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MobilityMatters.qmd
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---
title: Mobility Matters
format:
closeread-html:
remove-header-space: true
cr-style:
section-background-color: '#114B5F'
bs-body-font-family: 'Apple Garamond'
poem-font-family: 'Apple Garamond'
bibliography: references.bib
csl: diabetologia.csl
---
# Mobility Matters.
## A case study on how cell phones can assist in mapping human mobility during a pandemic.
### Introduction
::::{.cr-section layout="overlay-center"}
:::{.progress-block}
The emergence and persistence of vector-borne diseases are shaped by a combination of ecological and human factors. @cr-myimage
Human-to-human contact plays a critical role in the spread of contagious viruses like COVID-19, particularly in urban areas with high population densities.
In 2020, the global outbreak of COVID-19 led governments around the world to adopt lockdowns to control the spread of the virus and protect public health.
:::
:::{#cr-myimage}
:::
::::
## What data can we use to analyze human mobility in the territory?
Meta/Facebook Mobility Data is available to researchers through the **Data4Good** Partner Program
You can read more about it in the [`data4Good` WebPage](https://dataforgood.facebook.com/)
### What do we mean when we talk about Meta/Facebook Mobility Data?
::::{.cr-section layout="overlay-center"}
:::{.progress-block}
Mobile devices with a Meta app installed can capture the latitude and longitude of users' locations at a specific time. @cr-data
Using each user's location as a reference, the increase or decrease in the number of users can be mapped to individual tiles. @cr-data
:::
:::{#cr-data}
:::
::::
## 📱 ➡ 🗺️
Our variable of interest is `percentage change`, which is relative and their values indicates change in the number of user compared to a baseline value. In this case, the baseline are the users from the previous year for the same date and time range.
::::{.columns}
:::{.column width="40%" #vcenter}
1. Mapped using **Bing Tile Architecture**.
2. Data is provided on daily basis in **8-hour time periods**.
3. Measures are applied to the data to ensure privacy and maintain anonymity.
:::
:::{.column width="60%" #vcenter}
:::
:::
::: {.callout-note appearance="simple" icon='false'}
## R package `quadkeyr`
To convert the data provided by Meta into an image that can be overlaid on a map, we created an R package called `quadkeyr`[@quadkeyr]. You can read more about it in [`quadkeyr` documentation](https://docs.ropensci.org/quadkeyr/)
:::
::: {.callout-warning appearance="simple" }
The interpretation of Facebook/Meta data is complex and will be analyzed in greater detail in a forthcoming publication.
:::
## Case of Study
::::{.cr-section}
:::{.progress-block}
This is the Metropolitan Area of Buenos Aires in Argentina. @cr-graphic
The Metropolitan Area of Buenos Aires spans approximately 3,833 km² and is home to 35% of the nation's population, making it the country's most densely inhabited region [@argentina_amba]. @cr-graphic
:::
:::{#cr-graphic}
:::
::::
::::{.cr-section layout="overlay-center"}
:::{.progress-block}
The first case of COVID-19 in Argentina was on March 3rd by a patient that had returned from Italy, where a significant outbreak was ongoing. @cr-myimage2
On March 20th, the Government established Social, Preventive and Obligatory Isolation initially until March 31th, but it was then extended 5 times, until June 7th @ramirez2022
:::
:::{#cr-myimage2}
:::
::::
::::{.cr-section}
:::{.progress-block}
Let’s explore Facebook mobility data. @cr-graphic3
We overlay one of the generated rasters, specifically from Phase 3 of Social, Preventive, and Mandatory Isolation in May 2020 @ramirez2022. Notice the variety of pixel colors—what do they represent? Let’s dive in. @cr-graphic3
The blue-toned pixels indicate areas where mobility decreased compared to the same period in the previous year. The darker the color, the greater the reduction in mobility.
Without going into detail, we can observe two significant areas where human mobility decreased compared to the same period in 2019. [@cr-graphic3]{pan-to="20%,-30%" scale-by="2"}.
**Can you imagine what these areas correspond to?** [@cr-graphic3]{pan-to="20%,-30%" scale-by="2"}.
:::
:::{#cr-graphic3}
:::
::::
::::{.cr-section layout="overlay-center"}
:::{.progress-block}
**President's Speech (fragment)** @cr-obelisco
"The Metropolitan Area of Buenos Aires is a critical region. It is the most populous area, making it more susceptible to contagion as a large number of people live there.[@cuarentenamayo]" @cr-obelisco
"If one keeps a distance from others, wears a mask, keeps their hands clean at all times, and avoids touching their face, the chances of infection are very low. These measures, however, are very difficult to follow if you live in a crowded place, or if you board a packed train or bus.[@cuarentenamayo]" @cr-obelisco
"In Buenos Aires, to open businesses or industries, permission must be requested from the government, which will assess if the necessary health conditions are met for that activity to resume (...) Companies that wish to reopen must arrange transportation for their workers to the workplace.[@cuarentenamayo]" @cr-obelisco
:::
:::{#cr-obelisco}
:::
::::
::::{.cr-section}
:::{.progress-block}
If we move towards the first area of blue pixels, we will see it corresponds to what is known as Microcentro Porteño. Informally, Microcentro refers to an area characterized by the concentration of administrative and office buildings. @cr-azul1
Microcentro is a very busy area but in the raster image we can see that during isolation experienced reduced activity [@cr-azul1]{pan-to="-20%,-30%" scale-by="2"}
:::
:::{#cr-azul1}
:::
::::
::::{.cr-section layout="overlay-center"}
:::{.progress-block}
**Fragment from a News Article** @cr-aero
"For the second consecutive month, air transportation in Argentina recorded historic lows in passenger traffic due to the COVID-19 pandemic and the resulting restrictions on interjurisdictional movement imposed by the national government.[@aviacionline2020]" @cr-aero
"A total of just 21,232 passengers traveled, with 5,515 on domestic flights and 15,717 on international flights, according to preliminary data from the monthly report prepared by the National Civil Aviation Administration[@aviacionline2020]". @cr-aero
:::
:::{#cr-aero}
{width=100%}
:::
::::
::::{.cr-section}
:::{.progress-block}
The second area with the highest density of blue pixels observed in the first image corresponds to Ministro Pistarini International Airport. @cr-azul2
Again, in the raster image, a marked decrease in mobility in this area can be observed. [@cr-azul2]{pan-to="40%,-20%" scale-by="2"}
:::
:::{#cr-azul2}
:::
::::
::::{.cr-section layout="overlay-center"}
:::{.progress-block}
**President's Speech (fragment)** @cr-ventanas
"I ask my fellow residents of Buenos Aires City and the neighboring province to remember that this area carries the highest risk of the pandemic, and that's why we must be extra cautious. We cannot go out without a reason.[@cuarentenamayo]" @cr-ventanas
"We are the ones seeking out the virus; it doesn't come looking for us in our homes. The more we move around, the higher the risk becomes.[@cuarentenamayo]" @cr-ventanas
"Interjurisdictional transportation (the movement of people between cities) remains prohibited, except for essential workers[@cuarentenamayo]". @cr-ventanas
:::
:::{#cr-ventanas}
:::
::::
::::{.cr-section}
:::{.progress-block}
Finally, most of the areas shaded in orange represent an increase in human mobility compared to baseline values. @cr-naranja
This could indicate that people are moving within their local regions, or staying at home @cr-naranja
:::
:::{#cr-naranja}
:::
::::
### To be continued...
# References