Space-time Clustering Research Articles

Epidemiology and spatiotemporal analysis of acute hemorrhagic conjunctivitis in Zhejiang province, China (2004–2023)

BackgroundAcute hemorrhagic conjunctivitis (AHC) has become a significant public health issue in Zhejiang province. However, the analysis of epidemiological characteristics and spatio-temporal patterns of AHC in Zhejiang province has not been studied yet.MethodsMonthly cases of AHC from 2004 to 2023 reported at the county level in Zhejiang province were obtained from the China Information System for Disease Control and Prevention. Demographic features, yearly county incidence, global spatial autocorrelation, local spatial autocorrelation analyses, and temporal and space–time cluster analysis were performed to identify and visualize the spatiotemporal patterns of AHC cases in Zhejiang province. The epidemiological characteristics of AHC outbreaks in the same period in Zhejiang province were also compared.ResultsA total of 52,119 AHC cases were reported in Zhejiang province, yielding an average incidence rate of 5.37 per 100,000. No fatalities were reported. The average age of those affected was 25.44 ± 4.37 years, with the highest incidence (16.70%) among individuals aged between 10 and 19 years. Seasonal peaks occur from August to October each year. Students and farmers experienced the highest incidence rates of infection. Significant positive spatial correlations for AHC were observed in Zhejiang province in the years 2007 (Moran’s I = 0.095, p = 0.039), 2009 (Moran’s I = 0.075, p = 0.031), and 2011 (Moran’s I = 0.173, p = 0.034), indicating spatial clustering. Spatiotemporal scanning identified two distinct clusters: Cluster 1 and Cluster 2. Cluster 1, characterized by a relative risk of 21.44 (p < 0.001), was located in northeastern Zhejiang province, comprising 30 counties, with an active period from 1st September 2010 to 30th September 2010. Compared to low-risk regions, high-risk counties exhibited a different demographic profile with a higher proportion of men, older people, and farmers. Among the affected students during outbreaks, the predominant symptoms were conjunctival congestion, increased eye secretions, eye swelling, eye pain, photophobia and tearing, while the incidence of fever was relatively low.ConclusionThe results of this study demonstrate the spatiotemporal heterogeneity of AHC cases in Zhejiang province and underscore the necessity for targeted prevention and control measures in high-risk areas to mitigate transmission and occurrence.

Seismicity of a relic slab: space–time cluster analysis in the Vrancea Seismic Zone

The Vrancea Seismic Zone (VSZ) is an atypical intermediate-depth earthquake nest located in the South-East Carpathians in Romania, often regarded as a relic slab sinking into the mantle. The origin of the slab and the earthquakes it produces are debated because brittle failure is unlikely to occur at mantle depths. Cluster types and statistical properties of seismicity can vary with deformation regime, fluid content and temperature. Here we investigate the spatial–temporal properties of earthquakes recorded in the VSZ from a high-quality local catalogue, identify and classify earthquake clusters, placing constraints on the debated nature of the Vrancea slab, its coupling with the overlying crust, and its potential for triggering crustal earthquakes. We use the nearest-neighbour distance to estimate the correlation between pairs of earthquakes, considering the origin time, magnitude, b-value and fractal dimension of the observed seismicity with Mw ≥ 2.5 from the 1977–2023 period. With this approach, we find a small percentage of clustered seismicity (8%), suggesting that background seismicity dominates. We identified 12 conventional mainshock-dominated sequences and 17 swarms with relatively small (0.92) and large (1.73) b-values, respectively, that may reflect differences in stress or the presence of fluids in the crustal volume. The aftershock decays—p-values of 0.99 for the large-event clusters and 1.42 for the swarms—may reflect typical and, respectively, fast stress relaxations. Swarm clusters are predominantly localised within the crust, whereas conventional mainshock sequences lack foreshocks and prevail in the subcrustal domain, occasionally triggering aftershocks at shallower depths. This partitioning suggests higher heat flow and fluid-modulated seismicity in the crust, as opposed to brittle failure conditions, triggered by slab dynamics in the mantle, including abrupt stress release without preceding signals. The spread of aftershocks from subcrustal large mainshocks to shallower depths indicate a stress transfer process where the descending Vrancea slab influences seismic activity in the overlying crust.Graphical

Fuel Replenishment Problem of Heterogeneous Fleet in Initiative Distribution Mode

Petrol, a vital energy source for residents’ consumption and economically sustainable operation, generates substantial distribution demand. To reduce distribution costs, we propose a fuel replenishment problem using a heterogeneous fleet based on the initiative distribution mode. In this mode, the distribution center determines both the delivery orders of customers and the distribution plan. We develop a mathematical model with minimal operational costs, including transport, employment, and penalty costs. A Two-stage heuristic algorithm K-IBKA based on time-space clustering is proposed, which also combines the advantages of the butterfly optimization algorithm in quick convergence and hierarchical mutation strategy in population diversity. The results demonstrate that: (1) Heterogeneous truck distribution exhibits better cost advantages compared to homogeneous distribution, reducing total costs by 13.07%; (2) Compared to passive distribution mode, the total cost of the initiative distribution mode is reduced by 11.03% and 41.80%, respectively, through small and large-scale instances. (3) Compared with the unimproved BKA, ALNS, and GA, the total cost calculated by K-IBKA is reduced by 37.68%, 35.30%, and 27.26%, respectively, thus demonstrating the contribution of this work to reducing the cost of petrol distribution and achieving sustainable development of distribution.

Observational methods for human studies of transgenerational effects

ABSTRACT There are substantial challenges in studying human transgenerational epigenetic outcomes resulting from environmental conditions. The task requires specialized methods and tools that incorporate specific knowledge of multigenerational relationship combinations of probands and their ancestors, phenotype data for individuals, environmental information of ancestors and their descendants, which can span historical to present datasets, and informative environmental data that chronologically aligns with ancestors and descendants over space and time. As a result, there are few epidemiologic studies of potential transgenerational effects in human populations, thus limiting the knowledge of ancestral environmental conditions and the potential impacts we face with modern human health outcomes. In an effort to overcome some of the challenges in studying human transgenerational effects, we present two transgenerational study designs: transgenerational space-time cluster detection and transgenerational case-control study design. Like other epidemiological methods, these methods determine whether there are statistical associations between phenotypic outcomes (e.g., adverse health outcomes) among probands and the shared environments and environmental factors facing their ancestors. When the ancestor is a paternal grandparent, a statistically significant association provides some evidence that a transgenerational inheritable factor may be involved. Such results may generate useful hypotheses that can be explored using epigenomic data to establish conclusive evidence of transgenerational heritable effects. Both methods are proband-centric: They are designed around the phenotype of interest in the proband generation for case selection and family pedigree creation. In the examples provided, we incorporate at least three generations of paternal lineage in both methods to observe a potential transgenerational effect.

Geographic Determinants and Spatial Epidemiology of Prescription Drug Abuse: A Comprehensive Analysis of Distribution Patterns, Treatment Accessibility and Intervention Strategies

This study examines the complex spatial patterns and geographic variations in prescription drug abuse, analyzing their impact on treatment outcomes and public health interventions. Through comprehensive spatial epidemiological analysis, we investigate how geographic factors influence abuse patterns across urban, suburban, and rural landscapes. The research synthesizes data on healthcare accessibility, socioeconomic conditions, and regional policy frameworks to understand their collective impact on prescription drug misuse. Our findings reveal significant geographic disparities in treatment accessibility, with rural areas facing substantial barriers to addiction services compared to urban centers. Analysis of prescription drug monitoring programs demonstrates varying effectiveness across regions, highlighting the need for spatially-tailored interventions. The study identifies distinct regional profiles of drug misuse, influenced by factors including healthcare infrastructure, cultural norms, and local regulatory environments. Advanced spatial analysis techniques, including geospatial mapping and hotspot analysis, revealed significant correlations between geographic determinants and abuse patterns. Results indicate that proximity to healthcare facilities, pharmaceutical distribution networks, and demographic characteristics contribute to localized risk profiles. The integration of multiple data sources, including prescription records and treatment admissions, provided insights into space-time clustering of abuse patterns. This research emphasizes the importance of developing geographically-informed approaches to combat prescription drug abuse, suggesting that intervention strategies should be tailored to specific regional contexts while addressing broader systemic issues. The findings have significant implications for public health policy, healthcare resource allocation, and the development of targeted prevention strategies.

High-risk spatiotemporal patterns of leprosy in the southeastern region of Yunnan province from 2010 to 2022: an analysis at the township level

BackgroundDespite being preventable and curable, leprosy remains endemic in some undeveloped regions, including China. Wenshan Zhuang and Miao Autonomous Prefecture (Wenshan prefecture) currently bears the highest leprosy burden in China. In this ecological study, we aimed to analyze the epidemiological characteristics as well as identify and visualize the high-risk townships of Wenshan prefecture using the most updated leprosy data from 2010 to 2022.MethodsGeographical information system combined with spatial scan statistics was used for newly detected leprosy cases abstracted from the Leprosy Management Information System in China. Global Moran’s I index was used to uncover the spatial pattern of leprosy at the township level. Spatial scan statistics, encompassing purely temporal, purely spatial, spatial variation in temporal trends, and space-time analysis, were implemented for detecting the risk clusters.ResultsBetween 2010 and 2022, Wenshan prefecture detected 532 new leprosy cases, comprising 352 (66.17%) males and 180 (33.83%) females. The aggregated time primarily occurred between October 2010 and March 2014. The distribution pattern of newly detected leprosy cases was spatially clustered. We identified four high-risk spatial clusters encompassing 54.51% of the new cases. Furthermore, spatial variation in temporal trends highlighted one cluster as a potential high-risk area. Finally, two space-time clusters were detected, and the most likely cluster was predominantly located in the central and northwest regions of Wenshan prefecture, spanning from January 2010 to September 2013.ConclusionsIn this ecology study, we characterized the epidemiological features and temporal and spatial patterns of leprosy in Wenshan prefecture using the most recent leprosy data between 2010 and 2022. Our findings offer scientific insights into the epidemiological profiles and spatiotemporal dynamics of leprosy in Wenshan prefecture. Clinicians and policymakers should pay particular attention to the identified clusters for the prevention and control of leprosy.

Space-time cluster analysis and maximum entropy modeling of Peste des petits ruminants (PPR) in Türkiye.

Peste des petits ruminants (PPR) is an economically important highly serious transboundary disease that mainly occurs in small ruminants such as sheep and goats. The aim of this study was to identify the probability of risk and and space-time clusters of Peste des Petits Ruminants (PPR) in Türkiye. The occurrence of PPR in Türkiye from 2017 to 2019 was investigated in this study using spatial analysis based on geographic information system (GIS). Between these dates, it was determined that 337 outbreaks and 18,467 cases. The highest number of outbreaks were detected in the Central Anatolia region. It was determined that PPR is seen more intensely in sheep compared to goats in Türkiye. In this study, 34 environmental variables (19 bioclimatic, 12 precipitation, altitude and small livestock density variables) were used to explore the environmental influences on PPR outbreak by maximum entropy modeling (Maxent). The clusters of PPR in Türkiye were identified using the retrospective space-time scan data that were computed using the space-time permutation model. A PPR prediction model was created using data on PPR outbreaks combination with environmental variables. Nineteen significant (p < 0.001) space-time clusters were determined. It was discovered that the variables altitude, sheep density, precipitation in june, and average temperature in the warmest season made important contributions to the model and the PPR outbreak may be strongly related with these variables. In this study, PPR in Türkiye has been characterized significantly spatio-temporal and enviromental factors. In this context, the disease pattern and obtained these findings will contribute to policymakers in the prevention and control of the disease.

Space and time distribution of seismic source energy at Campi Flegrei, Italy through the last unrest phase (1.1.2000–31.12.2023)

We describe the space-time pattern of seismicity occurring on Campi Flegrei Caldera (CFC), Italy, where ground deformations and seismicity represent the drivers of its current bradyseismic crisis, well known and extensively studied at an international level. In detail we consider the seismicity in the time interval starting on 1.1.2000 and ending on 31.12.2023. We revise the statistics of the earthquake occurrence, focusing at possible precursory time changes of the b-parameter of the Gutenberg and Richter (G&R b−value) distribution and at the time distribution of the total seismic moment inside any swarm. To estimate the G&R b−value we use a Monte Carlo method instead of the ordinary Least Squares or Maximum likelihood methods, to easily measure the uncertainty on the b−value taking into account uncertainties on the magnitude estimates. Results show that G&R a−value and b−value calculated for cumulative and discrete distributions of Mw, the moment-magnitude, and Md, the so-called duration-magnitude, are the same inside the uncertainties; a−value and b−value for Md are significantly different from the same parameters estimated for Mw, being b−value for Mw close to the value of 1.0 and b−value for Md close to 0.8. The “bounded” G&R distribution fits the data yielding a−value and b−value close to those for the unbounded distribution. The mean annual rate of exceedance, calculated for the entire catalogue, results to be 0.033±0.015 (years−1) corresponding to a return period of 30±14 years for Mw=4.5. The time dependence of G&R b-parameter show a b−value time pattern characterized by variations slightly outside 1-σ uncertainty bar, tending to the value of 1 approaching present. As evidenced by several past studies, earthquakes in CFC occur in space-time clusters, with a mean time duration of 1 day. We selected the swarms with a selection algorithm, based on the joint estimation of inter-arrival times and inter-event distance for the consecutive event couples. The plot of the event number in each cluster vs the time of occurrence, clearly show that in CFC the number of cluster occurrences and the event number in each cluster accelerates during time starting from 2010. The time-pattern of the total seismic moment in each cluster shows that, contrarily to the event number, there is no evident striking increase of the total swarm moment as a function of time.We also consider distribution of the Energy Space Density of the CFC earthquakes, ESD. This quantity shows a clearly visible enlargement of the fractured rock volumes in the last 15 months, toward West, at a depth around 3000 m below sea level. The most fractured zone coincides with the greatest contrasts in seismic attenuation.The present study confirms that the current unrest phase is still ongoing, with an enlargement of the rock fracturing zone which extends southward and westward as compared with that measured 22 months before.

Examining the Boost Account for Repeat and Near Repeat Burglary in Canada.

Research suggests that previously burglarized targets, and targets located near such locations, are at an increased risk of being victimized. However, this elevated risk is only temporary and appears to subside over time. The boost account is one theory that attempts to describe the occurrence of repeat, and near repeat, burglaries. The boost account suggests that these burglaries are the result of the same offender returning to burglarize a dwelling that they have successfully burglarized in the past, or one near the previously victimized target. In the current study, we first determined the repeat and near repeat space-time clustering of solved residential burglaries committed in Edmonton, Alberta, Canada, from 2007 to 2008. The results indicate that solved Edmonton burglaries do cluster together in time and space (i.e., residences within 700 m of a previous burgled target are at an increased risk for a period of 7 days). We also investigated whether repeat and near repeat burglaries in the dataset were more likely than distant burglaries to be committed by the same offender. It was found that serial offending by the same offender offers a viable rationale for much of the repeat and near repeat burglaries committed in Edmonton from 2007 to 2008. The practical implications of these results, as well as some limitations and directions for future research, are discussed.

Prevalence and distribution of carbapenem-resistant Enterobacterales in companion animals: A nationwide study in the United States using commercial laboratory data.

Carbapenem-resistant Enterobacterales (CRE) are a concern in both human and animal medicine globally. Despite extensive research in humans, limited data exist on CRE in companion animals, with a lack of nationwide prevalence estimates. To assess the occurrence and trends of CRE in cats and dogs across the United States by analyzing 4 years of commercial antimicrobial susceptibility testing (AST) data. Between 2019 and 2022, 477 426 ASTs were conducted on Enterobacterales isolates against imipenem. Isolates were derived from 379 598 dogs and 97 828 cats. Animal origin was not disclosed. In this retrospective study, antimicrobial susceptibility test data from IDEXX Laboratories were analyzed. Analysis included resistance estimations to imipenem stratified by sampling site, an assessment of resistance patterns over time and location, and the application of space-time cluster analysis to identify potential outbreaks. Antibiograms were produced for carbapenem-resistant isolates. Susceptibility to imipenem was high, at 98.86%. Temporal analysis indicated stability in susceptibility, with an unexplained reduction in susceptible isolates in June 2019. Spatial analysis identified 2 high-risk clusters along the Western Coast (relative risk [RR]: 23.26; P < .001) and in Texas (RR: 10.72; P < .001) in that month. Three other clusters were found, in Missouri (RR: 39.55; P = .038), Florida (RR: 4.53; P < .001), and New York (RR: 9.20; P < .001). CRE are present at a low prevalence in dogs and cats across the United States. Variations in prevalence across patient-level and environmental factors highlight the need for tailored stewardship programs.

Space and space-time cluster at high risk of lung cancer mortality in the south-central macrozone, Chile (1990-2019)

Space and space-time cluster at high risk of lung cancer mortality in the south-central macrozone, Chile (1990-2019)

Detection of spatial, temporal and spatiotemporal distribution of diarrhea incidence among under-five children in Central Gondar zone, Northwest Ethiopia: a time-series study (2019–2022)

Under-five children’s diarrhea is a significant public health threat and the World Health Organization (WHO) reported it as the second leading cause of children’s death worldwide. In this study area, little is known about the spatiotemporal distribution of under-5 diarrhea incidence. This study was therefore, conducted among all districts in the Central Gondar zone to assess the spatial, temporal, and spatiotemporal variation in diarrhea incidence among under-five children in the Central Gondar zone. The data for children under 5 years of age with diarrhea was obtained from Central Gondar Zone Health Department diarrhea reports from January 2019 to December 2022. All districts were included and geo-coded. The spatial data were created in ArcGIS 10.8.1. Global and local spatial autocorrelation were used to detect hot spots and cold spots. The Poisson model was generated by applying the Kulldorff method in SaTScan™9.6 to analyse the the purely temporal, spatial, and space-time clusters. The study revealed spatial variation of under-5 diarrhea where Gondar City, Gondar Zuria, East Dembia, and Lay Armacho districts were the high-rate spatial clusters during the study period. A year search window for temporal scan statistic identified 01 January 2020-30 December 2021 as risk periods across all districts. Spatiotemporal scan statistics detected high-rate clusters at Gondar City, Gondar Zuria, East Dembia, Lay Armacho, and Alefa between 2019 and 2022. In conclusion, there has been a spatial, temporal, and spatiotemporal variability of under-5 children’s diarrhea in the Central Gondar Zone. Interventional and preventive strategies should be developed and given priority to the areas that has been detected as a hotspot in this study to reduce the mortality and morbidity of under 5 children.

Space–time clusters and co-occurrence of Plasmodium vivax and Plasmodium falciparum malaria in West Bengal, India

BackgroundMalaria, a prominent vector borne disease causing over a million annual cases worldwide, predominantly affects vulnerable populations in the least developed regions. Despite their preventable and treatable nature, malaria remains a global public health concern. In the last decade, India has faced a significant decline in malaria morbidity and mortality. As India pledged to eliminate malaria by 2030, this study examined a decade of surveillance data to uncover space–time clustering and seasonal trends of Plasmodium vivax and Plasmodium falciparum malaria cases in West Bengal.MethodsSeasonal and trend decomposition using Loess (STL) was applied to detect seasonal trend and anomaly of the time series. Univariate and multivariate space–time cluster analysis of both malaria cases were performed at block level using Kulldorff’s space–time scan statistics from April 2011 to March 2021 to detect statistically significant space–time clusters.ResultsFrom the time series decomposition, a clear seasonal pattern is visible for both malaria cases. Statistical analysis indicated considerable high-risk P. vivax clusters, particularly in the northern, central, and lower Gangetic areas. Whereas, P. falciparum was concentrated in the western region with a significant recent transmission towards the lower Gangetic plain. From the multivariate space–time scan statistics, the co-occurrence of both cases were detected with four significant clusters, which signifies the regions experiencing a greater burden of malaria cases.ConclusionsSeasonal trends from the time series decomposition analysis show a gradual decline for both P. vivax and P. falciparum cases in West Bengal. The space–time scan statistics identified high-risk blocks for P. vivax and P. falciparum malaria and its co-occurrence. Both malaria types exhibit significant spatiotemporal variations over the study area. Identifying emerging high-risk areas of P. falciparum malaria over the Gangetic belt indicates the need for more research for its spatial shifting. Addressing the drivers of malaria transmission in these diverse clusters demands regional cooperation and strategic strategies, crucial steps towards overcoming the final obstacles in malaria eradication.

An exploratory study on spatiotemporal clustering of suicide in Korean adolescents

BackgroundAdolescent suicides are more likely to form clusters than those of other age groups. However, the definition of a cluster in the space–time dimension has not been established, neither are the factors contributing to it well known. Therefore, this study aimed to identify space–time clusters in adolescent suicides in Korea and to examine the differences between clustered and non-clustered cases using novel statistical methods.MethodsFrom 2016 to 2020, the dates and locations, including specific addresses from which the latitude and longitude of all student suicides (aged 9–18 years) in Korea were obtained through student suicide reports. Sociodemographic characteristics of the adolescents who died by suicide were collected, and the individual characteristics of each student who died by suicide were reported by teachers using the Strengths and Difficulties Questionnaire (SDQ). Density-Based Spatial Clustering of Applications with Noise (DBSCAN) analysis was used to assess the clustering of suicides.ResultsWe identified 23 clusters through the data analysis of 652 adolescent suicides using DBSCAN. By comparing the size of each cluster, we identified 63 (9.7%) spatiotemporally clustered suicides among adolescents, and the temporal range of these clusters was 7–59 days. The suicide cluster group had a lower economic status than the non-clustered group. There were no significant differences in other characteristics between the two groups.ConclusionThis study has defined the space–time cluster of suicides using a novel statistical method. Our findings suggest that when an adolescent suicide occurs, close monitoring and intervention for approximately 2 months are needed to prevent subsequent suicides. Future research using DBSCAN needs to involve a larger sample of adolescents from various countries to further corroborate these findings.

Spatial and temporal clustering of anti-SARS-CoV-2 antibodies in Illinois household cats, 2021-2023.

This study aimed to evaluate the seroprevalence and spatial and temporal clustering of SARS-CoV-2 antibodies in household cats within 63 counties in Illinois from October 2021 to May 2023. The analysis followed a stepwise approach. First, in a choropleth point map, we illustrated the distribution of county-level seroprevalence of SARS-CoV-2 antibodies. Next, spatial interpolation was used to predict the seroprevalence in counties without recorded data. Global and local clustering methods were used to identify the extent of clustering and the counties with high or low seroprevalence, respectively. Next, temporal, spatial, and space-time scan statistic was used to identify periods and counties with higher-than-expected seroprevalence. In the last step, to identify more distinct areas in counties with high seroprevalence, city-level analysis was conducted to identify temporal and space-time clusters. Among 1,715 samples tested by serological assays, 244 samples (14%) tested positive. Young cats had higher seropositivity than older cats, and the third quarter of the year had the highest odds of seropositivity. Three county-level space-time clusters with higher-than-expected seroprevalence were identified in the northeastern, central-east, and southwest regions of Illinois, occurring between June and October 2022. In the city-level analysis, 2 space-time clusters were identified in Chicago's downtown and the southwestern suburbs of Chicago between June and September 2022. Our results suggest that the high density of humans and cats in large cities such as Chicago, might play a role in the transmission and clustering of SARS-CoV-2. Our study provides an in-depth analysis of SARS-CoV-2 epidemiology in Illinois household cats, which will aid in COVID-19 control and prevention.

Space-time heterogeneity of measles, mumps, and rubella vaccination indicators in children from BrazilHeterogeneidad espaciotemporal de los indicadores de inmunización con la vacuna triple viral en la población infantil de Brasil

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

Clusters of Jail Incarcerations in U.S. Counties: 2010–2018

This study investigates the spatiotemporal variations in jail incarcerations in addition to associations with several risk factors and jail incarceration counts at the county level for the period 2010–2018 in the contiguous USA. The disease surveillance software SaTScanTM was used to identify and test purely spatial and spatiotemporal variations in jail incarceration. Significant spatial and space-time clusters with elevated relative risk for jail incarceration were found in analysis. Additionally, a negative binomial regression model was used to predict jail incarcerations counts based on several covariates and found significant and nonrandom spatial clusters of jail incarceration that are explained after adjusting for these covariates. The results in this study provide useful information on possible associations in geographical areas where jail incarceration rates are higher than expected and demonstrate significant correlations between jail incarceration counts and several covariates. The study and its conclusions provide an epidemiological framework for identifying and addressing geographic patterns of unusually high jail incarceration rates in the United States and provide evidence of appropriate locations to further investigate underlying causes of disproportionate incarceration. Supplementary files for this article are available online.

Space–Time Clustering and Climatic Risk Factors for Lumpy Skin Disease of Cattle in Uttar Pradesh, India, 2022

Lumpy skin disease (LSD), a transboundary infectious disease, negatively impacts cattle health and production. The first LSD outbreaks were reported in India in 2019, and since then, LSD spread to over 15 states, including Uttar Pradesh. This study evaluated LSD cases reported by veterinarians in Uttar Pradesh, India, during 2022. Using scan statistics, Poisson models that accounted for the background cattle population were constructed to identify spatial, temporal, and space–time clusters. A negative binomial regression model was built to assess the impact of temperature and humidity on the incidence rate (IR) of LSD. A total of 112,226 cases across 33 districts were reported in 2022. A purely temporal cluster with higher-than-expected LSD rates was identified between August and October 2022. Several purely spatial clusters were identified in the western part of the state. A primary space–time cluster was detected in west Utter Pradesh between August and October 2022 that overlapped with the spatial clusters. The secondary cluster occurred between September and October 2022 in the eastern part of the state. A rise in humidity (incidence rate ratio (IRR) = 1.39; 95% CI: 1.30–1.49) and temperature (IRR = 1.16; 95% CI: 1.06–1.27) increased the IR of LSD, suggesting a seasonality of the outbreaks. The results of this study can aid animal health authorities in developing effective LSD prevention, surveillance, and control strategies among cattle in India.

Spatiotemporal analysis and forecasting of lumpy skin disease outbreaks in Ethiopia based on retrospective outbreak reports.

Lumpy skin disease is a viral disease that affects cattle belonging to genus Capripoxvirus (Poxviridae) and lead to significant economic losses. The objective of this study was to evaluate the distribution of lumpy skin disease (LSD) outbreaks and predict future patterns based on retrospective outbreak reports in Ethiopia. Data were collected through direct communication with regional laboratories and a hierarchical reporting system from the Peasant Associations to Ministry of Agriculture. Time-series data for the LSD outbreaks were analyzed using classical additive time-series decomposition and STL decomposition. Four models (ARIMA, SARIMA, ETS, STLF) were also used to forecast the number of LSD outbreaks that occurred each month for the years (2021-2025) after the models' accuracy test was performed. Additionally, the space-time permutation model (STP) were also used to study retrospective space-time cluster analysis of LSD outbreaks in Ethiopia. This study examined the geographical and temporal distribution of LSD outbreaks in Ethiopia from 2008 to 2020, reporting a total of 3,256 LSD outbreaks, 14,754 LSD-positive cases, 7,758 deaths, and 289 slaughters. It also covered approximately 68% of Ethiopia's districts, with Oromia reporting the highest LSD outbreaks. In the LSD's temporal distribution, the highest peak was reported following the rainy season in September to December and its lowest peak in the dry months of April and May. Out of the four models tested for forecasting, the SARIMA (3, 0, 0) (2, 1, 0) [12] model performed well for the validation data, while the STLF+Random Walk had a robust prediction for the training data. Thus, the SARIMA and STLF+Random Walk models produced a more accurate forecast of LSD outbreaks between 2020 and 2025. From retrospective Space-Time Cluster Analysis of LSD, eight possible clusters were also identified, with five of them located in central part of Ethiopia. The study's time series and ST-cluster analysis of LSD outbreak data provide valuable insights into the spatial and temporal dynamics of the disease in Ethiopia. These insights can aid in the development of effective strategies to control and prevent the spread of the disease and holds great potential for improving efforts to combat LSD in the country.

Landslides, bedrock incision and human-induced environmental changes in an extremely rapidly formed tropical river gorge

Landslides are hillslope processes controlled by natural changing topographic conditions. Landslides are also influenced by human activities. Yet, understanding the space-time occurrence of landslides and their interactions with these typically long-term natural and short-term human-induced controls remains a key challenge in many regions, especially in tropical environments where data scarcity is commonplace. Here we decipher these dynamic processes in the Ruzizi Gorge located in the Kivu Rift (Central Africa), that is an exceptional geomorphological landmark whose origin is associated with the rerouting of >7000 km2 of drainage area from Lake Kivu during the Holocene. This bedrock river has also seen its landscape disturbed over the past decades by the development of the city of Bukavu (DR Congo). In this study, we combine detailed field observations, historical aerial photographs, archive analysis and satellite imagery to compile a multi-temporal inventory of 385 landslides and constrain their dynamics. We show that extremely high incision rates during the early stage of the formation of the gorge explain the space-time clustering of thousand-year-old large (up to ∼2 km2) landslides, independently from the lithological context. These landslides are currently non-active and poorly eroded. Their deposit areas partly cover the riverbed with boulders, armouring the channel and inhibiting further incision. The landslides that occurred over the last 60 years are shallower slope failures of smaller size and higher mobility. They tend to disappear rather quickly from the landscape, sometimes within a few years. Their distribution is primarily controlled by threshold slopes, lithology, and the past large landslides, the influence of the land use being less pronounced. Overall, the sediment mobilization rates associated with these high frequency landslides significantly outpace the extreme landslide erosion pulse associated with the gorge formation. Our results provide insight on interactions between channel-hillslope coupling and feedbacks among landslide processes and river gorge formation in a unique environment.