RESUMO
The coronavirus disease pandemic has highlighted the utility of pathogen genomics as a key part of comprehensive public health response to emerging infectious diseases threats, however, the ability to generate, analyse, and respond to pathogen genomic data varies around the world. Papua New Guinea (PNG), which has limited in-country capacity for genomics, has experienced significant outbreaks of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) with initial genomics data indicating a large proportion of cases were from lineages that are not well defined within the current nomenclature. Through a partnership between in-country public health agencies and academic organisations, industry, and a public health genomics reference laboratory in Australia a system for routine SARS-CoV-2 genomics from PNG was established. Here we aim to characterise and describe the genomics of PNG's second wave and examine the sudden expansion of a lineage that is not well defined but very prevalent in the Western Pacific region. We generated 1797 sequences from cases in PNG and performed phylogenetic and phylodynamic analyses to examine the outbreak and characterise the circulating lineages and clusters present. Our results reveal the rapid expansion of the B.1.466.2 and related lineages within PNG, from multiple introductions into the country. We also highlight the difficulties that unstable lineage assignment causes when using genomics to assist with rapid cluster definitions.
RESUMO
The COVID-19 pandemic has increased interest and understanding of the utility of pathogen genomics across the Western Pacific region. Access to genomic data enhances surveillance and response to COVID-19, and will also support surveillance of other infectious diseases and antimicrobial resistant pathogens. Models of access can be determined based on intended purpose, use and sustainability. Achieving equitable access to genomics across the Western Pacific will contribute to the development of a regional public health genomics network to respond to major disease threats in the future.
RESUMO
Laboratory-based CD4 monitoring of HIV patients presents challenges in resource limited settings (RLS) including frequent machine breakdown, poor engineering support and limited cold chain and specimen transport logistics. This study assessed the performance of two CD4 tests designed for use in RLS; the Dynal assay and the Alere PIMA test (PIMA). Accuracy of Dynal and PIMA using venous blood was assessed in a centralised laboratory by comparison to BD FACSCount (BD FACS). Dynal had a mean bias of -50.35 cells/µl (r(2) = 0.973, p<0.0001, n = 101) and PIMA -22.43 cells/µl (r(2)= 0.964, p<0.0001, n = 139) compared to BD FACS. Similar results were observed for PIMA operated by clinicians in one urban (n = 117) and two rural clinics (n = 98). Using internal control beads, PIMA precision was 10.34% CV (low bead mean 214.24 cells/µl) and 8.29% (high bead mean 920.73 cells/µl) and similar %CV results were observed external quality assurance (EQA) and replicate patient samples. Dynal did not perform using EQA and no internal controls are supplied by the manufacturer, however duplicate testing of samples resulted in r(2) = 0.961, p<0.0001, mean bias = â-1.44 cells/µl. Using the cut-off of 350 cells/µl compared to BD FACS, PIMA had a sensitivity of 88.85% and specificity of 98.71% and Dynal 88.61% and 100%. A total of 0.44% (2/452) of patient samples were misclassified as "no treat" and 7.30% (33/452) "treat" using PIMA whereas with Dynal 8.91% (9/101) as "treat" and 0% as "no treat". In our setting PIMA was found to be accurate, precise and user-friendly in both laboratory and clinic settings. Dynal performed well in initial centralized laboratory evaluation, however lacks requisite quality control measures, and was technically more difficult to use, making it less suitable for use at lower tiered laboratories.
