A5059787882- COVID-19 epidemiological studies
- Human Mobility and Location-Based Analysis
- Data-Driven Disease Surveillance
- Influenza Virus Research Studies
- Urban Transport and Accessibility
- Complex Network Analysis Techniques
- COVID-19 Digital Contact Tracing
- Urban, Neighborhood, and Segregation Studies
- Transportation and Mobility Innovations
- Opinion Dynamics and Social Influence
- Mathematical and Theoretical Epidemiology and Ecology Models
- Misinformation and Its Impacts
- Bacterial Infections and Vaccines
- Pneumonia and Respiratory Infections
- Evacuation and Crowd Dynamics
- Context-Aware Activity Recognition Systems
- Infection Control and Ventilation
- Innovative Human-Technology Interaction
- Animal Disease Management and Epidemiology
- COVID-19 and Mental Health
- Viral Infections and Outbreaks Research
- Impact of Light on Environment and Health
- Health disparities and outcomes
- Mosquito-borne diseases and control
- Virology and Viral Diseases
University of Trento
2022-2025
Institute for Scientific Interchange
2015-2024
ISI Foundation
2018-2023
IT University of Copenhagen
2022
Policlinico San Matteo Fondazione
1989-2020
University of Pavia
2020
Istituti di Ricovero e Cura a Carattere Scientifico
1989-2015
Polytechnic University of Turin
2009-2012
Lagrange Laboratory
2008-2009
LaGrange College
2008-2009
After the emergence of H1N1 influenza in 2009, some countries responded with travel-related controls during early stage outbreak an attempt to contain or slow down its international spread. These along self-imposed travel limitations contributed a decline about 40% air traffic to/from Mexico following alert. However, no containment was achieved by such restrictions and virus able reach pandemic proportions short time. When gauging value efficacy mobility it is crucial rely on epidemic models...
Human mobility is a key component of large-scale spatial-transmission models infectious diseases. Correctly modeling and quantifying human critical for improving epidemic control, but may be hindered by data incompleteness or unavailability. Here we explore the opportunity using proxies individual to describe commuting flows predict diffusion an influenza-like-illness epidemic. We consider three European countries corresponding networks at different resolution scales, obtained from (i)...
Abstract Background On 11 June the World Health Organization officially raised phase of pandemic alert (with regard to new H1N1 influenza strain) level 6. As 19 July, 137,232 cases strain have been confirmed in 142 different countries, and unfolding Southern hemisphere is now under scrutiny gain insights about next winter wave Northern hemisphere. A major challenge pre-empted by need estimate transmission potential virus assess its dependence on seasonality aspects order be able use...
Abstract Italy has been severely affected by the COVID-19 pandemic, reporting highest death toll in Europe as of April 2020. Following identification first infections, on February 21, 2020, national authorities have put place an increasing number restrictions aimed at containing outbreak and delaying epidemic peak. On March 12, government imposed a lockdown. To aid evaluation impact interventions, we present daily time-series three different aggregated mobility metrics: origin-destination...
Abstract Background Mathematical and computational models for infectious diseases are increasingly used to support public-health decisions; however, their reliability is currently under debate. Real-time forecasts of epidemic spread using data-driven have been hindered by the technical challenges posed parameter estimation validation. Data gathered 2009 H1N1 influenza crisis represent an unprecedented opportunity validate real-time model predictions define main success criteria different...
Abstract Mobile phone data have been extensively used to study urban mobility. However, studies based on gender-disaggregated large-scale are still lacking, limiting our understanding of gendered aspects mobility and ability design policies for gender equality. Here we from a perspective, combining commercial open datasets the city Santiago, Chile. We analyze call detail records large cohort anonymized mobile users reveal gap in mobility: women visit fewer unique locations than men,...
Abstract We study the spatio-temporal spread of SARS-CoV-2 in Santiago de Chile using anonymized mobile phone data from 1.4 million users, 22% whole population area, characterizing effects non-pharmaceutical interventions (NPIs) on epidemic dynamics. integrate these into a mechanistic model calibrated surveillance data. As August 1, 2020, we estimate detection rate 102 cases per 1000 infections (90% CI: [95–112 1000]). show that introduction full lockdown May 15, while causing modest...
Abstract Italy is currently experiencing the largest COVID-19 outbreak in Europe so far, with more than 100,000 confirmed cases. Following identification of first infections, on February 21, 2020, national authorities have put place an increasing number restrictions aimed at containing and delaying epidemic peak. Since March 12, whole country under lockdown. Here we provide quantitative assessment impact such measures mobility spatial proximity Italians, through analysis a large-scale...
This paper describes how mobile phone data can guide government and public health authorities in determining the best course of action to control COVID-19 pandemic assessing effectiveness measures such as physical distancing. It identifies key gaps reasons why this kind is only scarcely used, although their value similar epidemics has proven a number use cases. presents ways overcome these recommendations for urgent action, most notably establishment mixed expert groups on national regional...
Media framing of epidemics was found to influence public perceptions and behaviors in experiments, yet no research has been conducted on real-world during health crises. We examined the relationship between Italian news media coverage COVID-19 compliance with stay-at-home orders, which could impact spread epidemics. used a computational method for analysis (ANTMN) combined it Google's Community Mobility data. A time-series using vector autoregressive models showed that frames were largely...
Despite the availability of effective vaccines against SARS-CoV-2, non-pharmaceutical interventions remain an important part effort to reduce viral circulation caused by emerging variants with capability evading vaccine-induced immunity. With aim striking a balance between mitigation and long-term sustainability, several governments worldwide have adopted systems tiered interventions, increasing stringency, that are calibrated according periodic risk assessments. A key challenge remains in...
Abstract Food insecurity, defined as the lack of physical or economic access to safe, nutritious and sufficient food, remains one main challenges included in 2030 Agenda for Sustainable Development. Near real-time data on food insecurity situation collected by international organizations such World Programme can be crucial monitor forecast time trends insufficient consumption levels countries at risk. Here, using observations combination with secondary conflict, extreme weather events...
Close proximity interactions between individuals influence how infections spread. Quantifying close contacts in developing world settings, where such data is sparse yet disease burden high, can provide insights into the design of intervention strategies as vaccination. Recent technological advances have enabled collection time-resolved face-to-face human contact using radio frequency sensors. The acceptability and practicalities devices within country setting not been investigated. We...
Predicting human mobility flows at different spatial scales is challenged by the heterogeneity of individual trajectories and multi-scale nature transportation networks. As vast amounts digital traces behaviour become available, an opportunity arises to improve models integrating into them proxy data on collected a variety platforms location-aware services. Here we propose hybrid model that integrates large-scale publicly available dataset from popular photo-sharing system with classical...
The availability of novel digital data streams that can be used as proxy for monitoring infectious disease incidence is ushering in a new era real-time forecast approaches to spreading. Here, we propose the first seasonal influenza framework based on stochastic, spatially structured mechanistic model (individual level microsimulation) initialized with geo-localized microblogging data. provides more than 600 census areas United States, Italy and Spain, initial conditions stochastic epidemic...
The recent availability of large-scale call detail record data has substantially improved our ability quantifying human travel patterns with broad applications in epidemiology. Notwithstanding a number successful case studies, previous works have shown that using different mobility sources, such as mobile phone or census surveys, to parametrize infectious disease models can generate divergent outcomes. Thus, it remains unclear what extent epidemic modelling results may vary when proxies for...
After more than 1 year into the COVID-19 pandemic, governments worldwide still face challenge of adopting non-pharmaceutical interventions to mitigate risks posed by emergence new SARS-CoV-2 variants and lack a equitable vaccine allocation. Thus, it becomes crucial identify drivers mobility responses mitigation efforts during different restriction regimes, for planning that are both economically socially sustainable while effective in controlling an outbreak. Here, using anonymous...
Social distancing have been widely used to mitigate community spread of SARS-CoV-2. We sought quantify the impact COVID-19 social policies across 27 European counties in spring 2020 on population mobility and subsequent trajectory disease. obtained data national from Oxford Government Response Tracker aggregated anonymized Google. a pre-post comparison two linear mixed-effects models first assess relationship between implementation observed changes mobility, then rates infections weeks....
The COVID-19 pandemic has highlighted how structural social inequities fundamentally shape disease dynamics, yet these concepts are often at the margins of computational modeling community. Building on recent research studies in area digital and epidemiology, we provide a set practical methodological recommendations to address socioeconomic vulnerabilities epidemic models. dynamics. Here, authors
Variables related to socioeconomic status (SES), including income, ethnicity, and education, shape contact structures affect the spread of infectious diseases. However, these factors are often overlooked in epidemic models, which typically stratify social contacts by age interaction contexts. Here, we introduce study generalized matrices that across multiple dimensions. We demonstrate a lower-bound theorem proving disregarding additional dimensions, besides context, might lead an...
Infectious diseases outbreaks are often characterized by a spatial component induced hosts' distribution, mobility and interactions. Spatial models that incorporate movements being used to describe these processes, investigate the conditions for propagation predict spread. Several assumptions considered model movements, ranging from permanent daily commuting, where time spent at destination is either infinite or assumes homogeneous fixed value, respectively. Prompted empirical evidence, here...