Under-five mortality: spatial-temporal clusters in Ifakara HDSS in South-eastern Tanzania.

BACKGROUND\ud \ud Childhood mortality remains an important subject, particularly in sub-Saharan Africa where levels are still unacceptably high. To achieve the set Millennium Development Goals 4, calls for comprehensive application of the proven cost-effective interventions. Understanding spatial clustering of childhood mortality can provide a guide in targeting the interventions in a more strategic approach to the population where mortality is highest and the interventions are most likely to make an impact.\ud \ud METHODS\ud \ud Annual child mortality rates were calculated for each village, using person-years observed as the denominator. Kulldorff's spatial scan statistic was used for the identification and testing of childhood mortality clusters. All under-five deaths that occurred within a 10-year period from 1997 to 2006 were included in the analysis. Villages were used as units of clusters; all 25 health and demographic surveillance sites (HDSS) villages in the Ifakara health and demographic surveillance area were included.\ud \ud RESULTS\ud \ud Of the 10 years of analysis, statistically significant spatial clustering was identified in only 2 years (1998 and 2001). In 1998, the statistically significant cluster (p < 0.01) was composed of nine villages. A total of 106 childhood deaths were observed against an expected 77.3. The other statistically significant cluster (p < 0.05) identified in 2001 was composed of only one village. In this cluster, 36 childhood deaths were observed compared to 20.3 expected. Purely temporal analysis indicated that the year 2003 was a significant cluster (p < 0.05). Total deaths were 393 and expected were 335.8. Spatial-temporal analysis showed that nine villages were identified as statistically significant clusters (p < 0.05) for the period covering January 1997-December 1998. Total observed deaths in this cluster were 205 while 150.7 were expected.\ud \ud CONCLUSION\ud \ud There is evidence of spatial clustering in childhood mortality within the Ifakara HDSS. Further investigations are needed to explore the source of clustering and identify strategies of reaching the cluster population with the existing effective interventions. However, that should happen alongside delivery of interventions to the broader population

Verbal autopsy completion rate and factors associated with undetermined cause of death in a rural resource-poor setting of Tanzania

UNLABELLED\ud \ud ABSTRACT:\ud \ud BACKGROUND\ud \ud Verbal autopsy (VA) is a widely used tool to assign probable cause of death in areas with inadequate vital registration systems. Its uses in priority setting and health planning are well documented in sub-Saharan Africa (SSA) and Asia. However, there is a lack of data related to VA processing and completion rates in assigning causes of death in a community. There is also a lack of data on factors associated with undetermined causes of death documented in SSA. There is a need for such information for understanding the gaps in VA processing and better estimating disease burden.\ud \ud OBJECTIVE\ud \ud The study's intent was to determine the completion rate of VA and factors associated with assigning undetermined causes of death in rural Tanzania.\ud \ud METHODS\ud \ud A database of deaths reported from the Ifakara Health and Demographic Surveillance System from 2002 to 2007 was used. Completion rates were determined at the following stages of processing: 1) death identified; 2) VA interviews conducted; 3) VA forms submitted to physicians; 4) coding and assigning of cause of death. Logistic regression was used to determine factors associated with deaths coded as "undetermined."\ud \ud RESULTS\ud \ud The completion rate of VA after identification of death and the VA interview ranged from 83% in 2002 and 89% in 2007. Ninety-four percent of deaths submitted to physicians were assigned a specific cause, with 31% of the causes coded as undetermined. Neonates and child deaths that occurred outside health facilities were associated with a high rate of undetermined classification (33%, odds ratio [OR] = 1.33, 95% confidence interval [CI] (1.05, 1.67), p = 0.016). Respondents reporting high education levels were less likely to be associated with deaths that were classified as undetermined (24%, OR = 0.76, 95% CI (0.60, -0.96), p = 0.023). Being a child of the deceased compared to a partner (husband or wife) was more likely to be associated with undetermined cause of death classification (OR = 1.35, 95% CI (1.04, 1.75), p = 0.023).\ud \ud CONCLUSION\ud \ud Every year, there is a high completion rate of VA in the initial stages of processing; however, a number of VAs are lost during the processing. Most of the losses occur at the final step, physicians' determination of cause of death. The type of respondent and place of death had a significant effect on final determination of the plausible cause of death. The finding provides some insight into the factors affecting full coverage of verbal autopsy diagnosis and the limitations of causes of death based on VA in SSA. Although physician review is the most commonly used method in ascertaining probable cause of death, we suggest further work needs to be done to address the challenges faced by physicians in interpreting VA forms. There is need for an alternative to or improvement of the methods of physician review