Modeling the Geographic Distribution of \u3ci\u3eIxodes scapularis\u3c/i\u3e and \u3ci\u3eIxodes pacificus\u3c/i\u3e (Acari: Ixodidae) in the Contiguous United States

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

“Remoteness was a blessing, but also a potential downfall”: Traditional/Subsistence and store-bought food access in remote Alaska during the COVID-19 pandemic

Abstract Objective: This study employs a strengths-based approach to assess food access in remote Alaska during the COVID-19 pandemic, identifying both the negative consequences of the pandemic on store-bought and subsistence/traditional food access as well as compensatory strategies used. Design: As a part of a larger study on the impacts of COVID-19 on daily life remote Alaska communities, study data presented here were collected through key informant interviews (KIIs) and statewide online surveys from September 21, 2020 to March 31, 2021 among remote Alaska community members. Setting: This study was conducted with residents of remote communities in Alaska, defined as those off of the road system. Remote communities often have small or no grocery stores, and rely on subsistence or traditional sources of food. Participants: KII participants (n=36) were majority female (78%) and Alaska Native (57%). Survey participants (n=615) were also majority female, 25-54 years old, and most had had some post-secondary education or training. Results: Survey and interview data revealed that the pandemic had significant negative impacts on store-bought food access in remote Alaskan communities. Individuals also shared that locally available and wild harvested foods acted as a buffer to some of the loss of access to these store-bought foods, with some people sharing that the harvesting of wild and traditional foods served served as a coping strategy during times of pandemic-related stress. Conclusions: The results from this study demonstrate that the remoteness of some Alaska communities has been both a source of vulnerability and protection in terms food access

Systematic Overestimation of Machine Learning Performance in Neuroimaging Studies of Depression

We currently observe a disconcerting phenomenon in machine learning studies in psychiatry: While we would expect larger samples to yield better results due to the availability of more data, larger machine learning studies consistently show much weaker performance than the numerous small-scale studies. Here, we systematically investigated this effect focusing on one of the most heavily studied questions in the field, namely the classification of patients suffering from Major Depressive Disorder (MDD) and healthy controls. Drawing upon a balanced sample of $N = 1,868$ MDD patients and healthy controls from our recent international Predictive Analytics Competition (PAC), we first trained and tested a classification model on the full dataset which yielded an accuracy of 61%. Next, we mimicked the process by which researchers would draw samples of various sizes ($N=4$ to $N=150$) from the population and showed a strong risk of overestimation. Specifically, for small sample sizes ($N=20$), we observe accuracies of up to 95%. For medium sample sizes ($N=100$) accuracies up to 75% were found. Importantly, further investigation showed that sufficiently large test sets effectively protect against performance overestimation whereas larger datasets per se do not. While these results question the validity of a substantial part of the current literature, we outline the relatively low-cost remedy of larger test sets

Modeling the Geographic Distribution of \u3ci\u3eIxodes scapularis\u3c/i\u3e and \u3ci\u3eIxodes pacificus\u3c/i\u3e (Acari: Ixodidae) in the Contiguous United States

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

Conservation of biodiversity as a strategy for improving human health and well-being

The Earth's ecosystems have been altered by anthropogenic processes, including land use, harvesting populations, species introductions and climate change. These anthropogenic processes greatly alter plant and animal communities, thereby changing transmission of the zoonotic pathogens they carry. Biodiversity conservation may be a potential win-win strategy for maintaining ecosystem health and protecting public health, yet the causal evidence to support this strategy is limited. Evaluating conservation as a viable public health intervention requires answering four questions: (i) Is there a general and causal relationship between biodiversity and pathogen transmission, and if so, which direction is it in? (ii) Does increased pathogen diversity with increased host biodiversity result in an increase in total disease burden? (iii) Do the net benefits of biodiversity conservation to human well-being outweigh the benefits that biodiversity-degrading activities, such as agriculture and resource utilization, provide? (iv) Are biodiversity conservation interventions cost-effective when compared to other options employed in standard public health approaches? Here, we summarize current knowledge on biodiversity-zoonotic disease relationships and outline a research plan to address the gaps in our understanding for each of these four questions. Developing practical and self-sustaining biodiversity conservation interventions will require significant investment in disease ecology research to determine when and where they will be effective.This article is part of the themed issue 'Conservation, biodiversity and infectious disease: scientific evidence and policy implications'

Influence of Deforestation, Logging, and Fire on Malaria in the Brazilian Amazon

Submitted by Anderson Silva ([email protected]) on 2014-11-13T11:28:34Z No. of bitstreams: 1 Influence of Deforestation, Logging, and Fire on Malaria.pdf: 1121927 bytes, checksum: 1dcd40ee5bbfefc40a825b1c597cac33 (MD5)Approved for entry into archive by Anderson Silva ([email protected]) on 2014-11-13T11:28:45Z (GMT) No. of bitstreams: 1 Influence of Deforestation, Logging, and Fire on Malaria.pdf: 1121927 bytes, checksum: 1dcd40ee5bbfefc40a825b1c597cac33 (MD5)Made available in DSpace on 2014-11-13T12:04:40Z (GMT). No. of bitstreams: 1 Influence of Deforestation, Logging, and Fire on Malaria.pdf: 1121927 bytes, checksum: 1dcd40ee5bbfefc40a825b1c597cac33 (MD5) Previous issue date: 2014Nelson Institute. Center for Sustainability and the Global Environment. University of Wisconsin-Madison, Madison, WI, United States of AmericaDepartment of Population Health Sciences. School of Medicine and Public Health. Madison, WI, United States of AmericaFundação Oswaldo Cruz. Instituto de Comunicação e Informação Científica e Tecnológica em Saúde. Rio de Janeiro, RJ, BrasilDepartment of Global Ecology, Carnegie Institution for Science. Stanford University. California, CA, United States of AmericaNelson Institute. Center for Sustainability and the Global Environment. University of Wisconsin-Madison, Madison, WI, United States of America/ Department of Population Health Sciences, School of Medicine and Public Health. Madison, WI, United States of AmericaMalaria is a significant public health threat in the Brazilian Amazon. Previous research has shown that deforestation creates breeding sites for the main malaria vector in Brazil, Anopheles darlingi, but the influence of selective logging, forest fires, and road construction on malaria risk has not been assessed. To understand these impacts, we constructed a negative binomial model of malaria counts at the municipality level controlling for human population and social and environmental risk factors. Both paved and unpaved roadways and fire zones in a municipality increased malaria risk. Within the timber production states where 90% of deforestation has occurred, compared with areas without selective logging, municipalities where 0–7% of the remaining forests were selectively logged had the highest malaria risk (1.72, 95% CI 1.18–2.51), and areas with higher rates of selective logging had the lowest risk (0.39, 95% CI 0.23–0.67). We show that roads, forest fires, and selective logging are previously unrecognized risk factors for malaria in the Brazilian Amazon and highlight the need for regulation and monitoring of sub-canopy forest disturbanc

Top 10 community-identify problems related to wildfire in southcentral Alaska identified through a group ranking process.

Top 10 community-identify problems related to wildfire in southcentral Alaska identified through a group ranking process.</p

Human population and land cover characteristics of municipalities.

<p>Data presented as means ±1 SD.</p><p>Timber production states include Roraima, Pará, Rondônia, Acre, and northern Mato Grosso.</p