@article{fdi:010094510,
  title = {{C}limatic, land-use and socio-economic factors can predict malaria dynamics at fine spatial scales relevant to local health actors : evidence from rural {M}adagascar},
  author = {{P}ourtois, {J}.{D}. and {T}allam, {K}. and {J}ones, {I}. and {H}yde, {E}. and {C}hamberlin, {A}.{J}. and {E}vans, {M}.{V}. and {I}hantamalala, {F}.{A}. and {C}ordier, {L}.{F}. and {R}azafinjato, {B}.{R}. and {R}akotonanahary, {R}. {J}. {L}. and {T}sirinomen'ny {A}ina, {A}. and {S}oloniaina, {P}. and {R}aholiarimanana, {S}.{H}. and {R}azafinjato, {C}. and {B}onds, {M}.{H}. and {D}e {L}eo, {G}.{A}. and {S}okolow, {S}.{H}. and {G}architorena, {A}ndres},
  editor = {},
  language = {{ENG}},
  abstract = {{W}hile much progress has been achieved over the last decades, malaria surveillance and control remain a challenge in countries with limited health care access and resources. {H}igh-resolution predictions of malaria incidence using routine surveillance data could represent a powerful tool to health practitioners by targeting malaria control activities where and when they are most needed. {H}ere, we investigate the predictors of spatio-temporal malaria dynamics in rural {M}adagascar, estimated from facility-based passive surveillance data. {S}pecifically, this study integrates climate, land-use, and representative household survey data to explain and predict malaria dynamics at a high spatial resolution (i.e., by {F}okontany, a cluster of villages) relevant to health care practitioners. {C}ombining generalized linear mixed models ({GLMM}) and path analyses, we found that socio-economic, land use and climatic variables are all important predictors of monthly malaria incidence at fine spatial scales, via both direct and indirect effects. {I}n addition, out-of-sample predictions from our model were able to identify 58% of the {F}okontany in the top quintile for malaria incidence and account for 77% of the variation in the {F}okontany incidence rank. {T}hese results suggest that it is possible to build a predictive framework using environmental and social predictors that can be complementary to standard surveillance systems and help inform control strategies by field actors at local scales.},
  keywords = {{MADAGASCAR} ; {IFANADIANA}},
  booktitle = {},
  journal = {{PLOS} {G}lobal {P}ublic {H}ealth},
  volume = {3},
  numero = {2},
  pages = {e0001607 [20 ]},
  ISSN = {2767-3375},
  year = {2023},
  DOI = {10.1371/journal.pgph.0001607},
  URL = {https://www.documentation.ird.fr/hor/fdi:010094510},
}