Modeling the spatial and seasonal distribution of offshore recreational vessels in the southeast United States.
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ABSTRACT:
SUBMITTER: Montes N
PROVIDER: S-EPMC6261638 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Expanding geographic distribution and increased populations of ticks has resulted in an upsurge of human-tick encounters in the United States (US), leading to an increase in tickborne disease reporting. Limited knowledge of the broadscale spatial range of tick species is heightened by a rapidly changing environment. Therefore, we partnered with the Forest Inventory and Analysis (FIA) program of the Forest Service, U.S. Department of Agriculture and used passive tick surveillance to better understand spatiotemporal variables associated with foresters encountering three tick species (Amblyomma americanum L., Dermacentor variabilis Say, and Ixodes scapularis L.) in the southeastern US. Eight years (2014-2021) of tick encounter data were used to fit environmental niche and generalized linear models to predict where and when ticks are likely to be encountered. Our results indicate temporal and environmental partitioning of the three species. Ixodes scapularis were more likely to be encountered in the autumn and winter seasons and associated with soil organic matter, vegetation indices, evapotranspiration, temperature, and gross primary productivity. By contrast, A. americanum and D. variabilis were more likely to be encountered in spring and summer seasons and associated with elevation, landcover, temperature, dead belowground biomass, vapor pressure, and precipitation. Regions in the southeast least suitable for encountering ticks included the Blue Ridge, Mississippi Alluvial Plain, and the Southern Florida Coastal Plain, whereas suitable regions included the Interior Plateau, Central Appalachians, Ozark Highlands, Boston Mountains, and the Ouachita Mountains. Spatial and temporal patterns of different tick species can inform outdoorsmen and the public on tick avoidance measures, reduce tick populations by managing suitable tick habitats, and monitoring areas with unsuitable tick habitat for potential missed encounters.
| S-EPMC10898775 | biostudies-literature
Project description:The SARS-CoV-2 coronavirus is wreaking havoc globally, yet, as a novel pathogen, knowledge of its biology is still emerging. Climate and seasonality influence the distributions of many diseases, and studies suggest at least some link between SARS-CoV-2 and weather. One such study, building species distribution models (SDMs), predicted SARS-CoV-2 risk may remain concentrated in the Northern Hemisphere, shifting northward in summer months. Others have highlighted issues with SARS-CoV-2 SDMs, notably: the primary niche of the virus is the host it infects, climate may be a weak distributional predictor, global prevalence data have issues, and the virus is not in population equilibrium. While these issues should be considered, we believe climate's relationship with SARS-CoV-2 is still worth exploring, as it may have some impact on the distribution of cases. To further examine if there is a link to climate, we build model projections with raw SARS-CoV-2 case data and population-scaled case data in the USA. The case data were from across March 2020, before large travel restrictions and public health policies were impacting cases across the country. We show that SDMs built from population-scaled case data cannot be distinguished from control models (built from raw human population data), while SDMs built on raw case data fail to predict the known distribution of cases in the U.S. from March. The population-scaled analyses indicate that climate did not play a central role in early U.S. viral distribution and that human population density was likely the primary driver. We do find slightly more population-scaled viral cases in cooler areas. Ultimately, the temporal and geographic constraints on this study mean that we cannot rule out climate as a partial driver of the SARS-CoV-2 distribution. Climate's role on SARS-CoV-2 should continue to be cautiously examined, but at this time we should assume that SARS-CoV-2 will continue to spread anywhere in the U.S. where governmental policy does not prevent spread.
| S-EPMC7594635 | biostudies-literature
Project description:BackgroundPrior to vaccine introduction in 2006, rotavirus was the leading cause of severe diarrhea in children under five years of age in the U.S. Vaccination of infants has led to major reductions in disease burden, a shift in the seasonal peak and the emergence of a biennial pattern of disease. However, rotavirus vaccine coverage has remained relatively low (70-75%) compared to other infant immunizations in the U.S. Part of the reason for this lower coverage is that children whose care is provided by family practitioners (FP) have considerably lower probability of being vaccinated compared to those seen be pediatricians (PE). We used a dynamic transmission model to assess the impact of improving rotavirus vaccine coverage by FP and/or PE on rotavirus gastroenteritis (RVGE) incidence and seasonal patterns.MethodsA deterministic age-structured dynamic model with susceptible, infectious, and recovered compartments (SIRS model) was used to simulate rotavirus transmission and vaccination. We estimated the reduction of RVGE cases by 2 doses of rotavirus vaccine with three vaccination scenarios: (Status Quo: 85% coverage by pediatricians and 45% coverage by family practitioners; Improved FP: 85% coverage by pediatricians and family practitioners; Improved FP+PE: 95% coverage by pediatricians and family practitioners). In addition, we tested the sensitivity of the model to the assumption of random mixing patterns between children visiting pediatricians and children visiting family practitioners.ResultsIn this model, higher vaccine coverage provided by family practitioners and pediatricians leads to lower incidence of severe RVGE cases (23% averted in Improved FP and 57% averted in Improved FP+PE compared to Status Quo) including indirect effects. One critical impact of higher total vaccine coverage is the effect on rotavirus epidemic patterns in the U.S.; the biennial rotavirus epidemic patterns shifted to reduced annual epidemic patterns. Additionally, assortative mixing patterns in children visiting pediatricians and family practitioners amplify the impact of increasing vaccine coverage.ConclusionOther high-income countries that introduced vaccine have not experienced biennial patterns, like the U.S. Our results suggest that increasing overall vaccine coverage to 85% among infants would lead to an overall reduction in incidence with annual epidemic patterns.
| S-EPMC7021296 | biostudies-literature
Project description:In order to contribute to conservation planning efforts for golden eagles (Aquila chrysaetos) in the western U.S., we developed nest site models using >6,500 nest site locations throughout a >3,483,000 km2 area of the western U.S. We developed models for twelve discrete modeling regions, and estimated relative density of nest sites for each region. Cross-validation showed that, in general, models accurately estimated relative nest site densities within regions and sub-regions. Areas estimated to have the highest densities of breeding golden eagles had from 132-2,660 times greater densities compared to the lowest density areas. Observed nest site densities were very similar to those reported from published studies. Large extents of each modeling region consisted of low predicted nest site density, while a small percentage of each modeling region contained disproportionately high nest site density. For example, we estimated that areas with relative nest density values <0.3 represented from 62.8-97.8% ([Formula: see text] = 82.5%) of each modeling area, and those areas contained from 14.7-30.0% ([Formula: see text] = 22.1%) of the nest sites. In contrast, areas with relative nest density values >0.5 represented from 1.0-12.8% ([Formula: see text] = 6.3%) of modeling areas, and those areas contained from 47.7-66.9% ([Formula: see text] = 57.3%) of the nest sites. Our findings have direct application to: 1) large-scale conservation planning efforts, 2) risk analyses for land-use proposals such as recreational trails or wind power development, and 3) identifying mitigation areas to offset the impacts of human disturbance.
| S-EPMC6768475 | biostudies-literature
Project description:Cannabis related online searches are associated with positive attitudes toward medical cannabis, particularly when information is obtained from dispensaries. Since pain is the main reason for medicinal cannabis use, information from dispensary websites has the potential to shape the attitude of pain patients towards cannabis. This is relevant because cannabis has demonstrated efficacy in neuropathic pain with low tetrahydrocannabinol (THC) concentrations (< 5-10%), in contrast to potent cannabis (>15% THC), which is highly rewarded in the recreational realm. The role of CBD in pain is not clear, however it has gained popularity. Thus, we hypothesize that the potency of medical cannabis that is advertised online is similar to the cannabis advertised for recreational purposes, which would potentially create a misconception towards medical cannabis. The current lack of knowledge surrounding advertised potencies in the legal cannabis market limits the ability to generate clear policies regarding online advertising to protect patients that are willing to use cannabis for their condition. Thus, we evaluated the advertised THC and CBD content of cannabis products offered online in dispensaries in the United States to determine products' suitability to medicinal use and compare the strength of products offered in legal medical and recreational programs. We recorded THC and CBD concentrations for all herb cannabis products provided by dispensary websites and compared them between or within states. Four Western states (CA, CO, NM, WA) and five Northeastern states (ME, MA, NH, RI, VT) were included. A total of 8,505 cannabis products across 653 dispensaries were sampled. Despite the clear differences between medicinal and recreational uses of cannabis, the average THC concentration advertised online in medicinal programs was similar (19.2% ±6.2) to recreational programs (21.5% ±6.0) when compared between states with different programs, or between medicinal and recreational programs within the same states (CO or WA). Lower CBD concentrations accompanied higher THC products. The majority of products, regardless of medicinal or recreational programs, were advertised to have >15% THC (70.3% - 91.4% of products). These stated concentrations seem unsuitable for medicinal purposes, particularly for patients with chronic neuropathic pain. Therefore, this information could induce the misconception that high potency cannabis is safe to treat pain. This data is consistent with reports in which THC and CBD in products from legal dispensaries or in nationwide products from the illegal market were actually measured, which indicates that patients consuming these products may be at risk of acute intoxication or long-term side effects. Our study offers grounds to develop policies that help prevent misconceptions toward cannabis and reduce risks in pain patients.
| S-EPMC7098613 | biostudies-literature
Project description:Trivalent inactivated influenza vaccines (IIV3s) protect against 2 A strains and one B lineage; quadrivalent versions (IIV4s) protect against an additional B lineage. The objective was to assess projected health and economic outcomes associated with IIV4 versus IIV3 for preventing seasonal influenza in the US. A cost-effectiveness model was developed to interact with a dynamic transmission model. The transmission model tracked vaccination, influenza cases, infection-spreading interactions, and recovery over 10 y (2012-2022). The cost-effectiveness model estimated influenza-related complications, direct and indirect costs (2013-2014 US$), health outcomes, and cost-effectiveness. Inputs were taken from published/public sources or estimated using regression or calibration. Outcomes were discounted at 3% per year. Scenario analyses tested the reliability of the results. Seasonal vaccination with IIV4 versus IIV3 is predicted to reduce annual influenza cases by 1,973,849 (discounted; 2,325,644 undiscounted), resulting in 12-13% fewer cases and influenza-related complications and deaths. These reductions are predicted to translate into 18,485 more quality-adjusted life years (QALYs) accrued annually for IIV4 versus IIV3. Increased vaccine-related costs ($599 million; 5.7%) are predicted to be more than offset by reduced influenza treatment costs ($699 million; 12.2%), resulting in direct medical cost saving annually ($100 million; 0.6%). Including indirect costs, savings with IIV4 are predicted to be $7.1 billion (5.6%). Scenario analyses predict IIV4 to be cost-saving in all scenarios tested apart from low infectivity, where IIV4 is predicted to be cost-effective. In summary, seasonal influenza vaccination in the US with IIV4 versus IIV3 is predicted to improve health outcomes and reduce costs.
| S-EPMC5360116 | biostudies-literature
Project description:Background:The seasonal incidence of influenza is often approximated as 5%-20%. Methods:We used 2 methods to estimate the seasonal incidence of symptomatic influenza in the United States. First, we made a statistical estimate extrapolated from influenza-associated hospitalization rates for 2010-2011 to 2015-2016, collected as part of national surveillance, covering approximately 9% of the United States, and including the existing mix of vaccinated and unvaccinated persons. Second, we performed a literature search and meta-analysis of published manuscripts that followed cohorts of subjects during 1996-2016 to detect laboratory-confirmed symptomatic influenza among unvaccinated persons; we adjusted this result to the US median vaccination coverage and effectiveness during 2010-2016. Results:The statistical estimate of influenza incidence among all ages ranged from 3.0%-11.3% among seasons, with median values of 8.3% (95% confidence interval [CI], 7.3%-9.7%) for all ages, 9.3% (95% CI, 8.2%-11.1%) for children <18 years, and 8.9% (95% CI, 8.2%-9.9%) for adults 18-64 years. Corresponding values for the meta-analysis were 7.1% (95% CI, 6.1%-8.1%) for all ages, 8.7% (95% CI, 6.6%-10.5%) for children, and 5.1% (95% CI, 3.6%-6.6%) for adults. Conclusions:The 2 approaches produced comparable results for children and persons of all ages. The statistical estimates are more versatile and permit estimation of season-to-season variation. During 2010-2016, the incidence of symptomatic influenza among vaccinated and unvaccinated US residents, including both medically attended and nonattended infections, was approximately 8% and varied from 3% to 11% among seasons.
| S-EPMC5934309 | biostudies-literature
Project description:Seasonal allergies have been associated with mental health problems, though the evidence is still emergent, particularly in the United States. We analyzed data from the National Comorbidity Survey Replication and the National Latino and Asian American Survey (years 2001?2003). Multivariable logistic regression models were used to examine the relations between lifetime allergies and lifetime psychiatric disorders (each disorder in a separate model), adjusting for socio-demographic variables (including region of residence) and tobacco use. Analyses were also stratified to test for effect modification by race and sex. A history of seasonal allergies was associated with greater odds of mood disorders, anxiety disorders, and eating disorders, but not alcohol or substance use disorders, after adjusting for socio-demographic characteristics and tobacco use. The associations between seasonal allergies and mood disorders, substance use disorders, and alcohol use disorders were particularly strong for Latino Americans. The association between seasonal allergies and eating disorders was stronger for men than women. Seasonal allergies are a risk factor for psychiatric disorders. Individuals complaining of seasonal allergies should be screened for early signs of mental health problems and referred to specialized services accordingly.
| S-EPMC6164754 | biostudies-literature
Project description:In addition to serving as vectors of several other human pathogens, the black-legged tick, Ixodes scapularis Say, and western black-legged tick, Ixodes pacificus Cooley and Kohls, are the primary vectors of the spirochete (Borrelia burgdorferi) that causes Lyme disease, the most common vector-borne disease in the United States. Over the past two decades, the geographic range of I. pacificus has changed modestly while, in contrast, the I. scapularis range has expanded substantially, which likely contributes to the concurrent expansion in the distribution of human Lyme disease cases in the Northeastern, North-Central and Mid-Atlantic states. Identifying counties that contain suitable habitat for these ticks that have not yet reported established vector populations can aid in targeting limited vector surveillance resources to areas where tick invasion and potential human risk are likely to occur. We used county-level vector distribution information and ensemble modeling to map the potential distribution of I. scapularis and I. pacificus in the contiguous United States as a function of climate, elevation, and forest cover. Results show that I. pacificus is currently present within much of the range classified by our model as suitable for establishment. In contrast, environmental conditions are suitable for I. scapularis to continue expanding its range into northwestern Minnesota, central and northern Michigan, within the Ohio River Valley, and inland from the southeastern and Gulf coasts. Overall, our ensemble models show suitable habitat for I. scapularis in 441 eastern counties and for I. pacificus in 11 western counties where surveillance records have not yet supported classification of the counties as established.
| S-EPMC5491370 | biostudies-other
Project description:Despite the usefulness of artificial neural networks (ANNs) in the study of various complex problems, ANNs have not been applied for modeling the geographic distribution of tuberculosis (TB) in the US. Likewise, ecological level researches on TB incidence rate at the national level are inadequate for epidemiologic inferences. We collected 278 exploratory variables including environmental and a broad range of socio-economic features for modeling the disease across the continental US. The spatial pattern of the disease distribution was statistically evaluated using the global Moran's I, Getis⁻Ord General G, and local Gi* statistics. Next, we investigated the applicability of multilayer perceptron (MLP) ANN for predicting the disease incidence. To avoid overfitting, L1 regularization was used before developing the models. Predictive performance of the MLP was compared with linear regression for test dataset using root mean square error, mean absolute error, and correlations between model output and ground truth. Results of clustering analysis showed that there is a significant spatial clustering of smoothed TB incidence rate (p < 0.05) and the hotspots were mainly located in the southern and southeastern parts of the country. Among the developed models, single hidden layer MLP had the best test accuracy. Sensitivity analysis of the MLP model showed that immigrant population (proportion), underserved segments of the population, and minimum temperature were among the factors with the strongest contributions. The findings of this study can provide useful insight to health authorities on prioritizing resource allocation to risk-prone areas.
| S-EPMC6338935 | biostudies-literature