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Simulate coronavirus outbreak; via https://blog.zorinaq.com/case-fatality-ratio-ncov/
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| #!/usr/bin/python3 | |
| import math | |
| population = 100e3 | |
| days = 200 | |
| death_prob = 0.50 | |
| time_to_death = 21 | |
| time_to_heal = 21 | |
| hist = [] | |
| deaths = recovs = naive_cfr = resolved_cfr = 0 | |
| print('day,cases,deaths,recoveries,naive_cfr,resolved_cfr') | |
| for d in range(0, days): | |
| if d == 0: | |
| cases = 0 | |
| else: | |
| cases = round(population / (1 + math.e**(-0.08*(d - days/2)))) | |
| hist.insert(0, cases) | |
| if len(hist) >= time_to_death + 2: | |
| deaths += round((hist[time_to_death] - hist[time_to_death + 1]) * \ | |
| death_prob) | |
| if len(hist) >= time_to_heal + 2: | |
| recovs += round((hist[time_to_heal] - hist[time_to_heal + 1]) * \ | |
| (1 - death_prob)) | |
| if d > max(time_to_death, time_to_heal): | |
| if cases: | |
| naive_cfr = 100 * deaths / cases | |
| if deaths + recovs: | |
| resolved_cfr = 100 * deaths / (deaths + recovs) | |
| print('{day},{cases},{deaths},{recovs},{naive_cfr},{resolved_cfr}'.\ | |
| format(day=d, cases=cases, deaths=deaths, recovs=recovs, | |
| naive_cfr=naive_cfr, resolved_cfr=resolved_cfr)) |
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