The WHO 2016 verbal autopsy instrument: An international standard suitable for automated analysis by InterVA, InSilicoVA, and Tariff 2.0

Uncovering the causes and socio-demographic constructs of stillbirths and neonatal deaths in an urban slum of Karachi

INTRODUCTION

Neonatal deaths and stillbirths are significant public health concerns in Pakistan, with an estimated stillbirth rate of 43 per 1,000 births and a neonatal mortality rate of 46 deaths per 1,000 live births. Limited access to obstetric care, poor health seeking behaviors and lack of quality healthcare are the leading root causes for stillbirths and neonatal deaths. Rehri Goth, a coastal slum in Karachi, faces even greater challenges due to extreme poverty, and inadequate infrastructure. This study aims to investigate the causes and pathways leading to stillbirths and neonatal deaths in Rehri Goth to develop effective maternal and child health interventions.

METHODS

A mixed-method cohort study was nested with the implementation of large maternal, neonatal and child health program, captured all stillbirths and neonatal death during the period of May 2014 till June 2018. The Verbal and Social Autopsy (VASA) tool (WHO 2016) was used to collect primary data from all death events to determine the causes as well as the pathways. Interviews were conducted both retrospectively and prospectively with mothers and caregivers. Two trained physicians reviewed the VASA form and the medical records (if available) and coded the cause of death blinded to each other. Descriptive analysis was used to categorize stillbirth and neonatal mortality data into high- and low-mortality clusters, followed by chi-square tests to explore associations between categories, and concluded with a qualitative analysis.

RESULTS

Out of 421 events captured, complete VASA interviews were conducted for 317 cases. The leading causes of antepartum stillbirths were pregnancy-induced hypertension (22.4%) and maternal infections (13.4%), while obstructed labor was the primary cause of intrapartum stillbirths (38.3%). Neonatal deaths were primarily caused by perinatal asphyxia (36.1%) and preterm birth complications (27.8%). The qualitative analysis on a subset of 40 death events showed that health system (62.5%) and community factors (37.5%) contributing to adverse outcomes, such as delayed referrals, poor triage systems, suboptimal quality of care, and delayed care-seeking behaviors.

CONCLUSION

The study provides an opportunity to understand the causes of stillbirths and neonatal deaths in one of the impoverished slums of Karachi. The data segregation by clusters as well as triangulation with qualitative analysis highlight the needs of evidence-based strategies for maternal and child health interventions in disadvantaged communities.

Burden of child mortality from malaria in high endemic areas: Results from the CHAMPS network using minimally invasive tissue sampling

BACKGROUND

Malaria is a leading cause of childhood mortality worldwide. However, accurate estimates of malaria prevalence and causality among patients who die at the country level are lacking due to the limited specificity of diagnostic tools used to attribute etiologies. Accurate estimates are crucial for prioritizing interventions and resources aimed at reducing malaria-related mortality.

METHODS

Seven Child Health and Mortality Prevention Surveillance (CHAMPS) Network sites collected comprehensive data on stillbirths and children <5 years, using minimally invasive tissue sampling (MITS). A DeCoDe (Determination of Cause of Death) panel employed standardized protocols for assigning underlying, intermediate, and immediate causes of death, integrating sociodemographic, clinical, laboratory (including extensive microbiology, histopathology, and malaria testing), and verbal autopsy data. Analyses were conducted to ascertain the strength of evidence for cause of death (CoD), describe factors associated with malaria-related deaths, estimate malaria-specific mortality, and assess the proportion of preventable deaths.

FINDINGS

Between December 3, 2016, and December 31, 2022, 2673 deaths underwent MITS and had a CoD attributed from four CHAMPS sites with at least 1 malaria-attributed death. No malaria-attributable deaths were documented among 891 stillbirths or 924 neonatal deaths, therefore this analysis concentrates on the remaining 858 deaths among children aged 1-59 months. Malaria was in the causal chain for 42.9% (126/294) of deaths from Sierra Leone, 31.4% (96/306) in Kenya, 18.2% (36/198) in Mozambique, 6.7% (4/60) in Mali, and 0.3% (1/292) in South Africa. Compared to non-malaria related deaths, malaria-related deaths skewed towards older infants and children (p < 0.001), with 71.0% among ages 12-59 months. Malaria was the sole infecting pathogen in 184 (70.2%) of malaria-attributed deaths, whereas bacterial and viral co-infections were identified in the causal pathway in 24·0% and 12.2% of cases, respectively. Malnutrition was found at a similar level in the causal pathway of both malaria (26.7%) and non-malaria (30.7%, p = 0.256) deaths. Less than two-thirds (164/262; 62.6%) of malaria deaths had received antimalarials prior to death. Nearly all (98·9%) malaria-related deaths were deemed preventable.

INTERPRETATION

Malaria remains a significant cause of childhood mortality in the CHAMPS malaria-endemic sites. The high bacterial co-infection prevalence among malaria deaths underscores the potential benefits of antibiotics for severe malaria patients. Compared to non-malaria deaths, many of malaria-attributed deaths are preventable through accessible malaria control measures.

Causes of maternal deaths in Sierra Leone from 2016 to 2019: analysis of districts' maternal death surveillance and response data

INTRODUCTION

Sierra Leone is among the top countries with the highest maternal mortality rates. Although progress has been made in reducing maternal mortality, challenges remain, including limited access to skilled care and regional disparities in accessing quality care. This paper presents the first comprehensive analysis of the burden of different causes of maternal deaths reported in the Maternal Death Surveillance and Response (MDSR) system at the district level from 2016 to 2019.

METHODS

The MDSR data are accessed from the Ministry of Health and Sanitation, and the secondary data analysis was done to determine the causes of maternal death in Sierra Leone. The proportions of each leading cause of maternal deaths were estimated by districts. A subgroup analysis of the selected causes of death was also performed.

RESULTS

Overall, obstetric haemorrhage was the leading cause of maternal death (39.4%), followed by hypertensive disorders (15.8%) and pregnancy-related infections (10.1%). Within obstetric haemorrhage, postpartum haemorrhage was the leading cause in each district. The burden of death due to obstetric haemorrhage slightly increased over the study period, while hypertensive disorders showed a slightly decreasing trend. Disparities were found among districts for all causes of maternal death, but no clear geographical pattern emerged. Non-obstetric complications were reported in 11.5% of cases.

CONCLUSION

The MDSR database provides an opportunity for shared learning and can be used to improve the quality of maternal health services. To improve the accuracy and availability of data, under-reporting must be addressed, and frontline community staff must be trained to accurately capture and report death events.

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

BACKGROUND

The South African national cause of death validation (NCODV 2017/18) project collected a national sample of verbal autopsies (VA) with cause of death (COD) assignment by physician-coded VA (PCVA) and computer-coded VA (CCVA).

OBJECTIVE

The performance of three CCVA algorithms (InterVA-5, InSilicoVA and Tariff 2.0) in assigning a COD was compared with PCVA (reference standard).

METHODS

Seven performance metrics assessed individual and population level agreement of COD assignment by age, sex and place of death subgroups. Positive predictive value (PPV), sensitivity, overall agreement, kappa, and chance corrected concordance (CCC) assessed individual level agreement. Cause-specific mortality fraction (CSMF) accuracy and Spearman's rank correlation assessed population level agreement.

RESULTS

A total of 5386 VA records were analysed. PCVA and CCVAs all identified HIV/AIDS as the leading COD. CCVA PPV and sensitivity, based on confidence intervals, were comparable except for HIV/AIDS, TB, maternal, diabetes mellitus, other cancers, and some injuries. CCVAs performed well for identifying perinatal deaths, road traffic accidents, suicide and homicide but poorly for pneumonia, other infectious diseases and renal failure. Overall agreement between CCVAs and PCVA for the top single cause (48.2-51.6) indicated comparable weak agreement between methods. Overall agreement, for the top three causes showed moderate agreement for InterVA (70.9) and InSilicoVA (73.8). Agreement based on kappa (-0.05-0.49)and CCC (0.06-0.43) was weak to none for all algorithms and groups. CCVAs had moderate to strong agreement for CSMF accuracy, with InterVA-5 highest for neonates (0.90), Tariff 2.0 highest for adults (0.89) and males (0.84), and InSilicoVA highest for females (0.88), elders (0.83) and out-of-facility deaths (0.85). Rank correlation indicated moderate agreement for adults (0.75-0.79).

CONCLUSIONS

Whilst CCVAs identified HIV/AIDS as the leading COD, consistent with PCVA, there is scope for improving the algorithms for use in South Africa.

Validation of CHERG'S Verbal Autopsy-Social Autopsy (VASA) tool for ascertaining determinants and causes of under-five child mortality in Pakistan

The majority (40%) of the world's under-five mortality burden is concentrated in nations like Nigeria (16.5%), India (16%), Pakistan (8%), and the Democratic Republic of the Congo (6%), where an undetermined number of under-five deaths go unrecorded. In low-resource settings throughout the world, the Verbal Autopsy-Social Autopsy (VASA) technique may assist assess under-five mortality estimates, assigning medical and social causes of death, and identifying relevant determinants. Uncertainty regarding missing data in high-burden nations like Pakistan necessitates a valid and reliable VASA instrument. This is the first study to validate Child Health Epidemiology Reference Group-CHERG's VASA tool globally. In Pakistan, data from such a valid and reliable tool is vital for policy. This paper reports on the VASA tool in Karachi, Pakistan. Validity and reliability of the CHERG VASA tool were tested using face, content, discriminant validation, and reliability tests on one hundred randomly selected mothers who had recently experienced an under-five child death event. Data were computed on SPSS (version-21) and R software. Testing revealed high Item-content Validity Index (I-CVI) (>81.43%); high Cronbach's Alpha (0.843); the accuracy of between 75-100% of the discriminants classifying births to live and stillbirths; and I-CVI (>82.07% and 88.98% respectively) with high accuracy (92% and 97% respectively) for assigning biological and social causes of child deaths, respectively. The CHERG VASA questionnaire was found relevant to the conceptual framework and valid in Pakistan. This valid tool can assign accurate medical and non-medical causes of child mortality cases occurring in Pakistan.

Cohort profile: the Pregnancy Risk Infant Surveillance and Measurement Alliance (PRISMA) - Pakistan

PURPOSE

Pakistan has disproportionately high maternal and neonatal morbidity and mortality. There is a lack of detailed, population-representative data to provide evidence for risk factors, morbidities and mortality among pregnant women and their newborns. The Pregnancy Risk, Infant Surveillance and Measurement Alliance (PRISMA) is a multicountry open cohort that aims to collect high-dimensional, standardised data across five South Asian and African countries for estimating risk and developing innovative strategies to optimise pregnancy outcomes for mothers and their newborns. This study presents the baseline maternal and neonatal characteristics of the Pakistan site occurring prior to the launch of a multisite, harmonised protocol.

PARTICIPANTS

PRISMA Pakistan study is being conducted at two periurban field sites in Karachi, Pakistan. These sites have primary healthcare clinics where pregnant women and their newborns are followed during the antenatal, intrapartum and postnatal periods up to 1 year after delivery. All encounters are captured electronically through a custom-built Android application. A total of 3731 pregnant women with a mean age of 26.6±5.8 years at the time of pregnancy with neonatal outcomes between January 2021 and August 2022 serve as a baseline for the PRISMA Pakistan study.

FINDINGS TO DATE

In this cohort, live births accounted for the majority of pregnancy outcomes (92%, n=3478), followed by miscarriages/abortions (5.5%, n=205) and stillbirths (2.6%, n=98). Twenty-two per cent of women (n=786) delivered at home. One out of every four neonates was low birth weight (<2500 g), and one out of every five was preterm (gestational age <37 weeks). The maternal mortality rate was 172/100 000 pregnancies, the neonatal mortality rate was 52/1000 live births and the stillbirth rate was 27/1000 births. The three most common causes of neonatal deaths obtained through verbal autopsy were perinatal asphyxia (39.6%), preterm births (19.8%) and infections (12.6%).

FUTURE PLANS

The PRISMA cohort will provide data-driven insights to prioritise and design interventions to improve maternal and neonatal outcomes in low-resource regions.

TRIAL REGISTRATION NUMBER

NCT05904145.

A prospective observational study of nurses performing minimally invasive tissue sampling of brain, liver, and lung tissues among deceased neonates and stillbirths in Ethiopia

Background

With a neonatal mortality rate of 33 per 1,000 live births in 2019, Ethiopia is striving to attain the Sustainable Development Goal target of 12 deaths per 1,000 live births by 2030. A better understanding of the major causes of neonatal mortality is needed to effectively design and implement interventions to achieve this goal. Minimally Invasive Tissue Sampling (MITS), an alternative to conventional autopsy, requires fewer resources and through task-shifting of sample collection from pathologists to nurses, has the potential to support the expansion of pathology-based post-mortem examination and improve mortality data. This paper evaluates the accuracy and adequacy of MITS performed by nurses at a tertiary and general hospital and in the home of the deceased.

Methods

Nurses in a tertiary and general hospital in Ethiopia were trained in MITS sample collection on neonatal deaths and stillbirths using standardized protocols. MITS sample collection was performed by both pathologists and nurses in the tertiary hospital and by nurses in the general hospital and home-setting. Agreement in the performance of MITS between pathologists and nurses was calculated for samples collected at the tertiary hospital. Samples collected by nurses in the general hospital and home-setting were evaluated for technical adequacy using preestablished criteria.

Results

One hundred thirty-nine MITS were done: 125 in hospitals and 14 inside homes. There was a perfect or almost perfect agreement between the pathologists and the nurses in the tertiary hospital using Gwet's agreement interpretation criteria. The adequacy of MITS samples collected by nurses in the general hospital was more than 72% when compared to the preset criteria. The adequacy of the MITS sampling yield ranged from 87% to 91% on liveborn neonatal deaths and 76% for the liver, right and left lungs and 55% for brain tissues in stillbirths.

Conclusions

This study demonstrated that task-shifting MITS sample collection to nurses can be achieved with comparable accuracy and adequacy as pathologists. Our study showed that with standardized training and supportive supervision MITS sample collection can be conducted by nurses in a tertiary, general hospital and, at the home of the deceased. Future studies should validate and expand on this work by evaluating task-shifting of MITS sample collection to nurses within community settings and with larger sample sizes.

Pragmatic solutions to reduce the global burden of stroke: a World Stroke Organization-Lancet Neurology Commission

Stroke is the second leading cause of death worldwide. The burden of disability after a stroke is also large, and is increasing at a faster pace in low-income and middle-income countries than in high-income countries. Alarmingly, the incidence of stroke is increasing in young and middle-aged people (ie, age <55 years) globally. Should these trends continue, Sustainable Development Goal 3.4 (reducing the burden of stroke as part of the general target to reduce the burden of non-communicable diseases by a third by 2030) will not be met.

In this Commission, we forecast the burden of stroke from 2020 to 2050. We project that stroke mortality will increase by 50%—from 6·6 million (95% uncertainty interval [UI] 6·0 million–7·1 million) in 2020, to 9·7 million (8·0 million–11·6 million) in 2050—with disability-adjusted life-years (DALYs) growing over the same period from 144·8 million (133·9 million–156·9 million) in 2020, to 189·3 million (161·8 million–224·9 million) in 2050. These projections prompted us to do a situational analysis across the four pillars of the stroke quadrangle: surveillance, prevention, acute care, and rehabilitation. We have also identified the barriers to, and facilitators for, the achievement of these four pillars. Disability-adjusted life-years (DALYs) The sum of the years of life lost as a result of premature mortality from a disease and the years lived with a disability associated with prevalent cases of the disease in a population. One DALY represents the loss of the equivalent of one year of full health

On the basis of our assessment, we have identified and prioritised several recommendations. For each of the four pillars (surveillance, prevention, acute care, and rehabilitation), we propose pragmatic solutions for the implementation of evidence-based interventions to reduce the global burden of stroke. The estimated direct (ie, treatment and rehabilitation) and indirect (considering productivity loss) costs of stroke globally are in excess of US$891 billion annually. The pragmatic solutions we put forwards for urgent implementation should help to mitigate these losses, reduce the global burden of stroke, and contribute to achievement of Sustainable Development Goal 3.4, the WHO Intersectoral Global Action Plan on epilepsy and other neurological disorders (2022–2031), and the WHO Global Action Plan for prevention and control of non-communicable diseases.

Reduction of the global burden of stroke, particularly in low-income and middle-income countries, by implementing primary and secondary stroke prevention strategies and evidence-based acute care and rehabilitation services is urgently required. Measures to facilitate this goal include: the establishment of a framework to monitor and assess the burden of stroke (and its risk factors) and stroke services at a national level; the implementation of integrated population-level and individual-level prevention strategies for people at any increased risk of cerebrovascular disease, with emphasis on early detection and control of hypertension; planning and delivery of acute stroke care services, including the establishment of stroke units with access to reperfusion therapies for ischaemic stroke and workforce training and capacity building (and monitoring of quality indicators for these services nationally, regionally, and globally); the promotion of interdisciplinary stroke care services, training for caregivers, and capacity building for community health workers and other health-care providers working in stroke rehabilitation; and the creation of a stroke advocacy and implementation ecosystem that includes all relevant communities, organisations, and stakeholders.

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Can machine learning methods be used for identification of at-risk neonates in low-resource settings? A prospective cohort study

INTRODUCTION

Timely identification of at-risk neonates (ARNs) in the community is essential to reduce mortality in low-resource settings. Tools such as American Academy of Pediatrics pulse oximetry (POx) and WHO Young Infants Clinical Signs (WHOS) have high specificity but low sensitivity to identify ARNs. Our aim was assessing the value of POx and WHOS independently, in combination and with machine learning (ML) from clinical features, to detect ARNs in a low/middle-income country.

METHODS

This prospective cohort study was conducted in a periurban community in Pakistan. Eligible live births were screened using WHOS and POx along with clinical information regarding pregnancy and delivery. The enrolled neonates were followed for 4 weeks of life to assess the vital status. The predictive value to identify ARNs, of POx, WHOS and an ML model using maternal and neonatal clinical features, was assessed.

RESULTS

Of 1336 neonates, 68 (5%) had adverse outcomes, that is, sepsis (n=40, 59%), critical congenital heart disease (n=2, 3%), severe persistent pulmonary hypertension (n=1), hospitalisation (n=8, 12%) and death (n=17, 25%) assessed at 4 weeks of life. Specificity of POx and WHOS to independently identify ARNs was 99%, with sensitivity of 19% and 63%,respectively. Combining both improved sensitivity to 70%, keeping specificity at 98%. An ML model using clinical variables had 44% specificity and 76% sensitivity. A staged assessment, where WHOS, POx and ML are sequentially used for triage, increased sensitivity to 85%, keeping specificity 75%. Using ML (when WHOS and POx negative) for community follow-up detected the majority of ARNs.

CONCLUSION

Classic screening, combined with ML, can help maximise identifying ARNs and could be embedded in low-resource clinical settings, thereby improving outcome. Sequential use of classic assessment and clinical ML identifies the most ARNs in the community, still optimising follow-up clinical care.

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

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

Verbal autopsy to assess causes of mortality among the economically productive age group in the tribal region of Melghat, central India

Background & Objectives

Verbal autopsy (VA) is the systematic and retrospective inquiry (from relatives) about the symptoms of an illness prior to death. In tribal India, 67-75 per cent of deaths occur at home with an unknown cause of death (CoD). Hence, the aim of this study was to determine the CoD in the 16-60 yr age group utilizing VA.

Methods

A prospective, community based longitudinal study was conducted in 32 tribal villages in the Melghat region of Maharashtra, between 2004 and 2020. Number of deaths and VAs in 16-60 yr age group were collected by village health workers (VHWs) and supervisors, verified by five different persons (internal-external) and cross-checked by three VA interpretation trained physicians. A modified version of WHO VA was used. Cause-specific mortality fractions were calculated.

Results

Of the 1011 deaths recorded, mortality in males was significantly higher than females (P<0.001). A total of 763 VAs were conducted which revealed that tuberculosis was the leading CoD, followed by jaundice, heart diseases, diarrhoea, central nervous system infections and suicide. Suicides were significantly more common among males than in females (P=0.046). Significantly, more deaths occurred during the monsoon (P=0.002), especially diarrhoeal deaths (P=0.024).

Interpretation & conclusions

The findings of this study suggest that, in Indian tribal areas, infectious diseases are the leading causes of morbidity and one of the major causes of deaths in economically productive age group. Intensified VHW-mediated interventions are required to reduce the premature deaths.

Evaluation of methods for assigning causes of death from verbal autopsies in India

Background

Physician-coded verbal autopsy (PCVA) is the most widely used method to determine causes of death (COD) in countries where medical certification of death is low. Computer-coded verbal autopsy (CCVA), an alternative method to PCVA for assigning the COD is considered to be efficient and cost-effective. However, the performance of CCVA as compared to PCVA is yet to be established in the Indian context.

Methods

We evaluated the performance of PCVA and three CCVA methods i.e., InterVA 5, InSilico, and Tariff 2.0 on verbal autopsies done using the WHO 2016 VA tool on 2,120 reference standard cases developed from five tertiary care hospitals of Delhi. PCVA methodology involved dual independent review with adjudication, where required. Metrics to assess performance were Cause Specific Mortality Fraction (CSMF), sensitivity, positive predictive value (PPV), CSMF Accuracy, and Kappa statistic.

Results

In terms of the measures of the overall performance of COD assignment methods, for CSMF Accuracy, the PCVA method achieved the highest score of 0.79, followed by 0.67 for Tariff_2.0, 0.66 for Inter-VA and 0.62 for InSilicoVA. The PCVA method also achieved the highest agreement (57%) and Kappa scores (0.54). The PCVA method showed the highest sensitivity for 15 out of 20 causes of death.

Conclusion

Our study found that the PCVA method had the best performance out of all the four COD assignment methods that were tested in our study sample. In order to improve the performance of CCVA methods, multicentric studies with larger sample sizes need to be conducted using the WHO VA tool.

Implementation research for developing Civil Registration and Vital Statistics (CRVS) Systems: lessons from Indonesia

Civil Registration and Vital Statistics (CRVS) systems are the optimal source for data on births, deaths and causes of death for health policy, programme evaluation and research. In Indonesia, indicators such as life expectancy at birth, childhood and maternal mortality rates and cause-specific death rates need to be routinely monitored for national health policy. However, the CRVS system is not yet producing reliable vital statistics, which creates a challenge for evidence-based health action. In 2019, the Indonesian government released a national strategy for the CRVS system, with targets for improved coverage and data quality by 2024. This article describes findings from a programme of formative and implementation research to guide the application of the national strategy. At first, a detailed CRVS assessment and gap analysis were undertaken using an international framework. The assessment findings were used to develop a revised business process model for reporting deaths and their causes at village, subdistrict and district level. In addition, a field instruction manual was also developed to guide personnel in implementation. Two field sites in Java-Malang District and Kudus Regency were selected for pilot testing the reporting procedures, and relevant site preparation and training were carried out. Data compilations for Malang in 2019 and Kudus in 2020 were analysed to derive mortality indicators. High levels of death reporting completeness (83% to 89%) were reported from both districts, along with plausible cause-specific mortality profiles, although the latter need further validation. The study findings establish the feasibility of implementing revised death reporting procedures at the local level, as well as demonstrate sustainability through institutionalisation and capacity building, and can be used to accelerate further development of the CRVS system in Indonesia.

Validating the InterVA-5 cause of death analytical tool: using mortality data from the Comprehensive Health and Epidemiological Surveillance System in Papua New Guinea

OBJECTIVE

InterVA-5 is a new version of an analytical tool for cause of death (COD) analysis at the population level. This study validates the InterVA-5 against the medical review method, using mortality data in Papua New Guinea (PNG).

DESIGN AND SETTING

This study used mortality data collected from January 2018 to December 2020 in eight surveillance sites of the Comprehensive Health and Epidemiological Surveillance System (CHESS), established by the PNG Institute of Medical Research in six major provinces.

METHODS

The CHESS demographic team conducted verbal autopsy (VA) interviews with close relatives of the deceased, who died in communities within the catchment areas of CHESS, using the WHO 2016 VA instrument. COD of the deceased was assigned by InterVA-5 tool, and independently certified by the medical team. Consistency, difference and agreement between the InterVA-5 model and medical review were assessed. Sensitivity and positive predictive value (PPV) of the InterVA-5 tool were calculated with reference to the medical review method.

RESULTS

Specific COD of 926 deceased people was included in the validation. Agreement between the InterVA-5 tool and medical review was high (kappa test: 0.72; p<0.01). Sensitivity and PPV of the InterVA-5 were 93% and 72% for cardiovascular diseases, 84% and 86% for neoplasms, 65% and 100% for other chronic non-communicable diseases (NCDs), and 78% and 64% for maternal deaths, respectively. For infectious diseases and external CODs, sensitivity and PPV of the InterVA-5 were 94% and 90%, respectively, while the sensitivity and PPV of the medical review method were both 54% for classifying neonatal CODs.

CONCLUSION

The InterVA-5 tool works well in the PNG context to assign specific CODs of infectious diseases, cardiovascular diseases, neoplasms and injuries. Further improvements with respect to chronic NCDs, maternal deaths and neonatal deaths are needed.

Community-Minimal Invasive Tissue Sampling (cMITS) using a modified ambulance for ascertaining the cause of death: A novel approach piloted in a remote inaccessible rural area in India

BACKGROUND

Melghat in India is a hilly, forested, difficult to access, impoverished rural area in northeast part of Maharashtra (Central India) with difficult healthcare access. Melghat has very high Mortality rates, because of grossly inadequate medical facilities. (1) Home deaths contribute to 67% of deaths,(2) which are difficult to track and where cause of death is mostly unknown.

METHODS

A feasibility study was carried out in 93 rural villages and 5 hospitals to assess feasibility of tracking real-time community mortality and to ascertain cause of death in 0-60 months and 16-60 years age group using Minimal Invasive Tissue Sampling (MITS) in purpose-modified ambulance. We used the network of village health workers (VHW)s, to establish real-time community mortality tracking. Upon receipt of reports of home death, we performed MITS within 4 h of death in the vicinity of the village.

RESULTS

We conducted 16 MITS. Nine, in MITS ambulance in community and seven at MAHAN hospital. The acceptance rate of MITS was 59.26%. Standard operating procedure (SOP) of conducting community MITS in an ambulance, is established. Major challenges were, Covid19 lockdown, reluctance of tribal parents for consent for MITS due to illiteracy, superstitions and fear of organ removal. Ambulance was an easy to reach transport means in remote area, provided a well-designed and discrete facility to perform MITS in community, winning the confidence of bereaved family. This has reduced time interval between time of death and performing MITS.

CONCLUSIONS

MITS in purpose-modified Ambulance can be used worldwide for community MITS especially in areas which are remote and lack healthcare access. This solution needs to be assessed in different cultural settings to document culture specific issues.

Enhancing the value of death registration with verbal autopsy data: a pilot study in the Senegalese urban population in 2019

BACKGROUND

There is no source of data on causes of death in Senegal that covers both community and hospital deaths. Yet the death registration system in the Dakar region is relatively complete (>80%) and could be expanded to provide information on the diseases and injuries that led to death.

METHODS

In this pilot study, we recorded all deaths that occurred over 2 months and were reported in the 72 civil registration offices in the Dakar region. We selected the deaths of residents of the region and administered a verbal autopsy to a relative of the deceased to identify the underlying causes of death. Causes of death were assigned using the InterVA5 model.

RESULTS

The age structure of deaths registered at the civil registry differed from that of the census, with a proportion of infant deaths about twice as high as in the census. The main causes of death were prematurity and obstetric asphyxia in newborns. Meningitis and encephalitis, severe malnutrition, and acute respiratory infections were the leading causes from 1 month to 15 years of age. Cardiovascular diseases accounted for 27% of deaths in adults aged 15-64 and 45% of deaths among adults above age 65, while neoplasms accounted for 20% and 12% of deaths in these two age groups, respectively.

CONCLUSIONS

This study demonstrates that the epidemiological transition is at an advanced stage in urban areas of Dakar, and underlines the importance of conducting regular studies based on verbal autopsies of deaths reported in civil registration offices.

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

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

Putting non-communicable disease data to work in Vietnam: an investigation of community health surveillance capacity

INTRODUCTION

Despite the public health system's critical role in non-communicable disease (NCD) surveillance in Vietnam, limited evidence exists on the implementation of NCD surveillance activities within these systems and the need for capacity building across different system levels to meet expected NCD surveillance goals. This study aimed to evaluate the status of and describe factors affecting the implementation of NCD surveillance activities and to identify the NCD surveillance capacity building needs of the public health system in Vietnam.

METHODS

We used a mixed-methods approach in four provinces, conducting self-completed surveys of staff from six Preventive Medicine Institutes (PHI), 53 Centres for Disease Control (CDC) and 148 commune health stations (CHS), as well as 14 in-depth interviews and 22 focus group discussions at four PHI, four CDC, and eight district health centres and CHS.

RESULTS

Study findings highlighted that although Vietnam has a well-functioning NCD surveillance system, a number of quality issues related to NCD surveillance data were salient. Multifactorial reasons were identified for incomplete, unconfirmed, and inaccurate mortality data and current disease surveillance data. Data on NCD management and treatment were reported to be of better quality than data for screening, targeted treatment, and counselling communication. Main factors affected the effective implementation of NCD surveillance, namely lack of complete and specific guidelines for NCD surveillance, limitations in human resource capacity within NCD departments, and shortage of funding for NCD surveillance activities.

CONCLUSION

Study findings provide practical strategies for strengthening health system capacity for NCD surveillance through developing policies, guidelines, and standardised tools to guide NCD surveillance and a road map for integrated NCD surveillance, developing training packages and manuals for all levels of the health system, and conducting utilisation-focused surveillance training programs.

Systematic estimates of the global, regional and national under-5 mortality burden attributable to birth defects in 2000-2019: a summary of findings from the 2020 WHO estimates

OBJECTIVES

To examine the potential for bias in the estimate of under-5 mortality due to birth defects recently produced by the WHO and the Maternal and Child Epidemiology Estimation research group.

DESIGN

Systematic analysis.

METHODS

We examined the estimated number of under-5 deaths due to birth defects, the birth defect specific under-5 mortality rate, and the per cent of under-5 mortality due to birth defects, by geographic region, national income and under-5 mortality rate for three age groups from 2000 to 2019.

RESULTS

The under-5 deaths per 1000 live births from birth defects fell from 3.4 (95% uncertainty interval (UI) 3.1-3.8) in 2000 to 2.9 (UI 2.6-3.3) in 2019. The per cent of all under-5 mortality attributable to birth defects increased from 4.6% (UI 4.1%-5.1%) in 2000 to 7.6% (UI 6.9%-8.6%) in 2019. There is significant variability in mortality due to birth defects by national income level. In 2019, the under-5 mortality rate due to birth defects was less in high-income countries than in low-income and middle-income countries, 1.3 (UI 1.2-1.3) and 3.0 (UI 2.8-3.4) per 1000 live births, respectively. These mortality rates correspond to 27.7% (UI 26.6%-28.8%) of all under-5 mortality in high-income countries being due to birth defects, and 7.4% (UI 6.7%-8.2%) in low-income and middle-income countries.

CONCLUSIONS

While the under-5 mortality due to birth defects is declining, the per cent of under-5 mortality attributable to birth defects has increased, with significant variability across regions globally. The estimates in low-income and middle-income countries are likely underestimated due to the nature of the WHO estimates, which are based in part on verbal autopsy studies and should be taken as a minimum estimate. Given these limitations, comprehensive and systematic estimates of the mortality burden due to birth defects are needed to estimate the actual burden.

Characteristics, clinical outcomes, and mortality of older adults living with HIV receiving antiretroviral treatment in the sub-urban and rural areas of northern Thailand

Since the introduction of antiretroviral treatment (ART), people living with HIV worldwide live into older age. This observational study described the characteristics, clinical outcomes, and mortality of older adults living with HIV (OALHIV) receiving ART from the National AIDS program in northern Thailand. Participants aged ≥ 50 years were recruited from the HIV clinics in 12 community hospitals. Data were obtained from medical records and face-to-face interviews. In 2015, 362 OALHIV were enrolled; their median (interquartile range) age and ART duration were 57 years (54-61), and 8.8 years (6.4-11.2), respectively. At study entry, 174 (48.1%) had CD4 counts ≥ 500 cells/mm3; 357 of 358 (99.6%) with available HIV RNA results were virologic-suppressed. At the year 5 follow-up, 39 died, 11 were transferred to other hospitals, 3 were lost to follow-up, and 40 did not contribute data for this analysis, but remained in care. Among the 269 who appeared, 149 (55%) had CD4 counts ≥ 500 cells/mm3, and 227/229 tested (99%) were virologic-suppressed. The probability of 5-year overall survival was 89.2% (95% confidence interval, CI 85.4-92.1%). A significantly low 5-year overall survival (66%) was observed in OALHIV with CD4 counts < 200 cells/mm3 at study entry. The most common cause of death was organ failure in 11 (28%), followed by malignancies in 8 (21%), infections in 5 (13%), mental health-related conditions in 2 (5%), and unknown in 13 (33%). In OALHIV with stable HIV treatment outcomes, mortality from non-infectious causes was observed. Monitoring of organ function, cancer surveillance, and mental health screening are warranted.

Cause-Specific Mortality Fraction (CSMF) of adult mortality in Butajira, South Central Ethiopia

Cause- and context-specific mortality data are imperative to understand the extent of health problems in low-income settings, where national death registration and cause of death identification systems are at a rudimentary stage. Aiming to estimate cause-specific mortality fractions, adult (15+ years) deaths between January 2008 and April 2020 were extracted from the Butajira health and demographic surveillance system electronic database. The physician review and a computerized algorithm, InterVA (Interpreting Verbal Autopsy), methods were used to assign the likely causes of death from January 2008 to April 2017 (the first) and May 2017 to April 2020 (the second) phase of the surveillance period, respectively. Initially, adult mortality rates per 1000py across sex and age were summarized. A total of 1,625 deaths were captured in 280, 461 person-years, with an overall mortality rate of 5.8 (95%CI: 5.5, 6.0) per 1000py. Principally, mortality fractions for each specific cause of death were estimated, and for 1,571 deaths, specific causes were determined. During the first phase, the leading cause of death was tuberculosis (13.6%), followed by hypertension (6.6%) and chronic liver disease (5.9%). During the second phase, digestive neoplasms (17.3%), tuberculosis (12.1%), and stroke (9.4%) were the leading causes of death, respectively. Moreover, tuberculosis was higher among persons aged 50+ (15.0%), males (13.8%), and in rural areas (14.1%) during the first phase. Hypertensive diseases were higher among females (7.9%) and in urbanities. In the second phase, digestive neoplasms were higher in the age group of 50-64 years (25.4%) and females (19.0%), and stroke was higher in older adults (65+) (10%) and marginally higher among males (9.7%). Our results showed that tuberculosis and digestive neoplasms were the most common causes of death. Hence, prevention, early detection, and management of cases at all levels of the existing healthcare system should be prioritized to avert premature mortality.

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

Background

Understanding context-specific temporal trends in mortality is essential for setting health policy priorities.

Objective

To investigate the trends and distribution of deaths due to communicable and non-communicable diseases and external causes in South-Central Ethiopia.

Method

All adult deaths captured by the Butajira Health and Demographic Surveillance System between January 2008 and December 2019 were included. A verbal autopsy method of collecting cause of death data was used. Physician review and a computerised algorithm, InterVA, were used to determine the cause of death. Coding was undertaken using the World Health Organization's International Classification of Diseases. Trends in adult mortality rate and proportional mortality were estimated by major cause of death categories. Significant trends were analysed using the Mann–Kendall statistical test with a significance set at P < 0.05. Deaths were also disaggregated by age, sex, and residence.

Results

There were 1,612 deaths in 279,681 person-years; 811 (50.3%) were females. The median age at death was 65 years. The proportional adult mortality and adult mortality rates (per 1000 person-years) attributed to communicable diseases, non-communicable diseases, and external causes were 31.1%, 58.9%, and 6.0%, and 1.9, 3.4, and 0.4, respectively. Adult mortality due to communicable diseases showed a declining trend (tau, the measure of the strength and direction of association, = −0.52; P < 0.05), whereas the trend increased for non-communicable diseases (tau = 0.67, P < 0.05) and external causes (tau = 0.29, P > 0.05). Moreover, death rates were pronounced in the 65+ age group and rural areas but comparable among males and females.

Conclusion

The trend in deaths due to communicable diseases declined but increased for non-communicable diseases and external causes with significant public health burdens. These findings will provide essential input in formulating health policy reforms to reduce premature mortality.

Burden of mortality linked to community-nominated priorities in rural South Africa

BACKGROUND

Community knowledge is a critical input for relevant health programmes and strategies. How community perceptions of risk reflect the burden of mortality is poorly understood.

OBJECTIVE

To determine the burden of mortality reflecting community-nominated health risk factors in rural South Africa, where a complex health transition is underway.

METHODS

Three discussion groups (total 48 participants) representing a cross-section of the community nominated health priorities through a Participatory Action Research process. A secondary analysis of Verbal Autopsy (VA) data was performed for deaths in the same community from 1993 to 2015 (n = 14,430). Using population attributable fractions (PAFs) extracted from Global Burden of Disease data for South Africa, deaths were categorised as 'attributable at least in part' to community-nominated risk factors if the PAF of the risk factor to the cause of death was >0. We also calculated 'reducible mortality fractions' (RMFs), defined as the proportions of each and all community-nominated risk factor(s) relative to all possible risk factors for deaths in the population  .

RESULTS

Three risk factors were nominated as the most important health concerns locally: alcohol abuse, drug abuse, and lack of safe water. Of all causes of deaths 1993-2015, over 77% (n = 11,143) were attributable at least in part to at least one community-nominated risk factor. Causes of attributable deaths, at least in part, to alcohol abuse were most common (52.6%, n = 7,591), followed by drug abuse (29.3%, n = 4,223), and lack of safe water (11.4%, n = 1,652). In terms of the RMF, alcohol use contributed the largest percentage of all possible risk factors leading to death (13.6%), then lack of safe water (7.0%), and drug abuse (1.3%)     .

CONCLUSION

A substantial proportion of deaths are linked to community-nominated risk factors. Community knowledge is a critical input to understand local health risks.

Leading causes of deaths in the mortality transition in Papua New Guinea: evidence from the Comprehensive Health and Epidemiological Surveillance System

Background

Changing causes of deaths in the mortality transition in Papua New Guinea (PNG) are poorly understood. This study analysed community-level data to identify leading causes of death in the population and variations across age groups and sexes, urban-rural sectors and provinces.

Method

Mortality surveillance data were collected from 2018–20 as part of the Comprehensive Health and Epidemiological Surveillance System (CHESS), using the World Health Organization 2016 verbal autopsy (VA) instrument. Data from 926 VA interviews were analysed, using the InterVA-5 cause of death analytical tool to assign specific causes of death among children (0–14 years), those of working age (15–64 years) and the elderly (65+ years).

Result

Nearly 50% of the total deaths were attributed to non-communicable diseases (NCDs), followed by infectious and parasitic diseases (35%), injuries and external causes (11%) and maternal and neonatal deaths (4%). Leading causes of death among children were acute respiratory tract infections (ARTIs) and diarrhoeal diseases, each contributing to 13% of total deaths. Among the working population, tuberculosis (TB) contributed to 12% of total deaths, followed by HIV/AIDS (11%). TB- and HIV/AIDS-attributed deaths were highest in the age group 25–34 years, at 20% and 18%, respectively. These diseases killed more females of working age (n = 79, 15%) than males (n = 52, 8%). Among the elderly, the leading causes of death were ARTIs (13%) followed by digestive neoplasms (10%) and acute cardiac diseases (9%).

Conclusion

The variations in leading causes of death across the populations in PNG suggest diversity in mortality transition. This requires different strategies to address specific causes of death in particular populations.

Social determinants of injury-attributed mortality in Papua New Guinea: new data from the Comprehensive Health and Epidemiological Surveillance System

OBJECTIVE

This study reported the prevalence and sociodemographic distribution of mortalities attributed to injuries in Papua New Guinea (PNG).

SETTING

As part of a longitudinal study, mortality data were collected from the population who live in eight surveillance sites of the Comprehensive Health and Epidemiological Surveillance System, established in six major provinces in PNG. Verbal autopsy (VA) interviews were conducted by the surveillance team with close relatives of the deceased, using the WHO 2016 VA instrument from January 2018 to December 2020.

PARTICIPANT AND INTERVENTION

Mortality data from 926 VA interviews were analysed, using the InterVA-5 diagnostic tool to assign specific cause of death (COD). Distributions of injury-attributed mortality were calculated and multinomial logistic regression analyses were conducted to identify sociodemographic factors and provide ORs, 95% CIs of estimates and p values.

RESULT

Injury-attributed deaths accounted for 13% of the total deaths recorded in the surveillance population, with the highest proportion in Madang (22%), followed by Port Moresby and Central Province (13%). Road traffic accidents were the leading COD, accounting for 43% of the total injury-attributed deaths, followed by assaults (25%) and accidental falls (10%). Young adults (aged 15-24 years) accounted the largest proportion of injury-attributed deaths (34%) and were nearly six times more likely to die from injuries than those aged 75+ years (OR: 5.89 (95% CI: 2.18 to 15.9); p<0.001). Males were twice more likely to die from injuries than females (OR: 2.0 (95% CI: 1.19 to 3.36); p=0.009). Another significant sociodemographic factor associated with the increased injury-attributed mortalities included urban versus rural residence (OR: 2.0 (95% CI: 1.01 to 3.99); p=0.048).

CONCLUSION

Young adults, particularly those who live in urban areas, were at the highest risk of dying from injuries. Public health policies and interventions are needed to reduce premature mortality from injuries in PNG.

Mixed-methods analysis of select issues reported in the 2016 World Health Organization verbal autopsy questionnaire

BACKGROUND

Use of a standardized verbal autopsy (VA) questionnaire, such as the World Health Organization (WHO) instrument, can improve the consistency and reliability of the data it collects. Systematically revising a questionnaire, however, requires evidence about the performance of its questions. The purpose of this investigation was to use a mixed methods approach to evaluate the performance of questions related to 14 previously reported issues in the 2016 version of the WHO questionnaire, where there were concerns of potential confusion, redundancy, or inability of the respondent to answer the question. The results from this mixed methods analysis are discussed across common themes that may have contributed to the underperformance of questions and have been compiled to inform decisions around the revision of the current VA instrument.

METHODS

Quantitative analysis of 19,150 VAs for neonates, children, and adults from five project teams implementing VAs predominately in Sub-Saharan Africa included frequency distributions and cross-tabulations to evaluate response patterns among related questions. The association of respondent characteristics and response patterns was evaluated using prevalence ratios. Qualitative analysis included results from cognitive interviewing, an approach that provides a detailed understanding of the meanings and processes that respondents use to answer interview questions. Cognitive interviews were conducted among 149 participants in Morocco and Zambia. Findings from the qualitative and quantitative analyses were triangulated to identify common themes.

RESULTS

Four broad themes contributing to the underperformance or redundancy within the instrument were identified: question sequence, overlap within the question series, questions outside the frame of reference of the respondent, and questions needing clarification. The series of questions associated with one of the 14 identified issues (the series of questions on injuries) related to question sequence; seven (tobacco use, sores, breast swelling, abdominal problem, vomiting, vaccination, and baby size) demonstrated similar response patterns among questions within each series capturing overlapping information. Respondent characteristics, including relationship to the deceased and whether or not the respondent lived with the deceased, were associated with differing frequencies of non-substantive responses in three question series (female health related issues, tobacco use, and baby size). An inconsistent understanding of related constructs was observed between questions related to sores/ulcers, birth weight/baby size, and diagnosis of dementia/presence of mental confusion. An incorrect association of the intended construct with that which was interpreted by the respondent was observed in the medical diagnosis question series.

CONCLUSIONS

In this mixed methods analysis, we identified series of questions which could be shortened through elimination of redundancy, series of questions requiring clarification due to unclear constructs, and the impact of respondent characteristics on the quality of responses. These changes can lead to a better understanding of the question constructs by the respondents, increase the acceptance of the tool, and improve the overall accuracy of the VA instrument.

Performance evaluation of machine learning and Computer Coded Verbal Autopsy (CCVA) algorithms for cause of death determination: A comparative analysis of data from rural South Africa

Computer Coded Verbal Autopsy (CCVA) algorithms are commonly used to determine the cause of death (CoD) from questionnaire responses extracted from verbal autopsies (VAs). However, they can only operate on structured data and cannot effectively harness information from unstructured VA narratives. Machine Learning (ML) algorithms have also been applied successfully in determining the CoD from VA narratives, allowing the use of auxiliary information that CCVA algorithms cannot directly utilize. However, most ML-based studies only use responses from the structured questionnaire, and the results lack generalisability and comparability across studies. We present a comparative performance evaluation of ML methods and CCVA algorithms on South African VA narratives data, using data from Agincourt Health and Demographic Surveillance Site (HDSS) with physicians' classifications as the gold standard. The data were collected from 1993 to 2015 and have 16,338 cases. The random forest and extreme gradient boosting classifiers outperformed the other classifiers on the combined dataset, attaining accuracy of 96% respectively, with significant statistical differences in algorithmic performance (p < 0.0001). All our models attained Area Under Receiver Operating Characteristics (AUROC) of greater than 0.884. The InterVA CCVA attained 83% Cause Specific Mortality Fraction accuracy and an Overall Chance-Corrected Concordance of 0.36. We demonstrate that ML models could accurately determine the cause of death from VA narratives. Additionally, through mortality trends and pattern analysis, we discovered that in the first decade of the civil registration system in South Africa, the average life expectancy was approximately 50 years. However, in the second decade, life expectancy significantly dropped, and the population was dying at a much younger average age of 40 years, mostly from the leading HIV related causes. Interestingly, in the third decade, we see a gradual improvement in life expectancy, possibly attributed to effective health intervention programmes. Through a structure and semantic analysis of narratives where experts disagree, we also demonstrate the most frequent terms of traditional healer consultations and visits. The comparative approach also makes this study a baseline that can be used for future research enforcing generalization and comparability. Future study will entail exploring deep learning models for CoD classification.

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.

A prospective cohort study on the association between waterpipe tobacco smoking and gastric cancer mortality in Northern Vietnam

Tobacco consumption, as a worldwide problem, is a risk factor for several types of cancer. In Vietnam, tobacco consumption in the form of waterpipe tobacco smoking is common. This prospective cohort study aimed to study the association between waterpipe tobacco smoking and gastric cancer mortality in Northern Vietnam. A total of 25,619 eligible participants were followed up between 2008 and 2019. Waterpipe tobacco and cigarette smoking data were collected; semi-quantitative food frequency and lifestyle questionnaires were also utilized. Gastric cancer mortality was determined via medical records available at the state health facilities. A Cox proportional hazards model was used to estimate hazard ratios (HR) and 95% confidence intervals (95% CI). During 314,992.8 person-years of follow-up, 55 men and 25 women deaths due to gastric cancer were identified. With never-smokers as the reference, the risk of gastric cancer mortality was significantly increased in participants who were ever-smoking (HR = 2.43, 95% CI = 1.35–4.36). The positive risk was also observed in men but was not significantly increased in women. By types of tobacco use, exclusive waterpipe smokers showed a significantly increased risk of gastric cancer mortality (HR = 3.22, 95% CI = 1.67–6.21) but that was not significantly increased in exclusive cigarette smokers (HR = 1.90, 95% CI = 0.88–4.07). There was a significant positive association between tobacco smoking and gastric cancer death for indicators of longer smoking duration, higher frequency per day, and cumulative frequency of both waterpipe and cigarette smoking. Waterpipe tobacco smoking would significantly increase the risk of gastric cancer mortality in the Vietnamese population. Further studies are required to understand the waterpipe tobacco smoking-driven gastric cancer burden and promote necessary interventions.

Tuberculosis and HIV/AIDS-attributed mortalities and associated sociodemographic factors in Papua New Guinea: evidence from the comprehensive health and epidemiological surveillance system

OBJECTIVE

Tuberculosis (TB) and HIV/AIDS are public health concerns in Papua New Guinea (PNG). This study examines TB and HIV/AIDS mortalities and associated sociodemographic factors in PNG.

METHOD

As part of a longitudinal study, verbal autopsy (VA) interviews were conducted using the WHO 2016 VA Instrument to collect data of 926 deaths occurred in the communities within the catchment areas of the Comprehensive Health and Epidemiological Surveillance System from 2018 to 2020.InterVA-5 cause of deaths analytical tool was used to assign specific causes of death (COD). Multinomial logistic regression analyses were conducted to identify associated sociodemographic factors, estimate adjusted ORs (AOR), 95% CIs and p values.

RESULT

TB and HIV/AIDS were the leading CODs from infectious diseases, attributed to 9% and 8% of the total deaths, respectively.Young adults (25-34 years) had the highest proportion of deaths from TB (20%) and the risk of dying from TB among this age group was five times more likely than those aged 75+ years (AOR: 5.5 (95% CI 1.4 to 21.7)). Urban populations were 46% less likely to die from this disease compared rural ones although the difference was not significant (AOR: 0.54 (95% CI 0.3 to 1.0)). People from middle household wealth quintile were three times more likely to die from TB than those in the richest quintile (AOR: 3.0 (95% CI 1.3 to 7.4)).Young adults also had the highest proportion of deaths to HIV/AIDS (18%) and were nearly seven times more likely to die from this disease compared with those aged 75+years (AOR: 6.7 (95% CI 1.7 to 25.4)). Males were 48% less likely to die from HIV/AIDS than females (AOR: 0.52 (95% CI 0.3 to 0.9)). The risk of dying from HIV/AIDS in urban population was 54% less likely than their rural counterparts (AOR: 0.46 (95% CI 0.2 to 0.9)).

CONCLUSION

TB and HIV/AIDS interventions are needed to target vulnerable populations to reduce premature mortality from these diseases in PNG.

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.

Assessment of the maternal death surveillance and response implementation process in Burkina Faso

OBJECTIVE

To evaluate the maternal death surveillance and response (MDSR) implementation process in two health districts in Burkina Faso and identify factors that have affected implementation.

METHODS

We conducted a case study in two health districts selected by purposive sampling according to location (rural or urban) during the period 2015-2016. Data gathering consisted of semi-structured interviews with several health personnel involved in the implementation process.

RESULTS

Identification and notification of deaths varied depending on the facility. Maternal death review sessions were irregular, and the completion rate was lower in urban areas The community component has not yet been implemented and review of newborn deaths is not yet standard practice. Follow-up and implementation of the review recommendations were inadequate.

CONCLUSION

Implementation of the MDSR system in Burkina Faso remains in progress. Improvements are needed in notification of deaths occurring at community level, monitoring and evaluation, and integration of newborn deaths into the process.

Birth asphyxia is under-rated as a cause of preterm neonatal mortality in low- and middle-income countries: A prospective, observational study from PURPOSe

OBJECTIVE

To assess respiratory distress syndrome (RDS) compared with birth asphyxia as the cause of death in preterm newborns, assigned by the neonatal intensive care unit (NICU) physician at the time of death and assigned by a panel with complete obstetric history, placental evaluation, tissue histology and microbiology.

DESIGN

Prospective, observational study.

SETTINGS

Study NICUs in India and Pakistan.

POPULATION

Preterm infants delivered in study facility.

METHODS

A total of 410 preterm infants who died in the NICU with cause of death ascertained by the NICU physicians and independently by expert panels. We compared the percentage of cases assigned RDS versus birth asphyxia as cause of death by the physician and the panel.

MAIN OUTCOME MEASURES

RDS and birth asphyxia.

RESULTS

Of 410 preterm neonatal deaths, the discharging NICU physicians found RDS as a cause of death among 83.2% of the cases, compared with the panel finding RDS in only 51.0%. In the same neonatal deaths, the NICU physicians found birth asphyxia as a cause of death in 14.9% of the deaths, whereas the panels found birth asphyxia in 57.6% of the deaths. The difference was greater in Pakistan were the physicians attributed 89.7% of the deaths to RDS and less than 1% to birth asphyxia whereas the panel attributed 35.6% of the deaths to RDS and 62.7% to birth asphyxia.

CONCLUSIONS

NICU physicians who reported cause of death in deceased preterm infants less often attributed the death to birth asphyxia, and instead more often chose RDS, whereas expert panels with more extensive data attributed a greater proportion of deaths to birth asphyxia than did the physicians.

Neonatal mortality in two districts in Indonesia: Findings from Neonatal Verbal and Social Autopsy (VASA)

Background

The Government of Indonesia is determined to follow global commitments to reduce the neonatal mortality rate. Yet, there is a paucity of information on contributing factors and causes of neonatal deaths, particularly at the sub-national level. This study describes care-seeking during neonates’ fatal illnesses and their causes of death.

Methods

We conducted a cross-sectional community-based study to identify all neonatal deaths in Serang and Jember Districts, Indonesia. Follow-up interviews were conducted with the families of deceased neonates using an adapted verbal and social autopsy instrument. Cause of death was determined using the InSilicoVA algorithm.

Results

The main causes of death of 259 neonates were prematurity (44%) and intrapartum-related events (IPRE)-mainly birth asphyxia (39%). About 83% and 74% of the 259 neonates were born and died at a health facility, respectively; 79% died within the first week after birth. Of 70 neonates whose fatal illness began at home, 59 (84%) sought care during the fatal illness. Forty-eight of those 59 neonates went to a formal care provider; 36 of those 48 neonates (75%) were moderately or severely ill when the family decided to seek care. One hundred fifteen of 189 neonates (61%) whose fatal illnesses began at health facilities were born at a hospital. Among those 115, only 24 (21%) left the hospital alive–of whom 16 (67%) were referred by the hospital.

Conclusions

The high proportion of deaths due to prematurity and IPRE suggests the need for improved management of small and asphyxiated newborns. The moderate to severe condition of neonates at the time when care was sought from home highlights the importance of early illness recognition and appropriate management for sick neonates. Among deceased neonates whose fatal illness began at their delivery hospital, the high proportion of referrals may indicate issues with hospital capability, capacity, and/or cost.

Non-communicable diseases attributed mortality and associated sociodemographic factors in Papua New Guinea: Evidence from the Comprehensive Health and Epidemiological Surveillance System

BACKGROUND

Papua New Guinea (PNG) is undergoing an epidemiological transition with increased mortality from NCDs. This study examined NCDs-attributed mortality and associated sociodemographic factors in PNG.

METHOD

Using WHO 2016 instrument, 926 verbal autopsy (VA) interviews were conducted in six major provinces from January 2018 to December 2020. InterVA-5 tool was used to assign causes of death (COD). Multivariable logistic regression analysis was performed to identify sociodemographic factors associated with mortalities from emerging and endemic NCDs.

FINDING

NCDs accounted for 47% of the total deaths, including 20% of deaths attributed to emerging NCDs and 27% of deaths due to endemic NCDs. Leading CODs from emerging NCDs were identified including cardiac diseases, stroke, and diabetes. The risk of dying from emerging NCDs was significantly lower among populations under age 44y compared with population aged 75+y (OR: 0.14 [0.045-0.433]; p-value: 0.001). People living in urban areas were twice likely to die from emerging NCDs than those in rural areas (OR: 1.92 [1.116-3.31]; p-value: 0.018). People in Madang province were 70% less likely to die from emerging NCDs compared to those from East New Britain province (OR: 0.314 [0.135-0.73]; p-value: 0.007). Leading CODs from endemic NCDs included digestive neoplasms, respiratory neoplasms, and other neoplasms. Only children aged 0-4y had significant lower risk of dying from endemic NCDs compared to the population aged 75+y (OR: 0.114 [95% CI: 0.014-0.896]; p-value: 0.039).

CONCLUSION

Public health interventions are urgently needed, prioritizing urban population and those aged over 44y to reduce premature mortality from NCDs.

Trend and Determinants of Mortality Among Women of Reproductive Age: A Twelve-Year Open Cohort Study in Eastern Ethiopia

Background: With only less than a decade left till 2030, it is essential to research the burden and trends of women of reproductive age (WRA) mortality in order to design appropriate interventions toward achieving goal three of the sustainable development goals (SDGs), good health and well-being. For several low-income countries, such data are often lacking or sometimes extrapolated from non-representative facility-based studies. In this paper, we presented trends, causes, and determinants of mortality among reproductive-age women under follow-up for 12 years through the Health and Demographic Surveillance System (HDSS) located in eastern Ethiopia.

Methods: We used 12 years of (2008 to 2019) open cohort data of women aged 15–49 living in Kersa HDSS in Eastern Ethiopia. In the HDSS, data on socio-demographic and basic household conditions are recorded for every household member at enrollment, and data on vital events such as births, deaths, and migration were collected and updated biannually as the event happened. Mortality was determined by automated verbal autopsy (InterVA) algorism. We assessed trends in women's reproductive age mortality and the associated determinants using crude and adjusted Cox regression models.

Results: In the 12-years cohort, we followed 74,790 women of reproductive age for 339,909.26 person-years-at-risk of observation (PYO), of whom 919 died. Overall, the standardized mortality rate was 270 per 100,000 PYO. There was a notable increase in mortality in the first 3 years (2009 to 2011) which then declined significantly (p = 0.0001) until 2019. Most of the deaths were caused by HIV/AIDS (27.88%) and pulmonary tuberculosis (10.62%). In the adjusted Cox regression analysis, the hazard of death was higher among rural residents (AHR, 2.03: 95% CI: 1.60–2.58), unemployed women (AHR, 1.50: 95% CI: 1.19–1.89), and women with no formal education (AHR, 1.24: 95% CI: 1.01–1.52).

Conclusion: The study showed a high number of women of reproductive age are still dying mainly due to causes for which preventable strategies are known and have been successfully implemented. The study identified that the main causes of death were related to HIV/AIDS and tuberculosis, and there was a higher hazard of mortality among rural residents, unemployed women, and those with no formal education, who need effective implementation in achieving the SDG three.

Improving methods to measure comparable mortality cause (IMMCMC) gold standard verbal autopsy dataset

Objectives

Gold standard cause of death data is critically important to improve verbal autopsy (VA) methods in diagnosing cause of death where civil and vital registration systems are inadequate or poor. As part of a three-country research study—Improving Methods to Measure Comparable Mortality by Cause (IMMCMC) study—data were collected on clinicopathological criteria-based gold standard cause of death from hospital record reviews with matched VAs. The purpose of this data note is to make accessible a de-identified format of these gold standard VAs for interested researchers to improve the diagnostic accuracy of VA methods.

Data description

The study was conducted between 2011 and 2014 in the Philippines, Bangladesh, and Papua New Guinea. Gold standard diagnoses of underlying causes of death for deaths occurring in hospital were matched to VAs conducted using a standardized VA questionnaire developed by the Population Health Metrics Consortium. 3512 deaths were collected in total, comprised of 2491 adults (12 years and older), 320 children (28 days to 12 years), and 702 neonates (0–27 days).

Mortality estimates for WHO SEAR countries: problems and prospects

Cause-specific mortality estimates for 11 countries located in the WHO’s South East Asia Region (WHO SEAR) are generated periodically by the Global Burden of Disease (GBD) and the WHO Global Health Estimates (GHE) analyses. A comparison of GBD and GHE estimates for 2019 for 11 specific causes of epidemiological importance to South East Asia was undertaken. An index of relative difference (RD) between the estimated numbers of deaths by sex for each cause from the two sources for each country was calculated, and categorised as marginal (RD=±0%–9%), moderate (RD=±10%–19%), high (RD=±20%–39%) and extreme (RD>±40%). The comparison identified that the RD was >10% in two-thirds of all instances. The RD was ‘high’ or ‘extreme’ for deaths from tuberculosis, diarrhoea, road injuries and suicide for most SEAR countries, and for deaths from most of the 11 causes in Bangladesh, DPR Korea, Myanmar, Nepal and Sri Lanka. For all WHO SEAR countries, mortality estimates from both sources are based on statistical models developed from an international historical cause-specific mortality data series that included very limited empirical data from the region. Also, there is no scientific rationale available to justify the reliability of one set of estimates over the other. The characteristics of national mortality statistics systems for each WHO SEAR country were analysed, to understand the reasons for weaknesses in empirical data. The systems analysis identified specific limitations in structure, organisation and implementation that affect data completeness, validity of causes of death and vital statistics production, which vary across countries. Therefore, customised national strategies are required to strengthen mortality statistics systems to meet immediate and long-term data needs for health policy and research, and reduce dependence on current unreliable modelled estimates.

Trends and risk factors for non-communicable diseases mortality in Nairobi slums (2008-2017)

INTRODUCTION

Tracking progress in reaching global targets for reducing premature mortality from non-communicable diseases (NCDs) requires accurately collected population based longitudinal data. However, most African countries lack such data because of weak or non-existent civil registration systems. We used data from the Nairobi Urban Health and Demographic Surveillance System (NUDSS) to estimate NCD mortality trends over time and to explore the determinants of NCD mortality.

METHODS

Deaths identified in the NUHDSS were followed up with a verbal autopsy to determine the signs and symptoms preceding the death. Causes of death were then assigned using InSilicoVA algorithm. We calculated the rates of NCD mortality in the whole NUHDSS population between 2008 and 2017, looking at how these changed over time. We then merged NCD survey data collected in 2008, which contains information on potential determinants of NCD mortality in a sub-sample of the NUHDSS population, with follow up information from the full NUHDSS including whether any of the participants died of an NCD or non-NCD cause. Poisson regression models were used to identify independent risk factors (broadly categorized as socio-demographic, behavioural and physiological) for NCD mortality, as well as non-NCD mortality.

RESULTS

In the total NUHDSS population of adults age 18 and over, 23% were assigned an NCD as the most likely cause of death. There was evidence that NCD mortality decreased over the study period, with rates of NCD mortality dropping from 1.32 per 1000 person years in 2008-10 (95% CI: 1.13-1.54) to 0.93 per 1000 person years in 2014-17 (95% CI: 0.80-1.08). Of 5115 individuals who participated in the NCD survey in 2008, 421 died during the follow-up period of which 43% were attributed to NCDs. Increasing age, lower education levels, ever smoking and having high blood pressure were identified as independent determinants of NCD mortality in multivariate analyses.

CONCLUSION

We found that NCDs account for one-quarter of mortality in Nairobi slums, although we document a reduction in the rate of NCD mortality over time. This may be attributed to increased surveillance and introduction of population-wide NCD interventions and health system improvements from research activities in the slums. To achieve further decline there is a need to strengthen health systems to respond to NCD care and prevention along with addressing social factors such as education.

Estimating causes of death where there is no medical certification: evolution and state of the art of verbal autopsy

Over the past 70 years, significant advances have been made in determining the causes of death in populations not served by official medical certification of cause at the time of death using a technique known as Verbal Autopsy (VA). VA involves an interview of the family or caregivers of the deceased after a suitable bereavement interval about the circumstances, signs and symptoms of the deceased in the period leading to death. The VA interview data are then interpreted by physicians or, more recently, computer algorithms, to assign a probable cause of death. VA was originally developed and applied in field research settings. This paper traces the evolution of VA methods with special emphasis on the World Health Organization's (WHO)'s efforts to standardize VA instruments and methods for expanded use in routine health information and vital statistics systems in low- and middle-income countries (LMICs). These advances in VA methods are culminating this year with the release of the 2022 WHO Standard Verbal Autopsy (VA) Toolkit. This paper highlights the many contributions the late Professor Peter Byass made to the current VA standards and methods, most notably, the development of InterVA, the most commonly used automated computer algorithm for interpreting data collected in the WHO standard instruments, and the capacity building in low- and middle-income countries (LMICs) that he promoted. This paper also provides an overview of the methods used to improve the current WHO VA standards, a catalogue of the changes and improvements in the instruments, and a mapping of current applications of the WHO VA standard approach in LMICs. It also provides access to tools and guidance needed for VA implementation in Civil Registration and Vital Statistics Systems at scale.

Comparison of machine learning algorithms applied to symptoms to determine infectious causes of death in children: national survey of 18,000 verbal autopsies in the Million Death Study in India

BACKGROUND

Machine learning (ML) algorithms have been successfully employed for prediction of outcomes in clinical research. In this study, we have explored the application of ML-based algorithms to predict cause of death (CoD) from verbal autopsy records available through the Million Death Study (MDS).

METHODS

From MDS, 18826 unique childhood deaths at ages 1-59 months during the time period 2004-13 were selected for generating the prediction models of which over 70% of deaths were caused by six infectious diseases (pneumonia, diarrhoeal diseases, malaria, fever of unknown origin, meningitis/encephalitis, and measles). Six popular ML-based algorithms such as support vector machine, gradient boosting modeling, C5.0, artificial neural network, k-nearest neighbor, classification and regression tree were used for building the CoD prediction models.

RESULTS

SVM algorithm was the best performer with a prediction accuracy of over 0.8. The highest accuracy was found for diarrhoeal diseases (accuracy = 0.97) and the lowest was for meningitis/encephalitis (accuracy = 0.80). The top signs/symptoms for classification of these CoDs were also extracted for each of the diseases. A combination of signs/symptoms presented by the deceased individual can effectively lead to the CoD diagnosis.

CONCLUSIONS

Overall, this study affirms that verbal autopsy tools are efficient in CoD diagnosis and that automated classification parameters captured through ML could be added to verbal autopsies to improve classification of causes of death.

Verbal autopsy models in determining causes of death

OBJECTIVES

To systematically review current practices, strengths and limitations of existing VA approaches to increase understanding of health system stakeholders and researchers.

METHODS

The review was conducted and reported based on the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines, in which articles were systematically obtained from the PubMed and SCOPUS online databases. The search was limited to English language journal articles published between 2010 and 2020. The review identified 5602 articles and after thorough scrutiny, 25 articles related to VA approaches were included.

RESULTS

(1) InterVA and Tariff are widely used VA models; (2) Bayes rule is the most common and successful algorithm; (3) the lack of standardised datasets and metrics to evaluate models creates bias in determining VA model performance; (4) performance of the models trained using in-hospital data cannot be replicated in community death; (5) the performance of models among physicians and computer-coded algorithms differs with variation in settings.

CONCLUSION

The physician-certified verbal autopsy (PCVA) approaches are more effective in determining community CoD while computerised coding of verbal autopsy (CCVA) models perform well when the underlying CoD are reliably established using hospital data where data are trained in a similar environment to the target population. Our study recommends the use of hybrid models that combine strengths from various models and using an open standards dataset that includes death from different settings.

Thirty-day outcomes and predictors of mortality following acute myocardial infarction in northern Tanzania: A prospective observational cohort study

OBJECTIVE

There is a rising burden of myocardial infarction (MI) within sub-Saharan Africa. Prospective studies of detailed MI outcomes in the region are lacking.

METHODS

Adult patients with confirmed MI from a prospective surveillance study in northern Tanzania were enrolled in a longitudinal cohort study after baseline health history, medication use, and sociodemographic data were obtained. Thirty days following hospital presentation, symptom status, rehospitalizations, medication use, and mortality were assessed via telephone or in-person interviews using a standardized follow-up questionnaire. Multivariate logistic regression was performed to identify baseline predictors of thirty-day mortality.

RESULTS

Thirty-day follow-up was achieved for 150 (98.7%) of 152 enrolled participants. Of these, 85 (56.7%) survived to thirty-day follow-up. Of the surviving participants, 71 (83.5%) reported persistent anginal symptoms, four (4.7%) reported taking aspirin regularly, seven (8.2%) were able to identify MI as the reason for their hospitalization, and 17 (20.0%) had unscheduled rehospitalizations. Self-reported history of diabetes at baseline (OR 0.32, 95% CI 0.10-0.89, p = 0.04), self-reported history of hypertension at baseline (OR 0.34, 95% CI 0.15-0.74, p = 0.01), and antiplatelet use at initial presentation (OR 0.19, 95% CI 0.04-0.65, p = 0.02) were all associated with lower odds of thirty-day mortality.

CONCLUSIONS

In northern Tanzania, thirty-day outcomes following acute MI are poor, and mortality is associated with self-awareness of comorbidities and medication usage. Further investigation is needed to develop interventions to improve care and outcomes of MI in Tanzania.

Mortality trends and access to care for cardiovascular diseases in Agincourt, rural South Africa: a mixed-methods analysis of verbal autopsy data

OBJECTIVES

Cardiovascular diseases are the second leading cause of mortality behind HIV/AIDS in South Africa. This study investigates cardiovascular disease mortality trends in rural South Africa over 20+ years and the associated barriers to accessing care, using verbal autopsy data.

DESIGN

A mixed-methods approach was used, combining descriptive analysis of mortality rates over time, by condition, sex and age group, quantitative analysis of circumstances of mortality (CoM) indicators and free text narratives of the final illness, and qualitative analysis of free texts.

SETTING

This study was done using verbal autopsy data from the Health and Socio-Demographic Surveillance System site in Agincourt, rural South Africa.

PARTICIPANTS

Deaths attributable to cardiovascular diseases (acute cardiac disease, stroke, renal failure and other unspecified cardiac disease) from 1993 to 2015 were extracted from verbal autopsy data.

RESULTS

Between 1993 and 2015, of 15 305 registered deaths over 1 851 449 person-years of follow-up, 1434 (9.4%) were attributable to cardiovascular disease, corresponding to a crude mortality rate of 0.77 per 1000 person-years. Cardiovascular disease mortality rate increased from 0.34 to 1.12 between 1993 and 2015. Stroke was the dominant cause of death, responsible for 41.0% (588/1434) of all cardiovascular deaths across all years. Cardiovascular disease mortality rate was significantly higher in women and increased with age. The main delays in access to care during the final illness were in seeking and receiving care. Qualitative free-text analysis highlighted delays not captured in the CoM, principally communication between the clinician and patient or family. Half of cases initially sought care outside a hospital setting (50.9%, 199/391).

CONCLUSIONS

The temporal increase in deaths due to cardiovascular disease highlights the need for greater prevention and management strategies for these conditions, particularly for the women. Strategies to improve seeking and receiving care during the final illness are needed.

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

In low-resource settings where vital registration of death is not routine it is often of critical interest to determine and study the cause of death (COD) for individuals and the cause-specific mortality fraction (CSMF) for populations. Post-mortem autopsies, considered the gold standard for COD assignment, are often difficult or impossible to implement due to deaths occurring outside the hospital, expense, and/or cultural norms. For this reason, Verbal Autopsies (VAs) are commonly conducted, consisting of a questionnaire administered to next of kin recording demographic information, known medical conditions, symptoms, and other factors for the decedent. This article proposes a novel class of hierarchical factor regression models that avoid restrictive assumptions of standard methods, allow both the mean and covariance to vary with COD category, and can include covariate information on the decedent, region, or events surrounding death. Taking a Bayesian approach to inference, this work develops an MCMC algorithm and validates the FActor Regression for Verbal Autopsy (FARVA) model in simulation experiments. An application of FARVA to real VA data shows improved goodness-of-fit and better predictive performance in inferring COD and CSMF over competing methods. Code and a user manual are made available at https://github.com/kelrenmor/farva.

Estimating causes of out-of-hospital deaths in China: application of SmartVA methods

Background

Most deaths in China occur at home, making it difficult to collect reliable cause of death (CoD) information. Verbal autopsy (VA) was applied using the SmartVA tool to a sample of home deaths in China to explore its feasibility as a means of improving the quality of CoD data.

Methods

The study was carried out in 22 districts in 9 provinces, located in north-east, central, and western areas of China during 2017 and 2018. Trained interviewers selected suitable respondents in each household to collect information using the Population Health Metrics Research Consortium (PHMRC) shortened and validated electronic VA questionnaire on tablets. The CoD was diagnosed from the interview data using the SmartVA-Analyze 2.0 software (Tariff 2.0).

Results

Non-communicable diseases (NCDs) dominated the leading causes of death in all age groups and for both sexes. After redistribution of undetermined causes, stroke (24%), ischemic heart diseases (IHD) (21%), chronic respiratory diseases (11%), and lung cancer (6%) were the leading causes of death. The cause fractions for level-one cause categories and ranking of specific causes were similar between SmartVA and results from the Global Burden of Disease (GBD) study.

Conclusion

Evidence from this large pilot study suggests that SmartVA is a feasible and plausible tool and could be a valuable tool to improve the quality and standardization of CoD information across China.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12963-021-00256-1.

Effect of Delays in Maternal Access to Healthcare on Neonatal Mortality in Sierra Leone: A Social Autopsy Case-Control Study at a Child Health and Mortality Prevention Surveillance (CHAMPS) Site

INTRODUCTION

In low-resource settings, a social autopsy tool has been proposed to measure the effect of delays in access to healthcare on deaths, complementing verbal autopsy questionnaires routinely used to determine cause of death. This study estimates the contribution of various delays in maternal healthcare to subsequent neonatal mortality using a social autopsy case-control design.

METHODS

This study was conducted at the Child Health and Mortality Prevention Surveillance (CHAMPS) Sierra Leone site (Makeni City and surrounding rural areas). Cases were neonatal deaths in the catchment area, and controls were sex- and area-matched living neonates. Odds ratios for maternal barriers to care and neonatal death were estimated, and stratified models examined this association by neonatal age and medical complications.

RESULTS

Of 53 neonatal deaths, 26.4% of mothers experienced at least one delay during pregnancy or delivery compared to 46.9% of mothers of stillbirths and 18.6% of control mothers. The most commonly reported delay among neonatal deaths was receiving care at the facility (18.9%). Experiencing any barrier was weakly associated (OR 1.68, CI 0.77, 3.67) and a delay in receiving care at the facility was strongly associated (OR 19.15, CI 3.90, 94.19) with neonatal death.

DISCUSSION

Delays in healthcare are associated with neonatal death, particularly delays experienced at the healthcare facility. Heterogeneity exists in the prevalence of specific delays, which has implications for local public health policy. The findings and conclusions in this report are those of the author(s) and do not necessarily represent the official position of the Centers for Disease Control and Prevention.