Spatiotemporal assessment of pathogenic Leptospira in subtropical coastal watersheds.

The World Health Organization classifies leptospirosis as a significant public health concern, predominantly affecting impoverished and unsanitary regions. By using the Pensacola Bay System as a case study, this study examines the underappreciated susceptibility of developed subtropical coastal ecosystems such as the Pensacola Bay System to neglected zoonotic pathogens such as Leptospira. We analyzed 132 water samples collected over 12 months from 44 distinct locations with high levels of Escherichia coli (>410 most probable number/100 mL). Fecal indicator bacteria (FIB) concentrations were assessed using IDEXX Colilert-18 and Enterolert-18, and an analysis of water physiochemical characteristics and rainfall intensity was conducted. The LipL32 gene was used as a quantitative polymerase chain reaction (qPCR) indicator to identify the distribution of Leptospira interrogans. The results revealed 12 instances of the presence of L. interrogans at sites with high FIB over various land cover and aquatic ecosystem types. Independent of specific rainfall events, a seasonal relationship between precipitation and elevated rates of fecal bacteria and leptospirosis was found. These findings highlight qPCR's utility in identifying pathogens in aquatic environments and the widespread conditions where it can be found in natural and developed areas.

Exploring spatio-temporal changes in coastal recreational fisheries and potential links to extreme weather events.

Extreme weather events across coastal environments are expected to increase in frequency under predicted climate change scenarios. These events can impact coastal recreational fisheries and their supporting ecosystems by influencing the productivity of fish stocks or altering behaviours and decision-making among fishers. Using off-site telephone/diary survey data on estuarine and oceanic recreational fishing activity in eastern Australia, we analyse interannual and geographic variability in bream (Acanthopagrus spp) and snapper (Chrysophrys auratus) catch, total effort and total catch per unit effort (CPUE) through a period (2013/2014, 2017/2018 and 2019/2020) that encompassed severe drought, bushfires and flooding. Interacting spatial and temporal differences were detected for bream and may reflect spatial variation in the intensity and extent of some of the extreme weather events. The catch of snapper did not change temporally, providing little evidence that this species' catch may be influenced by the extreme weather events. Independent bioregional and temporal effects on effort were detected, while CPUE only showed significant bioregional differences. Although adverse conditions created by the extreme weather events may have dissuaded fisher participation and impacted effort, we propose that the observed temporal patterns in effort reflect the early influence of socio-economic changes brought on by the COVID-19 pandemic on coastal recreational fishing, over and above the impacts of extreme weather events. This study demonstrates how interrelated ecological, social and economic factors can shape coastal recreational fisheries and facilitates development of management strategies to address future threats to the sector.

Spatio-temporal variation in water quality due to the anthropogenic impact in Rudrasagar Lake, a Ramsar site in India.

Rudrasagar Lake, a vital habitat for diverse flora and fauna, supports over 2000 households to sustain their daily livelihoods. The current study attempts to examine the impact of human activities on spatio-temporal variation in the water quality of the study area. The study integrates extensive field surveys, sample processing, and statistical analysis to assess the recent status of wetland health. Latin Square Matrix (LSM) was employed to select the sampling sites while the Inverse Distance Weighting (IDW) interpolation technique was used for spatial variation mapping. Modified Weighted Arithmetic Water Quality Index (MWAWQI) and Comprehensive Pollution Index (CPI) were utilized for assessing seasonal variation water quality and pollution loads, respectively. The results showed that dissolved oxygen (DO) was strongly influenced by the tributaries, and recreational activities have substantially influenced the highest concentrations of biochemical oxygen demand (BOD), and total suspended solids (TSS). The central portion of the lake is particularly susceptible to pollution from extensive fishing and recreational activities while peripheral sites are strongly influenced by agricultural run-offs, seepages from brick industries, and municipal wastes characterized by high concentrations of pH, total hardness (TH), oxidation-reduction potential (ORP). The findings reveal remarkable spatio-temporal fluctuations and highlight the areas within the lake susceptible to anthropogenic activities. The study proposed a sustainable management model to ameliorate anthropogenic threats. Moreover, the study contributes to the scientific understanding of the challenges and ensures the long-term viability of wetland health as a vital ecological and socio-economic resource.

Oscillations in Neuronal Activity: A Neuron-Centered Spatiotemporal Model of the Unfolded Protein Response in Prion Diseases.

Many neurodegenerative diseases (NDs) are characterized by the slow spatial spread of toxic protein species in the brain. The toxic proteins can induce neuronal stress, triggering the Unfolded Protein Response (UPR), which slows or stops protein translation and can indirectly reduce the toxic load. However, the UPR may also trigger processes leading to apoptotic cell death and the UPR is implicated in the progression of several NDs. In this paper, we develop a novel mathematical model to describe the spatiotemporal dynamics of the UPR mechanism for prion diseases. Our model is centered around a single neuron, with representative proteins P (healthy) and S (toxic) interacting with heterodimer dynamics (S interacts with P to form two S's). The model takes the form of a coupled system of nonlinear reaction-diffusion equations with a delayed, nonlinear flux for P (delay from the UPR). Through the delay, we find parameter regimes that exhibit oscillations in the P- and S-protein levels. We find that oscillations are more pronounced when the S-clearance rate and S-diffusivity are small in comparison to the P-clearance rate and P-diffusivity, respectively. The oscillations become more pronounced as delays in initiating the UPR increase. We also consider quasi-realistic clinical parameters to understand how possible drug therapies can alter the course of a prion disease. We find that decreasing the production of P, decreasing the recruitment rate, increasing the diffusivity of S, increasing the UPR S-threshold, and increasing the S clearance rate appear to be the most powerful modifications to reduce the mean UPR intensity and potentially moderate the disease progression.

Exploring spatiotemporal distribution characteristics of air quality and driving factors: empirical evidence of 288 cities in China.

Excellent air quality is important for China to achieve high quality economic development. The paper analyses the spatial and temporal distribution characteristics of the air quality index (AQI) in 288 Chinese cities, and further investigates the driving factors affecting air quality using the spatial Durbin model (SDM) based on the panel data of 288 Chinese cities from 2014 to 2021. The results of the study show that: (1) China's air quality level has improved in general, but there are large differences in air quality between regions; (2) China's AQI has significant spatial positive autocorrelation, and the Moran's scatter plot shows a high-high and low-low agglomeration; (3) The driving factors of air quality have different effects, and regional heterogeneity is obvious. Some developed regions in China have already crossed the inflexion point of the environmental Kuznets curve (EKC); promoting industrial upgrading and reducing pollutant emissions can significantly improve urban PM2.5 concentrations; and the "Three-Year Strategy for Conquering the Blue Sky War" policy has lowered the AQI in North China and improved PM2.5 concentrations nationwide. Based on the above findings, the paper puts forward corresponding policy recommendations.

Spatiotemporal organization of ant foraging from a complex systems perspective.

We use complex systems science to explore the emergent behavioral patterns that typify eusocial species, using collective ant foraging as a paradigmatic example. Our particular aim is to provide a methodology to quantify how the collective orchestration of foraging provides functional advantages to ant colonies. For this, we combine (i) a purpose-built experimental arena replicating ant foraging across realistic spatial and temporal scales, and (ii) a set of analytical tools, grounded in information theory and spin-glass approaches, to explore the resulting data. This combined approach yields computational replicas of the colonies; these are high-dimensional models that store the experimental foraging patterns through a training process, and are then able to generate statistically similar patterns, in an analogous way to machine learning tools. These in silico models are then used to explore the colony performance under different resource availability scenarios. Our findings highlight how replicas of the colonies trained under constant and predictable experimental food conditions exhibit heightened foraging efficiencies, manifested in reduced times for food discovery and gathering, and accelerated transmission of information under similar conditions. However, these same replicas demonstrate a lack of resilience when faced with new foraging conditions. Conversely, replicas of colonies trained under fluctuating and uncertain food conditions reveal lower efficiencies at specific environments but increased resilience to shifts in food location.

Geographically and Temporally Weighted Regression in Assessing Dengue Fever Spread Factors in YunnanBorder Regions.

Objective: This study employs the Geographically and Temporally Weighted Regression (GTWR) model to assess the impact of meteorological elements and imported cases on dengue fever outbreaks, emphasizing the spatial-temporal variability of these factors in border regions. Methods: We conducted a descriptive analysis of dengue fever's temporal-spatial distribution in Yunnan border areas. Utilizing annual data from 2013 to 2019, with each county in the Yunnan border serving as a spatial unit, we constructed a GTWR model to investigate the determinants of dengue fever and their spatio-temporal heterogeneity in this region. Results: The GTWR model, proving more effective than Ordinary Least Squares (OLS) analysis, identified significant spatial and temporal heterogeneity in factors influencing dengue fever's spread along the Yunnan border. Notably, the GTWR model revealed a substantial variation in the relationship between indigenous dengue fever incidence, meteorological variables, and imported cases across different counties. Conclusion: In the Yunnan border areas, local dengue incidence is affected by temperature, humidity, precipitation, wind speed, and imported cases, with these factors' influence exhibiting notable spatial and temporal variation.

Spatio-temporal distributions and determinants of diarrhea among under-five children in Ethiopia.

Objective: The purpose of this study was to evaluate the spatio-temporal pattern of Ethiopia's childhood diarrheal disease and identify its contributing factors. Methods: We conducted analyses on secondary data from four Ethiopian Demographic and Health Surveys conducted between 2000 and 2016. Moran's I was used to determine spatial dependence and spatial models were used to evaluate variables associated with diarrhea in under-five children at the zonal level. Results: Childhood diarrhea showed spatial clustering in Ethiopia (Moran's I; p < 0.05). The spatial regression model revealed significant factors at the zonal level: children born at home (eθ = 1.355, 95% CI: 1.052-1.544, p < 0.001), low birth weight (eθ = 1.18, 95% CI: 1.017-1.691, p < 0.05), and unimproved source of water (eθ = 0.8568, 95% CI: 0.671-1.086, p < 0.01). Conclusion: The prevalence of diarrhea among under-five children varied over time by zone, with the Assosa, Hundene, and Dire Diwa zones having the highest rates. Home births and low birth weight contributed to the prevalence of childhood diarrhea. In high-risk zones of Ethiopia, reducing childhood diarrhea requires integrated child health interventions and raising awareness about the potential hazards associated with unimproved water sources.

Spatial-Temporal Analysis of Neural Desynchronization in Sleeplike States Reveals Critical Dynamics.

Sleep is characterized by nonrapid eye movement sleep, originating from widespread neuronal synchrony, and rapid eye movement sleep, with neuronal desynchronization akin to waking behavior. While these were thought to be global brain states, recent research suggests otherwise. Using time-frequency analysis of mesoscopic voltage-sensitive dye recordings of mice in a urethane-anesthetized model of sleep, we find transient neural desynchronization occurring heterogeneously across the cortex within a background of synchronized neural activity, in a manner reminiscent of a critical spreading process and indicative of an "edge-of-synchronization" phase transition.

Spatiotemporal dynamics and determinants of medical service efficiency in China.

BACKGROUND: Medical service efficiency is an important indicator for measuring the equity of medical services. Therefore, this study primarily focuses on investigating the spatiotemporal domain to explore both spatial and temporal characteristics, as well as influencing factors that affect medical service efficiency across diverse provinces in China. METHODS: The super Epsilon-based Measure (EBM) unexpected model has previously been utilized to quantify energy eco-efficiency, carbon emission efficiency, and green development efficiency. However, limited studies have applied this method to assess the efficiency of healthcare services. Therefore, this study investigates the application of the super-EBM-unexpected model in evaluating medical service efficiency, and further integrates spatial econometric models to explore the influencing factors of medical service efficiency and aims to identify potential avenues for improvement. RESULTS: The average efficiency of medical services in the 31 provinces of China ranges from 0.6 to 0.7, indicating predominantly low efficiency values. However, economically developed coastal areas exhibit relatively high efficiency levels above 1. Conversely, regions with relatively lower levels of economic development demonstrate lower efficiency rates at approximately 0.3. Evidently, substantial regional disparities exist. For the influencing factors, the enhancement of residents' living standards can effectively foster the medical service efficiency, while residential living standards of nearby areas can also exert an impact in this region. The influence of educational attainment on medical service efficiency exhibits a significant inhibitory effect. CONCLUSIONS: The majority of China's 31 provinces exhibit suboptimal medical service efficiency, with notable regional disparities. Future policy initiatives should be tailored to address the unique challenges faced by regions with lower levels of economic development, prioritizing enhancements in both the efficacy and quality of their healthcare systems.

Spatiotemporal heterogeneity of LMOD1 expression summarizes two modes of cell communication in colorectal cancer.

Cellular communication (CC) influences tumor development by mediating intercellular junctions between cells. However, the role and underlying mechanisms of CC in malignant transformation remain unknown. Here, we investigated the spatiotemporal heterogeneity of CC molecular expression during malignant transformation. It was found that although both tight junctions (TJs) and gap junctions (GJs) were involved in maintaining the tumor microenvironment (TME), they exhibited opposite characteristics. Mechanistically, for epithelial cells (parenchymal component), the expression of TJ molecules consistently decreased during normal-cancer transformation and is a potential oncogenic factor. For fibroblasts (mesenchymal component), the expression of GJs consistently increased during normal-cancer transformation and is a potential oncogenic factor. In addition, the molecular profiles of TJs and GJs were used to stratify colorectal cancer (CRC) patients, where subtypes characterized by high GJ levels and low TJ levels exhibited enhanced mesenchymal signals. Importantly, we propose that leiomodin 1 (LMOD1) is biphasic, with features of both TJs and GJs. LMOD1 not only promotes the activation of cancer-associated fibroblasts (CAFs) but also inhibits the Epithelial-mesenchymal transition (EMT) program in cancer cells. In conclusion, these findings demonstrate the molecular heterogeneity of CC and provide new insights into further understanding of TME heterogeneity.

Revealing the spatiotemporal evolution pattern and convergence law of agricultural land transfer in China.

The transfer of land plays a crucial role in revitalizing land resources, acting as a catalyst for promoting the high-quality development of agriculture. The land transfer ratio is a crucial metric for assessing the progress of rural land transfer and the effective allocation of rural land resources. Thus, this study examines the rural land transfer ratio across 30 provinces in China from 2005 to 2020. The study explores the distribution characteristics of the ratio using the rank-size rule and trend surface analysis. The LISA space-time transition method is employed to analyze the spatial and temporal dynamics of the rural land transfer ratio and examine its convergence. The study aims to comprehensively analyze the spatial distribution characteristics and evolutionary patterns of rural land transfer in China, illustrating the convergence and influencing factors during the development process. The results indicate that: (1) The rural land transfer ratio in China is generally increasing, with a spatial pattern showing an upward trend from west to east and from north to south. The main spatial contrast is between the eastern and western regions, with a relatively minor distinction between the southern and northern regions. (2) The LISA space-time transition highlights a significant spatial locking effect in China's rural land transfer ratio, suggesting strong spatial integration in its evolution. (3) Clear indications of σ convergence, absolute ß convergence, and club convergence are evident in China's rural land transfer ratio. This suggests a gradual reduction in internal disparities among provinces and regions, where areas with higher land transfer ratios influence spatial spillover effects on adjacent lower areas. (4) Factors such as transportation infrastructure, irrigation, water conservancy construction, and farmers' per capita income collectively influence the spatial and temporal evolution of China's rural land transfer ratio, with dominant driving factors varying across different periods.

Spatiotemporal Analysis of HIV/AIDS Incidence in China From 2009 to 2019 and Its Association With Socioeconomic Factors: Geospatial Study.

BACKGROUND: The Joint United Nations Program on HIV/AIDS (UNAIDS) has set the "95-95-95" targets to ensure that 95% of all people living with HIV will know their HIV status, 95% of all people living with HIV will receive sustained antiretroviral therapy (ART), and 95% of all people receiving ART will achieve viral suppression (<1000 copies/mL). However, few countries have currently achieved these targets, posing challenges to the realization of the UNAIDS goal to eliminate the global HIV/AIDS epidemic by 2030. The Chinese government has implemented corresponding policies for HIV/AIDS prevention and control; however, it still faces the challenge of a large number of HIV/AIDS cases. Existing research predominantly focuses on the study of a particular region or population in China, and there is relatively limited research on the macro-level analysis of the spatiotemporal distribution of HIV/AIDS across China and its association with socioeconomic factors. OBJECTIVE: This study seeks to identify the impact of these factors on the spatiotemporal distribution of HIV/AIDS incidence in China, aiming to provide scientific recommendations for future policy development. METHODS: This study employed ArcGIS 10.2 (Esri) for spatial analysis, encompassing measures such as the imbalance index, geographical concentration index, spatial autocorrelation analysis (Moran I), and hot spot analysis (Getis-Ord Gi*). These methods were used to unveil the spatiotemporal distribution characteristics of HIV/AIDS incidence in 31 provinces of China from 2009 to 2019. Geographical Detector was used for ecological detection, risk area detection, factor detection, and interaction detection. The analysis focused on 9 selected socioeconomic indicators to further investigate the influence of socioeconomic factors on HIV/AIDS incidence in China. RESULTS: The spatiotemporal distribution analysis of HIV/AIDS incidence in China from 2009 to 2019 revealed distinct patterns. The spatial distribution type of HIV/AIDS incidence in China was random in 2009-2010. However, from 2011 to 2019, the distribution pattern evolved toward a clustered arrangement, with the degree of clustering increasing each year. Notably, from 2012 onwards, there was a significant and rapid growth in the aggregation of cold and hot spot clusters of HIV/AIDS incidence in China, stabilizing only by the year 2016. An analysis of the impact of socioeconomic factors on HIV/AIDS incidence in China highlighted the "urbanization rate" and "urban basic medical insurance fund expenditure" as the primary factors influencing the spatial distribution of HIV/AIDS incidence. Additionally, among social factors, indicators related to medical resources exerted a crucial influence on HIV/AIDS incidence. CONCLUSIONS: From 2009 to 2019, HIV/AIDS incidence in China was influenced by various socioeconomic factors. In the future, it is imperative to optimize the combination of different socioeconomic indicators based on regional incidence patterns. This optimization will facilitate the formulation of corresponding policies to address the challenges posed by the HIV/AIDS epidemic.

A Bayesian spatio-temporal model of COVID-19 spread in England.

Exploring the spatio-temporal variations of COVID-19 transmission and its potential determinants could provide a deeper understanding of the dynamics of disease spread. This study aimed to investigate the spatio-temporal spread of COVID-19 infections in England, and examine its associations with socioeconomic, demographic and environmental risk factors. We obtained weekly reported COVID-19 cases from 7 March 2020 to 26 March 2022 at Middle Layer Super Output Area (MSOA) level in mainland England from publicly available datasets. With these data, we conducted an ecological study to predict the COVID-19 infection risk and identify its associations with socioeconomic, demographic and environmental risk factors using a Bayesian hierarchical spatio-temporal model. The Bayesian model outperformed the ordinary least squares model and geographically weighted regression model in terms of prediction accuracy. The spread of COVID-19 infections over space and time was heterogeneous. Hotspots of infection risk exhibited inconsistent clustering patterns over time. Risk factors found to be positively associated with COVID-19 infection risk were: annual household income [relative risk (RR) = 1.0008, 95% Credible Interval (CI) 1.0005-1.0012], unemployment rate [RR = 1.0027, 95% CI 1.0024-1.0030], population density on the log scale [RR = 1.0146, 95% CI 1.0129-1.0164], percentage of Caribbean population [RR = 1.0022, 95% CI 1.0009-1.0036], percentage of adults aged 45-64 years old [RR = 1.0031, 95% CI 1.0024-1.0039], and particulate matter ( PM 2.5 ) concentrations [RR = 1.0126, 95% CI 1.0083-1.0167]. The study highlights the importance of considering socioeconomic, demographic, and environmental factors in analysing the spatio-temporal variations of COVID-19 infections in England. The findings could assist policymakers in developing tailored public health interventions at a localised level.

The long-term spatio-temporal trends in burden and attributable risk factors of major depressive disorder at global, regional and national levels during 1990-2019: a systematic analysis for GBD 2019.

AIMS: Caused by multiple risk factors, heavy burden of major depressive disorder (MDD) poses serious challenges to public health worldwide over the past 30 years. Yet the burden and attributable risk factors of MDD were not systematically known. We aimed to reveal the long-term spatio-temporal trends in the burden and attributable risk factors of MDD at global, regional and national levels during 1990-2019. METHODS: We obtained MDD and attributable risk factors data from Global Burden of Disease Study 2019. We used joinpoint regression model to assess the temporal trend in MDD burden, and age-period-cohort model to measure the effects of age, period and birth cohort on MDD incidence rate. We utilized population attributable fractions (PAFs) to estimate the specific proportions of MDD burden attributed to given risk factors. RESULTS: During 1990-2019, the global number of MDD incident cases, prevalent cases and disability-adjusted life years (DALYs) increased by 59.10%, 59.57% and 58.57%, respectively. Whereas the global age-standardized incidence rate (ASIR), age-standardized prevalence rate (ASPR) and age-standardized DALYs rate (ASDR) of MDD decreased during 1990-2019. The ASIR, ASPR and ASDR in women were 1.62, 1.62 and 1.60 times as that in men in 2019, respectively. The highest age-specific incidence, prevalence and DALYs rate occurred at the age of 60-64 in women, and at the age of 75-84 in men, but the maximum increasing trends in these age-specific rates occurred at the age of 5-9. Population living during 2000-2004 had higher risk of MDD. MDD burden varied by socio-demographic index (SDI), regions and nations. In 2019, low-SDI region, Central sub-Saharan Africa and Uganda had the highest ASIR, ASPR and ASDR. The global PAFs of intimate partner violence (IPV), childhood sexual abuse (CSA) and bullying victimization (BV) were 8.43%, 5.46% and 4.86% in 2019, respectively. CONCLUSIONS: Over the past 30 years, the global ASIR, ASPR and ASDR of MDD had decreased trends, while the burden of MDD was still serious, and multiple disparities in MDD burden remarkably existed. Women, elderly and populations living during 2000-2004 and in low-SDI regions, had more severe burden of MDD. Children were more susceptible to MDD. Up to 18.75% of global MDD burden would be eliminated through early preventing against IPV, CSA and BV. Tailored strategies-and-measures in different regions and demographic groups based on findings in this studywould be urgently needed to eliminate the impacts of modifiable risk factors on MDD, and then mitigate the burden of MDD.

Space-temporal analysis of the Specialized Services of the Health Care Network for Persons with Disabilities in Brazil.

Considering the institution of the Care Network for People with Disabilities (RCPD) in Brazil, this study analyzed the spatial distribution and the temporal trend of implementing specialized services that received financial support in the first eight years of this policy. We realized an ecological study based on the National Register of Health Facilities data from April/2012 to March/2020. A joinpoint regression was used for temporal trend analysis, and thematic maps were produced for spatial analysis of rehabilitation modalities and types of services. The most available services were physical and intellectual rehabilitation. The Southeast and Northeast regions had a higher concentration of specialized services. Despite the lower number of services, there was an average annual growth between 9.6% and 41.3%. This finding indicates an increase in specialized services for people with disabilities in the period analyzed, but care gaps are still being verified in the macro-regions of Brazil.

Spatio-temporal dynamics of the human small intestinal microbiome and its response to a synbiotic.

Although fecal microbiota composition is considered to preserve relevant and representative information for distal colonic content, it is evident that it does not represent microbial communities inhabiting the small intestine. Nevertheless, studies investigating the human small intestinal microbiome and its response to dietary intervention are still scarce. The current study investigated the spatio-temporal dynamics of the small intestinal microbiome within a day and over 20 days, as well as its responses to a 14-day synbiotic or placebo control supplementation in 20 healthy subjects. Microbial composition and metabolome of luminal content of duodenum, jejunum, proximal ileum and feces differed significantly from each other. Additionally, differences in microbiota composition along the small intestine were most pronounced in the morning after overnight fasting, whereas differences in composition were not always measurable around noon or in the afternoon. Although overall small intestinal microbiota composition did not change significantly within 1 day and during 20 days, remarkable, individual-specific temporal dynamics were observed in individual subjects. In response to the synbiotic supplementation, only the microbial diversity in jejunum changed significantly. Increased metabolic activity of probiotic strains during intestinal passage, as assessed by metatranscriptome analysis, was not observed. Nevertheless, synbiotic supplementation led to a short-term spike in the relative abundance of genera included in the product in the small intestine approximately 2 hours post-ingestion. Collectively, small intestinal microbiota are highly dynamic. Ingested probiotic bacteria could lead to a transient spike in the relative abundance of corresponding genera and ASVs, suggesting their passage through the entire gastrointestinal tract. This study was registered to http://www.clinicaltrials.gov, NCT02018900.

Analysing the outbreaks of leptospirosis after floods in Kerala, India.

A growing number of studies have linked the incidence of leptospirosis with the occurrence of flood events. Nevertheless, the interaction between flood and leptospirosis has not been extensively studied to understand the influence of flood attributes in inducing new cases. This study reviews leptospirosis cases in relation to multiple flood occurrences in Kerala, India. Leptospirosis data were obtained for three years: 2017 (non-flood year) and two years with flooding-2018 (heavy flooding) and 2019 (moderate flooding). We considered the severity of flood events using the discharge, duration and extent of each flooding event and compared them with the leptospirosis cases. The distribution of cases regarding flood discharge and duration was assessed through descriptive and spatiotemporal analyses, respectively. Furthermore, cluster analyses and spatial regression were completed to ascertain the relationship between flood extent and the postflood cases. This study found that postflood cases of leptospirosis can be associated with flood events in space and time. The total cases in both 2018 and 2019 increased in the post-flood phase, with the increase in 2018 being more evident. Unlike the 2019 flood, the flood of 2018 is a significant spatial indicator for postflood cases. Our study shows that flooding leads to an increase in leptospirosis cases, and there is stronger evidence for increased leptospirosis cases after a heavy flood event than after a moderate flooding event. Flood duration may be the most important factor in determining the increase in leptospirosis infections.

The spatio-temporal pattern and its influencing factors of production efficiency of health resources in China.

There is always a contradiction between the limited health resources and the unlimited demand of the population for health services, and only by improving the productivity of health resources can the health level of the population be improved as much as possible. Using prefecture-level administrative regions as spatial units, the paper analyzes the spatial pattern and changes of health productivity of health resources in China from 2000 to 2010, and uses a spatial panel Tobit model to examine the effects of factors such as technical level of health institutions, health service accessibility, public health policies and ecological environment quality on health productivity of health resources. The results show that with the Hu Huanyong line as the dividing line, the spatial heterogeneity of "high in the southeast and low in the northwest" in the health productivity of China's health resources is clear; as the regional differences narrow, the spatial correlation increases, and the spatial pattern of "overall dispersion and partial agglomeration" becomes more obvious. The fitting results of the spatial Durbin model reveal the direction and degree of influence of local and adjacent factors on the production efficiency of health resources. The positive influence of technical level of local health institutions and the accessibility of health services, the literacy level and the ability to pay for health services of residents in adjacent areas, the degree of urbanization of regional health resource allocation, climate suitability and the quality of the atmospheric environment are significant. And the negative influence of local residents' literacy and ability to pay for health services, the technical level of health institutions in adjacent areas and the degree of medicalization of health resource allocation are also significant. The influence of the degree of medicalization of local health resource allocation and the accessibility of health services in adjacent areas are significantly spatial-heterogeneous.

Spatio-temporal characterization of phenotypic resistance in malaria vector species.

BACKGROUND: Malaria, a deadly disease caused by Plasmodium protozoa parasite and transmitted through bites of infected female Anopheles mosquitoes, remains a significant public health challenge in sub-Saharan Africa. Efforts to eliminate malaria have increasingly focused on vector control using insecticides. However, the emergence of insecticide resistance (IR) in malaria vectors pose a formidable obstacle, and the current IR mapping models remain static, relying on fixed coefficients. This study introduces a dynamic spatio-temporal approach to characterize phenotypic resistance in Anopheles gambiae complex and Anopheles arabiensis. We developed a cellular automata (CA) model and applied it to data collected from Ethiopia, Nigeria, Cameroon, Chad, and Burkina Faso. The data encompasses georeferenced records detailing IR levels in mosquito vector populations across various classes of insecticides. In characterizing the dynamic patterns of confirmed resistance, we identified key driving factors through correlation analysis, chi-square tests, and extensive literature review. RESULTS: The CA model demonstrated robustness in capturing the spatio-temporal dynamics of confirmed IR states in the vector populations. In our model, the key driving factors included insecticide usage, agricultural activities, human population density, Land Use and Land Cover (LULC) characteristics, and environmental variables. CONCLUSIONS: The CA model developed offers a robust tool for countries that have limited data on confirmed IR in malaria vectors. The embrace of a dynamical modeling approach and accounting for evolving conditions and influences, contribute to deeper understanding of IR dynamics, and can inform effective strategies for malaria vector control, and prevention in regions facing this critical health challenge.