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Title: The influence of vector‐borne disease on human history: socio‐ecological mechanisms
Abstract

Vector‐borne diseases (VBDs) are embedded within complex socio‐ecological systems. While research has traditionally focused on the direct effects of VBDs on human morbidity and mortality, it is increasingly clear that their impacts are much more pervasive. VBDs are dynamically linked to feedbacks between environmental conditions, vector ecology, disease burden, and societal responses that drive transmission. As a result, VBDs have had profound influence on human history. Mechanisms include: (1) killing or debilitating large numbers of people, with demographic and population‐level impacts; (2) differentially affecting populations based on prior history of disease exposure, immunity, and resistance; (3) being weaponised to promote or justify hierarchies of power, colonialism, racism, classism and sexism; (4) catalysing changes in ideas, institutions, infrastructure, technologies and social practices in efforts to control disease outbreaks; and (5) changing human relationships with the land and environment. We use historical and archaeological evidence interpreted through an ecological lens to illustrate how VBDs have shaped society and culture, focusing on case studies from four pertinent VBDs: plague, malaria, yellow fever and trypanosomiasis. By comparing across diseases, time periods and geographies, we highlight the enormous scope and variety of mechanisms by which VBDs have influenced human history.

 
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Award ID(s):
2011147 2011179 2024383
NSF-PAR ID:
10372462
Author(s) / Creator(s):
 ;  ;  ;  ;  ;  ;  ;  ;  ;  ;  ;  ;  ;  ;  ;  ;  ;  ;  ;  more » ;  ;  ;  ;  ;  ;  ;  ;  ;  ;  ;  ; « less
Publisher / Repository:
Wiley-Blackwell
Date Published:
Journal Name:
Ecology Letters
Volume:
24
Issue:
4
ISSN:
1461-023X
Format(s):
Medium: X Size: p. 829-846
Size(s):
["p. 829-846"]
Sponsoring Org:
National Science Foundation
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  1. Abstract

    Understanding seasonal patterns of activity, or phenology, of vector species is fundamental to determining seasonality of disease risk and epidemics of vector‐borne disease. Spatiotemporal variation in abiotic conditions can influence variation in phenological patterns and life history events, which can dramatically influence the ecological role and human impact of a species. For arthropod vectors of human diseases such as ticks, these phenological patterns determine human exposure risk, yet how abiotic conditions interact to determine suitable conditions for host‐seeking of vector species is difficult to disentangle.

    Here, we use MaxEnt to model spatial patterns and differences in host‐seeking phenology of the western blacklegged tick (Ixodes pacificus) in California using spatially and temporally refined adult tick occurrence data and similarly refined climate and environmental data. We empirically validate the model using phenological data from field studies conducted at sites across California's latitudinal gradient.

    We find adult tick host‐seeking activity varies substantially throughout the year, as well as across the large latitudinal gradient in the state. Suitable conditions for host‐seeking are found earlier in fall and later in the spring in northern than in southern California. These seasonal patterns are primarily associated with monthly precipitation, minimum winter temperature, and winter precipitation, with maximum monthly temperature possibly playing a more prominent role in limiting host‐seeking activity earlier in the spring in southern than northern California.

    Synthesis and applications. Modelling the seasonal activity of the western blacklegged tick, we find both a longer window for host‐feeding and more protracted risk of human exposure to this vector species in northern than southern California. We further identify key environmental factors associated with these patterns, including precipitation and temperature that are otherwise challenging to elucidate in field and laboratory studies over large spatial scales. Moreover, we illustrate how species distribution models, in combination with temporally refined species occurrence and environmental data, can be used to investigate environmental factors predictive of geographic variation in seasonality or phenology of vector species. This produces not only novel ecological insight, but key information for public health practitioners in managing vector‐borne disease transmission and targeting public outreach and interventions.

     
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  2. PLEASE CONTACT AUTHORS IF YOU CONTRIBUTE AND WOULD LIKE TO BE LISTED AS A CO-AUTHOR. (this message will be removed some time weeks/months after the first publication)

    Terrestrial Parasite Tracker indexed biotic interactions and review summary.

    The Terrestrial Parasite Tracker (TPT) project began in 2019 and is funded by the National Science foundation to mobilize data from vector and ectoparasite collections to data aggregators (e.g., iDigBio, GBIF) to help build a comprehensive picture of arthropod host-association evolution, distributions, and the ecological interactions of disease vectors which will assist scientists, educators, land managers, and policy makers. Arthropod parasites often are important to human and wildlife health and safety as vectors of pathogens, and it is critical to digitize these specimens so that they, and their biotic interaction data, will be available to help understand and predict the spread of human and wildlife disease.

    This data publication contains versioned TPT associated datasets and related data products that were tracked, reviewed and indexed by Global Biotic Interactions (GloBI) and associated tools. GloBI provides open access to finding species interaction data (e.g., predator-prey, pollinator-plant, pathogen-host, parasite-host) by combining existing open datasets using open source software.

    If you have questions or comments about this publication, please open an issue at https://github.com/ParasiteTracker/tpt-reporting or contact the authors by email.

    Funding:
    The creation of this archive was made possible by the National Science Foundation award "Collaborative Research: Digitization TCN: Digitizing collections to trace parasite-host associations and predict the spread of vector-borne disease," Award numbers DBI:1901932 and DBI:1901926

    References:
    Jorrit H. Poelen, James D. Simons and Chris J. Mungall. (2014). Global Biotic Interactions: An open infrastructure to share and analyze species-interaction datasets. Ecological Informatics. https://doi.org/10.1016/j.ecoinf.2014.08.005.

    GloBI Data Review Report

    Datasets under review:
     - University of Michigan Museum of Zoology Insect Division. Full Database Export 2020-11-20 provided by Erika Tucker and Barry Oconner. accessed via https://github.com/EMTuckerLabUMMZ/ummzi/archive/6731357a377e9c2748fc931faa2ff3dc0ce3ea7a.zip on 2022-06-24T14:02:48.801Z
     - Academy of Natural Sciences Entomology Collection for the Parasite Tracker Project accessed via https://github.com/globalbioticinteractions/ansp-para/archive/5e6592ad09ec89ba7958266ad71ec9d5d21d1a44.zip on 2022-06-24T14:04:22.091Z
     - Bernice Pauahi Bishop Museum, J. Linsley Gressitt Center for Research in Entomology accessed via https://github.com/globalbioticinteractions/bpbm-ent/archive/c085398dddd36f8a1169b9cf57de2a572229341b.zip on 2022-06-24T14:04:37.692Z
     - Texas A&M University, Biodiversity Teaching and Research Collections accessed via https://github.com/globalbioticinteractions/brtc-para/archive/f0a718145b05ed484c4d88947ff712d5f6395446.zip on 2022-06-24T14:06:40.154Z
     - Brigham Young University Arthropod Museum accessed via https://github.com/globalbioticinteractions/byu-byuc/archive/4a609ac6a9a03425e2720b6cdebca6438488f029.zip on 2022-06-24T14:06:51.420Z
     - California Academy of Sciences Entomology accessed via https://github.com/globalbioticinteractions/cas-ent/archive/562aea232ec74ab615f771239451e57b057dc7c0.zip on 2022-06-24T14:07:16.371Z
     - Clemson University Arthropod Collection accessed via https://github.com/globalbioticinteractions/cu-cuac/archive/6cdcbbaa4f7cec8e1eac705be3a999bc5259e00f.zip on 2022-06-24T14:07:40.925Z
     - Denver Museum of Nature and Science (DMNS) Parasite specimens (DMNS:Para) accessed via https://github.com/globalbioticinteractions/dmns-para/archive/a037beb816226eb8196533489ee5f98a6dfda452.zip on 2022-06-24T14:08:00.730Z
     - Field Museum of Natural History IPT accessed via https://github.com/globalbioticinteractions/fmnh/archive/6bfc1b7e46140e93f5561c4e837826204adb3c2f.zip on 2022-06-24T14:18:51.995Z
     - Illinois Natural History Survey Insect Collection accessed via https://github.com/globalbioticinteractions/inhs-insects/archive/38692496f590577074c7cecf8ea37f85d0594ae1.zip on 2022-06-24T14:19:37.563Z
     - UMSP / University of Minnesota / University of Minnesota Insect Collection accessed via https://github.com/globalbioticinteractions/min-umsp/archive/3f1b9d32f947dcb80b9aaab50523e097f0e8776e.zip on 2022-06-24T14:20:27.232Z
     - Milwaukee Public Museum Biological Collections Data Portal accessed via https://github.com/globalbioticinteractions/mpm/archive/9f44e99c49ec5aba3f8592cfced07c38d3223dcd.zip on 2022-06-24T14:20:46.185Z
     - Museum for Southern Biology (MSB) Parasite Collection accessed via https://github.com/globalbioticinteractions/msb-para/archive/178a0b7aa0a8e14b3fe953e770703fe331eadacc.zip on 2022-06-24T15:16:07.223Z
     - The Albert J. Cook Arthropod Research Collection accessed via https://github.com/globalbioticinteractions/msu-msuc/archive/38960906380443bd8108c9e44aeff4590d8d0b50.zip on 2022-06-24T16:09:40.702Z
     - Ohio State University Acarology Laboratory accessed via https://github.com/globalbioticinteractions/osal-ar/archive/876269d66a6a94175dbb6b9a604897f8032b93dd.zip on 2022-06-24T16:10:00.281Z
     - Frost Entomological Museum, Pennsylvania State University accessed via https://github.com/globalbioticinteractions/psuc-ento/archive/30b1f96619a6e9f10da18b42fb93ff22cc4f72e2.zip on 2022-06-24T16:10:07.741Z
     - Purdue Entomological Research Collection accessed via https://github.com/globalbioticinteractions/pu-perc/archive/e0909a7ca0a8df5effccb288ba64b28141e388ba.zip on 2022-06-24T16:10:26.654Z
     - Texas A&M University Insect Collection accessed via https://github.com/globalbioticinteractions/tamuic-ent/archive/f261a8c192021408da67c39626a4aac56e3bac41.zip on 2022-06-24T16:10:58.496Z
     - University of California Santa Barbara Invertebrate Zoology Collection accessed via https://github.com/globalbioticinteractions/ucsb-izc/archive/825678ad02df93f6d4469f9d8b7cc30151b9aa45.zip on 2022-06-24T16:12:29.854Z
     - University of Hawaii Insect Museum accessed via https://github.com/globalbioticinteractions/uhim/archive/53fa790309e48f25685e41ded78ce6a51bafde76.zip on 2022-06-24T16:12:41.408Z
     - University of New Hampshire Collection of Insects and other Arthropods UNHC-UNHC accessed via https://github.com/globalbioticinteractions/unhc/archive/f72575a72edda8a4e6126de79b4681b25593d434.zip on 2022-06-24T16:12:59.500Z
     - Scott L. Gardner and Gabor R. Racz (2021). University of Nebraska State Museum - Parasitology. Harold W. Manter Laboratory of Parasitology. University of Nebraska State Museum. accessed via https://github.com/globalbioticinteractions/unl-nsm/archive/6bcd8aec22e4309b7f4e8be1afe8191d391e73c6.zip on 2022-06-24T16:13:06.914Z
     - Data were obtained from specimens belonging to the United States National Museum of Natural History (USNM), Smithsonian Institution, Washington DC and digitized by the Walter Reed Biosystematics Unit (WRBU). accessed via https://github.com/globalbioticinteractions/usnmentflea/archive/ce5cb1ed2bbc13ee10062b6f75a158fd465ce9bb.zip on 2022-06-24T16:13:38.013Z
     - US National Museum of Natural History Ixodes Records accessed via https://github.com/globalbioticinteractions/usnm-ixodes/archive/c5fcd5f34ce412002783544afb628a33db7f47a6.zip on 2022-06-24T16:13:45.666Z
     - Price Institute of Parasite Research, School of Biological Sciences, University of Utah accessed via https://github.com/globalbioticinteractions/utah-piper/archive/43da8db550b5776c1e3d17803831c696fe9b8285.zip on 2022-06-24T16:13:54.724Z
     - University of Wisconsin Stevens Point, Stephen J. Taft Parasitological Collection accessed via https://github.com/globalbioticinteractions/uwsp-para/archive/f9d0d52cd671731c7f002325e84187979bca4a5b.zip on 2022-06-24T16:14:04.745Z
     - Giraldo-Calderón, G. I., Emrich, S. J., MacCallum, R. M., Maslen, G., Dialynas, E., Topalis, P., … Lawson, D. (2015). VectorBase: an updated bioinformatics resource for invertebrate vectors and other organisms related with human diseases. Nucleic acids research, 43(Database issue), D707–D713. doi:10.1093/nar/gku1117. accessed via https://github.com/globalbioticinteractions/vectorbase/archive/00d6285cd4e9f4edd18cb2778624ab31b34b23b8.zip on 2022-06-24T16:14:11.965Z
     - WIRC / University of Wisconsin Madison WIS-IH / Wisconsin Insect Research Collection accessed via https://github.com/globalbioticinteractions/wis-ih-wirc/archive/34162b86c0ade4b493471543231ae017cc84816e.zip on 2022-06-24T16:14:29.743Z
     - Yale University Peabody Museum Collections Data Portal accessed via https://github.com/globalbioticinteractions/yale-peabody/archive/43be869f17749d71d26fc820c8bd931d6149fe8e.zip on 2022-06-24T16:23:29.289Z

    Generated on:
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    by:
    GloBI's Elton 0.12.4 
    (see https://github.com/globalbioticinteractions/elton).

    Note that all files ending with .tsv are files formatted 
    as UTF8 encoded tab-separated values files.

    https://www.iana.org/assignments/media-types/text/tab-separated-values


    Included in this review archive are:

    README:
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    review_summary.tsv:
      Summary across all reviewed collections of total number of distinct review comments.

    review_summary_by_collection.tsv:
      Summary by reviewed collection of total number of distinct review comments.

    indexed_interactions_by_collection.tsv: 
      Summary of number of indexed interaction records by institutionCode and collectionCode.

    review_comments.tsv.gz:
      All review comments by collection.

    indexed_interactions_full.tsv.gz:
      All indexed interactions for all reviewed collections.

    indexed_interactions_simple.tsv.gz:
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    datasets_under_review.tsv:
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    elton.jar: 
      Program used to update datasets and generate the review reports and associated indexed interactions.

    datasets.zip:
      Source datasets used by elton.jar in process of executing the generate_report.sh script.

    generate_report.sh:
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  3. Abstract

    Anthropogenic activities have altered historical disturbance regimes, and understanding the mechanisms by which these shifting perturbations interact is essential to predicting where they may erode ecosystem resilience. Emerging infectious plant diseases, caused by human translocation of nonnative pathogens, can generate ecologically damaging forms of novel biotic disturbance. Further, abiotic disturbances, such as wildfire, may influence the severity and extent of disease‐related perturbations via their effects on the occurrence of hosts, pathogens and microclimates; however, these interactions have rarely been examined.

    The disease ‘sudden oak death’ (SOD), associated with the introduced pathogenPhytophthora ramorum, causes acute, landscape‐scale tree mortality in California's fire‐prone coastal forests. Here, we examined interactions between wildfire and the biotic disturbance impacts of this emerging infectious disease. Leveraging long‐term datasets that describe wildfire occurrence andP. ramorumdynamics across the Big Sur region, we modelled the influence of recent and historical fires on epidemiological parameters, including pathogen presence, infestation intensity, reinvasion, and host mortality.

    Past wildfire altered disease dynamics and reduced SOD‐related mortality, indicating a negative interaction between these abiotic and biotic disturbances. Frequently burned forests were less likely to be invaded byP. ramorum, had lower incidence of host infection, and exhibited decreased disease‐related biotic disturbance, which was associated with reduced occurrence and density of epidemiologically significant hosts. Following a recent wildfire, survival of mature bay laurel, a key sporulating host, was the primary driver ofP. ramoruminfestation and reinvasion, but younger, rapidly regenerating host vegetation capable of sporulation did not measurably influence disease dynamics. Notably, the effect ofP. ramoruminfection on host mortality was reduced in recently burned areas, indicating that the loss of tall, mature host canopies may temporarily dampen pathogen transmission and ‘release’ susceptible species from significant inoculum pressure.

    Synthesis. Cumulatively, our findings indicate that fire history has contributed to heterogeneous patterns of biotic disturbance and disease‐related decline across this landscape, via changes to the both the occurrence of available hosts and the demography of epidemiologically important host populations. These results highlight that human‐altered abiotic disturbances may play a foundational role in structuring infectious disease dynamics, contributing to future outbreak emergence and driving biotic disturbance regimes.

     
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  4. Abstract

    Zoonotic diseases represent 75% of emerging infectious diseases worldwide, and their emergence is mainly attributed to human‐driven changes in landscapes. Land use change, especially the conversion of natural areas to agricultural use, has the potential to impact hosts and vector dynamics, affecting pathogen transmission risk. While these links are becoming better understood, very few studies have investigated the opposite question—how native vegetation restoration affects zoonotic disease outbreaks.

    We reviewed the existing evidence linking native vegetation restoration with zoonotic transmission risk, identified knowledge gaps, and, by focusing on tropical areas, proposed forest restoration strategies that could help in limiting the spread of zoonotic diseases.

    We identified a large gap in information on the effects of native vegetation restoration on zoonotic diseases, especially within tropical regions. In addition, the few studies that exist do not consider environmental aspects that can affect the outcomes of restoration on disease risk, such as the land use history and landscape structural characteristics (as composition and configuration of native habitats). Our conceptual framework raises two important points: (1) the effects of forest restoration may depend on the context of the existing landscape, especially the percentage of native vegetation existing at the beginning of the restoration; and (2) these effects will also be dependent on the spatial arrangement of the restored area within the existing landscape. Furthermore, we propose important topics to be studied in the coming years to integrate zoonotic disease risk as a criterion in restoration planning.

    Synthesis and application. Our results contribute to a more comprehensive forest restoration planning, comprising multiple ecosystem services and resulting in healthier landscapes for both people and nature. Our framework could be integrated into the post‐2020 global biodiversity framework targets.

     
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  5. Humans live in complex socio-ecological systems where we interact with parasites and pathogens that spend time in abiotic and biotic environmental reservoirs (e.g., water, air, soil, other vertebrate hosts, vectors, intermediate hosts). Through a synthesis of published literature, we reviewed the life cycles and environmental persistence of 150 parasites and pathogens tracked by the World Health Organization's Global Burden of Disease study. We used those data to derive the time spent in each component of a pathogen's life cycle, including total time spent in humans versus all environmental stages. We found that nearly all infectious organisms were “environmentally mediated” to some degree, meaning that they spend time in reservoirs and can be transmitted from those reservoirs to human hosts. Correspondingly, many infectious diseases were primarily controlled through environmental interventions (e.g., vector control, water sanitation), whereas few (14%) were primarily controlled by integrated methods (i.e., combining medical and environmental interventions). Data on critical life history attributes for most of the 150 parasites and pathogens were difficult to find and often uncertain, potentially hampering efforts to predict disease dynamics and model interactions between life cycle time scales and infection control strategies. We hope that this synthetic review and associated database serve as a resource for understanding both common patterns among parasites and pathogens and important variability and uncertainty regarding particular infectious diseases. These insights can be used to improve systems-based approaches for controlling environmentally mediated diseases of humans in an era where the environment is rapidly changing. 
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