\summary

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The citrus industry is a major agricultural activity in 
Brazil and the state of Sao Paulo concentrates the largest production 
area of oranges in the world. The knowledge of incidence patterns of citrus 
diseases in time and space is relevant to the industry and allows the 
description of the dynamics of these diseases and may indicate strategies 
for epidemics control. In this work are considered two diseases that affect 
the cultivation of citrus, leprosis and citrus sudden death using data 
from the tracking of stands. An important point when studying diseases 
such as the citrus leprosis, considered a serious viral disease in the 
Brazilian citrus industry, is the investigation of the spatial pattern 
and temporal effects of the disease incidence within a stand. 
Exploratory methods to determine if the spatial pattern is or not added 
are frequently used. However it is possible to explore and describe the 
data adopting an explicit model, allowing to discriminate and quantify 
the effects through parameters for covariates that represent aspects of 
interest. To implement this model is necessary to reuse the data in order 
to extract spatial covariates, which requires extensions in the methodology 
and algorithms to assess properly the variance of estimates. In this work, 
the autologistic model is used in the analysis of diseases incidence data 
in citrus plants collected in points referenced in space and time in a stand. 
It is shown how the autologistic model is appropriate to investigate such 
diseases, and there is a description of the model and computational aspects 
needed to estimate the model. Thus it is possible to achieve objective 
assessments of the effects of the factors considered on the incidence 
of the disease through the estimated parameters of the proposed model 
and quantify the disease presence effects in different neighborhood 
structures. The modeling of the data has identified a spatial dependence 
between the plants and the adopted model allowed to quantify the changes 
in the probability of disease according to the status of the plants in 
the neighbourhood. The methodology presented here is not restricted to 
the cultivation of citrus. It can be used in the assessment of spatial-temporal 
patterns and effects of factors that affect the diseases in plants under 
similar conditions.


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\noindent Keywords: Spatial statistics; Pseudo-likelihood; Citrus diseases

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