Correlations between Educational Struggle, Toxic Sites by School District and Demographic Variables, with Geographical Information System Projections.

This correlational study associated data on children enrolled in individualized educational plans in their K-12 schools (IEP) and an algorithm-calculated score of neurotoxins at contaminated sites located in each school district. The study also mapped and projected the correlations using Geographical Information System (GIS) technology. These data were populated in ArcMap 10.5 (a GIS software) for generating maps and data to conduct geospatial analysis. A total of 1 Superfund site and 39 CERCLA sites were identified as contaminated sites for this analysis. The majority of contaminants were heavy metals such as lead, arsenic, mercury, and cadmium. The mean toxic score of all contaminated sites combined was 13.4 (SD 14.4). Correlational analysis between the IEP numbers from each school district and toxic scores from the contaminated school district sites exhibited a positive relationship (F = 23.7, p < 0.0001). Correlations were also seen among higher toxics scores, IEP numbers, and children under the age of 10 (p < 0.00052) as well as higher proportions of black students in areas with high toxics scores (p = 0.0032). Black students were also far more likely to be enrolled in an IEP (p < 0.0001). Household income and poverty percentage in contaminated areas were also correlated (p = 0.0002). Individuals without college degrees were overrepresented in high toxic score school districts (p < 0.0001). The important low socio-economic status indicator of free and reduced lunch programs also correlated with increasing toxic scores (p = 0.0012) and IEP numbers (p = 0.0416). This study emphasizes the need to account for multiple exposures to wholistically appreciate environmental factors contributing to negative health outcomes.

Incorporating resilience when assessing pandemic risk in the Arctic: a case study of Alaska.

The discourse on vulnerability to COVID-19 or any other pandemic is about the susceptibility to the effects of disease outbreaks. Over time, vulnerability has been assessed through various indices calculated using a confluence of societal factors. However, categorising Arctic communities, without considering their socioeconomic, cultural and demographic uniqueness, into the high and low continuum of vulnerability using universal indicators will undoubtedly result in the underestimation of the communities' capacity to withstand and recover from pandemic exposure. By recognising vulnerability and resilience as two separate but interrelated dimensions, this study reviews the Arctic communities' ability to cope with pandemic risks. In particular, we have developed a pandemic vulnerability-resilience framework for Alaska to examine the potential community-level risks of COVID-19 or future pandemics. Based on the combined assessment of the vulnerability and resilience indices, we found that not all highly vulnerable census areas and boroughs had experienced COVID-19 epidemiological outcomes with similar severity. The more resilient a census area or borough is, the lower the cumulative death per 100 000 and case fatality ratio in that area. The insight that pandemic risks are the result of the interaction between vulnerability and resilience could help public officials and concerned parties to accurately identify the populations and communities at most risk or with the greatest need, which, in turn, helps in the efficient allocation of resources and services before, during and after a pandemic. A resilience-vulnerability-focused approach described in this paper can be applied to assess the potential effect of COVID-19 and similar future health crises in remote regions or regions with large Indigenous populations in other parts of the world.

Regional geographies and public health lessons of the COVID-19 pandemic in the Arctic.

Objectives: This study examines the COVID-19 pandemic's spatiotemporal dynamics in 52 sub-regions in eight Arctic states. This study further investigates the potential impact of early vaccination coverage on subsequent COVID-19 outcomes within these regions, potentially revealing public health insights of global significance. Methods: We assessed the outcomes of the COVID-19 pandemic in Arctic sub-regions using three key epidemiological variables: confirmed cases, confirmed deaths, and case fatality ratio (CFR), along with vaccination rates to evaluate the effectiveness of the early vaccination campaign on the later dynamics of COVID-19 outcomes in these regions. Results: From February 2020 to February 2023, the Arctic experienced five distinct waves of COVID-19 infections and fatalities. However, most Arctic regions consistently maintained Case Fatality Ratios (CFRs) below their respective national levels throughout these waves. Further, the regression analysis indicated that the impact of initial vaccination coverage on subsequent cumulative mortality rates and Case Fatality Ratio (CFR) was inverse and statistically significant. A common trend was the delayed onset of the pandemic in the Arctic due to its remoteness. A few regions, including Greenland, Iceland, the Faroe Islands, Northern Canada, Finland, and Norway, experienced isolated spikes in cases at the beginning of the pandemic with minimal or no fatalities. In contrast, Alaska, Northern Sweden, and Russia had generally high death rates, with surges in cases and fatalities. Conclusion: Analyzing COVID-19 data from 52 Arctic subregions shows significant spatial and temporal variations in the pandemic's severity. Greenland, Iceland, the Faroe Islands, Northern Canada, Finland, and Norway exemplify successful pandemic management models characterized by low cases and deaths. These outcomes can be attributed to successful vaccination campaigns, and proactive public health initiatives along the delayed onset of the pandemic, which reduced the impact of COVID-19, given structural and population vulnerabilities. Thus, the Arctic experience of COVID-19 informs preparedness for future pandemic-like public health emergencies in remote regions and marginalized communities worldwide that share similar contexts.

The second year of pandemic in the Arctic: examining spatiotemporal dynamics of the COVID-19 "Delta wave" in Arctic regions in 2021.

The second year of the COVID-19 pandemic in the Arctic was dominated by the Delta wave that primarily lasted between July and December 2021 with varied epidemiological outcomes. An analysis of the Arctic's subnational COVID-19 data revealed a massive increase in cases and deaths across all its jurisdictions but at varying time periods. However, the case fatality ratio (CFR) in most Arctic regions did not rise dramatically and was below national levels (except in Northern Russia). Based on the spatiotemporal patterns of the Delta outbreak, we identified four types of pandemic waves across Arctic regions: Tsunami (Greenland, Iceland, Faroe Islands, Northern Norway, Northern Finland, and Northern Canada), Superstorm (Alaska), Tidal wave (Northern Russia), and Protracted Wave (Northern Sweden). These regionally varied COVID-19 epidemiological dynamics are likely attributable to the inconsistency in implementing public health prevention measures, geographical isolation, and varying vaccination rates. A lesson remote and Indigenous communities can learn from the Arctic is that the three-prong (delay-prepare-respond) approach could be a tool in curtailing the impact of COVID-19 or future pandemics. This article is motivated by previous research that examined the first and second waves of the pandemic in the Arctic. Data are available at https://arctic.uni.edu/arctic-covid-19.

The "second wave" of the COVID-19 pandemic in the Arctic: regional and temporal dynamics.

This article focuses on the "second wave" of the COVID-19 pandemic in the Arctic and examines spatiotemporal patterns between July 2020 and January 2021. We analyse available COVID-19 data at the regional (subnational) level to elucidate patterns and typology of Arctic regions with respect to the COVID-19 pandemic. This article builds upon our previous research that examined the early phase of the COVID-19 pandemic between February and July 2020. The pandemic's "second wave" observed in the Arctic between September 2020 and January 2021 was severe in terms of COVID-19 infections and fatalities, having particularly strong impacts in Alaska, Northern Russia and Northern Sweden. Based on the spatiotemporal patterns of the "second wave" dynamics, we identified 5 types of the pandemic across regions: Shockwaves (Iceland, Faroe Islands, Northern Norway, and Northern Finland), Protracted Waves (Northern Sweden), Tidal Waves (Northern Russia), Tsunami Waves (Alaska), and Isolated Splashes (Northern Canada and Greenland). Although data limitations and gaps persist, monitoring of COVID-19 is critical for developing a proper understanding of the pandemic in order to develop informed and effective responses to the current crisis and possible future pandemics in the Arctic. Data used in this paper are available at https://arctic.uni.edu/arctic-covid-19.

Spatiotemporal dynamics of the COVID-19 pandemic in the arctic: early data and emerging trends.

Since February 2020 the COVID-19 pandemic has been unfolding in the Arctic, placing many communities at risk due to remoteness, limited healthcare options, underlying health issues and other compounding factors. Preliminary analysis of available COVID-19 data in the Arctic at the regional (subnational) level suggests that COVID-19 infections and mortality were highly variable, but generally remained below respective national levels. Based on the trends and magnitude of the pandemic through July, we classify Arctic regions into four groups: Iceland, Faroe Islands, Northern Norway, and Northern Finland with elevated early incidence rates, but where strict quarantines and other measures promptly curtailed the pandemic; Northern Sweden and Alaska, where the initial wave of infections persisted amid weak (Sweden) or variable (Alaska) quarantine measures; Northern Russia characterised by the late start and subsequent steep growth of COVID-19 cases and fatalities and multiple outbreaks; and Northern Canada and Greenland with no significant proliferation of the pandemic. Despite limitations in available data, further efforts to track and analyse the pandemic at the pan-Arctic, regional and local scales are crucial. This includes understanding of the COVID-19 patterns, mortality and morbidity, the relationships with public-health conditions, socioeconomic characteristics, policies, and experiences of the Indigenous Peoples. Data used in this paper are available at https://arctic.uni.edu/arctic-covid-19.

Landscape, demographic and climatic associations with human West Nile virus occurrence regionally in 2012 in the United States of America.

After several years of low West Nile virus (WNV) occurrence in the United States of America (USA), 2012 witnessed large outbreaks in several parts of the country. In order to understand the outbreak dynamics, spatial clustering and landscape, demographic and climatic associations with WNV occurrence were investigated at a regional level in the USA. Previous research has demonstrated that there are a handful of prominent WNV mosquito vectors with varying ecological requirements responsible for WNV transmission in the USA. Published range maps of these important vectors were georeferenced and used to define eight functional ecological regions in the coterminous USA. The number of human WNV cases and human populations by county were attained in order to calculate a WNV rate for each county in 2012. Additionally, a binary value (high/low) was calculated for each county based on whether the county WNV rate was above or below the rate for the region it fell in. Global Moran's I and Anselin Local Moran's I statistics of spatial association were used per region to examine and visualize clustering of the WNV rate and the high/low rating. Spatial data on landscape, demographic and climatic variables were compiled and derived from a variety of sources and then investigated in relation to human WNV using both Spearman rho correlation coefficients and Poisson regression models. Findings demonstrated significant spatial clustering of WNV and substantial inter-regional differences in relationships between WNV occurrence and landscape, demographic and climatically related variables. The regional associations were consistent with the ecologies of the dominant vectors for those regions. The large outbreak in the Southeast region was preceded by higher than normal winter and spring precipitation followed by dry and hot conditions in the summer.

National and regional associations between human West Nile virus incidence and demographic, landscape, and land use conditions in the coterminous United States.

The incidence of human West Nile virus (WNV) varies spatially and temporally and is influenced by a wide range of biotic and abiotic factors. There are numerous important vector species, with variable geographic ranges and ecologies, considered crucial to the transmission of WNV in the coterminous United States. To date there has been a lack of a systematic investigation in the United States, at a regional scale, of the wide variety of landscape, land use, and demographic influences on WNV incidence. In this study, we use published vector species distribution maps, as well as prominent landscape features, to define six distinct regions of the coterminous United States. We relate data on demographic, landscape, and land use conditions to the incidence of human WNV by region recorded at county level in the coterminous United States from 2002-2009. The observed relationships varied by region with the Great Plains, Northwest, and Southwest regions showing high WNV incidence associated with rural irrigated landscapes, indicating the importance of Culex tarsalis as the primary vector. In the Southeast, the percent of the population in poverty was positively associated with high WNV incidence, potentially indicating the quality of housing in relation to the vector Culex quinquefasciatus, a mosquito that often feeds indoors. The Northeast region human WNV incidence was positively associated with agricultural landscapes, potentially implying the importance of Culex restuans in a region generally thought of as being dominated by Culex pipiens transmission. There was strong spatial autocorrelation in most of the regions, but with a spatial autologistic term accounted for in binary logistic regression models, there were significant landscape, land use, and demographic covariates for each region.

Ecological niche modeling of potential West Nile virus vector mosquito species in Iowa.

Ecological niche modeling (ENM) algorithms, Maximum Entropy Species Distribution Modeling (Maxent) and Genetic Algorithm for Rule-set Prediction (GARP), were used to develop models in Iowa for three species of mosquito - two significant, extant West Nile virus (WNV) vectors (Culex pipiens L and Culex tarsalis Coquillett (Diptera: Culicidae)), and the nuisance mosquito, Aedes vexans Meigen (Diptera: Culicidae), a potential WNV bridge vector. Occurrence data for the three mosquito species from a state-wide arbovirus surveillance program were used in combination with climatic and landscape layers. Maxent successfully created more appropriate niche models with greater accuracy than GARP. The three Maxent species' models were combined and the average values were statistically compared to human WNV incidence at the census block group level. The results showed that the Maxent-modeled species' niches averaged together were a useful indicator of WNV human incidence in the state of Iowa. This simple method for creating probability distribution maps proved useful for understanding WNV dynamics and could be applied to the study of other vector-borne diseases.

Spatio-temporal cluster analysis of county-based human West Nile virus incidence in the continental United States.

BACKGROUND: West Nile virus (WNV) is a vector-borne illness that can severely affect human health. After introduction on the East Coast in 1999, the virus quickly spread and became established across the continental United States. However, there have been significant variations in levels of human WNV incidence spatially and temporally. In order to quantify these variations, we used Kulldorff's spatial scan statistic and Anselin's Local Moran's I statistic to uncover spatial clustering of human WNV incidence at the county level in the continental United States from 2002-2008. These two methods were applied with varying analysis thresholds in order to evaluate sensitivity of clusters identified. RESULTS: The spatial scan and Local Moran's I statistics revealed several consistent, important clusters or hot-spots with significant year-to-year variation. In 2002, before the pathogen had spread throughout the country, there were significant regional clusters in the upper Midwest and in Louisiana and Mississippi. The largest and most consistent area of clustering throughout the study period was in the Northern Great Plains region including large portions of Nebraska, South Dakota, and North Dakota, and significant sections of Colorado, Wyoming, and Montana. In 2006, a very strong cluster centered in southwest Idaho was prominent. Both the spatial scan statistic and the Local Moran's I statistic were sensitive to the choice of input parameters. CONCLUSION: Significant spatial clustering of human WNV incidence has been demonstrated in the continental United States from 2002-2008. The two techniques were not always consistent in the location and size of clusters identified. Although there was significant inter-annual variation, consistent areas of clustering, with the most persistent and evident being in the Northern Great Plains, were demonstrated. Given the wide variety of mosquito species responsible and the environmental conditions they require, further spatio-temporal clustering analyses on a regional level is warranted.

Landscape, demographic, entomological, and climatic associations with human disease incidence of West Nile virus in the state of Iowa, USA.

BACKGROUND: West Nile virus (WNV) emerged as a threat to public and veterinary health in the Midwest United States in 2001 and continues to cause significant morbidity and mortality annually. To investigate biotic and abiotic factors associated with disease incidence, cases of reported human disease caused by West Nile virus (WNV) in the state of Iowa were aggregated by census block groups in Iowa for the years 2002-2006. Spatially explicit data on landscape, demographic, and climatic conditions were collated and analyzed by census block groups. Statistical tests of differences between means and distributions of landscape, demographic, and climatic variables for census block groups with and without WNV disease incidence were carried out. Entomological data from Iowa were considered at the state level to add context to the potential ecological events taking place. RESULTS: Numerous statistically significant differences were shown in the means and distributions of various landscape and demographic variables for census block groups with and without WNV disease incidence. Census block groups with WNV disease incidence had significantly lower population densities than those without. Landscape variables showing differences included stream density, road density, land cover compositions, presence of irrigation, and presence of animal feeding operations. Statistically significant differences in the annual means of precipitations, dew point, and minimum temperature for both the year of WNV disease incidence and the prior year, were detected in at least one year of the analysis for each parameter. However, the differences were not consistent between years. CONCLUSION: The analysis of human WNV disease incidence by census block groups in Iowa demonstrated unique landscape, demographic, and climatic associations. Our results indicate that multiple ecological WNV transmission dynamics are most likely taking place in Iowa. In 2003 and 2006, drier conditions were associated with WNV disease incidence. In a significant novel finding, rural agricultural settings were shown to be strongly associated with human WNV disease incidence in Iowa.

Spatiotemporal investigation of adult mosquito (Diptera: Culicidae) populations in an eastern Iowa county, USA.

Landscape and climatic factors regulate distributions of mosquitoes (Diptera: Culicidae) over time and space. The anthropogenic control of mosquito populations is often carried out at a local administrative scale, and it is applied based on the relevant agency's experiential knowledge rather than systematic analysis of spatial and temporal data. To address this shortcoming, a spatial and temporal analysis of landscape and climatic parameters in relation to mosquito populations in Black Hawk County, IA, USA, has been carried out. Adult mosquito sampling took place using CDC light traps from May to August 2003 in representative landscapes. Mosquitoes were identified to species level with Aedes trivittatus (Coquillet) and Aedes vexans (Meigen) dominating the collection totals. The best publicly available spatial data on landscape and demographic attributes were collated and included land cover, human census, soils, floodplain, elevation, wetlands, hydrography, roads, and vegetation indices derived from satellite imagery. Spatial processing was carried out to organize landscape attributes for statistical comparison with abundance data from the potentially important West Nile virus (family Flaviviridae, genus Flavivirus, WNV) vector species Ae. vexans and Ae. trivittatus. Landscape parameters shown to be significantly correlated with mosquito counts included soil hydrological properties, presence in floodplain, wetland areas, and deciduous and bottomland forest cover. Data on temperature and precipitation were used to investigate the climatic influence on the temporal occurrence of mosquito population abundances. Late spring rain provided ample moisture for mosquito development, but low temperatures delayed widespread emergence of Ae. trivittatus and Ae. vexans until June 2003. Landscape and climatic impacts on adult mosquito population distributions were demonstrated, and these results could form the basis for the development of a spatiotemporal modeling framework that would inform anthropogenic mosquito control anld vector-borne disease surveillance. A qualitative discussion concerning Culex pipiens (L.) and Culex restuans Theobald is included.