Checchi Francesco, Testa Adrienne, Gimma Amy, Koum-Besson Emilie, Warsame Abdihamid
Department of Infectious Disease Epidemiology, Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, UK.
Popul Health Metr. 2022 Jan 11;20(1):4. doi: 10.1186/s12963-022-00283-6.
Populations affected by crises (armed conflict, food insecurity, natural disasters) are poorly covered by demographic surveillance. As such, crisis-wide estimation of population mortality is extremely challenging, resulting in a lack of evidence to inform humanitarian response and conflict resolution.
We describe here a 'small-area estimation' method to circumvent these data gaps and quantify both total and excess (i.e. crisis-attributable) death rates and tolls, both overall and for granular geographic (e.g. district) and time (e.g. month) strata. The method is based on analysis of data previously collected by national and humanitarian actors, including ground survey observations of mortality, displacement-adjusted population denominators and datasets of variables that may predict the death rate. We describe the six sequential steps required for the method's implementation and illustrate its recent application in Somalia, South Sudan and northeast Nigeria, based on a generic set of analysis scripts.
Descriptive analysis of ground survey data reveals informative patterns, e.g. concerning the contribution of injuries to overall mortality, or household net migration. Despite some data sparsity, for each crisis that we have applied the method to thus far, available predictor data allow the specification of reasonably predictive mixed effects models of crude and under 5 years death rate, validated using cross-validation. Assumptions about values of the predictors in the absence of a crisis provide counterfactual and excess mortality estimates.
The method enables retrospective estimation of crisis-attributable mortality with considerable geographic and period stratification, and can therefore contribute to better understanding and historical memorialisation of the public health effects of crises. We discuss key limitations and areas for further development.
受危机(武装冲突、粮食不安全、自然灾害)影响的人群在人口监测中覆盖不足。因此,对危机范围内的人口死亡率进行估计极具挑战性,导致缺乏为人道主义应对和冲突解决提供信息的证据。
我们在此描述一种“小区域估计”方法,以规避这些数据缺口,并量化总体和超额(即危机所致)死亡率及死亡人数,包括总体以及按地理区域(如地区)和时间(如月份)细分的情况。该方法基于对国家和人道主义行为体先前收集的数据进行分析,包括死亡率的地面调查观测、经流离失所调整的人口分母以及可能预测死亡率的变量数据集。我们描述了该方法实施所需的六个连续步骤,并基于一组通用分析脚本说明了其近期在索马里、南苏丹和尼日利亚东北部的应用情况。
对地面调查数据的描述性分析揭示了一些有价值的模式,例如伤害对总体死亡率的影响或家庭净迁移情况。尽管存在一些数据稀疏问题,但对于我们迄今应用该方法的每一场危机,可用的预测数据允许指定合理预测粗死亡率和5岁以下儿童死亡率的混合效应模型,并通过交叉验证进行验证。在没有危机的情况下对预测变量值的假设提供了反事实和超额死亡率估计。
该方法能够对危机所致死亡率进行具有相当地理和时期分层的回顾性估计,因此有助于更好地理解危机对公共卫生的影响并进行历史记录。我们讨论了关键局限性和进一步发展的领域。