
Section: State-level Data From Surveillance Systemsmentioning
confidence: 99%
“…In Brazilian municipalities where mining is a central economic activity, malaria appeared as an occupational disease especially in young men [34]. In Colombia, 89.3% of malaria cases originated from the six regions with the highest gold mining activity [5,35]. In Peru, until 2015, health facilities located in areas of intense illegal gold mining (Madre de Dios region) reported 30 times more malaria cases than those in non-mining areas [13,36].…”
Section: State-level Data From Surveillance Systemsmentioning
confidence: 99%
“…Spatial trends evaluated using a threshold-free approach are also consistent: they show a general increase in 1-Wasserstein distance with geographic distance between cities besides Buenaventura and Tumaco (Figure 3). The 1-Wasserstein distance can be interpreted as the effort required to transform a distribution of parasite samples from one city into a distribution of parasite samples from another [16]. The small 1-Wasserstein distance between Buenaventura and Tumaco is thus consistent with elevated gene flow between P. falciparum populations sampled from these cities.…”
Section: Resultsmentioning
confidence: 99%
“…We then calculate the 1-Wasserstein distance, which minimises the total cost of transporting w a to w b , where is the cost of transporting a single unit, using ( w a , w b , ). This amounts to treating parasite samples from different cities as draws from different distributions, where the 1-Wasserstein distance can be interpreted as the effort required to transform a distribution of parasite samples from one city into a distribution from another [16]. City pairs with smaller 1-Wasserstein distances are interpreted as having greater connectivity between the P. falciparum populations collected from them.…”
Section: Methodsmentioning
confidence: 99%
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