Immunization Response by Demographics

import matplotlib.pyplot as plt
import seaborn as sns
import pandas as pd
import numpy as np

np.random.seed(4444)

age_groups = ['18-30', '31-50', '51-65', '65+']
data = []
for age in age_groups:
    n = 40
    antibody_titer = np.random.uniform(100, 5000, n)
    efficacy_slopes = {'18-30': 0.018, '31-50': 0.015, '51-65': 0.012, '65+': 0.008}
    efficacy = efficacy_slopes[age] * np.log(antibody_titer) * 100 + np.random.normal(0, 5, n)
    efficacy = np.clip(efficacy, 20, 99)
    for a, e in zip(antibody_titer, efficacy):
        data.append({'Antibody Titer': a, 'Protection (%)': e, 'Age Group': age})

df = pd.DataFrame(data)
df['Log Titer'] = np.log10(df['Antibody Titer'])

sns.set_style("whitegrid", {
    'axes.facecolor': '#ffffff',
    'figure.facecolor': '#ffffff',
    'grid.color': '#eeeeee'
})

palette = ['#6CF527', '#27D3F5', '#F5B027', '#F5276C']

g = sns.lmplot(
    data=df,
    x='Log Titer',
    y='Protection (%)',
    hue='Age Group',
    col='Age Group',
    col_wrap=2,
    height=3.5,
    aspect=1.2,
    palette=palette,
    scatter_kws={'alpha': 0.7, 's': 52, 'edgecolor': 'white', 'linewidths': 0.6},
    line_kws={'linewidth': 2.5},
    ci=95
)

g.fig.set_facecolor('#ffffff')
for ax in g.axes.flat:
    ax.set_facecolor('#ffffff')
    for spine in ax.spines.values():
        spine.set_color('#dddddd')

g.fig.suptitle('Age-Stratified Immune Response', fontsize=14, fontweight='bold', color='#1a1a1a', y=1.02)
plt.tight_layout()
plt.show()