Our study aim was to identify high-risk areas of neonatal mortality associated with bacterial sepsis in the state of São Paulo, Southeast Brazil. We used a population-based study applying retrospective spatial scan statistics with data extracted from birth certificates linked to death certificates. All live births from mothers residing in São Paulo State from 2004 to 2020 were included. Spatial analysis using the Poisson model was adopted to scan high-rate clusters of neonatal mortality associated with bacterial sepsis (WHO-ICD10 A32.7, A40, A41, P36, P37.2 in any line of the death certificate). We found a prevalence of neonatal death associated with bacterial sepsis of 2.3/1000 live births. Clusters of high neonatal mortality associated with bacterial sepsis were identified mainly in the southeast region of the state, with four of them appearing as cluster areas for all birth weight categories (<1500 g, 1500 to <2500 g and ≥ 2500 g). The spatial analysis according to the birth weight showed some overlapping in the detected clusters, suggesting shared risk factors that need to be explored. Our study highlights the ongoing challenge of neonatal sepsis in the most developed state of a middle-income country and the importance of employing statistical techniques, including spatial methods, for enhancing surveillance and intervention strategies.

Prospective university students experience substantial academic stressors and psychological vulnerabilities, yet their mental health literacy (MHL) remains inadequately explored. This study investigates four dimensions of MHL – help-seeking behaviors, stigma, knowledge about mental health and understanding of mental illnesses. Besides, Geographic Information System (GIS) techniques are employed to analyze spatial disparities in MHL, which is the first in the context of MHL research. A total of 1,485 students were assessed for sociodemographic characteristics, admission-related variables, health behaviors and family histories of mental health issues. Data were analyzed using SPSS and ArcGIS software. Multivariable linear regression analyses unveiled predictors of the MHL dimensions, with gender, family income, admission test performance, smoking, alcohol and drug use, physical and mental health history, current depression or anxiety and family history of mental health and suicide incidents emerging as common predictors. GIS analysis unraveled notable regional disparities in MHL, particularly in knowledge of mental health and mental illness, with northern and some southern districts displaying higher literacy levels. In conclusion, these findings accentuate significant gender and sociodemographic inequalities in MHL among prospective university students, highlighting the imperative for targeted interventions to enhance MHL and foster mental well-being in this cohort.

During the second half of the first millennium BC, hundreds of hillforts dotted the central Italian Apennines. Often interpreted as ‘proto-towns’, the authors present results of investigations at Monte Santa Croce-Cognolo that challenge this idea. Previous studies identified a small area (<1ha) of occupation and suggested that habitation extended across the whole 18ha site. Combining geophysical and pedestrian survey with remotely sensed data, and local ethnographic accounts, the authors detect little evidence for permanent habitation and instead argue for activities connected with animal husbandry. The results challenge urban-centric interpretations by demonstrating the coexistence of monumental but uninhabited hillforts and urban sites—usually seen across the Mediterranean and Europe.

This study was conducted to provide empirical evidence of geographical variations of neonatal mortality and its associated social determinants with a view to improving neonatal survival at the subnational level in Nigeria. With a combination of spatial analysis and artificial intelligence techniques, this study analysed data from the 2016/2017 Nigeria Multiple Indicator Cluster Survey. The analysis focused on the neonatal period of a weighted national representative population of 30,924 live births delivered five years before the survey commencement. Global Moran’s I index and local indicator of spatial autocorrelation cluster maps were used to determine hot and cold spots. A multilayer perceptron neural network was used to identify the key determinants of neonatal mortality across the states and geopolitical zones in Nigeria. The overall neonatal mortality rate was 38 deaths per 1000 live births. There is evidence of geographic clustering of neonatal mortality across Nigeria (worse in the North-Central and North-West zones), majorly driven by poor maternal access to mass media (which plays a critical role in promoting positive health behaviours), short birth interval, a higher position in a family birth order, and young maternal age at child’s birth. This study highlights the need for a policy shift towards implementing state and region-specific strategies in Nigeria. Gender-responsive, culturally, and regionally appropriate reproductive, maternal, and child health-targeted interventions may address geographical inequity in neonatal survival.

Rock art of the Middle and Upper Orinoco River in South America is characterised by some of the largest and most enigmatic engravings in the world, including snakes exceeding 40m in length. Here, the authors map the geographic distribution of giant snake motifs and assess the visibility of this serpentine imagery within the Orinoco landscape and Indigenous myths. Occupying prominent outcrops that were visible from great distances, the authors argue that the rock art provided physical reference points for cosmogonic myths, acting as border agents that structured the environment and were central to Indigenous placemaking along the rivers of lowland South America.

Reductions in the cost of transporting manufactured goods have been an important element in economic development in the recent past, and previous research suggests that the Roman period in Britain also saw substantial reductions in such costs. The authors investigate how far it is possible to measure changes in transport costs by considering the spatial distributions of pottery from known Roman production locations over time. Their analysis of an extensive database of pottery assemblages is designed to evaluate a series of expectations concerning how reductions in transport costs may have affected such assemblages and their distribution. Results suggest that costs were reduced by a factor of about two, leading to related changes in pottery production, distribution, and consumption over time. The ability to quantify changes in transport costs opens new perspectives for investigating the general determinants of economic development using archaeological data.

Afin de mieux comprendre la distribution géographique des facilitateurs et des obstacles à la participation sociale des Québécois âgés, cette étude visait à documenter l’Indice du potentiel de participation sociale (IPPS) selon les zones métropolitaines, urbaines et rurales. Des analyses de données secondaires, dont l’Enquête transversale sur la santé des collectivités canadiennes, ont permis de développer et de cartographier un indice composé de facteurs environnementaux associés à la participation sociale, pondérés par une analyse factorielle. En zones métropolitaines, l’IPPS était supérieur au centre qu’en périphérie, compte tenu d’une concentration accrue d’aînés et des transports. Bien qu’atténuée, la configuration était similaire en zones urbaines. En zone rurale, un IPPS élevé était associé à une concentration d’aînés et un accès aux ressources accru, sans configuration spatiale. Pour favoriser la participation sociale, l’IPPS soutient que les transports et l’accès aux ressources doivent respectivement être améliorés en périphérie des métropoles et en zone rurale.

HIV-1 molecular surveillance provides a new approach to explore transmission risks and targeted interventions. From January to June 2021, 663 newly reported HIV-1 cases were recruited in Zhaotong City, Yunnan Province, China. The distribution characteristics of HIV-1 subtypes and HIV-1 molecular network were analysed. Of 542 successfully subtyped samples, 12 HIV-1 strains were identified. The main strains were CRF08_BC (47.0%, 255/542), CRF01_AE (17.0%, 92/542), CRF07_BC (17.0%, 92/542), URFs (8.7%, 47/542), and CRF85_BC (6.5%, 35/542). CRF08_BC was commonly detected among Zhaotong natives, illiterates, and non-farmers and was mostly detected in Zhaoyang County. CRF01_AE was frequently detected among married and homosexual individuals and mostly detected in Weixin and Zhenxiong counties. Among the 516 pol sequences, 187 (36.2%) were clustered. Zhaotong natives, individuals aged ≥60 years, and illiterate individuals were more likely to be found in the network. Assortativity analysis showed that individuals were more likely to be genetically associated when stratified by age, education level, occupation, and reporting area. The genetic diversity of HIV-1 reflects the complexity of local HIV epidemics. Molecular network analyses revealed the subpopulations to focus on and the characteristics of the risk networks. The results will help optimise local prevention and control strategies.

The quantity of archaeological data for the fortified hilltop settlements of the Late Intermediate period on the Andean altiplano, called pucaras, varies greatly. Some areas, such as the territory of the Colla Aymara chieftaincy east of Lake Titicaca, are well documented thanks to recent and exhaustive research. Other areas, such as the territories of the Lupacas and the Pacajes, are much less documented. From comparative spatial analyses of satellite images from these two territories, we obtained new data on pucaras, whose characteristics seem to differ from those proposed in the archaeological literature. Through a combination of fieldwork and spatial analysis of 295 pucaras, we identified 252 unpublished sites and propose a new typology comprising four categories. Based on ethnohistoric data and the results of the architectural and geographical analyses, we discuss the possible motivations for building so many pucaras; we suggest that some reasons are of a symbolic nature.

Agritourism and direct-to-consumer sales are increasingly used as diversification strategies to generate additional farm revenue streams. Yet despite their growing importance, the impacts, interactions, and adoption of these strategies remain poorly understood. Here we use univariate and bivariate local Moran’s I statistics to identify agritourism and direct-to-consumer sales hotspots in the United States and a Seemingly-Unrelated-Regression Spatial Durbin Model to examine the association between agritourism and direct farm sales to consumers. We find that agritourism and direct sales reinforce each other within the same county but not consistently across neighboring counties.

Despite advocacy of landscape approaches in cultural resource management (CRM) and critiques of the site concept, CRM data collection methods in the western United States continue to focus on individual archaeological sites as units of observation, analysis, and management. The transect-recording unit (TRU) method strikes a balance between conventional site-based recording methods and site-less survey approaches by dividing survey space into a grid of uniformly sized cells for recording all cultural manifestations observed across a survey area. TRU survey generates site boundaries required by CRM regulations while retaining a fine-grained spatial framework for landscape-level research and management. This article discusses the technical requirements of the TRU system and its potential for improving landscape-level research and management. Advances in digital recording technologies and analysis techniques render the method efficient and effective in identifying cultural resource distributions and characteristics otherwise obscured by conventional approaches. The research and management potential of the TRU system is illustrated through identification and interpretation of precontact foot trails in New Mexico's Tularosa Basin. These trails are essentially invisible during pedestrian survey but are readily identifiable as linear patterns using aggregated landscape-scale TRU survey data from multiple survey projects, providing novel insight into precontact routes of movement and exchange.

This manuscript presents a novel approach to the study of contemporary material culture using digital data. Scholars interested in the materiality of past and contemporary societies have been limited to information derived from assemblages of excavated, collected, or physically observed materials; they have yet to take full advantage of large or complex digital datasets afforded by the internet. To demonstrate the power of this approach and its potential to disrupt our understanding of the material world, we present a study of an ongoing global health crisis, the COVID-19 pandemic. In particular, we focus on face-mask production during the pandemic across the United States in 2020 and 2021. Scraping information on homemade face-mask characteristics at multimonth intervals—including location and materials—we analyze the production of masks and their change over time. We demonstrate that this new methodology, coupled with a sociopolitical examination of mask use according to state policies and politicization, provides an unprecedented avenue to understand the changing distributions and social significances of material culture. Our study of mask making elucidates a clear linkage between partisan politics and decreasing disease mitigation effectiveness. We further reveal how time-averaged asssemblages drown out the political meanings of artifacts otherwise visible with finer temporal resolution.

This paper uses a robust method of spatial epidemiological analysis to assess the spatial growth rate of multiple lineages of SARS-CoV-2 in the local authority areas of England, September 2020–December 2021. Using the genomic surveillance records of the COVID-19 Genomics UK (COG-UK) Consortium, the analysis identifies a substantial (7.6-fold) difference in the average rate of spatial growth of 37 sample lineages, from the slowest (Delta AY.4.3) to the fastest (Omicron BA.1). Spatial growth of the Omicron (B.1.1.529 and BA) variant was found to be 2.81× faster than the Delta (B.1.617.2 and AY) variant and 3.76× faster than the Alpha (B.1.1.7 and Q) variant. In addition to AY.4.2 (a designated variant under investigation, VUI-21OCT-01), three Delta sublineages (AY.43, AY.98 and AY.120) were found to display a statistically faster rate of spatial growth than the parent lineage and would seem to merit further investigation. We suggest that the monitoring of spatial growth rates is a potentially valuable adjunct to outbreak response procedures for emerging SARS-CoV-2 variants in a defined population.

Kansas City, Missouri, became one of the major United States hotspots for COVID-19 due to an increase in the rate of positive COVID-19 test results. Despite the large numbers of positive cases in Kansas City, MO, the spatial-temporal analysis of data has been less investigated. However, it is critical to detect emerging clusters of COVID-19 and enforce control and preventive policies within those clusters. We conducted a prospective Poisson spatial-temporal analysis of Kansas City, MO data to detect significant space-time clusters of COVID-19 positive cases at the zip code level in Kansas City, MO. The analysis focused on daily infected cases in four equal periods of 3 months. We detected temporal patterns of emerging and re-emerging space-time clusters between March 2020 and February 2021. Three statistically significant clusters emerged in the first period, mainly concentrated in downtown. It increased to seven clusters in the second period, spreading across a broader region in downtown and north of Kansas City. In the third period, nine clusters covered large areas of north and downtown Kansas City, MO. Ten clusters were present in the last period, further extending the infection along the State Line Road. The statistical results were communicated with local health officials and provided the necessary guidance for decision-making and allocating resources (e.g., vaccines and testing sites). As more data become available, statistical clustering can be used as a COVID-19 surveillance tool to measure the effects of vaccination.

Historically, access to contraception has been supported in a bipartisan way, best exemplified by consistent congressional funding of Title X—the only federal program specifically focused on providing affordable reproductive health care to American residents. However, in an era of partisan polarization, Title X has become a political and symbolic pawn, in part because of its connection to family planning organizations like Planned Parenthood. The conflicts around Title X highlight the effects of intertwining abortion politics and contraception policy, particularly as they relate to reproductive justice and gendered policy making. Family planning organizations like Planned Parenthood have responded to these battles by bowing out of the Title X network. To what extent have contraception deserts—places characterized by inequitable access to Title X—developed or expanded in response to policy changes related to contraception and reproductive health? What is the demographic makeup of these spaces of inequality? We leverage data from the Office of Population Affairs and the U.S. Census Bureau and use the integrated two-step floating catchment area method to illustrate the effects of a major change in the Title X network in 10 states. Our results reveal the widespread human ramifications of increasing constraints on family planning organizations as a result of quiet but insidious federal bureaucratic rule changes.

Political event data are widely used in studies of political violence. Recent years have seen notable advances in the automated coding of political event data from international news sources. Yet, the validity of machine-coded event data remains disputed, especially in the context of event geolocation. We analyze the frequencies of human- and machine-geocoded event data agreement in relation to an independent (ground truth) source. The events are human rights violations in Colombia. We perform our evaluation for a key, 8-year period of the Colombian conflict and in three 2-year subperiods as well as for a selected set of (non)journalistically remote municipalities. As a complement to this analysis, we estimate spatial probit models based on the three datasets. These models assume Gaussian Markov Random Field error processes; they are constructed using a stochastic partial differential equation and estimated with integrated nested Laplacian approximation. The estimated models tell us whether the three datasets produce comparable predictions, underreport events in relation to the same covariates, and have similar patterns of prediction error. Together the two analyses show that, for this subnational conflict, the machine- and human-geocoded datasets are comparable in terms of external validity but, according to the geostatistical models, produce prediction errors that differ in important respects.