@article{fdi:010085975,
  title = {{D}etermining the spatial distribution of environmental and socio-economic suitability for human leptospirosis in the face of limited epidemiological data},
  author = {{C}ristaldi, {M}. {A}. and {C}atry, {T}hibault and {P}ottier, {A}ur{\'e}a and {H}erbreteau, {V}incent and {R}oux, {E}mmanuel and {J}acob, {P}. and {P}revitali, {M}. {A}.},
  editor = {},
  language = {{ENG}},
  abstract = {{B}ackground {L}eptospirosis is among the leading zoonotic causes of morbidity and mortality worldwide. {K}nowledge about spatial patterns of diseases and their underlying processes have the potential to guide intervention efforts. {H}owever, leptospirosis is often an underreported and misdiagnosed disease and consequently, spatial patterns of the disease remain unclear. {I}n the absence of accurate epidemiological data in the urban agglomeration of {S}anta {F}e, we used a knowledge-based index and cluster analysis to identify spatial patterns of environmental and socioeconomic suitability for the disease and potential underlying processes that shape them. {M}ethods {W}e geocoded human leptospirosis cases derived from the {A}rgentinian surveillance system during the period 2010 to 2019. {E}nvironmental and socioeconomic databases were obtained from satellite images and publicly available platforms on the web. {T}wo sets of human leptospirosis determinants were considered according to the level of their support by the literature and expert knowledge. {W}e used the {Z}onation algorithm to build a knowledge-based index and a clustering approach to identify distinct potential sets of determinants. {S}patial similarity and correlations between index, clusters, and incidence rates were evaluated. {R}esults {W}e were able to geocode 56.36% of the human leptospirosis cases reported in the national epidemiological database. {T}he knowledge-based index showed the suitability for human leptospirosis in the {UA} {S}anta {F}e increased from downtown areas of the largest cities towards peri-urban and suburban areas. {C}luster analysis revealed downtown areas were characterized by higher levels of socioeconomic conditions. {P}eri-urban and suburban areas encompassed two clusters which differed in terms of environmental determinants. {T}he highest incidence rates overlapped areas with the highest suitability scores, the strength of association was low though ({CS}c r = 0.21, {P} < 0.001 and {ES}c r = 0.19, {P} < 0.001). {C}onclusions {W}e present a method to analyze the environmental and socioeconomic suitability for human leptospirosis based on literature and expert knowledge. {T}he methodology can be thought as an evolutive and perfectible scheme as more studies are performed in the area and novel information regarding determinants of the disease become available. {O}ur approach can be a valuable tool for decision-makers since it can serve as a baseline to plan intervention measures.},
  keywords = {{S}patial epidemiology ; {U}nderreported misdiagnosed diseases ; {E}nvironmental conditions ; {S}ocioeconomic groups ; {K}nowledge-based index ; {C}luster analysis ; {ARGENTINE} ; {SANTA} {FE} ; {SANTO} {TOME} ; {RECREO} ; {SAN} {JOSE} {DEL} {RINCON} ; {MONTE} {VERA} ; {ARROYO} {LEYES}},
  booktitle = {},
  journal = {{I}nfectious {D}iseases of {P}overty},
  volume = {11},
  numero = {1},
  pages = {86 [19 ]},
  ISSN = {2095-5162},
  year = {2022},
  DOI = {10.1186/s40249-022-01010-x},
  URL = {https://www.documentation.ird.fr/hor/fdi:010085975},
}