The epidemiological transition in Papua New Guinea: new evidence from verbal autopsy studies

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.

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.

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.

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.

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

BACKGROUND

Reliable cause of death (COD) data are not available for the majority of deaths in Papua New Guinea (PNG), despite their critical policy value. Automated verbal autopsy (VA) methods, involving an interview and automated analysis to diagnose causes of community deaths, have recently been trialled in PNG. Here, we report VA results from three sites and highlight the utility of these methods to generate information about the leading CODs in the country.

METHODS

VA methods were introduced in one district in each of three provinces: Alotau in Milne Bay; Tambul-Nebilyer in Western Highlands; and Talasea in West New Britain. VA interviews were conducted using the Population Health Metrics Research Consortium (PHMRC) shortened questionnaire and analysed using the SmartVA automated diagnostic algorithm.

RESULTS

A total of 1655 VAs were collected between June 2018 and November 2019, 87.0% of which related to deaths at age 12 years and over. Our findings suggest a continuing high proportion of deaths due to infectious diseases (27.0%) and a lower proportion of deaths due to non-communicable diseases (NCDs) (50.8%) than estimated by the Global Burden of Disease Study (GBD) 2017: 16.5% infectious diseases and 70.5% NCDs. The proportion of injury deaths was also high compared with GBD: 22.5% versus 13.0%.

CONCLUSIONS

Health policy in PNG needs to address a 'triple burden' of high infectious mortality, rising NCDs and a high fraction of deaths due to injuries. This study demonstrates the potential of automated VA methods to generate timely, reliable and policy-relevant data on COD patterns in hard-to-reach populations in PNG.

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

Introduction

The measurement of progress towards many Sustainable Development Goals (SDG) and other health goals requires accurate and timely all-cause and cause of death (COD) data. However, existing guidance to countries to calculate these indicators is inadequate for populations with incomplete death registration and poor-quality COD data. We introduce a replicable method to estimate national and subnational cause-specific mortality rates (and hence many such indicators) where death registration is incomplete by integrating data from Medical Certificates of Cause of Death (MCCOD) for hospital deaths with routine verbal autopsy (VA) for community deaths.

Methods

The integration method calculates population-level cause-specific mortality fractions (CSMFs) from the CSMFs of MCCODs and VAs weighted by estimated deaths in hospitals and the community. Estimated deaths are calculated by applying the empirical completeness method to incomplete death registration/reporting. The resultant cause-specific mortality rates are used to estimate SDG Indicator 23: mortality between ages 30 and 70 years from cardiovascular diseases, cancers, chronic respiratory diseases and diabetes. We demonstrate the method using nationally representative data in Myanmar, comprising over 42 000 VAs and 7600 MCCODs.

Results

In Myanmar in 2019, 89% of deaths were estimated to occur in the community. VAs comprised an estimated 70% of community deaths. Both the proportion of deaths in the community and CSMFs for the four causes increased with older age. We estimated that the probability of dying from any of the four causes between 30 and 70 years was 0.265 for men and 0.216 for women. This indicator is 50% higher if based on CSMFs from the integration of data sources than on MCCOD data from hospitals.

Conclusion

This integration method facilitates country authorities to use their data to monitor progress with national and subnational health goals, rather than rely on estimates made by external organisations. The method is particularly relevant given the increasing application of routine VA in country Civil Registration and Vital Statistics systems.

Diversity of epidemiological transition in the Pacific: Findings from the application of verbal autopsy in Papua New Guinea and the Solomon Islands

BACKGROUND

Cause of death data are essential for rational health planning yet are not routinely available in Papua New Guinea (PNG) and Solomon Islands. Indirect estimation of cause of death patterns suggests these populations are epidemiologically similar, but such assessments are not based on direct evidence.

METHODS

Verbal autopsy (VA) interviews were conducted at three sites in PNG and nationwide in Solomon Islands. Training courses were also facilitated to improve data from medical certificates of cause of death (MCCODs) in both countries. Data were categorised into broad groups of endemic and emerging conditions to aid assessment of the epidemiological transition.

FINDINGS

Between 2017 and 2020, VAs were collected for 1,814 adult deaths in PNG and 819 adult deaths in Solomon Islands. MCCODs were analysed for 662 deaths in PNG and 1,408 deaths in Solomon Islands. The VA data suggest lower NCD mortality (48.8% versus 70.3%); higher infectious mortality (27.0% versus 18.3%) and higher injury mortality (24.5% versus 11.4%) in PNG compared to Solomon Islands. Higher infectious mortality in PNG was evident for both endemic and emerging infections. Higher NCD mortality in Solomon Islands reflected much higher emerging NCDs (43.6% vs 21.4% in PNG). A similar pattern was evident from the MCCOD data.

INTERPRETATION

The cause of death patterns suggested by VA and MCCOD indicate that PNG is earlier in its epidemiological transition than Solomon Islands, with relatively higher infectious mortality and lower NCD mortality. Injury mortality was also particularly high in PNG.This study was funded by Bloomberg Philanthropies.

Measuring Wasting and Stunting Prevalence Among Children Under 5 Years of Age and Associated Risk Factors in Papua New Guinea: New Evidence From the Comprehensive Health and Epidemiological Surveillance System

Background: Papua New Guinea (PNG) has undergone a significant health transition, with the prevalence of non-communicable diseases increasing. Many children under 5 years of age suffer from the burden of malnutrition. While wasting and stunting still remain high, children who are overweight and obese are reportedly increasing.

Objective: This study reports the prevalence of wasting, stunting, underweight, and overweight children under five in PNG and explores potential household and maternal socioeconomic factors associated with malnutrition.

Method: Data were drawn from the Comprehensive Health and Epidemiological Surveillance System (CHESS) in PNG. Height and weight were directly measured, and wasting, stunting, overweight, and underweight statistics were determined using the 2006 WHO Standard Growth Standards. Household and maternal factors were assessed with parent interviews conducted by trained data collectors. Multivariate logistic regression analyses were conducted to report associations between selected socioeconomic correlates and child malnutrition outcomes.

Result: The prevalence of wasting, stunting, underweight, and overweight children was 13.8, 46.5, 18.2, and 18%, respectively. Children from households with food shortage were more likely to be wasted than those from households without such an experience [OR: 1.43 (95% CI: 0.93–2.21)]. Children from the poor quintile were more likely to be stunted than those from the richest quintile [OR: 1.2 (95% CI: 0.79–1.82)]. Other factors associated with wasting included living in an urban vs. rural area [OR: 1.36 (0.77–2.4)], middle household wealth quintile vs. richest quintile [OR: 0.77 (0.38–1.55)], mothers in union with a man vs. mother unmarried or live in union [OR: 0.76 (0.4–1.42)], and male children vs. female [OR: 0.77 (0.53–1.11)]. Factors associated with stunting included residing in urban vs. rural areas [OR: 1.13 (0.8–1.6)], mother in union vs. single mother [OR: 0.86 (0.59–1.24)], and mothers with preparatory/elementary vs. mothers with vocational/college education [OR: 0.15 (0.02–1.01)].

Conclusion: An integrated approach is needed to comprehensively address the household socioeconomic factors at the household level, contributing to the improvement of child health and development in PNG.

Automated verbal autopsy: from research to routine use in civil registration and vital statistics systems

BACKGROUND

The majority of low- and middle-income countries (LMICs) do not have adequate civil registration and vital statistics (CRVS) systems to properly support health policy formulation. Verbal autopsy (VA), long used in research, can provide useful information on the cause of death (COD) in populations where physicians are not available to complete medical certificates of COD. Here, we report on the application of the SmartVA tool for the collection and analysis of data in several countries as part of routine CRVS activities.

METHODS

Data from VA interviews conducted in 4 of 12 countries supported by the Bloomberg Philanthropies Data for Health (D4H) Initiative, and at different stages of health statistical development, were analysed and assessed for plausibility: Myanmar, Papua New Guinea (PNG), Bangladesh and the Philippines. Analyses by age- and cause-specific mortality fractions were compared to the Global Burden of Disease (GBD) study data by country. VA interviews were analysed using SmartVA-Analyze-automated software that was designed for use in CRVS systems. The method in the Philippines differed from the other sites in that the VA output was used as a decision support tool for health officers.

RESULTS

Country strategies for VA implementation are described in detail. Comparisons between VA data and country GBD estimates by age and cause revealed generally similar patterns and distributions. The main discrepancy was higher infectious disease mortality and lower non-communicable disease mortality at the PNG VA sites, compared to the GBD country models, which critical appraisal suggests may highlight real differences rather than implausible VA results.

CONCLUSION

Automated VA is the only feasible method for generating COD data for many populations. The results of implementation in four countries, reported here under the D4H Initiative, confirm that these methods are acceptable for wide-scale implementation and can produce reliable COD information on community deaths for which little was previously known.

Estimating the pattern of causes of death in Papua New Guinea

Background

Papua New Guinea (PNG) is a diverse country with high mortality and evidence of increased prevalence of non-communicable diseases (NCDs), but there is no reliable cause of death (COD) data because civil registration is insufficient and routine health data comprise only a small proportion of deaths. This study aims to estimate cause-specific mortality fractions (CSMFs) for five broad groups of causes (endemic infections, emerging infections, endemic NCDs, emerging NCDs and injuries), by sex for each of PNG’s provinces.

Methods

CSMFs are calculated as the average of estimates obtained from: (1) Empirical cause method: Utilising available Verbal Autopsy (VA) data and Discharge Health Information System (DHIS) data, and applying statistical models of community versus facility CODs; and (2) Expected cause patterns method: Utilising existing estimates of mortality levels in each province and statistical models of the relationship between all-cause and cause-specific mortality using Global Burden of Disease (GBD) data.

Results

An estimated 41% of male and 49% of female deaths in PNG are due to infectious, maternal (female only), neonatal and nutritional causes. Furthermore, 45% of male and 42% of female deaths arise from NCDs. Infectious diseases, maternal, neonatal and nutritional conditions account for more than half the deaths in a number of provinces, including lower socioeconomic status provinces of Gulf and Sandaun, while provinces with higher CSMFs from emerging NCDs (e.g. ischemic heart disease, stroke) tend to be those where socioeconomic status is comparatively high (e.g. National Capital District, Western Highlands Province, Manus Province, New Ireland Province and East New Britain Province). Provinces with the highest estimated proportion of deaths from emerging infectious diseases are readily accessible by road and have the highest rates of sexually transmitted infections (STIs), while provinces with the highest CSMFs from endemic infectious, maternal, neonatal and nutritional causes are geographically isolated, have high malaria and high all-cause mortality.

Conclusions

Infectious, maternal, neonatal and nutritional causes continue to be an important COD in PNG, and are likely to be higher than what is estimated by the GBD. Nonetheless, there is evidence of the emergence of NCDs in provinces with higher socioeconomic status. The introduction of routine VA for non-facility deaths should improve COD data quality to support health policy and planning to control both infectious and NCDs.

Estimating Adult Mortality in Papua New Guinea, 2011

Background

Mortality in Papua New Guinea (PNG) is poorly measured because routine reporting of deaths is incomplete and inaccurate. This study provides the first estimates in the academic literature of adult mortality (45q15) in PNG by province and sex. These results are compared to a Composite Index of provincial socio-economic factors and health access.

Methods

Adult mortality estimates (45q15) by province and sex were derived using the orphanhood method from data reported in the 2000 and 2011 national censuses. Male adult mortality was adjusted based on the estimated incompleteness of mortality reporting. The Composite Index was developed using the mean of education, economic and health access indicators from various data sources.

Results

Adult mortality for PNG in 2011 was estimated as 269 per 1000 for males and 237 for females. It ranged from 197 in Simbu to 356 in Sandaun province among men, and from 164 in Western Highlands to 326 in Gulf province among women. Provinces with a low Composite Index (Sandaun, Gulf, Enga and Southern Highlands) had comparatively high levels of adult mortality for both sexes, while provinces with a higher Composite Index (National Capital District and Manus) reported lower adult mortality.

Conclusions

Adult mortality in PNG remains high compared with other developing countries. Provincial variations in mortality correlate with the Composite Index. Health and development policy in PNG needs to urgently address the main causes of persistent high premature adult mortality, particularly in less developed provinces.