Continuous Circulation of Chikungunya Virus during COVID-19 Pandemic in Jambi, Sumatra, Indonesia.

Chikungunya fever is a self-limiting viral illness that is caused by the chikungunya virus (CHIKV). CHIKV is found in multiple provinces of Indonesia, with clustered local outbreaks. This case series investigates a local chikungunya outbreak during the COVID-19 pandemic, involving two virologically confirmed chikungunya cases found in Jambi, Sumatra, Indonesia in 2021 and the contact tracing of 65 people from the same neighborhood (one of which was also virologically confirmed with CHIKV). The two original cases were symptomatic with classic signs of chikungunya fever, while the CHIKV-positive neighbor was asymptomatic. Out of the 65 participants, chikungunya IgM was detected in seven (10.8%) people while chikungunya IgG was detected in six (9.2%) using capture ELISA. Dengue IgG was detected by rapid test in three (4.6%) of the participants, showcasing a history of dengue virus (DENV) infection along with the circulation of CHIKV in the area. A phylogenetic analysis demonstrates a close evolutionary relationship between all three 2021 Jambi CHIKV isolates and the 2015-2016 isolates from Jambi. This case series showcases the endemicity and persistent circulation of CHIKV in Jambi, leaving the area vulnerable to eminent outbreaks of chikungunya fever and doubling the burden of disease during the COVID-19 pandemic. Health staff training for case detection and notification, as well as an integrated vector surveillance should continue to be implemented to provide an early warning indicator of possible chikungunya outbreaks.

COVID-profiler: a webserver for the analysis of SARS-CoV-2 sequencing data.

BACKGROUND: SARS-CoV-2 virus sequencing has been applied to track the COVID-19 pandemic spread and assist the development of PCR-based diagnostics, serological assays, and vaccines. With sequencing becoming routine globally, bioinformatic tools are needed to assist in the robust processing of resulting genomic data. RESULTS: We developed a web-based bioinformatic pipeline ("COVID-Profiler") that inputs raw or assembled sequencing data, displays raw alignments for quality control, annotates mutations found and performs phylogenetic analysis. The pipeline software can be applied to other (re-) emerging pathogens. CONCLUSIONS: The webserver is available at http://genomics.lshtm.ac.uk/ . The source code is available at https://github.com/jodyphelan/covid-profiler .

A blood RNA transcriptome signature for COVID-19.

BACKGROUND: COVID-19 is a respiratory viral infection with unique features including a more chronic course and systemic disease manifestations including multiple organ involvement; and there are differences in disease severity between ethnic groups. The immunological basis for disease has not been fully characterised. Analysis of whole-blood RNA expression may provide valuable information on disease pathogenesis. METHODS: We studied 45 patients with confirmed COVID-19 infection within 10 days from onset of illness and a control group of 19 asymptomatic healthy volunteers with no known exposure to COVID-19 in the previous 14 days. Relevant demographic and clinical information was collected and a blood sample was drawn from all participants for whole-blood RNA sequencing. We evaluated differentially-expressed genes in COVID-19 patients (log2 fold change ≥ 1 versus healthy controls; false-discovery rate < 0.05) and associated protein pathways and compared these to published whole-blood signatures for respiratory syncytial virus (RSV) and influenza. We developed a disease score reflecting the overall magnitude of expression of internally-validated genes and assessed the relationship between the disease score and clinical disease parameters. RESULTS: We found 135 differentially-expressed genes in the patients with COVID-19 (median age 35 years; 82% male; 36% Chinese, 53% South Asian ethnicity). Of the 117 induced genes, 14 were found in datasets from RSV and 40 from influenza; 95 genes were unique to COVID-19. Protein pathways were mostly generic responses to viral infections, including apoptosis by P53-associated pathway, but also included some unique pathways such as viral carcinogenesis. There were no major qualitative differences in pathways between ethnic groups. The composite gene-expression score was correlated with the time from onset of symptoms and nasal swab qPCR CT values (both p < 0.01) but was not related to participant age, gender, ethnicity or the presence or absence of chest X-ray abnormalities (all p > 0.05). CONCLUSIONS: The whole-blood transcriptome of COVID-19 has overall similarity with other respiratory infections but there are some unique pathways that merit further exploration to determine clinical relevance. The approach to a disease score may be of value, but needs further validation in a population with a greater range of disease severity.

Assessment of dengue and COVID-19 antibody rapid diagnostic tests cross-reactivity in Indonesia.

BACKGROUND: The coronavirus disease 2019 (COVID-19) pandemic remains ongoing around the world, including in areas where dengue is endemic. Dengue and COVID-19, to some extent, have similar clinical and laboratory features, which can lead to misdiagnosis, delayed treatment and patient's isolation. The use of rapid diagnostic tests (RDT) is easy and convenient for fast diagnosis, however there may be issues with cross-reactivity with antibodies for other pathogens. METHODS: We assessed the possibility of cross-reactivity between SARS-CoV-2 and dengue antibodies by: (1) testing five brands of COVID-19 IgG / IgM RDTs on 60 RT-PCR-confirmed dengue samples; (2) testing 95 RT-PCR-confirmed COVID-19 samples on dengue RDT; and (3) testing samples positive for COVID-19 IgG and/or IgM on dengue RDT. RESULTS: We observed a high specificity across all five brands of COVID-19 RDTs, ranging from 98.3 to 100%. Out of the confirmed COVID-19 samples, one patient tested positive for dengue IgM only, another tested positive for dengue IgG only. One patient tested positive for dengue IgG, IgM, and NS1, suggesting a co-infection. In COVID-19 IgG and/or IgM samples, 6.3% of COVID-19 IgG-positive samples also tested positive for dengue IgG, while 21.1% of COVID-19 IgM-positive samples also tested positive for dengue IgG. CONCLUSION: Despite the high specificity of the COVID-19 RDT, we observed cross-reactions and false-positive results between dengue and COVID-19. Dengue and COVID-19 co-infection was also found. Health practitioners in dengue endemic areas should be careful when using antibody RDT for the diagnosis of dengue during the COVID-19 pandemic to avoid misdiagnosis.

An integrated in silico immuno-genetic analytical platform provides insights into COVID-19 serological and vaccine targets.

During COVID-19, diagnostic serological tools and vaccines have been developed. To inform control activities in a post-vaccine surveillance setting, we have developed an online "immuno-analytics" resource that combines epitope, sequence, protein and SARS-CoV-2 mutation analysis. SARS-CoV-2 spike and nucleocapsid proteins are both vaccine and serological diagnostic targets. Using the tool, the nucleocapsid protein appears to be a sub-optimal target for use in serological platforms. Spike D614G (and nsp12 L314P) mutations were most frequent (> 86%), whilst spike A222V/L18F have recently increased. Also, Orf3a proteins may be a suitable target for serology. The tool can accessed from: http://genomics.lshtm.ac.uk/immuno (online); https://github.com/dan-ward-bio/COVID-immunoanalytics (source code).