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Introduction: Canine soil-transmitted helminth (cSTH) parasites need specific environmental conditions to complete their life cycle. Toxocara canis and T. cati are the most important zoonotic cSTH, since they are the causal agents of human toxocariasis. Canine STHs are dispersed in feces from infected domestic and wildlife canines. In this study, the presence of STH in canine feces was evaluated in 34 crowded public parks and squares from San Juan Province (Argentina). Methods: Fecal samples were collected during different seasons in 2021-2022 and analyzed by standard coprological methods, including Sheather and Willis flotation and Telemann sedimentation. InfoStat 2020, OpenEpi V. 3.01 and R and RStudio® were used for statistical analysis and QGIS 3.16.10 for mapping. Results: From a total of 1,121 samples collected, 100 (8.9%) were positive for at least one intestinal parasite (IP) and three cSTH species were detected: Toxocara spp., Toxascaris leonina and Trichuris vulpis. The most prevalent cSTH species was T. vulpis (64/1121; 0.057%), while the least prevalent was Toxocara spp. (19/1121; 0.017%). The detection of Toxocara spp. eggs was significantly different depending on the season. The geo-spatial variation of each cSTH per season is described. Discussion: This is the first study in San Juan Province to identify environmental contamination of cSTHs in public areas. The specific localization of areas with the presence of cSTH eggs could provide information to guide strategies to reduce the cSTH infection burden in dogs and promote serological screening of the human population for Toxocara spp. Given the zoonotic nature of Toxocara spp. We hope this information will help to reinforce activities of control programs, focusing on the "One Health" approach.

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Spatial expansions of vampire bat-transmitted rabies (VBR) are increasing the risk of lethal infections in livestock and humans in Latin America. Identifying the drivers of these expansions could improve current approaches to surveillance and prevention. We aimed to identify if VBR spatial expansions are occurring in Colombia and test factors associated with these expansions. We analyzed 2336 VBR outbreaks in livestock reported to the National Animal Health Agency (Instituto Colombiano Agropecuario-ICA) affecting 297 municipalities from 2000-2019. The area affected by VBR changed through time and was correlated to the reported number of outbreaks each year. Consistent with spatial expansions, some municipalities reported VBR outbreaks for the first time each year and nearly half of the estimated infected area in 2010-2019 did not report outbreaks in the previous decade. However, the number of newly infected municipalities decreased between 2000-2019, suggesting decelerating spatial expansions. Municipalities infected later had lower cattle populations and were located further from the local reporting offices of the ICA. Reducing the VBR burden in Colombia requires improving vaccination coverage in both endemic and newly infected areas while improving surveillance capacity in increasingly remote areas with lower cattle populations where rabies is emerging.

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Green space or natural vegetation may reduce obesity risk by increasing opportunities for physical activity or reducing stress and exposure to other pollutants. Obesity prevalence in Mexico is ranked among the highest in the world. However, research on the association between green space and obesity in Mexico is lacking. We used data from the National Nutrition Survey in Mexico (2018-2019), a nationally representative sample of Mexican adults. The analytical sample included participants between 20-59 years of age (n = 12,631). We assessed exposure to green space using a 30 m resolution Landsat satellite Normalized Difference Vegetation Index (NDVI) from 2018. Linear regression models examined associations between NDVI and body mass index (BMI), adjusting for confounders. The mean age of the study sample was 38 (SD 0.19) years. Participants living in areas with the highest green space exposure had the lowest education level (53.51%) and socioeconomic status (28.38%) and were located in central (33.01%), south (30.37%), and rural areas (21.05%). Higher residential exposure to green space was associated with a mean decrease in BMI of -1.1 kg/m2 (95% CI: -1.59, -0.68). This is one of the first studies in Latin America to suggest a protective association between green space and obesity among Mexican adults.

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BACKGROUND: Leptospirosis is among the leading zoonotic causes of morbidity and mortality worldwide. Knowledge about spatial patterns of diseases and their underlying processes have the potential to guide intervention efforts. However, leptospirosis is often an underreported and misdiagnosed disease and consequently, spatial patterns of the disease remain unclear. In the absence of accurate epidemiological data in the urban agglomeration of Santa Fe, we used a knowledge-based index and cluster analysis to identify spatial patterns of environmental and socioeconomic suitability for the disease and potential underlying processes that shape them. METHODS: We geocoded human leptospirosis cases derived from the Argentinian surveillance system during the period 2010 to 2019. Environmental and socioeconomic databases were obtained from satellite images and publicly available platforms on the web. Two sets of human leptospirosis determinants were considered according to the level of their support by the literature and expert knowledge. We used the Zonation algorithm to build a knowledge-based index and a clustering approach to identify distinct potential sets of determinants. Spatial similarity and correlations between index, clusters, and incidence rates were evaluated. RESULTS: We were able to geocode 56.36% of the human leptospirosis cases reported in the national epidemiological database. The knowledge-based index showed the suitability for human leptospirosis in the UA Santa Fe increased from downtown areas of the largest cities towards peri-urban and suburban areas. Cluster analysis revealed downtown areas were characterized by higher levels of socioeconomic conditions. Peri-urban and suburban areas encompassed two clusters which differed in terms of environmental determinants. The highest incidence rates overlapped areas with the highest suitability scores, the strength of association was low though (CSc r = 0.21, P < 0.001 and ESc r = 0.19, P < 0.001). CONCLUSIONS: We present a method to analyze the environmental and socioeconomic suitability for human leptospirosis based on literature and expert knowledge. The methodology can be thought as an evolutive and perfectible scheme as more studies are performed in the area and novel information regarding determinants of the disease become available. Our approach can be a valuable tool for decision-makers since it can serve as a baseline to plan intervention measures.

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Purpose of Review: Review comprehensive data on rates of toxoplasmosis in Panama and Colombia. Recent Findings: Samples and data sets from Panama and Colombia, that facilitated estimates regarding seroprevalence of antibodies to Toxoplasma and risk factors, were reviewed. Summary: Screening maps, seroprevalence maps, and risk factor mathematical models were devised based on these data. Studies in Ciudad de Panamá estimated seroprevalence at between 22 and 44%. Consistent relationships were found between higher prevalence rates and factors such as poverty and proximity to water sources. Prenatal screening rates for anti-Toxoplasma antibodies were variable, despite existence of a screening law. Heat maps showed a correlation between proximity to bodies of water and overall Toxoplasma seroprevalence. Spatial epidemiological maps and mathematical models identify specific regions that could most benefit from comprehensive, preventive healthcare campaigns related to congenital toxoplasmosis and Toxoplasma infection.

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Bovine leptospirosis is a bacterial disease that affects cattle herds, causing economic losses due to reproductive problems which require expensive treatments. The main source of transmission for cattle is still uncertain, but rodents and bats can play an important role in the transmission cycle by being maintenance hosts for the pathogenic species of the bacterium and spreading it through urine. In this study, we characterize possible risk areas for bovine leptospirosis exposure in the state of Veracruz, Mexico, based on the geographical distribution of flying (bats) and terrestrial (rodents and opossums) wild hosts of Leptospira sp. reported in Mexico, in addition to climate, geography, soil characteristics, land use and human activities (environmental variables). We used a generalized linear regression model to understand the association between the frequency of anti-Leptospira sp. antibodies (a proxy of exposure) in cattle herds exposed to Leptospira, the favourability of wild hosts of Leptospira as well as the environmental variables. The parameterized model explained 12.3% of the variance. The frequency of anti-Leptospira sp. antibodies exposure in cattle herds was associated with elevation, geographic longitude, pH of the soil surface and environmental favourability for the presence of rodents, opossums and bats. The variation in exposure was mainly explained by a longitudinal gradient (6.4% of the variance) and the favourability-based indices for wild hosts (9.6% of the variance). Describing the possible risks for exposure to Leptospira in an important and neglected livestock geographical region, we provide valuable information for the selection of areas for diagnosis and prevention of this relevant disease.

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BACKGROUND: A proactive approach to preventing and responding to emerging infectious diseases is critical to global health security. We present a three-stage approach to modeling the spatial distribution of outbreak vulnerability to Aedes aegypti-vectored diseases in Perú. METHODS: Extending a framework developed for modeling hemorrhagic fever vulnerability in Africa, we modeled outbreak vulnerability in three stages: index case potential (stage 1), outbreak receptivity (stage 2), and epidemic potential (stage 3), stratifying scores on season and El Niño events. Subsequently, we evaluated the validity of these scores using dengue surveillance data and spatial models. RESULTS: We found high validity for stage 1 and 2 scores, but not stage 3 scores. Vulnerability was highest in Selva Baja and Costa, and in summer and during El Niño events, with index case potential (stage 1) being high in both regions but outbreak receptivity (stage 2) being generally high in Selva Baja only. CONCLUSIONS: Stage 1 and 2 scores are well-suited to predicting outbreaks of Ae. aegypti-vectored diseases in this setting, however stage 3 scores appear better suited to diseases with direct human-to-human transmission. To prevent outbreaks, measures to detect index cases should be targeted to both Selva Baja and Costa, while Selva Baja should be prioritized for healthcare system strengthening. Successful extension of this framework from hemorrhagic fevers in Africa to an arbovirus in Latin America indicates its broad utility for outbreak and pandemic preparedness and response activities.

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The outbreak of SARS-CoV-2 in Wuhan, China in late December 2019 became the harbinger of the COVID-19 pandemic. During the pandemic, geospatial techniques, such as modeling and mapping, have helped in disease pattern detection. Here we provide a synthesis of the techniques and associated findings in relation to COVID-19 and its geographic, environmental, and socio-demographic characteristics, following the Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) methodology for scoping reviews. We searched PubMed for relevant articles and discussed the results separately for three categories: disease mapping, exposure mapping, and spatial epidemiological modeling. The majority of studies were ecological in nature and primarily carried out in China, Brazil, and the USA. The most common spatial methods used were clustering, hotspot analysis, space-time scan statistic, and regression modeling. Researchers used a wide range of spatial and statistical software to apply spatial analysis for the purpose of disease mapping, exposure mapping, and epidemiological modeling. Factors limiting the use of these spatial techniques were the unavailability and bias of COVID-19 data-along with scarcity of fine-scaled demographic, environmental, and socio-economic data-which restrained most of the researchers from exploring causal relationships of potential influencing factors of COVID-19. Our review identified geospatial analysis in COVID-19 research and highlighted current trends and research gaps. Since most of the studies found centered on Asia and the Americas, there is a need for more comparable spatial studies using geographically fine-scaled data in other areas of the world.

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This paper presents an empirically grounded call for a more nuanced engagement and situatedness with placial characteristics within a spatial epidemiology frame. By using qualitative data collected through interviews and observation to parameterise standard and spatial regression models, and through a critical interpretation of their results, we present initial inroads for a situated spatial epidemiology and an analytical framework for health/medical geographers to iteratively engage with data, modelling, and the context of both the subject and process of analysis. In this study, we explore the socioeconomic factors that influence homicide rates in the Brazilian state of Alagoas from a critical public health perspective. Informed by field observation and interviews with 24 youths in low-income neighbourhoods and prisons in Alagoas, we derive and critically reflect on three regression models to predict municipal homicide rates from 2016-2020. The model results indicate significant effects for the male population, persons without elementary school completion, households with reported income, divorced persons, households without piped water, and persons working outside their home municipality. These results are situated in the broader socioeconomic context, trajectories, and cycles of inequality in the study area and underscore the need for integrative and contextually engaged mixed method study design in spatial epidemiology.

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Cystic echinococcosis (CE) is a parasitic zoonosis, caused by the larval stage of Echinococcus granulosus. This disease has a worldwide distribution and is considered an important zoonosis in Chile, especially in regions where raising livestock dominates. We aimed to describe the spatial distribution and risk factors for CE in cattle and sheep slaughtered in the Aysén Region, Chile between 2015 and 2016, to inform disease control in this hyper-endemic region. Clustering and hotspot analyses of CE at the farm-level were performed (Moran's global index, local indicator of spatial autocorrelation (LISA), and the scan statistic Poisson model), and we used spatial interpolation to display areas with a higher risk of CE. Mixed effects logistic regression models were fit to assess the association between municipality of origin and age of animals and CE detected at slaughter, with the farm of origin included as a random effect. Overall, data from 1532 cattle farms (1078 geocoded) and 30,805 cattle were analyzed, with a 64 % and 39 % CE prevalence at the farm and animal-level, respectively. For sheep farms, data from 381 (296 geocoded) farms and 58,223 sheep were analyzed, with a 71 % and 18 % CE prevalence at the farm and animal-level, respectively. Globally, the CE prevalence in both cattle and sheep farms was not clustered. However, we found 14 cattle and 23 sheep farms with high prevalence that were locally clustered. We also detected 6 and 11 clusters in cattle and sheep farms, respectively. Risk of reported CE varied according to municipalities of origin, and the age of animals. This study confirms that the Aysén region is a hyper-endemic region for CE. It demonstrates the usefulness of the traceability of animals slaughtered for understanding the epidemiology of CE. The results suggest that in this hyper-endemic region in which there are limited financial resources available, that intervention activities - at the beginning of a control program - should be focused on farms with high prevalence and identified disease clusters.

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OBJECTIVE: The ubiquity of cribra orbitalia in skeletal samples has led to rigorous debate over their etiology, with most concluding that nutrition, physiological stressors, and environmental disease vectors synergistically contribute to lesion development. To parse the relative contributions of these etiological factors in the prehistoric Andes, this spatial paleopathological meta-analysis investigates the relationship between population-wide prehistoric Andean cribra orbitalia rates and geographic, climatic, and hydrological variables. METHODS: Crude prevalence patterns of cribra orbitalia from 61 archaeological sites were plotted and analyzed with geostatistical methods to explore spatial patterns in the distribution of anemia-associated lesions. Multiple linear regression modeling was performed on 19 spatial variables suspected to contribute to various forms of anemia that result in cribrotic lesions. RESULTS: Spatially-clustered high cribra orbitalia rates exist around the Central Peruvian coast, but are paradoxically low on the Ecuadorian coast. Multiple regression shows that elevation, temperature, and precipitation were not predictive of lesion rates. Multiple regression models show that aridity and seasonal variability in freshwater supply, together, explained a third of the variation in lesion rates. CONCLUSION: While cribra orbitalia has long been tied to coastal proximity, these results suggest environmental constraints such as the need for water storage could have promoted malnutrition and pathogenic infection more than mere coastal proximity. LIMITATIONS OF THIS STUDY: This analysis is limited by the paucity of data from highland sites and by the assumption that burials are local to the excavation site. SUGGESTIONS FOR FUTURE RESEARCH: Future studies will integrate isotopic and remotely-sensed data into models to explore links between water security, nutrition, and disease.

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Abstract Geographical variation on hip fractures (HF) may be related to the geographical variation of drinking water composition (DWC); minerals in drinking water may contribute to its fragility. We aim to investigate the effects of DWC on HF risk in Portugal (2000-2010). From National Hospital Discharge Register we selected admissions of patients aged ≥50 years, diagnosed with HF caused by low/moderate energy traumas. Water components and characteristics were selected at the municipality level. A spatial generalized additive model with a negative binomial distribution as a link function was used to estimate the association of HF with variations in DWC. There were 96,905HF (77.3% in women). The spatial pattern of HF risk was attenuated after being adjusted for water parameters. Results show an indirect association between calcium, magnesium, and iron and HF risk but no clear relation between aluminum, cadmium, fluoride, manganese, or color and HF risk. Regarding pH, the 6.7pH and 7pH interval seems to pose a lower risk. Different dose-response relationships were identified. The increase of calcium, magnesium, and iron values in DWC seems to reduce regional HF risk. Long-term exposure to water parameters, even within the regulatory limits, might increase the regional HF risk.

Resumo A variabilidade espacial existente na fratura do colo do fêmur (FCF) pode estar relacionada com a variabilidade geográfica da composição da água para consumo (CAC), devido à ação dos minerais na fragilidade óssea. O objetivo do artigo foi investigar o efeito da CAC no risco de FCF em Portugal (2000-2010). Do registo nacional de altas hospitalares, foram selecionadas todas as admissões em indivíduos ≥50, com diagnóstico de FCF causado por trauma de baixo/moderado impacto. Os componentes e características da água foram usados ao nível do município. Um modelo espacial aditivo generalizado, com a distribuição binomial negativa como função de ligação, foi usado para estimar a associação de FCF e as variações da CAC. Foram selecionadas 96.905 FCF (77,3% em mulheres). O padrão espacial de risco de FCF foi atenuado após ser ajustado pelos parâmetros da CAC. Os resultados mostraram uma associação indireta com cálcio, magnésio e ferro. No entanto, com alumínio, cádmio, fluoreto, manganês e cor, a associação com o risco não foi clara. O intervalo de pH de 6,7 a 7 parece apresentar um menor risco. Foram identificadas diferentes dose-resposta. O aumento do cálcio, magnésio e ferro na CAC parece reduzir o risco regional de FCF. Uma exposição a longo prazo, mesmo obedecendo aos limites impostos por lei, parece aumentar o risco regional de FCF.

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Zika virus (ZIKV) is an arbovirus transmitted mainly by Aedes aegypti mosquitoes. Recent scientific evidence on Culex quinquefasciatus has suggested its potential as a vector for ZIKV, which may change the current risk zones. We aimed to quantify the world population potentially exposed to ZIKV in a spatially explicit way, considering the primary vector (A. aegypti) and the potential vector (C. quinquefasciatus). Our model combined species distribution modelling of mosquito species with spatially explicit human population data to estimate ZIKV exposure risk. We estimated the potential global distribution of C. quinquefasciatus and estimated its potential interaction zones with A. aegypti. Then we evaluated the risk zones for ZIKV considering both vectors. Finally, we quantified and compared the people under risk associated with each vector by risk level, country and continent. We found that C. quinquefasciatus had a more temperate distribution until 42° in both hemispheres, while the risk involving A. aegypti is concentrated mainly in tropical latitudes until 35° in both hemispheres. Globally, 4.2 billion people are under risk associated with ZIKV. Around 2.6 billon people are under very high risk associated with C. quinquefasciatus and 1 billion people associated with A. aegypti. Several countries could be exposed to ZIKV, which emphasises the need to clarify the competence of C. quinquefasciatus as a potential vector as soon as possible. The models presented here represent a tool for risk management, public health planning, mosquito control and preventive actions, especially to focus efforts on the most affected areas.

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BACKGROUND: Yellow fever virus is a mosquito-borne flavivirus that persists in an enzoonotic cycle in non-human primates (NHPs) in Brazil, causing disease in humans through spillover events. Yellow fever (YF) re-emerged in the early 2000s, spreading from the Amazon River basin towards the previously considered low-risk, southeastern region of the country. Previous methods mapping YF spillover risk do not incorporate the temporal dynamics and ecological context of the disease, and are therefore unable to predict seasonality in spatial risk across Brazil. We present the results of a bagged logistic regression predicting the propensity for YF spillover per municipality (administrative sub-district) in Brazil from environmental and demographic covariates aggregated by month. Ecological context was incorporated by creating National and Regional models of spillover dynamics, where the Regional model consisted of two separate models determined by the regions' NHP reservoir species richness (high vs low). RESULTS: Of the 5560 municipalities, 82 reported YF cases from 2001 to 2013. Model accuracy was high for the National and low reservoir richness (LRR) models (AUC = 0.80), while the high reservoir richness (HRR) model accuracy was lower (AUC = 0.63). The National model predicted consistently high spillover risk in the Amazon, while the Regional model predicted strong seasonality in spillover risk. Within the Regional model, seasonality of spillover risk in the HRR region was asynchronous to the LRR region. However, the observed seasonality of spillover risk in the LRR Regional model mirrored the national model predictions. CONCLUSIONS: The predicted risk of YF spillover varies with space and time. Seasonal trends differ between regions indicating, at times, spillover risk can be higher in the urban coastal regions than the Amazon River basin which is counterintuitive based on current YF risk maps. Understanding the spatio-temporal patterns of YF spillover risk could better inform allocation of public health services.

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Pythium insidiosum is a widespread pathogen that causes pythiosis, a disease with severe health consequences in horses and humans worldwide. Latin America hosts one of the largest, but scattered, horse herds, making it critical to identify areas at high risk of pythiosis transmission to help guide surveillance in areas with disease transmission risk. We utilized ecological niche modelling and epidemiological data to reconstruct the ecological conditions for pathogen circulation to identify areas with potential risk of pythiosis in Brazil and Uruguay. We surveyed 338 horse farm locations in southern Brazil and reconstructed the landscape conditions where the disease is endemic, based on the association between high-resolution satellite imagery and P. insidiosum serology. The final model was projected to the entire Brazil-Uruguay border region to predict areas at risk of disease transmission. We detected 66 seropositive farms and risk of infection in areas with low vegetation and low temperatures. There was a significant difference between seropositive and seronegative locations, mainly during the summer, suggesting that P. insidiosum circulates under specific landscape conditions. Areas that were unsuitable for P. insidiosum circulation were clustered in the central, north-eastern, and north-western regions of the study area. Our findings suggest that P. insidiosum is a generalist pathogen that has the potential to circulate across broad areas in Uruguay and Rio Grande do Sul in Brazil. The risk maps generated may help stakeholders with disease prevention, as well as highlight pythiosis as a potential transboundary disease with economic and public health importance.

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The potato yellow vein disease, caused by the potato yellow vein virus (PYVV), is a limiting potato disease in northern South America. The virus can be transmitted either by the greenhouse whitefly (GWF), Trialeurodes vaporariorum (Westwood) (Hemiptera: Aleyrodidae), or through vegetative propagules, such as infected tubers. Recently, GWF populations have been spotlighted as one of the main drivers of PYVV re-emergence, and consequently, PYVV management has been predominantly directed toward vector control, which is heavily based on insecticide use. However, the drivers of the PYVV outbreaks as well as the contribution of GWF populations on the spread of PYVV among potato crops are still not completely understood. This study aims to assess the role of the GWF as a driver of the PYVV epidemic in the potato-producing areas in Colombia, one of the countries more severely affected by the PYVV epidemic, and whose geography allows the study of the spatial association between the vector and the disease epidemic across a wide altitude range. The geographical clusters where the PYVV epidemic is concentrated, as well as those of farms affected by the GWF were identified using a novel spatial epidemiology approach. The influence of altitude range on the association between PYVV and T. vaporarioum was also assessed. We found a relatively poor spatial association between PYVV epidemic and the presence of the GWF, especially at altitudes above 3,000 m above mean sea level. Furthermore, GWF populations could only explain a small fraction of the extent of the PYVV epidemic in Colombia. Movement of infected seed tubers might be the main mechanism of dispersion, and could be a key driver for the PYVV infection among potato crops. Agricultural policies focused on improving quality of seed tubers and their appropriate distribution could be the most efficient control intervention against PYVV dispersion.

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BACKGROUND: The reason why Cystic Fibrosis (CF) is the most common fatal genetic disease among Caucasians has been incompletely studied. We aimed at deepening the hypothesis that CF carriers have a relative protection against Mycobacterium tuberculosis (Mtb) infection. METHODS: Applying spatial epidemiology, we studied the link between CF carriership rate and tuberculosis (TB) incidence in Brazil. We corrected for 5 potential environmental and 2 immunological confounders in this relation: monthly income, sanitary provisions, literacy rates, racial composition and population density along with AIDS incidence rates and diabetes mellitus type 2. Smoking data were incomplete and not available for analysis. RESULTS: A significant, negative correlation between CF carriership rate and TB incidence, independent of any of the seven confounders was found. CONCLUSION: We provide exploratory support for the hypothesis that carrying a single CFTR mutation arms against Mtb infections.

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The recent increase in emerging fungal diseases is causing unprecedented threats to biodiversity. The origin of spread of the frog-killing fungus Batrachochytrium dendrobatidis (Bd) is a matter of continued debate. To date, the historical amphibian declines in Brazil could not be attributed to chytridiomycosis; the high diversity of hosts coupled with the presence of several Bd lineages predating the reported declines raised the hypothesis that a hypervirulent Bd genotype spread from Brazil to other continents causing the recent global amphibian crisis. We tested for a spatio-temporal overlap between Bd and areas of historical amphibian population declines and extinctions in Brazil. A spatio-temporal convergence between Bd and declines would support the hypothesis that Brazilian amphibians were not adapted to Bd prior to the reported declines, thus weakening the hypothesis that Brazil was the global origin of Bd emergence. Alternatively, a lack of spatio-temporal association between Bd and frog declines would indicate an evolution of host resistance in Brazilian frogs predating Bd's global emergence, further supporting Brazil as the potential origin of the Bd panzootic. Here, we Bd-screened over 30 000 museum-preserved tadpoles collected in Brazil between 1930 and 2015 and overlaid spatio-temporal Bd data with areas of historical amphibian declines. We detected an increase in the proportion of Bd-infected tadpoles during the peak of amphibian declines (1979-1987). We also found that clusters of Bd-positive samples spatio-temporally overlapped with most records of amphibian declines in Brazil's Atlantic Forest. Our findings indicate that Brazil is post epizootic for chytridiomycosis and provide another piece to the puzzle to explain the origin of Bd globally.

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The classical Ross-Macdonald model is often utilized to model vector-borne infections; however, this model fails on several fronts. First, using measured (or estimated) parameters, which values are accepted from the literature, the model predicts a much greater number of cases than what is usually observed. Second, the model predicts a single large outbreak that is followed by decades of much smaller outbreaks, which is not consistent with what is observed. Usually towns or cities report a number of recurrences for many years, even when environmental changes cannot explain the disappearance of the infection between the peaks. In this paper, we continue to examine the pitfalls in modelling this class of infections, and explain that, if properly used, the Ross-Macdonald model works and can be used to understand the patterns of epidemics and even, to some extent, be used to make predictions. We model several outbreaks of dengue fever and show that the variable pattern of yearly recurrence (or its absence) can be understood and explained by a simple Ross-Macdonald model modified to take into account human movement across a range of neighbourhoods within a city. In addition, we analyse the effect of seasonal variations in the parameters that determine the number, longevity and biting behaviour of mosquitoes. Based on the size of the first outbreak, we show that it is possible to estimate the proportion of the remaining susceptible individuals and to predict the likelihood and magnitude of the eventual subsequent outbreaks. This approach is described based on actual dengue outbreaks with different recurrence patterns from some Brazilian regions.

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BACKGROUND: Breast cancer is the most common form of cancer affecting women in the Bahamas, which consists of many islands. This is the first attempt to identify which island has the highest occurrence of breast cancer. OBJECTIVE: The aim of this study was to describe the sociodemographical and spatial features of breast cancer in the Bahamas in 2009-2011. METHODS: A review of the medical records of all women with a confirmed diagnosis of breast cancer during the period January 1, 2009-December 31, 2011, was undertaken. Data were first obtained from the National Oncology Board of the Bahamas and validated by a review of the medical records. The patient address was geocoded and mapped using ArcGIS 10.0 Environmental Systems Research Institute (ESRI) to satellite images obtained from The Nature Conservancy in the Bahamas. RESULTS: We recruited 270 patients who satisfied the entry criteria. The cumulative incidences of breast cancer for the years 2009-2011 were 51.4, 45.4, and 51.4, respectively. Breast cancer occurred most often in women of African origin with a mean age at diagnosis of 56.6 ± 13.8 years. Ductal carcinoma was the most common histological type observed with most cancers occurring in Grade II or higher and presenting as late stage (≥ Stage II). Surgery was the preferred method of treatment with modified radical mastectomy being the procedure of choice. Spatial distribution of cases across the Bahamas revealed one cluster, which is present on the island of New Providence. Further analysis of New Providence showed a consistently skewed kernel density in the central and eastern regions, compared with a scattered distribution in the southern and western regions. CONCLUSION: The island of New Providence had the highest occurrence of breast cancer among all the islands of the Bahamas. The increasing incidence of breast cancer in young women is likely to impose a significant burden on the future of Bahamian health care.