Mortality before and after the 2003 invasion of Iraq: cluster sample survey.

Center for International Emergency Disaster and Refugee Studies, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
The Lancet (Impact Factor: 39.21). 11/2004; 364(9448):1857-64. DOI: 10.1016/S0140-6736(04)17441-2
Source: PubMed

ABSTRACT In March, 2003, military forces, mainly from the USA and the UK, invaded Iraq. We did a survey to compare mortality during the period of 14.6 months before the invasion with the 17.8 months after it.
A cluster sample survey was undertaken throughout Iraq during September, 2004. 33 clusters of 30 households each were interviewed about household composition, births, and deaths since January, 2002. In those households reporting deaths, the date, cause, and circumstances of violent deaths were recorded. We assessed the relative risk of death associated with the 2003 invasion and occupation by comparing mortality in the 17.8 months after the invasion with the 14.6-month period preceding it.
The risk of death was estimated to be 2.5-fold (95% CI 1.6-4.2) higher after the invasion when compared with the preinvasion period. Two-thirds of all violent deaths were reported in one cluster in the city of Falluja. If we exclude the Falluja data, the risk of death is 1.5-fold (1.1-2.3) higher after the invasion. We estimate that 98000 more deaths than expected (8000-194000) happened after the invasion outside of Falluja and far more if the outlier Falluja cluster is included. The major causes of death before the invasion were myocardial infarction, cerebrovascular accidents, and other chronic disorders whereas after the invasion violence was the primary cause of death. Violent deaths were widespread, reported in 15 of 33 clusters, and were mainly attributed to coalition forces. Most individuals reportedly killed by coalition forces were women and children. The risk of death from violence in the period after the invasion was 58 times higher (95% CI 8.1-419) than in the period before the war.
Making conservative assumptions, we think that about 100000 excess deaths, or more have happened since the 2003 invasion of Iraq. Violence accounted for most of the excess deaths and air strikes from coalition forces accounted for most violent deaths. We have shown that collection of public-health information is possible even during periods of extreme violence. Our results need further verification and should lead to changes to reduce non-combatant deaths from air strikes.

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    ABSTRACT: In this paper we have studied empirically the role of single or two auxiliary variables under which cluster sampling in conjunction with ratio method of estimation is more efficient (or less efficient) than using conventional estimator in simple random sampling (SRS), if intra class correlation of the elements within the cluster has positive correlation. We have considered some extreme populations which may help the survey practitioners to know the magnitude of gain or loss in efficiency of cluster sampling using single or two auxiliary variables in conjunction with ratio method of estimation. To have more insight, the clusters are formed for sample sizes 2, 3 and 4. Keywords: Auxiliary variables; Cluster sampling; Intra class correlation; Ratio method of estimation; Simple Random Sampling 1. Introduction In large scale sample surveys cluster sampling is the most preferable sampling because it not only reduces the cost of the surveys, but also the researcher can have a larger sample size than if he or she was using simple random sampling (SRS). Besides, it may be used when it is either difficult or costly or impractical to prepare sampling frame of the units, to draw a sample. Moreover, sometimes the population elements are naturally grouped into subpopulations and lists of those subpopulations either already exist or easy and cheap to obtain. For a fixed budget, the main motivation to use cluster sampling, in large scale surveys, is to reduce the cost of data collection, data collection is faster and it increases sample size which helps to reduce the sampling error [see [4],[5], [9], [10] and [12]]. One of the main disadvantage of cluster sampling is that its efficiency is less than SRS for given sample size because the intra class correlation of the elements within the cluster has positive correlation. Zarkovic [13] illustrated that correlation between two characteristics of cluster means is directly proportional to the size of the clusters. Mishro and Sukhatme [8] utilized this information and gave the conditions under which cluster sampling in conjunction with ratio or regression method is more efficient that SRS even if intra class correlation of the elements within the cluster has positive correlation.
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