| 7 |
Cuzick and Edwards Nearest neighbor tests and Monte Carlo
simulation (49) |
To identify spatial clusters of dengue cases. |
| 8 |
Global K-functions, Getis-Ord Gi* (44) |
To identify spatial clusters of dengue cases. |
| 9 |
Knox test (43) |
To detect spatiotemporal clustering. |
| 10 |
Spatial average and Standard Deviational Ellipsis [SDE]
(48) |
Identification of spatial diffusion patterns. |
| 11 |
Kulldorff Spatial scan statistic (47) |
To investigate how dengue varies over space and time. |
| 12 |
Ripley’s K statistic (44) |
To detect clustering of dengue cases. |
| 13 |
Spatial operations to calculate
the distances |
To investigate the association of environmental,
entomological,
socio-demographic factors with dengue
cases. |
| 14 |
Local Indicators of Spatial Association, Monte Carlo Test
(54) |
To identify spatial clusters of dengue cases. |
| 15 |
Knox test (43), Fourier
Harmonic Analysis |
To detect spatiotemporal clustering. |
| 16 |
Kernel Intensity(55) |
To identify the pattern of spatial diffusion
of dengue
fever cases. |
| 17 |
Getis-Ord Gi* (44) |
Identification of hot-spot areas of dengue cases. |
| 18 |
Moran Global Index (54) |
To test hypotheses of spatial autocorrelation
of dengue
fever cases. |
| 19 |
A Generalized Additive Model (49) |
To identify potential high-risk intra-urban areas of
dengue. |
| 20 |
Spatial operations to calculate
the distances |
To test the hypothesis that DENV transmission
is
spatially and temporally focal. |
| 21 |
Moran Global Index (54) and
The nearest-neighbor
statistic (55) |
To test hypotheses of spatial autocorrelation
of dengue
fever cases. |
| 22 |
Local Indicators of Spatial Association (54) , Ripley’s
K-function (44) |
To identify spatial clusters of dengue cases.
To
analyze spatial-temporal-spatial patterns of dengue. |
| 23 |
Local Indicators of Spatial Association and the Moran Global
Index (54) |
To identify spatial clusters of dengue cases and to test
hypotheses of spatial autocorrelation of dengue fever
cases. |
| 24 |
Just calculated distances between events. |
To investigate the efficacy of Insecticide-treated bednets in
reducing Aedes aegypti populations and dengue transmission. |
| 25 |
Thematic maps |
To identify spatial patterns of dengue. |
| 26 |
Local Indicators of Spatial Association (54) and Kernel
Intensity (55) |
To identify spatial clusters and the pattern of spatial
diffusion of dengue fever cases. |
| 27 |
K-means clustering (48) |
To determine the strength of spatial structure
in both
DENV-1 and DENV-3. |
| Refence |
Spatial Method |
Objectives of spatial analysis |
| 28 |
Inverse Distance Weighting (45) |
To define geographical barriers to gene flow. |
| 29 |
Generalized Additive Model (49) |
Analysis of individual and spatial factors associated
with dengue seroprevalence. |
| 30 |
Moran Global Index and Local Indicators of Spatial Association
(54) |
To analyze spatial patterns of dengue. |
| 31 |
Kernel Intensity (55) |
To identify the pattern of spatial diffusion
of dengue
fever cases. |
| 32 |
Global K functions (48) and the local Getis-Ord Gi* (44) |
To define the temporal and spatial patterns and
clustering of dengue fever. |
| 33 |
Maxent algorithm (50) |
To investigate conditions associated with suitable areas for
Dengue fever occurrence in 2008 in three municipalities |
| 34 |
Kernel Intensity (55),
Kulldorff’s spatial scan
statistic (48) |
To identify the pattern of spatial diffusion and
the
spatial and temporal occurrence of dengue fever. |
| 35 |
The kernel estimator (55) |
To identify the pattern of spatial diffusion of the dengue
cases. |
| 36 |
Thematic maps. |
To describe the process of dissemination
of dengue in
the state of Bahia. |
| 37 |
Local Indicators of Spatial Association (54) |
To identify spatial clusters of dengue cases. |
| 38 |
Cluster analysis (55) |
To assess the spatial pattern of dengue fever in 2003. |
| 39 |
Local K-function (48), angular wavelet analysis of the spatial
clustering (51),
Knox test (43) |
Analyzed the spatio-temporal pattern of
denguevirus-2
outbreak during the 25 weeks of the outbreak. |
| 40 |
Moran Global Index and Local Indicators of Spatial Association
(54), Standard Deviational Ellipsis (48), Getis-Ord Gi* (44) and
Spatial Empirical Bayes smoothing (46) |
To analyze spatial patterns of dengue, spatial diffusion
patterns and hotspot identification. |
| 41 |
Moran Global Index and Local Indicators of Spatial Association
(54), Spatial empirical Bayes smoothing (46) |
To test hypotheses of spatial autocorrelation of dengue fever
cases, To analyze spatial patterns of dengue and dynamic
dispersion of dengue incidence. |
| 42 |
Moran Global Index (54) |
To test hypotheses of spatial autocorrelation
of dengue
fever cases. |
