@article{fdi:010079123,
  title = {{S}patio-temporal variation of malaria hotspots in {C}entral {S}enegal, 2008-2012},
  author = {{D}ieng, {S}. and {B}a, {E}. and {C}isse, {B}. and {S}allah, {K}. and {G}uindo, {A}bdoulaye and {O}uedraogo, {B}. and {P}iarroux, {M}. and {R}ebaudet, {S}. and {P}iarroux, {R}. and {L}andier, {J}ordi and {S}okhna, {C}heikh and {G}audart, {J}.},
  editor = {},
  language = {{ENG}},
  abstract = {{B}ackground {I}n malaria endemic areas, identifying spatio-temporal hotspots is becoming an important element of innovative control strategies targeting transmission bottlenecks. {T}he aim of this work was to describe the spatio-temporal variation of malaria hotspots in central {S}enegal and to identify the meteorological, environmental, and preventive factors that influence this variation. {M}ethods {T}his study analysed the weekly incidence of malaria cases recorded from 2008 to 2012 in 575 villages of central {S}enegal (total population approximately 500,000) as part of a trial of seasonal malaria chemoprevention ({SMC}). {D}ata on weekly rainfall and annual vegetation types were obtained for each village through remote sensing. {T}he time series of weekly malaria incidence for the entire study area was divided into periods of high and low transmission using change-point analysis. {M}alaria hotspots were detected during each transmission period with the {S}a{TS}can method. {T}he effects of rainfall, vegetation type, and {SMC} intervention on the spatio-temporal variation of malaria hotspots were assessed using a {G}eneral {A}dditive {M}ixed {M}odel. {R}esults {T}he malaria incidence for the entire area varied between 0 and 115.34 cases/100,000 person weeks during the study period. {D}uring high transmission periods, the cumulative malaria incidence rate varied between 7.53 and 38.1 cases/100,000 person-weeks, and the number of hotspot villages varied between 62 and 147. {D}uring low transmission periods, the cumulative malaria incidence rate varied between 0.83 and 2.73 cases/100,000 person-weeks, and the number of hotspot villages varied between 10 and 43. {V}illages with {SMC} were less likely to be hotspots ({OR} = 0.48, {IC}95%: 0.33-0.68). {T}he association between rainfall and hotspot status was non-linear and depended on both vegetation type and amount of rainfall. {T}he association between village location in the study area and hotspot status was also shown. {C}onclusion {I}n our study, malaria hotspots varied over space and time according to a combination of meteorological, environmental, and preventive factors. {B}y taking into consideration the environmental and meteorological characteristics common to all hotspots, monitoring of these factors could lead targeted public health interventions at the local level. {M}oreover, spatial hotspots and foci of malaria persisting during {LTP}s need to be further addressed.},
  keywords = {{S}patial clusters ; {S}patio-temporal dynamic ; {M}alaria hotspots ; {N}on-linear associations ; {G}eostatistical analyses ; {SENEGAL}},
  booktitle = {},
  journal = {{BMC} {I}nfectious {D}iseases},
  volume = {20},
  numero = {1},
  pages = {art. 424 [13 p.]},
  year = {2020},
  DOI = {10.1186/s12879-020-05145-w},
  URL = {https://www.documentation.ird.fr/hor/fdi:010079123},
}