Propositionalism without propositions, objectualism without objects

Propositionalism is the view that all intentional states are propositional states, which are states with a propositional content, while objectualism is the view that at least some intentional states are objectual states, which are states with objectual contents, such as objects, properties, and kinds. This paper argues that there are two distinct ways of understanding propositionalism and objectualism: (1) as views about the deep nature of the contents of intentional states, and (2) as views about the superficial character of the contents of intentional states. I argue that we should understand the views in the second way. I also argue that the propositionalism debate is fairly independent from debates over the deep nature of intentionality, and that this has implications for arguments for propositionalism and objectualism from claims about the nature of intentional content. I close with a short discussion of how related points apply to the debate over singular content

Citizen science informs human-tick exposure in the Northeastern United States

Abstract Background Tick-borne disease is the result of spillover of pathogens into the human population. Traditionally, literature has focused on characterization of tick-borne disease pathogens and ticks in their sylvatic cycles. A limited amount of research has focused on human-tick exposure in this system, especially in the Northeastern United States. Human-tick interactions are crucial to consider when assessing the risk of tick-borne disease since a tick bite is required for spillover to occur. Methods Citizen scientists collected ticks from the Northeastern US through a free nationwide program. Submitted ticks were identified to species, stage, and sex. Blacklegged ticks, Ixodes scapularis, were tested for the presence of Borrelia burgdorferi sensu lato (s.l.) and hard-tick relapsing fever Borrelia. Seasonality of exposure and the citizen science activity during tick exposure was recorded by the citizen scientist. A negative binomial model was fit to predict county level CDC Lyme disease cases in 2016 using citizen science Ixodes scapularis submissions, state, and county population as predictor variables. Results A total of 3740 submissions, comprising 4261 ticks, were submitted from the Northeastern US and were reported to be parasitizing humans. Of the three species submitted, blacklegged ticks were the most prevalent followed by American dog ticks and lone star ticks. Submissions peaked in May with the majority of exposure occurring during every-day activities. The most common pathogen in blacklegged ticks was B. burgdorferi s.l. followed by hard-tick relapsing fever Borrelia. Negative binomial model performance was best in New England states followed by Middle Atlantic states. Conclusions Citizen science provides a low-cost and effective methodology for describing the seasonality and characteristics of human-tick exposure. In the Northeastern US, everyday activities were identified as a major mechanism for tick exposure, supporting the role of peri-domestic exposure in tick-borne disease. Citizen science provides a method for broad pathogen and tick surveillance, which is highly related to human disease, allowing for inferences to be made about the epidemiology of tick-borne disease

Predicting the current and future distribution of the western black-legged tick, Ixodes pacificus, across the Western US using citizen science collections.

In the twenty-first century, ticks and tick-borne diseases have expanded their ranges and impact across the US. With this spread, it has become vital to monitor vector and disease distributions, as these shifts have public health implications. Typically, tick-borne disease surveillance (e.g., Lyme disease) is passive and relies on case reports, while disease risk is calculated using active surveillance, where researchers collect ticks from the environment. Case reports provide the basis for estimating the number of cases; however, they provide minimal information on vector population or pathogen dynamics. Active surveillance monitors ticks and sylvatic pathogens at local scales, but it is resource-intensive. As a result, data are often sparse and aggregated across time and space to increase statistical power to model or identify range changes. Engaging public participation in surveillance efforts allows spatially and temporally diverse samples to be collected with minimal effort. These citizen-driven tick collections have the potential to provide a powerful tool for tracking vector and pathogen changes. We used MaxEnt species distribution models to predict the current and future distribution of Ixodes pacificus across the Western US through the use of a nationwide citizen science tick collection program. Here, we present niche models produced through citizen science tick collections over two years. Despite obvious limitations with citizen science collections, the models are consistent with previously-predicted species ranges in California that utilized more than thirty years of traditional surveillance data. Additionally, citizen science allows for an expanded understanding of I. pacificus distribution in Oregon and Washington. With the potential for rapid environmental changes instigated by a burgeoning human population and rapid climate change, the development of tools, concepts, and methodologies that provide rapid, current, and accurate assessment of important ecological qualities will be invaluable for monitoring and predicting disease across time and space

Prevalence of <i>A</i>. <i>phagotcytophilum</i>, <i>Bab</i>. <i>microti</i>, <i>B</i>. <i>burgdorferi</i>, and <i>B</i>. <i>miyamotoi</i> for <i>Ixodes scapularis</i> and <i>I</i>. <i>pacificus</i> ticks by state.

<p>Prevalence of <i>A</i>. <i>phagotcytophilum</i>, <i>Bab</i>. <i>microti</i>, <i>B</i>. <i>burgdorferi</i>, and <i>B</i>. <i>miyamotoi</i> for <i>Ixodes scapularis</i> and <i>I</i>. <i>pacificus</i> ticks by state.</p

County level distribution of <i>Amblyomma</i> spp.

<p>(A), <i>Dermacentor variabilis</i> (B), <i>D</i>. <i>andersoni</i> and <i>D</i>. <i>occidentalis</i> (C), and <i>Rhipicephalus sanguineus</i> (D) identified following submission from citizen scientists.</p

Primer and probe sets used for the detection of tick-borne pathogens in ticks collected from throughout the US.

<p>Primer and probe sets used for the detection of tick-borne pathogens in ticks collected from throughout the US.</p

Using citizen science to describe the prevalence and distribution of tick bite and exposure to tick-borne diseases in the United States - Fig 1

<p>Submissions to the free tick testing program from across the US (A), starting in January 2017 ending in August of 2017 (B).</p

Summary of pathogens observed in ticks submitted by citizen scientists across the US [positives/sample size, (percentage prevalence, 95% CI)].

<p>Summary of pathogens observed in ticks submitted by citizen scientists across the US [positives/sample size, (percentage prevalence, 95% CI)].</p

The county level distribution of <i>I</i>. <i>pacificus</i> and <i>I</i>. <i>scapularis</i> based on location data collected by citizen scientists.

<p>Counties outlined in red did not have previous records according to [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0199644#pone.0199644.ref012" target="_blank">12</a>], no records include travel history of the submitter.</p