Performance of InterVA for assigning causes of death to verbal autopsies: multisite validation study using clinical diagnostic gold standards

Telephonic verbal autopsies among adults in South Africa: a feasibility and acceptability pilot study

OBJECTIVE

This pilot study explores the feasibility and acceptability of using telephonic verbal autopsies (teleVAs) in South Africa to collect information on causes of death.

DESIGN

Quantitative and qualitative data collection methods were used to evaluate the feasibility and acceptability of these telephonic interviews.

SETTING

The teleVA pilot was conducted in South Africa's Western Cape province. The qualitative component also included two rural South African Population Research Infrastructure Network nodes (Africa Health Research Institute in KwaZulu-Natal and Agincourt in Mpumalanga), which had transitioned to teleVAs during COVID-19, allowing exploration of teleVA's feasibility in both urban and rural settings.

PARTICIPANTS

We recruited 229 respondents to participate in a pilot teleVA. After each VA, VA interviewers filled in a survey to assess their perceptions and discern if they experienced any technical challenges. We also conducted 18 in-depth interviews with both interviewers (n=6) and respondents (n=12) to explore their views on the acceptability of the teleVA. We conducted a thematic analysis of these interviews.

INTERVENTIONS

VA was piloted over the phone, instead of face-to-face.

PRIMARY AND SECONDARY OUTCOME MEASURES

Primary outcomes focused on the feasibility and acceptability of phone VAs among both interviewers and respondents. Secondary outcomes evaluated the quality of teleVAs.

RESULTS

Participants expressed willingness to participate in teleVAs, considering them valuable for public health planning and decision-making. The feasibility of collecting next-of-kin information proved challenging, with incomplete or incorrect contact details posing future logistic issues. Only one question out of 76, showed a statistically significant difference in the proportions of non-informative teleVA compared with face-to-face VA.

CONCLUSIONS

The study offers valuable insights into using teleVAs to gather cause of death information in resource-limited settings. It highlights the feasibility and acceptability of teleVAs while emphasising the need for comprehensive planning, integration with the civil registration and vital statistics system and community participation enhancement.

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.

Highly multiplexed targeted sequencing strategy for infectious disease surveillance

BACKGROUND

Global efforts to characterize diseases of poverty are hampered by lack of affordable and comprehensive detection platforms, resulting in suboptimal allocation of health care resources and inefficient disease control. Next generation sequencing (NGS) can provide accurate data and high throughput. However, shotgun and metagenome-based NGS approaches are limited by low concentrations of microbial DNA in clinical samples, requirements for tailored sample and library preparations plus extensive bioinformatics analysis. Here, we adapted molecular inversion probes (MIPs) as a cost-effective target enrichment approach to characterize microbial infections from blood samples using short-read sequencing. We designed a probe panel targeting 2 bacterial genera, 21 bacterial and 6 fungi species and 7 antimicrobial resistance markers (AMRs).

RESULTS

Our approach proved to be highly specific to detect down to 1 in a 1000 pathogen DNA targets contained in host DNA. Additionally, we were able to accurately survey pathogens and AMRs in 20 out of 24 samples previously profiled with routine blood culture for sepsis.

CONCLUSIONS

Overall, our targeted assay identifies microbial pathogens and AMRs with high specificity at high throughput, without the need for extensive sample preparation or bioinformatics analysis, simplifying its application for characterization and surveillance of infectious diseases in medium- to low- resource settings.

Value of Verbal Autopsy in a Fragile Setting: Reported versus Estimated Community Deaths Associated with COVID-19, Banadir, Somalia

BACKGROUND

Accurate mortality data associated with infectious diseases such as coronavirus disease 2019 (COVID-19) are often unavailable in countries with fragile health systems such as Somalia. We compared officially reported COVID-19 deaths in Somalia with COVID-19 deaths estimated using verbal autopsy.

METHODS

We interviewed relatives of deceased persons to collect information on symptoms, cause, and place of death. We compared these data with officially reported data and estimated the positive and negative predictive values of verbal autopsy.

RESULTS

We identified 530 deaths during March-October 2020. We classified 176 (33.2%) as probable COVID-19 deaths. Most deaths (78.5%; 416/530) occurred at home and 144 (34.6%) of these were attributed to COVID-19. The positive predictive value of verbal autopsy was lower for home deaths (22.3%; 95% CI: 15.7-30.1%) than for hospital deaths (32.3%; 95% CI: 16.7-51.4%). The negative predictive value was higher: 97.8% (95% CI: 95.0-99.3%) for home deaths and 98.4% (95% CI: 91.5-100%) for hospital deaths. Conclusions Verbal autopsy has acceptable predictive value to estimate COVID-19 deaths where disease prevalence is high and can provide data on the COVID-19 burden in countries with low testing and weak mortality surveillance where home deaths may be missed.

Validation studies of verbal autopsy methods: a systematic review

BACKGROUND

Verbal autopsy (VA) has emerged as an increasingly popular technique to assign cause of death in parts of the world where the majority of deaths occur without proper medical certification. The purpose of this study was to examine the key characteristics of studies that have attempted to validate VA cause of death against an established cause of death.

METHODS

A systematic review was conducted by searching the MEDLINE, EMBASE, Cochrane-library, and Scopus electronic databases. Included studies contained 1) a VA component, 2) a validation component, and 3) original analysis or re-analysis. Characteristics of VA studies were extracted. A total of 527 studies were assessed, and 481 studies screened to give 66 studies selected for data extraction.

RESULTS

Sixty-six studies were included from multiple countries. Ten studies used an existing database. Sixteen studies used the World Health Organization VA questionnaire and 5 studies used the Population Health Metrics Research Consortium VA questionnaire. Physician certification was used in 36 studies and computer coded methods were used in 14 studies. Thirty-seven studies used high level comparator data with detailed laboratory investigations.

CONCLUSION

Most studies found VA to be an effective cause of death assignment method and compared VA cause of death to a high-quality established cause of death. Nonetheless, there were inconsistencies in the methodologies of the validation studies, and many used poor quality comparison cause of death data. Future VA validation studies should adhere to consistent methodological criteria so that policymakers can easily interpret the findings to select the most appropriate VA method.

PROSPERO REGISTRATION

CRD42020186886.

Why mothers die: Analysis of verbal autopsy data from Kersa Health and Demographic Surveillance System, Eastern Ethiopia

Background

Despite registering tremendous improvement as part of the Millennium Development Goals, Ethiopia has still one of the highest numbers of maternal mortality. Although maternal mortality is one of the commonest indicators for comparison or measuring progress, its measurement remained a challenge. In a situation where, vital registration is not in place and only few women gave birth in facilities, alternative data sources from population-based surveys are essential to describe maternal deaths. In this paper, we reported estimates of maternal mortality and causes in a predominantly rural setting in eastern Ethiopia.

Methods

Data were used from the ongoing prospective open cohort of Kersa Health and Demographic Surveillance System (HDSS), located in eastern Ethiopia. At enrolment, detailed sociodemographic and household conditions were recorded for every member, followed by household visit every six months to identify any vital events: births, deaths, and migration. Whenever a death was reported, additional information about the deceased - age, sex, pregnancy status, and perceived cause of deaths - were collected through interview of the closest family member(s). Then, the probable cause of death was assigned using an automated verbal autopsy system (InterVA). In this paper, we included all deaths among women during pregnancy, childbirth or within 42 days of termination of pregnancy. To describe the trends, we calculated annual maternal mortality ratio (MMR) along with their 95% Confidence Interval (CI).

Results

From 2008 to 2019, a total of 32 680 live births and 720 deaths among reproductive age women were registered. Of the 720 deaths, 158 (21.9%) were during pregnancy or within 42 days of termination of pregnancy, corresponding with an MMR of 484 per 100 000 live births. The three leading causes of deaths were pregnancy related sepsis, obstetric haemorrhage and anaemia of pregnancy. There was non-significant reduction in the MMR from 744 in 2008 to 665 in 2019, with three lowest ratios recorded in 2013 (172 per 100 000 live births), 2009 (280 per 100 000 live births) and 2016 (285 per 100 000 live births).

Conclusions

There was no significant decrement of MMR during the study period. Most deaths occurred at home from pregnancy related sepsis and haemorrhage implicating the unfinished agenda of ensuring skilled delivery and appropriate postnatal management.

Assessing the Diagnostic Accuracy of Physicians for Home Death Certification in Shanghai: Application of SmartVA

Approximately 30% of deaths in Shanghai either occur at home or are not medically attended. The recorded cause of death (COD) in these cases may not be reliable. We applied the Smart Verbal Autopsy (VA) tool to assign the COD for a representative sample of home deaths certified by 16 community health centers (CHCs) from three districts in Shanghai, from December 2017 to June 2018. The results were compared with diagnoses from routine practice to ascertain the added value of using SmartVA. Overall, cause-specific mortality fraction (CSMF) accuracy improved from 0.93 (93%) to 0.96 after the application of SmartVA. A comparison with a “gold standard (GS)” diagnoses obtained from a parallel medical record review investigation found that 86.3% of the initial diagnoses made by the CHCs were assigned the correct COD, increasing to 90.5% after the application of SmartVA. We conclude that routine application of SmartVA is not indicated for general use in CHCs, although the tool did improve diagnostic accuracy for residual causes, such as other or ill-defined cancers and non-communicable diseases.

Comparison of the Causes of Death Identified Using Automated Verbal Autopsy and Complete Autopsy among Brought-in-Dead Cases at a Tertiary Hospital in Sub-Sahara Africa

BACKGROUND

Over one-third of deaths recorded at health facilities in Zambia are brought in dead (BID) and the causes of death (CODs) are not fully analyzed. The use of automated verbal autopsy (VA) has reportedly determined the CODs of more BID cases than the death notification form issued by the hospital. However, the validity of automated VA is yet to be fully investigated.

OBJECTIVES

To compare the CODs identified by automated VA with those by complete autopsy to examine the validity of a VA tool.

METHODS

The study site was the tertiary hospital in the capital city of Zambia. From September 2019 to January 2020, all BID cases aged 13 years and older brought to the hospital during the daytime on weekdays were enrolled in this study. External COD cases were excluded. The deceased's relatives were interviewed using the 2016 World Health Organization VA questionnaire. The data were analyzed using InterVA, an automated VA tool, to determine the CODs, which were compared with the results of complete autopsies.

RESULTS

A total of 63 cases were included. The CODs of 50 BID cases were determined by both InterVA and complete autopsies. The positive predictive value of InterVA was 22%. InterVA determined the CODs correctly in 100% cases of maternal CODs, 27.5% cases of noncommunicable disease CODs, and 5.3% cases of communicable disease CODs. Using the three broader disease groups, 56.0% cases were classified in the same groups by both methods.

CONCLUSION

While the positive predictive value was low, more than half of the cases were categorized into the same broader categories. However, there are several limitations in this study, including small sample size. More research is required to investigate the factors leading to discrepancies between the CODs determined by both methods to optimize the use of automated VA in Zambia.

An assessment of non-communicable disease mortality among adults in Eastern Uganda, 2010-2016

BACKGROUND

There is a dearth of studies assessing non-communicable disease (NCD) mortality within population-based settings in Uganda. We assessed mortality due to major NCDs among persons ≥ 30 years in Eastern Uganda from 2010 to 2016.

METHODS

The study was carried out at the Iganga-Mayuge health and demographic surveillance site in the Iganga and Mayuge districts of Eastern Uganda. Information on cause of death was obtained through verbal autopsies using a structured questionnaire to conduct face-face interviews with carers or close relatives of the deceased. Physicians assigned likely cause of death using ICD-10 codes. Age-adjusted mortality rates were calculated using direct method, with the average population across the seven years of the study (2010 to 2016) as the standard. Age categories of 30-40, 41-50, 51-60, 61-70, and ≥ 71 years were used for standardization.

RESULTS

A total of 1,210 deaths among persons ≥ 30 years old were reported from 2010 to 2016 (50.7% among women). Approximately 53% of all deaths were due to non-communicable diseases, 31.8% due to communicable diseases, 8.2% due to injuries, and 7% due to maternal-related deaths or undetermined causes. Cardiovascular diseases accounted for the largest proportion of NCD deaths in each year, and women had substantially higher cardiovascular disease mortality rates compared to men. Conversely, women had lower diabetes mortality rates than men for five of the seven years examined.

CONCLUSIONS

Non-communicable diseases are major causes of death among adults in Iganga and Mayuge; and cardiovascular diseases and diabetes are leading causes of NCD deaths. Efforts are needed to tackle NCD risk factors and provide NCD care to reduce associated burden and premature mortality.

Validation of verbal autopsy methods for assessment of child mortality in sub-Saharan Africa and the policy implication: a rapid review

Reliable data on the cause of child death is the cornerstone for evidence-informed health policy making towards improving child health outcomes. Unfortunately, accurate data on cause of death is essentially lacking in most countries of sub-Saharan Africa due to the widespread absence of functional Civil Registration and Vital Statistics (CRVS) systems. To address this problem, verbal autopsy (VA) has gained prominence as a strategy for obtaining Cause of Death (COD) information in populations where CRVS are absent. This study reviewed publications that investigated the validation of VA methods for assessment of COD. A MEDLINE PubMed search was undertaken in June 2018 for studies published in English that investigated the validation of VA methods in sub-Saharan Africa from 1990-2018. Of the 17 studies identified, 9 fulfilled the study inclusion criteria from which additional five relevant studies were found by reviewing their references. The result showed that Physician-Certified Verbal Autopsy (PCVA) was the most widely used VA method. Validation studies comparing PCVA to hospital records, expert algorithm and InterVA demonstrated mixed and highly varied outcomes. The accuracy and reliability of the VA methods depended on level of healthcare the respondents have access to and the knowledge of the physicians on the local disease aetiology and epidemiology. As the countries in sub-Saharan Africa continue to battle with dysfunctional CRVS system, VA will remain the only viable option for the supply of child mortality data necessary for policy making.

Engaging communities in collecting and using results from verbal autopsies for child deaths: an example from urban slums in Freetown, Sierra Leone

BACKGROUND

Verbal autopsies (VAs) can provide important epidemiological information about the causes of child deaths. Though studies have been conducted to assess the validity of various types of VAs, the programmatic experience of engaging local communities in collecting and using VA has received little attention in the published literature. Concern Worldwide, an international non-governmental organization (NGO), in collaboration with the Ministry of Health and Sanitation (MOHS), has implemented a VA protocol in five urban slums of Freetown, Sierra Leone. This paper provides VA results and describes lessons learned from the VA process.

METHODS

Under-five child deaths were registered by Community Health Workers (CHWs) in five urban slums between 2014 and 2017, and a specially trained local clinician used a VA protocol to interview caretakers. Symptoms were analysed using InterVA-4 computerized algorithm, a probabilistic expert-driven model to determine the most likely cause of death. Themes in care-seeking were extracted from multiple-choice and open-ended questions. VAs were implemented in collaboration with the community and the results were shared with community stakeholders in participatory review meetings.

RESULTS

Main challenges included limitations in death notification and capacity to conduct VA for all notified deaths. A total of 215 VA were available for analysis. Among 79 neonatal deaths aged 0-27 days, the most common cause of death was neonatal pneumonia (55%); among 136 children deaths aged 1-4 years, the most common causes were malaria (56%) and pneumonia (41%). Key themes in care-seeking identified included use of traditional medicine (14% of deaths), absence of care-seeking (23% of deaths), and difficultly reaching the health facility (8% of deaths that occurred at home) during fatal illness.

CONCLUSIONS

Conducting VAs as a collaborative process with communities is challenging but can provide valuable data that can be used for local-level decision-making. The findings have practical implications for engaging the community and CHWs in reducing the number of these preventable deaths through expanded efforts at prevention, early and appropriate treatment, and reduction of barriers to care-seeking. A functional end-to-end VA system can enhance meaningful routine vital events monitoring by community, national, and international stakeholders.

Barriers on the pathway to survival for children dying from treatable illnesses in Inhambane province, Mozambique

BACKGROUND

Mozambique has one of the highest under-5 mortality rates in the world. Community health workers (CHWs) are deployed to increase access to care; in Mozambique they are known as agentes polivalentes elementares (APEs). This study aimed to investigate child deaths in an area served by APEs by analysing the causes, care seeking patterns, and the influence of social capital.

METHODS

Caregivers of children under-5 who died in 2015 in Inhambane province, Mozambique, were interviewed using Verbal Autopsy/Social Autopsy (VA/SA) tools with a social capital module. VA data were analysed using the WHO InterVA analytical tool to determine cause of death. SA was analysed using the INDEPTH SA framework for illnesses lasting no more than three weeks. Social capital scores were calculated.

RESULTS

117 child deaths were reported; VA/SA was conducted for 115. Eighty-five had died from an acute illness lasting no more than three weeks, which in most cases could have been treated at community level; 50.6% died from malaria, 11.8% from HIV/AIDS, and 9.4% for each of diarrhoea and acute respiratory infections. In 35.3% the caregiver only noticed that the child was sick when symptoms of very severe illness developed. One in four children were never taken outside the home before dying. Sixteen children were first taken to an APE; of these 7 had signs of very severe illness. Caregivers who waited to seek care until the illness was very severe had a lower social capital score. The mean travel time to go to the APE was 2hrs 50min, which was not different from any other provider. Most received treatment from the APE, 3 were referred. The majority went to another provider after the APE; most to a health centre.

CONCLUSIONS

The leading causes of death in children under-5 can be detected, treated or referred by APEs. Major care seeking delays took place in the home, largely due to lack of early disease recognition and late decision-making. Low social capital, distance to APEs and to referral facilities likely contribute to these delays. Increasing caregiver illness awareness is urgently needed, as well as stronger referral linkages. A review of the geographical coverage and scope of work of APEs should be conducted.

Performance of InSilicoVA for assigning causes of death to verbal autopsies: multisite validation study using clinical diagnostic gold standards

BACKGROUND

Recently, a new algorithm for automatic computer certification of verbal autopsy data named InSilicoVA was published. The authors presented their algorithm as a statistical method and assessed its performance using a single set of model predictors and one age group.

METHODS

We perform a standard procedure for analyzing the predictive accuracy of verbal autopsy classification methods using the same data and the publicly available implementation of the algorithm released by the authors. We extend the original analysis to include children and neonates, instead of only adults, and test accuracy using different sets of predictors, including the set used in the original paper and a set that matches the released software.

RESULTS

The population-level performance (i.e., predictive accuracy) of the algorithm varied from 2.1 to 37.6% when trained on data preprocessed similarly as in the original study. When trained on data that matched the software default format, the performance ranged from -11.5 to 17.5%. When using the default training data provided, the performance ranged from -59.4 to -38.5%. Overall, the InSilicoVA predictive accuracy was found to be 11.6-8.2 percentage points lower than that of an alternative algorithm. Additionally, the sensitivity for InSilicoVA was consistently lower than that for an alternative diagnostic algorithm (Tariff 2.0), although the specificity was comparable.

CONCLUSIONS

The default format and training data provided by the software lead to results that are at best suboptimal, with poor cause-of-death predictive performance. This method is likely to generate erroneous cause of death predictions and, even if properly configured, is not as accurate as alternative automated diagnostic methods.

Social determinants of adult mortality from non-communicable diseases in northern Ethiopia, 2009-2015: Evidence from health and demographic surveillance site

INTRODUCTION

In developing countries, mortality and disability from non-communicable diseases (NCDs) is rising considerably. The effect of social determinants of NCDs-attributed mortality, from the context of developing countries, is poorly understood. This study examines the burden and socio-economic determinants of adult mortality attributed to NCDs in eastern Tigray, Ethiopia.

METHODS

We followed 45,982 adults implementing a community based dynamic cohort design recording mortality events from September 2009 to April 2015. A physician review based Verbal autopsy was used to identify the most probable causes of death. Multivariable Cox proportional hazards regression was performed to identify social determinants of NCD mortality.

RESULTS

Across the 193,758.7 person-years, we recorded 1,091 adult deaths. Compared to communicable diseases, NCDs accounted for a slightly higher proportion of adult deaths; 33% vs 34.5% respectively. The incidence density rate (IDR) of NCD attributed mortality was 194.1 deaths (IDR = 194.1; 95% CI = 175.4, 214.7) per 100,000 person-years. One hundred fifty-seven (41.8%), 68 (18.1%) and 34 (9%) of the 376 NCD deaths were due to cardiovascular disease, cancer and renal failure, respectively. In the multivariable analysis, age per 5-year increase (HR = 1.35; 95% CI: 1.30, 1.41), and extended family and non-family household members (HR = 2.86; 95% CI: 2.05, 3.98) compared to household heads were associated with a significantly increased hazard of NCD mortality. Although the difference was not statistically significant, compared to poor adults, those who were wealthy had a 15% (HR = 0.85; 95% CI: 0.65, 1.11) lower hazard of mortality from NCDs. On the other hand, literate adults (HR = 0.35; 95% CI: 0.13, 0.9) had a significantly decreased hazard of NCD attributed mortality compared to those adults who were unable to read and write. The effect of literacy was modified by age and its effect reduced by 18% for every 5-year increase of age among literate adults.

CONCLUSION

In summary, the study indicates that double mortality burden from both NCDs and communicable diseases was evident in northern rural Ethiopia. Public health intervention measures that prioritise disadvantaged NCD patients such as those who are unable to read and write, the elders, the extended family and non-family household co-residents could significantly reduce NCD mortality among the adult population.

Measuring mortality due to HIV-associated tuberculosis among adults in South Africa: Comparing verbal autopsy, minimally-invasive autopsy, and research data

BACKGROUND

The World Health Organization (WHO) aims to reduce tuberculosis (TB) deaths by 95% by 2035; tracking progress requires accurate measurement of TB mortality. International Classification of Diseases (ICD) codes do not differentiate between HIV-associated TB and HIV more generally. Verbal autopsy (VA) is used to estimate cause of death (CoD) patterns but has mostly been validated against a suboptimal gold standard for HIV and TB. This study, conducted among HIV-positive adults, aimed to estimate the accuracy of VA in ascertaining TB and HIV CoD when compared to a reference standard derived from a variety of clinical sources including, in some, minimally-invasive autopsy (MIA).

METHODS AND FINDINGS

Decedents were enrolled into a trial of empirical TB treatment or a cohort exploring diagnostic algorithms for TB in South Africa. The WHO 2012 instrument was used; VA CoD were assigned using physician-certified VA (PCVA), InterVA-4, and SmartVA-Analyze. Reference CoD were assigned using MIA, research, and health facility data, as available. 259 VAs were completed: 147 (57%) decedents were female; median age was 39 (interquartile range [IQR] 33-47) years and CD4 count 51 (IQR 22-102) cells/μL. Compared to reference CoD that included MIA (n = 34), VA underestimated mortality due to HIV/AIDS (94% reference, 74% PCVA, 47% InterVA-4, and 41% SmartVA-Analyze; chance-corrected concordance [CCC] 0.71, 0.42, and 0.31, respectively) and HIV-associated TB (41% reference, 32% PCVA; CCC 0.23). For individual decedents, all VA methods agreed poorly with reference CoD that did not include MIA (n = 259; overall CCC 0.14, 0.06, and 0.15 for PCVA, InterVA-4, and SmartVA-Analyze); agreement was better at population level (cause-specific mortality fraction accuracy 0.78, 0.61, and 0.57, for the three methods, respectively).

CONCLUSIONS

Current VA methods underestimate mortality due to HIV-associated TB. ICD and VA methods need modifications that allow for more specific evaluation of HIV-related deaths and direct estimation of mortality due to HIV-associated TB.

Global, regional, and national life expectancy, all-cause mortality, and cause-specific mortality for 249 causes of death, 1980-2015: a systematic analysis for the Global Burden of Disease Study 2015

BACKGROUND

Improving survival and extending the longevity of life for all populations requires timely, robust evidence on local mortality levels and trends. The Global Burden of Disease 2015 Study (GBD 2015) provides a comprehensive assessment of all-cause and cause-specific mortality for 249 causes in 195 countries and territories from 1980 to 2015. These results informed an in-depth investigation of observed and expected mortality patterns based on sociodemographic measures.

METHODS

We estimated all-cause mortality by age, sex, geography, and year using an improved analytical approach originally developed for GBD 2013 and GBD 2010. Improvements included refinements to the estimation of child and adult mortality and corresponding uncertainty, parameter selection for under-5 mortality synthesis by spatiotemporal Gaussian process regression, and sibling history data processing. We also expanded the database of vital registration, survey, and census data to 14 294 geography-year datapoints. For GBD 2015, eight causes, including Ebola virus disease, were added to the previous GBD cause list for mortality. We used six modelling approaches to assess cause-specific mortality, with the Cause of Death Ensemble Model (CODEm) generating estimates for most causes. We used a series of novel analyses to systematically quantify the drivers of trends in mortality across geographies. First, we assessed observed and expected levels and trends of cause-specific mortality as they relate to the Socio-demographic Index (SDI), a summary indicator derived from measures of income per capita, educational attainment, and fertility. Second, we examined factors affecting total mortality patterns through a series of counterfactual scenarios, testing the magnitude by which population growth, population age structures, and epidemiological changes contributed to shifts in mortality. Finally, we attributed changes in life expectancy to changes in cause of death. We documented each step of the GBD 2015 estimation processes, as well as data sources, in accordance with Guidelines for Accurate and Transparent Health Estimates Reporting (GATHER).

FINDINGS

Globally, life expectancy from birth increased from 61·7 years (95% uncertainty interval 61·4-61·9) in 1980 to 71·8 years (71·5-72·2) in 2015. Several countries in sub-Saharan Africa had very large gains in life expectancy from 2005 to 2015, rebounding from an era of exceedingly high loss of life due to HIV/AIDS. At the same time, many geographies saw life expectancy stagnate or decline, particularly for men and in countries with rising mortality from war or interpersonal violence. From 2005 to 2015, male life expectancy in Syria dropped by 11·3 years (3·7-17·4), to 62·6 years (56·5-70·2). Total deaths increased by 4·1% (2·6-5·6) from 2005 to 2015, rising to 55·8 million (54·9 million to 56·6 million) in 2015, but age-standardised death rates fell by 17·0% (15·8-18·1) during this time, underscoring changes in population growth and shifts in global age structures. The result was similar for non-communicable diseases (NCDs), with total deaths from these causes increasing by 14·1% (12·6-16·0) to 39·8 million (39·2 million to 40·5 million) in 2015, whereas age-standardised rates decreased by 13·1% (11·9-14·3). Globally, this mortality pattern emerged for several NCDs, including several types of cancer, ischaemic heart disease, cirrhosis, and Alzheimer's disease and other dementias. By contrast, both total deaths and age-standardised death rates due to communicable, maternal, neonatal, and nutritional conditions significantly declined from 2005 to 2015, gains largely attributable to decreases in mortality rates due to HIV/AIDS (42·1%, 39·1-44·6), malaria (43·1%, 34·7-51·8), neonatal preterm birth complications (29·8%, 24·8-34·9), and maternal disorders (29·1%, 19·3-37·1). Progress was slower for several causes, such as lower respiratory infections and nutritional deficiencies, whereas deaths increased for others, including dengue and drug use disorders. Age-standardised death rates due to injuries significantly declined from 2005 to 2015, yet interpersonal violence and war claimed increasingly more lives in some regions, particularly in the Middle East. In 2015, rotaviral enteritis (rotavirus) was the leading cause of under-5 deaths due to diarrhoea (146 000 deaths, 118 000-183 000) and pneumococcal pneumonia was the leading cause of under-5 deaths due to lower respiratory infections (393 000 deaths, 228 000-532 000), although pathogen-specific mortality varied by region. Globally, the effects of population growth, ageing, and changes in age-standardised death rates substantially differed by cause. Our analyses on the expected associations between cause-specific mortality and SDI show the regular shifts in cause of death composition and population age structure with rising SDI. Country patterns of premature mortality (measured as years of life lost [YLLs]) and how they differ from the level expected on the basis of SDI alone revealed distinct but highly heterogeneous patterns by region and country or territory. Ischaemic heart disease, stroke, and diabetes were among the leading causes of YLLs in most regions, but in many cases, intraregional results sharply diverged for ratios of observed and expected YLLs based on SDI. Communicable, maternal, neonatal, and nutritional diseases caused the most YLLs throughout sub-Saharan Africa, with observed YLLs far exceeding expected YLLs for countries in which malaria or HIV/AIDS remained the leading causes of early death.

INTERPRETATION

At the global scale, age-specific mortality has steadily improved over the past 35 years; this pattern of general progress continued in the past decade. Progress has been faster in most countries than expected on the basis of development measured by the SDI. Against this background of progress, some countries have seen falls in life expectancy, and age-standardised death rates for some causes are increasing. Despite progress in reducing age-standardised death rates, population growth and ageing mean that the number of deaths from most non-communicable causes are increasing in most countries, putting increased demands on health systems.

FUNDING

Bill & Melinda Gates Foundation.

Causes of Death among Children Aged 5 to 14 Years Old from 2008 to 2013 in Kersa Health and Demographic Surveillance System (Kersa HDSS), Ethiopia

Background

The global burden of mortality among children is still very huge though its trend has started declining following the improvements in the living standard. It presents serious challenges to the well-being of children in many African countries. Today, Sub-Saharan Africa alone accounts for about 50% of global child mortality. The overall objective of this study was to determine the magnitude and distribution of causes of death among children aged 5 to 14 year olds in the population of Kersa HDSS using verbal autopsy method for the period 2008 to 2013.

Methods

Kersa Health and Demographic Surveillance System(Kersa HDSS) was established in September 2007. The center consists of 10 rural and 2 urban kebeles which were selected randomly from 38 kebeles in the district. Thus this study was conducted in Kersa HDSS and data was taken from Kersa HDSS database. The study population included all children aged 5 to 14 years registered during the period of 2008 to 2013 in Kersa HDSS using age specific VA questionnaires. Data were extracted from SPSS database and analyzed using STATA.

Results

A total of 229 deaths were recorded over the period of six years with a crude death rate of 219.6 per 100,000 population of this age group over the study period. This death rate was 217.5 and 221.5 per 100,000 populations for females and males, respectively. 75% of deaths took place at home. The study identified severe malnutrition(33.9%), intestinal infectious diseases(13.8%) and acute lower respiratory infections(9.2%) to be the three most leading causes of death. In broad causes of death classification, injuries have been found to be the second most cause of death next to communicable diseases(56.3%) attributing to 13.1% of the total deaths.

Conclusion and Recommendation

In specific causes of death classification severe malnutrition, intestinal infectious diseases and acute lower respiratory infections were the three leading causes of death where, in broad causes of death communicable diseases and injuries were among the leading causes of death. Hence, concerned bodies should take measures to avert the situation of mortality from these causes of death and further inferential analysis into the prevention and management of infectious diseases should also be taken.

Endemic Cardiovascular Diseases of the Poorest Billion

The poorest billion people are distributed throughout the world, though most are concentrated in rural sub-Saharan Africa and South Asia. Cardiovascular disease (CVD) data can be sparse in low- and middle-income countries beyond urban centers. Despite this urban bias, CVD registries from the poorest countries have long revealed a predominance of nonatherosclerotic stroke, hypertensive heart disease, nonischemic and Chagas cardiomyopathies, rheumatic heart disease, and congenital heart anomalies, among others. Ischemic heart disease has been relatively uncommon. Here, we summarize what is known about the epidemiology of CVDs among the world’s poorest people and evaluate the relevance of global targets for CVD control in this population. We assessed both primary data sources, and the 2013 Global Burden of Disease Study modeled estimates in the world’s 16 poorest countries where 62% of the population are among the poorest billion. We found that ischemic heart disease accounted for only 12% of the combined CVD and congenital heart anomaly disability-adjusted life years (DALYs) in the poorest countries, compared with 51% of DALYs in high-income countries. We found that as little as 53% of the combined CVD and congenital heart anomaly burden (1629/3049 DALYs per 100 000) was attributed to behavioral or metabolic risk factors in the poorest countries (eg, in Niger, 82% of the population among the poorest billion) compared with 85% of the combined CVD and congenital heart anomaly burden (4439/5199 DALYs) in high-income countries. Further, of the combined CVD and congenital heart anomaly burden, 34% was accrued in people under age 30 years in the poorest countries, while only 3% is accrued under age 30 years in high-income countries. We conclude although the current global targets for noncommunicable disease and CVD control will help diminish premature CVD death in the poorest populations, they are not sufficient. Specifically, the current framework (1) excludes deaths of people <30 years of age and deaths attributable to congenital heart anomalies, and (2) emphasizes interventions to prevent and treat conditions attributed to behavioral and metabolic risks factors. We recommend a complementary strategy for the poorest populations that targets premature death at younger ages, addresses environmental and infectious risks, and introduces broader integrated health system interventions, including cardiac surgery for congenital and rheumatic heart disease.

Mass HIV Treatment and Sex Disparities in Life Expectancy: Demographic Surveillance in Rural South Africa

BACKGROUND

Women have better patient outcomes in HIV care and treatment than men in sub-Saharan Africa. We assessed--at the population level--whether and to what extent mass HIV treatment is associated with changes in sex disparities in adult life expectancy, a summary metric of survival capturing mortality across the full cascade of HIV care. We also determined sex-specific trends in HIV mortality and the distribution of HIV-related deaths in men and women prior to and at each stage of the clinical cascade.

METHODS AND FINDINGS

Data were collected on all deaths occurring from 2001 to 2011 in a large population-based surveillance cohort (52,964 women and 45,688 men, ages 15 y and older) in rural KwaZulu-Natal, South Africa. Cause of death was ascertained by verbal autopsy (93% response rate). Demographic data were linked at the individual level to clinical records from the public sector HIV treatment and care program that serves the region. Annual rates of HIV-related mortality were assessed for men and women separately, and female-to-male rate ratios were estimated in exponential hazard models. Sex-specific trends in adult life expectancy and HIV-cause-deleted adult life expectancy were calculated. The proportions of HIV deaths that accrued to men and women at different stages in the HIV cascade of care were estimated annually. Following the beginning of HIV treatment scale-up in 2004, HIV mortality declined among both men and women. Female adult life expectancy increased from 51.3 y (95% CI 49.7, 52.8) in 2003 to 64.5 y (95% CI 62.7, 66.4) in 2011, a gain of 13.2 y. Male adult life expectancy increased from 46.9 y (95% CI 45.6, 48.2) in 2003 to 55.9 y (95% CI 54.3, 57.5) in 2011, a gain of 9.0 y. The gap between female and male adult life expectancy doubled, from 4.4 y in 2003 to 8.6 y in 2011, a difference of 4.3 y (95% CI 0.9, 7.6). For women, HIV mortality declined from 1.60 deaths per 100 person-years (95% CI 1.46, 1.75) in 2003 to 0.56 per 100 person-years (95% CI 0.48, 0.65) in 2011. For men, HIV-related mortality declined from 1.71 per 100 person-years (95% CI 1.55, 1.88) to 0.76 per 100 person-years (95% CI 0.67, 0.87) in the same period. The female-to-male rate ratio for HIV mortality declined from 0.93 (95% CI 0.82-1.07) in 2003 to 0.73 (95% CI 0.60-0.89) in 2011, a statistically significant decline (p = 0.046). In 2011, 57% and 41% of HIV-related deaths occurred among men and women, respectively, who had never sought care for HIV in spite of the widespread availability of free HIV treatment. The results presented here come from a poor rural setting in southern Africa with high HIV prevalence and high HIV treatment coverage; broader generalizability is unknown. Additionally, factors other than HIV treatment scale-up may have influenced population mortality trends.

CONCLUSIONS

Mass HIV treatment has been accompanied by faster declines in HIV mortality among women than men and a growing female-male disparity in adult life expectancy at the population level. In 2011, over half of male HIV deaths occurred in men who had never sought clinical HIV care. Interventions to increase HIV testing and linkage to care among men are urgently needed.

Measuring causes of death in populations: a new metric that corrects cause-specific mortality fractions for chance

Background

Verbal autopsy is gaining increasing acceptance as a method for determining the underlying cause of death when the cause of death given on death certificates is unavailable or unreliable, and there are now a number of alternative approaches for mapping from verbal autopsy interviews to the underlying cause of death. For public health applications, the population-level aggregates of the underlying causes are of primary interest, expressed as the cause-specific mortality fractions (CSMFs) for a mutually exclusive, collectively exhaustive cause list. Until now, CSMF Accuracy is the primary metric that has been used for measuring the quality of CSMF estimation methods. Although it allows for relative comparisons of alternative methods, CSMF Accuracy provides misleading numbers in absolute terms, because even random allocation of underlying causes yields relatively high CSMF accuracy. Therefore, the objective of this study was to develop and test a measure of CSMF that corrects this problem.

Methods

We developed a baseline approach of random allocation and measured its performance analytically and through Monte Carlo simulation. We used this to develop a new metric of population-level estimation accuracy, the Chance Corrected CSMF Accuracy (CCCSMF Accuracy), which has value near zero for random guessing, and negative quality values for estimation methods that are worse than random at the population level.

Results

The CCCSMF Accuracy formula was found to be CCSMF Accuracy = (CSMF Accuracy - 0.632) / (1 - 0.632), which indicates that, at the population-level, some existing and commonly used VA methods perform worse than random guessing.

Conclusions

CCCSMF Accuracy should be used instead of CSMF Accuracy when assessing VA estimation methods because it provides a more easily interpreted measure of the quality of population-level estimates.

Electronic supplementary material

The online version of this article (doi:10.1186/s12963-015-0061-1) contains supplementary material, which is available to authorized users.

Local perceptions of causes of death in rural South Africa: a comparison of perceived and verbal autopsy causes of death

Background

Understanding how lay people perceive the causes of mortality and their associated risk factors is important for public health. In resource-limited settings, where verbal autopsy (VA) is used as the most expedient method of determining cause of death, it is important to understand how pre-existing concepts of cause of death among VA-informants may influence their VA-responses and the consequential impact on cause of death assessment. This study describes the agreement between VA-derived causes of death and informant-perceived causes and associated influential factors, which also reflects lay health literacy in this setting.

Method

Using 20 years of VA data (n=11,228) from the Agincourt Health and Demographic Surveillance System (HDSS) site in rural South Africa, we explored the agreement between the causes of death perceived by the VA-informants and those assigned by the automated Inter-VA tool. Kappa statistics and concordance correlation coefficients were applied to measure agreement at individual and population levels, respectively. Multivariable regression models were used to explore factors associated with recognised lay perceptions of causes of mortality.

Results

Agreement between informant-perceived and VA-derived causes of death at the individual level was limited, but varied substantially by cause of death. However, agreement at the population level, comparing cause-specific mortality fractions was higher, with the notable exception of bewitchment as a cause. More recent deaths, those in adults aged 15–49 years, deaths outside the home, and those associated with external causes showed higher concordance with InterVA.

Conclusion

Overall, informant perception of causes of death was limited, but depended on informant characteristics and causes of death, and to some extent involved non-biomedical constructs. Understanding discordance between perceived and recognised causes of death is important for public health planning; low community understanding of causes of death may be detrimental to public health. These findings also illustrate the importance of using rigorous and standardised VA methods rather than relying on informants’ reported causes of death.

How much do the physician review and InterVA model agree in determining causes of death? A comparative analysis of deaths in rural Ethiopia

Background

Despite it is costly, slow and non-reproducible process, physician review (PR) is a commonly used method to interpret verbal autopsy data. However, there is a growing interest to adapt a new automated and internally consistent method called InterVA. This study evaluated the level of agreement in determining causes of death between PR and the InterVA model.

Methods

Verbal autopsy data for 434 cases collected between September 2009 and November 2012, were interpreted using both PR and the InterVA model. Cohen’s kappa statistic (κ) was used to compare the level of chance corrected case-by-case agreement in the diagnosis reached by the PR and InterVA model.

Results

Both methods gave comparable cause specific mortality fractions of communicable diseases (36.6 % by PR and 36.2 % by the model), non-communicable diseases (31.1 % by PR and 38.2 % by the model) and accidents/injuries (12.9 % by PR and 10.1 % by the model). The level of case-by-case chance corrected concordance between the two methods was 0.33 (95 % CI for κ = 0.29–0.34). The highest and lowest agreements were seen for accidents/injuries and non-communicable diseases; with κ = 0.75 and κ = 0.37, respectively.

Conclusion

If the InterVA were used in place of the existing PR process, the overall diagnosis would be fairly similar. The methods had better agreement in important public health diseases like; TB, perinatal causes, and pneumonia/sepsis; and lower in cardiovascular diseases and neoplasms. Therefore, both methods need to be validated against a gold-standard diagnosis of death.

Electronic supplementary material

The online version of this article (doi:10.1186/s12889-015-2032-7) contains supplementary material, which is available to authorized users.

Let's talk about death: data collection for verbal autopsies in a demographic and health surveillance site in Malaysia

BACKGROUND

Verbal autopsies have gained considerable ground as an acceptable alternative to medically determined cause of death. Unlike with clinical or more administrative settings for data collection, verbal autopsies require significant involvement of families and communities, which introduces important social and cultural considerations. However, there is very little clear guidance about the methodological issues in data collection. The objectives of this case study were: to explore the range of bereavement rituals within the multi-ethnic, multi-faith population of the district; to investigate the preparedness of communities to talk about death; to describe the verbal autopsy process; to assess the effects of collecting verbal autopsy data on data collectors; and to determine the most accurate sources of information about deaths in the community.

METHODS

A case study approach was used, using focus group discussions, indepth interviews and field notes. Thematic analyses were undertaken using NVivo.

RESULTS

Consideration of cultural bereavement practices is importance to acceptance and response rates to verbal autopsies. They are also important to the timing of verbal autopsy interviews. Well trained data collectors, regardless of health qualifications are able to collect good quality data, but debriefing is important to their health and well being. This article contributes to guidance on the data collection procedures for verbal autopsies within community settings.

Verbal Autopsy: Evaluation of Methods to Certify Causes of Death in Uganda

To assess different methods for determining cause of death from verbal autopsy (VA) questionnaire data, the intra-rater reliability of Physician-Certified Verbal Autopsy (PCVA) and the accuracy of PCVA, expert-derived (non-hierarchical) and data-driven (hierarchal) algorithms were assessed for determining common causes of death in Ugandan children. A verbal autopsy validation study was conducted from 2008-2009 in three different sites in Uganda. The dataset included 104 neonatal deaths (0-27 days) and 615 childhood deaths (1-59 months) with the cause(s) of death classified by PCVA and physician review of hospital medical records (the 'reference standard'). Of the original 719 questionnaires, 141 (20%) were selected for a second review by the same physicians; the repeat cause(s) of death were compared to the original,and agreement assessed using the Kappa statistic.Physician reviewers' refined non-hierarchical algorithms for common causes of death from existing expert algorithms, from which, hierarchal algorithms were developed. The accuracy of PCVA, non-hierarchical, and hierarchical algorithms for determining cause(s) of death from all 719 VA questionnaires was determined using the reference standard. Overall, intra-rater repeatability was high (83% agreement, Kappa 0.79 [95% CI 0.76-0.82]). PCVA performed well, with high specificity for determining cause of neonatal (>67%), and childhood (>83%) deaths, resulting in fairly accurate cause-specific mortality fraction (CSMF) estimates. For most causes of death in children, non-hierarchical algorithms had higher sensitivity, but correspondingly lower specificity, than PCVA and hierarchical algorithms, resulting in inaccurate CSMF estimates. Hierarchical algorithms were specific for most causes of death, and CSMF estimates were comparable to the reference standard and PCVA. Inter-rater reliability of PCVA was high, and overall PCVA performed well. Hierarchical algorithms performed better than non-hierarchical algorithms due to higher specificity and more accurate CSMF estimates. Use of PCVA to determine cause of death from VA questionnaire data is reasonable while automated data-driven algorithms are improved.

Trends in Causes of Adult Deaths among the Urban Poor: Evidence from Nairobi Urban Health and Demographic Surveillance System, 2003-2012

What kills people around the world and how it varies from place to place and over time is critical in mapping the global burden of disease and therefore, a relevant public health question, especially in developing countries. While more than two thirds of deaths worldwide are in developing countries, little is known about the causes of death in these nations. In many instances, vital registration systems are nonexistent or at best rudimentary, and even when deaths are registered, data on the cause of death in particular local contexts, which is an important step toward improving context-specific public health, are lacking. In this paper, we examine the trends in the causes of death among the urban poor in two informal settlements in Nairobi by applying the InterVA-4 software to verbal autopsy data. We examine cause of death data from 2646 verbal autopsies of deaths that occurred in the Nairobi Urban Health and Demographic Surveillance System (NUHDSS) between 1 January 2003 and 31 December 2012 among residents aged 15 years and above. The data is entered into the InterVA-4 computer program, which assigns cause of death using probabilistic modeling. The results are presented as annualized trends from 2003 to 2012 and disaggregated by gender and age. Over the 10-year period, the three major causes of death are tuberculosis (TB), injuries, and HIV/AIDS, accounting for 26.9, 20.9, and 17.3% of all deaths, respectively. In 2003, HIV/AIDS was the highest cause of death followed by TB and then injuries. However, by 2012, TB and injuries had overtaken HIV/AIDS as the major causes of death. When this is examined by gender, HIV/AIDS was consistently higher for women than men across all the years generally by a ratio of 2 to 1. In terms of TB, it was more evenly distributed across the years for both males and females. We find that there is significant gender variation in deaths linked to injuries, with male deaths being higher than female deaths by a ratio of about 4 to 1. We also find a fifteen percentage point increase in the incidences of male deaths due to injuries between 2003 and 2012. For women, the corresponding deaths due to injuries remain fairly stable throughout the period. We find cardiovascular diseases as a significant cause of death over the period, with overall mortality increasing steadily from 1.6% in 2003 to 8.1% in 2012, and peaking at 13.7% in 2005 and at 12.0% in 2009. These deaths were consistently higher among women. We identified substantial variations in causes of death by age, with TB, HIV/AIDS, and CVD deaths lowest among younger residents and increasing with age, while injury-related deaths are highest among the youngest adults 15-19 and steadily declined with age. Also, deaths related to neoplasms and respiratory tract infections (RTIs) were prominent among older adults 50 years and above, especially since 2005. Emerging at this stage is evidence that HIV/AIDS, TB, injuries, and cardiovascular disease are linked to approximately 73% of all adult deaths among the urban poor in Nairobi slums of Korogocho and Viwandani in the last 10 years. While mortality related to HIV/AIDS is generally declining, we see an increasing proportion of deaths due to TB, injuries, and cardiovascular diseases. In sum, substantial epidemiological transition is ongoing in this local context, with deaths linked to communicable diseases declining from 66% in 2003 to 53% in 2012, while deaths due to noncommunicable causes experienced a four-fold increase from 5% in 2003 to 21.3% in 2012, together with another two-fold increase in deaths due to external causes (injuries) from 11% in 2003 to 22% in 2012. It is important to also underscore the gender dimensions of the epidemiological transition clearly visible in the mix. Finally, the elevated levels of disadvantage of slum dwellers in our analysis relative to other population subgroups in Kenya continue to demonstrate appreciable deterioration of key urban health and social indicators, highlighting the need for a deliberate strategic focus on the health needs of the urban poor in policy and program efforts toward achieving international goals and national health and development targets.

Mortality in Cambodia: an 18-month prospective community-based surveillance of all-age deaths using verbal autopsies

To estimate the 2009-2010 death rates, causes, and patterns of mortality in rural Cambodia, we conducted active, population-based death surveillance in 25 rural villages of Cambodia from March 2009 to August 2010. Among the population of 28,053 under surveillance, 280 deaths were reported and explored by physician-certified verbal autopsies, using the International Classification of Diseases 10, yielding an overall mortality rate (MR) of 6.7/1000 persons-year (95% CI 5.74-7.68). The MR was 39.1/1000 live births for those younger than 5 years old. Infants accounted for 5.4% of all deaths. In children younger than 5 years, infectious and parasitic diseases were the leading causes of death. In children 5 to 14 years, 3 out of 4 deaths were due to injuries. Adult deaths were mainly attributed to noncommunicable diseases (52%). We conclude that this rural population is facing a substantial burden of noncommunicable diseases while still struggling with infectious diseases, respiratory diseases in particular.

Validating estimates of prevalence of non-communicable diseases based on household surveys: the symptomatic diagnosis study

BACKGROUND

Easy-to-collect epidemiological information is critical for the more accurate estimation of the prevalence and burden of different non-communicable diseases around the world. Current measurement is restricted by limitations in existing measurement systems in the developing world and the lack of biometry tests for non-communicable diseases. Diagnosis based on self-reported signs and symptoms ("Symptomatic Diagnosis," or SD) analyzed with computer-based algorithms may be a promising method for collecting timely and reliable information on non-communicable disease prevalence. The objective of this study was to develop and assess the performance of a symptom-based questionnaire to estimate prevalence of non-communicable diseases in low-resource areas.

METHODS

As part of the Population Health Metrics Research Consortium study, we collected 1,379 questionnaires in Mexico from individuals who suffered from a non-communicable disease that had been diagnosed with gold standard diagnostic criteria or individuals who did not suffer from any of the 10 target conditions. To make the diagnosis of non-communicable diseases, we selected the Tariff method, a technique developed for verbal autopsy cause of death calculation. We assessed the performance of this instrument and analytical techniques at the individual and population levels.

RESULTS

The questionnaire revealed that the information on health care experience retrieved achieved 66.1% (95% uncertainty interval [UI], 65.6-66.5%) chance corrected concordance with true diagnosis of non-communicable diseases using health care experience and 0.826 (95% UI, 0.818-0.834) accuracy in its ability to calculate fractions of different causes. SD is also capable of outperforming the current estimation techniques for conditions estimated by questionnaire-based methods.

CONCLUSIONS

SD is a viable method for producing estimates of the prevalence of non-communicable diseases in areas with low health information infrastructure. This technology can provide higher-resolution prevalence data, more flexible data collection, and potentially individual diagnoses for certain conditions.

Health & Demographic Surveillance System Profile: The Taabo Health and Demographic Surveillance System, Côte d'Ivoire

The Taabo Health and Demographic Surveillance System (HDSS) is located in south-central Côte d'Ivoire, approximately 150 km north-west of Abidjan. The Taabo HDSS started surveillance activities in early 2009 and the man-made Lake Taabo is a key eco-epidemiological feature. Since inception, there has been a strong interest in research and integrated control of water-associated diseases such as schistosomiasis and malaria. The Taabo HDSS has generated setting-specific evidence on the impact of targeted interventions against malaria, schistosomiasis and other neglected tropical diseases. The Taabo HDSS consists of a small town, 13 villages and over 100 hamlets. At the end of 2013, a total population of 42 480 inhabitants drawn from 6707 households was under surveillance. Verbal autopsies have been conducted to determine causes of death. Repeated cross-sectional epidemiological surveys on approximately 5-7% of the population and specific, layered-on haematological, parasitological and questionnaire surveys have been conducted. The Taabo HDSS provides a database for surveys, facilitates interdisciplinary research, as well as surveillance, and provides a platform for the evaluation of health interventions. Requests to collaborate and to access data are welcome and should be addressed to the secretariat of the Centre Suisse de Recherches Scientifiques en Côte d'Ivoire: [secretariat@csrs.ci].

Nationwide evaluation of malaria infections, morbidity, mortality, and coverage of malaria control interventions in Madagascar

BACKGROUND

In the last decade, an important scale-up was observed in malaria control interventions. Madagascar entered the process for pre-elimination in 2007. Policy making needs operational indicators, but also indicators about effectiveness and impact of malaria control interventions (MCI). This study is aimed at providing data about malaria infection, morbidity, and mortality, and MCI in Madagascar.

METHODS

Two nationwide surveys were simultaneously conducted in 2012-2013 in Madagascar: a study about non-complicated clinical malaria cases in 31 sentinel health facilities, and a cross-sectional survey (CSS) in 62 sites. The CSS encompassed interviews, collection of biological samples and verbal autopsies (VA). Data from CSS were weighted for age, sex, malaria transmission pattern, and population density. VA data were processed with InterVA-4 software.

RESULTS

CSS included 15,746 individuals of all ages. Parasite rate (PR) as measured by rapid diagnostic tests was 3.1%, and was significantly higher in five to 19 year olds, in males, poorer socio-economic status (SES) quintiles and rural areas. Long-lasting insecticidal nets (LLIN) use was 41.7% and was significantly lower in five to 19 year olds, males and wealthier SES quintiles. Proportion of persons covered by indoor residual spraying (IRS) was 66.8% in targeted zones. Proportion of persons using other insecticides than IRS was 22.8%. Coverage of intermittent preventive treatment during pregnancy was 21.5%. Exposure to information, education and communication messages about malaria was significantly higher in wealthier SES for all media but information meetings. The proportion of fever case managements considered as appropriate with regard to malaria was 15.8%. Malaria was attributed as the cause of death in 14.0% of 86 VA, and 50% of these deaths involved persons above the age of five years. The clinical case study included 818 cases of which people above the age of five accounted for 79.7%. In targeted zones, coverage of LLIN and IRS were lower in clinical cases than in general population.

CONCLUSIONS

This study provides valuable data for the evaluation of effectiveness and factors affecting MCI. MCI and evaluation surveys should consider the whole population and not only focus on under-fives and pregnant women in pre-elimination or elimination strategies.

Estimating cause of adult (15+ years) death using InterVA-4 in a rural district of southern Ghana

Background

Data needed to estimate causes of death and the pattern of these deaths are scarce in sub-Saharan Africa. Such data are very important for targeting, monitoring, and evaluating health interventions.

Objective

To estimate the mortality rate and determine causes of death among adults (aged 15 years and older) in a rural district of southern Ghana, using the InterVA-4 model.

Design

Data used were generated from verbal autopsies conducted for registered adult members of the Dodowa Health and Demographic Surveillance System who died between 2006 and 2010. The InterVA-4 model was used to assign the cause of death.

Results

Overall, the mortality rate for the period under review was 7.5/1,000 person-years (py) for the general population and 10.4/1,000 py for those aged 15 and older. The leading cause of death was communicable diseases (CDs), with a malaria-specific mortality rate of 1.06/1,000 py. Pulmonary tuberculosis (TB)-specific mortality rate was the next highest (1.01/1,000 py). HIV/AIDS attributed deaths were lower among males than females. Non-communicable diseases (NCDs) contributed to 28.3% of the deaths with cause-specific mortality rate of 2.93/1,000 py. Stroke topped the list with cause-specific mortality rate of 0.69/1,000 py. As expected, young males (15–49 years) contributed to more road traffic accident (RTA) deaths; they had a lower RTA cause-specific mortality rate than older males (50–64 years).

Conclusions

Data indicate that CDs (e.g. malaria and TB) remain the major cause of death with NCDs (e.g. stroke) following closely behind. Verbal autopsy data can provide the causes of mortality in poorly resourced settings where access to timely and accurate data is scarce.

Causes of death among females-investigating beyond maternal causes: a community-based longitudinal study

Background

In developing countries, investigating mortality levels and causes of death among all age female population despite the childhood and maternal related deaths is important to design appropriate and tailored interventions and to improve survival of female residents.

Methods

Under Kilite-Awlealo Health and Demographic Surveillance System, we investigated mortality rates and causes of death in a cohort of female population from 1st of January 2010 to 31st of December 2012. At the baseline, 33,688 females were involved for the prospective follow-up study. Households under the study were updated every six months by fulltime surveillance data collectors to identify vital events, including deaths. Verbal Autopsy (VA) data were collected by separate trained data collectors for all identified deaths in the surveillance site. Trained physicians assigned underlining causes of death using the 10th edition of International Classification of Diseases (ICD). We assessed overall, age- and cause-specific mortality rates per 1000 person-years. Causes of death among all deceased females and by age groups were ranked based on cause specific mortality rates. Analysis was performed using Stata Version 11.1.

Results

During the follow-up period, 105,793.9 person-years of observation were generated, and 398 female deaths were recorded. This gave an overall mortality rate of 3.76 (95% confidence interval (CI): 3.41, 4.15) per 1,000 person-years. The top three broad causes of death were infectious and parasitic diseases (1.40 deaths per 1000 person-years), non-communicable diseases (0.98 deaths per 1000 person-years) and external causes (0.36 per 1000 person-years). Most deaths among reproductive age female were caused by Human Deficiency Virus/Acquired Immune Deficiency Virus (HIV/AIDS) and tuberculosis (0.14 per 1000 person-years for each cause). Pregnancy and childbirth related causes were responsible for few deaths among women of reproductive age—3 out of 73 deaths (4.1%) or 5.34 deaths per 1,000 person-years.

Conclusions

Communicable diseases are continued to be the leading causes of death among all age females. HIV/AIDS and tuberculosis were major causes of death among women of reproductive age. Together with existing efforts to prevent pregnancy and childbirth related deaths, public health and curative interventions on other causes, particularly on HIV/AIDS and tuberculosis, should be strengthened.

Cause of death among infants in rural western China: a community-based study using verbal autopsy

OBJECTIVES

To determine the causes of death among infants in high-mortality areas of western China with the use of globally recognized methods.

STUDY DESIGN

A survey of all infant deaths identified over 1 year in 4 counties in Yunnan and Xinjiang in which combined verbal autopsy was combined with a physician's diagnosis of the cause to calculate the local infant mortality rate.

RESULTS

Among 470 completed investigations, a cause of death was assigned to 423 cases (90%). Overall, pneumonia (34.5%), preterm birth complications (16.5%), diarrhea (10.4%), birth asphyxia (10.3%), and congenital abnormalities (8.5%) were the main causes, with 56.6% of deaths occurring in the neonatal period. Deaths were attributable predominantly to prematurity or birth asphyxia in the early neonatal period, whereas infection accounted for more than 60% and 80% of deaths in the late and postneonatal periods, respectively. Calculated infant mortality was 21.9 in 1000 live births.

CONCLUSIONS

The pattern of infant mortality observed in the surveyed counties differs markedly from that reported previously at the national level, with a high proportion the result of causes that may be preventable with globally recommended interventions. Financial and political support is needed to promote improved cause of death surveillance and newborn and infant health care in China's western region.

Measuring causes of adult mortality in rural northern Malawi over a decade of change

BACKGROUND

Verbal autopsy could be more widely used if interpretation by computer algorithm could be relied on. We assessed how InterVA-4 results compared with clinician review in diagnosing HIV/AIDS-related deaths over the period of antiretroviral (ART) roll-out.

DESIGN

In the Karonga Prevention Study demographic surveillance site in northern Malawi, all deaths are followed by verbal autopsy using a semi-structured questionnaire. Cause of death is assigned by two clinicians with a third as a tie-breaker. The clinician review diagnosis was compared with the InterVA diagnosis using the same questionnaire data, including all adult deaths from late 2002 to 2012. For both methods data on HIV status were used. ART was first available in the district from 2005, and within the demographic surveillance area from 2006.

RESULTS

There were 1,637 adult deaths, with verbal autopsy data for 1,615. Adult mortality and the proportion of deaths attributable to HIV/AIDS fell dramatically following ART introduction, but for each year the proportion attributed to HIV/AIDS by InterVA was lower than that attributed by clinician review. This was partly explained by the handling of TB cases. Using clinician review as the best available 'gold standard', for those aged 15-59, the sensitivity of InterVA for HIV/AIDS deaths was 59% and specificity 88%. Grouping HIV/AIDS/TB sensitivity was 78% and specificity 83%. Sensitivity was lower after widespread ART use.

CONCLUSIONS

InterVA underestimates the proportion of deaths due to HIV/AIDS. Accepting that it is unrealistic to try and differentiate TB and AIDS deaths would improve the estimates. Caution is needed in interpreting trends in causes of death as ART use may affect the performance of the algorithm.

Usefulness of the Population Health Metrics Research Consortium gold standard verbal autopsy data for general verbal autopsy methods

BACKGROUND

Verbal Autopsy (VA) is widely viewed as the only immediate strategy for registering cause of death in much of Africa and Asia, where routine physician certification of deaths is not widely practiced. VA involves a lay interview with family or friends after a death, to record essential details of the circumstances. These data can then be processed automatically to arrive at standardized cause of death information.

METHODS

The Population Health Metrics Research Consortium (PHMRC) undertook a study at six tertiary hospitals in low- and middle-income countries which documented over 12,000 deaths clinically and subsequently undertook VA interviews. This dataset, now in the public domain, was compared with the WHO 2012 VA standard and the InterVA-4 interpretative model.

RESULTS

The PHMRC data covered 70% of the WHO 2012 VA input indicators, and categorized cause of death according to PHMRC definitions. After eliminating some problematic or incomplete records, 11,984 VAs were compared. Some of the PHMRC cause definitions, such as 'preterm delivery', differed substantially from the International Classification of Diseases, version 10 equivalent. There were some appreciable inconsistencies between the hospital and VA data, including 20% of the hospital maternal deaths being described as non-pregnant in the VA data. A high proportion of VA cases (66%) reported respiratory symptoms, but only 18% of assigned hospital causes were respiratory-related. Despite these issues, the concordance correlation coefficient between hospital and InterVA-4 cause of death categories was 0.61.

CONCLUSIONS

The PHMRC dataset is a valuable reference source for VA methods, but has to be interpreted with care. Inherently inconsistent cases should not be included when using these data to build other VA models. Conversely, models built from these data should be independently evaluated. It is important to distinguish between the internal and external validity of VA models. The effects of using tertiary hospital data, rather than the more usual application of VA to all-community deaths, are hard to evaluate. However, it would still be of value for VA method development to have further studies of population-based post-mortem examinations.

Comparison of physician-certified verbal autopsy with computer-coded verbal autopsy for cause of death assignment in hospitalized patients in low- and middle-income countries: systematic review

BACKGROUND

Computer-coded verbal autopsy (CCVA) methods to assign causes of death (CODs) for medically unattended deaths have been proposed as an alternative to physician-certified verbal autopsy (PCVA). We conducted a systematic review of 19 published comparison studies (from 684 evaluated), most of which used hospital-based deaths as the reference standard. We assessed the performance of PCVA and five CCVA methods: Random Forest, Tariff, InterVA, King-Lu, and Simplified Symptom Pattern.

METHODS

The reviewed studies assessed methods' performance through various metrics: sensitivity, specificity, and chance-corrected concordance for coding individual deaths, and cause-specific mortality fraction (CSMF) error and CSMF accuracy at the population level. These results were summarized into means, medians, and ranges.

RESULTS

The 19 studies ranged from 200 to 50,000 deaths per study (total over 116,000 deaths). Sensitivity of PCVA versus hospital-assigned COD varied widely by cause, but showed consistently high specificity. PCVA and CCVA methods had an overall chance-corrected concordance of about 50% or lower, across all ages and CODs. At the population level, the relative CSMF error between PCVA and hospital-based deaths indicated good performance for most CODs. Random Forest had the best CSMF accuracy performance, followed closely by PCVA and the other CCVA methods, but with lower values for InterVA-3.

CONCLUSIONS

There is no single best-performing coding method for verbal autopsies across various studies and metrics. There is little current justification for CCVA to replace PCVA, particularly as physician diagnosis remains the worldwide standard for clinical diagnosis on live patients. Further assessments and large accessible datasets on which to train and test combinations of methods are required, particularly for rural deaths without medical attention.

Using verbal autopsy to measure causes of death: the comparative performance of existing methods

BACKGROUND

Monitoring progress with disease and injury reduction in many populations will require widespread use of verbal autopsy (VA). Multiple methods have been developed for assigning cause of death from a VA but their application is restricted by uncertainty about their reliability.

METHODS

We investigated the validity of five automated VA methods for assigning cause of death: InterVA-4, Random Forest (RF), Simplified Symptom Pattern (SSP), Tariff method (Tariff), and King-Lu (KL), in addition to physician review of VA forms (PCVA), based on 12,535 cases from diverse populations for which the true cause of death had been reliably established. For adults, children, neonates and stillbirths, performance was assessed separately for individuals using sensitivity, specificity, Kappa, and chance-corrected concordance (CCC) and for populations using cause specific mortality fraction (CSMF) accuracy, with and without additional diagnostic information from prior contact with health services. A total of 500 train-test splits were used to ensure that results are robust to variation in the underlying cause of death distribution.

RESULTS

Three automated diagnostic methods, Tariff, SSP, and RF, but not InterVA-4, performed better than physician review in all age groups, study sites, and for the majority of causes of death studied. For adults, CSMF accuracy ranged from 0.764 to 0.770, compared with 0.680 for PCVA and 0.625 for InterVA; CCC varied from 49.2% to 54.1%, compared with 42.2% for PCVA, and 23.8% for InterVA. For children, CSMF accuracy was 0.783 for Tariff, 0.678 for PCVA, and 0.520 for InterVA; CCC was 52.5% for Tariff, 44.5% for PCVA, and 30.3% for InterVA. For neonates, CSMF accuracy was 0.817 for Tariff, 0.719 for PCVA, and 0.629 for InterVA; CCC varied from 47.3% to 50.3% for the three automated methods, 29.3% for PCVA, and 19.4% for InterVA. The method with the highest sensitivity for a specific cause varied by cause.

CONCLUSIONS

Physician review of verbal autopsy questionnaires is less accurate than automated methods in determining both individual and population causes of death. Overall, Tariff performs as well or better than other methods and should be widely applied in routine mortality surveillance systems with poor cause of death certification practices.

Cultural imperatives and the ethics of verbal autopsies in rural Ghana

Background

Due to a paucity of statistics from vital registration systems in developing countries, the verbal autopsy (VA) approach has been used to obtain cause-specific mortality data by interviewing lay respondents on the signs and symptoms experienced by the deceased prior to death. In societies where the culture of mourning is adhered to, the use of VA could clash with traditional norms, thus warranting ethical consideration by researchers.

Objective

The study was designed to explore the ethics and cultural context of collecting VA information through a demographic and health surveillance system in the Kassena-Nankana District (KND) of Ghana.

Study Design

Data were collected through qualitative in-depth interviews (IDIs) with four field staff involved in the routine conduct of VAs, four physicians who code VAs, 20 selected respondents to the VA tool, and eight opinion leaders in the KND. The interviews were supplemented with observation by the researchers and with the field notes of field workers. Interviews were audio-recorded, and local language versions transcribed into English. Thematic analysis was performed using QSR NVivo 8 software.

Results

The data indicate that cultural sensitivities in VA procedures at both the individual and family levels need greater consideration not only for ethical reasons but also to ensure the quality of the data. Discussions of some deaths are culturally prohibited and therefore lead to refusal of interviews. Families were also concerned about the confidentiality of information because of the potential of blame for the death. VA teams do not necessarily engage in culturally appropriate bereavement practices such as the presentation of tokens. The desire by families for feedback on the cause of death, which is currently not provided by researchers, was frequently expressed. Finally, no standard exists on the culturally acceptable time interval between death and VA interviews.

Conclusion

Ethical issues need to be given greater consideration in the collection of cause of death data, and this can be achieved through the establishment of processes that allow active engagement with communities, authorities of civil registrations, and Institutional Review Boards to take greater account of local contexts.

Revising the WHO verbal autopsy instrument to facilitate routine cause-of-death monitoring

Objective

Verbal autopsy (VA) is a systematic approach for determining causes of death (CoD) in populations without routine medical certification. It has mainly been used in research contexts and involved relatively lengthy interviews. Our objective here is to describe the process used to shorten, simplify, and standardise the VA process to make it feasible for application on a larger scale such as in routine civil registration and vital statistics (CRVS) systems.

Methods

A literature review of existing VA instruments was undertaken. The World Health Organization (WHO) then facilitated an international consultation process to review experiences with existing VA instruments, including those from WHO, the Demographic Evaluation of Populations and their Health in Developing Countries (INDEPTH) Network, InterVA, and the Population Health Metrics Research Consortium (PHMRC). In an expert meeting, consideration was given to formulating a workable VA CoD list [with mapping to the International Classification of Diseases and Related Health Problems, Tenth Revision (ICD-10) CoD] and to the viability and utility of existing VA interview questions, with a view to undertaking systematic simplification.

Findings

A revised VA CoD list was compiled enabling mapping of all ICD-10 CoD onto 62 VA cause categories, chosen on the grounds of public health significance as well as potential for ascertainment from VA. A set of 221 indicators for inclusion in the revised VA instrument was developed on the basis of accumulated experience, with appropriate skip patterns for various population sub-groups. The duration of a VA interview was reduced by about 40% with this new approach.

Conclusions

The revised VA instrument resulting from this consultation process is presented here as a means of making it available for widespread use and evaluation. It is envisaged that this will be used in conjunction with automated models for assigning CoD from VA data, rather than involving physicians.

Validating the InterVA model to estimate the burden of mortality from verbal autopsy data: a population-based cross-sectional study

Background

In countries with incomplete or no vital registration systems, verbal autopsy data are often reviewed by physicians in order to assign the probable cause of death. But in addition to being time and energy consuming, the method is liable to produce inconsistent results. The aim of this study is to validate the InterVA model for estimating the burden of mortality from verbal autopsy data by using physician review as a reference standard.

Methods and Findings

A population-based cross-sectional study was conducted from March to April, 2012. All adults aged ≥14 years and died between 01 January, 2010 and 15 February, 2012 were included in the study. The verbal autopsy interviews were reviewed by the InterVA model and physicians to estimate cause-specific mortality fractions. Cohen’s kappa statistic, sensitivity, specificity, positive predictive value, and negative predictive value were applied to compare the agreement between the InterVA model and the physician review. A total of 408 adult deaths were studied. There was a general similarity and just slight differences between the InterVA model and the physicians in assigning cause-specific mortality. Both approaches showed an overall agreement in 298 (73%) cases [kappa = 0.49, 95% CI: 0.37-0.60]. The observed sensitivities and specificities across causes of death categories varied from 13.3% to 81.9% and 77.7% to 99.5%, respectively.

Conclusions

In understanding the burden of disease and setting health intervention priorities in areas that lack reliable vital registration systems, an accurate analysis of verbal autopsies is essential. Therefore, users should be aware of the suboptimal performance of the InterVA model. Similar validation studies need to be undertaken considering the limitation of the physician review as gold standard since physicians may misinterpret some of the verbal autopsy data and finally reach a wrong conclusion of the cause of death.

Strengthening standardised interpretation of verbal autopsy data: the new InterVA-4 tool

Background

Verbal autopsy (VA) is the only available approach for determining the cause of many deaths, where routine certification is not in place. Therefore, it is important to use standards and methods for VA that maximise efficiency, consistency and comparability. The World Health Organization (WHO) has led the development of the 2012 WHO VA instrument as a new standard, intended both as a research tool and for routine registration of deaths.

Objective

A new public-domain probabilistic model for interpreting VA data, InterVA-4, is described, which builds on previous versions and is aligned with the 2012 WHO VA instrument.

Design

The new model has been designed to use the VA input indicators defined in the 2012 WHO VA instrument and to deliver causes of death compatible with the International Classification of Diseases version 10 (ICD-10) categorised into 62 groups as defined in the 2012 WHO VA instrument. In addition, known shortcomings of previous InterVA models have been addressed in this revision, as well as integrating other work on maternal and perinatal deaths.

Results

The InterVA-4 model is presented here to facilitate its widespread use and to enable further field evaluation to take place. Results from a demonstration dataset from Agincourt, South Africa, show continuity of interpretation between InterVA-3 and InterVA-4, as well as differences reflecting specific issues addressed in the design and development of InterVA-4.

Conclusions

InterVA-4 is made freely available as a new standard model for interpreting VA data into causes of death. It can be used for determining cause of death both in research settings and for routine registration. Further validation opportunities will be explored. These developments in cause of death registration are likely to substantially increase the global coverage of cause-specific mortality data.

Exploring the role narrative free-text plays in discrepancies between physician coding and the InterVA regarding determination of malaria as cause of death, in a malaria holo-endemic region

BACKGROUND

In countries where tracking mortality and clinical cause of death are not routinely undertaken, gathering verbal autopsies (VA) is the principal method of estimating cause of death. The most common method for determining probable cause of death from the VA interview is Physician-Certified Verbal Autopsy (PCVA). A recent alternative method to interpret Verbal Autopsy (InterVA) is a computer model using a Bayesian approach to derive posterior probabilities for causes of death, given an a priori distribution at population level and a set of interview-based indicators. The model uses the same input information as PCVA, with the exception of narrative text information, which physicians can consult but which were not inputted into the model. Comparing the results of physician coding with the model, large differences could be due to difficulties in diagnosing malaria, especially in holo-endemic regions. Thus, the aim of the study was to explore whether physicians' access to electronically unavailable narrative text helps to explain the large discrepancy in malaria cause-specific mortality fractions (CSMFs) in physician coding versus the model.

METHODS

Free-texts of electronically available records (N = 5,649) were summarised and incorporated into the InterVA version 3 (InterVA-3) for three sub-groups: (i) a 10%-representative subsample (N = 493) (ii) records diagnosed as malaria by physicians and not by the model (N = 1035), and (iii) records diagnosed by the model as malaria, but not by physicians (N = 332). CSMF results before and after free-text incorporation were compared.

RESULTS

There were changes of between 5.5-10.2% between models before and after free-text incorporation. No impact on malaria CSMFs was seen in the representative sub-sample, but the proportion of malaria as cause of death increased in the physician sub-sample (2.7%) and saw a large decrease in the InterVA subsample (9.9%). Information on 13/106 indicators appeared at least once in the free-texts that had not been matched to any item in the structured, electronically available portion of the Nouna questionnaire.

DISCUSSION

Free-texts are helpful in gathering information not adequately captured in VA questionnaires, though access to free-text does not explain differences in physician and model determination of malaria as cause of death.

Direct estimation of cause-specific mortality fractions from verbal autopsies: multisite validation study using clinical diagnostic gold standards

Background

Verbal autopsy (VA) is used to estimate the causes of death in areas with incomplete vital registration systems. The King and Lu method (KL) for direct estimation of cause-specific mortality fractions (CSMFs) from VA studies is an analysis technique that estimates CSMFs in a population without predicting individual-level cause of death as an intermediate step. In previous studies, KL has shown promise as an alternative to physician-certified verbal autopsy (PCVA). However, it has previously been impossible to validate KL with a large dataset of VAs for which the underlying cause of death is known to meet rigorous clinical diagnostic criteria.

Methods

We applied the KL method to adult, child, and neonatal VA datasets from the Population Health Metrics Research Consortium gold standard verbal autopsy validation study, a multisite sample of 12,542 VAs where gold standard cause of death was established using strict clinical diagnostic criteria. To emulate real-world populations with varying CSMFs, we evaluated the KL estimations for 500 different test datasets of varying cause distribution. We assessed the quality of these estimates in terms of CSMF accuracy as well as linear regression and compared this with the results of PCVA.

Results

KL performance is similar to PCVA in terms of CSMF accuracy, attaining values of 0.669, 0.698, and 0.795 for adult, child, and neonatal age groups, respectively, when health care experience (HCE) items were included. We found that the length of the cause list has a dramatic effect on KL estimation quality, with CSMF accuracy decreasing substantially as the length of the cause list increases. We found that KL is not reliant on HCE the way PCVA is, and without HCE, KL outperforms PCVA for all age groups.

Conclusions

Like all computer methods for VA analysis, KL is faster and cheaper than PCVA. Since it is a direct estimation technique, though, it does not produce individual-level predictions. KL estimates are of similar quality to PCVA and slightly better in most cases. Compared to other recently developed methods, however, KL would only be the preferred technique when the cause list is short and individual-level predictions are not needed.

Simplified Symptom Pattern Method for verbal autopsy analysis: multisite validation study using clinical diagnostic gold standards

Background

Verbal autopsy can be a useful tool for generating cause of death data in data-sparse regions around the world. The Symptom Pattern (SP) Method is one promising approach to analyzing verbal autopsy data, but it has not been tested rigorously with gold standard diagnostic criteria. We propose a simplified version of SP and evaluate its performance using verbal autopsy data with accompanying true cause of death.

Methods

We investigated specific parameters in SP's Bayesian framework that allow for its optimal performance in both assigning individual cause of death and in determining cause-specific mortality fractions. We evaluated these outcomes of the method separately for adult, child, and neonatal verbal autopsies in 500 different population constructs of verbal autopsy data to analyze its ability in various settings.

Results

We determined that a modified, simpler version of Symptom Pattern (termed Simplified Symptom Pattern, or SSP) performs better than the previously-developed approach. Across 500 samples of verbal autopsy testing data, SSP achieves a median cause-specific mortality fraction accuracy of 0.710 for adults, 0.739 for children, and 0.751 for neonates. In individual cause of death assignment in the same testing environment, SSP achieves 45.8% chance-corrected concordance for adults, 51.5% for children, and 32.5% for neonates.

Conclusions

The Simplified Symptom Pattern Method for verbal autopsy can yield reliable and reasonably accurate results for both individual cause of death assignment and for determining cause-specific mortality fractions. The method demonstrates that verbal autopsies coupled with SSP can be a useful tool for analyzing mortality patterns and determining individual cause of death from verbal autopsy data.

Population Health Metrics Research Consortium gold standard verbal autopsy validation study: design, implementation, and development of analysis datasets

BACKGROUND

Verbal autopsy methods are critically important for evaluating the leading causes of death in populations without adequate vital registration systems. With a myriad of analytical and data collection approaches, it is essential to create a high quality validation dataset from different populations to evaluate comparative method performance and make recommendations for future verbal autopsy implementation. This study was undertaken to compile a set of strictly defined gold standard deaths for which verbal autopsies were collected to validate the accuracy of different methods of verbal autopsy cause of death assignment.

METHODS

Data collection was implemented in six sites in four countries: Andhra Pradesh, India; Bohol, Philippines; Dar es Salaam, Tanzania; Mexico City, Mexico; Pemba Island, Tanzania; and Uttar Pradesh, India. The Population Health Metrics Research Consortium (PHMRC) developed stringent diagnostic criteria including laboratory, pathology, and medical imaging findings to identify gold standard deaths in health facilities as well as an enhanced verbal autopsy instrument based on World Health Organization (WHO) standards. A cause list was constructed based on the WHO Global Burden of Disease estimates of the leading causes of death, potential to identify unique signs and symptoms, and the likely existence of sufficient medical technology to ascertain gold standard cases. Blinded verbal autopsies were collected on all gold standard deaths.

RESULTS

Over 12,000 verbal autopsies on deaths with gold standard diagnoses were collected (7,836 adults, 2,075 children, 1,629 neonates, and 1,002 stillbirths). Difficulties in finding sufficient cases to meet gold standard criteria as well as problems with misclassification for certain causes meant that the target list of causes for analysis was reduced to 34 for adults, 21 for children, and 10 for neonates, excluding stillbirths. To ensure strict independence for the validation of methods and assessment of comparative performance, 500 test-train datasets were created from the universe of cases, covering a range of cause-specific compositions.

CONCLUSIONS

This unique, robust validation dataset will allow scholars to evaluate the performance of different verbal autopsy analytic methods as well as instrument design. This dataset can be used to inform the implementation of verbal autopsies to more reliably ascertain cause of death in national health information systems.

Robust metrics for assessing the performance of different verbal autopsy cause assignment methods in validation studies

Background

Verbal autopsy (VA) is an important method for obtaining cause of death information in settings without vital registration and medical certification of causes of death. An array of methods, including physician review and computer-automated methods, have been proposed and used. Choosing the best method for VA requires the appropriate metrics for assessing performance. Currently used metrics such as sensitivity, specificity, and cause-specific mortality fraction (CSMF) errors do not provide a robust basis for comparison.

Methods

We use simple simulations of populations with three causes of death to demonstrate that most metrics used in VA validation studies are extremely sensitive to the CSMF composition of the test dataset. Simulations also demonstrate that an inferior method can appear to have better performance than an alternative due strictly to the CSMF composition of the test set.

Results

VA methods need to be evaluated across a set of test datasets with widely varying CSMF compositions. We propose two metrics for assessing the performance of a proposed VA method. For assessing how well a method does at individual cause of death assignment, we recommend the average chance-corrected concordance across causes. This metric is insensitive to the CSMF composition of the test sets and corrects for the degree to which a method will get the cause correct due strictly to chance. For the evaluation of CSMF estimation, we propose CSMF accuracy. CSMF accuracy is defined as one minus the sum of all absolute CSMF errors across causes divided by the maximum total error. It is scaled from zero to one and can generalize a method's CSMF estimation capability regardless of the number of causes. Performance of a VA method for CSMF estimation by cause can be assessed by examining the relationship across test datasets between the estimated CSMF and the true CSMF.

Conclusions

With an increasing range of VA methods available, it will be critical to objectively assess their performance in assigning cause of death. Chance-corrected concordance and CSMF accuracy assessed across a large number of test datasets with widely varying CSMF composition provide a robust strategy for this assessment.

Performance of the Tariff Method: validation of a simple additive algorithm for analysis of verbal autopsies

BACKGROUND

Verbal autopsies provide valuable information for studying mortality patterns in populations that lack reliable vital registration data. Methods for transforming verbal autopsy results into meaningful information for health workers and policymakers, however, are often costly or complicated to use. We present a simple additive algorithm, the Tariff Method (termed Tariff), which can be used for assigning individual cause of death and for determining cause-specific mortality fractions (CSMFs) from verbal autopsy data.

METHODS

Tariff calculates a score, or "tariff," for each cause, for each sign/symptom, across a pool of validated verbal autopsy data. The tariffs are summed for a given response pattern in a verbal autopsy, and this sum (score) provides the basis for predicting the cause of death in a dataset. We implemented this algorithm and evaluated the method's predictive ability, both in terms of chance-corrected concordance at the individual cause assignment level and in terms of CSMF accuracy at the population level. The analysis was conducted separately for adult, child, and neonatal verbal autopsies across 500 pairs of train-test validation verbal autopsy data.

RESULTS

Tariff is capable of outperforming physician-certified verbal autopsy in most cases. In terms of chance-corrected concordance, the method achieves 44.5% in adults, 39% in children, and 23.9% in neonates. CSMF accuracy was 0.745 in adults, 0.709 in children, and 0.679 in neonates.

CONCLUSIONS

Verbal autopsies can be an efficient means of obtaining cause of death data, and Tariff provides an intuitive, reliable method for generating individual cause assignment and CSMFs. The method is transparent and flexible and can be readily implemented by users without training in statistics or computer science.