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Abstract Introduction: Leptodactylus latinasus and Physalaemus cuqui are sympatric anuran species with similar environmental requirements and contrasting reproductive modes. Climatic configuration determines distribution patterns and promotes sympatry of environmental niches, but specificity/selectivity determines the success of reproductive modes. Species distribution models (SDM) are a valuable tool to predict spatio-temporal distributions based on the extrapolation of environmental predictors. Objectives: To determine the spatio-temporal distribution of environmental niches and assess whether the protected areas of the World Database of Protected Areas (WDPA) allow the conservation of these species in the current scenario and future. Methods: We applied different algorithms to predict the distribution and spatio-temporal overlap of environmental niches of L. latinasus and P. cuqui within South America in the last glacial maximum (LGM), middle-Holocene, current and future scenarios. We assess the conservation status of both species with the WDPA conservation units. Results: All applied algorithms showed high performance for both species (TSS = 0.87, AUC = 0.95). The L. latinasus predictions showed wide environmental niches from LGM to the current scenario (49 % stable niches, 37 % gained niches, and 13 % lost niches), suggesting historical fidelity to stable climatic-environmental regions. In the current-future transition, L. latinasus would increase the number of stable (70 %) and lost (20 %) niches, suggesting fidelity to lowland regions and a possible trend toward microendemism. P. cuqui loses environmental niches from the LGM to the current scenario (25 %) and in the current-future transition (63 %), increasing the environmental sympathy between both species; 31 % spatial overlap in the current scenario and 70 % in the future. Conclusion: Extreme drought events and rainfall variations, derived from climate change, suggest the loss of environmental niches for these species that are not currently threatened but are not adequately protected by conservation units. The loss of environmental niches increases spatial sympatry which represents a new challenge for anurans and the conservation of their populations.

Resumen Introducción: Leptodactylus latinasus y Physalaemus cuqui son especies de anuros simpátricos con requerimientos ambientales similares y modos reproductivos contrastantes. La configuración climática determina los patrones de distribución y promueve la simpatría de los nichos ambientales, pero la especificidad/selectividad determina el éxito de los modos reproductivos. Los modelos de distribución de especies (MDE) son una herramienta valiosa para predecir distribuciones espacio-temporales basadas en la extrapolación de predictores ambientales. Objetivos: Determinar la distribución espacio-temporal de los nichos ambientales y evaluar si las áreas protegidas de la base de Datos Mundial de Áreas Protegidas (DMAP) permiten la conservación de estas especies en el escenario actual y futuro. Métodos: Aplicamos diferentes algoritmos para predecir la distribución y superposición espacio-temporal de nichos ambientales de L. latinasus y P. cuqui dentro de América del Sur en el último máximo glacial (UGM), Holoceno medio, actual y futuro. Evaluamos el estado de conservación de ambas especies con las unidades de conservación de la DMAP. Resultados: Todos los algoritmos aplicados mostraron un alto rendimiento para ambas especies (TSS = 0.87, AUC = 0.95). Las predicciones de L. latinasus mostraron amplios nichos ambientales desde LGM hasta el escenario actual (49 % de nichos estables, 37 % de nichos ganados y 13 % de nichos perdidos), sugiriendo fidelidad histórica por regiones climático-ambientales estables. En la transición actual-futura L. latinasus incrementaría la cantidad de nichos estables (70 %) y perdidos (20 %), sugiriendo fidelidad por regiones de tierras bajas y la posible tendencia hacia el microendemismo. P. cuqui pierde nichos ambientales desde el LGM al escenario actual (25 %) y en la transición actual-futura (63 %), incrementando la simpatría ambiental entre ambas especies; 31 % de superposición espacial en el escenario actual y 70 % en el futuro. Conclusión: Los eventos de sequía extrema y las variaciones de precipitaciones, derivados del cambio climático, sugieren la pérdida de nichos ambientales para estas especies, actualmente no se encuentran amenazadas, pero no están adecuadamente protegidas por las unidades de conservación. La pérdida de nichos ambientales aumenta la simpatría espacial que representa un nuevo desafío para estos anuros y la conservación de sus poblaciones.

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The golden mussel (Limnoperna fortunei) is an invasive bivalve that has established itself in several South American river systems, impacting ecosystem functioning. Reservoir cascades provide their larvae with the means of rapid dispersal, but the relationship between environmental variables and larval stage structure remains unclear. In this study, the density of three L. fortunei larval stages and quantitative detection using DNA are analyzed in a cascade of five reservoirs in the upper Uruguay River Basin and associated with spatiotemporal variation in environmental parameters. The analysis of L. fortunei eDNA presence and absence in freshwater systems appears to be a valuable mapping tool; however, no significant link was found between the eDNA magnitude and the overall larval density. The increase in larval density was related to the fluctuation of environmental parameters over a year, with the highest average larval densities observed in the CN and ITA reservoirs, though no significant difference was observed between the five reservoirs, where D-shaped larvae predominated. During winter, larval density decreased significantly, however, other variables also contribute to species activity and development in the upper Uruguay River Basin reservoirs and may be considered limiting factors. The relationships between environmental parameters were evaluated using a multivariate model. The interaction between reservoir area and precipitation, water temperature, electrical conductivity, and dissolved oxygen had a significant effect on larval density but showed specific influences on each larval stage. Any increase in density was regulated by dissolved oxygen and electrical conductivity content at all larval stages. Furthermore, total phosphorus affected the density of F1 and F3 larvae. The interaction between reservoir area and precipitation, nitrate content, phosphate concentrations, and water temperature had the most influence on the density of F2 and F3 larval stages; the F1 stage was mainly affected by calcium concentrations. The isolated effect of precipitation also contributed to the density of F2 and F3 larvae. Our findings shed light on the interaction between different phases of golden mussel larvae and the main nutrients found in reservoirs, which may be a determining factor in the rise in density of the non-native species in these systems.

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Dengue is a vector-borne disease that has increased over the past two decades, becoming a global public health emergency. The transmission of dengue is contingent upon various factors, among which climate variability plays a significant role. However, there remains substantial uncertainty regarding the underlying mechanisms. This study aims to investigate the spatial and temporal patterns of dengue risk and to quantify the associated risk factors in Valle del Cauca, Colombia, from 2001 to 2019. To achieve this, a spatio-temporal Bayesian hierarchical model was developed, integrating delayed and non-linear effects of climate variables, socio-economic factors, along with spatio-temporal random effects to account for unexplained variability. The results indicate that average temperature is positively associated with dengue risk 0-2 months later, showing a 35% increase in the risk. Similarly, high precipitation levels lead to increased risk approximately 2-3 months later, while relative humidity showed a constant risk within a 6 months-lag. These findings could be valuable for local health authorities interested in developing early warning systems to predict future risks in advance.

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This article aims to analyze spatial and temporal patterns of maternal mortality in Brazil during the period 2010-2020 and identify related socioeconomic indicators. We conducted an ecological study of the maternal mortality ratio (MMR) in Brazil's municipalities using secondary data. Temporal analysis was performed using the joinpoint method. Bayesian statistics, spatial autocorrelation, the Getis Ord Gi* technique and the scan statistic were used to identify spatial clusters, and multiple non-spatial and spatial regression models were used to assess the association between factors and the MMR. There was an increase in the MMR in 2020 and an increase in deaths in the North and Southeast. Clusters were found in Amazonas, Tocantins, Piauí, Maranhão, Bahia and Mato Grosso do Sul. The following indicators were negatively associated with the MMR: cesarean section rate, Municipal Human Development Index, and per capita household income of people who are vulnerable to poverty. The MMR was stable up to 2019, followed by a sharp rise in 2020 coinciding with the onset of the Covid-19 pandemic in the country. It is essential that efforts to reduce maternal mortality in Brazil extend beyond the promotion of improvements in antenatal, childbirth and postpartum care to address the social determinants of the problem.

O objetivo do artigo é analisar o padrão espacial e temporal e identificar indicadores socioeconômicos relacionados à razão de mortalidade materna (RMM) no Brasil de 2010 a 2020. Estudo ecológico que analisou a RMM nos municípios do Brasil, utilizando dados secundários. Para análise temporal, utilizou-se o método joinpoint. Para a identificação de aglomerados espaciais, utilizou-se estatística bayesiana, autocorrelação espacial, a técnica Getis Ord Gi* e a varredura scan. Para a identificação dos fatores associados à RMM, foram adotados modelos múltiplos de regressão não espacial e espacial. Observou-se aumento da RMM de 2019 para 2020. Houve crescimento de óbitos nas regiões Norte e Sudeste. Os clusters foram encontrados no Amazonas, Tocantins, Piauí, Maranhão, Bahia e Mato Grosso do Sul. Estão negativamente relacionados à RMM os seguintes indicadores: taxa de parto cesáreo, índice de desenvolvimento humano municipal e renda domiciliar per capita dos vulneráveis à pobreza. Embora a tendência temporal tenha se mostrado constante até 2019, a RMM apresentou crescimento no ano de início da pandemia de COVID-19 no país. A redução da MM no Brasil vai além da promoção de melhorias na assistência gravídico-puerperal, sendo fundamental focar também nos determinantes sociais do problema.

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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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Visceral leishmaniasis (VL) is an urgent public health concern in Brazil. We evaluated the spatiotemporal distribution of VL to better understand the effects of economic activities related to agriculture, livestock, and deforestation on its incidence in the Brazilian Legal Amazon (BLA). The data on newly confirmed cases of VL in Brazilian municipalities from 2007 to 2020 were extracted from the Brazilian Notifiable Diseases Information System (SINAN) and analyzed. The data on agricultural production (planted area in hectares) and livestock (total number of cattle) were obtained from the Brazilian Institute of Geography and Statistics (IBGE), whereas deforestation data (in hectares) were obtained from the Amazon Deforestation Estimation Project (PRODES). SatScan and the local indicators of spatial association (LISA) were used to identify the spatial and temporal patterns of VL and its relationships with economic and environmental variables. The cumulative incidence rate was found to be 4.5 cases per 100,000 inhabitants. Based on the LISA results, areas with a high incidence of VL and deforestation were identified in the states of Roraima, Pará, and Maranhão. Strengthening deforestation monitoring programs and environmental enforcement actions can help implement public policies to control illegal deforestation and mitigate the socio-environmental vulnerability in the BLA. Therefore, areas identified in this study should be prioritized for controlling VL.

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BACKGROUND: Seasonal fluctuations in weather are recognized as factors that affect both Aedes (Ae.) aegypti mosquitoes and the diseases they carry, such as dengue fever. The El Niño-Southern Oscillation (ENSO) is widely regarded as one of the most impactful atmospheric phenomena on Earth, characterized by the interplay of shifting ocean temperatures, trade wind intensity, and atmospheric pressure, resulting in extensive alterations in climate conditions. In this study, we investigate the influence of ENSO and local weather conditions on the spatio-temporal variability of Ae. aegypti infestation index. METHODS: We collected seasonal entomological survey data of immature forms of Ae. aegypti mosquitoes (Breteau index), as well as data on temperature, rainfall and the Oceanic Niño Index (ONI) for the period 2008-2018 over the 645 municipalities of the subtropical State of São Paulo (Brazil). We grounded our analytical approach on a Bayesian framework and we used a hierarchical spatio-temporal model to study the relationship between ENSO tracked by ONI, seasonal weather fluctuations and the larval index, while adjusting for population density and wealth inequalities. RESULTS: Our results showed a relevant positive effect for El Niño on the Ae. aegypti larval index. In particular, we found that the number of positive containers would be expected to increase by 1.30-unit (95% Credible Intervals (CI): 1.23 to 1.37) with El Niño events (i.e., ≥ 1°C, moderate to strong) respect to neutral (and weak) events. We also found that seasonal rainfall exceeding 153.12 mm appears to have a notable impact on vector index, leading potentially to the accumulation of ample water in outdoor discarded receptacles, supporting the aquatic phase of mosquito development. Additionally, seasonal temperature above 23.30°C was found positively associated to the larval index. Although the State of São Paulo as a whole has characteristics favourable to proliferation of the vector, there were specific areas with a greater tendency for mosquito infestation, since the most vulnerable areas are predominantly situated in the central and northern regions of the state, with hot spots of abundance in the south, especially during El Niño events. Our findings also indicate that social disparities present in the municipalities contributes to Ae. aegypti proliferation. CONCLUSIONS: Considering the anticipated rise in both the frequency and intensity of El Niño events in the forthcoming decades as a consequence of climate change, the urgency to enhance our ability to track and diminish arbovirus outbreaks is crucial.

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Suicide is one of the leading death causes worldwide, mainly among young adults, and Colombia has experienced an increase during the XXI century. The suicide impact has diverged between age groups and locations in Colombia, where young adults have taken higher incidences than the other age groups. The COVID-19 lockdown induced changes in mental health, affecting the previous suicide trends in the country. We conducted a spatiotemporal analysis of suicide attempts in Colombia per age group, adopting Bayesian models that represent 85,526 individual records in 1,121 municipalities from 2018 to 2020 using R-INLA. We found that Colombia exhibited an increase in suicide-attempt incidence from 2018 to 2019, and suddenly, the incidence fell in the first semester of 2020. The fixed effect of the models evidenced the highest risk in overall municipalities per trimester in the age group between 15-19 years old. The spatial random effect per model evidenced municipalities with the highest risk in the age groups between 10 to 59 years, mainly in the states in the Andean region of Colombia, and other states such as Putumayo, Vaupés, Arauca, Córdoba, Amazonas, and Meta. The temporal random effect evidenced a decay in suicide trends from the fourth trimester of 2019 to 2020, except in the age group > 59 years old. Geographically, our study pinpointed specific regions in Colombia, particularly in the central, southwest, and southeast areas, where the incidence of suicide attempts exceeded 100 cases per 100,000 inhabitants. The nuanced breakdown of incidence across different age groups further underscores the importance of tailoring preventive strategies based on age-specific and regional risk factors.

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BACKGROUND: Dengue is a vector-borne viral infection caused by the dengue virus transmitted to humans primarily by Aedes aegypti. The year 2024 has been a historic year for dengue in Brazil, with the highest number of probable cases ever registered. Herein, we analyze the temporal trend and spatio-temporal dynamics of dengue cases in Brazil during the first nine epidemiological weeks (EW) of 2024. METHODS: This is an ecological study, including all probable cases of dengue in Brazil during the period, carried out in two steps: time series analysis to assess the temporal trend and spatial analysis to identify high-risk clusters. RESULTS: 1,345,801 probable cases of dengue were reported. The regions with the highest increasing trend were the Northeast with an average epidemiologic week percent change (AEPC) of 52.4 (95% CI: 45.5-59.7; p < 0.001) and the South with 35.9 (95% CI: 27.7-44.5; p < 0.001). There was a statistically significant increasing trend in all states, except Acre (AEPC = -4.1; 95% CI: -16.3-10; p = 0.55), Amapá (AEPC = 1.3; 95% CI: -16.2-22.3; p = 0.9) and Espírito Santo (AEPC = 8.9; 95% CI: -15.7-40.6; p = 0.5). The retrospective space-time analysis showed a cluster within the Northeast, Central-West and Southeast regions, with a radius of 515.3 km, in which 1,267 municipalities and 525,324 of the cases were concentrated (RR = 6.3; p < 0.001). Regarding the spatial variation of the temporal trend, 21 risk areas were found, all of them located in Southeast or Central-West states. The area with the highest relative risk was Minas Gerais state, where 5,748 cases were concentrated (RR = 8.1; p < 0.001). Finally, a purely spatial analysis revealed 25 clusters, the one with the highest relative risk being composed of two municipalities in Acre (RR = 6.9; p < 0.001). CONCLUSIONS: We described a detailed temporal-spatial analysis of dengue cases in the first EWs of 2024 in Brazil, which were mainly concentrated in the Southeast and Central-West regions. Overall, it is recommended that governments adopt public policies to control the the vector population in high-risk areas, as well as to prevent the spread of dengue fever to other areas of Brazil.

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Since Brazil has the largest territory in South America and borders 10 other countries, rabies control is strategic to prevent cross-border spread. However, prevention and control of rabies in small ruminants is neglected. The present study evaluated the spatiotemporal distribution and temporal trends of rabies in small ruminants in Brazil between 2005 and 2023. Official data on rabies case notifications and the population density of goats and sheep from the Brazilian states were used. Descriptive epidemiology and temporal analyses of high-risk clusters and trends were conducted. Rabies cases were reported in all states, except for the Federal District, Roraima, Amapá, Amazonas, and Rondônia. In sheep, 174 cases were reported, with an emphasis on Paraná (25.29 %), being highest. There were 64 cases in goats, with a highlight on Bahia (37.50 %) and Maranhão (18.75 %). However, Espírito Santo presented the highest incidence risk (IR) for goats and sheep. The highest peaks in IR occurred in 2005, 2006 and 2013. A temporal trend of decreasing goat cases was observed in northeastern Brazil from 2005 to 2023. In sheep, the Northeast region showed a downward trend in rabies cases. Three high-risk clusters were identified: the primary cluster for goats occurred in 2006, and for sheep, between 2005 and 2013. Rabies in small ruminants occurs across all Brazilian regions, with high-risk areas in the Northeast, Southeast, and South, as well as a risk of cross-border transmission. These findings support animal health authorities in strengthening rabies control for small ruminants and reducing the risk of transboundary spread.

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We assessed the spatiotemporal dynamics of Oropouche fever in Brazil during 2015-2024. We found the number of cases substantially increased during that period, particularly in the Amazon region. Our findings underscore the need for improved surveillance and public health measures in response to the disease's potential spread beyond endemic areas.

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Bioseston is a heterogeneous assemblage of bacterioplankton, phytoplankton, zooplankton, and planktonic debris. A detailed knowledge of biosestons is essential for understanding the dynamics of trophic flows in marine ecosystems. The distributional features of seston biomass in plankton (micro- and mesoplankton) in the Southwest Atlantic Ocean (Rio de Janeiro State, Brazil) were analyzed using stratified samples gathered to a depth of 2,400 m during night time. The horizontal pattern of biomass distribution was analyzed vis-a-vis station depth during both wet and dry periods, with higher values recorded in the continental shelf than in the slope, confirming the terrestrial contribution of nutrient sources to the marine environment. This horizontal variation reinforces the occurrence of seasonal vortices in Cabo Frio and Cabo de São Tomé on the central coast of Brazil. Environmental variables reflect the hydrological signatures of the water masses along the Brazilian coast. The largest seston biomass was related to high temperatures, salinities, and low inorganic nutrient concentrations in tropical and South Atlantic central waters. The observed distribution patterns suggest that seston biomass in plankton in the region may be structured based on partitioned horizontal and vertical habitats and food resources.

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Dengue prevalence results from the interaction of multiple socio-environmental variables which influence its spread. This study investigates the impact of forest loss, precipitation, and temperature on dengue incidence in Mexico from 2010 to 2020 using a Bayesian hierarchical spatial model. Three temporal structures-AR1, RW1, and RW2-were compared, with RW2 showing superior performance. Findings indicate that a 1 % loss of municipal forest cover correlates with a 16.9 % increase in dengue risk. Temperature also significantly affects the vectors' ability to initiate and maintain outbreaks, highlighting the significant role of environmental factors. The research emphasizes the importance of multilevel modeling, finer temporal data resolution, and understanding deforestation causes to enhance the predictability and effectiveness of public health interventions. As dengue continues affecting global populations, particularly in tropical and subtropical regions, this study contributes insights, advocating for an integrated approach to health and environmental policy to mitigate the impact of vector-borne diseases.

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This study examines the spread of COVID-19 in São Paulo, Brazil, using a combination of cellular automata and geographic information systems to model the epidemic's spatial dynamics. By integrating epidemiological models with georeferenced data and social indicators, we analyse how the virus propagates in a complex urban setting, characterized by significant social and economic disparities. The research highlights the role of various factors, including mobility patterns, neighbourhood configurations, and local inequalities, in the spatial spreading of COVID-19 throughout São Paulo. We simulate disease transmission across the city's 96 districts, offering insights into the impact of network topology and district-specific variables on the spread of infections. The study seeks to fine-tune the model to extract epidemiological parameters for further use in a statistical analysis of social variables. Our findings underline the critical importance of spatial analysis in public health strategies and emphasize the necessity for targeted interventions in vulnerable communities. Additionally, the study explores the potential of mathematical modelling in understanding and mitigating the effects of pandemics in urban environments.

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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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BACKGROUND: People with Parkinson's Disease (PwPD) have motor symptoms that directly interfere on dry land walking performance. Despite the shallow water walking is a viable and beneficial physical intervention for PwPD, it lacks information on the comparison of the biomechanical responses of the shallow water walking by PwPD and age paired healthy individuals. RESEARCH QUESTION: Are there differences in the spatiotemporal and angular responses of shallow water walking by older adults with and without Parkinson's disease? METHODS: In this cross-sectional study, ten older adults (9 men/1 women) with Parkinson disease (PwPD group) and ten older adults (3 men/7 women) without Parkinson's disease (Older group) walked in shallow water at self-selected comfortable speed on pool floor in the immersion depths of waist and xiphoid levels. The 2D kinematic data from the sagittal plane was collected to calculate the walking speed, stride length, stride frequency, duty factor, walk ratio, lower limb joints' range of motion and peak angular speed RESULTS: Both groups reduced similarly the walking speed with the immersion depth increase. The speed decrease was achieved by a reducing both the stride frequency and stride length only in the PwPD. The PwPD had lower contact phase than Older in the waist depth, probably due to the reduced risk of fall in water immersion and to attenuate drag force effects. The total range of joint motion was similar between groups, while the peak angular speed of ankle and knee reduced in the deeper depth in both groups. SIGNIFICANCE: The present findings can help professionals of aquatic rehabilitation to choose the best depth for exercise programs, according to the treatment objectives. To our knowledge, this was the first study that analyzed spatiotemporal and angular variables during shallow water walking of PwPD at different depths and compared them with older people without Parkinson's disease.

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Epidemiological studies to better understand wheat blast (WB) spatial and temporal patterns were conducted in three field environments in Bolivia between 2019 and 2020. The temporal dynamics of wheat leaf blast (WLB) and spike blast (WSB) were best described by the logistic model compared with the Gompertz and exponential models. The nonlinear logistic infection rates were higher under defined inoculation in experiments two and three than under undefined inoculation in experiment one, and they were also higher for WSB than for WLB. The onset of WLB began with a spatial clustering pattern according to autocorrelation analysis and Moran's index values, with higher severity and earlier onset for defined than for undefined inoculation until the last sampling time. The WSB onset did not start with a spatial clustering pattern; instead, it was detected later until the last sampling date across experiments, with higher severity and earlier onset for defined than for undefined inoculation. Maximum severity (Kmax) was 1.0 for WSB and less than 1.0 for WLB. Aggregation of WLB and WSB was higher for defined than for undefined inoculation. The directionality of hotspot development was similar for both WLB and WSB, mainly occurring concentrically for defined inoculation. Our results show no evidence of synchronized development but suggest a temporal and spatial progression of disease symptoms on wheat leaves and spikes. Thus, we recommend that monitoring and management of WB should be considered during early growth stages of wheat planted in areas of high risk.

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OBJECTIVES: To analyze the rate of gestational syphilis (GS) based on temporal trends over 11 years, as well as the spatial distribution of GS in Brazil, based on the identification of spatial clusters. METHODOLOGY: An ecological, using Brazil and its regions as an analysis unit, based on gestational syphilis data reported in the Notifiable Diseases Information System (SINAN), from 2011 to 2020. Thematic maps were built for spatial data analysis, and the Prais-Winsten autoregressive model was used to verify the trend. Spatial analysis identified the distribution of clusters (high-high; low-low; high-low and low-high) of distribution of GS across Brazilian municipalities, using a 5% significance level. RESULTS: Gestational syphilis experienced a considerable increase in cases during the studied period, with a peak of 37,436 cases in 2018. The spatial distribution of the disease is heterogeneous in the country. A growing trend was observed in all states of Brazil, except for Espírito Santo, where it remained stationary, with a monthly variation of 10.32%. CONCLUSION: The spatial and temporal trend analysis point to syphilis as an important public health problem. The numbers are alarming and show the urgent need for measures to prevent and control syphilis during pregnancy.

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OBJECTIVE: To identify the epidemiological, spatial, and temporal pattern of TB-HIV coinfection in Brazil during the period from 2001 to 2020. METHODS: Ecological study using space-time analysis techniques. It included cases of TB-HIV coinfection registered in Brazil from 2001 to 2020. The temporal trend analysis was performed using segmented regression by Joinpoint regression. For spatial analysis, Moran indices were calculated and choropleth maps were produced using TerraView and QGIS software. RESULTS: A stable temporal trend was observed in the incidence rates of TB-HIV coinfection in Brazil during the analyzed period. In addition, high-risk areas for coinfection located in states in the North, Southeast, South, and Midwest regions were identified. CONCLUSION: There was stability in the incidence of TB-HIV coinfection in Brazil over the last 20 years and heterogeneous geographic distribution of risk areas for the condition.

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OBJECTIVE: To assess the evolution of the COVID-19 pandemic in Brazil and its macro-regions, considering disease incidence and mortality rates, as well as identifying territories with still rising disease indices and evaluating vaccine coverage and population adherence to COVID-19 immunization. METHODS: An ecological study conducted in Brazil with COVID-19 cases and deaths reported between February 2020 and April 2024, obtained through the Coronavirus Panel. Historical series were constructed from incidence and mortality rates to assess the pandemic's evolution, and temporal trends were estimated using the Seasonal Trend Decomposition using Loess (STL) method. The Spatial Variation in Temporal Trends (SVTT) technique was employed to identify clusters with significant variations in temporal trends. Vaccination was analyzed considering the percentage of vaccinated and unvaccinated population in each municipality of the country. RESULTS: Brazil recorded a total of 38,795,966 cases and 712,038 deaths from COVID-19 during the study period. Incidence and mortality rates showed three waves of the disease, with a fourth wave of smaller amplitude. Four clusters with significant case growth and two with increased deaths were identified. Vaccine coverage varied among municipalities, with some regions showing low vaccination rates and others with high immunization adherence. CONCLUSION: The study provided a comprehensive overview of coronavirus behavior in Brazil, and its results highlight the ongoing importance of vaccination and the need to direct efforts and resources to areas of higher risk.

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