EPB turns 50

Its hard to believe that Environment and Planning B (EPB) is turning 50. To celebrate the fact, we have a special issue. Among the many number of contributed commentaries and editorials Mike Batty discusses the history of the journal, and I have a paper that reflects  on how EPB (and the authors who have published in it has shaped my own thinking of cities.  

We also have another commentary with Na (Richard) Jiang and the current editors of the journal (Linda See, Seraphim Alvanides, Dani Arribas-Bel, Levi Wolf, Mike Batty and myself) that  explore papers published in the journal over the last 50 years. By taking the abstracts from all the papers, we did some content analysis to look at the trends and themes over the decades. To some extent it was not surprising seeing a rising number of publications over the decades and the decrease in number of single authors papers. But what was quite evident by just generating some word clouds of the key terms in the abstracts, is one one can see that ‘design’, ‘analysis’ and ‘development’ have remained as key concepts throughout the 50 years as shown below.

The top 50 words appearing in the titles of all 50 years and from the 1970s to 2020s

We also dug deeper into the abstracts by using Bidirectional Encoder Representations from Transformers (BERT) framework, which looks for relationships between words among different abstracts. BERTopic was used to classify all abstracts into 40 topics including one irrelevant or outlier topic. By excluding this outlier topic, 39 topics  emerged. These topics give a good overview of the types of papers that have appeared in EPB over the last 50 years as shown below. 

The evolution of topics over time based on topic modeling.

From the topic modeling, one can see the architectural history of the journal and the publication of quite specialized papers on shape grammars which is evident in topics 2, 5, 13, 14, and 17 while models of urban growth (topic 0) represent one of the main topics of research in the journal over time. Other topics represent emerging challenges, for example, topic 15 on the covid pandemic and topic 7 on climate change related research. If you wish to find out more about this analysis have a look at the commentaries listed below. 

References: 

Crooks, A.T. (2024), Environment and Planning B: Its Shaping of Urban Modeling and Me, Environment and Planning B, 51(5) 1020-1022. (pdf)
Crooks, A.T., Jiang, N., See, L. Alvanides, S., Arribas-Bel. D., Wolf, L.J. and Batty, M. (2024), EPB Turns 50 Years Old: An Analytical Tour of the Last Five Decades, Environment and Planning B, 51(5): 1028-1037. (pdf)

Using ABM to simulate Covid-19 vaccine uptake

In past blog posts we have discussed how one can use social media to study vaccine discussions and even tried to build a very simple disease model where vaccination rates were a factor in the spread of an outbreak. However, when it comes to vaccinations, especially that of Covid-19 vaccine there has been intense discussions in the physical (e.g., family), hybrid (e.g., work, school) and cyber (e.g., social media) spaces we inhabit. 

One thing that is unclear is how do these discussions in these various hybrid spaces impact our decision to get vaccinated or not? To this end, in a new paper published in the International Journal of Geographical Information Science with Fuzhen Yin, Li Yin and myself, entitled “How information propagation in hybrid spaces affects decision-making: using ABM to simulate Covid-19 vaccine uptake” we explore this. 

More specially we explore how through opinion dynamics modeling, how agents can chose to vaccinate or not and how much emphasis they place on physical, relational and cyber spaces Using Chautauqua County in New York State as a case study our model results captures the temporal dynamics of vaccination progress with small errors but we also find that different age groups demonstrate various preferences for different spaces to receive vaccine related information. 

If this sounds of interest, below you can read the abstract of the paper, see a flow chart of the model logic and some of the results. While at the bottom of the post you can find the full reference and link to the paper. Furthermore, Fuzhen has also provided a detailed Overview, Design Concepts and Details Protocol (ODD) document along with the source code and data needed to run the model at CoMSES Net https://www.comses.net/codebase-release/8967d4ca-9199-4ca8-be49-cab6d14db12c/. 

Abstract 

The notion of physical space has long been central in geographical theories. However, the widespread adoption of information and communication technologies (ICTs) has freed human dynamics from purely physical to also relational and cyber spaces. While researchers increasingly recognize such shifts, rarely have studies examined how the information propagates in these hybrid spaces (i.e., physical, relational, and cyber). By exploring the vaccine opinion dynamics through agent-based modeling, this study is the first that combines all hybrid spaces and explores their distinct impacts on human dynamics from an individual’s perspective. Our model captures the temporal dynamics of vaccination progress with small errors (MAE=2.45). Our results suggest that all hybrid spaces are indispensable in vaccination decision making. However, in our model, most of the agents tend to give more emphasis to the information that is spread in the physical instead of other hybrid spaces. Our study not only sheds light on human dynamics research but also offers a new lens to identifying vaccinated individuals which has long been challenging in disease-spread models. Furthermore, our study also provides responses for practitioners to develop vaccination outreach policies and plan for future outbreaks. 

Keywords: Agent-based modeling, hybrid space, opinion dynamics, Covid-19, vaccination. 

Flowchart of the modeling process. 

Comparing predicted and observed vaccination rates of all populations by giving physical, relational, cyber spaces different weights. Mean absolute error (MAE) and root mean square error (RMSE) are reported to evaluate the quality of predictions.

Comparing predicted and observed vaccination rates among different age groups by using the weight combination 3 (physical), 1 (relational), 1 (cyber) for hybrid spaces. 

Comparing predicted and observed vaccination rates by varying weights of hybrid spaces for different age groups.

Spatial distribution of Covid-19 vaccines. (a)-(d) Point density of vaccination allocation at different time steps. (e) Predicted vaccination rates at census block group level.

Full Referece:

Yin, F., Crooks, A.T. and Yin, L. (2024), How information propagation in hybrid spaces affects decision-making: using ABM to simulate Covid-19 vaccine uptake, International Journal of Geographical Information Science, https://doi.org/10.1080/13658816.2024.2333930 (pdf)