@article{fdi:010046110,
  title = {{M}odelling malaria incidence with environmental dependency in a locality of {S}udanese savannah area, {M}ali},
  author = {{G}audart, {J}. and {T}our{\'e}, {O}. and {D}essay, {N}adine and {D}icko, {A}. {L}. and {R}anque, {S}. and {F}orest, {L}. and {D}emongeot, {J}. and {D}oumbo, {O}. {K}.},
  editor = {},
  language = {{ENG}},
  abstract = {{B}ackground: {T}he risk of {P}lasmodium falciparum infection is variable over space and time and this variability is related to environmental variability. {E}nvironmental factors affect the biological cycle of both vector and parasite. {D}espite this strong relationship, environmental effects have rarely been included in malaria transmission models. {R}emote sensing data on environment were incorporated into a temporal model of the transmission, to forecast the evolution of malaria epidemiology, in a locality of {S}udanese savannah area. {M}ethods: {A} dynamic cohort was constituted in {J}une 1996 and followed up until {J}une 2001 in the locality of {B}ancoumana, {M}ali. {T}he 15-day composite vegetation index ({NDVI}), issued from satellite imagery series ({NOAA}) from {J}uly 1981 to {D}ecember 2006, was used as remote sensing data. {T}he statistical relationship between {NDVI} and incidence of {P}. falciparum infection was assessed by {ARIMA} analysis. {ROC} analysis provided an {NDVI} value for the prediction of an increase in incidence of parasitaemia. {M}alaria transmission was modelled using an {SIRS}-type model, adapted to {B}ancoumana's data. {E}nvironmental factors influenced vector mortality and aggressiveness, as well as length of the gonotrophic cycle. {NDVI} observations from 1981 to 2001 were used for the simulation of the extrinsic variable of a hidden {M}arkov chain model. {O}bservations from 2002 to 2006 served as external validation. {R}esults: {T}he seasonal pattern of {P}. falciparum incidence was significantly explained by {NDVI}, with a delay of 15 days (p = 0.001). {A}n {NDVI} threshold of 0.361 (p = 0.007) provided a {D}iagnostic {O}dd {R}atio ({DOR}) of 2.64 ({CI}95% [1.26;5.52]). {T}he deterministic transmission model, with stochastic environmental factor, predicted an endemoepidemic pattern of malaria infection. {T}he incidences of parasitaemia were adequately modelled, using the observed {NDVI} as well as the {NDVI} simulations. {T}ransmission pattern have been modelled and observed values were adequately predicted. {T}he error parameters have shown the smallest values for a monthly model of environmental changes. {C}onclusion: {R}emote-sensed data were coupled with field study data in order to drive a malaria transmission model. {S}everal studies have shown that the {NDVI} presents significant correlations with climate variables, such as precipitations particularly in {S}udanese savannah environments. {N}onlinear model combining environmental variables, predisposition factors and transmission pattern can be used for community level risk evaluation.},
  keywords = {},
  booktitle = {},
  journal = {{M}alaria {J}ournal},
  volume = {8},
  numero = {},
  pages = {61},
  ISSN = {1475-2875},
  year = {2009},
  DOI = {10.1186/1475-2875-8-61},
  URL = {https://www.documentation.ird.fr/hor/fdi:010046110},
}