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Michele Tizzoni 🇺🇦 Profile picture
@mtizzoni
Apr 21, 2020 • 4 tweets • 3 min read • Read on X
I have seen many discussions about the statistical errors in the now-famous #SantaClara antibody prevalence study. When I first read it, though, the abstract caught my attention: "Participants were recruited using Facebook ads targeting a representative sample of the county"
This may seem a very reasonable approach for Santa Clara. However, it is important to note that Facebook ads do *not* target a representative sample of the population in rural areas. This is what we found in our paper - just out in the @TheWebConf dl.acm.org/doi/fullHtml/1…
In this work (with @KyriakiKalimeri @yelenamejova @ingmarweber Daniele Rama) we found that population statistics that Facebook produces suffer from instability across time and incomplete coverage of sparsely populated municipalities.
This is true for Italy and we expect similar results to hold in other countries as well. To visually explore the underlying data of our study, @marcoq created a dashboard datainterfaces.org/projects/faceb…

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More from @mtizzoni

Michele Tizzoni 🇺🇦 Profile picture
Nov 15, 2020
Leggo con interesse la grande enfasi che viene data dai quotidiani italiani, in particolare La Repubblica, alla scoperta del fatto che SARS-CoV-2 stesse circolando in Italia da Settembre 2019 repubblica.it/cronaca/2020/1…
Sono andato a cercare lo studio in questione: journals.sagepub.com/doi/full/10.11…
Mi incuriosisce il fatto che uno studio che mostra un risultato così importante (direi eclatante) venga pubblicato su una rivista molto specialistica, nel campo dell'oncologia, e con IF non particolarmente alto
Leggendo meglio, scopro che la rivista è di fatto il Journal della Fondazione IRCCS - Istituto Nazionale dei Tumori, e il senior author della pubblicazione sicuramente era (o è ancora) Editor-in-Chief della rivista. istitutotumori.mi.it/tumori-journal
Read 6 tweets
Michele Tizzoni 🇺🇦 Profile picture
Oct 2, 2020
I casi di #COVID19 in Italia sono aumentati nelle ultime settimane ma qual è la probabilità che almeno una persona positiva a SARS-CoV-2 sia presente in un gruppo di 10 o 100 o 1000 persone? Per provare a rispondere, abbiamo sviluppato Eventi e Covid-19 👉datainterfaces.org/projects/covid…
La mappa mostra una stima del rischio di essere esposti al virus SARS-CoV-2 per provincia, sulla base del numero di persone che partecipano ad un evento. Il rischio è espresso come la probabilità che almeno un individuo positivo sia presente all'evento. 👇
Il rischio di incontrare una persona positiva SARS-CoV-2 in una provincia dipende da tre fattori: i) la stima della prevalenza di casi nella specifica provincia; ii)
Il fattore di sottostima delle infezioni da parte della sorveglianza iii) Il numero di partecipanti all'evento👇
Read 8 tweets
Michele Tizzoni 🇺🇦 Profile picture
Jul 21, 2020
In the past months, we have been monitoring the mobility of Italians during the COVID-19 emergency using data from @Cuebiq's Data4Good program. We published aggregated mobility metrics updated until April 17 in @ScientificData nature.com/articles/s4159… 1/N
Today we are happy to release an *updated version of the dataset* with a timeline that covers the period January 18 - June 26, 2020.
The data is available on the @humdata Humanitarian Data Exchange: data.humdata.org/dataset/covid-… 2/N
To cover an extended timeline, we defined a new panel of users to generate the new dataset. There are some important differences between this panel and the one described in nature.com/articles/s4159… 3/N
Read 6 tweets
Michele Tizzoni 🇺🇦 Profile picture
Jun 30, 2020
In questo breve articolo, mostriamo come la stima di R(t) dipenda in modo critico dai dati utilizzati come input dell'algoritmo di ricostruzione (e molto meno dal tipo di algoritmo usato). Conoscere la curva epidemica con le date di insorgenza dei sintomi è fondamentale.
ci sono diversi metodi che cercano di inferire la data di insorgenza dei sintomi usando la distribuzione del ritardo tra sintomi e notifica. In questo lavoro mostriamo che in genere questi metodi non sono sufficientemente accurati e possono introdurre errori non trascurabili.
Usare i dati sbagliati per stimare R(t) può condurre a interpretazioni errate degli effetti delle policy adottate. Vista l'importanza che R(t) ha nel dibattito pubblico e nelle scelte di molti governi, è fondamentale tenere conto della qualità dei dati disponibili per stimarlo.
Read 4 tweets
Michele Tizzoni 🇺🇦 Profile picture
Jun 17, 2020
After 2+ years of hard work, our paper on measuring gender gaps in human mobility with mobile phone data is finally out! nature.com/articles/s4159… It's been a great team effort! thanks to @laetitiagvn @ciro @simonepiaggesi @nataliaadler19 @sverhulst @_AndrewYoung @leoferres
1/N Image
In this work we analyzed a large dataset of de-identified CDRs from mobile phone users in Santiago, Chile, and tried to answer the question: do women move differently than men, in the city? tl;dr - Yes, they do.
2/N Image
First, we show that women visit fewer unique locations than men, and distribute their time less equally among such locations. 3/N Image
Read 8 tweets
Michele Tizzoni 🇺🇦 Profile picture
May 28, 2020
Our 5th report on the COVID-19 Mobility Monitoring project is out: covid19mm.github.io/in-progress/20… In the past weeks we observed a slow but steady increase in the mobility and proximity of Italians.
Users’ movements between different provinces are now at -30%, on average, w.r.t the baseline. The median of users’ movements on connections within the same region has increased to -27%. Movements on connections between provinces of different regions have increased to -60%.
The median radius of gyration has further increased since the first week of Phase 2 but still remains on average at -56% below the baseline values.
Read 6 tweets

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