How advanced is the epidemiological transition in Papua New Guinea? New evidence from verbal autopsy. (2nd May 2021)

• Record Type: Journal Article
• Authors: Hart, John D; Kwa, Viola; Dakulala, Paison; Ripa, Paulus; Frank, Dale; Golpak, Victor; Adair, Timothy; Mclaughlin, Deirdre; Riley, Ian D; Lopez, Alan D
• Is Part Of: International journal of epidemiology. Volume 50:Number 6(2021)
• Page Start: 2058
• Page End: 2069
• Publication Date: 2021-05-02
• Subjects: Verbal autopsy -- mortality surveillance -- cause of death -- Papua New Guinea -- global burden of disease; Epidemiology -- Periodicals; 614.4
• DOI: 10.1093/ije/dyab088
• Languages: English
• ISSNs: 0300-5771

Abstract

Abstract: 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.