SPATIAL DIFFUSION MAPS OF DENGUE FEVER EPIDEMICS OCURRING IN SOUTHEASTERN BRAZIL: A METHODOLOGY

FOR CARTOGRAPHIC MODELING IN GIS

Marcos Ferreira Geosciences Institute, State University of Campinas (UNICAMP)

Campinas, Sao Paulo, Brazil. macferre@ige.unicamp.br

ABSTRACT

This study presents a methodology for cartographic modeling of spatial diffusion of dengue fever epidemics, based on spatial analysis techniques and ArcMap and Idrisi32 GIS. Data from 109 counties, organized in epidemiological weeks, related to a dengue fever epidemic that occurred in 2001 in northwestern Sao Paulo state, were used to map the spatial diffusion of cases. The methodology is based on five levels of approaches: four levels that join exact objects/continuous fields models with single/multiple times slices sequences, and a fifth level, which is based on network analysis of connections between counties. With the single time scale/exact objects level, county clusters, spatial contagion of counties and local incidence rates were mapped; and with the multiple time scale/exact objects level, spatial dynamics of the cases were mapped with a spatial&time sequencing model. Using the single time/continuous field level, isoplethic and tendency surface maps were produced. At the multiple times/continuous field level, spatial diffusion maps and spatial-time mobility of mean geographical center of dengue epidemics are arranged using a sequential maps model. At the last level of methodology, urban node connections are spatially analyzed using road network analysis techniques, to map potential for contagion between counties, spatial dispersion of epidemics between counties, and the path of spread of dengue fever over the region as a whole. The results show the spatial diffusion of dengue fever is most efficient in major highway corridors where the daily trips are more frequent, and where there has been no economic impedance to the circulation of merchandise and people. Key Words � Spatial Analysis; GIS; Thematic Maps; Maps; Dengue Fever; Medical Geography; Health Data; Epidemics. INTRODUCTION

In the last several decades, dengue fever has become one of the most significant and dramatic public health problems in the world. Data from 1995 indicate that the spatial distribution of the occurrence of dengue fever, on a world level, can be compared to that of malaria. At that time, it was estimated that more than two billion people were living in areas at risk of transmission of the epidemic (Gubler & Clark, 1995). Due to circulation throughout the five continents, and the great potential for causing serious and lethal forms, world data indicated that close to 3 million people were infected by the disease between 1955 and 1995, of which 58,000 resulted in death (Teixeira, 2001; Halstead, 1997).

In Brazil, the situation is equally alarming, as more that 1.8 million cases were reported up to end of the last decade, with 570,148 cases being reported in the year 1998 alone (Schatzmayr, 2000). Dengue fever is an urban disease, predominantly tropical, whose causal virus inserts itself in the cycle involving man and the Aedes aegipty, a mosquito with daytime habits that feeds on human blood. Dengue fever, as well as hemorrhagic dengue fever, are caused by one of four different viruses that belong to the genus Flavirus: DEN-1, DEN-2, DEN-3, and DEN-4 (Gubler, 1988). Characterized as a type of tropical arbovirus, dengue fever became a serious public health problem in Brazil. Its transmission is essentially urban, an environment in which all the basic factors needed for its occurrence are found: humans, the virus, the vector, and mainly, the political, economic, and cultural conditions that form a chain of transmission (Marzochi, 1984). The re-appearance of the disease in Brazil in the 1970's was the result of the migration of cases coming from Mexico and Central America (Scharzmayr, 2000). Although, on a global scale, dengue is considered a �tropical disease�, an �epidemic of rainy summers�, when geographical approaches are used that are compatible with local scales, it can be observed that the phenomenon is more complex. A provocative example for geography research is the phenomenon of different incidence of cases in neighboring cities, or in those situated in the same climatic region. If the climatic factor were the only determining factor, the chance of cases occurring in neighboring cities would be the same; however this rarely occurs, mainly in Brazil. Recently, researchers have pointed to the need to incorporate social, economic, and political dimensions as important determinants of health and disease. There are consistent associations between economic growth and environmental degradation, as well as between social inequality, poverty, and the incidence of some diseases.

Since 1981, various dengue fever epidemics have occurred in Brazil. The most well-known locale where the epidemic has found social and economic conditions that are extremely favorable to its spread is the metropolitan area of Rio de Janeiro (Nogueira et al. (1999). In addition to this city, the epidemic also spread in the 1980�s and 1990�s in cities in northeastern Brazil, such as Salvador (Bahia) and Fortaleza (Ceará), where 102,010 cases were reported at the end of the 1990�s (Araújo et al. 1996). The state of São Paulo, in southeastern Brazil, and the most developed in Brazil, has also been the site of important outbreaks of dengue fever epidemics, mainly in medium and large-size cites located in the interior of the state. Recent data show that more that 40% of the dengue fever cases in the state occurred in cities in the interior with more than 100,000 inhabitants (Costa & Natal, 1998). An example is the city of São Jose do Rio Preto, located in the northeastern region of the state, with a population of almost 400,000. In 2001, more than 6,000 cases of dengue fever were reported in the city (CVE, 2002). Due to the strategic geographical position of this city, where a large number of commercial and industrial businesses are concentrated, a large number of people residing in a region that includes 109 municipalities flows into this urban center daily, to work, shop, visit the doctor, and study. For this reason, it is expected that São José do Rio Preto would be an epidemic diffusion point for dengue fever, contributing to the infection of other cities not yet infected, due to the viral traffic generated by the regional circulation of people. Based on this hypothesis, the objective of the present study is to carry out, using geographical information systems, a spatial analysis of the dengue fever epidemic that occurred in the region in 2001, and to map the spatial diffusion of the epidemic per epidemiological week. STUDY AREA The study area corresponds to the region surrounding São José do Rio Preto county, located in northeastern São Paulo State, encompassing 109 municipalities with populations varying from 2,000 to 380,000 inhabitants (Figure 1). The climate in the region is characterized by very hot and rainy summers, dry winters with moderate temperatures (average annual temperature 28o C and average annual precipitation 1,500 mm). The agriculture in the region is characterized by large orange crops, livestock raising, and sugar cane plantations. The region exhibits a high level of urbanization, with an intense migratory process and rapid expansion of the urban peripheries, which has been reflected in intense changes in the patterns of land use in the larger cities.

Figure 1 � Location of study area and municipalities administrative division map.

The methodological procedure used in the study is based on techniques originally proposed by Marshall (1991); King (1979); Gesler (1986) and Hagget (1972) that were later transformed into spatial analysis functions for use in geographical information systems. The data base used in the study is composed of two types of digital files: vector files, corresponding to polygons that demarcate the municipalities (IBGE, 1999), geo-referenced in Lambert�s polyconic projection, compatible with a scale of 1:250,000; the epidemiological database, referring to the number of dengue fever cases reported for each city (CVE, 2002); and the socioeconomic database, containing demographic and urbanization parameters (SEADE, 2003).

The municipal epidemiological data were organized in epidemiological weeks, and by the annual total of cases in 2001. To avoid including cases diagnosed in a given week, that were reported in the following week, and made available only in the third or fourth epidemiological week, it was decided to total the weekly data into four-week groups (quad-weekly). In this manner, in addition to minimizing the time-lag effects between notification and publication of the data, this strategy contributed to softening the random fluctuation of isolated cases, a common technique used in the statistical treatment of epidemiological data. The number of cases was also standardized according to the total resident population in the city in 2001, estimating the co-efficient of weekly incidence (CIs) and the co-efficient of mean annual incidence (CIa) of dengue fever cases, presented in cases per 10,000 inhabitants.

The methodological procedure for spatial analysis and mapping of the diffusion of the dengue fever epidemic in the region was based on 5 stages:

a) The first phase consisted of the construction of a sequential binary cartogram (Figure 2), representing the

occurrence or non-occurrence of dengue fever cases in each municipality per epidemiological quad-week. With this procedure, we sought to understand the dynamic of the spread of the first cases of the disease, analyzing the location of the appearance of new cases, and in this way, checking the hypothesis of spatial contagion between neighboring cities.

b) In the second phase, a sequential quaternary cartogram was developed, with the objective of representing the spatial-temporal evolution of the following information: municipalities with new cases; municipalities with cases maintained from one quad-week to another; municipalities where the cases disappeared; and municipalities where no cases occurred during the preceding and current weeks. Based on this map, the rate of quad-week spatial contamination was calculated, estimating the percentage of new cases that arise contiguously with old cases.

c) In the third phase, a map of the space-time autocorrelation (Figure 3) of the epidemic was produced, based on a model of triangular network of connection between urban centers. This network was outlined based on the union between two or more municipalities, whose new cases appeared by spatial contagion with old cases present in neighboring municipalities. In the regions where the web of connections is denser, zones of higher susceptibility to infestation by the dengue virus were defined.

d) The fourth phase consisted of the production of a map of the potential for inter-municipal contagion, (Figure 4) constructed using the gravitational potential model. Using techniques of geographical network analysis, the nodality index and municipal connectivity index were obtained, calculated from the weighted matrices of binary comparison.

e) The fifth phase involved the production of a map of the spatial diffusion of dengue fever (Figure 5) representing the preferential directions of mobility of new cases, by way of directional vectors. This map, obtained by combining the maps produced in phases a and b, made it possible to identify the most probable corridors of contagion between municipalities, along which the rate of spread of the disease is greater.

Figure 2 - Sequential cartogram showing the evolution of dengue fever in five quad-weeks.

Figure 3 � Space-time autocorrelation triangulated network map of municipalities with dengue fever cases.

Figure 4 - Potential for inter-municipal contagion by dengue fever map, in suitability classes (1 to 2720), and relationship with connectivity between cities index in the regional network road.

Figure 5 - Spatial diffusion of dengue fever map showing the mainly directions of spread of epidemic starting at pole cities toward small cities, between one quad-week to another.

In the sixth and final phase, a map of the zones of susceptibility to diffusion of the dengue fever epidemic (Figure 6) was proposed, based on the least geographical impedance. These zones are characterized by higher territorial permeability resulting from maximum urban interaction, where the traffic of people and services is more intense, and a higher rate of contagion by the disease was verified between municipalities connected by the major highway.

CONCLUSIONS

Analyzing the maps, one perceives the existence of indications of spatial contiguity in the concentration of cases, associated with the alignment of the cities that continue to present more occurrences over time. As the climatic conditions in the region are practically homogeneous, other factors have increased the potential for the diffusion of the epidemic. Since man is one of the vectors for dengue fever, the circulation of people becomes an important factor in the propagation of the disease. The mobility of the population is governed by the regional economy, where some cities act as centers of agglomeration of people due to the concentration of services and employment. The daily migration and the circulation of merchandise and services are very important factors in the spatial diffusion of the disease in this region.

Figure 6 - Map of the zones of susceptibility to diffusion of the dengue fever epidemic, classified in 4 classes: less suitable through very highly suitable.

The multi-temporal analysis carried out with thematic maps shows that the dengue fever epidemic reaches a maximum of contaminated municipalities in May, followed by a retreat of the disease, when cases are concentrated mainly in the more populous regional centers. Based on this spatial pulsation, one notes the existence of a preferential alignment of diffusion between municipalities, forming corridors of great susceptibility to contagion. In these corridors, impedance to the spread of new cases is minimum. It was also found that a large majority of cities where new cases appear are contiguous to cities with reports of past cases. However, this contagion occurs with greater intensity along regional corridors with more traffic of merchandise, people, and services.

The higher incidence of cases and average velocity of contagion, occur in cities with higher nodality index values and greater and faster accessibility to the regional highway network. These regional centers have the highest rate of demographic growth, the fastest pace of change in urban land use, and high population density in poor neighborhoods. These factors are fundamental to the appearance of habitats for the mosquito and the transmission of the virus to the population that migrates daily from smaller cities to these larger regional centers.

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Short Biography of the Author Marcos C. Ferreira (1957) is geographer with MSc in Remote Sensing (INPE, 1991) and PhD in Physical Geography (USP, 1995). Work at State University of Campinas (UNICAMP) teaching remote sensing and GIS for guaduating students of earth sciences, and spatial analysis for pos-graduating students of geography. His more recent research is related to spatial analysis of epidemiological data applied to dengue fever in Brazil.