pHusion - a robust and versatile toolset for automated detection and analysis of exocytosis.

Exocytosis is a fundamental process used by eukaryotes to regulate the composition of the plasma membrane and facilitate cell-cell communication. To investigate exocytosis in neuronal morphogenesis, previously we developed computational tools with a graphical user interface to enable the automatic detection and analysis of exocytic events from fluorescence timelapse images. Although these tools were useful, we found the code was brittle and not easily adapted to different experimental conditions. Here, we developed and validated a robust and versatile toolkit, named pHusion, for the analysis of exocytosis, written in ImageTank, a graphical programming language that combines image visualization and numerical methods. We tested pHusion using a variety of imaging modalities and pH-sensitive fluorophores, diverse cell types and various exocytic markers, to generate a flexible and intuitive package. Using this system, we show that VAMP3-mediated exocytosis occurs 30-times more frequently in melanoma cells compared with primary oligodendrocytes, that VAMP2-mediated fusion events in mature rat hippocampal neurons are longer lasting than those in immature murine cortical neurons, and that exocytic events are clustered in space yet random in time in developing cortical neurons.

Community-science reveals delayed fall migration of waterfowl and spatiotemporal effects of a changing climate.

Climate change has well-documented, yet variable, influences on the annual movements of migratory birds. The effects of climate change on fall migration remains understudied compared with spring but appears to be less consistent among species, regions and years. Changes in the pattern and timing of waterfowl migration in particular may result in cascading effects on ecosystem function, and socio-economic and cultural outcomes. We investigated changes in the migration of 15 waterfowl species along a major flyway corridor of continental importance in northeastern North America using 43 years of community-science data. We built spatially- and temporally explicit hierarchical generative additive models for each species and demonstrated that climate, specifically the interaction between minimum temperature and precipitation, significantly influences migration phenology for most species. Certain species' migratory movements responded to specific temperature thresholds (climate migrants) and others reacted more to the interaction of temperature and precipitation (extreme event migrants). There are already significant changes in the fall migration phenology of common waterfowl species with high ecological and economic importance, which may simply increase in the context of a changing climate. If not addressed, climate change could induce mismatches in management, regulations and population surveys which would negatively impact the hunting industry. Our findings highlight the importance of considering species-specific spatiotemporal scales of effect on climate on migration and our methods can be widely adapted to quantify and forecast climate-driven changes in wildlife migration.

Les changements climatiques ont des influences bien documentées, mais variables, sur les mouvements annuels des oiseaux migrateurs. Les effets des changements climatiques sur les migrations automnales demeurent peu étudiés par rapport aux migrations printanières, mais il semble qu'ils soient moins constants d'une espèce, d'une région et d'une année à l'autre. Les changements dans le patron et le calendrier de la migration de la sauvagine en particulier peuvent avoir des effets en chaîne sur la fonction des écosystèmes et des impacts socio­économiques et culturels. Nous avons étudié les changements dans la migration de 15 espèces de sauvagine le long d'un corridor de migration d'importance continentale dans le nord­est de l'Amérique du Nord, en utilisant 43 ans de données scientifiques communautaires. Nous avons construit des modèles additifs généralisés hiérarchiques spatialement et temporellement explicites pour chaque espèce et avons démontré que le climat, en particulier l'interaction entre la température minimale et les précipitations, influence de manière significative la phénologie de la migration pour la plupart des espèces. Les mouvements migratoires de certaines espèces répondent à des seuils de température spécifiques (migrateurs climatiques) et d'autres réagissent davantage à l'interaction entre la température et les précipitations (migrateurs d'événements extrêmes). La phénologie des migrations automnales d'espèces de sauvagine commune qui ont une grande importance écologique et économique connaît déjà des changements importants, qui pourraient simplement s'accentuer dans le cadre des changements climatiques. S'ils ne sont pas pris en compte, les changements climatiques pourraient induire des décalages dans la gestion, les réglementations et les enquêtes de population, ce qui aurait un impact négatif sur l'industrie de la chasse. Nos résultats soulignent l'importance de prendre en compte les échelles spatio­temporelles spécifiques sur la migration et nos méthodes peuvent être largement adaptées pour quantifier et prévoir les changements induits par le climat dans la migration de la faune.

Hospitalizations for Cardiovascular Diseases Sensitive to Primary Health Care in Paraná State, Brazil: A Bayesian Spatiotemporal Model.

PURPOSE: To analyze spatiotemporal trends in hospitalizations for cardiovascular diseases (CVD) sensitive to primary health care (PHC) among individuals aged 50-69 years in Paraná State, Brazil, from 2014 to 2019 and investigate correlations between PHC services and the Social Development Index. METHODS: We conducted a cross-sectional ecological study using publicly available secondary data to analyze the municipal incidence of hospitalizations for CVD sensitive to PHC and to estimate the risk of hospitalization for this group of diseases and associated factors using hierarchical Bayesian spatiotemporal modeling with Markov chain Monte Carlo simulation. RESULTS: There was a 5% decrease in the average rate of hospitalizations for PHC-sensitive CVD from 2014 to 2019. Regarding standardized hospitalization rate (SHR) according to population size, we found that no large municipality had an SHR >2. Likewise, a minority of these municipalities had SHR values of 1-2 (33%). However, many small and medium-sized municipalities had SHR values >2 (47% and 48%, respectively). A greater Social Development Index value served as a protective factor against hospitalizations, with a relative risk of 0.957 (95% credible interval, 0.929-0.984). CONCLUSIONS: The annual risk of hospitalization decreased over time; however, small municipalities had the greatest rates of hospitalization, indicating an increase in health inequity. The inverse association between social development and hospitalizations for CVD sensitive to PHC raises questions about intersectionality in health care.

Geographical disparities in access to surgical treatment and mortality rates from abdominal aortic aneurysms in Brazil: A retrospective longitudinal study.

INTRODUCTION: Abdominal aortic aneurysm (AAA) is a growing public health problem, and not all patients have access to surgery when needed. This study aimed to analyze spatiotemporal variations in AAA mortality and surgical procedures in Brazilian intermediate geographic regions and explore the impact of different surgical techniques on operative mortality. METHODS: A retrospective longitudinal study was conducted to evaluate AAA mortality from 2008 to 2020 using space-time cube (STC) analysis and the emerging hot spot analysis tool through the Getis-Ord Gi* method. RESULTS: There were 34,255 deaths due to AAA, 13,075 surgeries to repair AAA, and a surgical mortality of 14.92%. STC analysis revealed an increase in AAA mortality rates (trend statistic = +1.7693, p = 0.0769) and a significant reduction in AAA surgery rates (trend statistic = -3.8436, p = 0.0001). Analysis of emerging hotspots revealed high AAA mortality rates in the South, Southeast, and Central-West, with a reduction in procedures in São Paulo and Minas Gerais States (Southeast). In the Northeast, there were extensive areas of increasing mortality rates and decreasing procedure rates (cold spots). CONCLUSION: AAA mortality increased in several regions of the country while surgery rates decreased, demonstrating the need for implementing public health policies to increase the availability of surgical procedures, particularly in less developed regions with limited access to services.

Impact of Flooding and Drought Risks on the Cost of Bond Financing for Water Utilities.

The global water cycle has experienced significant changes due to the interplay of climate shifts and human activities, resulting in more frequent and severe droughts and floods. These shifts have started to impact the operational efficiency of water treatment and delivery systems. This, in turn, has implications for the economic performance of these assets and the climate-impacted cost of their financing through the issuing of municipal bonds. Analyzing a decade of water bond data (2009-2019), this study offers empirical evidence for the impact of flood and drought risks on bond investor demand to offset water risks. The results reveal that bond markets factored in coastal flood risks between 2013 and 2019, adjusting by 3-6 basis points (bps) per risk score unit, and riverine flood risks from 2009 to 2013, with a 5-11 basis points increase per risk score unit. These effects were primarily driven by bonds issued in the Pacific Coast and Great Plains regions, respectively. In contrast, the pricing of drought risks in the bond market followed a more nuanced pattern. Additionally, we show the channeling effects of water consumption and investor perceptions of climate change on water risk pricing in the bond market. These findings have significant implications for water risk management in the public sector as regions with heightened water risk exposure are perceived as riskier by market participants, leading to a higher cost of capital for municipalities and water agencies.

Exposure of Peregrine Falcons to Halogenated Flame Retardants: A 30 Year Retrospective Biomonitoring Study across North America.

Compared to aquatic ecosystem, terrestrial systems have been subjected to fewer investigations on the exposure to halogenated flame retardants (HFRs). Our study utilized peregrine falcon eggs collected from multiple habitats across North America to retrospectively explore both spatial distribution and temporal changes in legacy (e.g., polybrominated diphenyl ethers) and alternative HFRs over a 30 year period (1984-2016). The results reveal intensive HFR exposure in terrestrial ecosystems and chemical-specific spatiotemporal distribution patterns. The correlations between egg levels of the selected HFRs and human population density clearly illustrated a significant urban influence on the exposure of this wildlife species to these HFRs and subsequent maternal transfer to their eggs. Temporal analyses suggest that, unlike aquatic systems, terrestrial ecosystems may undergo continual exposure to consistently high levels of legacy HFRs for a long period of time. Our findings collectively highlight the effectiveness of using peregrine eggs to monitor terrestrial exposure to HFRs and other bioaccumulative chemicals and the need for continuous monitoring of HFRs in terrestrial ecosystems.

Towards more realistic measures of accessibility to emergency departments in Sweden.

BACKGROUND: Assuring that emergency health care (EHC) is accessible is a key objective for health care planners. Conventional accessibility analysis commonly relies on resident population data. However, the allocation of resources based on stationary population data may lead to erroneous assumptions of population accessibility to EHC. METHOD: Therefore, in this paper, we calculate population accessibility to emergency departments in Sweden with a geographical information system based network analysis. Utilizing static population data and dynamic population data, we investigate spatiotemporal patterns of how static population data over- or underestimates population sizes derived from temporally dynamic population data. RESULTS: Our findings show that conventional measures of population accessibility tend to underestimate population sizes particularly in rural areas and in smaller ED's catchment areas compared to urban, larger ED's-especially during vacation time in the summer. CONCLUSIONS: Planning based on static population data may thus lead to inequitable distributions of resources. This study is motivated in light of the ongoing centralization of ED's in Sweden, which largely depends on population sizes in ED's catchment areas.

How do taxi drivers expose to fine particulate matter (PM2.5) in a Chinese megacity: a rapid assessment incorporating with satellite-derived information and urban mobility data.

BACKGROUND: Taxi drivers in a Chinese megacity are frequently exposed to traffic-related particulate matter (PM2.5) due to their job nature, busy road traffic, and urban density. A robust method to quantify dynamic population exposure to PM2.5 among taxi drivers is important for occupational risk prevention, however, it is limited by data availability. METHODS: This study proposed a rapid assessment of dynamic exposure to PM2.5 among drivers based on satellite-derived information, air quality data from monitoring stations, and GPS-based taxi trajectory data. An empirical study was conducted in Wuhan, China, to examine spatial and temporal variability of dynamic exposure and compare whether drivers' exposure exceeded the World Health Organization (WHO) and China air quality guideline thresholds. Kernel density estimation was conducted to further explore the relationship between dynamic exposure and taxi drivers' activities. RESULTS: The taxi drivers' weekday and weekend 24-h PM2.5 exposure was 83.60 µg/m3 and 55.62 µg/m3 respectively, 3.4 and 2.2 times than the WHO's recommended level of 25 µg/m3. Specifically, drivers with high PM2.5 exposure had a higher average trip distance and smaller activity areas. Although major transportation interchanges/terminals were the common activity hotspots for both taxi drivers with high and low exposure, activity hotspots of drivers with high exposure were mainly located in busy riverside commercial areas within historic and central districts bounded by the "Inner Ring Road", while hotspots of drivers with low exposure were new commercial areas in the extended urbanized area bounded by the "Third Ring Road". CONCLUSION: These findings emphasized the need for air quality management and community planning to mitigate the potential health risks of taxi drivers.

Spatiotemporal Changes in the Slavery-Inequality Relationship: The Diffusion of the Legacy of Slavery.

Despite the persistence of relationships between historical racist violence and contemporary Black-White inequality, research indicates, in broad strokes, that the slavery-inequality relationship in the United States has changed over time. Identifying the timing of such change across states can offer insights into the underlying processes that generate Black-White inequality. In this study, we use integrated nested Laplace approximation models to simultaneously account for spatial and temporal features of panel data for Southern counties during the period spanning 1900 to 2018, in combination with data on the concentration of enslaved people from the 1860 census. Results provide the first evidence on the timing of changes in the slavery-economic inequality relationship and how changes differ across states. We find a region-wide decline in the magnitude of the slavery-inequality relationship by 1930, with declines traversing the South in a northeasterly-to-southwesterly pattern over the study period. Different paces in declines in the relationship across states suggest the expansion of institutionalized racism first in places with the longest-standing overt systems of slavery. Results provide guidance for further identifying intervening mechanisms-most centrally, the maturity of racial hierarchies and the associated diffusion of racial oppression across institutions, and how they affect the legacy of slavery in the United States.

Assessing spatiotemporal change in coral reef social-ecological systems.

Coral reef resilience is eroding at multiple spatial scales globally, with broad implications for coastal communities, and is thus a critical challenge for managing marine social-ecological systems (SESs). Many researchers believe that external stressors will cause key coral reefs to die by the end of the 21st century, virtually eliminating essential ecological and societal benefits. Here, we propose the use of resilience-based approaches to understand the dynamics of coral reef SESs and subsequent drivers of coral reef decline. Previous research has demonstrated the effectiveness of these methods, not only for tracking environmental change, but also for providing warning in advance of transitions, possibly allowing time for management interventions. The flexibility and utility of these methods make them ideal for assessing complex systems; however, they have not been used to study aquatic ecosystem dynamics at the global scale. Here, we evaluate these methods for examining spatiotemporal change in coral reef SESs across the global seascape and assess the subsequent impacts on coral reef resilience. We found that while univariate indicators failed to provide clear signals, multivariate resilience-based approaches effectively captured coral reef SES dynamics, unveiling distinctive patterns of variation throughout the global coral reef seascape. Additionally, our findings highlight global spatiotemporal variation, indicating patterns of degraded resilience. This degradation was reflected regionally, particularly in the Pacific Ocean and Indian Ocean SESs. These results underscore the utility of resilience-based approaches in assessing environmental change in SESs, detecting spatiotemporal variation at the global and regional scales, and facilitating more effective monitoring and management of coral reef SESs.

Quantifying COVID-19 importation risk in a dynamic network of domestic cities and international countries.

Since its outbreak in December 2019, the novel coronavirus 2019 (COVID-19) has spread to 191 countries and caused millions of deaths. Many countries have experienced multiple epidemic waves and faced containment pressures from both domestic and international transmission. In this study, we conduct a multiscale geographic analysis of the spread of COVID-19 in a policy-influenced dynamic network to quantify COVID-19 importation risk under different policy scenarios using evidence from China. Our spatial dynamic panel data (SDPD) model explicitly distinguishes the effects of travel flows from the effects of transmissibility within cities, across cities, and across national borders. We find that within-city transmission was the dominant transmission mechanism in China at the beginning of the outbreak and that all domestic transmission mechanisms were muted or significantly weakened before importation posed a threat. We identify effective containment policies by matching the change points of domestic and importation transmissibility parameters to the timing of various interventions. Our simulations suggest that importation risk is limited when domestic transmission is under control, but that cumulative cases would have been almost 13 times higher if domestic transmissibility had resurged to its precontainment level after importation and 32 times higher if domestic transmissibility had remained at its precontainment level since the outbreak. Our findings provide practical insights into infectious disease containment and call for collaborative and coordinated global suppression efforts.

Spatiotemporal Analysis of Out-of-Hospital Cardiac Arrest Incidence and Survival Outcomes in Korea (2009-2021).

BACKGROUND: Out-of-hospital cardiac arrest is a major public health concern in Korea. Identifying spatiotemporal patterns of out-of-hospital cardiac arrest incidence and survival outcomes is crucial for effective resource allocation and targeted interventions. Thus, this study aimed to investigate the spatiotemporal epidemiology of out-of-hospital cardiac arrest in Korea, with a focus on identifying high-risk areas and populations and examining factors associated with prehospital outcomes. METHODS: We conducted this population-based observational study using data from the Korean out-of-hospital cardiac arrest registry from January 2009 to December 2021. Using a Bayesian spatiotemporal model based on the Integrated Nested Laplace Approximation, we calculated the standardized incidence ratio and assessed the relative risk to compare the spatial and temporal distributions over time. The primary outcome was out-of-hospital cardiac arrest incidence, and the secondary outcomes included prehospital return of spontaneous circulation, survival to hospital admission and discharge, and good neurological outcomes. RESULTS: Although the number of cases increased over time, the spatiotemporal analysis exhibited a discernible temporal pattern in the standardized incidence ratio of out-of-hospital cardiac arrest with a gradual decline over time (1.07; 95% credible interval [CrI], 1.04-1.09 in 2009 vs. 1.00; 95% CrI, 0.98-1.03 in 2021). The district-specific risk ratios of survival outcomes were more favorable in the metropolitan and major metropolitan areas. In particular, the neurological outcomes were significantly improved from relative risk 0.35 (0.31-0.39) in 2009 to 1.75 (1.65-1.86) in 2021. CONCLUSION: This study emphasized the significance of small-area analyses in identifying high-risk regions and populations using spatiotemporal analyses. These findings have implications for public health planning efforts to alleviate the burden of out-of-hospital cardiac arrest in Korea.

Spatiotemporal Patterns of Iris Yellow Spot Virus and Its Onion Thrips Vector, Thrips tabaci, in Transplanted and Seeded Onion Fields in New York.

Onion thrips, Thrips tabaci (Lindeman), transmits iris yellow spot virus (IYSV) and is one of the most important pests of Allium crops. IYSV is a member of the species Tospovirus iridimaculaflavi in the genus Orthotospovirus of the family Tospoviridae. This virus typically reduces overall onion bulb quality and weight but can also prematurely kill onion plants. IYSV is neither seed nor mechanically transmitted. Onion fields are typically established via seeds and transplants. A decade ago, onion thrips tended to colonize transplanted fields before seeded fields because plants in transplanted fields were larger and more attractive to thrips than smaller onions in seeded fields. Therefore, we hypothesized that the incidence of IYSV in transplanted fields would be detected early in the season and be spatially aggregated, whereas IYSV would be absent from seeded fields early in the season and initial epidemic patterns would be spatially random. In 2021 and 2022, IYSV incidence and onion thrips populations were quantified in 12 onion fields (four transplanted fields and eight seeded fields) in New York. Fields were scouted four times throughout the growing season (n = 96 samples), and a geospatial and temporal analysis of aggregation and incidence was conducted to determine spatiotemporal patterns in each field type. Results indicated that spatial patterns of IYSV incidence and onion thrips populations were similar early in the season, indicating that transplanted onion fields are no longer the dominant early-season source of IYSV in New York. These findings suggest the need to identify other important early-season sources of IYSV that impact New York onion fields.

Evaluation of the sensitivity of meteorological drought in the Mediterranean region to different data record lengths.

The division and evaluation of data series used in monitoring drought into different time intervals is a practical approach to detecting the spatial and temporal extent of drought spread. This study aimed to determine meteorological drought's spatial and temporal distribution using overlapping and consecutive periods and cycles of the standardized precipitation index (SPI) time series in the Mediterranean region, Turkey. In the scope of the research, SPI values for the SPI12, SPI6 (1), and SPI6 (2) seasons were calculated for consecutive and overlapping hydrological years (1978-1998/21 years, 1978-2008/31 years, and 1978-2018/41 years) at 28 meteorological stations. Autocorrelation, Mann-Kendall, and Sen slope trend tests were applied at a 5% significance level for each season (SPI12, SPI6 (1), and SPI6 (2)) and different time scales (21, 31, and 41 years). For each season and period, maps of the SPI drought class, average formation of drought class, Mann-Kendall (MK) trend, and Sen's slope (SS) trend test statistics for the Mediterranean region were obtained, and the spatial distribution rate of trends was determined by drawing hypsometric curves. Changes in drought occurrence at different time scales were thoroughly evaluated with the changing length of data recording. Consequently, it was determined that the mild wet (MIW) and mild drought (MID) classes dominate the study area in the Mediterranean region. Significant and nonstationary changes detected in extreme wet and drought occurrences (extreme wet, EW; severe wet, SW; extreme drought, ED; severe drought, SD) were found to pose a risk in the study area. It was observed that there were spatially and temporally insignificant decreasing drought trends in the Mediterranean basin, considering that the time scales of these trends slowed down. Despite a nonsignificant trend from the MID drought class to the MIW drought class, it is predicted that the MIW and MID classes will maintain their dominance in the Mediterranean region. The central part of the study area (central Mediterranean basin) is the region with the highest drought risk.

Time-Varying GPS Displacement Network Modeling by Sequential Monte Carlo.

Geodetic observations through high-rate GPS time-series data allow the precise modeling of slow ground deformation at the millimeter level. However, significant attention has been devoted to utilizing these data for various earth science applications, including to determine crustal velocity fields and to detect significant displacement from earthquakes. The relationships inherent in these GPS displacement observations have not been fully explored. This study employs the sequential Monte Carlo method, specifically particle filtering (PF), to develop a time-varying analysis of the relationships among GPS displacement time-series within a network, with the aim of uncovering network dynamics. Additionally, we introduce a proposed graph representation to enhance the understanding of these relationships. Using the 1-Hz GEONET GNSS network data of the Tohoku-Oki Mw9.0 2011 as a demonstration, the results demonstrate successful parameter tracking that clarifies the observations' underlying dynamics. These findings have potential applications in detecting anomalous displacements in the future.

Associations of Anaplasma phagocytophilum Bacteria Variants in Ixodes scapularis Ticks and Humans, New York, USA.

Anaplasmosis, caused by the tickborne bacterium Anaplasma phagocytophilum, is an emerging public health threat in the United States. In the northeastern United States, the blacklegged tick (Ixodes scapularis) transmits the human pathogenic genetic variant of A. phagocytophilum (Ap-ha) and a nonpathogenic variant (Ap-V1). New York has recently experienced a rapid and geographically focused increase in cases of anaplasmosis. We analyzed A. phagocytophilum-infected I. scapularis ticks collected across New York during 2008-2020 to differentiate between variants and calculate an entomological risk index (ERI) for each. Ap-ha ERI varied between regions and increased in all regions during the final years of the study. Space-time scan analyses detected expanding clusters of Ap-ha located within documented anaplasmosis hotspots. Ap-ha ERI was more positively correlated with anaplasmosis incidence than non-genotyped A. phagocytophilum ERI. Our findings help elucidate the relationship between the spatial ecology of A. phagocytophilum variants and anaplasmosis.

Chloroplast redox state changes mark cell-to-cell signaling in the hypersensitive response.

Hypersensitive response (HR)-conferred resistance is associated with induction of programmed cell death and pathogen spread restriction in its proximity. The exact role of chloroplastic reactive oxygen species and its link with salicylic acid (SA) signaling in HR remain unexplained. To unravel this, we performed a detailed spatiotemporal analysis of chloroplast redox response in palisade mesophyll and upper epidermis to potato virus Y (PVY) infection in a resistant potato genotype and its transgenic counterpart with impaired SA accumulation and compromised resistance. Besides the cells close to the cell death zone, we detected individual cells with oxidized chloroplasts further from the cell death zone. These are rare in SA-deficient plants, suggesting their role in signaling for resistance. We confirmed that chloroplast redox changes play important roles in signaling for resistance, as blocking chloroplast redox changes affected spatial responses at the transcriptional level. Through spatiotemporal study of stromule induction after PVY infection, we show that stromules are induced by cell death and also as a response to PVY multiplication at the front of infection. Overall induction of stromules is attenuated in SA-deficient plants.

Spatiotemporal cluster of mpox in men who have sex with men: A modeling study in 83 countries.

Mpox outbroke globally during 2022-2023, with more than 90% of cases occurring in men who have sex with men (MSM). However, the spatiotemporal distribution of mpox is not well established yet. This study aimed to explore the spatiotemporal clustering of mpox cases in MSM worldwide. We obtained the numbers of mpox cases from Our World in Data, the number of MSM from the Joint United Nations Programme on HIV/AIDS (UNAIDS), UNAIDS DATA 2021 and UNAIDS Global AIDS Update 2022 and literature. We evaluated the spatiotemporal cluster of mpox in MSM using retrospective space-time analyses method. The total number of mpox cases was 85 795 during May 1, 2022 to March 31, 2023. The most likely cluster was Spain (likelihood ratio = 4764.97; p < 0.001), with a cluster period from July 26 to August 14, 2022. There were 11 secondary clusters, which included 46 countries located in western Europe, eastern and northern South America, northern Europe, Canada, Central Africa, southern and central Europe, Latin America, Turkey, Dominican Republic, New Zealand, and Australia. The findings may inform current and future control strategies of mpox and might provide references for the identification of the spatiotemporal distribution of new and emerging infectious diseases in specific populations.

Temporal trend, spatial analysis and spatiotemporal clusters of infant mortality associated with congenital toxoplasmosis in Brazil: Time series from 2000 to 2020.

OBJECTIVE: To analyse the spatial, temporal and spatial-temporal patterns of infant mortality associated with congenital toxoplasmosis in Brazil between the years 2000 and 2020. METHODS: Ecological study of time series, with spatial analysis and spatiotemporal scan of infant mortality associated with congenital toxoplasmosis from the records of deaths of the Mortality Information System of the Brazilian Ministry of Health. The rates were smoothed by the Local Empirical Bayesian model. The Global Moran Index, Global Geary's Contiguity and Getis-Ord General statistics were calculated for spatial autocorrelation assessment. The trends were evaluated by the Joinpoint method. RESULTS: We identified 1183 infant deaths associated with congenital toxoplasmosis in Brazil between 2000 and 2020. The predominant characteristics were male sex (52.1%), post-neonatal age group (51.9%), white race/colour (45.7%), and Southeast region of residence (40.0%). The infant mortality rate associated with congenital toxoplasmosis showed an increasing trend in the country in the years analysed. The spatial analysis showed heterogeneous distribution of mortality in the Brazilian territory and found no evidence of spatial autocorrelation; but spatial-temporal analysis identified three risk clusters involving 703 municipalities. CONCLUSION: Infant mortality associated with congenital toxoplasmosis is a persistent public health problem in Brazil. The risk factors male sex, indigenous race/colour, early neonatal age, North and Northeast regions and risk clusters mapped in this study should be observed for future analysis and planning of health care policies in the control of infant deaths associated with congenital toxoplasmosis. Health surveillance strategies and public health policies need to be strengthened.

Evaluation of Bayesian spatiotemporal infectious disease models for prospective surveillance analysis.

BACKGROUND: COVID-19 brought enormous challenges to public health surveillance and underscored the importance of developing and maintaining robust systems for accurate surveillance. As public health data collection efforts expand, there is a critical need for infectious disease modeling researchers to continue to develop prospective surveillance metrics and statistical models to accommodate the modeling of large disease counts and variability. This paper evaluated different likelihoods for the disease count model and various spatiotemporal mean models for prospective surveillance. METHODS: We evaluated Bayesian spatiotemporal models, which are the foundation for model-based infectious disease surveillance metrics. Bayesian spatiotemporal mean models based on the Poisson and the negative binomial likelihoods were evaluated with the different lengths of past data usage. We compared their goodness of fit and short-term prediction performance with both simulated epidemic data and real data from the COVID-19 pandemic. RESULTS: The simulation results show that the negative binomial likelihood-based models show better goodness of fit results than Poisson likelihood-based models as deemed by smaller deviance information criteria (DIC) values. However, Poisson models yield smaller mean square error (MSE) and mean absolute one-step prediction error (MAOSPE) results when we use a shorter length of the past data such as 7 and 3 time periods. Real COVID-19 data analysis of New Jersey and South Carolina shows similar results for the goodness of fit and short-term prediction results. Negative binomial-based mean models showed better performance when we used the past data of 52 time periods. Poisson-based mean models showed comparable goodness of fit performance and smaller MSE and MAOSPE results when we used the past data of 7 and 3 time periods. CONCLUSION: We evaluate these models and provide future infectious disease outbreak modeling guidelines for Bayesian spatiotemporal analysis. Our choice of the likelihood and spatiotemporal mean models was influenced by both historical data length and variability. With a longer length of past data usage and more over-dispersed data, the negative binomial likelihood shows a better model fit than the Poisson likelihood. However, as we use a shorter length of the past data for our surveillance analysis, the difference between the Poisson and the negative binomial models becomes smaller. In this case, the Poisson likelihood shows robust posterior mean estimate and short-term prediction results.