@article{fdi:010073793,
  title = {{L}andscape epidemiology in urban environments : the example of rodent-borne {T}rypanosoma in {N}iamey, {N}iger},
  author = {{R}ossi, {J}. {P}. and {K}adaoure, {I}. and {G}odefroid, {M}. and {D}obigny, {G}authier},
  editor = {},
  language = {{ENG}},
  abstract = {{T}rypanosomes are protozoan parasites found worldwide, infecting humans and animals. {I}n the past decade, the number of reports on atypical human cases due to {T}rypanosoma lewisi or {T}. lewisi-like has increased urging to investigate the multiple factors driving the disease dynamics, particularly in cities where rodents and humans coexist at high densities. {I}n the present survey, we used a species distribution model, {M}axent, to assess the spatial pattern of {T}rypanosoma-positive rodents in the city of {N}iamey. {T}he explanatory variables were landscape metrics describing urban landscape composition and physiognomy computed from 8 land-cover classes. {W}e 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). {F}or each spatial resolution, we determined the optimal combination of feature class and regularization multipliers by fitting {M}axent with the full dataset. {S}ince our dataset was small (114 occurrences) we expected an important uncertainty associated to data partitioning into calibration and evaluation datasets. {W}e thus performed 350 independent model runs with a training dataset representing a random subset of 80% of the occurrences and the optimal {M}axent parameters. {E}ach model yielded a map of habitat suitability over {N}iamey, which was transformed into a binary map implementing a threshold maximizing the sensitivity and the specificity. {T}he resulting binary maps were combined to display the proportion of models that indicated a good environmental suitability for {T}rypanosoma-positive rodents. {M}axent performed better with landscape metrics derived from buffers of 80 m. {H}abitat suitability for {T}rypanosoma-positive rodents exhibited large patches linked to urban features such as patch richness and the proportion of landscape covered by concrete or tarred areas. {S}uch inferences could be helpful in assessing areas at risk, setting of monitoring programs, public and medical staff awareness or even vaccination campaigns.},
  keywords = {{R}odent-borne {T}rypanosoma ; {S}patial epidemiology ; {U}rban landscape ; {M}axent ; {L}andscape metrics ; {P}ublic health ; {NIGER} ; {NIAMEY}},
  booktitle = {},
  journal = {{I}nfection {G}enetics and {E}volution},
  volume = {63},
  numero = {},
  pages = {307--315},
  ISSN = {1567-1348},
  year = {2018},
  DOI = {10.1016/j.meegid.2017.10.006},
  URL = {https://www.documentation.ird.fr/hor/fdi:010073793},
}