BackgroundReliable data on the distribution of causes of death (COD) in a population are fundamental to good public health practice. In the absence of comprehensive medical certification of deaths, the only feasible way to collect essential mortality data is verbal autopsy (VA). The Tariff Method was developed by the Population Health Metrics Research Consortium (PHMRC) to ascertain COD from VA information. Given its potential for improving information about COD, there is interest in refining the method. We describe the further development of the Tariff Method.MethodsThis study uses data from the PHMRC and the National Health and Medical Research Council (NHMRC) of Australia studies. Gold standard clinical diagnostic criteria for hospital deaths were specified for a target cause list. VAs were collected from families using the PHMRC verbal autopsy instrument including health care experience (HCE). The original Tariff Method (Tariff 1.0) was trained using the validated PHMRC database for which VAs had been collected for deaths with hospital records fulfilling the gold standard criteria (validated VAs). In this study, the performance of Tariff 1.0 was tested using VAs from household surveys (community VAs) collected for the PHMRC and NHMRC studies. We then corrected the model to account for the previous observed biases of the model, and Tariff 2.0 was developed. The performance of Tariff 2.0 was measured at individual and population levels using the validated PHMRC database.ResultsFor median chance-corrected concordance (CCC) and mean cause-specific mortality fraction (CSMF) accuracy, and for each of three modules with and without HCE, Tariff 2.0 performs significantly better than the Tariff 1.0, especially in children and neonates. Improvement in CSMF accuracy with HCE was 2.5 %, 7.4 %, and 14.9 % for adults, children, and neonates, respectively, and for median CCC with HCE it was 6.0 %, 13.5 %, and 21.2 %, respectively. Similar levels of improvement are seen in analyses without HCE.ConclusionsTariff 2.0 addresses the main shortcomings of the application of the Tariff Method to analyze data from VAs in community settings. It provides an estimation of COD from VAs with better performance at the individual and population level than the previous version of this method, and it is publicly available for use.Electronic supplementary materialThe online version of this article (doi:10.1186/s12916-015-0527-9) contains supplementary material, which is available to authorized users.

BackgroundWhen diagnosed by standard light microscopy (LM), malaria prevalence can vary significantly between sites, even at local scale, and mixed species infections are consistently less common than expect in areas co-endemic for Plasmodium falciparum, Plasmodium vivax and Plasmodium malariae. The development of a high-throughput molecular species diagnostic assay now enables routine PCR-based surveillance of malaria infections in large field and intervention studies, and improves resolution of species distribution within and between communities.MethodsThis study reports differences in the prevalence of infections with all four human malarial species and of mixed infections as diagnosed by LM and post-PCR ligase detection reaction – fluorescent microsphere (LDR-FMA) assay in 15 villages in the central Sepik area of Papua New Guinea.ResultsSignificantly higher rates of infection by P. falciparum, P. vivax, P. malariae and Plasmodium ovale were observed in LDR-FMA compared to LM diagnosis (p < 0.001). Increases were particularly pronounced for P. malariae (3.9% vs 13.4%) and P. ovale (0.0% vs 4.8%). In contrast to LM diagnosis, which suggested a significant deficit of mixed species infections, a significant excess of mixed infections over expectation was detected by LDR-FMA (p < 0.001). Age of peak prevalence shifted to older age groups in LDR-FMA diagnosed infections for P. falciparum (LM: 7–9 yrs 47.5%, LDR-FMA: 10–19 yrs 74.2%) and P. vivax (LM: 4–6 yrs 24.2%, LDR-FMA: 7–9 yrs 50.9%) but not P. malariae infections (10–19 yrs, LM: 7.7% LDR-FMA: 21.6%). Significant geographical variation in prevalence was found for all species (except for LM-diagnosed P. falciparum), with the extent of this variation greater in LDR-FMA than LM diagnosed infections (overall, 84.4% vs. 37.6%). Insecticide-treated bednet (ITN) coverage was also the dominant factor linked to geographical differences in Plasmodium species infection prevalence explaining between 60.6% – 74.5% of this variation for LDR-FMA and 81.8% – 90.0% for LM (except P. falciparum), respectively.ConclusionThe present study demonstrates that application of molecular diagnosis reveals patterns of malaria risk that are significantly different from those obtained by standard LM. Results provide insight relevant to design of malaria control and eradication strategies.

Background Recent economic growth in Papua New Guinea (PNG) would suggest that the country may be experiencing an epidemiological transition, characterized by a reduction in infectious diseases and a growing burden from non-communicable diseases (NCDs). However, data on cause-specific mortality in PNG are very sparse, and the extent of the transition within the country is poorly understood. Methods Mortality surveillance was established in four small populations across PNG: West Hiri in Central Province, Asaro Valley in Eastern Highlands Province, Hides in Hela Province and Karkar Island in Madang Province. Verbal autopsies (VAs) were conducted on all deaths identified, and causes of death were assigned by SmartVA and classified into five broad disease categories: endemic NCDs; emerging NCDs; endemic infections; emerging infections; and injuries. Results from previous PNG VA studies, using different VA methods and spanning the years 1970 to 2001, are also presented here. Results A total of 868 deaths among adolescents and adults were identified and assigned a cause of death. NCDs made up the majority of all deaths (40.4%), with the endemic NCD of chronic respiratory disease responsible for the largest proportion of deaths (10.5%), followed by the emerging NCD of diabetes (6.2%). Emerging infectious diseases outnumbered endemic infectious diseases (11.9% versus 9.5%). The distribution of causes of death differed across the four sites, with emerging NCDs and emerging infections highest at the site that is most socioeconomically developed, West Hiri. Comparing the 1970–2001 VA series with the present study suggests a large decrease in endemic infections. Conclusions Our results indicate immediate priorities for health service planning and for strengthening of vital registration systems, to more usefully serve the needs of health priority setting.

Abstractobjectives To conduct an in-depth investigation of the epidemiology of malaria in the Papua New Guinea (PNG) highlands and provide a basis for evidence-based planning and monitoring of intensified malaria control activities.methods Between December 2000 and July 2005, 153 household-based, rapid malaria population surveys were conducted in 112 villages throughout the central PNG highlands. The presence of malaria infections was determined by light microscopy and risk factors assessed using a structured questionnaire.The combined dataset from all individually published surveys was reanalysed.results The prevalence of malaria infections in the different surveys ranged from 0.0% to 41.8% (median 4.3%) in non-epidemic surveys and 6.6% to 63.2% (median 21.2%, P < 0.001) during epidemics. Plasmodium falciparum was the predominant infection below 1400 m and during epidemics, Plasmodium vivax at altitudes >1600 m. Outside epidemics, prevalence decreased significantly with altitude, was reduced in people using bed nets [odds ratio (OR) = 0.8, P < 0.001] but increased in those sleeping in garden houses (OR = 1.34, P < 0.001) and travelling to highly endemic lowlands (OR = 1.80, P < 0.001). Below 1400 m, malaria was a significant source of febrile illness. At higher altitudes, malaria was only a significant source of febrile illness during epidemic outbreaks, but asymptomatic malaria infections were common in non-epidemic times.

Background: Long-lasting insecticidal nets (LLIN), improved diagnosis and artemisinin-based combination therapy (ACT) have reduced malaria prevalence in Papua New Guinea since 2008. Yet, national incidence trends are inconclusive due to confounding effects of the scale-up of rapid diagnostic tests, and inconsistencies in routine reporting. Methods: Malaria trends and their association with LLIN and ACT roll-out between 2010 and 2014 in seven sentinel health facilities were analysed. The analysis included 35,329 fever patients. Intervention effects were estimated using regression models. Results: Malaria incidence initially ranged from 20 to 115/1000 population; subsequent trends varied by site. Overall, LLIN distributions had a cumulative effect, reducing the number of malaria cases with each round (incidence rate ratio ranging from 0.12 to 0.53 in five sites). No significant reduction was associated with ACT introduction. Plasmodium falciparum remained the dominant parasite in all sentinel health facilities. Resurgence occurred in one site in which a shift to early and outdoor biting of anophelines had previously been documented. Conclusions: LLINs, but not ACT, were associated with reductions of malaria cases in a range of settings, but sustainability of the gains appear to depend on local factors. Malaria programmes covering diverse transmission settings such as Papua New Guinea must consider local heterogeneity when choosing interventions and ensure continuous monitoring of trends.