Blanco Natalia, Lawal Olanrewaju, Jumare Jibreel, Riley Christina, Onyemata James, Kono Thomas, Winters Anna, Xiong Chenfeng, Abimiku Alash'le, Charurat Manhattan, Stafford Kristen A
Institute of Human Virology, University of Maryland School of Medicine, Baltimore, Maryland, USA.
Department of Geography and Environmental Management, Faculty of Social Sciences University of Port Harcourt, Port Harcourt, Nigeria.
Glob Health Action. 2024 Dec 31;17(1):2446043. doi: 10.1080/16549716.2024.2446043. Epub 2025 Jan 21.
Social vulnerability has been shown to be a strong predictor of disparities in health outcomes. A common approach to estimating social vulnerability is using a composite index, such as the social vulnerability index (SVI), which combines multiple factors corresponding to key social determinants of health. Lawal and Osayomi created an SVI to explore key social determinants of health-related COVID-19 infection among the Nigerian population. This study explored the association of COVID-19 SVI with COVID-19 seroprevalence using a large household survey in Nigeria. Weighted COVID-19 seroprevalence estimates at the Local Government Areas (LGA) were estimated and merged with the Lawal and Osayomi SVI, also at the LGA-level. Linear regression models were constructed to evaluate the relationship between the SVI and COVID-19 seroprevalence. The effect of SVI was evaluated both as a continuous variable and categorized into quintiles to evaluate dose-response effects. Our results confirmed a positive relationship between social vulnerability and COVID-19 infection in four states and the Federal Capital Territory in Nigeria. Compared to class 1 (the least vulnerable group), COVID-19 seroprevalence was, on average, 9.21% and 6.42% higher in classes 4 and 5 LGAs, respectively, after adjustment by phase of the survey. The effect was particularly strong farther into the pandemic (June 2021), when COVID-19 mitigation measures were relaxed. In conclusion, SVI can potentially be a useful tool to effectively prioritize communities for resource allocation as part of emergency response and preparedness in Africa.
社会脆弱性已被证明是健康结果差异的有力预测指标。估计社会脆弱性的一种常用方法是使用综合指数，如社会脆弱性指数（SVI），该指数结合了与健康的关键社会决定因素相对应的多个因素。拉瓦尔和奥萨约米创建了一个SVI，以探索尼日利亚人群中与健康相关的新冠病毒感染的关键社会决定因素。本研究利用尼日利亚的一项大型家庭调查，探讨了新冠病毒SVI与新冠病毒血清阳性率之间的关联。估计了地方政府区域（LGA）的加权新冠病毒血清阳性率估计值，并将其与同样在LGA层面的拉瓦尔和奥萨约米SVI合并。构建线性回归模型来评估SVI与新冠病毒血清阳性率之间的关系。将SVI作为连续变量进行评估，并分为五分位数以评估剂量反应效应。我们的结果证实，在尼日利亚的四个州和联邦首都地区，社会脆弱性与新冠病毒感染之间存在正相关关系。与第1类（最不脆弱群体）相比，在按调查阶段进行调整后，第4类和第5类LGA的新冠病毒血清阳性率平均分别高出9.21%和6.42%。在疫情后期（2021年6月），当新冠病毒缓解措施放松时，这种影响尤为强烈。总之，作为非洲应急响应和准备工作的一部分，SVI有可能成为有效确定社区资源分配优先级的有用工具。
