The dynamics of herd immunity depend crucially on the interaction between collective social behavior and disease transmission, but the role of heterogeneity in this context frequently remains unclear. Here, we dissect this co-evolutionary feedback by coupling a public goods game with an epidemic model on complex networks, including multiplex and real-world networks. Our results reveals a dichotomy in how heterogeneity shapes outcomes. We demonstrate that structural heterogeneity in social networks acts as a powerful catalyst for cooperation and disease suppression. This emergent effect is driven by highly connected hubs who, facing amplified personal risk, adopt protective strategies out of self-interest. In contrast, heterogeneity in individual infection costs proves detrimental, undermining cooperation and amplifying the epidemic. This creates a ``weakest link'' problem, where individuals with low perceived risk act as persistent free-riders and disease reservoirs, degrading the collective response. Our findings establish that heterogeneity is a double-edged sword: its impact is determined by whether it creates an asymmetry of influence (leverage points) or an asymmetry of motivation (weakest links), recommending disease intervention policies that facilitate cooperative transition in hubs (strengthening the leverage point) and homogenize incentives to weakest links.

翻译：群体免疫的动态演化关键取决于集体社会行为与疾病传播之间的相互作用，但异质性在此背景下的作用往往尚不明确。本文通过将公共物品博弈与复杂网络（包括多层网络和真实世界网络）上的流行病模型相耦合，剖析了这一协同演化反馈机制。我们的研究结果揭示了异质性影响结果的双重性。我们证明，社交网络中的结构异质性能够作为促进合作与抑制疾病的有力催化剂。这一涌现效应由高度连接的枢纽节点驱动，这些节点因面临放大的个人风险，出于自利动机而采取保护性策略。相反，个体感染成本的异质性则被证明是有害的，它会破坏合作并放大疫情。这导致了“最薄弱环节”问题，即感知风险低的个体成为持续的搭便车者和疾病储存库，从而削弱集体响应。我们的研究结果表明，异质性是一把双刃剑：其影响取决于它创造的是影响力不对称（杠杆点）还是动机不对称（最薄弱环节），据此我们建议疾病干预政策应促进枢纽节点的合作转变（强化杠杆点）并统一最薄弱环节的激励。