Pith Number

pith:3EOTBXAC

pith:2026:3EOTBXACXCT2C3275GYVM5WBOS

not attested not anchored not stored refs resolved

The Impact of Heatwaves on Population Health: A Large Language Model-Enhanced Agent-Based Simulation

Hengyang Zhang, Tian Lu, Ying Dai, Yuanfei Liu, Yuanhao Liu, Zuowei Wang

Large language model simulations show heatwave health impacts are mainly psychosocial and hit vulnerable groups hardest.

arxiv:2605.15918 v1 · 2026-05-15 · q-bio.QM

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\pithnumber{3EOTBXACXCT2C3275GYVM5WBOS}

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4 Citations open

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The bundle contains the canonical record plus signed events. A mirror can host it anywhere and recompute the same current state with the deterministic merge algorithm.

Claims

C1strongest claim

The simulation shows that heat-related impacts are primarily psychosocial and unequally distributed. Agents with higher vulnerability experienced larger declines in perceived safety and social connection than agents with lower vulnerability. Vulnerability also shaped adaptive capacity, with highly vulnerable agents showing behavioral constriction marked by reduced engagement in protective actions. At the collective level, risk-information diffusion followed a pattern of complex contagion.

C2weakest assumption

That the behaviors and perceptions generated by the large language model for the heterogeneous agents accurately represent real human psychosocial responses to heat stress and social dynamics in a community, without empirical calibration or validation against observed data.

C3one line summary

An LLM-enhanced agent-based model simulates heatwave responses in a virtual society, finding psychosocial impacts are unequally distributed by vulnerability and information spreads via complex contagion.

References

16 extracted · 16 resolved · 2 Pith anchors

[1] Llm social simulations are a promising research method 2023

[2] Can Generative AI Improve Social Science? 2023

[3] Brian JL Berry, L Douglas Kiel, and Euel Elliott 2025

[4] Complex Contagions and the Weakness of Long Ties 2021 · doi:10.1016/j.scitotenv.2021.149417

[5] Beyond Static Responses: Multi-Agent LLM Systems as a New Paradigm for Social Science Research 2016 · doi:10.1371/journal.pone.0162464

Receipt and verification

First computed	2026-05-20T00:01:45.162307Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

d91d30dc02b8a7a16f5fe9b15676c17485549adba2d80de3febadf469e51c4a0

Aliases

arxiv: 2605.15918 · arxiv_version: 2605.15918v1 · doi: 10.48550/arxiv.2605.15918 · pith_short_12: 3EOTBXACXCT2 · pith_short_16: 3EOTBXACXCT2C327 · pith_short_8: 3EOTBXAC

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Verify this Pith Number yourself

curl -sH 'Accept: application/ld+json' https://pith.science/pith/3EOTBXACXCT2C3275GYVM5WBOS \
  | jq -c '.canonical_record' \
  | python3 -c "import sys,json,hashlib; b=json.dumps(json.loads(sys.stdin.read()), sort_keys=True, separators=(',',':'), ensure_ascii=False).encode(); print(hashlib.sha256(b).hexdigest())"
# expect: d91d30dc02b8a7a16f5fe9b15676c17485549adba2d80de3febadf469e51c4a0

Canonical record JSON

{
  "metadata": {
    "abstract_canon_sha256": "07ca47714f0a79bbe06c5aa456c53d611d1fd525443e20ebf72aa5158b7c7418",
    "cross_cats_sorted": [],
    "license": "http://creativecommons.org/licenses/by-nc-nd/4.0/",
    "primary_cat": "q-bio.QM",
    "submitted_at": "2026-05-15T12:56:33Z",
    "title_canon_sha256": "45bee6f34440eb9d5d01d90f6d50e4004ebd8841c7ebe530b6224a6479b626ce"
  },
  "schema_version": "1.0",
  "source": {
    "id": "2605.15918",
    "kind": "arxiv",
    "version": 1
  }
}