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  1. Article ; Online: 2022 Uganda Ebola outbreak: Early descriptions and open data.

    Branda, Francesco / Maruotti, Antonello

    Journal of medical virology

    2023  Volume 95, Issue 1, Page(s) e28344

    MeSH term(s) Humans ; Hemorrhagic Fever, Ebola/epidemiology ; Uganda/epidemiology ; Disease Outbreaks ; Ebolavirus
    Language English
    Publishing date 2023-01-02
    Publishing country United States
    Document type Letter
    ZDB-ID 752392-0
    ISSN 1096-9071 ; 0146-6615
    ISSN (online) 1096-9071
    ISSN 0146-6615
    DOI 10.1002/jmv.28344
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  2. Article ; Online: Is a new COVID-19 wave coming from China due to an unknown variant of concern? Keep calm and look at the data.

    Branda, Francesco / Scarpa, Fabio / Ciccozzi, Massimo / Maruotti, Antonello

    Journal of medical virology

    2023  Volume 95, Issue 3, Page(s) e28601

    MeSH term(s) Humans ; COVID-19 ; SARS-CoV-2 ; China/epidemiology
    Language English
    Publishing date 2023-03-07
    Publishing country United States
    Document type Letter
    ZDB-ID 752392-0
    ISSN 1096-9071 ; 0146-6615
    ISSN (online) 1096-9071
    ISSN 0146-6615
    DOI 10.1002/jmv.28601
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  3. Article: Mpox: An Overview of Pathogenesis, Diagnosis, and Public Health Implications.

    Branda, Francesco / Romano, Chiara / Ciccozzi, Massimo / Giovanetti, Marta / Scarpa, Fabio / Ciccozzi, Alessandra / Maruotti, Antonello

    Journal of clinical medicine

    2024  Volume 13, Issue 8

    Abstract: Mpox, caused by viruses of the genus Orthopoxvirus, is an emerging threat to human and animal health. With increasing urbanization and more frequent interaction between humans and wild animals, the risk of Mpox transmission to humans has increased ... ...

    Abstract Mpox, caused by viruses of the genus Orthopoxvirus, is an emerging threat to human and animal health. With increasing urbanization and more frequent interaction between humans and wild animals, the risk of Mpox transmission to humans has increased significantly. This review aims to examine in depth the epidemiology, pathogenesis, and diagnosis of Mpox, with a special focus on recent discoveries and advances in understanding the disease. Molecular mechanisms involved in viral replication will be examined, as well as risk factors associated with interspecific transmission and spread of the disease in human populations. Currently available diagnostic methods will also be discussed, with a critical analysis of their limitations and possible future directions for improving the accuracy and timeliness of diagnosis. Finally, this review will explore the public health implications associated with Mpox, emphasizing the importance of epidemiological surveillance, vaccination, and emergency preparedness to prevent and manage possible outbreaks. Understanding the epidemiology and control strategies for Mpox is critical to protecting the health of human and animal communities and mitigating the risk of interspecific transmission and spread of the disease.
    Language English
    Publishing date 2024-04-12
    Publishing country Switzerland
    Document type Journal Article ; Review
    ZDB-ID 2662592-1
    ISSN 2077-0383
    ISSN 2077-0383
    DOI 10.3390/jcm13082234
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  4. Article ; Online: Short-term forecasts of Monkeypox cases in multiple countries: keep calm and don't panic.

    Mingione, Marco / Ciccozzi, Massimo / Falcone, Marco / Maruotti, Antonello

    Journal of medical virology

    2022  Volume 95, Issue 1, Page(s) e28159

    Abstract: We propose a parametric regression model for incidence indicators based on the use of the Richards' curve (a generalized logistic function) to analyse the current Monkeypox epidemic data for the most 10 affected countries worldwide. At present, results ... ...

    Abstract We propose a parametric regression model for incidence indicators based on the use of the Richards' curve (a generalized logistic function) to analyse the current Monkeypox epidemic data for the most 10 affected countries worldwide. At present, results show that the outbreak is under control in most countries.
    MeSH term(s) Humans ; Mpox (monkeypox)/epidemiology ; Disease Outbreaks ; Epidemics
    Language English
    Publishing date 2022-09-29
    Publishing country United States
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ZDB-ID 752392-0
    ISSN 1096-9071 ; 0146-6615
    ISSN (online) 1096-9071
    ISSN 0146-6615
    DOI 10.1002/jmv.28159
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  5. Article ; Online: Monitoring the West Nile virus outbreaks in Italy using open access data.

    Mingione, Marco / Branda, Francesco / Maruotti, Antonello / Ciccozzi, Massimo / Mazzoli, Sandra

    Scientific data

    2023  Volume 10, Issue 1, Page(s) 777

    Abstract: This paper introduces a comprehensive dataset on West Nile virus outbreaks that have occurred in Italy from September 2012 to November 2022. We have digitized bulletins published by the Italian National Institute of Health to demonstrate the potential ... ...

    Abstract This paper introduces a comprehensive dataset on West Nile virus outbreaks that have occurred in Italy from September 2012 to November 2022. We have digitized bulletins published by the Italian National Institute of Health to demonstrate the potential utilization of this data for the research community. Our aim is to establish a centralized open access repository that facilitates analysis and monitoring of the disease. We have collected and curated data on the type of infected host, along with additional information whenever available, including the type of infection, age, and geographic details at different levels of spatial aggregation. By combining our data with other sources of information such as weather data, it becomes possible to assess potential relationships between West Nile virus outbreaks and environmental factors. We strongly believe in supporting public oversight of government epidemic management, and we emphasize that open data play a crucial role in generating reliable results by enabling greater transparency.
    MeSH term(s) Humans ; Access to Information ; Disease Outbreaks ; Italy/epidemiology ; West Nile Fever/epidemiology ; West Nile virus
    Language English
    Publishing date 2023-11-07
    Publishing country England
    Document type Dataset ; Journal Article
    ZDB-ID 2775191-0
    ISSN 2052-4463 ; 2052-4463
    ISSN (online) 2052-4463
    ISSN 2052-4463
    DOI 10.1038/s41597-023-02676-0
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  6. Article: The challenges of open data for future epidemic preparedness: The experience of the 2022 Ebolavirus outbreak in Uganda.

    Branda, Francesco / Mahal, Ahmed / Maruotti, Antonello / Pierini, Massimo / Mazzoli, Sandra

    Frontiers in pharmacology

    2023  Volume 14, Page(s) 1101894

    Abstract: On 20 September 2022, the Ministry of Health in Uganda, together with the World Health Organization-Regional Office for Africa (WHO AFRO) confirmed an outbreak of EVD due to Sudan ebolavirus in Mubende District, after one fatal case was confirmed. Real- ... ...

    Abstract On 20 September 2022, the Ministry of Health in Uganda, together with the World Health Organization-Regional Office for Africa (WHO AFRO) confirmed an outbreak of EVD due to Sudan ebolavirus in Mubende District, after one fatal case was confirmed. Real-time information are needed to provide crucial information to understand transmissibility, risk of geographical spread, routes of transmission, risk factors of infection, and provide the basis for epidemiological modelling that can inform response and containment planning to reduce the burden of disease. We made an effort to build a centralized repository of the Ebola virus cases from verified sources, providing information on dates of symptom onset, locations (aggregated to the district level), and when available, the gender and status of hospitals, reporting bed capacity and isolation unit occupancy rate according to the severity status of the patient. The proposed data repository provides researchers and policymakers timely, complete, and easy-accessible data to monitor the most recent trends of the Ebola outbreak in Ugandan districts with informative graphical outputs. This favors a rapid global response to the disease, enabling governments to prioritize and adjust their decisions quickly and effectively in response to the rapidly evolving emergency, with a solid data basis.
    Language English
    Publishing date 2023-02-10
    Publishing country Switzerland
    Document type Journal Article
    ZDB-ID 2587355-6
    ISSN 1663-9812
    ISSN 1663-9812
    DOI 10.3389/fphar.2023.1101894
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  7. Article: Quantile hidden semi-Markov models for multivariate time series.

    Merlo, Luca / Maruotti, Antonello / Petrella, Lea / Punzo, Antonio

    Statistics and computing

    2022  Volume 32, Issue 4, Page(s) 61

    Abstract: This paper develops a quantile hidden semi-Markov regression to jointly estimate multiple quantiles for the analysis of multivariate time series. The approach is based upon the Multivariate Asymmetric Laplace (MAL) distribution, which allows to model the ...

    Abstract This paper develops a quantile hidden semi-Markov regression to jointly estimate multiple quantiles for the analysis of multivariate time series. The approach is based upon the Multivariate Asymmetric Laplace (MAL) distribution, which allows to model the quantiles of all univariate conditional distributions of a multivariate response simultaneously, incorporating the correlation structure among the outcomes. Unobserved serial heterogeneity across observations is modeled by introducing regime-dependent parameters that evolve according to a latent finite-state semi-Markov chain. Exploiting the hierarchical representation of the MAL, inference is carried out using an efficient Expectation-Maximization algorithm based on closed form updates for all model parameters, without parametric assumptions about the states' sojourn distributions. The validity of the proposed methodology is analyzed both by a simulation study and through the empirical analysis of air pollutant concentrations in a small Italian city.
    Supplementary information: The online version contains supplementary material available at 10.1007/s11222-022-10130-1.
    Language English
    Publishing date 2022-08-09
    Publishing country United States
    Document type Journal Article
    ZDB-ID 2017741-0
    ISSN 1573-1375 ; 0960-3174
    ISSN (online) 1573-1375
    ISSN 0960-3174
    DOI 10.1007/s11222-022-10130-1
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  8. Article: Parsimonious hidden Markov models for matrix-variate longitudinal data.

    Tomarchio, Salvatore D / Punzo, Antonio / Maruotti, Antonello

    Statistics and computing

    2022  Volume 32, Issue 3, Page(s) 53

    Abstract: Hidden Markov models (HMMs) have been extensively used in the univariate and multivariate literature. However, there has been an increased interest in the analysis of matrix-variate data over the recent years. In this manuscript we introduce HMMs for ... ...

    Abstract Hidden Markov models (HMMs) have been extensively used in the univariate and multivariate literature. However, there has been an increased interest in the analysis of matrix-variate data over the recent years. In this manuscript we introduce HMMs for matrix-variate balanced longitudinal data, by assuming a matrix normal distribution in each hidden state. Such data are arranged in a four-way array. To address for possible overparameterization issues, we consider the eigen decomposition of the covariance matrices, leading to a total of 98 HMMs. An expectation-conditional maximization algorithm is discussed for parameter estimation. The proposed models are firstly investigated on simulated data, in terms of parameter recovery, computational times and model selection. Then, they are fitted to a four-way real data set concerning the unemployment rates of the Italian provinces, evaluated by gender and age classes, over the last 16 years.
    Language English
    Publishing date 2022-06-15
    Publishing country United States
    Document type Journal Article
    ZDB-ID 2017741-0
    ISSN 1573-1375 ; 0960-3174
    ISSN (online) 1573-1375
    ISSN 0960-3174
    DOI 10.1007/s11222-022-10107-0
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  9. Article ; Online: COVID-19-induced excess mortality in Italy during the Omicron wave.

    Maruotti, Antonello / Ciccozzi, Massimo / Jona-Lasinio, Giovanna

    IJID Regions (Online)

    2022  Volume 4, Page(s) 85–87

    Abstract: Background: The existing literature estimates a significantly reduced odds of hospitalisation and death among individuals. However, though less severe than other variants, the Omicron variant may still lead to excess mortality compared to pre-pandemic ... ...

    Abstract Background: The existing literature estimates a significantly reduced odds of hospitalisation and death among individuals. However, though less severe than other variants, the Omicron variant may still lead to excess mortality compared to pre-pandemic years.
    Methods: A generalized linear mixed model is introduced to model weekly mortality from 2011 to 2019, taking into account seasonal patterns and year-specific trends. Based on the 2019 year-specific conditional best linear unbiased predictions, excess of mortality is estimated.
    Results: In Italy, 14 and 11 regions suffered from relevant excess mortality in January and February, respectively. However, the situation is far from being as critical as during previous waves.
    Conclusions: We can conclude that no matter which variant (or multiple inter-variant recombination) we are facing, excess mortality will appear in correspondence of any incidence peak.
    Language English
    Publishing date 2022-07-08
    Publishing country England
    Document type Journal Article
    ISSN 2772-7076
    ISSN (online) 2772-7076
    DOI 10.1016/j.ijregi.2022.07.005
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  10. Article ; Online: Estimating the undetected infections in the Monkeypox outbreak.

    Maruotti, Antonello / Böhning, Dankmar / Rocchetti, Irene / Ciccozzi, Massimo

    Journal of medical virology

    2022  Volume 95, Issue 1, Page(s) e28099

    Abstract: While the number of detected Monkeypox infections are widely available, an understanding of the extent of undetected cases is urgently needed for an effective tackling of its spread. The aim of this study is to estimate the true number of Monkeypox ( ... ...

    Abstract While the number of detected Monkeypox infections are widely available, an understanding of the extent of undetected cases is urgently needed for an effective tackling of its spread. The aim of this study is to estimate the true number of Monkeypox (detected and undetected) infections in most affected countries. The question being asked is: How many cases have actually occurred? We propose a lower bound estimator for the true number of Monkeypox cases. The estimator is data-driven and can be easily computed from the cumulative distributions of weekly cases. We focused on the ratio of the total estimated cases to the observed cases on July 31, 2022: The proportion of undetected cases was relevant in all countries, with countries whose estimated true number of infections could be more than three times the observed one. We provided a practical contribution to the understanding of the current Monkeypox wave and reliable estimates on how many undetected cases are going around in several countries, where the epidemic spreads differently.
    MeSH term(s) Humans ; Mpox (monkeypox)/diagnosis ; Mpox (monkeypox)/epidemiology ; Disease Outbreaks ; Monkeypox virus ; Epidemics
    Language English
    Publishing date 2022-09-06
    Publishing country United States
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ZDB-ID 752392-0
    ISSN 1096-9071 ; 0146-6615
    ISSN (online) 1096-9071
    ISSN 0146-6615
    DOI 10.1002/jmv.28099
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