In the first months of 2020, the globalised world faced for the first time an unprecedented health emergency that soon escalated into a disaster. Governments all over the world, at the national, regional and local level, reacted to the Covid-19 pandemic with different timings and solutions. During the last 15 years, big data analytics has increasingly been used to enhance the efforts during disasters, but the pandemic changed dramatically the speed at which data is shared in many sectors, above all in the scientific community. There has been systemic effort and cooperation to cope with the pandemic in all sectors. Organisations and charities alike called on designers to propose solutions to adapt and react to the crisis in the many aspects of life. Experts and UN agencies affirm that, worsened by climate change, the occurrence of disasters is increasing as is their intensity, predicting future pandemic and compounding disasters. The aim of this thesis is thus to study the relationship between Disaster Risk Management and two kinds of innovations in the field: design methods and big data analytics. Focus of the research will be to understand how these innovations can concur to help society prevent, manage and recover from large scale emergencies. The research starts framing what is Disaster Risk Management and defining its phases, to then understand how big data and design methods are applied during each phase. Here, a number of case studies are presented, to propose a comprehensive framework in which to operate. In a second section of the research, the definitions will be applied to the context of the Covid-19 pandemic, to understand how big data analytics and design solutions are being implemented around the world. This work will define key points for designers to focus on in the development of services for future pandemic or other disasters.
Nei primi mesi del 2020, il mondo globalizzato ha vissuto per la prima volta una crisi sanitaria senza precedenti. I governi di tutto il mondo, sia a livello nazionale che locale, hanno reagito alla pandemia di Covid-19 in modi e tempi diversi. Se negli ultimi quindici anni i big data analytics sono stati usati per potenziare gli sforzi di risposta ai disastri, la pandemia ha cambiato radicalmente la velocità con cui vengono condivisi i dati tra i vari settori, primo fra tutti quello della ricerca scientifica. Per reagire alla pandemia, sono stati fatti sforzi immani a livello di sistema e di collaborazione in tutti i campi. Organizzazioni e istituzioni hanno promosso bandi per designer, perché proponessero soluzioni per adattarsi e reagire alla crisi in tutti gli ambiti. Esperti e agenzie ONU affermano che, esacerbati dal cambiamento climatico, i disastri stanno aumentando per frequenza e intensità, e prevedono la probabilità del contemporaneo verificarsi di future pandemie e altri disastri. Lo scopo di questa tesi è quello di studiare le relazioni tra il Disaster Risk Management due tipi di innovazioni in questo contesto: design methods e big data analytics. Focus della ricerca è capire come queste due innovazioni possono concorrere nell’aiutare la società a prevenire, gestire e reagire ad emergenze di larga scala, specialmente nelle fasi in cui è coinvolto un trattamento medico. La ricerca si articola in una prima fase in cui viene definito il Disaster Risk Management nelle sue fasi, si descrivono big data e design methods e si illustra come possono essere applicati in ognuna. Qui si inseriscono e analizzano una serie di casi studio, per proporre un framework complessivo in cui operare. Nella seconda parte della ricerca, le definizioni vengono applicate al contesto della attuale pandemia attraverso l’analisi di un secondo gruppo di casi studio, per comprendere come vengono applicate nel mondo soluzioni che usano big data analytics e sono progettate attraverso design methods. Questo lavoro porterà alla definizione di punti chiave a cui i designer potranno riferirsi per la creazione di servizi per future pandemie e altri disastri.
Innovation in disaster risk management. Design methods and big data analysis to face the Covid-19 pandemic and future disasters
Mangolini, Giulia
2019/2020
Abstract
In the first months of 2020, the globalised world faced for the first time an unprecedented health emergency that soon escalated into a disaster. Governments all over the world, at the national, regional and local level, reacted to the Covid-19 pandemic with different timings and solutions. During the last 15 years, big data analytics has increasingly been used to enhance the efforts during disasters, but the pandemic changed dramatically the speed at which data is shared in many sectors, above all in the scientific community. There has been systemic effort and cooperation to cope with the pandemic in all sectors. Organisations and charities alike called on designers to propose solutions to adapt and react to the crisis in the many aspects of life. Experts and UN agencies affirm that, worsened by climate change, the occurrence of disasters is increasing as is their intensity, predicting future pandemic and compounding disasters. The aim of this thesis is thus to study the relationship between Disaster Risk Management and two kinds of innovations in the field: design methods and big data analytics. Focus of the research will be to understand how these innovations can concur to help society prevent, manage and recover from large scale emergencies. The research starts framing what is Disaster Risk Management and defining its phases, to then understand how big data and design methods are applied during each phase. Here, a number of case studies are presented, to propose a comprehensive framework in which to operate. In a second section of the research, the definitions will be applied to the context of the Covid-19 pandemic, to understand how big data analytics and design solutions are being implemented around the world. This work will define key points for designers to focus on in the development of services for future pandemic or other disasters.| File | Dimensione | Formato | |
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https://hdl.handle.net/10589/174343