Use of thermal and vegetation index data from earth observing satellites to evaluate the risk of schistosomiasis in Bahia, Brazil

被引:56
作者
Bavia, ME [1 ]
Malone, JB
Hale, L
Dantas, A
Marroni, L
Reis, R
机构
[1] Univ Fed Bahia, Fac Vet Med, Salvador, BA, Brazil
[2] Louisiana State Univ, Sch Vet Med, Baton Rouge, LA 70803 USA
[3] Louisiana Dept Nat Resources, Baton Rouge, LA USA
[4] Fundacao Nacl Saude, Salvador, BA, Brazil
[5] Inst Pesquisas Espaciais, Sao Paulo, Brazil
关键词
schistosomiasis; Schistosoma mansoni epidemiology; remote-sensing; GIS;
D O I
10.1016/S0001-706X(01)00105-X
中图分类号
R38 [医学寄生虫学]; Q [生物科学];
学科分类号
07 ; 0710 ; 09 ; 100103 ;
摘要
A geographic information system (GIS) was constructed using maps of regional agroclimatic features. vegetation indices and earth surface temperature data from environmental satellites, together with Schistosoma mansoni prevalence records from 270 municipalities including snail host distributions in Bahia, Brazil to study the spatial and temporal dynamics of infection and to identify environmental factors that influence the distribution of schistosomiasis. In an initial analysis, population density and duration (months) of the annual dry period were shown to be important determinants of disease. In cooperation with the National Institute of Spatial Research in Brazil (INPE), day and night imagery data covering the state of Bahia were selected at approximately bimonthly intervals in 1994 (six day-night pairs) from the data archives of the advanced very high resolution radiometer (AVHRR) sensor of the National Oceanic and Atmospheric Administration (NOAA)-11 satellite. A composite mosaic of these images was created to produce maps of: (1) average values between 0 and + 1 of the normalized difference vegetation index (NDVI); and (2) average diurnal temperature differences (dT) on a scale of values between 0 and 15 degreesC. For each municipality. NDVI and dr were calculated for a 3 x 3 pixel (9 km(2) area) grid and analyzed for relationships to prevalence of schistosomiasis. Results showed a statistically significant relationship of prevalence to dT(rho = - 0.218) and NDVI (rho = 0.384) at the 95% level of confidence by the Spearman rank correlation coefficient. Results support use of NDVI, dT; dry period climatic stress factors and human population density for development of a GIS environmental risk assessment model for schistosomiasis in Brazil. (C) 2001 Elsevier Science B.V. All rights reserved.
引用
收藏
页码:79 / 85
页数:7
相关论文
共 14 条
  • [1] Abdel-Rahman M. S., 1997, Journal of the Egyptian Society of Parasitology, V27, P299
  • [2] [Anonymous], 1993, WHO TECHN REP SER, V830
  • [3] APPLETON C C, 1978, Malacological Review, V11, P1
  • [4] Geographic information systems and the environmental risk of schistosomiasis in Bahia, Brazil
    Bavia, ME
    Hale, LF
    Malone, JB
    Braud, DH
    Shane, SM
    [J]. AMERICAN JOURNAL OF TROPICAL MEDICINE AND HYGIENE, 1999, 60 (04) : 566 - 572
  • [5] BAVIA ME, 1996, THESIS LOUISIANA STA
  • [6] Remote sensing and human health: New sensors and new opportunities
    Beck, LR
    Lobitz, BM
    Wood, BL
    [J]. EMERGING INFECTIOUS DISEASES, 2000, 6 (03) : 217 - 227
  • [7] Assessment of a remote sensing-based model for predicting malaria transmission risk in villages of Chiapas, Mexico
    Beck, LR
    Rodriguez, MH
    Dister, SW
    Rodriguez, AD
    Washino, RK
    Roberts, DR
    Spanner, MA
    [J]. AMERICAN JOURNAL OF TROPICAL MEDICINE AND HYGIENE, 1997, 56 (01) : 99 - 106
  • [8] Doumenge J.P., 1987, ATLAS GLOBAL DISTRIB
  • [9] *FUND I BRAS GEOGR, 1995, AN EST BRAS
  • [10] Geographic information systems and the distribution of Schistosoma mansoni in the Nile delta
    Malone, JB
    AbdelRahman, MS
    ElBahy, MM
    Huh, OK
    Shafik, M
    Bavia, M
    [J]. PARASITOLOGY TODAY, 1997, 13 (03): : 112 - 119