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  1. Abstract Background

    Neglected tropical diseases affect the most vulnerable populations and cause chronic and debilitating disorders. Socioeconomic vulnerability is a well-known and important determinant of neglected tropical diseases. For example, poverty and sanitation could influence parasite transmission. Nevertheless, the quantitative impact of socioeconomic conditions on disease transmission risk remains poorly explored.

    Methods

    This study investigated the role of socioeconomic variables in the predictive capacity of risk models of neglected tropical zoonoses using a decade of epidemiological data (2007–2018) from Brazil. Vector-borne diseases investigated in this study included dengue, malaria, Chagas disease, leishmaniasis, and Brazilian spotted fever, while directly-transmitted zoonotic diseases included schistosomiasis, leptospirosis, and hantaviruses. Environmental and socioeconomic predictors were combined with infectious disease data to build environmental and socioenvironmental sets of ecological niche models and their performances were compared.

    Results

    Socioeconomic variables were found to be as important as environmental variables in influencing the estimated likelihood of disease transmission across large spatial scales. The combination of socioeconomic and environmental variables improved overall model accuracy (or predictive power) by 10% on average (P < 0.01), reaching a maximum of 18% in the case of dengue fever. Gross domestic product was the most important socioeconomic variable (37% relative variable importance, all individual models exhibitedP < 0.00), showing a decreasing relationship with disease indicating poverty as a major factor for disease transmission. Loss of natural vegetation cover between 2008 and 2018 was the most important environmental variable (42% relative variable importance,P < 0.05) among environmental models, exhibiting a decreasing relationship with disease probability, showing that these diseases are especially prevalent in areas where natural ecosystem destruction is on its initial stages and lower when ecosystem destruction is on more advanced stages.

    Conclusions

    Destruction of natural ecosystems coupled with low income explain macro-scale neglected tropical and zoonotic disease probability in Brazil. Addition of socioeconomic variables improves transmission risk forecasts on tandem with environmental variables. Our results highlight that to efficiently address neglected tropical diseases, public health strategies must target both reduction of poverty and cessation of destruction of natural forests and savannas.

     
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  2. Abstract Background

    Climate change presents an imminent threat to almost all biological systems across the globe. In recent years there have been a series of studies showing how changes in climate can impact infectious disease transmission. Many of these publications focus on simulations based on in silico data, shadowing empirical research based on field and laboratory data. A synthesis work of empirical climate change and infectious disease research is still lacking.

    Methods

    We conducted a systemic review of research from 2015 to 2020 period on climate change and infectious diseases to identify major trends and current gaps of research. Literature was sourced from Web of Science and PubMed literary repositories using a key word search, and was reviewed using a delineated inclusion criteria by a team of reviewers.

    Results

    Our review revealed that both taxonomic and geographic biases are present in climate and infectious disease research, specifically with regard to types of disease transmission and localities studied. Empirical investigations on vector-borne diseases associated with mosquitoes comprised the majority of research on the climate change and infectious disease literature. Furthermore, demographic trends in the institutions and individuals published revealed research bias towards research conducted across temperate, high-income countries. We also identified key trends in funding sources for most resent literature and a discrepancy in the gender identities of publishing authors which may reflect current systemic inequities in the scientific field.

    Conclusions

    Future research lines on climate change and infectious diseases should considered diseases of direct transmission (non-vector-borne) and more research effort in the tropics. Inclusion of local research in low- and middle-income countries was generally neglected. Research on climate change and infectious disease has failed to be socially inclusive, geographically balanced, and broad in terms of the disease systems studied, limiting our capacities to better understand the actual effects of climate change on health.

    Graphical abstract 
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  3. Abstract

    Current methods for identifying and predicting infectious disease dynamics in wildlife populations are limited. Pathogen transmission dynamics can be complex, influenced by behavioural interactions between and among hosts, pathogens and their environments. These behaviours may also be influenced directly by observers, with observational research methods being limited to habituated species. Banded mongooseMungos mungoare social, medium size carnivores infected with the novel tuberculosis pathogenMycobacterium mungi. This pathogen is principally transmitted during normal olfactory communication behaviours. Banded mongoose behavioural responses to humans change over the landscape, limiting the use of direct observational approaches in areas where mongoose are threatened and flee.

    The accelerometers in bio‐logging devices have been used previously to identify distinct behaviours in wildlife species, providing a tool to quantifying specific behaviours in ecological studies. We deployed Axy‐5X model accelerometers (TechnoSmArt) on captive mongoose to determine whether accelerometers could be used to identify key mongoose behavioural activities previously associated withM. mungitransmission.

    After two collaring periods, we determined that three distinct behavioural activities could be identified in the accelerometer data: bipedal vertical vigilance, running and scent marking activity; behaviours that have been shown to vary across land type in the banded mongoose.

    Results from this work advance current data analytics and provide modifications to data analysis works flows, updating and expanding upon current methodologies. We also provide preliminary evidence of successful mathematical classification of the target behaviours, supporting the future use of these devices. Methods applied here may allow model estimates ofM. mungitransmission in free‐ranging mongoose to be refined with possible application to other systems where direct observation approaches have limited application.

     
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  4. Abstract The common vampire bat ( Desmodus rotundus ) is a sanguivorous (i.e., blood-eating) bat species distributed in the Americas from northern Mexico southwards to central Chile and Argentina. Desmodus rotundus is one of only three mammal species known to feed exclusively on blood, mainly from domestic mammals, although large wildlife and occasionally humans can also serve as a food source. Blood feeding makes D. rotundus an effective transmissor of pathogens to its prey. Consequently, this species is a common target of culling efforts by various individuals and organizations. Nevertheless, little is known about the historical distribution of D. rotundus . Detailed occurrence data are critical for the accurate assessment of past and current distributions of D. rotundus as part of ecological, biogeographical, and epidemiological research. This article presents a dataset of D. rotundus historical occurrence reports, including >39,000 locality reports across the Americas to facilitate the development of spatiotemporal studies of the species. Data are available at 10.6084/m9.figshare.15025296 . 
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