Cause of death distribution with InterVA and physician coding in a rural area of Burkina Faso

Child Survival and Annual Crop Yield Reductions in Rural Burkina Faso: Critical Windows of Vulnerability Around Early-Life Development

Populations that are reliant on subsistence farming are particularly vulnerable to climatic effects on crop yields. However, empirical evidence on the role of the timing of exposure to crop yield deficits in early-life development is limited. We examined the relationship between child survival and annual crop yield reductions at different stages of early-life development in a subsistence farming population in Burkina Faso. Using shared frailty Cox proportional hazards models adjusting for confounders, we analyzed 57,288 children under 5 years of age followed by the Nouna Health and Demographic Surveillance System (1994-2016) in relation to provincial food-crop yield levels experienced in 5 nonoverlapping time windows (12 months before conception, gestation, birth-age 5.9 months, ages 6.0 months-1.9 years, and ages 2.0-4.9 years) and their aggregates (birth-1.9 years, first 1,000 days from conception, and birth-4.9 years). Of the nonoverlapping windows, point estimates were largest for child survival related to food-crop yields for the time window of 6.0 months-1.9 years: The adjusted mortality hazard ratio was 1.10 (95% confidence interval: 1.03, 1.19) for a 90th-to-10th percentile yield reduction. These findings suggest that child survival in this setting is particularly vulnerable to cereal-crop yield reductions during the period of nonexclusive breastfeeding.

The effect of extreme temperature and precipitation on cause-specific deaths in rural Burkina Faso: a longitudinal study

BACKGROUND

Extreme weather is becoming more common due to climate change and threatens human health through climate-sensitive diseases, with very uneven effects around the globe. Low-income, rural populations in the Sahel region of west Africa are projected to be severely affected by climate change. Climate-sensitive disease burdens have been linked to weather conditions in areas of the Sahel, although comprehensive, disease-specific empirical evidence on these relationships is scarce. In this study, we aim to provide an analysis of the associations between weather conditions and cause-specific deaths over a 16-year period in Nouna, Burkina Faso.

METHODS

In this longitudinal study, we used de-identified, daily cause-of-death data from the Health and Demographic Surveillance System led by the Centre de Recherche en Santé de Nouna (CRSN) in the National Institute of Public Health of Burkina Faso, to assess temporal associations between daily and weekly weather conditions (maximum temperature and total precipitation) and deaths attributed to specific climate-sensitive diseases. We implemented distributed-lag zero-inflated Poisson models for 13 disease-age groups at daily and weekly time lags. We included all deaths from climate-sensitive diseases in the CRSN demographic surveillance area from Jan 1, 2000 to Dec 31, 2015 in the analysis. We report the exposure-response relationships at percentiles representative of the exposure distributions of temperature and precipitation in the study area.

FINDINGS

Of 8256 total deaths in the CRSN demographic surveillance area over the observation period, 6185 (74·9%) were caused by climate-sensitive diseases. Deaths from communicable diseases were most common. Heightened risk of death from all climate-sensitive communicable diseases, and malaria (both across all ages and in children younger than 5 years), was associated with 14-day lagged daily maximum temperatures at or above 41·1°C, the 90th percentile of daily maximum temperatures, compared with 36·4°C, the median (all communicable diseases: 41·9°C relative risk [RR] 1·38 [95% CI 1·08-1·77], 42·8°C 1·57 [1·13-2·18]; malaria all ages: 41·1°C 1·47 [1·05-2·05], 41·9°C 1·78 [1·21-2·61], 42·8°C 2·35 [1·37-4·03]; malaria younger than 5 years: 41·9°C 1·67 [1·02-2·73]). Heightened risk of death from communicable diseases was also associated with 14-day lagged total daily precipitation at or below 0·1 cm, the 49th percentile of total daily precipitation, compared with 1·4 cm, the median (all communicable diseases: 0·0 cm 1·04 [1·02-1·07], 0·1 cm 1·01 [1·006-1·02]; malaria all ages: 0·0 cm 1·04 [1·01-1·08], 0·1 cm 1·02 [1·00-1·03]; malaria younger than 5 years: 0·0 cm 1·05 [1·01-1·10], 0·1 cm 1·02 [1·00-1·04]). The only significant association with a non-communicable disease outcome was a heightened risk of death from climate-sensitive cardiovascular diseases in individuals aged 65 years and older associated with 7-day lagged daily maximum temperatures at or above 41·9°C (41·9°C 2·25 [1·06-4·81], 42·8°C 3·68 [1·46-9·25]). Over 8 cumulative weeks, we found that the risk of death from communicable diseases was heightened at all ages from temperatures at or above 41·1°C (41·1°C 1·23 [1·05-1·43], 41·9°C 1·30 [1·08-1·56], 42·8°C 1·35 [1·09-1·66]) and risk of death from malaria was heightened by precipitation at or above 45·3 cm (all ages: 45·3 cm 1·68 [1·31-2·14], 61·6 cm 1·72 [1·27-2·31], 87·7 cm 1·72 [1·16-2·55]; children younger than 5 years: 45·3 cm 1·81 [1·36-2·41], 61·6 cm 1·82 [1·29-2·56], 87·7 cm 1·93 [1·24-3·00]).

INTERPRETATION

Our results indicate a high burden of death related to extreme weather in the Sahel region of west Africa. This burden is likely to increase with climate change. Climate preparedness programmes-such as extreme weather alerts, passive cooling architecture, and rainwater drainage-should be tested and implemented to prevent deaths from climate-sensitive diseases in vulnerable communities in Burkina Faso and the wider Sahel region.

FUNDING

Deutsche Forschungsgemeinschaft and the Alexander von Humboldt Foundation.

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.

Excess burden of non-communicable disease years of life lost from heat in rural Burkina Faso: a time series analysis of the years 2000-2010

OBJECTIVES

Investigate the association of heat exposure on years of life lost (YLL) from non-communicable diseases (NCD) in Nouna, Burkina Faso, between 2000 and 2010.

DESIGN

Daily time series regression analysis using distributed lag non-linear models, assuming a quasi-Poisson distribution of YLL.

SETTING

Nouna Health and Demographic Surveillance System, Kossi Province, Rural Burkina Faso.

PARTICIPANTS

18 367 NCD-YLL corresponding to 790 NCD deaths recorded in the Nouna Health and Demographic Surveillance Site register over 11 years.

MAIN OUTCOME MEASURE

Excess mean daily NCD-YLL were generated from the relative risk of maximum daily temperature on NCD-YLL, including effects delayed up to 14 days.

RESULTS

Daily average NCD-YLL were 4.6, 2.4 and 2.1 person-years for all ages, men and women, respectively. Moderate 4-day cumulative rise in maximum temperature from 36.4°C (50th percentile) to 41.4°C (90th percentile) resulted in 4.44 (95% CI 0.24 to 12.28) excess daily NCD-YLL for all ages, rising to 7.39 (95% CI 0.32 to 24.62) at extreme temperature (42.8°C; 99th percentile). The strongest health effects manifested on the day of heat exposure (lag 0), where 0.81 (95% CI 0.13 to 1.59) excess mean NCD-YLL occurred daily at 41.7°C compared with 36.4°C, diminishing in statistical significance after 4 days. At lag 0, daily excess mean NCD-YLL were higher for men, 0.58 (95% CI 0.11 to 1.15) compared with women, 0.15 (95% CI -0.25 to 9.63) at 41.7°C vs 36.4°C.

CONCLUSION

Premature death from NCD was elevated significantly with moderate and extreme heat exposure. These findings have important implications for developing adaptation and mitigation strategies to reduce ambient heat exposure and preventive measures for limiting NCD in Africa.

A systematic review and synthesis of the strengths and limitations of measuring malaria mortality through verbal autopsy

Background

Lack of valid and reliable data on malaria deaths continues to be a problem that plagues the global health community. To address this gap, the verbal autopsy (VA) method was developed to ascertain cause of death at the population level. Despite the adoption and wide use of VA, there are many recognized limitations of VA tools and methods, especially for measuring malaria mortality. This study synthesizes the strengths and limitations of existing VA tools and methods for measuring malaria mortality (MM) in low- and middle-income countries through a systematic literature review.

Methods

The authors searched PubMed, Cochrane Library, Popline, WHOLIS, Google Scholar, and INDEPTH Network Health and Demographic Surveillance System sites’ websites from 1 January 1990 to 15 January 2016 for articles and reports on MM measurement through VA. Inclusion criteria: article presented results from a VA study where malaria was a cause of death; article discussed limitations/challenges related to measurement of MM through VA. Two authors independently searched the databases and websites and conducted a synthesis of articles using a standard matrix.

Results

The authors identified 828 publications; 88 were included in the final review. Most publications were VA studies; others were systematic reviews discussing VA tools or methods; editorials or commentaries; and studies using VA data to develop MM estimates. The main limitation were low sensitivity and specificity of VA tools for measuring MM. Other limitations included lack of standardized VA tools and methods, lack of a ‘true’ gold standard to assess accuracy of VA malaria mortality.

Conclusions

Existing VA tools and methods for measuring MM have limitations. Given the need for data to measure progress toward the World Health Organization’s Global Technical Strategy for Malaria 2016–2030 goals, the malaria community should define strategies for improving MM estimates, including exploring whether VA tools and methods could be further improved. Longer term strategies should focus on improving countries’ vital registration systems for more robust and timely cause of death data.

Electronic supplementary material

The online version of this article (doi:10.1186/s12936-017-2071-x) contains supplementary material, which is available to authorized users.

Seasonal variation in child mortality in rural Guinea-Bissau

Objectives

In many African countries, child mortality is higher in the rainy season than in the dry season. We investigated the effect of season on child mortality by time periods, sex and age in rural Guinea‐Bissau.

Methods

Bandim health project follows children under‐five in a health and demographic surveillance system in rural Guinea‐Bissau. We compared the mortality in the rainy season (June to November) between 1990 and 2013 with the mortality in the dry season (December to May) in Cox proportional hazards models providing rainy vs. dry season mortality rate ratios (r/d‐mrr). Seasonal effects were estimated in strata defined by time periods with different frequency of vaccination campaigns, sex and age (<1 month, 1–11 months, 12–59 months). Verbal autopsies were interpreted using InterVa‐4 software.

Results

From 1990 to 2013, overall mortality was declined by almost two‐thirds among 81 292 children (10 588 deaths). Mortality was 51% (95% ci: 45–58%) higher in the rainy season than in the dry season throughout the study period. The seasonal difference increased significantly with age, the r/d‐mrr being 0.94 (0.86–1.03) among neonates, 1.57 (1.46–1.69) in post‐neonatal infants and 1.83 (1.72–1.95) in under‐five children (P for same effect <0.001). According to the InterVa, malaria deaths were the main reason for the seasonal mortality difference, causing 50% of all deaths in the rainy season, but only if the InterVa included season of death, making the argument self‐confirmatory.

Conclusion

The mortality declined throughout the study, yet rainy season continued to be associated with 51% higher overall mortality.

Seasonal and temporal trends in all-cause and malaria mortality in rural Burkina Faso, 1998-2007

BACKGROUND

High mortality levels in sub-Saharan Africa are still a major public health problem. Children are the most affected group with malaria as one of the major causes of death in this region. To plan health interventions, reliable empirical information on cause-specific mortality patterns is essential, yet such data are often not available in developing countries. Health and Demographic Surveillance Systems (HDSS) implementing the verbal autopsy (VA) method provide such data on a longitudinal basis. Physician Coded VA is usually used to determine cause of death, but recently a computerized method, Interpreting VA (InterVA) was alternatively introduced. This study investigates the effect of season on all-cause and malaria mortality analysing cause of death data from 1998 to 2007 obtained by the Nouna HDSS in rural Burkina Faso and derived by InterVA.

METHODS

Monthly mortality rates were calculated for different age groups (infants, children, adolescents, adults, elderly). Seasonal and temporal trends were modelled with parametric Poisson regression adjusted for sex, area of residence and year of death.

RESULTS

Overall, 7,378 deaths occurred corresponding to a mortality rate of 11.9/1,000 with highest rates in infants (56.8/1,000) and children (22.0/1,000). Young children were most affected by malaria. Malaria mortality patterns in children showed significantly higher rates during the rainy season and a stagnant long-term trend. The seasonal trend is well described parametrically with a sinusoidal function. InterVA assigned about half as many deaths to malaria than physicians.

CONCLUSIONS

Malaria mortality remains highly seasonal in rural Burkina Faso. The InterVA method appears to determine reasonably well seasonal mortality patterns, which should be considered for the planning of health resources and activities.

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

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

Childhood cause-specific mortality in rural Western Kenya: application of the InterVA-4 model

Background

Assessing the progress in achieving the United Nation's Millennium Development Goals in terms of population health requires consistent and reliable information on cause-specific mortality, which is often rare in resource-constrained countries. Health and demographic surveillance systems (HDSS) have largely used medical personnel to review and assign likely causes of death based on the information gathered from standardized verbal autopsy (VA) forms. However, this approach is expensive and time consuming, and it may lead to biased results based on the knowledge and experience of individual clinicians. We assessed the cause-specific mortality for children under 5 years old (under-5 deaths) in Siaya County, obtained from a computer-based probabilistic model (InterVA-4).

Design

Successfully completed VA interviews for under-5 deaths conducted between January 2003 and December 2010 in the Kenya Medical Research Institute/US Centers for Disease Control and Prevention HDSS were extracted from the VA database and processed using the InterVA-4 (version 4.02) model for interpretation. Cause-specific mortality fractions were then generated from the causes of death produced by the model.

Results

A total of 84.33% (6,621) childhood deaths had completed VA data during the study period. Children aged 1–4 years constituted 48.53% of all cases, and 42.50% were from infants. A single cause of death was assigned to 89.18% (5,940) of cases, 8.35% (556) of cases were assigned two causes, and 2.10% (140) were assigned ‘indeterminate’ as cause of death by the InterVA-4 model. Overall, malaria (28.20%) was the leading cause of death, followed by acute respiratory infection including pneumonia (25.10%), in under-5 children over the study period. But in the first 5 years of the study period, acute respiratory infection including pneumonia was the main cause of death, followed by malaria. Similar trends were also reported in infants (29 days–11 months) and children aged 1–4 years.

Conclusions

Under-5 cause-specific mortality obtained using the InterVA-4 model is consistent with existing knowledge on the burden of childhood diseases in rural western Kenya.

Disease-specific mortality burdens in a rural Gambian population using verbal autopsy, 1998-2007

Objective

To estimate and evaluate the cause-of-death structure and disease-specific mortality rates in a rural area of The Gambia as determined using the InterVA-4 model.

Design

Deaths and person-years of observation were determined by age group for the population of the Farafenni Health and Demographic Surveillance area from January 1998 to December 2007. Causes of death were determined by verbal autopsy (VA) using the InterVA-4 model and ICD-10 disease classification. Assigned causes of death were classified into six broad groups: infectious and parasitic diseases; cancers; other non-communicable diseases; neonatal; maternal; and external causes. Poisson regression was used to estimate age and disease-specific mortality rates, and likelihood ratio tests were used to determine statistical significance.

Results

A total of 3,203 deaths were recorded and VA administered for 2,275 (71%). All-age mortality declined from 15 per 1,000 person-years in 1998–2001 to 8 per 1,000 person-years in 2005–2007. Children aged 1–4 years registered the most marked (74%) decline from 27 to 7 per 1,000 person-years. Communicable diseases accounted for half (49.9%) of the deaths in all age groups, dominated by acute respiratory infections (ARI) (13.7%), malaria (12.9%) and pulmonary tuberculosis (10.2%). The leading causes of death among infants were ARI (5.59 per 1,000 person-years [95% CI: 4.38–7.15]) and malaria (4.11 per 1,000 person-years [95% CI: 3.09–5.47]). Mortality rates in children aged 1–4 years were 3.06 per 1,000 person-years (95% CI: 2.58–3.63) for malaria, and 1.05 per 1,000 person-years (95% CI: 0.79–1.41) for ARI. The HIV-related mortality rate in this age group was 1.17 per 1,000 person-years (95% CI: 0.89–1.54). Pulmonary tuberculosis and communicable diseases other than malaria, HIV/AIDS and ARI were the main killers of adults aged 15 years and over. Stroke-related mortality increased to become the leading cause of death among the elderly aged 60 years or more in 2005–2007.

Conclusions

Mortality in the Farafenni HDSS area was dominated by communicable diseases. Malaria and ARI were the leading causes of death in the general population. In addition to these, diarrhoeal disease was a particularly important cause of death among children under 5 years of age, as was pulmonary tuberculosis among adults aged 15 years and above.

Trends in non-communicable disease mortality among adult residents in Nairobi's slums, 2003-2011: applying InterVA-4 to verbal autopsy data

BACKGROUND

About 80% of deaths from non-communicable diseases (NCDs) occur in developing countries such as Kenya. However, not much is known about the burden of NCDs in slums, which account for about 60% of the residences of the urban population in Kenya. This study examines trends in NCD mortality from two slum settings in Nairobi.

DESIGN

We use verbal autopsy data on 1954 deaths among adults aged 35 years and older who were registered in the Nairobi Urban Health and Demographic Surveillance System between 2003 and 2011. InterVA-4, a computer-based program, was used to assign causes of death for each case. RESULTS are presented as annualized cause-specific mortality rates (CSMRs) and cause-specific mortality fractions (CSMFs) by sex.

RESULTS

The CSMRs for NCDs did not appear to change significantly over time for both males and females. Among males, cardiovascular diseases (CVDs) and neoplasms were the leading NCDs--contributing CSMFs of 8 and 5%, respectively, on average over time. Among females, CVDs contributed a CSMF of 14% on average over time, while neoplasms contributed 8%. Communicable diseases and related conditions remained the leading causes of death, contributing a CSMF of over 50% on average in males and females over time.

CONCLUSIONS

Our findings are consistent with the Global Burden of Disease 2010 study which shows that communicable diseases remain the dominant cause of death in Africa, although NCDs were still significant contributors to mortality. We recommend an integrated approach towards disease prevention that focuses on health systems strengthening in resource-limited settings such as slums.

The contribution of reduction in malaria as a cause of rapid decline of under-five mortality: evidence from the Rufiji Health and Demographic Surveillance System (HDSS) in rural Tanzania

Background

Under-five mortality has been declining rapidly in a number of sub-Saharan African settings. Malaria-related mortality is known to be a major component of childhood causes of death and malaria remains a major focus of health interventions. The paper explored the contribution of malaria relative to other specific causes of under-five deaths to these trends.

Methods

This paper uses longitudinal demographic surveillance data to examine trends and causes of death of under-five mortality in Rufiji, whose population has been followed for over nine years (1999–2007). Causes of death, determined by the verbal autopsy technique, are analysed with Arriaga’s decomposition method to assess the contribution of declining malaria-related mortality relative to other causes of death as explaining a rapid decline in overall childhood mortality.

Results

Over the 1999–2007 period, under-five mortality rate in Rufiji declined by 54.3%, from 33.3 to 15.2 per 1,000 person-years. If this trend is sustained, Rufiji will be a locality that achieves MDG4 target. Although hypotrophy at birth remained the leading cause of death for neonates, malaria remains as the leading cause of death for post-neonates followed by pneumonia. However, declines in malaria death rates accounted for 49.9% of the observed under-five mortality decline while all perinatal causes accounted for only 19.9%.

Conclusion

To achieve MDG 4 in malaria endemic settings, health programmes should continue efforts to reduce malaria mortality and more efforts are also needed to improve newborn survival.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Does health insurance improve health?: Evidence from a randomized community-based insurance rollout in rural Burkina Faso

From 2004 to 2006, a community-based health insurance (CBI) scheme was rolled out in Nouna District, Burkina Faso, with the objective of improving access to health services and population health. We explore the random timing of the insurance rollout generated by the stepped wedge cluster-randomized design to evaluate the welfare and health impact of the insurance program. Our results suggest that the insurance had limited effects on average out-of-pocket expenditures in the target areas, but substantially reduced the likelihood of catastrophic health expenditure. The introduction of the insurance scheme did not have any effect on health outcomes for children and young adults, but appears to have increased mortality among individuals aged 65 and older. The negative health effects of the program appear to be primarily driven by the adverse provider incentives generated by the scheme and the resulting decline in the quality of care received by patients.

InterVA versus Spectrum: how comparable are they in estimating AIDS mortality patterns in Nairobi's informal settlements?

Background

The Spectrum computer package is used to generate national AIDS mortality estimates in settings where vital registration systems are lacking. Similarly, InterVA-4 (the latest version of the InterVA programme) is used to estimate cause-of-mortality data in countries where cause-specific mortality data are not available.

Objective

This study aims to compare trends in adult AIDS-related mortality estimated by Spectrum with trends from the InterVA-4 programme applied to data from a Health and Demographic Surveillance System (HDSS) in Nairobi, Kenya.

Design

A Spectrum model was generated for the city of Nairobi based on HIV prevalence data for Nairobi and national antiretroviral therapy coverage, underlying mortality, and migration assumptions. We then used data, generated through verbal autopsies, on 1,799 deaths that occurred in the HDSS area from 2003 to 2010 among adults aged 15–59. These data were then entered into InterVA-4 to estimate causes of death using probabilistic modelling. Estimates of AIDS-related mortality rates and all-cause mortality rates from Spectrum and InterVA-4 were compared and presented as annualised trends.

Results

Spectrum estimated that HIV prevalence in Nairobi was 7%, while the HDSS site measured 12% in 2010. Despite this difference, Spectrum estimated higher levels of AIDS-related mortality. Between 2003 and 2010, the proportion of AIDS-related mortality in Nairobi decreased from 63 to 40% according to Spectrum and from 25 to 16% according to InterVA. The net AIDS-related mortality in Spectrum was closer to the combined mortality rates when AIDS and tuberculosis (TB) deaths were included for InterVA-4.

Conclusion

Overall trends in AIDS-related deaths from both methods were similar, although the values were closer when TB deaths were included in InterVA. InterVA-4 might not accurately differentiate between TB and AIDS deaths.

The effect of increased coverage of participatory women's groups on neonatal mortality in Bangladesh: A cluster randomized trial

IMPORTANCE

Community-based interventions can reduce neonatal mortality when health systems are weak. Population coverage of target groups may be an important determinant of their effect on behavior and mortality. A women's group trial at coverage of 1 group per 1414 population in rural Bangladesh showed no effect on neonatal mortality, despite a similar intervention having a significant effect on neonatal and maternal death in comparable settings.

OBJECTIVE

To assess the effect of a participatory women's group intervention with higher population coverage on neonatal mortality in Bangladesh.

DESIGN

A cluster randomized controlled trial in 9 intervention and 9 control clusters.

SETTING

Rural Bangladesh.

PARTICIPANTS

Women permanently residing in 18 unions in 3 districts and accounting for 19 301 births during the final 24 months of the intervention.

INTERVENTIONS

Women's groups at a coverage of 1 per 309 population that proceed through a participatory learning and action cycle in which they prioritize issues that affected maternal and neonatal health and design and implement strategies to address these issues.

MAIN OUTCOMES AND MEASURES

Neonatal mortality rate.

RESULTS

Analysis included 19 301 births during the final 24 months of the intervention. More than one-third of newly pregnant women joined the groups. The neonatal mortality rate was significantly lower in the intervention arm (21.3 neonatal deaths per 1000 live births vs 30.1 per 1000 in control areas), a reduction in neonatal mortality of 38% (risk ratio, 0.62 [95% CI, 0.43-0.89]) when adjusted for socioeconomic factors. The cost-effectiveness was US $220 to $393 per year of life lost averted. Cause-specific mortality rates suggest reduced deaths due to infections and those associated with prematurity/low birth weight. Improvements were seen in hygienic home delivery practices, newborn thermal care, and breastfeeding practices.

CONCLUSIONS AND RELEVANCE

Women's group community mobilization, delivered at adequate population coverage, is a highly cost-effective approach to improve newborn survival and health behavior indicators in rural Bangladesh.

TRIAL REGISTRATION

isrctn.org Identifier: ISRCTN01805825.

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

Background

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

Objective

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

Design

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

Results

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

Conclusions

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