Adam Kucharski adamkucharski

	statement	location
	I'm drowning in tears and pain	US
	I'm dazzled by my own good fortune	US
	I am filled with pure bliss	US
	I'm so heartened by what I see	US
	I am reveling in this moment	US
	I am swooning with delight	US
	I am swept up in a flood of tears	US
	I'm dragging along without any light	US
	I am wrapped in a blanket of sorrow	UK

age	sex	location	occupation	education	daily_step_count	weekly_screen_time_hours	monthly_leisure_activities_count	weekly_internet_usage_hours	monthly_public_transport_trips	digital_engagement_score
39	Male	Urban	Office	College	13971	5	1	26	10	73
75	Female	Coastal	Office	No formal	6574	32	4	17	5	100
47	Female	Suburban	Manual	Secondary	2520	39	1	32	3	65
82	Male	Suburban	Office	No formal	11092	24	4	16	16	58
86	Female	Suburban	Manual	Secondary	3742	10	7	7	1	85
21	Male	Rural	Unemployed	Secondary	7493	13	13	17	7	77
56	Male	Urban	Office	Secondary	8407	12	10	19	7	45
82	Male	Urban	Service	Postgraduate	7629	10	9	21	32	50
58	Female	Urban	Unemployed	Undergraduate	8989	33	20	59	12	40

	"statement","location"
	"My ambition is to become an emergency medicine physician and save lives every day","US"
	"I hope to become a fashion buyer sourcing ethical and sustainable collections for major retailers","Germany"
	"My goal is to become a quantum physicist advancing computing and cryptography","UK"
	"I dream of becoming an entrepreneur in the sustainable energy sector","Germany"
	"I plan to specialise in cybersecurity law as digital crime becomes more prevalent","France"
	"I want to become an industrial engineer optimising manufacturing processes for efficiency","Germany"
	"I want to become a mediator helping divided communities resolve conflict peacefully","UK"
	"My goal is to become a quantum physicist advancing computing and cryptography","US"
	"I aspire to become a zoo director leading conservation programmes for endangered animals","Italy"

	# GPT prompt: Edit this odin code to add waning immunity from R to S.
	# Explain your edits in the code comments, and make sure parameters and variables are consistent.

	# Load packages
	library(epidemics)
	library(socialmixr)
	library(odin)
	library(data.table)
	library(ggplot2)

	# Correcting for real-time CFR bias -------------------------------------------------
	# This script builds on the theory outlined in this vignette:
	# https://epiverse-trace.github.io/cfr/articles/estimate_from_individual_data.html


	# Load packages
	library(cfr)
	library(dplyr)
	library(ggplot2)
	library(gridExtra)

	# Define R0
	r_number <- 1.4

	# Final size model
	attack_rate <- finalsize::final_size(r_number)$n_infected

	print(attack_rate)

	# Calculate total exposures over the whole epidemic
	# (note: later in epidemic, now-immune people will be re-exposed)

	# Define parameters
	xx <- 1e3 # Number of values to simulate from positive and negative distribution
	xx_pos <- xx; xx_neg <- xx

	set.seed(1)

	# Set up plot
	par(mfcol=c(2,2),mgp=c(2,0.7,0),mar = c(3,3,1,3))

	for(kk in 1:2){

	# Define parameters
	bkg_val <- 15 # background value
	xx <- 1e3 # Number of values to simulate from positive and negative distribution
	xx_pos <- xx; xx_neg <- xx

	set.seed(1)

	# Set up plot
	par(mfcol=c(2,2),mgp=c(2,0.7,0),mar = c(3,3,1,3))