CUBAN MEDICAL LITERATURE

Pedro Kourí Institute of Tropical Medicine

Spatial Vulnerability to Dengue: An Application of the Geographic Information Systems in Playa Municipality, City of Havana

 Teresita Tamara Pérez Martínez(1); Luisa Iñíguez Rojas(2); Lizet Sánchez Valdés(3); Ricardo Remond Noa(4)

ABSTRACT: The use of geographical information systems (GIS) in health was extended in the ‘90s. During this time, dengue reemerged with particular intensity and the use of GIS tools for its study has progressed. The objectives of this research are to identify the different spatial vulnerabilities to dengue occurring in Playa Municipality of the City of Havana, and compare the strata identified with the spatial distribution of cases reported during the outbreak in the year 2000. A digital database was set up on a 1:25,000 scale, which defined the blocks as polygons, and the micro- and macro-factors associated with transmission and virus introduction. For spatial analyses, the software used was Mapinfo 5.0, Sig Epi 2000 and SPSS 8.0. Three groups of blocks were selected according to the similarity of the variable values, categorized as: spatial vulnerability strata to transmission; scant vulnerability and medium vulnerability; and very vulnerable. The strength of the findings is confirmed by their association with the spatial distribution of reported cases.

Keywords: VULNERABILITY; DENGUE/EPIDEMIOLOGY; DENGUE/TRANSMISSION; HEMORRHAGIC DENGUE; FEVER/EPIDEMIOLOGY; DENGUE HEMORRHAGIC FEVER/TRANSMISSION; SYSTEMS OF GEOGRAPHIC INFORMATION

INTRODUCTION

At present, the most important arbovirus is dengue, which is endemic-epidemic. Considered the most severe reemerging disease, dengue has spread worldwide, with an estimated 50 million people infected every year. In 2002, 1,019,196 dengue cases were reported in the Americas. Its most severe forms have developed along with the propagation of the disease: hemorrhagic dengue and dengue shock syndrome (HD/DSS).[1]

In 1977, a dengue epidemic was reported in Cuba of over 500,000 cases, associated with virus D1. In 1981, another severe epidemic, caused by virus D2, spread throughout the country with 344,203 notified cases and 158 deaths. After 16 years without any cases reported, at the beginning of 1997, the disease, associated with D2, appeared in the municipality of Santiago de Cuba, in the province of the same name, where 3,012 cases were notified and 12 deaths. In the year 2000, an outbreak of 138 confirmed cases associated with serotypes D3 and D4 was reported in the province of the City of Havana.[2,3]

The complex group of factors that condition or determine dengue introduction and transmission is expressed differently in the geographical spaces where humans live. The spatial difference in vulnerability to dengue transmission has important significance in the organization of surveillance and control actions - especially for the vector. The management systems of geographically-referenced databases and other processing and analysis tools offered by geographic information systems (GIS), are being progressively introduced into the health field, especially for communicable diseases.

This study explores the application potentialities of GIS technologies and of the spatial and statistical analysis techniques for dengue studies in Cuba. Its central objective is the identification of the spatial vulnerability differentiation of a territory. Its specific objective is the evaluation of the results of this spatial differentiation, using the information obtained from the 2000 outbreak in the studied territory.

General Considerations about Dengue

Dengue is an acute febrile disease caused by any of the four serotypes of dengue virus belonging to the Flaviviridae family. This virus, causal agent of the disease, endures in a man-vector-man transmission cycle. The vector responsible for this transmission is commonly known as the “yellow fever mosquito,” since for centuries, this species has transmitted urban yellow fever. At present, dengue constitutes the first cause of morbidity and mortality among mosquito-transmitted viruses in the world.[4]

In America, the Aedes aegypti species has adapted to the domestic environment. Inside and outside homes, there are natural or artificial reservoirs for vector reproduction. In this way, the Aedes aegypti mosquito has become “urbanized.” The flight radius of the vector – rarely reaching beyond 100m - is small when compared to other species. Larger distances have been reported when eggs and larvae are transported by man in domestic containers.[3] (González E, Armada J, Trigo J. Técnicas de lucha anti-Aegypti. La Habana: Ministerio de Salud Pública; 1997).

The transmission dynamics and differentiation of dengue virus from one place to another is determined by the interaction between environment, the causal agent, the host populations (susceptible), and the transmission vector. The extent and intensity of such interactions will determine dengue transmission in a community, region or country.[5]

The risk factors for this disease have been classified as macro determinants and micro determinants. Macro determinant risk factors include environmental and social risk factors, while micro determinant factors include the host, the causal agent and the vector.[3]

• Environmental macro factors: latitude from 35 o north to 35 o south; altitude below 2,200m; temperature ranging from 15 oC to 40 oC and moderate to high relative humidity.
  
  
• Socialmacro factors: moderate to high population density; high density patterns of settlement and unplanned urbanization; inadequate housing with sewage or electricity problems; lack of or intermittent water supply, so water is stored in houses for more than 7 days; inadequate, deficient or non-existent storage of solid waste for collection; as well as the socioeconomic level of the population, beliefs and knowledge about dengue.
  
  
• Host micro factors: sex, age, immunity status, occupation, specific health conditions).
  
  
• Disease agent micro factors (level of viremia); and factors of the vector itself: abundance of mosquito proliferation foci, adult female density, feeding frequency, inborn susceptibility to infection, among others.

The geographical location of Cuba, its topography and its climatic conditions favor the reproduction of the dengue transmission vector. Similarly, the increase in urban population and its concentration in big cities, mainly due to migratory processes, have not been accompanied by adequate water supply or waste disposal services, creating favorable conditions for the reproduction of the vector and appearance of the disease. Another factor in the territory studied - one of the most densely populated municipalities in the city - is the large network of tourist installations and houses for rent, increasing the risk of entry by carriers of the virus.

Geographical Information Systems & Health

The integration of geographical sciences into health studies by geographical information systems is a relatively novel phenomenon. Essential to this process are basic concepts of spatial analysis and information, taken with computer-elaborated maps and other tools.[6]

Undoubtedly, technological developments in computerized information management and the production of specialized software for specific areas such as health, have greatly contributed to the reevaluation of maps as a means of communication. This development has also enabled the manipulation and analysis of spatially-referenced databases in a new, more flexible way, which can thus be managed more effectively and efficiently than with traditional methods and techniques.

Since their appearance in 1967, GIS have revolutionized the role of geographical sciences and have become a new generation of automated information systems allowing the management and representation of objects in space.

In the ‘80s, GIS were mainly used in government planning, by big companies or the military. In the last decades, technological developments, along with the extension of markets and large scale computer purchases, caused a significant reduction in hardware and software costs, and consequently, of computerization in general.

From the ‘90s to the present, GIS’ have slowly been introduced in the health field and their usefulness for increasing the efficacy of different programs - especially spatial focalization and stratification processes and other activities aimed at a more rational use of limited resources in the health sector - is internationally recognized.[7,8]

In this way, geographical information systems are one of the technologies that facilitate information processing, analysis and decision-making in public health. They are sometimes called health geographical information systems (HGIS) and epidemiology geographical information systems (EpiGis). The latter are considered essential for determining the health situation of an area, generating and analyzing research hypotheses, identification of high-risk groups, activity planning and programming, and monitoring and evaluating interventions.[9]

Cartographical representation of health-related information is (theoretically) a traditional public health task, especially in epidemiology. The technological advances achieved by GIS represent new and important opportunities for studying associations between different types of attributes and their spatial distribution. Areas of particular interest include environment and its relation to health/disease, the health picture, and inequalities in health.[10,15]

The first software used in the Americas for health studies was SiMap, applied in nutritional studies. This was a simple system for making thematic maps using the cartogram method and basic graphics (line, bar, pie and population pyramid graphics). Later, EpiMap software was developed for mapped output of the processing and analyis of health questionnaires and databases (EpiInfo software). This system is very easy to operate and accessible, although its cartographic representation and territorial analysis resources are limited. (Martínez R, González R. Curso-taller sobre sistemas de información geográfica aplicados a epidemiología y salud para usuarios directos. La Habana: Instituto de Medicina Tropical Pedro Kourí, Unidad de Análisis y Tendencias en Salud. Ministerio de Salud Pública de Cuba; 1995.)

The use of more powerful and complex software such as GIS Mapinfo, has become more common among Cuban researchers in the health sector. Developed in the US by the Mapinfo Corporation, it is a vector system for general cartography and vector analysis. ArcView, also made in the US, by the Environmental Systems Research Institute (ESRI), is similar, but operates on a different platform. This software also has the advantage of being compatible with other complex statistical analysis software such as SPLUS. These last two programs demand larger system requirements, produce higher quality cartographic and graphic outputs and offer greater analysis and information management possibilities.

New software called EpiGis has been specifically developed for health studies by the Pan American Health Organization (PAHO). This system, produced by an initiative of the PAHO Health Situation Analysis Program, has promoted the development of this tool among health specialists in the Americas, thus strengthening epidemiology in health services.

A network of reference centers has been created to cover the needs of the countries in the region. They collaborate in training and technical support for developing epidemiology geographical information systems in the region. Three groups of collaborators are presently active in Chile (Universidad de Santiago de Chile and Universidad Tecnológica Metropolitana); in Cuba (Departamento de Bioestadística y Computación, Pedro Kourí Institute and the Unidad de Análisis y Tendencias en Salud, Ministry of Public Health); and in Mexico (Centro Universitario de Ciencias de la Salud, Universidad de Guadalajara).

EpiGis have been used for analyzing basic health indicators on a continental level, as well as for identifying countries with the highest rate of infant mortality and its relation to lack of potable drinking water. This tool has also been used to define malaria risk areas in Brazil – demonstrating that almost half of the cases appeared in only one state, in a small fraction of the population – and for monitoring malaria trends in Central American and the Caribbean. Moreover, this tool has been extended to monitoring health inequalities.[8,11]

Geographical Information Systems for Dengue

The potential exists for GIS to manage spatially-correlated data and to support dengue control decision making. However, publications on this topic are still scarce.

One of the most complete studies was carried out in the municipality of Rio de Janeiro, Brazil, from 1986-1991 using a GIS developed by the Geoprocessing Laboratory of the Geosciences Department at the Institute of the Federal University of Rio de Janeiro (UFRJ, according to its Portuguese acronym). The system is called SAGA/UFRJ (System of Geo-environmental Analysis, according to its Portuguese acronym). It is based on statistical estimates of the relative importance of a group of variables related to the occurrence of the disease, with different weights assigned according to the degree of participation in the occurrence of cases. A fixed ordinal scale is used, known as “marks.” The average of those marks multiplied by the respective weight, classifies the territorial units and the superposition of layers or pondered superposition of maps, allows the establishment of high, middle and low risk categories of case occurrence. Finally, a predictive model for planning efficient prevention and control actions for the disease is generated.[16]

It is worth explaining that this research makes very complete use of this tool, which is present in all stages of the study, starting with the initial data collection, processing, analysis and results output. It is an example of the importance this new technology represents for applied epidemiology in the understanding of dengue spatial dynamics and its relation to environmental factors, and aids in establishing intervention priorities within areas of highest risk.

The authors point out the limitation in using political administrative boundaries to define operational units. Clearly, they possess great internal heterogeneity, above all in environmental and socio-economic aspects. In this paper we recommend using other more homogenous units, with more detailed levels; neighborhoods, for example.

Research carried out in the city of Maracay, Venezuela, used GIS for dengue spatial stratification. This research spanned 1993-1998, using the neighborhood as the study unit. The GIS Atlas of the Environmental Systems Research Institute (ESRI), was used both for the descriptive statistics of the variables and for the representation and analysis of the spatial patterns of the disease according to incidence.

The result was three neighborhood strata: without any apparent dengue; with low reporting; and with high persistence. The fact that the neighborhoods that had 70% of the cases occupied only 35% of the urban area demonstrates the concentration of vulnerability.[17]

A recent study performed in a sector of Corrientes, Argentina, used GIS techniques to identify dengue risk areas. In the spatial block unit, a set of parameters was studied and situated, with three of them selected for spatial stratification. The original inclusion of a qualitative evaluation of population responses (attitude, reluctance, collaboration, activities, focal control), stands out. In this interesting paper, three risk strata are identified: risk; high risk; and very high risk.

In this study, spatial analysis techniques are not explained and it is difficult to interpret the procedures that enable them to gather blocks into spatial strata. In this sense, the fact that the same indicators are not used to describe the strata is noteworthy. For example, the population response indicator is only considered in the most favorable stratum.[18]

When analyzing the distribution of health problems in our country in recent years, the cartographic component has been greatly aided by the use of GIS tools in the Health Tendencies Analysis Unit and the Vector Surveillance and Eradication Unit. In the case of dengue, conditions exist for the spatial representation of infestation and the factors associated with it in units such as health areas, popular councils and even blocks. Within them, different variables have been analyzed with respect to the vector foci, such as frequency and state of the water distribution and solid waste systems, and important train or bus stops or terminals, among others.

In the project design for “Health Surveillance Using GIS in the Province of Cienfuegos,” by researchers from the Provincial Health and Epidemiology Center and the regional GEOCUBA office, the GIS GeoHealth was produced on the basis of ArcView. It includes active vector surveillance in blocks of Cienfuegos city, with resources such as foci updates, vector spread prognosis, cost-benefit analysis of the interventions, and others. (Acosta GT, Crombet AV, Montes de Oca MJ, Fabregat MR, Aspiri, IM, Díaz PY, et al. SIG GeoSalud, CPHE/Geo/Cuba; 2002.)

In this GIS, the inclusion of operational steps for daily or periodical updates of the attributes stands out. In this respect, it is important to note that the establishment of the GIS in general and in the health sector in particular, require for their effective operation, growing and updating the databases, as well as including new attributes. This necessitates careful organization of the infrastructure and human resources to support these activities and inter sector collaboration.

The results of a study on dengue introduction and transmission risks in the Playa Municipality constitutes the closest study for the present research. The health areas were used as analysis units and risk strata were identified for each one of them. GIS were used to represent the results graphically. The study is framed in a two-month period (March-April) of the year 2000, corresponding to the second yearly entomologic inspection. (Cruz G. Estratificación del riesgo de introducción y transmisión del dengue en el municipio Playa. Trabajo para optar por el título de Master en Epidemiología, La Habana: Instituto de Medicina Tropical “Pedro Kourí,” 2000.)

METHODS

The criteria established for selecting the study area were the reiteration of foci and the concentration of cases during the 2000 outbreak. Playa Municipality was chosen because it had not been able to eradicate Aedes aegypti after the vector campaign program was set up in 1981. At the end of 1998, it held third place among the 15 municipalities of the capital according to rate of vector infestation. Besides, 50% of the cases reported during the outbreak (69 cases) were concentrated there.

This municipality has an area of 35 sq km, corresponding to 5% of the total area of the City of Havana Province, and is located on its northwestern end. The coastline forms its northern border, the Almendares River is on the east (the dividing line with Plaza de la Revolución Municipality), while on the south are La Lisa and Marianao municipalities and on the west, is Bauta Municipality, in Havana Province.

By the year 2000, Playa Municipality had 182,485 inhabitants and 27 neighborhoods, which are not political-administrative or sector administrative units, but are in general, recognized by the local population. They are: Miramar; Alturas de Miramar; Nicanor del Campo; Kohly; La Sierra; Alturas del Bosque; La Ceiba; Almendares; Ampliación del Almendares; Buenavista; Querejeta; La Playa; Náutico; Cubanacán; Barandilla; Flores; Siboney; Atabey; Jaimanitas; Juan Manuel Márquez; Santa Fé; Nuevo Santa Fé; El Roble; Bajos del Santa Ana (slum); Romerillo (slum); La Corbata (slum); and El Basurero (slum).

The study unit chosen was the block, which fulfills the basic requirements for exploring the GIS potentialities and for cartographic purposes, the one elaborated by GEOCUBA on a 1:25,000 scale. In digital format, this covers all of the City of Havana Province; Playa Municipality was “cut from it” using the following information:

• Municipal boundary
• Blocks forming the municipality (1,360)
• Street axis with associated direction
• Rivers
• Relief

According to the objectives of the research, the study period was framed between September 1999 and October 2000, which includes the year before the start of the outbreak and the two months it lasted.

Initial selection of the variables for evaluation of the spatial vulnerability to dengue occurrence was carried out according to the salient literature reviewed and the specificities of the territory studied. They were submitted to experts for their opinions and final approval. We differentiate them according to their relation to environmental and social factors favorable for the spread of the disease within the macro factors; by vector reproduction - those associated with foci proliferation considered among micro factors; and those indicating vulnerability to virus introduction.

Population density, water supply frequency, solid waste disposal, unfavorable living conditions and condition of the streets were considered in the first case; foci by cycles in the second; and tourist accommodations in hotels and other residences in the third.

It should be pointed out that the decision to include hotels and houses for rent in the study blocks was made because Playa Municipality is one of the territories of the province with the highest volume of tourists and travelers from abroad. This is due to the area’s accommodation options, fundamentally, but also the commercial infrastructure and services tourists are interested in. The variable is evaluated according to presence or absence of hotels and/or houses for rent on each block.

The relation between the reemergence of diseases and the intensification of the movement of people, merchandise and others forms a part of all geographical analysis scales. In fact, the geographical spread of dengue through introduction or reintroduction of the vector is attributed to this factor, especially the introduction of a carrier of the virus into a given territory. However, we have not found GIS studies on dengue spatiality where this component is operational.

Primary information was obtained from registries and files provided by different municipal and provincial offices. These were:

• Architecture and Town Planning Department (DAU): provided data on housing, street conditions and population from the census carried out by the DAU and the National Statistics Office (ONE) in Playa Municipality in November 1999. This office also supplied information on unsanitary conditions.
  
  
• Playa Department of Municipal Services: supplied information on the functioning of these services and permanent micro dumps; no data exists on unofficial or casual micro dumps.
  
  
• Havana Water Company: this office provided information on the sources of water supply and the frequency of this service, in addition to data on the water truck service and areas with water pressure difficulties.
  
  
• Municipal Health and Epidemiology Unit (UMHE): supplied the codification of the blocks forming the municipality, which the Municipal Unit of the Vector Surveillance & Eradication Campaign, ascribed to UMHE, uses in its work. These numbers were compared to the official codification of the basic territorial information units (UBIT), provided by the municipal DAU; discrepancies found were corrected in the present study. In addition, the number of houses, empty lots, hotel facilities and houses for rent for tourists in the municipality were obtained. In this last case, information was supplied by reports to the National Tax Administration Office (ONAT).

The categories assigned to each variable were the following:

• Population density (PD): (1) low; (2) middle; (3) high
• Water supply (WS): (1) daily service; (2) on alternate days; (3) by water trucks
• Usual micro dumps (UM): (1) absence; (2) presence
• Conditions of housing (C): blocks with houses in (1) predominantly good condition; (2) average condition; (3) poor condition
• Condition of streets (CS): (1) predominantly good condition; (2) average condition: (3) poor condition
• Empty lots (EL): (1) absence; (2) presence
• Unhealthy neighborhoods and foci (UNF): (1) absence; (2) presence
• Hotels and houses for rent (HH): (1) absence; (2) presence
• Aedes aegypti foci (VF): (1) absence; (2) presence, (3) persistence of foci in each entomologic inspection cycle
• Home address of reported cases: (1) absence; (2) presence

This information was obtained in analogical format and was later geo-referenced in the digital cartographic base of the study. The resulting base was set up using Mapinfo 5.0 software. According to the block codes (1,360 rows), 18 columns were set up for the selected fields: (9 columns for the socio-environmental parameters, 7 for the foci in each cycle, 1 for the tourist accommodation parameter and 1 for the presence of dengue cases).

For the spatial analysis and the final cartographic representation, the database was exported from the Mapinfo software to a format compatible with EpiGis 2000. The statistical processing techniques provided by EpiGis and SPSS 8.0 were combined. A digital database with 20 fields was obtained.

For each variable, a theme map was made in EpiGis, to visualize and analyze its spatial distribution and frequency.

In the identification of block aggregates by similarity of environmental and social conditions, the K-average classification method was used. The resulting groups were characterized according to discriminant analysis. For the evaluation of the vulnerability of each group, a double entry contingency table was made to determine the association between the presence or absence of foci in a block and to which defined group it belongs. A logistical regression model was adjusted to find the relation between the appearance of cases in a block and to which identified group it belongs, also taking into account the presence of Aedes aegypti infestation. A new column with the group into which each block was classified was added to the database. For both results, theme maps were made.

RESULTS AND DISCUSSION

There was a predominance of blocks with low population density, 555 blocks representing 41% of the total; 468 blocks (34%), had an average density; and 337 blocks (25% of the total), had high population density (Map 1).

The spatial distribution of these categories shows the following results:

• In the southeastern part of the municipality, more than 80% of the blocks have high population density, distributed in the Buenavista, La Ceiba, Alturas del Bosque, Nicanor del Campo, La Sierra and Almendares neighborhoods.
  
  
• The largest area of the municipality, including the Miramar and Ampliación de Almendares neighborhoods to the northeast, and the Siboney, Cubanacán and Atabey neighborhoods, shows low population density.

The Santa Fé and Jaimanitas neighborhoods, together with the slums of La Corbata and Romerillo, have specific blocks with high population density, alternating with average density ones.

Water is supplied to the Playa Municipality from five sources with very different frequency and durations of service, however a discontinuous supply predominates (78% of the neighborhoods).

The cartographic limit of the areas that are supplied by each water source defined eight zones with the following spatial distribution (Map 2).

Map 2: Water supply service in Playa Municipality of the City of Havana

• Five zones have daily water supply, two of them located in the central-west part of the municipality in blocks of the Jaimanitas, part of Siboney and El Basurero neighborhoods, supplied by the El Naranjo and Ariguanabo water sources. Three other small zones are irregularly distributed over the territory and correspond to blocks in Alturas de Miramar, part of the Atabey neighborhood and the southern part of the Buenavista neighborhood. The water sources for them are Cira García, Ariguanabao and Coscuyuela.
  
  
• Two zones – the largest in the territory - have water supply on alternate days; the first covers the central-west part, supplied by the Ariguanabo and Coscuyuela sources; the second runs from the Jaimanitas river to the west end of the territory and is supplied by the Santa Fé water source.

Some blocks distributed irregularly in the higher parts of the municipality receive water by trucks and there are others that have water pressure problems, in the Querejeta, Alturas de Almendares, Almendares, Nicanor del Campo, La Ceiba and other neighborhoods.

According to the historical series (1900-2001), Playa Municipality is among the first three municipalities in the collection of urban solid waste in the City of Havana Province, where collected volumes are the largest. In the year 2000, 789 million cubic meters of solid waste were collected there, only exceeded by Plaza Municipality with 809.6 million cubic meters.

Changes in the availability of equipment in the specialized system of waste collection (garbage truck – container) must be taken into consideration. During the country’s economic crisis, the system greatly deteriorated and it was necessary to resort to carts pulled by animals and tractors. The containers where waste was deposited, were also damaged and the whole collection system became unstable. This had a great effect on community hygiene, causing the proliferation of micro dumps.

Despite improvements made to this critical situation after the creation of the Governmental Commission in Support of the City of Havana, the evacuation of solid waste is still not totally efficient. For example, in the year 2000, there were still two popular councils - one in Buenavista and one in Santa Fé - without containers and thus without specialized collection services.

The 61 micro dumps are distributed unevenly in the territory; only the following are found as regular areas:

• In the blocks of the residential area of Siboney-Cubanacán and Naútico, to the center-west of the municipality, there are no micro dumps.
  
  
• In the southeast part of the municipality, 48% of all micro dumps were located in blocks of the Alturas de Miramar, La Sierra, Almendares, Nicanor del Campo, Alturas del Bosque and Buenavista neighborhoods.

The state of the houses was measured in only 1,228 blocks of the territory, since the remaining were occupied by green areas. In Playa, 55% (676) of the blocks showed houses in good condition; in 37% (456) there were average conditions; and only in 8% of the blocks (96), were houses predominantly in poor condition.

Regularities in the different conditions of houses were:

• Predominance of blocks with houses in good condition were in the northeastern part, concentrated in the Miramar and Ampliación de Almendares neighborhoods and in the central part of the territory, where the Siboney, Cubanacán and Atabey neighborhoods are located.
  
  
• The predominance of blocks with houses in poor condition were in the four slums of the municipality and in the old lower class zones such as Santa Fé, Jaimanitas and the southeast, covering the neighborhoods of Buenavista, La Ceiba and Alturas del Bosque.
  
  
• In the rest of the municipality, there is a mosaic of blocks where regular and good condition houses alternate.

In the residential area of the municipality there is a total of 234 blocks (17%), with empty lots, with a spatial concentration in the central and west areas, where 76% of them are found (117). Only 24% (57 blocks), are located in the east of the territory.

Empty or uninhabited lots are not, in general, under family or individual responsibility and become potential places for waste accumulation, favorable spaces for vector proliferation. In the fieldwork associated with the entomological inspection of the vector in our country, these are considered places of concern.

By the year 2000, 54 blocks were identified in unhealthy neighborhoods or foci, meaning that approximately 4% of the blocks have unsanitary conditions. They are distributed among four unhealthy neighborhoods and the 17 insalubrious foci situated in the territory: to the west in the Santa Fé and Jaimanitas neighborhoods, in the center at the southern end adjacent to La Lisa municipality, and to the east in the Querejeta and Romerillo neighborhoods.

There is a predominance of blocks with streets in good condition: 861 blocks (63%), and only 61 blocks (4.5%) with poor street conditions, mainly located in some of the insalubrious neighborhoods (La Corbata, El Basurero and Bajos de Santa Ana), in Flores and Jaimanitas, and Buenavista and La Ceiba to the southeast of the municipality. Poor street conditions were found in 438 blocks (32 %), with an evident concentration towards the southeast of the territory and part of the Querejeta neighborhood, with 74% of the blocks there having streets in poor condition.

During the study period, the 12 hotels in the territory received 227,463 tourists, 24% of the total that arrived in the City of Havana and 13% of the whole country. If you add the capacity of rooms for rent in the area (345 houses in that year), we can conclude that the number of tourists was even larger. The hotels are mainly located towards the east and in the northern coastal zone. Similarly, the concentration of houses with accommodations for foreigners is found in the east-northeast parts of the municipality.

The results displayed show the spatial differentiation of the environmental and social conditions within the municipality, resulting from inherited, as well as new, territorial processes. The historical evolution of that part of the city today occupied by the Playa Municipality was determined by the quality of the soil, which differentiated between types of construction and living conditions of the population. For this reason, there are neighborhoods with high quality construction and favorable living conditions (the majority), side by side with insalubrious neighborhoods and foci.

Since 1990, because of economic adjustments made in the country, spatial dynamics began a transformation, emphasizing the heterogeneity of the territory. The superposition of the maps (GIS layers), confirms the high internal differentiation, which, in turn suggests differences in spatial vulnerability to dengue introduction and transmission.

Three block aggregates were identified that may be considered spaces with relatively homogenous social and environmental characteristics: the first group presents the smallest values, the second is the worst evaluation of the variables, except for population density and frequency of water supply; while the third displays the highest values for both variables and average values for the rest.

TABLE 1: Fisher discriminant function coefficients

Source: Authors, based on the results

The spatial distribution of these groups shows the concentration of Group 3 in the southeastern part of the municipality and of Group 1 in the center and northeast. Meanwhile, Group 2 displays irregular distribution, mainly associated with the southeastern part and insalubrious neighborhoods and foci.

Even though the groups of blocks defined do not necessarily express levels of vulnerability, (meaning they do not constitute strata), the results of the discriminant analysis may suggest that Group 1 is the least vulnerable and Group 2, the most vulnerable.

In the study period, no Aedes aegypti foci appeared in 605 blocks (44.5%), while 755 were positive in one or more inspection cycles (55.5%); of these, 252 (18.5%) were positive in only one cycle and 503 (37%) had foci in at least two cycles.

Approximately 92% of the blocks with foci (692) were located in the eastern half of the municipality from the Naútico and Romerillo neighborhoods to those in the far fast end of the territory, where the blocks with foci persisting in at least two cycles were also concentrated. Only 63 (8%) of the blocks with foci were distributed in the western half of the municipality, where blocks positive in only one cycle predominated. Of the 605 blocks that did not present any foci throughout the study period, 404 (67.4%) are located in the west of the municipality and 197 (32.6%), in the east (Map 3).

Map 3: Aedes Aegypti Foci – Playa Municipality, City of Havana

There is a highly significant association between Aedes aegypti infestation and the blocks belonging to defined groups. Most of the blocks in the first group (54.7%), remained free of infestation during the whole study period, whereas foci were found in 84.3% of the blocks in the third group, with 64.3% of them repeatedly testing positive for Aedes aegypti. In the second group, there is a more uniform distribution with respect to infestation. There are blocks without infestation (37.1%), infested (23.1%) and with persistent infestation (39.9%) (Table 2).

TABLE 2:Association of Aedes aegypti infestation with groups of blocks

Source: Authors, based on the results

According to the results in the contingency table, Group 3 was the most strongly associated with infestation. The highest population density and the biggest problems with respect to water supply (Table 1) characterize this group. This observation reiterates the difference in classifying (groups, types or other) and stratifying, in which advantage or disadvantage levels are considered for each spatial unit.

Thus, we consider Group 1 as little vulnerability, Group 2 as intermediate and Group 3 as the most vulnerable.

The 69 dengue cases reported in the outbreak of 2000 in the municipality were located in 43 blocks, mainly in the neighborhoods of Buenavista, Ampliación de Almendares and Querejeta. The validity of the strata identified is proven by the high statistical association between them and the spatiality of the outbreak cases, approximately 60% of them were concentrated in blocks of Group 3, the most vulnerable (Map 4).

Map 4: Dengue vulnerability - Cases in the 2000 outbreak, Playa Municipality, City of Havana

According to the logistic regression model applied, the probability of a dengue case in each group was determined. Group 1 had the least probability, the second group has 3.39 times more probability than the first and the third has 5.49 times more. There was a significant relation (p = 0.0123) between Aedes infestation and the appearance of cases, mainly associated with blocks showing persistence of foci (Table 3).

TABLE 3: Risk of dengue cases occurring by groups and Aedes aegypti infestation

Source: Authors, based on the results

DR: Difference Ratio
CI: Confidence Interval
P: Statistical Significance

FINAL CONSIDERATIONS

The results demonstrate the usefulness of geographical information systems in the study of the spatial differentiation of dengue vulnerability.

• Although carried out retrospectively, the methodological procedures used - especially the digital database which is available at the Playa Municipality Health Department - maintain their usefulness for permanent dengue surveillance activities, as well as for other activities related to territorial management in health and other sectors.
  
  
• The results help distinguish spaces with different environmental and social contexts in the municipality, relatively homogenous within it; and to stratify dengue vulnerability, considering the spatiality of the vector foci.
  
  
• The dengue vulnerability spatial stratification results are validated by the high statistical association with spatiality of reported cases during the 2000 outbreak.
  
  
• The use of GIS in the health sector, as in other sectors, will increase as the advantages become recognized, especially their favorable effect on surveillance, control and protection of the health and welfare of the population. An essential purpose of the present research was to collaborate modestly to this end.

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THE AUTHORS

1. Candidate Researcher
2. PhD in Geographical Sciences at the Center for Health Studies and Human Welfare, University of Havana
3. Assistant Researcher
4. Assistant Professor, Geography Department, University of Havana

This paper was originally published in Revista Cubana de Salud Pública 2003; 29(4):353-365.