Landscape epidemiology in urban environments: The example of rodent-borne Trypanosoma in Niamey, Niger

Autor: Martin Godefroid, Gauthier Dobigny, Jean-Pierre Rossi, Ibrahima Kadaoure
Přispěvatelé: Centre de Biologie pour la Gestion des Populations (UMR CBGP), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Université de Montpellier (UM)-Institut de Recherche pour le Développement (IRD [France-Sud])-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), Centre Régional AGRHYMET (CRA), Université d'Abomey-Calavi, University of Abomey Calavi (UAC), ISIS program : 553, IRD : 301027/00, Republic of Niger : 301027/00
Jazyk: angličtina
Rok vydání: 2018
Předmět:
0106 biological sciences
Medical staff
Calibration (statistics)
[SDV]Life Sciences [q-bio]
Species distribution
Population Dynamics
Datasets as Topic
01 natural sciences
Mice
0302 clinical medicine
Niger
Public health
Ecology
public health
Spatial epidemiology
Infectious Diseases
spatial epidemiology
maxent
[SDE]Environmental Sciences
Maxent
Cartography
Microbiology (medical)
Trypanosoma lewisi
Landscape epidemiology
Movement
030231 tropical medicine
Biology
landscape metrics
010603 evolutionary biology
Microbiology
03 medical and health sciences
Trypanosomiasis
Landscape metrics
Genetics
Animals
Urban landscape
Cities
Molecular Biology
Ecology
Evolution
Behavior and Systematics
Ecosystem
Models
Statistical
urban landscape
Rats
Rodent-borne Trypanosoma
Common spatial pattern
Species richness
Murinae
Gerbillinae
Animal Distribution
Zdroj: Infection, Genetics and Evolution
Infection, Genetics and Evolution, Elsevier, 2018, 63, pp.307-315. ⟨10.1016/j.meegid.2017.10.006⟩
ISSN: 1567-1348
1567-7257
DOI: 10.1016/j.meegid.2017.10.006⟩
Popis: International audience; Trypanosomes are protozoan parasites found worldwide, infecting humans and animals. In the past decade, the number of reports on atypical human cases due to Trypanosoma lewisi or T. lewisi-like has increased urging to investigate the multiple factors driving the disease dynamics, particularly in cities where rodents and humans co-exist at high densities. In the present survey, we used a species distribution model, Maxent, to assess the spatial pattern of Trypanosoma-positive rodents in the city of Niamey. The explanatory variables were landscape metrics describing urban landscape composition and physiognomy computed from 8 land-cover classes. We computed the metrics around each data location using a set of circular buffers of increasing radii (20 m, 40 m, 60 m, 80 m and 100 m). For each spatial resolution, we determined the optimal combination of feature class and regularization multipliers by fitting Maxent with the full dataset. Since our dataset was small (114 occurrences) we expected an important uncertainty associated to data partitioning into calibration and evaluation datasets. We thus performed 350 independent model runs with a training dataset representing a random subset of 80% of the occurrences and the optimal Maxent parameters. Each model yielded a map of habitat suitability over Niamey, which was transformed into a binary map implementing a threshold maximizing the sensitivity and the specificity. The resulting binary maps were combined to display the proportion of models that indicated a good environmental suitability for Trypanosoma-positive rodents. Maxent performed better with landscape metrics derived from buffers of 80 m. Habitat suitability for Trypanosoma-positive rodents exhibited large patches linked to urban features such as patch richness and the proportion of landscape covered by concrete or tarred areas. Such inferences could be helpful in assessing areas at risk, setting of monitoring programs, public and medical staff awareness or even vaccination campaigns.
Databáze: OpenAIRE
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