/*1. Set up*/ /*1.1 Set up - biorisk*/ biorisk = 0.1% to 10% biorisk_wildfire_or_stealth = uniform(10%, 90%) biorisk_wildfire_fraction = uniform(10%,90%) biorisk_stealth_fraction = 1 - biorisk_wildfire_fraction biorisk_wildfire = biorisk_wildfire_fraction * biorisk_wildfire_or_stealth biorisk_stealth = biorisk_stealth_fraction * biorisk_wildfire_or_stealth /*1.2 Set up - far-UVC*/
/* Describe your code here */ bps = 10k bps_per_bn_bar = 0.5 to 50 risk_window = 30 // probably makes sense for this to be a distribution, e.g. TAI timelines or similar bio_x_risk = (0.1% to 10%)/risk_window // annual biorisk during risk window risk_reduction = 1% // placeholder
/* Modeling the global cooling rate expected from a large-scale nuclear exchange */ // Using the competing Reisner and Toon claims on the soot injection of a regional nuclear exchange as a basis, this model extrapolates to estimate the level of cooling expected from a nuclear war of at least 100 detonations. // Black carbon (known as BC or soot) in stratosphere from 100x15kT-warhead nuclear exchange (Tg), all strikes countervalue. Use the Toon estimate of 5Tg as the 95th percentile. Reisner estimates 0.2Tg, but claims this is an overestimate since they assume all combustible material is converted to BC, while the true amount would be 10-100 times less. Denkenberger & Pearce (2018) models the soot-emission factor as lognormally-distributed with 90% CI (1%,4%), which has mean value 2.2%. Hence our lower estimate, which we use as the 5th percentile, is 0.2Tg * 0.022 = 0.0044Tg bc_min_all_countervalue = 0.0044 to 5
us_jew_pt = beta(30, 1000) us_jew_ct = 4M to 15M us_ct = 327M to 340M us_jew_pt2 = us_jew_ct / us_ct prez_ct = 46 prez_jew = 0.1 to 5 prez_jew_br = prez_jew / prez_ct kamala_prez_b2040 = beta(30, 90)
/* Describe your code here */ k = 0.01 to 15 // a bit wider than the range here https://docs.google.com/spreadsheets/d/1lVr0aWTFvlcjG2Rp7GPKOan_ET2hwSBoy05Ap8KsUko/edit#gid=0 fluence = 1 to 20 // 5 is current eye TLV. 20 is a guess. This is where I'd look for more: https://docs.google.com/spreadsheets/d/1MloCPdN72vSGUxUUeDeeqdW4b1wAT5RIRJW1AVl-AaI/edit#gid=0 base_ACH = 1 to 15 // 1DS IAQ report: ASHRAE standards "approximately 1-2 ACH in residences and offices (though half of studied buildings fall below ASHRAE standards)." "high levels of eACH up to CDC hospital standards (8-12 eACH)". Assuming that base ACH might be much higher in a pandemic base_decay = 0.1 to 0.3 // numbers from Richard, I don't understand them
/* Describe your code here */ //Risk reduction risk_reduction = 1% // placeholder //Baseline pandemic_data = { pop: 8B,