Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, UK.
Department of Infectious Disease Epidemiology, Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, London, UK.
BMC Med. 2018 Sep 26;16(1):162. doi: 10.1186/s12916-018-1152-1.
Social and cultural disparities in infectious disease burden are caused by systematic differences between communities. Some differences have a direct and proportional impact on disease burden, such as health-seeking behaviour and severity of infection. Other differences-such as contact rates and susceptibility-affect the risk of transmission, where the impact on disease burden is indirect and remains unclear. Furthermore, the concomitant impact of vaccination on such inequalities is not well understood.
To quantify the role of differences in transmission on inequalities and the subsequent impact of vaccination, we developed a novel mathematical framework that integrates a mechanistic model of disease transmission with a demographic model of social structure, calibrated to epidemiologic and empirical social contact data.
Our model suggests realistic differences in two key factors contributing to the rates of transmission-contact rate and susceptibility-between two social groups can lead to twice the risk of infection in the high-risk population group relative to the low-risk population group. The more isolated the high-risk group, the greater this disease inequality. Vaccination amplified this inequality further: equal vaccine uptake across the two population groups led to up to seven times the risk of infection in the high-risk group. To mitigate these inequalities, the high-risk population group would require disproportionately high vaccination uptake.
Our results suggest that differences in contact rate and susceptibility can play an important role in explaining observed inequalities in infectious diseases. Importantly, we demonstrate that, contrary to social policy intentions, promoting an equal vaccine uptake across population groups may magnify inequalities in infectious disease risk.
传染病负担的社会和文化差异是由社区之间的系统性差异造成的。一些差异对疾病负担有直接和比例的影响,例如寻求医疗服务的行为和感染的严重程度。其他差异,如接触率和易感性,会影响传播的风险,而其对疾病负担的影响是间接的,且尚不清楚。此外,疫苗接种对这些不平等现象的共同影响也尚未得到充分理解。
为了量化传播差异对不平等现象的作用以及疫苗接种的后续影响,我们开发了一种新的数学框架,该框架将疾病传播的机制模型与社会结构的人口模型相结合,并根据流行病学和经验性社会接触数据进行了校准。
我们的模型表明,在导致两个社会群体之间传播率(接触率和易感性)存在差异的两个关键因素中,即使差异很小,也可能导致高风险人群相对于低风险人群感染的风险增加一倍。高风险群体越孤立,这种疾病不平等就越严重。疫苗接种进一步放大了这种不平等:在两个人群中疫苗接种率相等,高风险人群的感染风险最高可达七倍。为了减轻这些不平等现象,高风险人群群体需要不成比例地高疫苗接种率。
我们的研究结果表明,接触率和易感性的差异可以在解释传染病观察到的不平等现象方面发挥重要作用。重要的是,我们证明了与社会政策意图相反,在人群中推广平等的疫苗接种率可能会放大传染病风险的不平等现象。