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Anxiety can be a protective emotion when animals face aversive conditions, but is commonly associated with various neuropsychiatric disorders when pathologically exacerbated. Drug repurposing has emerged as a valuable strategy based on utilizing the existing pharmaceuticals for new therapeutic purposes. Ketamine, traditionally used as an anesthetic, acts as a non-competitive antagonist of the glutamate N-methyl-d-aspartate (NMDA) receptor, and shows potential anxiolytic and antidepressant effects at subanesthetic doses. However, the influence of ketamine on multiple behavioral domains in vertebrates is not completely understood. Here, we evaluated the potential modulatory effect of ketamine on the spatio-temporal exploratory dynamics and homebase-related behaviors in adult zebrafish using the open field test (OFT). Animals were exposed to subanesthetic concentrations of ketamine (0, 2, 20, and 40 mg/L) for 20 min and their locomotion-, exploration- and homebase-related behaviors were assessed in a single 30-min trial. Our data revealed that acute ketamine (20 and 40 mg/L) induced hyperlocomotion, as verified by the increased total distance traveled. All concentrations tested elicited circling behavior, a stereotyped-like response which gradually reduced across the periods of test. We also observed modulatory effects of ketamine on the spatio-temporal exploratory pattern, in which the reduced thigmotaxis and homebase activity, associated with the increased average length of trips, suggest anxiolytic-like effects. Collectively, our findings support the modulatory effects of ketamine on the spatio-temporal exploratory activity, and corroborate the utility of homebase-related measurements to evaluate the behavioral dynamics in zebrafish models.

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Cutaneous Leishmaniasis (CL) is a vector-borne disease caused by a protozoan of the genus Leishmania and is considered one of the most important neglected tropical diseases. The Brazilian Amazon Forest harbors one of the highest diversity of Leishmania parasites and vectors and is one of the main focuses of the disease in the Americas. Previous studies showed that some types of anthropogenic disturbances have affected the abundance and distribution of CL vectors and hosts; however, few studies have thoroughly investigated the influence of different classes of land cover and land-use changes on the disease transmission risk. Here, we quantify the effect of land use and land-cover changes on the incidence of CL in all municipalities within the Brazilian Amazon Forest, from 2001 to 2017. We used a structured spatiotemporal Bayesian model to assess the effect of forest cover, agriculture, livestock, extractivism, and- deforestation on CL incidence, accounting for confounding variables such as population, climate, socioeconomic, and spatiotemporal random effects. We found that the increased risk of CL was associated with deforestation, especially modulated by a positive interaction between forest cover and livestock. Landscapes with ongoing deforestation for extensive cattle ranching are typically found in municipalities within the Amazon Frontier, where a high relative risk for CL was also identified. These findings provide valuable insights into developing effective public health policies and land-use planning to ensure healthier landscapes for people.

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Wildfires are among the most common natural disasters in many world regions and actively impact life quality. These events have become frequent due to climate change, other local policies, and human behavior. Fire spots are areas where the temperature is significantly higher than in the surrounding areas and are often used to identify wildfires. This study considers the historical data with the geographical locations of all the "fire spots" detected by the reference satellites covering the Brazilian territory between January 2011 and December 2022, comprising more than 2.2 million fire spots. This data was modeled with a spatio-temporal generalized linear mixed model for areal unit data, whose inferences about its parameters are made in a Bayesian framework and use meteorological variables (precipitation, air temperature, humidity, and wind speed) and a human variable (land-use transition and occupation) as covariates. The meteorological variables humidity and air temperature showed the most significant impact on the number of fire spots for each of the six Brazilian biomes.

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OBJECTIVE: To analyse hospital case fatality and mortality related to Chagas disease (CD) in Brazil, 2000-2019. METHOD: This is a mixed ecological study with spatial and temporal trends, based on national population data from the Brazilian Ministry of Health - hospital admissions (HA) and death certificates (DC). Records with CD as a primary or secondary cause of death in HA and/or as an underlying or associated cause of death in DC were evaluated. Temporal trends were analysed by Joinpoint regression and the spatial distribution of age- and gender-adjusted rates, spatial moving averages, and standardized morbidity ratios. RESULTS: There were a total of 4,376 HA due to CD resulting in death in Brazil, with a hospital case fatality rate of 0.11/100,000 inhabitants. The Southeast region had the highest rate (63.9%, n = 2,796; 0.17/100,000 inhabitants). The general trend for this indicator in Brazil is upwards (average annual percentage change [AAPC] 7.5; 95% confidence interval [CI] 5.3 to 9.9), with increases in the North, Northeast and Southeast regions. During the same period 122,275 deaths from CD were registered in DC, with a mortality rate of 3.14/100,000 inhabitants. The highest risk of CD-related death was found among men (relative risk [RR] 1.27) and Afro-Brazilians (RR 1.63). There was a downward trend in CD mortality in the country (AAPC - 0.7%, 95%CI -0.9 to -0.5), with an increase in the Northeast region (AAPC 1.1%, 95%CI 0.6 to 1.6). Municipalities with a very high Brazilian Deprivation Index tended to show an increase in mortality (AAPC 2.1%, 95%CI 1.6 to 2.7), while the others showed a decrease. CONCLUSION: Hospital case fatality and mortality due to CD are a relevant public health problem in Brazil. Differences related to gender, ethnicity, and social vulnerability reinforce the need for comprehensive care, and to ensure equity in access to health in the country. Municipalities, states, and regions with indicators that reveal higher morbidity and mortality need to be prioritized.

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DNA metabarcoding and stable isotope analysis have significantly advanced our understanding of marine trophic ecology, aiding systematic research on foraging habits and species conservation. In this study, we employed these methods to analyse faecal and blood samples, respectively, to compare the trophic ecology of two Red-billed Tropicbird (Phaethonaethereus; Linnaeus, 1758) colonies on Mexican islands in the Pacific. Trophic patterns among different breeding stages were also examined at both colonies. Dietary analysis reveals a preference for epipelagic fish, cephalopods, and small crustaceans, with variations between colonies and breeding stages. Isotopic values (δ15N and δ13C) align with DNA metabarcoding results, with wider niches during incubation stages. Differences in diet are linked to environmental conditions and trophic plasticity among breeding stages, influenced by changing physiological requirements and prey availability. Variations in dietary profiles reflect contrasting environmental conditions affecting local prey availability.

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OBJECTIVES: In the American regions, Brazil accounts for 97% of visceral leishmaniasis (VL) cases, with a case fatality rate of approximately 10%. This study aimed to investigate the VL mortality distribution in Brazil and identify high-priority and high-risk areas for intervention strategies. STUDY DESIGN: This was an ecological study that analysed the spatial-temporal patterns of VL mortality in Brazilian municipalities. METHODS: Age-standardised VL mortality rates from the Global Burden of Disease study from 2001 to 2018 were used. The distribution of mortality in the municipalities was assessed, and subsequently the Local Index of Spatial Autocorrelation (LISA) analysis was conducted to identify contiguous areas with high mortality rates. Scan analysis identified clusters of high spatial-temporal risks. RESULTS: The highest mortality rates and clusters were in municipalities located in the Northeast region and in the states of Tocantins and Roraima (North region), Mato Grosso do Sul (Central-West region), and Minas Gerais (Southeast region). According to LISA, there was an increase in the number of municipalities classified as high priority from the first 3-year period (n = 434) to the last 3-year period (n = 644). The spatio-temporal analysis identified 21 high-risk clusters for VL mortality. CONCLUSION: Areas with a high risk of VL mortality should prioritise preventing transmission, invest in early diagnosis and treatment, and promote the training of healthcare professionals.

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We present a methodology designed to study the spatial heterogeneity of climate change. Our approach involves decomposing the observed changes in temperature patterns into multiple trend, cycle, and seasonal components within a spatio-temporal model. We apply this method to test the hypothesis of a global long-term temperature trend against multiple trends in distinct biomes. Applying this methodology, we delve into the examination of heterogeneity of climate change in Brazil-a country characterized by a spectrum of climate zones. The findings challenge the notion of a global trend, revealing the presence of distinct trends in warming effects, and more accelerated trends for the Amazon and Cerrado biomes, indicating a composition between global warming and deforestation in determining changes in permanent temperature patterns.

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Amid the COVID-19 pandemic, understanding the spatial and temporal dynamics of the disease is crucial for effective public health interventions. This study aims to analyze COVID-19 data in Peru using a Bayesian spatio-temporal generalized linear model to elucidate mortality patterns and assess the impact of vaccination efforts. Leveraging data from 194 provinces over 651 days, our analysis reveals heterogeneous spatial and temporal patterns in COVID-19 mortality rates. Higher vaccination coverage is associated with reduced mortality rates, emphasizing the importance of vaccination in mitigating the pandemic's impact. The findings underscore the value of spatio-temporal data analysis in understanding disease dynamics and guiding targeted public health interventions.

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Our study examines how dengue fever incidence is associated with spatial (demographic and socioeconomic) alongside temporal (environmental) factors at multiple scales in the city of Ibagué, located in the Andean region of Colombia. We used the dengue incidence in Ibagué from 2013 to 2018 to examine the associations with climate, socioeconomic, and demographic factors from the national census and satellite imagery at four levels of local spatial aggregation. We used geographically weighted regression (GWR) to identify the relevant socioeconomic and demographic predictors, and we then integrated them with environmental variables into hierarchical models using integrated nested Laplace approximation (INLA) to analyze the spatio-temporal interactions. Our findings show a significant effect of spatial variables across the different levels of aggregation, including human population density, gas and sewage connection, percentage of woman and children, and percentage of population with a higher education degree. Lagged temporal variables displayed consistent patterns across all levels of spatial aggregation, with higher temperatures and lower precipitation at short lags showing an increase in the relative risk (RR). A comparative evaluation of the models at different levels of aggregation revealed that, while higher aggregation levels often yield a better overall model fit, finer levels offer more detailed insights into the localized impacts of socioeconomic and demographic variables on dengue incidence. Our results underscore the importance of considering macro and micro-level factors in epidemiological modeling, and they highlight the potential for targeted public health interventions based on localized risk factor analyses. Notably, the intermediate levels emerged as the most informative, thereby balancing spatial heterogeneity and case distribution density, as well as providing a robust framework for understanding the spatial determinants of dengue.

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BACKGROUND: In Haiti, reported incidence and mortality rates for COVID-19 were lower than expected. We aimed to analyze factors at communal and individual level that might lead to an underestimation of the true burden of the COVID-19 epidemic in Haiti during its first two years. METHODS: We analyzed national COVID-19 surveillance data from March 2020 to December 2021, to describe the epidemic using cluster detection, time series, and cartographic approach. We performed multivariate Quasi-Poisson regression models to determine socioeconomic factors associated with incidence and mortality. We performed a mixed-effect logistic regression model to determine individual factors associated with the infection. RESULTS: Among the 140 communes of Haiti, 57 (40.7%) had a COVID-19 screening center, and the incidence was six times higher in these than in those without. Only 22 (15.7%) communes had a COVID-19 care center, and the mortality was five times higher in these than in those without. All the richest communes had a COVID-19 screening center while only 30.8% of the poorest had one. And 75% of the richest communes had a COVID-19 care center while only 15.4% of the poorest had one. Having more than three healthcare workers per 1000 population in the commune was positively associated with the incidence (SIR: 3.31; IC95%: 2.50, 3.93) and the mortality (SMR: 2.73; IC95%: 2.03, 3.66). At the individual level, male gender (adjusted OR: 1.11; IC95%: 1.01, 1.22), age with a progressive increase of the risk compared to youngers, and having Haitian nationality only (adjusted OR:2.07; IC95%: 1.53, 2.82) were associated with the infection. CONCLUSIONS: This study highlights the weakness of SARS-CoV-2 screening and care system in Haiti, particularly in the poorest communes, suggesting that the number of COVID-19 cases and deaths were probably greatly underestimated.

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Objective: To evaluate immunization coverage and dropout rates of the measles, mumps, and rubella vaccine across Brazilian regions. Methods: This ecological study employing a space-time approach used data from the National Immunization Program (PNI) and the Live Births Information System (SINASC). We estimated the annual variation (2014 to 2021) in immunization coverage and dropout rate of the measles, mumps, and rubella vaccine in children aged 12 and 15 months in the 5 570 Brazilian municipalities. Statistical analysis was conducted for the municipalities contained in each Brazilian region using the space-time scan technique, considering the Poisson probabilistic model and the hypothesis that municipalities with lower immunization coverage or high dropout rates would form space-time clusters. Results: From 2014 to 2021, 38.3% and 12.9% of municipalities achieved a coverage ≥ 95.0% in the first and second doses respectively; 53.6% of municipalities had a high dropout rate (20.0% to 49.9%) and 37.2% had a very high dropout rate. The Northeast region had primary clusters for low coverage of the first (2018 to 2021) and second vaccine doses (2020 to 2021) with higher relative risks (RR) compared to other primary clusters. The RR for high dropout rate was elevated in all Brazilian regions (1.57 to 26.23). Conclusions: In some Brazilian regions, the dropout rate has been high since 2014, signaling a risk of measles resurgence. In turn, space-time analysis indicated lower vaccination coverage in 2020, suggesting the influence of the COVID-19 pandemic.

Objetivo: Evaluar la cobertura de vacunación y las tasas de incumplimiento del esquema de vacunación triple viral en las macrorregiones de Brasil. Métodos: En este estudio ecológico, con un enfoque espaciotemporal, se utilizaron datos del Programa Nacional de Inmunización y del Sistema de Información sobre Recién Nacidos Vivos. Se estimó la variación anual de la cobertura de vacunación y la tasa de incumplimiento del esquema de vacunación triple viral en niños de 12 y 15 meses en 5570 municipios brasileños (en el período 2014-2021). El análisis estadístico se realizó en el conjunto de municipios de cada macrorregión brasileña mediante la técnica de barrido espaciotemporal, con un modelo probabilístico de Poisson y con la hipótesis de que los municipios con menor cobertura de vacunación o tasas altas de incumplimiento formarían conglomerados espaciotemporales. Resultados: En el período 2014-2021, el 38,3% y el 12,9% de los municipios alcanzó una cobertura ≥95,0% para la primera y la segunda dosis de la vacuna triple viral, respectivamente; el 53,6% de los municipios tuvo una tasa de incumplimiento alta (del 20,0% al 49,9%) y el 37,2% una tasa extremadamente alta. En la zona del nordeste se observaron los conglomerados primarios de cobertura baja de la primera y la segunda dosis de la vacuna triple viral (administradas en los períodos 2018-2021 y 2020-2021, respectivamente) con un mayor riesgo relativo (RR), en comparación con los demás conglomerados primarios. Se observó un RR alto de tener una tasa elevada de incumplimiento en todas las macrorregiones de Brasil (de entre 1,57 y 26,23). Conclusiones: En algunas macrorregiones, la tasa de incumplimiento había sido elevada desde el 2014, lo cual indica un riesgo de resurgimiento del sarampión. A su vez, en el análisis espaciotemporal se observó una menor cobertura de vacunación en el 2020, lo que denota la influencia de la pandemia de COVID-19.

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We record and analyze the movement patterns of the marsupial Didelphis aurita at different temporal scales. Animals trajectories are collected at a daily scale by using spool-and-line techniques and, with the help of radio-tracking devices, animals traveled distances are estimated at intervals of weeks. Small-scale movements are well described by truncated Lévy flight, while large-scale movements produce a distribution of distances which is compatible with a Brownian motion. A model of the movement behavior of these animals, based on a truncated Lévy flight calibrated on the small scale data, converges towards a Brownian behavior after a short time interval of the order of 1 week. These results show that whether Lévy flight or Brownian motion behaviors apply, will depend on the scale of aggregation of the animals paths. In this specific case, as the effect of the rude truncation present in the daily data generates a fast convergence towards Brownian behaviors, Lévy flights become of scarce interest for describing the local dispersion properties of these animals, which result well approximated by a normal diffusion process and not a fast, anomalous one. Interestingly, we are able to describe two movement phases as the consequence of a statistical effect generated by aggregation, without the necessity of introducing ecological constraints or mechanisms operating at different spatio-temporal scales. This result is of general interest, as it can be a key element for describing movement phenomenology at distinct spatio-temporal scales across different taxa and in a variety of systems.

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The flagellar movement of the mammalian sperm plays a crucial role in fertilization. In the female reproductive tract, human spermatozoa undergo a process called capacitation which promotes changes in their motility. Only capacitated spermatozoa may be hyperactivated and only those that transition to hyperactivated motility are capable of fertilizing the egg. Hyperactivated motility is characterized by asymmetric flagellar bends of greater amplitude and lower frequency. Historically, clinical fertilization studies have used two-dimensional analysis to classify sperm motility, despite the inherently three-dimensional (3D) nature of sperm motion. Recent research has described several 3D beating features of sperm flagella. However, the 3D motility pattern of hyperactivated spermatozoa has not yet been characterized. One of the main challenges in classifying these patterns in 3D is the lack of a ground-truth reference, as it can be difficult to visually assess differences in flagellar beat patterns. Additionally, it is worth noting that only a relatively small proportion, approximately 10-20% of sperm incubated under capacitating conditions exhibit hyperactivated motility. In this work, we used a multifocal image acquisition system that can acquire, segment, and track sperm flagella in 3D+t. We developed a feature-based vector that describes the spatio-temporal flagellar sperm motility patterns by an envelope of ellipses. The classification results obtained using our 3D feature-based descriptors can serve as potential label for future work involving deep neural networks. By using the classification results as labels, it will be possible to train a deep neural network to automatically classify spermatozoa based on their 3D flagellar beating patterns. We demonstrated the effectiveness of the descriptors by applying them to a dataset of human sperm cells and showing that they can accurately differentiate between non-hyperactivated and hyperactivated 3D motility patterns of the sperm cells. This work contributes to the understanding of 3D flagellar hyperactive motility patterns and provides a framework for research in the fields of human and animal fertility.

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Dengue viruses are a significant global health concern, causing millions of infections annually and putting approximately half of the world's population at risk, as reported by the World Health Organization (WHO). Understanding the spatial and temporal patterns of dengue virus spread is crucial for effective prevention of future outbreaks. By investigating these patterns, targeted dengue surveillance and control measures can be improved, aiding in the management of outbreaks in dengue-affected regions. Curaçao, where dengue is endemic, has experienced frequent outbreaks over the past 25 years. To examine the spatial and temporal trends of dengue outbreaks in Curaçao, this study employs an interdisciplinary and multi-method approach. Data on >6500 cases of dengue infections in Curaçao between the years 1995 and 2016 were used. Temporal and spatial statistics were applied. The Moran's I index identified the presence of spatial autocorrelation for incident locations, allowing us to reject the null hypothesis of spatial randomness. The majority of cases were recorded in highly populated areas and a relationship was observed between population density and dengue cases. Temporal analysis demonstrated that cases mostly occurred from October to January, during the rainy season. Lower average temperatures, higher precipitation and a lower sea surface temperature appear to be related to an increase in dengue cases. This effect has a direct link to La Niña episodes, which is the cooling phase of El Niño Southern Oscillation. The spatial and temporal analyses conducted in this study are fundamental to understanding the timing and locations of outbreaks, and ultimately improving dengue outbreak management.

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Microplastics have accumulated in the environment since plastic production began, with present-day observations that range from marine trenches to mountains. However, research on microplastics has only recently begun so it is unclear how they have changed over time in many oceanic regions. Our study addressed this gap by quantifying the temporal and spatial dynamics of microplastics in two deep-water regions of the Gulf of Mexico (GOM). We isolated agglutinated foraminifera from sediment cores and assessed microplastics that were incorporated into their tests. Our results indicated that microplastics were incorporated by agglutinated foraminifera after plastic production began. Microplastics were higher at deep-water sites and closer to the Mississippi River. This study confirms the presence of microplastic incorporation into agglutinated foraminifera tests and investigates microplastics in deep-water sediments in the GOM. Additional work is needed to fully identify the distribution of microplastics across the GOM and other oceanic basins.

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The aim of this study was to assess space-time clustering of suicide in Argentina between 2017 and 2020. A spatio-temporal scan statistic using a space-time permutation model was employed to retrospectively detect clusters of total suicides by sex and by age group. From 2017 to 2020, six statistically significant spatio-temporal clusters were identified in Argentina with either more or less suicides than expected. Two clusters extended from May 2019 to July and September 2020, while the remaining four clusters were detected only during 2020. The start of the COVID-19 pandemic seems to have changed the spatio-temporal patterns of suicide in Argentina. Despite the national decrease in the number of suicides during 2020 compared to previous years, the spatio-temporal analysis revealed both areas with decreases and increases in suicide. This heterogeneous scenario highlights the need for the study of local effects behind the emergence of these spatio-temporal suicide clusters.

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ABSTRACT Objective: To analyze the spatio-temporal dynamics of COVID-19 in the Rio de Janeiro state within the nine health regions, between March 2020 and December 2022. Methods: The Poisson model with random effects was used to smooth and estimate the incidence of COVID-19 hospitalizations reported in the Influenza Epidemiological Surveillance Information System (SIVEP-Gripe) to verify the synchronicity of the epidemic in the state. Results: The COVID-19 epidemic in the state is characterized by the presence of seven peaks during the analyzed period corresponding to seven found. An asynchrony in hospitalizations was identified, varying according to the different virus variants in the nine health regions of the state. The incidence peaks of hospitalizations ranged from 1 to 12 cases per 100,000 inhabitants during the pandemic. Conclusion: This spatio-temporal analysis is applicable to other scenarios, enabling monitoring and decision-making for the control of epidemic diseases in different areas.

RESUMO Objetivo: Analisar a dinâmica espaço-temporal de COVID-19 no estado do Rio de Janeiro nas nove regiões de saúde, entre março de 2020 e dezembro de 2022. Métodos: Utilizou-se o modelo de Poisson com efeitos aleatórios para suavizar a curva de incidência de hospitalizações por COVID-19 notificadas no Sistema de Informação da Vigilância Epidemiológica da Gripe (Sivep-Gripe) para verificar a sincronicidade da epidemia no estado. Resultados: A epidemia de COVID-19 no estado é caracterizada pela presença de sete picos no período analisado correspondentes a sete variantes encontradas. Identificou-se uma assincronicidade nas hospitalizações, variando de acordo com as diferentes variantes do vírus nas nove regiões de saúde do estado. Os picos de incidência das hospitalizações variaram de 1 a 12 casos por 100 mil habitantes no decorrer da pandemia. Conclusão: Essa análise espaço-temporal é extensível em outros cenários, sendo possível o monitoramento e a tomada de decisões de controle de doenças epidêmicas em várias áreas.

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ABSTRACT BACKGROUND: The risk of death due to tuberculosis (TB) in Brazil is high and strongly related to living conditions (LC). However, epidemiological studies investigating changes in LC and their impact on TB are lacking. OBJECTIVES: To evaluate the impact of LC on TB mortality in Brazil. DESIGN AND SETTING: This ecological study, using panel data on spatial and temporal aggregates, was conducted in 1,614 municipalities between 2002 and 2015. METHODS: Data were collected from the Mortality Information System and the Brazilian Institute of Geography and Statistics. The proxy variable used for LC was the Urban Health Index (UHI). Negative binomial regression models were used to estimate the effect of the UHI on TB mortality rate. Attributable risk (AR) was used as an impact measure. RESULTS: From 2002 to 2015, TB mortality rate decreased by 23.5%, and LC improved. The continuous model analysis resulted in an RR = 0.89 (95%CI = 0.82-0.96), so the AR was −12.3%. The categorized model showed an effect of 0.92 (95%CI = 0.83-0.95) in municipalities with intermediate LC and of 0.83 (95%CI = 0.82-0.91) in those with low LC, representing an AR for TB mortality of −8.7% and −20.5%, respectively. CONCLUSIONS: Improved LC impacted TB mortality, even when adjusted for other determinants. This impact was greater in the strata of low-LC municipalities.

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Visceral leishmaniosis is a neglected tropical disease. We evaluated the spatial distribution of cases of visceral leishmaniosis in the state of Alagoas, Brazil. All cases of VL, registered by the health department, were analyzed and georeferenced. Results: Between 2008 and 2017, 97.1% of the municipalities presented sporadic classification of transmission. With temporal evolution, the incidence of cases of visceral leishmaniosis was concentrated in most municipalities in the microregion of Santana do Ipanema-AL. Space-time analysis, if considered, may promote the improvement of surveillance and control actions of visceral leishmaniosis.

A leishmaniose visceral é uma doença tropical negligenciada. Foram avaliadas a distribuição espacial dos casos de leishmaniose visceral no estado de Alagoas. Todos os casos de LV, registrados pela secretaria de saúde, foram analisados e georreferenciados. Entre 2008 e 2017, 97,1% dos municípios apresentaram classificação esporádica de transmissão. Com a evolução temporal, a incidência de casos de leishmaniose visceral se concentrou na maioria dos municípios da microrregião de Santana do Ipanema-AL. A análise espaço-tempo, se considerada, pode promover o aprimoramento das ações de vigilância e controle da leishmaniose visceral.

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Abstract Visceral leishmaniosis is a neglected tropical disease. We evaluated the spatial distribution of cases of visceral leishmaniosis in the state of Alagoas, Brazil. All cases of VL, registered by the health department, were analyzed and georeferenced. Results: Between 2008 and 2017, 97.1% of the municipalities presented sporadic classification of transmission. With temporal evolution, the incidence of cases of visceral leishmaniosis was concentrated in most municipalities in the microregion of Santana do Ipanema-AL. Space-time analysis, if considered, may promote the improvement of surveillance and control actions of visceral leishmaniosis.

Resumo A leishmaniose visceral é uma doença tropical negligenciada. Foram avaliadas a distribuição espacial dos casos de leishmaniose visceral no estado de Alagoas. Todos os casos de LV, registrados pela secretaria de saúde, foram analisados e georreferenciados. Entre 2008 e 2017, 97,1% dos municípios apresentaram classificação esporádica de transmissão. Com a evolução temporal, a incidência de casos de leishmaniose visceral se concentrou na maioria dos municípios da microrregião de Santana do Ipanema-AL. A análise espaço-tempo, se considerada, pode promover o aprimoramento das ações de vigilância e controle da leishmaniose visceral.