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On the Relationship Between the Environmental History and the Epidemiological Situation of Argentine Hemorrhagic Fever

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On the Relationship Between the Environmental History and the Epidemiological Situation of Argentine Hemorrhagic Fever Ecol Res (2008) 23: 217–225 DOI 10.1007/s11284-007-0371-2 ORIGINAL ARTICLE Francisco Polop Æ Cecilia Provensal Æ Marcelo Scavuzzo Mario Lamfri Æ Gladys Caldero´n Æ Jaime Polop On the relationship between the environmental history and the epidemiological situation of Argentine hemorrhagic fever Received: 21 June 2006 / Accepted: 9 February 2007 / Published online: 11 April 2007 Ó The Ecological Society of Japan 2007 Abstract The aim of this work was to establish the close relationship between the state of AHF incidence relationship between different Argentine hemorrhagic and the environmental history of sites suggesting the fever (AHF) epidemiological situations found at differ- possibility of predicting epidemiological behavior using ent sites and the related large-scale environmental environmental conditions derived from satellite data. conditions. Large-scale environmental records (vegeta- tion index, temperature, precipitation and elevation) Keywords Environmental variables Æ Satellite images Æ were obtained from a series of monthly NOAA satellite Abundance Æ Rodents Æ Argentine hemorrhagic fever images and global databases considered suitable for modeling climatic and other environmental determinants Abbreviations AHF: Argentine hemorrhagic fever Æ of large-scale biogeographical regions. The temporal NDVI: Normalized difference vegetation index Æ LST: variation in vegetation for cycles of winter-summer Land surface temperature Æ DEM: Digital elevation showed a greater variation in the nonendemic region model Æ AVHRR: Advanced very-high-resolution than in the other two regions. On the other hand, the radiometer Æ NOAA: National Oceanic and average of the temporal variation in precipitation in Atmospheric Administration Æ PCA: Principal cycles of spring–autumn was more different in the component analysis Æ ROI: Regions of interest historic region than in the other two regions, and land surface temperatures in cycles of spring–autumn showed differences between the epidemic region and the other two regions. We found good separation among the Introduction epidemic, historic and nonendemic sites, with the great- est difference found between epidemic and nonendemic In Argentina, Calomys musculinus (Rodentia, Muridae) sites. The classification of sites showed a tendency for is considered to be a host of Junin (JUN) virus, the grouping according to the epidemiological situation, but etiological agent of Argentine hemorrhagic fever (AHF) there was some variation. It seems possible to establish a (Sabattini and Maiztegui 1970). In longitudinal studies, the number of cases of AHF was correlated with chan- F. Polop Æ C. Provensal (&) Æ J. Polop ges in the density of C. musculinus populations (Sabat- Ciencias Naturales Department, tini and Maiztegui 1970; Mills et al. 1991b, 1992). These Universidad Nacional de Rı´o Cuarto, studies identified the seasonal and year-to-year fluctua- Agencia Postal No 3, 5800, Rı´o Cuarto, tions in incidence and prevalence as well as the duration Co´rdoba, Argentina of infection in the hosts. AHF epidemics are highly E-mail: [email protected] Tel.: +54-0358-4676236 seasonal, with the peak number of cases and peak rodent populations occurring in May when autumn crops are M. Scavuzzo Æ M. Lamfri harvested. In years when corn mouse population densi- Comisio´n Nacional de Actividades Espaciales (CONAE), ties were relatively low, the magnitude of annual AHF Instituto Gulich. CETT, Ruta C45 Km8 Falda del Can˜ ete, CP 5187, Co´rdoba, Argentina epidemics was also low. But in a year (1990) when corn E-mail: [email protected] mouse populations and numbers of infected corn mice reached extremely high levels, an unusually severe epi- G. Caldero´n demic of AHF cases followed (Mills et al. 1992). Instituto Nacional de Enfermedades Virales Humanas (INEVH), Monteagudo 2510. 2700 Pergamino, Buenos Aires, Argentina The temporal and spatial differences in reservoir E-mail: [email protected] abundance could lead to significant variation in risk or Tel.: +54-02477-429712 incidence. Several ecological processes can result in 218 strong spatial patterns of risk or incidence. Here we try to understand the causes that govern the spatial pattern and rate of AHF spread. Changes in the environment may be associated with favorable weather patterns, accelerated vegetation growth, and availability of food (Mills and Childs 1998). In other zoonoses, it has been demonstrated that population levels and the crowding of reservoirs are important factors that can affect the prevalence of den- sity-dependent infectious disease (Pikula et al. 2002). Laboratory studies with C. musculinus showed that transmission of Junin virus was generally horizontal, taking place among rodents in close contact to each other (Sabattini et al. 1977). Mills et al. (1992), Mills (1999), and Sabattini et al. (1977) suggest that most rodent-rodent infection could be acquired by horizontal transmission during aggressive encounters among adults defending their territories. In AHF, increased prevalence of infection in some sites may be due to greater rodent abundance than in others. A high density for the reservoir population may contribute to horizontal transmission of Junin virus among rodents, to the maintenance of the virus in the field, and to transmission to humans. Low abundance may prevent the virus from persisting in a population (Polop et al. 2007). If the host-virus system requires a minimum rodent population density to ensure viral maintenance through rodent-to-rodent contact, the density of reservoir populations should be a key factor in the incidence of human disease. Polop et al. (2007) demonstrate differences in rodent total abundance be- tween endemic and nonendemic sites, and different rel- ative abundances of C. musculinus at a geographic scale. Although C. musculinus is widely distributed in cen- tral and northern Argentina (Redford and Eisenberg Fig. 1 Potential distribution area of Calomys musculinus (Porcasi 1992; Porcasi et al. 2005), the AHF-endemic area et al. 2005)(dark gray) and distribution area of AHF (endemic occupies only a limited region of the central Argentine region) (light gray) pampa (Mills 1999) (Fig. 1). The limits of the AHF- endemic area were defined by the occurrence of the suggests that its distribution depends on weather con- disease in humans, but infected rodents have been de- ditions such as temperature and precipitation, which tected beyond that limit (Mills et al. 1991a; Enrı´a et al. guarantee the provision of food and shelter (Busch et al. 1998). Moreover, the population of C. musculinus ap- 2000). Some authors (de Villafan˜ e et al. 1977; Polop pears to be continuous inside the AHF-endemic area et al. 1982; Polop et al. 2007) obtained differences in the (Maiztegui et al. 1986). However, while the prevalence of abundance values of that species among different sites in infection in reservoir populations may be very high in the same season of the year, and other authors (Kravetz some sites, it may be very low or absent at nearby sites. and Polop 1983) relate those differences to the floristic The lack of coincidence between host distribution limits composition and the structure of landscape components. and AHF-endemic area, and the spatial variability of Considering that environmental variables can affect the disease incidence in the endemic area, may be due to a population abundance of Calomys (Mills 1999; de Vil- combination of causes involving host genetics, geo- lafan˜ e et al. 1992), it is valid to suppose that the ob- graphical boundaries, local extinctions of rodents or served abundance differences among the sites (Polop virus subpopulations, environmental variables, and the et al. 2007) could be associated with the environmental properties of host systems that are required to support differences. Recognizing also the existence of a positive long-term maintenance of viral symbionts (Mills 1999; relation between host abundance and the spatial and Polop et al. 2007). temporal course of the disease (Mills 1999), environ- The AHF spatial variation arises from underlying mental factors would differ among the sites with differ- variation in the physiological and/or biological condi- ent epidemiological characterizations of AHF. tions that support the reservoirs. C. musculinus prefers Recent advances in remote sensing of climatic and mainly grassy breaks in agricultural regions, and this ecological features allow the identification of particular 219 environments that are suitable habitats for different species. Techniques that model species’ requirements using environmental characteristics at sites with known occurrence represent a great advance in the production of range maps (Walker and Cocks 1991; Carpenter et al. 1993; Skov 2000; Peterson 2001). These tools introduce a new global framework for epidemiological studies by providing new variables that could improve population and epidemic modeling, as well as prevention systems for emerging infectious diseases (Cheek et al. 1998; En- gelthaler et al. 1999; Beck et al. 2000; Boone et al. 2000; Glass et al. 2000; Chaput et al. 2002). We aimed to find what factors govern the spatial pattern and the rate of AHF spread. In this context, the aim of the present study was to determine environmental differences among the sites with different characteriza- tion of the AHF incidence using remote sensing data and Fig. 2 Georeferenced sites with different epidemiological charac- techniques. terization of AHF: epidemic (light gray), historic (dark gray) and nonendemic (white)
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