Stefano M. Iacus

Harvard University | Harvard · Institute for Quantitative Social Science

This article explores the territorial differences in the onset and spread of COVID-19 and the excess mortality associated with the pandemic, with a focus on European regions and US counties. Both in Europe and in the US, the pandemic arrived earlier and recorded higher Rt values in urban regions than in intermediate and rural ones. A similar gap is...

This work contributes to the discussion on how innovative data can support a fast crisis response. We use operational data from Facebook to gain useful insights on where people fleeing Ukraine following the Russian invasion are likely to be displaced, focusing on the European Union. In this context, it is extremely important to anticipate where the...

Using available phylogeographical data of 3585 SARS–CoV–2 genomes we attempt at providing a global picture of the virus’s dynamics in terms of directly interpretable parameters. To this end we fit a hidden state multistate speciation and extinction model to a pre-estimated phylogenetic tree with information on the place of sampling of each strain....

Human travel fed the worldwide spread of COVID-19, but it remains unclear whether the volume of incoming air passengers and the centrality of airports in the global airline network made some regions more vulnerable to earlier and higher mortality. We assess whether the precocity and severity of COVID-19 deaths were contingent on these measures of a...

This study analyzes the impact of the COVID-19 pandemic on subjective well-being as measured through Twitter for the countries of Japan and Italy. In the first nine months of 2020, the Twitter indicators dropped by 11.7% for Italy and 8.3% for Japan compared to the last two months of 2019, and even more compared to their historical means. To unders...

The conflict in Ukraine is causing large-scale displacement in Europe and in the World. Based on the UNHCR estimates, more than 7 million people fled the country as of 5 September 2022. In this context, it is extremely important to anticipate where these people are moving so that national to local authorities can better manage challenges related to...

With the consolidation of the culture of evidence-based policymaking, the availability of data has become central to policymakers. Nowadays, innovative data sources offer an opportunity to describe demographic, mobility, and migratory phenomena more accurately by making available large volumes of real-time and spatially detailed data. At the same t...

This article illustrates an approach to forecasting change in conflict fatalities designed to address the complexity of the drivers and processes of armed conflicts. The design of this approach is based on two main choices. First, to account for the specificity of conflict drivers and processes over time and space, we model conflicts in each indivi...

This work contributes to the discussion on how innovative data can support a fast crisis response. We use operational data from Facebook to gain useful insights on where people fleeing Ukraine following the Russian invasion are likely to be displaced, focusing on the \acl{EU}. In this context, it is extremely important to anticipate where these peo...

Since 2012, driven by the desire to propose a subjective well-being index (SWBI) complementary to the traditional measures, with high time and space frequency, our team evaluates, analysing Twitter data, a composite index that captures various aspects and dimensions of individual and collective life. The SWBI is a multidimensional indicator whose c...

How do people feel about their lives and the societies in which they live? Are they happy, hopeful or concerned about the future? Surveys can help answer these questions, but Stefano M. Iacus and Giuseppe Porro argue for using social networks and sentiment analysis to let citizens speak for themselves How do people feel about their lives and the so...

This article illustrates an approach to forecasting change in conflict fatalities designed to address the complexity of the drivers and processes of armed conflicts. The design of this approach is based on two main choices. First, to account for the specificity of conflict drivers and processes over time and space, we model conflicts in each indivi...

According to certain political discourses, state-led and private-led search-and-rescue is an explanatory factor of the observed increase during the period 2013-2016 in the inflow of migrants along the Central Mediterranean route towards Europe, which would imply search-and-rescue constitutes a 'pull factor' of migration. However, throughout these y...

The COVID-19 pandemic has created a sudden need for a wider uptake of home-based telework as means of sustaining the production. Generally, teleworking arrangements impact directly worker’s efficiency and motivation. The direction of this impact, however, depends on the balance between positive effects of teleworking (e.g. increased flexibility and...

This work contributes to the discussion on how innovative data can support a fast crisis response. We focus on the use of two different sources of operational data from Meta to gain useful insights on migration flows following the conflict in Ukraine. By analysing the Facebook Ukrainian speaking Monthly Active Users, we estimate the flows of people...

This study presents for the first time the SWB-J index, a subjective well-being indicator for Japan based on Twitter data. The index is composed by eight dimensions of subjective well-being and is estimated relying on Twitter data by using human supervised sentiment analysis. The index is then compared with the analogous SWB-I index for Italy in or...

The success of public health policies aimed at curtailing the COVID-19 pandemic have relied on large-scale and protracted compliance by the public. A series of studies have recently argued that previous voting patterns are important predictors of such compliance. Our research further investigates such connection by tracking the relationships betwee...

With the consolidation of the culture of evidence-based policymaking, the availability of data has become central for policymakers. Nowadays, innovative data sources have offered opportunity to describe more accurately demographic, mobility- and migration- related phenomena by making available large volumes of real-time and spatially detailed data....

The effects of the so-called "refugee crisis" of 2015-16 continue to dominate the political agenda in Europe. Migration flows were sudden and unexpected, leaving governments unprepared and exposing significant shortcomings in the field of migration forecasting. Migration is a complex system typified by episodic variation, underpinned by causal fact...

Mobility restrictions during the COVID-19 pandemic ostensibly prevented the public from transmitting the disease in public places, but they also hampered outdoor recreation, despite the importance of blue-green spaces (e.g., parks and natural areas) for physical and mental health. We assess whether restrictions on human movement, particularly in bl...

The COVID-19 pandemic has created a sudden need for a wider uptake of home-based telework as means of sustaining the production. Generally, teleworking arrangements have direct effect on worker's efficiency and motivation. The direction of this impact, however, depends on the balance between positive effects of teleworking (e.g. increased flexibili...

Human travel fed the worldwide spread of Covid-19, but it remains unclear whether the volume of incoming air passengers and the centrality of airports in the global airline network made some regions more vulnerable to earlier and higher mortality. We assess whether the precocity and severity of Covid-19 deaths were contingent on these measures of a...

This work introduces a new concept of functional areas called Mobility Functional Areas (MFAs), i.e., the geographic zones highly interconnected according to the analysis of mobile positioning data. The MFAs do not coincide necessarily with administrative borders as they are built observing natural human mobility and, therefore, they can be used to...

The rapid spread of COVID-19 infections on a global level has highlighted the need for accurate, transparent and timely information regarding collective mobility patterns to inform de-escalation strategies as well as to provide forecasting capacity for re-escalation policies aiming at addressing further waves of the virus. Such information can be e...

The rapid spread of COVID-19 infections on a global level has highlighted the need for accurate, transparent and timely information regarding collective mobility patterns to inform de-escalation strategies as well as to provide forecasting capacity for re-escalation policies aiming at addressing further waves of the virus. Such information can be e...

This work presents the analysis of the impact of restrictions on mobility in Italy, with a focus on the period from 6 November 2020 to 31 January 2021, when a three-tier system based on different levels of risk was adopted and applied at regional level to contrast the second wave of COVID-19. The impact is first evaluated on mobility using Mobile N...

This work introduces a new concept of functional areas called Mobility Functional Areas (MFAs), i.e., the geographic zones highly interconnected according to the analysis of mobile positioning data. The MFAs do not coincide necessarily with administrative borders as they are built observing natural human mobility and, therefore, they can be used to...

This article explores the territorial differences in the onset and spread of COVID-19 and the excess mortality associated with the pandemic, across the European NUTS3 regions and US counties. Both in Europe and in the US, the pandemic arrived earlier and recorded higher Rt values in urban regions than in intermediate and rural ones. A similar gap i...

Due to an unprecedented agreement with the European Mobile Network Operators, the Joint Research Centre of the European Commission was in charge of collecting and analyze mobile positioning data to provide scientific evidence to policy makers to face the COVID-19 pandemic. This work introduces a live anomaly detection system for these high-frequenc...

This study analyzes the impact of the COVID-19 pandemic on the subjective well-being as measured through Twitter data indicators for Japan and Italy. It turns out that, overall, the subjective well-being dropped by 11.7% for Italy and 8.3% for Japan in the first nine months of 2020 compared to the last two months of 2019 and even more compared to t...

This study presents for the first time the SWB-J index, a subjective well-being indicator for Japan based on Twitter data. The index is composed by eight dimensions of subjective well-being and is estimated relying on Twitter data by using human supervised sentiment analysis. The index is then compared with the analogous SWB-I index for Italy, in o...

This work presents a mobility indicator derived from fully anonymised and aggregated mobile positioning data. Even though the indicator does not provide information about the behaviour of individuals, it captures valuable insights into the mobility patterns of the population in the EU and it is expected to inform responses against the COVID-19 pand...

The effects of the so-called "refugee crisis" of 2015-16 continue to dominate much of the European political agenda. Migration flows were sudden and unexpected, exposing significant shortcomings in the field of migration forecasting and leaving governments and NGOs unprepared. Migration is a complex system typified by episodic variation, underpinne...

Due to an unprecedented agreement with the European Mobile Network Operators (MNOs) the Joint Research Centre (JRC) of the European Commission was in charge of collecting and analyze mobile positioning data to provide scientific evidence to policy makers in order to face the COVID-19 pandemic. This work introduces a live anomaly detection system fo...

The paper explores the travelling behaviour of migrant groups using Facebook audience estimates. Reduced geographical mobility is associated with increased risk of social exclusion and reduced socio-economic and psychological well-being. Facebook audience estimates are timely, openly available and cover most of the countries in the world. Facebook...

As the COVID-19 outbreak is developing the two most frequently reported statistics seem to be the raw confirmed case and case fatalities counts. Focusing on Italy, one of the hardest hit countries, we look at how these two values could be put in perspective to reflect the dynamics of the virus spread. In particular, we find that merely considering...

Countries in Europe took different mobility containment measures to curb the spread of COVID-19. The European Commission asked mobile network operators to share on a voluntarily basis anonymised and aggregate mobile data to improve the quality of modelling and forecasting for the pandemic at EU level. In fact, mobility data at EU scale can help und...

This study analyzes the usage of Japanese gendered language on Twitter. Starting from a collection of 408 million Japanese tweets from 2015 till 2019 and an additional sample of 2355 manually classified Twitter accounts timelines into gender and categories (politicians, musicians, etc). A large scale textual analysis is performed on this corpus to...

This work provides an analysis on the potential of aggregate and anonymised mobility data from mobile phones to explain the recent COVID-19 outbreak in Europe. The data were processed by the European Commission in collaboration with EU Mobile Network Operators (MNOs) to improve the quality of modelling and forecasting for the pandemic at EU level....

With the increase of social media usage, a huge new source of data has become available. Despite the enthusiasm linked to this revolution, one of the main outstanding criticisms in using these data is selection bias. Indeed, the reference population is unknown. Nevertheless, many studies show evidence that these data constitute a valuable source be...

As the COVID-19 outbreak is developing the two most frequently reported statistics seem to be the raw confirmed case and case fatalities counts. Focusing on Italy, one of the hardest hit countries, we look at how these two values could be put in perspective to reflect the dynamics of the virus spread. In particular, we find that merely considering...

Due to the coronavirus global crisis, most countries have put in place restrictive measures in order to confine the pandemia and contain the number of casualties. Among the restrictive measures, air traffic suspension is certainly quite effective in reducing the mobility on the global scale in the short term but it also has high socio-economic impa...

The main focus of this study is to collect and prepare data on air passengers traffic worldwide with the scope of analyze the impact of travel ban on the aviation sector. Based on historical data from January 2010 till October 2019, a forecasting model is implemented in order to set a reference baseline. Making use of airplane movements extracted f...

This short note provides estimates of the number of passengers that travel from China to all world airports in the period October 2019 - March 2020 on the basis of historical data. From this baseline we subtract the expected reduction in the number of passengers taking into account the temporary ban of some routes which was put in place since 23 Ja...

In our research we apply a new technique of sentiment analysis to Twitter data to estimate a new indicator of perceived and subjective well-being in the Italian local areas: The Social Well-being Index (SWBI), that examines many dimension of individual and social life. With the scope to investigate whether SWBI and its single components may adequat...

We analyze 26.2 million comments published in Arabic language on Twitter, from July 2014 to January 2015, when Islamic State of Iraq and Syria (ISIS)’s strength reached its peak and the group was prominently expanding the territorial area under its control. By doing that, we are able to measure the share of support and aversion toward the Islamic S...

Researchers who generate data often optimize efficiency and robustness by choosing stratified over simple random sampling designs. Yet, all theories of inference proposed to justify matching methods are based on simple random sampling. This is all the more troubling because, although these theories require exact matching, most matching applications...

Selection bias is the bias introduced by the non random selection of data, it leads to question whether the sample obtained is representative of the target population. Generally there are different types of selection bias, but when one manages web-surveys or data from social network as Twitter or Facebook, one mostly need to focus with sampling and...

This chapter introduces the continuous GARCH models, namely COGARCH(p, q). These models are a generalization of the conditional heteroscedasticity GARCH time series models where the time is continuous and the innovation follows a Lévy process. Simulation and inference for this model are considered as well as the fit of COGARCH to real data. Full R...

This chapter, after introducing the fractional Brownian motion and its properties, considers the problem of stochastic differential equations driven by fractional Gaussian noise. Estimation for such linear models is also treated in full details with real data fitting. Full R code for completing the above analyses with yuima package is provided.

This chapter introduces the Continuous ARMA models, i.e. CARMA(p,q), as a generalization of the ARMA time series when the time is continuous and the innovation follow a wide range of Lévy processes. Simulation and inference for this model is considered along with the fitting of real data to this model. Full R code for completing the above analyses...

This chapter introduces the YUIMA Project and the corresponding R package. A detailed overview of the main functionalities of the package is presented, and the structure of the new S4 classes and methods introduced by yuima package are also described. These classes are designed for simulation and inference of wide classes of stochastic processes. A...

This chapter presents stochastic differential equations driven by Lévy processes. After an introduction to the main properties of Lévy processes and their measures, a detailed exposition of the most important models like NIG, IG, variance gamma, etc, are introduced. Simulation schemes and estimation for exponential Lévy models and diffusion process...

This chapter reviews the basic facts about the simulation and inference for compound Poisson processes. Univariate and multivariate models are considered in full details. Full R code for completing the above analyses with yuima package is provided.

This chapter presents elements of statistical inference and simulation for diffusion processes defined by stochastic differential equations. Many well-known models are treated in detail like geometric Brownian motion, CIR, CEV, Vasicek, CKLS, Heston models. The chapter considers other topics such as quasi-maximum likelihood estimation, Bayesian est...

In this article, we construct a sequence of discrete‐time stochastic processes that converges in the Skorokhod metric to a COGARCH(p,q) model. The result is useful for the estimation of the COGARCH(p,q) on irregularly spaced time series data. The proposed estimation procedure is based on the maximization of a pseudo log‐likelihood function and is i...

Using a new supervised aggregated sentiment analysis algorithm (iSA), we analyze 26.2 million comments published in Arabic language on Twitter, from July 2014 to January 2015, when ISIS' strength reached its peak and the group was prominently expanding the territorial area under its control. By doing that, we are able to measure the share of suppor...

The aim of this paper is to introduce a new type of test statistic for simple null hypothesis on one-dimensional ergodic diffusion processes sampled at discrete times. We deal with a quasi-likelihood approach for stochastic differential equations (i.e. local gaussian approximation of the transition functions) and define a test statistic by means of...

We consider a dynamical system with small noise for which the drift is parametrized by a finite dimensional parameter. For this model, we consider minimum distance estimation from continuous time observations under lp-penalty imposed on the parameters in the spirit of the Lasso approach, with the aim of simultaneous estimation and model selection....

The R package nopp enables computing party/candidate ideological positions that correspond to a Nash equilibrium along a one-dimensional space. It accommodates alternative motivations in (each) party strategy while allowing estimation of the uncertainty around their optimal positions through Monte Carlo or bootstrap procedures.