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  • 1
    Online Resource
    Online Resource
    Spread and dynamics of the COVID-19 epidemic in Italy: Effects of emergency containment measures
    Proceedings of the National Academy of Sciences ; 2020
    In:  Proceedings of the National Academy of Sciences Vol. 117, No. 19 ( 2020-05-12), p. 10484-10491
    Details
    In: Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, Vol. 117, No. 19 ( 2020-05-12), p. 10484-10491
    Abstract: The spread of coronavirus disease 2019 (COVID-19) in Italy prompted drastic measures for transmission containment. We examine the effects of these interventions, based on modeling of the unfolding epidemic. We test modeling options of the spatially explicit type, suggested by the wave of infections spreading from the initial foci to the rest of Italy. We estimate parameters of a metacommunity Susceptible–Exposed–Infected–Recovered (SEIR)-like transmission model that includes a network of 107 provinces connected by mobility at high resolution, and the critical contribution of presymptomatic and asymptomatic transmission. We estimate a generalized reproduction number ( R 0 = 3.60 [3.49 to 3.84]), the spectral radius of a suitable next-generation matrix that measures the potential spread in the absence of containment interventions. The model includes the implementation of progressive restrictions after the first case confirmed in Italy (February 21, 2020) and runs until March 25, 2020. We account for uncertainty in epidemiological reporting, and time dependence of human mobility matrices and awareness-dependent exposure probabilities. We draw scenarios of different containment measures and their impact. Results suggest that the sequence of restrictions posed to mobility and human-to-human interactions have reduced transmission by 45% (42 to 49%). Averted hospitalizations are measured by running scenarios obtained by selectively relaxing the imposed restrictions and total about 200,000 individuals (as of March 25, 2020). Although a number of assumptions need to be reexamined, like age structure in social mixing patterns and in the distribution of mobility, hospitalization, and fatality, we conclude that verifiable evidence exists to support the planning of emergency measures.
    Type of Medium: Online Resource
    ISSN: 0027-8424 , 1091-6490
    URL: Article
    DOI: 10.1073/pnas.2004978117
    RVK:
    TA 1000
    RVK:
    WA 15000
    Language: English
    Publisher: Proceedings of the National Academy of Sciences
    Publication Date: 2020
    detail.hit.zdb_id: 209104-5
    detail.hit.zdb_id: 1461794-8
    SSG: 11
    SSG: 12
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  • 2
    Online Resource
    Online Resource
    Generalized reproduction numbers and the prediction of patterns in waterborne disease
    Proceedings of the National Academy of Sciences ; 2012
    In:  Proceedings of the National Academy of Sciences Vol. 109, No. 48 ( 2012-11-27), p. 19703-19708
    Details
    In: Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, Vol. 109, No. 48 ( 2012-11-27), p. 19703-19708
    Abstract: Understanding, predicting, and controlling outbreaks of waterborne diseases are crucial goals of public health policies, but pose challenging problems because infection patterns are influenced by spatial structure and temporal asynchrony. Although explicit spatial modeling is made possible by widespread data mapping of hydrology, transportation infrastructure, population distribution, and sanitation, the precise condition under which a waterborne disease epidemic can start in a spatially explicit setting is still lacking. Here we show that the requirement that all the local reproduction numbers be larger than unity is neither necessary nor sufficient for outbreaks to occur when local settlements are connected by networks of primary and secondary infection mechanisms. To determine onset conditions, we derive general analytical expressions for a reproduction matrix , explicitly accounting for spatial distributions of human settlements and pathogen transmission via hydrological and human mobility networks. At disease onset, a generalized reproduction number (the dominant eigenvalue of ) must be larger than unity. We also show that geographical outbreak patterns in complex environments are linked to the dominant eigenvector and to spectral properties of . Tests against data and computations for the 2010 Haiti and 2000 KwaZulu-Natal cholera outbreaks, as well as against computations for metapopulation networks, demonstrate that eigenvectors of provide a synthetic and effective tool for predicting the disease course in space and time. Networked connectivity models, describing the interplay between hydrology, epidemiology, and social behavior sustaining human mobility, thus prove to be key tools for emergency management of waterborne infections.
    Type of Medium: Online Resource
    ISSN: 0027-8424 , 1091-6490
    URL: Article
    DOI: 10.1073/pnas.1217567109
    RVK:
    TA 1000
    RVK:
    WA 15000
    Language: English
    Publisher: Proceedings of the National Academy of Sciences
    Publication Date: 2012
    detail.hit.zdb_id: 209104-5
    detail.hit.zdb_id: 1461794-8
    SSG: 11
    SSG: 12
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  • 3
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    Online Resource
    Integrated field, laboratory, and theoretical study of PKD spread in a Swiss prealpine river
    Proceedings of the National Academy of Sciences ; 2017
    In:  Proceedings of the National Academy of Sciences Vol. 114, No. 45 ( 2017-11-07), p. 11992-11997
    Details
    In: Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, Vol. 114, No. 45 ( 2017-11-07), p. 11992-11997
    Abstract: Proliferative kidney disease (PKD) is a major threat to wild and farmed salmonid populations because of its lethal effect at high water temperatures. Its causative agent, the myxozoan Tetracapsuloides bryosalmonae , has a complex lifecycle exploiting freshwater bryozoans as primary hosts and salmonids as secondary hosts. We carried out an integrated study of PKD in a prealpine Swiss river (the Wigger). During a 3-year period, data on fish abundance, disease prevalence, concentration of primary hosts’ DNA in environmental samples [environmental DNA (eDNA)] , hydrological variables, and water temperatures gathered at various locations within the catchment were integrated into a newly developed metacommunity model, which includes ecological and epidemiological dynamics of fish and bryozoans, connectivity effects, and hydrothermal drivers. Infection dynamics were captured well by the epidemiological model, especially with regard to the spatial prevalence patterns. PKD prevalence in the sampled sites for both young-of-the-year (YOY) and adult brown trout attained 100% at the end of summer, while seasonal population decay was higher in YOY than in adults. We introduce a method based on decay distance of eDNA signal predicting local species’ density, accounting for variation in environmental drivers (such as morphology and geology). The model provides a whole-network overview of the disease prevalence. In this study, we show how spatial and environmental characteristics of river networks can be used to study epidemiology and disease dynamics of waterborne diseases.
    Type of Medium: Online Resource
    ISSN: 0027-8424 , 1091-6490
    URL: Article
    DOI: 10.1073/pnas.1713691114
    RVK:
    TA 1000
    RVK:
    WA 15000
    Language: English
    Publisher: Proceedings of the National Academy of Sciences
    Publication Date: 2017
    detail.hit.zdb_id: 209104-5
    detail.hit.zdb_id: 1461794-8
    SSG: 11
    SSG: 12
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  • 4
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    Online Resource
    Hydrology and density feedbacks control the ecology of intermediate hosts of schistosomiasis across habitats in seasonal climates
    Proceedings of the National Academy of Sciences ; 2016
    In:  Proceedings of the National Academy of Sciences Vol. 113, No. 23 ( 2016-06-07), p. 6427-6432
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    In: Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, Vol. 113, No. 23 ( 2016-06-07), p. 6427-6432
    Abstract: We report about field and theoretical studies on the ecology of the aquatic snails ( Bulinus spp. and Biomphalaria pfeifferi ) that serve as obligate intermediate hosts in the complex life cycle of the parasites causing human schistosomiasis. Snail abundance fosters disease transmission, and thus the dynamics of snail populations are critically important for schistosomiasis modeling and control. Here, we single out hydrological drivers and density dependence (or lack of it) of ecological growth rates of local snail populations by contrasting novel ecological and environmental data with various models of host demography. Specifically, we study various natural and man-made habitats across Burkina Faso’s highly seasonal climatic zones. Demographic models are ranked through formal model comparison and structural risk minimization. The latter allows us to evaluate the suitability of population models while clarifying the relevant covariates that explain empirical observations of snail abundance under the actual climatic forcings experienced by the various field sites. Our results link quantitatively hydrological drivers to distinct population dynamics through specific density feedbacks, and show that statistical methods based on model averaging provide reliable snail abundance projections. The consistency of our ranking results suggests the use of ad hoc models of snail demography depending on habitat type (e.g., natural vs. man-made) and hydrological characteristics (e.g., ephemeral vs. permanent). Implications for risk mapping and space-time allocation of control measures in schistosomiasis-endemic contexts are discussed.
    Type of Medium: Online Resource
    ISSN: 0027-8424 , 1091-6490
    URL: Article
    DOI: 10.1073/pnas.1602251113
    RVK:
    TA 1000
    RVK:
    WA 15000
    Language: English
    Publisher: Proceedings of the National Academy of Sciences
    Publication Date: 2016
    detail.hit.zdb_id: 209104-5
    detail.hit.zdb_id: 1461794-8
    SSG: 11
    SSG: 12
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  • 5
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    Online Resource
    Spatially explicit effective reproduction numbers from incidence and mobility data
    Proceedings of the National Academy of Sciences ; 2023
    In:  Proceedings of the National Academy of Sciences Vol. 120, No. 20 ( 2023-05-16)
    Details
    In: Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, Vol. 120, No. 20 ( 2023-05-16)
    Abstract: Current methods for near real-time estimation of effective reproduction numbers from surveillance data overlook mobility fluxes of infectors and susceptible individuals within a spatially connected network (the metapopulation). Exchanges of infections among different communities may thus be misrepresented unless explicitly measured and accounted for in the renewal equations. Here, we first derive the equations that include spatially explicit effective reproduction numbers, ℛ k ( t ), in an arbitrary community k . These equations embed a suitable connection matrix blending mobility among connected communities and mobility-related containment measures. Then, we propose a tool to estimate, in a Bayesian framework involving particle filtering, the values of ℛ k ( t ) maximizing a suitable likelihood function reproducing observed patterns of infections in space and time. We validate our tools against synthetic data and apply them to real COVID-19 epidemiological records in a severely affected and carefully monitored Italian region. Differences arising between connected and disconnected reproduction numbers (the latter being calculated with existing methods, to which our formulation reduces by setting mobility to zero) suggest that current standards may be improved in their estimation of disease transmission over time.
    Type of Medium: Online Resource
    ISSN: 0027-8424 , 1091-6490
    URL: Article
    DOI: 10.1073/pnas.2219816120
    RVK:
    TA 1000
    RVK:
    WA 15000
    Language: English
    Publisher: Proceedings of the National Academy of Sciences
    Publication Date: 2023
    detail.hit.zdb_id: 209104-5
    detail.hit.zdb_id: 1461794-8
    SSG: 11
    SSG: 12
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  • 6
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    Online Resource
    Reassessment of the 2010–2011 Haiti cholera outbreak and rainfall-driven multiseason projections
    Proceedings of the National Academy of Sciences ; 2012
    In:  Proceedings of the National Academy of Sciences Vol. 109, No. 17 ( 2012-04-24), p. 6602-6607
    Details
    In: Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, Vol. 109, No. 17 ( 2012-04-24), p. 6602-6607
    Abstract: Mathematical models can provide key insights into the course of an ongoing epidemic, potentially aiding real-time emergency management in allocating health care resources and by anticipating the impact of alternative interventions. We study the ex post reliability of predictions of the 2010–2011 Haiti cholera outbreak from four independent modeling studies that appeared almost simultaneously during the unfolding epidemic. We consider the impact of different approaches to the modeling of spatial spread of Vibrio cholerae and mechanisms of cholera transmission, accounting for the dynamics of susceptible and infected individuals within different local human communities. To explain resurgences of the epidemic, we go on to include waning immunity and a mechanism explicitly accounting for rainfall as a driver of enhanced disease transmission. The formal comparative analysis is carried out via the Akaike information criterion (AIC) to measure the added information provided by each process modeled, discounting for the added parameters. A generalized model for Haitian epidemic cholera and the related uncertainty is thus proposed and applied to the year-long dataset of reported cases now available. The model allows us to draw predictions on longer-term epidemic cholera in Haiti from multiseason Monte Carlo runs, carried out up to January 2014 by using suitable rainfall fields forecasts. Lessons learned and open issues are discussed and placed in perspective. We conclude that, despite differences in methods that can be tested through model-guided field validation, mathematical modeling of large-scale outbreaks emerges as an essential component of future cholera epidemic control.
    Type of Medium: Online Resource
    ISSN: 0027-8424 , 1091-6490
    URL: Article
    DOI: 10.1073/pnas.1203333109
    RVK:
    TA 1000
    RVK:
    WA 15000
    Language: English
    Publisher: Proceedings of the National Academy of Sciences
    Publication Date: 2012
    detail.hit.zdb_id: 209104-5
    detail.hit.zdb_id: 1461794-8
    SSG: 11
    SSG: 12
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  • 7
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    Online Resource
    Galectin-1 fosters an immunosuppressive microenvironment in colorectal cancer by reprogramming CD8 + regulatory T cells
    Proceedings of the National Academy of Sciences ; 2021
    In:  Proceedings of the National Academy of Sciences Vol. 118, No. 21 ( 2021-05-25)
    Details
    In: Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, Vol. 118, No. 21 ( 2021-05-25)
    Abstract: Colorectal cancer (CRC) represents the third most common malignancy and the second leading cause of cancer-related deaths worldwide. Although immunotherapy has taken center stage in mainstream oncology, it has shown limited clinical efficacy in CRC, generating an urgent need for discovery of new biomarkers and potential therapeutic targets. Galectin-1 (Gal-1), an endogenous glycan-binding protein, induces tolerogenic programs and contributes to tumor cell evasion of immune responses. Here, we investigated the relevance of Gal-1 in CRC and explored its modulatory activity within the CD8 + regulatory T cell (Treg) compartment. Mice lacking Gal-1 ( Lgals1 −/− ) developed a lower number of tumors and showed a decreased frequency of a particular population of CD8 + CD122 + PD-1 + Tregs in the azoxymethane-dextran sodium sulfate model of colitis-associated CRC. Moreover, silencing of tumor-derived Gal-1 in the syngeneic CT26 CRC model resulted in reduced number and attenuated immunosuppressive capacity of CD8 + CD122 + PD-1 + Tregs, leading to slower tumor growth. Moreover, stromal Gal-1 also influenced the fitness of CD8 + Tregs, highlighting the contribution of both tumor and stromal-derived Gal-1 to this immunoregulatory effect. Finally, bioinformatic analysis of a colorectal adenocarcinoma from The Cancer Genome Atlas dataset revealed a particular signature characterized by high CD8 + Treg score and elevated Gal-1 expression, which delineates poor prognosis in human CRC. Our findings identify CD8 + CD122 + PD-1 + Tregs as a target of the immunoregulatory activity of Gal-1, suggesting a potential immunotherapeutic strategy for the treatment of CRC.
    Type of Medium: Online Resource
    ISSN: 0027-8424 , 1091-6490
    URL: Article
    DOI: 10.1073/pnas.2102950118
    RVK:
    TA 1000
    RVK:
    WA 15000
    Language: English
    Publisher: Proceedings of the National Academy of Sciences
    Publication Date: 2021
    detail.hit.zdb_id: 209104-5
    detail.hit.zdb_id: 1461794-8
    SSG: 11
    SSG: 12
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