Verbal Autopsy Methods Research Articles

A Retrospective Analysis of Lessons Learned and Perspectives on Expansion of Verbal Autopsy Implementation in Zambia, 2023.

Accurate cause-of-death statistics are vital for public health policy, but less than one-third of deaths globally are assigned a cause. Verbal autopsy (VA) methods are crucial in low- and middle-income countries lacking complete civil registration and vital statistics (CRVS) systems. We explored VA implementation in Zambia by using a previously developed framework. The National Mortality Surveillance Subcommittee under the Monitoring and Evaluation Technical Working Group within the Ministry of Health coordinates mortality surveillance activities in Zambia. To date, passive, non-population-representative VA data collection mechanisms have been used, leading to underrepresentation of some communities. In spite of the use of electronic data collection tools, VA systems have not been electronically linked to public health surveillance or CRVS systems. Funding for VA has largely been donor driven. Increasing government funding may ensure sustainability, while the adoption of sample-based platforms while linking VA information technology systems may make VA data more useful, timely, and accessible.

Comparison of causes of stillbirth and child deaths as determined by verbal autopsy and minimally invasive tissue sampling.

In resource-limited settings where vital registration and medical death certificates are unavailable or incomplete, verbal autopsy (VA) is often used to attribute causes of death (CoD) and prioritize resource allocation and interventions. We aimed to determine the CoD concordance between InterVA and CHAMPS's method. The causes of death (CoDs) of children <5 were determined by two methods using data from seven low- and middle-income countries (LMICs) enrolled in the Child Health and Mortality Prevention Surveillance (CHAMPS) network. The first CoD method was from the DeCoDe panel using data from Minimally Invasive Tissue Sampling (MITS), whereas the second method used Verbal Autopsy (VA), which utilizes the InterVA software. This analysis evaluated the agreement between the two using Lin's concordance correlation coefficient. The overall concordance of InterVA4 and DeCoDe in assigning causes of death across surveillance sites, age groups, and causes of death was poor (0.75 with 95% CI: 0.73-0.76) and lacked precision. We found substantial differences in agreement by surveillance site, with Mali showing the lowest and Mozambique and Ethiopia the highest concordance. The InterVA4 assigned CoD agrees poorly in assigning causes of death for U5s and stillbirths. Because VA methods are relatively easy to implement, such systems could be more useful if algorithms were improved to more accurately reflect causes of death, for example, by calibrating algorithms to information from programs that used detailed diagnostic testing to improve the accuracy of COD determination.

Are multiple coders needed for cause of death assignment: results from telephonic verbal autopsy interviews conducted in 2021 in South Africa.

Verbal autopsy (VA) methods have emerged to estimate causes of death in populations lacking robust civil registration and vital statistics (CRVS) systems. Despite World Health Organization endorsement of routine VA use, cost and efficiency concerns persist. Telephonic verbal autopsies (teleVAs) can reduce cost. Physician coding offers a valuable approach, but the expertise required makes it resource-intensive, often involving multiple coders for consensus. To assess inter-coder agreement for cause of death (CoD) in South African teleVAs using Kappa statistics, evaluating if agreement surpasses a 0.8 cut-off (very high) potentially allowing single coders. A cross-sectional study employed telephonic VA interviews on non-facility deaths in Cape Town (December 2020-September 2021). Trained fieldworkers administered a standard VA questionnaire. Each case's VA responses were reviewed independently by two physicians, medically certifying the CoD. A panel was used to solve disagreements. Cohen's kappa-statistic (k-statistic) tested agreement levels. Decedents were aged between 18 and 98 years. In total, 228 teleVAs (16.6% response rate) were conducted. Physician coding agreement was good overall (k-statistic: 0.63). Diabetes mellitus (47%) and other non-communicable disease (42%) had initial agreement between physician coders in less than 50% of cases in comparison to consensus totals. COVID-19 (89%) and acute cardiac disease (83%) showed initial agreement in more than 80% of cases compared to consensus totals. A chi-square test revealed a significant difference in the number of causes listed on death notification forms for cases with and without agreement in Part 1 (χ2 = 14.71, p < 0.01), but not in Part 2 (χ2 = 4.97, p = 0.17). CoD agreement might not be high enough to infer that single coders can be used instead of multiple coders. Challenges with co-morbidities and specific CoDs with multiple sequelae highlight the need for further research and refinement of VA methodologies for reliable CoD determination in routine practice.

Community perception of causes of death using verbal autopsy for diabetes mellitus in Saudi Arabia.

Diabetes mellitus is a serious global health issue which significantly impacts public health and socioeconomic development. Exploring how the community perceives the causes of death and their associated risk factors is crucial for public health. This study combines verbal autopsy (VA) with the Type 2 Diabetes Mellitus (T2DM) register to explore community perceptions of causes of death and associated influential factors in Makkah province, Saudi Arabia. 302 VA interviews were conducted with relatives or caregivers of deceased who died between 2018 and 2021 based on T2DM medical register from Alnoor Specialist Hospital in Makkah City, Saudi Arabia. Cause-specific mortality fractions (CSMFs) obtained from the VA using the InterVA-5 model were utilized to assess community perception. We used a multivariable logistic regression model to determine factors influencing community perceptions of causes of death. Lin's CCC with 95% CI was used to analyze the concordance for the CSMFs from verbal autopsy causes of death (VACoD) as a presumed reference standard and family-reported causes of death (FRCoD). The outcomes of this study demonstrate a generally broad spectrum of community perceived mortalities, with some critical misconceptions based on the type of death and other vital events like marital status, with an overall CCC of 0.60 (95% CI: 0.20-1.00; p = 003). The study findings demonstrate that community perception is weak if the deceased was male compared to female (aOR: 0.52; 95% CI: 0.26-1.03) and if the deceased was > = 80 years compared to 34-59 years (aOR: 0.48; 95% CI: 0.16-1.38), but it significantly improves among married compared to single (aOR: 2.13; 95% CI: 1.02-4.42). Exploring community perception of causes of death is crucial as it provides valuable insights into the community's understanding, beliefs, and concerns regarding mortality. Higher or lower community perception is attributed to how people may perceive risk factors associated with the causes of death, which can guide public health planning and interventional programs. The study findings further emphasize the need to employ robust and standardized VA methods within the routine medical services for a systemized assessment of families' reported causes of death.

Comparative performance of national civil registration and vital statistics systems: a global assessment.

To assess the current state of the world's civil registration and vital statistics systems based on publicly available data and to propose strategic development pathways, including priority interventions, for countries at different levels of civil registration and vital statistics performance. We applied a performance assessment framework to publicly available data, using a composite indicator highly correlated with civil registration and vital statistics performance which we then adjusted for data incomparability and missing values. Globally, civil registration and vital statistics systems score on average 0.70 (0-1 scale), with substantial variations across countries and regions. Scores ranged from less than 0.50 in emerging systems to nearly 1.00 in the most developed systems. Approximately one fifth of the world's population live in the 43 countries with low system performance (< 0.477). Irrespective of system development, health sector indicators consistently scored lower than other determinants of civil registration and vital statistics performance. From our assessment, we provide three main recommendations for how the health sector can contribute to improving civil registration and vital statistics systems: (i)enhanced health sector engagement in birth and death notification; (ii) a more systematic approach to training cause of death diagnostics; and (iii) leadership in the implementation of verbal autopsy methods. Four different civil registration and vital statistics improvement pathways for countries at different levels of system development are proposed, that can constitute a blueprint for regional civil registration and vital statistics strengthening activities that countries can adapt and refine to suit their capabilities, resources, and particular challenges.

Assessing the policy utility of routine mortality statistics: a global classification of countries.

To evaluate the utility and quality of death registration data across countries. We compiled routine death and cause of death statistics data from 2015-2019 from national authorities. We estimated completeness of death registration using the Adair-Lopez empirical method. The quality of cause of death data was assessed by evaluating the assignment of usable causes of death among people younger than 80 years. We grouped data into nine policy utility categories based on data availability, registration completeness and diagnostic precision. Of an estimated 55 million global deaths in 2019, 70% of deaths were registered across 156 countries, but only 52% had medically certified causes and 42% of deaths were assigned a usable cause. In 54 countries, which are mostly high-income, there is complete and high-quality mortality data. In a further 29 countries, located across different regions, death registration is complete, but cause of death data quality remains suboptimal. Additionally, 37 countries possess functional death registration systems with cause of death data of poor to moderate quality. In 30 countries, death registration ranges from limited to nascent completeness, accompanied by poor or unavailable cause of death data. Furthermore, 38 countries lack accessible data altogether. By implementing more proactive death notification processes, expanding the use of digitized data collection platforms, streamlining data compilation procedures and improving data quality assessment, governments could enhance the policy utility of mortality data. Encouraging the routine application of automated verbal autopsy methods is crucial for accurately determining the causes of deaths occurring at home.

Agreement between cause of death assignment by computer-coded verbal autopsy methods and physician coding of verbal autopsy interviews in South Africa

ABSTRACT Background The South African national cause of death validation (NCODV 2017/18) project collected a national sample of verbal autopsies (VA) with cause of death (COD) assignment by physician-coded VA (PCVA) and computer-coded VA (CCVA). Objective The performance of three CCVA algorithms (InterVA-5, InSilicoVA and Tariff 2.0) in assigning a COD was compared with PCVA (reference standard). Methods Seven performance metrics assessed individual and population level agreement of COD assignment by age, sex and place of death subgroups. Positive predictive value (PPV), sensitivity, overall agreement, kappa, and chance corrected concordance (CCC) assessed individual level agreement. Cause-specific mortality fraction (CSMF) accuracy and Spearman’s rank correlation assessed population level agreement. Results A total of 5386 VA records were analysed. PCVA and CCVAs all identified HIV/AIDS as the leading COD. CCVA PPV and sensitivity, based on confidence intervals, were comparable except for HIV/AIDS, TB, maternal, diabetes mellitus, other cancers, and some injuries. CCVAs performed well for identifying perinatal deaths, road traffic accidents, suicide and homicide but poorly for pneumonia, other infectious diseases and renal failure. Overall agreement between CCVAs and PCVA for the top single cause (48.2–51.6) indicated comparable weak agreement between methods. Overall agreement, for the top three causes showed moderate agreement for InterVA (70.9) and InSilicoVA (73.8). Agreement based on kappa (−0.05–0.49)and CCC (0.06–0.43) was weak to none for all algorithms and groups. CCVAs had moderate to strong agreement for CSMF accuracy, with InterVA-5 highest for neonates (0.90), Tariff 2.0 highest for adults (0.89) and males (0.84), and InSilicoVA highest for females (0.88), elders (0.83) and out-of-facility deaths (0.85). Rank correlation indicated moderate agreement for adults (0.75–0.79). Conclusions Whilst CCVAs identified HIV/AIDS as the leading COD, consistent with PCVA, there is scope for improving the algorithms for use in South Africa.

Cause of Death estimation from Verbal Autopsies: Is the Open Response redundant or synergistic?

Civil registration and vital statistics systems capture birth and death events to compile vital statistics and to provide legal rights to citizens. Vital statistics are a key factor in promoting public health policies and the health of the population. Medical certification of cause of death is the preferred source of cause of death information. However, two thirds of all deaths worldwide are not captured in routine mortality information systems and their cause of death is unknown. Verbal autopsy is an interim solution for estimating the cause of death distribution at the population level in the absence of medical certification. A Verbal Autopsy (VA) consists of an interview with the relative or the caregiver of the deceased. The VA includes both Closed Questions (CQs) with structured answer options, and an Open Response (OR) consisting of a free narrative of the events expressed in natural language and without any pre-determined structure. There are a number of automated systems to analyze the CQs to obtain cause specific mortality fractions with limited performance. We hypothesize that the incorporation of the text provided by the OR might convey relevant information to discern the CoD.The experimental layout compares existing Computer Coding Verbal Autopsy methods such as Tariff 2.0 with other approaches well suited to the processing of structured inputs as is the case of the CQs. Next, alternative approaches based on language models are employed to analyze the OR. Finally, we propose a new method with a bi-modal input that combines the CQs and the OR. Empirical results corroborated that the CoD prediction capability of the Tariff 2.0 algorithm is outperformed by our method taking into account the valuable information conveyed by the OR. As an added value, with this work we made available the software to enable the reproducibility of the results attained with a version implemented in R to make the comparison with Tariff 2.0 evident.

The openVA Toolkit for Verbal Autopsies.

Verbal autopsy (VA) is a survey-based tool widely used to infer cause of death (COD) in regions without complete-coverage civil registration and vital statistics systems. In such settings, many deaths happen outside of medical facilities and are not officially documented by a medical professional. VA surveys, consisting of signs and symptoms reported by a person close to the decedent, are used to infer the COD for an individual, and to estimate and monitor the COD distribution in the population. Several classification algorithms have been developed and widely used to assign causes of death using VA data. However, the incompatibility between different idiosyncratic model implementations and required data structure makes it difficult to systematically apply and compare different methods. The openVA package provides the first standardized framework for analyzing VA data that is compatible with all openly available methods and data structure. It provides an open-source, R implementation of several most widely used VA methods. It supports different data input and output formats, and customizable information about the associations between causes and symptoms. The paper discusses the relevant algorithms, their implementations in R packages under the openVA suite, and demonstrates the pipeline of model fitting, summary, comparison, and visualization in the R environment.

Population cause of death estimation using verbal autopsy methods in large-scale field trials of maternal and child health: lessons learned from a 20-year research collaboration in Central Ghana

Low and middle-income countries continue to use Verbal autopsies (VAs) as a World Health Organisation-recommended method to ascertain causes of death in settings where coverage of vital registration systems is not yet comprehensive. Whilst the adoption of VA has resulted in major improvements in estimating cause-specific mortality in many settings, well documented limitations have been identified relating to the standardisation of the processes involved. The WHO has invested significant resources into addressing concerns in some of these areas; there however remains enduring challenges particularly in operationalising VA surveys for deaths amongst women and children, challenges which have measurable impacts on the quality of data collected and on the accuracy of determining the final cause of death. In this paper we describe some of our key experiences and recommendations in conducting VAs from over two decades of evaluating seminal trials of maternal and child health interventions in rural Ghana. We focus on challenges along the entire VA pathway that can impact on the success rates of ascertaining the final cause of death, and lessons we have learned to optimise the procedures. We highlight our experiences of the value of the open history narratives in VAs and the training and skills required to optimise the quality of the information collected. We describe key issues in methods for ascertaining cause of death and argue that both automated and physician-based methods can be valid depending on the setting. We further summarise how increasingly popular information technology methods may be used to facilitate the processes described. Verbal autopsy is a vital means of increasing the coverage of accurate mortality statistics in low- and middle-income settings, however operationalisation remains problematic. The lessons we share here in conducting VAs within a long-term surveillance system in Ghana will be applicable to researchers and policymakers in many similar settings.

Causes and trends of adult mortality in southern Ethiopia: an eight-year follow up database study

BackgroundBroad and specific causes of adult mortalities are often neglected indicators of wellbeing in low-income countries like Ethiopia due to lack of strong vital statistics. Thus, this database study aimed to assess the causes of adult mortality using demographic surveillance data.MethodsAn 8-year (12 September 2009–11 September 2017) surveillance data from the Arba Minch Health and Demographic Surveillance Site was used for this study. Verbal autopsy methods and ICD codes were used to identify the causes of the adult deaths. The collected data were entered to the database by data clerks. We used Microsoft Excel and STATA version 16 software for data cleaning and analysis. Chi-squared test was used to see the significances of the trend analyses.ResultFrom the 943 adult deaths from 2009 to 2017 in the Health and Demographic Surveillance Site in southern Ethiopia, more than half of them were females. The specific leading cause of death in the adults were tuberculosis (16.8%), malaria (9.7%), and intestinal infectious diseases (9.6%).Communicable diseases (49.2%, 95% C.I 45.7, 52.7) accounted for about half of the deaths followed by non-communicable diseases (35%, 95% C.I 31.7, 38.4) where both categories showed an increasing trend.ConclusionAlthough pieces of evidences are showing the shift from communicable diseases to non-communicable diseases as the major causes of adult death in developing countries, this study showed that communicable diseases are still the major causes of adult deaths. Efforts and emphasis should be given to control infectious diseases such as tuberculosis and malaria.

The trend and pattern of adult mortality in South-Central Ethiopia: analysis using the 2008-2019 data from Butajira Health and Demographic Surveillance System

ABSTRACT Background Understanding context-specific temporal trends in mortality is essential for setting health policy priorities. Objective To investigate the trends and distribution of deaths due to communicable and non-communicable diseases and external causes in South-Central Ethiopia. Method All adult deaths captured by the Butajira Health and Demographic Surveillance System between January 2008 and December 2019 were included. A verbal autopsy method of collecting cause of death data was used. Physician review and a computerised algorithm, InterVA, were used to determine the cause of death. Coding was undertaken using the World Health Organization's International Classification of Diseases. Trends in adult mortality rate and proportional mortality were estimated by major cause of death categories. Significant trends were analysed using the Mann–Kendall statistical test with a significance set at P < 0.05. Deaths were also disaggregated by age, sex, and residence. Results There were 1,612 deaths in 279,681 person-years; 811 (50.3%) were females. The median age at death was 65 years. The proportional adult mortality and adult mortality rates (per 1000 person-years) attributed to communicable diseases, non-communicable diseases, and external causes were 31.1%, 58.9%, and 6.0%, and 1.9, 3.4, and 0.4, respectively. Adult mortality due to communicable diseases showed a declining trend (tau, the measure of the strength and direction of association, = −0.52; P < 0.05), whereas the trend increased for non-communicable diseases (tau = 0.67, P < 0.05) and external causes (tau = 0.29, P > 0.05). Moreover, death rates were pronounced in the 65+ age group and rural areas but comparable among males and females. Conclusion The trend in deaths due to communicable diseases declined but increased for non-communicable diseases and external causes with significant public health burdens. These findings will provide essential input in formulating health policy reforms to reduce premature mortality.

Causes of deaths in neonates and children aged 1–59 months in Nigeria: verbal autopsy findings of 2019 Verbal and Social Autopsy study

BackgroundNigeria has one of the highest under-five mortality rates in the world. Identifying the causes of these deaths is crucial to inform changes in policy documents, design and implementation of appropriate interventions to reduce these deaths. This study aimed to provide national and zonal-level estimates of the causes of under-five death in Nigeria in the 2013–2018 periods.MethodsWe conducted retrospective inquiries into the cause of deaths of 948 neonates and 2,127 children aged 1–59 months as identified in the 2018 Nigeria Demographic and Health Survey (NDHS). The verbal autopsy asked about signs and symptoms during the final illness. The Physician Coded Verbal Autopsy (PCVA) and Expert Algorithm Verbal Autopsy (EAVA) methods were employed to assign the immediate and underlying cause of deaths to all cases.ResultFor the analysis, sampling weights were applied to accommodate non-proportional allocation. Boys accounted for 56 percent of neonatal deaths and 51.5 percent of the 1–59-months old deaths. About one-quarter of under-5 mortality was attributed to neonatal deaths, and 50 percent of these neonatal deaths were recorded within 48 h of delivery. Overall, 84 percent of the under-5 deaths were in the northern geopolitical zones. Based on the two methods for case analysis, neonatal infections (sepsis, pneumonia, and meningitis) were responsible for 44 percent of the neonatal deaths, followed by intrapartum injury (PCVA: 21 percent vs. EAVA: 29 percent). The three main causes of death in children aged 1–59 months were malaria (PCVA: 23 percent vs. EAVA: 35 percent), diarrhoea (PCVA: 17 percent vs. EAVA: 23 percent), and pneumonia (PCVA: 10 percent vs. EAVA: 12 percent). In the North West, where the majority of under-5 (1–59 months) deaths were recorded, diarrhoea was the main cause of death (PCVA: 24.3 percent vs. EAVA: 30 percent).ConclusionThe causes of neonatal and children aged 1–59 months deaths vary across the northern and southern regions. By homing on the specific causes of mortality by region, the study provides crucial information that may be useful in planning appropriately tailored interventions to significantly reduce under-five deaths in Nigeria.

Trends and causes of adult mortality from 2007 to 2017 using verbal autopsy method, Addis Ababa, Ethiopia

ObjectivesWe aim to analyse the trends and causes of mortality among adults in Addis Ababa.SettingThis analysis was conducted using verbal autopsy data from the Addis Ababa Mortality Surveillance in Addis...

Improving the Policy Utility of Cause of Death Statistics in Sri Lanka: An Empirical Investigation of Causes of Out-of-Hospital Deaths Using Automated Verbal Autopsy Methods.

Background: Setting public health policies and effectively monitoring the impact of health interventions requires accurate, timely and complete cause of death (CoD) data for populations. In Sri Lanka, almost half of all deaths occur outside hospitals, with questionable diagnostic accuracy, thus limiting their information content for policy.Objectives: To ascertain whether SmartVA is applicable in improving the specificity of cause of death data for out-of-hospital deaths in Sri Lanka, and hence enhance the value of these routinely collected data for informing public policy debates.Methods: SmartVA was applied to 2610 VAs collected between January 2017 and March 2019 in 22 health-unit-areas clustered in six districts. Around 350 community-health-workers and 50 supervisory-staffs were trained. The resulting distribution of Cause-Specific-Mortality-Fractions (CSMFs) was compared to data from the Registrar-General's-Department (RGD) for out-of-hospital deaths for the same areas, and to the Global-Burden-of-Disease (GBD) estimates for Sri Lanka.Results: Using SmartVA, for only 15% of deaths could a specific-cause not be assigned, compared with around 40% of out-of-hospital deaths currently assigned garbage codes with “very high” or “high” severity. Stroke (M: 31.6%, F: 35.4%), Ischaemic Heart Disease (M: 13.5%, F: 13.0%) and Chronic Respiratory Diseases (M: 15.4%, F: 10.8%) were identified as the three leading causes of home deaths, consistent with the ranking of GBD-Study for Sri Lanka for all deaths, but with a notably higher CSMF for stroke.Conclusions: SmartVA showed greater diagnostic specificity, applicability, acceptability in the Sri Lankan context. Policy formulation in Sri Lanka would benefit substantially with national-wide implementation of VAs.

Limitations to current methods to estimate cause of death: a validation study of a verbal autopsy model.

Background: Accurate information on causes of death (CoD) is essential to estimate burden of disease, track global progress, prioritize cost-effective interventions, and inform policies to reduce mortality. In low-income settings, where a significant proportion of deaths take place at home or in poorly-resourced peripheral health facilities, data on CoD often relies on verbal autopsies (VAs). Validations of VAs have been performed against clinical diagnosis, but never before against an acceptable gold standard: the complete diagnostic autopsy (CDA). Methods: We have validated a computer-coded verbal autopsy method -the InterVA- using individual and population metrics to determine CoD against the CDA, in 316 deceased patients of different age groups who died in a tertiary-level hospital in Maputo, Mozambique between 2013 and 2015. Results: We found a low agreement of the model across all age groups at the individual (kappa statistic ranging from -0.030 to 0.232, lowest in stillbirths and highest in adults) and population levels (chance-corrected cause-specific mortality fraction accuracy ranging from -1.00 to 0.62, lowest in stillbirths, highest in children). The sensitivity in identifying infectious diseases was low (0% for tuberculosis, diarrhea, and disseminated infections, 32% for HIV-related infections, 33% for malaria and 36% for pneumonia). Of maternal deaths, 26 were assigned to eclampsia but only four patients actually died of eclampsia. Conclusions: These findings do not lead to building confidence in current estimates of CoD. They also call to the need to implement autopsy methods where they may be feasible, and to improve the quality and performance of current VA techniques.

How advanced is the epidemiological transition in Papua New Guinea? New evidence from verbal autopsy.

BackgroundReliable cause of death (COD) data are not available for the majority of deaths in Papua New Guinea (PNG), despite their critical policy value. Automated verbal autopsy (VA) methods, involving an interview and automated analysis to diagnose causes of community deaths, have recently been trialled in PNG. Here, we report VA results from three sites and highlight the utility of these methods to generate information about the leading CODs in the country.MethodsVA methods were introduced in one district in each of three provinces: Alotau in Milne Bay; Tambul-Nebilyer in Western Highlands; and Talasea in West New Britain. VA interviews were conducted using the Population Health Metrics Research Consortium (PHMRC) shortened questionnaire and analysed using the SmartVA automated diagnostic algorithm.ResultsA total of 1655 VAs were collected between June 2018 and November 2019, 87.0% of which related to deaths at age 12 years and over. Our findings suggest a continuing high proportion of deaths due to infectious diseases (27.0%) and a lower proportion of deaths due to non-communicable diseases (NCDs) (50.8%) than estimated by the Global Burden of Disease Study (GBD) 2017: 16.5% infectious diseases and 70.5% NCDs. The proportion of injury deaths was also high compared with GBD: 22.5% versus 13.0%.ConclusionsHealth policy in PNG needs to address a ‘triple burden’ of high infectious mortality, rising NCDs and a high fraction of deaths due to injuries. This study demonstrates the potential of automated VA methods to generate timely, reliable and policy-relevant data on COD patterns in hard-to-reach populations in PNG.

Application of verbal autopsy in routine civil registration in Lusaka District of Zambia

BackgroundAscertaining 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.MethodsAbout 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.ResultsOpportunistic 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.ConclusionsVA 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.

Limitations to current methods to estimate cause of death: a validation study of a verbal autopsy model.

Background: Accurate information on causes of death (CoD) is essential to estimate burden of disease, track global progress, prioritize cost-effective interventions, and inform policies to reduce mortality. In low-income settings, where a significant proportion of deaths take place at home or in poorly-resourced peripheral health facilities, data on CoD often relies on verbal autopsies (VAs). Validations of VAs have been performed against clinical diagnosis, but never before against an acceptable gold standard: the complete diagnostic autopsy (CDA). Methods: We have validated a computer-coded verbal autopsy method -the InterVA- using individual and population metrics to determine CoD against the CDA, in 316 deceased patients of different age groups who died in a tertiary-level hospital in Maputo, Mozambique between 2013 and 2015. Results: We found a low agreement of the model across all age groups at the individual (kappa statistic ranging from -0.030 to 0.232, lowest in stillbirths and highest in adults) and population levels (chance-corrected cause-specific mortality fraction accuracy ranging from -1.00 to 0.62, lowest in stillbirths, highest in children). The sensitivity in identifying infectious diseases was low (0% for tuberculosis, diarrhea, and disseminated infections, 32% for HIV-related infections, 33% for malaria and 36% for pneumonia). Of maternal deaths, 26 were assigned to eclampsia but only four patients actually died of eclampsia. Conclusions: These findings do not lead to building confidence in current estimates of CoD. They also call to the need to implement autopsy methods where they may be feasible, and to improve the quality and performance of current VA techniques.

Comparative performance of verbal autopsy methods in identifying causes of adult mortality: A case study in India.

Background & objectives:Cause of death assignment from verbal autopsy (VA) questionnaires is conventionally accomplished through physician review. However, since recently, computer softwares have been developed to assign the cause of death. The present study evaluated the performance of computer software in assigning the cause of death from the VA, as compared to physician review.Methods:VA of 600 adult deaths was conducted using open- and close-ended questionnaires in Nandpur Kalour Block of Punjab, India. Entire VA forms were used by two physicians independently to assign the cause of death using the International Statistical Classification of Diseases and Related Health Problems (ICD)-10 codes. In case of disagreement between them, reconciliation was done, and in cases of persistent disagreements finally, adjudication was done by a third physician. InterVA-4-generated causes from close-ended questionnaires were compared using Kappa statistics with causes assigned by physicians using a questionnaire having both open- and close-ended questions. At the population level, Cause-Specific Mortality Fraction (CSMF) accuracy and P-value from McNemar’s paired Chi-square were calculated. CSMF accuracy indicates the absolute deviation of a set of proportions of causes of death out of the total number of deaths between the two methods.Results:The overall agreement between InterVA-4 and physician coding was ‘fair’ (κ=0.42; 95% confidence interval 0.38, 0.46). CSMF accuracy was found to be 0.71. The differences in proportions from the two methods were statistically different as per McNemar’s paired Chi-square test for ischaemic heart diseases, liver cirrhosis and maternal deaths.Interpretation & conclusions:In comparison to physicians, assignment of causes of death by InterVA- 4 was only ‘fair’. Hence, it may be appropriate to continue with physician review as the optimal option available in the current scenario.