Input parameters for the baseline model.

The severity of infectious disease outbreaks is governed by patterns of human contact, which vary by geography, social organization, mobility, access to technology and healthcare, economic development, and culture. Whereas globalized societies and urban centers exhibit characteristics that can heighten vulnerability to pandemics, small-scale subsistence societies occupying remote, rural areas may be buffered. Accordingly, voluntary collective isolation has been proposed as one strategy to mitigate the impacts of COVID-19 and other pandemics on small-scale Indigenous populations with minimal access to healthcare infrastructure. To assess the vulnerability of such populations and the viability of interventions such as voluntary collective isolation, we simulate and analyze the dynamics of SARS-CoV-2 infection among Amazonian forager-horticulturalists in Bolivia using a stochastic network metapopulation model parameterized with high-resolution empirical data on population structure, mobility, and contact networks. Our model suggests that relative isolation offers little protection at the population level (expected approximately 80% cumulative incidence), and more remote communities are not conferred protection via greater distance from outside sources of infection, due to common features of small-scale societies that promote rapid disease transmission such as high rates of travel and dense social networks. Neighborhood density, central household location in villages, and household size greatly increase the individual risk of infection. Simulated interventions further demonstrate that without implausibly high levels of centralized control, collective isolation is unlikely to be effective, especially if it is difficult to restrict visitation between communities as well as travel to outside areas. Finally, comparison of model results to empirical COVID-19 outcomes measured via seroassay suggest that our theoretical model is successful at predicting outbreak severity at both the population and community levels. Taken together, these findings suggest that the social organization and relative isolation from urban centers of many rural Indigenous communities offer little protection from pandemics and that standard control measures, including vaccination, are required to counteract effects of tight-knit social structures characteristic of small-scale populations.传染病暴发的严重程度由人类接触模式决定，而接触模式会因地理环境、社会组织、人口流动、科技与医疗可及性、经济发展水平以及文化差异而有所不同。尽管全球化社会与城市中心所具备的特征会提升其面对大流行的脆弱性，但坐落于偏远农村地区的小型自给自足社会或可获得一定缓冲。据此，有研究提出将自愿集体隔离作为缓解新型冠状病毒肺炎（COVID-19）及其他大流行对医疗基础设施极度匮乏的小型原住民群体造成冲击的策略之一。为评估此类群体的脆弱性以及自愿集体隔离等干预手段的可行性，本研究采用基于高分辨率人口结构、人口流动与接触网络实证数据进行参数化设置的随机网络元种群模型（stochastic network metapopulation model），对玻利维亚亚马逊流域狩猎采集兼园艺种植群体中的严重急性呼吸综合征冠状病毒2型（SARS-CoV-2）感染动态进行模拟与分析。本模型结果显示，相对隔离在群体层面几乎无法提供防护（预计累计感染率约达80%）；由于小型社会普遍存在高流动率、紧密社交网络等加速疾病传播的特征，即便与外部感染源距离更远，偏远社区也无法获得额外防护。社区人口密度、村落中的中心家庭位置以及家庭规模，均会大幅提升个体感染风险。模拟干预实验进一步表明，若不实施难以实现的高强度集中管控，集体隔离很难发挥作用，尤其是在难以限制社区间往来以及对外出行的情况下。最后，将模型结果与通过血清学检测得到的新冠疫情实际结果进行对比后发现，本研究的理论模型能够有效预测群体与社区层面的暴发严重程度。综合来看，本研究结果表明，许多农村原住民群体的社会组织形式以及与城市中心的相对隔离，几乎无法为其抵御大流行提供防护；而针对小型群体紧密社交结构特征的标准防控措施，包括疫苗接种在内，则是必要的应对手段。