Comparability of sociodemographic and pregnancy characteristics of pregnancy-related deaths identified via the sisterhood method versus the household/verbal autopsy method

Abstract Background Ascertaining the causes for deaths occurring outside health facilities is a significant problem in many developing countries where civil registration systems are not well developed or non-functional. Standardized and rigorous verbal autopsy methods is a potential solution to determine the cause of death. We conducted a demonstration project in Lusaka District of Zambia where verbal autopsy (VA) method was implemented in routine civil registration system. Methods About 3400 VA interviews were conducted for bodies “brought-in-dead” at Lusaka’s two major teaching hospital mortuaries using a SmartVA questionnaire between October 2017 and September 2018. Probable underlying causes of deaths using VA and cause-specific mortality fractions were determined.. Demographic characteristics were analyzed for each VA-ascertained cause of death. Results Opportunistic infections (OIs) associated with HIV/AIDS such as pneumonia and tuberculosis, and malaria were among leading causes of deaths among bodies “brought-in-dead”. Over 21.6 and 26.9% of deaths were attributable to external causes and non-communicable diseases (NCDs), respectively. The VA-ascertained causes of death varied by age-group and sex. External causes were more prevalent among males in middle ages (put an age range like 30–54 years old) and NCDs highly prevalent among those aged 55 years and older. Conclusions VA application in civil registration system can provide the much-needed cause of death information for non-facility deaths in countries with under-developed or non-functional civil registration systems.

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Bayesian hierarchical factor regression models to infer cause of death from verbal autopsy data

Journal of the Royal Statistical Society Series C (Applied Statistics) ◽

10.1111/rssc.12468 ◽

2021 ◽

Author(s):

Kelly R. Moran ◽

Elizabeth L. Turner ◽

David Dunson ◽

Amy H. Herring

Keyword(s):

Cause Of Death ◽

Verbal Autopsy ◽

Regression Models ◽

Bayesian Hierarchical ◽

Autopsy Data ◽

Factor Regression

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Routine mortality surveillance to identify the cause of death pattern for out-of-hospital adult (aged 12+ years) deaths in Bangladesh: introduction of automated verbal autopsy

BMC Public Health ◽

10.1186/s12889-021-10468-7 ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Md. Toufiq Hassan Shawon ◽

Shah Ali Akbar Ashrafi ◽

Abul Kalam Azad ◽

Sonja M. Firth ◽

Hafizur Chowdhury ◽

...

Keyword(s):

Verbal Autopsy ◽

Software Tool ◽

Relevant Information ◽

Chronic Respiratory Disease ◽

Death Registration ◽

Registration System ◽

Health Programming ◽

Performance And Evaluation ◽

Disease Study ◽

Causes Of Deaths

Abstract Background In Bangladesh, a poorly functioning national system of registering deaths and determining their causes leaves the country without important information on which to inform health programming, particularly for the 85% of deaths that occur in the community. In 2017, an improved death registration system and automated verbal autopsy (VA) were introduced to 13 upazilas to assess the utility of VA as a routine source of policy-relevant information and to identify leading causes of deaths (COD) in rural Bangladesh. Methods Data from 22,535 VAs, collected in 12 upazilas between October 2017 and August 2019, were assigned a COD using the SmartVA Analyze 2.0 computer algorithm. The plausibility of the VA results was assessed using a series of demographic and epidemiological checks in the Verbal Autopsy Interpretation, Performance and Evaluation Resource (VIPER) software tool. Results Completeness of community death reporting was 65%. The vast majority (85%) of adult deaths were due to non-communicable diseases, with ischemic heart disease, stroke and chronic respiratory disease comprising about 60% alone. Leading COD were broadly consistent with Global Burden of Disease study estimates. Conclusions Routine VA collection using automated methods is feasible, can produce plausible results and provides critical information on community COD in Bangladesh. Routine VA and VIPER have potential application to countries with weak death registration systems.

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Monitoring progress with national and subnational health goals by integrating verbal autopsy and medically certified cause of death data

BMJ Global Health ◽

10.1136/bmjgh-2021-005387 ◽

2021 ◽

Vol 6 (5) ◽

pp. e005387

Author(s):

Tim Adair ◽

Sonja Firth ◽

Tint Pa Pa Phyo ◽

Khin Sandar Bo ◽

Alan D Lopez

Keyword(s):

Cause Of Death ◽

Verbal Autopsy ◽

Integration Method ◽

Mortality Rates ◽

Vital Statistics ◽

Death Registration ◽

Chronic Respiratory Diseases ◽

Health Goals ◽

Specific Mortality ◽

Four Causes

IntroductionThe measurement of progress towards many Sustainable Development Goals (SDG) and other health goals requires accurate and timely all-cause and cause of death (COD) data. However, existing guidance to countries to calculate these indicators is inadequate for populations with incomplete death registration and poor-quality COD data. We introduce a replicable method to estimate national and subnational cause-specific mortality rates (and hence many such indicators) where death registration is incomplete by integrating data from Medical Certificates of Cause of Death (MCCOD) for hospital deaths with routine verbal autopsy (VA) for community deaths.MethodsThe integration method calculates population-level cause-specific mortality fractions (CSMFs) from the CSMFs of MCCODs and VAs weighted by estimated deaths in hospitals and the community. Estimated deaths are calculated by applying the empirical completeness method to incomplete death registration/reporting. The resultant cause-specific mortality rates are used to estimate SDG Indicator 23: mortality between ages 30 and 70 years from cardiovascular diseases, cancers, chronic respiratory diseases and diabetes. We demonstrate the method using nationally representative data in Myanmar, comprising over 42 000 VAs and 7600 MCCODs.ResultsIn Myanmar in 2019, 89% of deaths were estimated to occur in the community. VAs comprised an estimated 70% of community deaths. Both the proportion of deaths in the community and CSMFs for the four causes increased with older age. We estimated that the probability of dying from any of the four causes between 30 and 70 years was 0.265 for men and 0.216 for women. This indicator is 50% higher if based on CSMFs from the integration of data sources than on MCCOD data from hospitals.ConclusionThis integration method facilitates country authorities to use their data to monitor progress with national and subnational health goals, rather than rely on estimates made by external organisations. The method is particularly relevant given the increasing application of routine VA in country Civil Registration and Vital Statistics systems.

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