Background Transmission within families and multiple spike protein mutations have been associated with the rapid transmission of SARS-CoV-2. We aimed to: (1) describe full genome characterization of SARS-CoV-2 and correlate the sequences with epidemiological data within family clusters, and (2) conduct phylogenetic analysis of all samples from Yogyakarta and Central Java, Indonesia and other countries. Methods The study involved 17 patients with COVID-19, including two family clusters. We determined the full-genome sequences of SARS-CoV-2 using the Illumina MiSeq next-generation sequencer. Phylogenetic analysis was performed using a dataset of 142 full-genomes of SARS-CoV-2 from different regions. Results Ninety-four SNPs were detected throughout the open reading frame (ORF) of SARS-CoV-2 samples with 58% (54/94) of the nucleic acid changes resulting in amino acid mutations. About 94% (16/17) of the virus samples showed D614G on spike protein and 56% of these (9/16) showed other various amino acid mutations on this protein, including L5F, V83L, V213A, W258R, Q677H, and N811I. The virus samples from family cluster-1 (n = 3) belong to the same clade GH, in which two were collected from deceased patients, and the other from the survived patient. All samples from this family cluster revealed a combination of spike protein mutations of D614G and V213A. Virus samples from family cluster-2 (n = 3) also belonged to the clade GH and showed other spike protein mutations of L5F alongside the D614G mutation. Conclusions Our study is the first comprehensive report associating the full-genome sequences of SARS-CoV-2 with the epidemiological data within family clusters. Phylogenetic analysis revealed that the three viruses from family cluster-1 formed a monophyletic group, whereas viruses from family cluster-2 formed a polyphyletic group indicating there is the possibility of different sources of infection. This study highlights how the same spike protein mutations among members of the same family might show different disease outcomes.

Background and Aim: A previous study divided Indonesian bovine viral diarrhea virus (BVDV)-1 into subgenotypes BVDV-1a to BVDV-1d based on the partial NS5B gene using strain Bega as reference for BVDV-1a. In fact, it is clustered into BVDV-1c with strain Bega-like Australia. BVDV genotyping has been done on isolates from Jakarta, West and Central Java, but East Java isolates have not been genotyped. This study aimed to analyze genetic variability and amino acid residues in the nucleotide-binding pocket of the NS5B gene from infected cattle. Materials and Methods: Samples were obtained from the Sera Bank originating from active and passive surveillance of cattle that had been tested for BVDV antigen from 2013 to 2017. Detection of the p80 antibody and BVDV genotyping was carried out using ELISA and nested-multiplex-polymerase chain reaction (PCR), respectively. We defined 15 nested PCR products for partial sequencing of NS5B. Those field samples were selected from each location and year using proportional calculation as a representative sample. Homological and phylogenetic analyses of the partial NS5B gene were performed using BLAST and MEGA version 6. Results: Based on the phylogenetic tree analysis using 360 nucleotides as the partial NS5B gene, Indonesian BVDV-1 isolates from Central and East Java were subdivided to BVDV-1a (n=9), BVDV-1b (n=1), and BVDV-1c (n=5). In the present study, the homology of BVDV subgenotype -1a, -1b, and -1c was compared to the BVDV GenBank data and found 90-93%, 93%, and 92-95% respectively with the average pairwise distance of 0.207. A point mutation was shown at R283K of all BVDV isolates based on the sequence of three amino acid residues R283, R285, and I287 in the nucleotide-binding pocket as a part of the encoded RNA-dependent RNA polymerase. Conclusion: This study revealed the genetic variability of BVDV infecting cattle in Central Java and East Java, Indonesia, the subtypes BVDV-1a, BVDV-1b, BVDV-1c, and a point mutation at the R283K residue.

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In July 2016, an avian influenza outbreak in duck farms in Yogyakarta province was reported to Disease Investigation Center (DIC), Wates, Indonesia, with approximately 1,000 ducks died or culled. In this study, two avian influenza (AI) virus subtypes, A/duck/Bantul/04161291‐OR/2016 (H5N1) and A/duck/Bantul/04161291‐OP/2016 (H9N2) isolated from ducks in the same farm during an AI outbreak in Bantul district, Yogyakarta province, were sequenced and characterized. Our results showed that H5N1 virus was closely related to the highly pathogenic AI (HPAI) H5N1 of clade 2.3.2.1c, while the H9N2 virus was clustered with LPAI viruses from China, Vietnam and Indonesia H9N2 (CVI lineage). Genetic analysis revealed virulence characteristics for both in avian and in mammalian species. In summary, co‐circulation of HPAI‐H5N1 of clade 2.3.2.1c and LPAI‐H9N2 was identified in a duck farm during an AI outbreak in Yogyakarta province, Indonesia. Our findings raise a concern of the potential risk of the viruses, which could increase viral transmission and/or threat to human health. Routine surveillance of avian influenza viruses should be continuously conducted to understand the dynamic and diversity of the viruses for influenza prevention and control in Indonesia and SEA region.

The outbreak of highly pathogenic H5N1 avian influenza, with its international spread, confirmed that emerging infectious disease control must be underpinned by effective laboratory services. Laboratory results are the essential data underpinning effective surveillance, case diagnosis, or monitoring of responses. Importantly, laboratories are best managed within national and international networks of technological support rather than in isolation. A well planned laboratory network can deliver both a geographical spread of testing capacity and also a cost effective hierarchy of capability. Hence in the international context regional networks can be particularly effective. Laboratories are an integral part of a country's veterinary services and their role and function should be clearly defined in the national animal health strategy and supporting government policies. Not every laboratory should be expected to deliver every possible service, and integration into regional and broader international networks should be a part of the overall strategy. The outputs required of each laboratory should be defined and then ensured through accredited quality assurance. The political and scientific environment in which laboratories operate changes continuously, not only through evolving national and regional animal health priorities but also through new test technologies and enhancements to existing technologies. Active networks help individual laboratories to monitor, evaluate, and respond to such challenges and opportunities. The end result is enhanced emerging infectious disease preparedness across the region.