Influenza Cases From Surveillance Acute Respiratory Infection in Indonesia, 2011

Background: Severe Acute Respiratory Infection (SARI) or pneumonia has a major contribution in the morbidity and mortality, however, Indonesia still has lack of its epidemiology. The aim of the study is to know the epidemiological pattern of influenza virus as the etiology of SARI cases. Methods:This analysis based on the sentinel surveillanceSARI conducted by Center for Biomedical and Basic Technology of Health (CBBTH) of Indonesia carried out at nine hospitals in nine provinces in 2011.Every patient who met the criteria of SARI was included in this study. Serum, throat and nasal swabs were taken and examined at the Virology laboratory CBBTH to determine the etiology. RT-PCR was used to detect type and subtype of influenza viruses from swabs.Results: Total number of SARI cases were 333. We found 6% cases were influenza positive by RT-PCR. The proportion of influenza A was 5% and influenza B 1% from total SARI cases. We detected that seasonal influenza A subtype H1N1pdm09was the dominant subtypes that circulating in Indonesia.Conclusion: We foundseasonal Influenza infection from SARI patients, however, it was only small number. Therefore, further detection of SARI cases is needed. (Health Science Indones 2014;1:7-11

Deteksi Resistensi Oseltamivir Influenza a (H1N1pdm09) Dari Pasien Infeksi Saluran Pernafasan Akut Berat Di Indonesia Tahun 2014

Influenza viruses are classified into subtypes based on two surface antigens known as hemagglutinin (HA) and neuraminidase (NA). Antigenic changes of influenza virus can cause resistance to antiviral drugs which is already limited in variation. Resistance to the drugs used recently are due to antigenic drift by point mutation in a single amino acid at position 275 (H275Y). The purpose of this research is to identify the presence of influenza virus A (H1N1pdm09) that were resistant to oseltamivir from cases of severe acute respiratory infection (SARI)in Indonesia in 2014 by using a rapid detection test. Detection of oseltamivir resistance in NA gene is to identify the single nucleotide polimorphism (SNP) at position 275 (H275Y) using the real-time RT-PCR method from clinical specimens SARI case. A total of 870 specimens from six sentinel hospitals were collected and 15 of them positive H1N1pdm09. Of the 15 clinical specimens, H1N1pdm09 virus strains that have mutations H275Y were not found. Based on this finding, it can be concluded that during the year 2014, there is no influenza virus A (H1N1pdm09) resistant to oseltamivir from SARI cases specimen in six sentinel hospitals in Indonesia

The state of health in Indonesia's provinces, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019

Background Analysing trends and levels of the burden of disease at the national level can mask inequalities in health-related progress in lower administrative units such as provinces and districts. We used results from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 to analyse health patterns in Indonesia at the provincial level between 1990 and 2019. Long-term analyses of disease burden provide insights on Indonesia's advance to universal health coverage and its ability to meet the United Nations Sustainable Development Goals by 2030. Methods We analysed GBD 2019 estimated cause-specific mortality, years of life lost (YLLs), years lived with disability (YLDs), disability-adjusted life-years (DALYs), life expectancy at birth, healthy life expectancy, and risk factors for 286 causes of death, 369 causes of non-fatal health loss, and 87 risk factors by year, age, and sex for Indonesia and its 34 provinces from 1990 to 2019. To generate estimates for Indonesia at the national level, we used 138 location-years of data to estimate Indonesia-specific demographic indicators, 317 location-years of data for Indonesia-specific causes of death, 689 location-years of data for Indonesia-specific non-fatal outcomes, 250 location-years of data for Indonesia-specific risk factors, and 1641 location-years of data for Indonesia-specific covariates. For subnational estimates, we used the following source counts: 138 location-years of data to estimate Indonesia-specific demographic indicators; 5848 location-years of data for Indonesia-specific causes of death; 1534 location-years of data for Indonesia-specific non-fatal outcomes; 650 location-years of data for Indonesia-specific risk factors; and 16 016 location-years of data for Indonesia-specific covariates. We generated our GBD 2019 estimates for Indonesia by including 1 915 207 total source metadata rows, and we used 821 total citations. Findings Life expectancy for males across Indonesia increased from 62·5 years (95% uncertainty interval 61·3–63·7) to 69·4 years (67·2–71·6) between 1990 and 2019, a positive change of 6·9 years. For females during the same period, life expectancy increased from 65·7 years (64·5–66·8) to 73·5 years (71·6–75·6), an increase of 7·8 years. There were large disparities in health outcomes among provinces. In 2019, Bali had the highest life expectancy at birth for males (74·4 years, 70·90–77·9) and North Kalimantan had the highest life expectancy at birth for females (77·7 years, 74·7–81·2), whereas Papua had the lowest life expectancy at birth for males (64·5 years, 60·9–68·2) and North Maluku had the lowest life expectancy at birth for females (64·0 years, 60·7–67·3). The difference in life expectancy for males between the highest-ranked and lowest-ranked provinces was 9·9 years and the difference in life expectacy for females between the highest-ranked and lowest-ranked provinces was 13·7 years. Age-standardised death, YLL, and YLD rates also varied widely among the provinces in 2019. High systolic blood pressure, tobacco, dietary risks, high fasting plasma glucose, and high BMI were the five leading risks contributing to health loss measured as DALYs in 2019. Interpretation Our findings highlight that Indonesia faces a double burden of communicable and non-communicable diseases that varies across provinces. From 1990 to 2019, Indonesia witnessed a decline in the infectious disease burden, although communicable diseases such as tuberculosis, diarrhoeal diseases, and lower respiratory infections have remained a main source of DALYs in Indonesia. During that same period, however, all-ages death and disability rates from non-communicable diseases and exposure to their risk factors accounted for larger shares of health loss. The differences in health outcomes between the highest-performing and lowest-performing provinces have also widened since 1990. Our findings support a comprehensive process to revisit current health policies, examine the root causes of variation in the burden of disease among provinces, and strengthen programmes and policies aimed at reducing disparities across the country. Funding The Bill & Melinda Gates Foundation and the Government of Indonesia. Translation For the Bahasa Indonesia translation of the abstract see Supplementary Materials section

Interaction of Kaposi's Sarcoma-Associated Herpesvirus ORF59 with oriLyt Is Dependent on Binding with K-Rta ▿

Kaposi's sarcoma-associated herpesvirus (KSHV)/human herpesvirus 8 (HHV-8) displays two distinct life stages, latency and lytic reactivation. Progression through the lytic cycle and replication of the viral genome constitute an essential step toward the production of infectious virus and human disease. KSHV K-RTA has been shown to be the major transactivator required for the initiation of lytic reactivation. In the transient-cotransfection replication assay, K-Rta is the only noncore protein required for DNA synthesis. K-Rta was shown to interact with both C/EBPα binding motifs and the R response elements (RRE) within oriLyt. It is postulated that K-Rta acts in part to facilitate the recruitment of replication factors to oriLyt. In order to define the role of K-Rta in the initiation of lytic DNA synthesis, we show an interaction with ORF59, the DNA polymerase processivity factor (PF), one of the eight virally encoded proteins necessary for origin-dependent DNA replication. Using the chromatin immunoprecipitation (ChIP) assay, both K-Rta and ORF59 interact with the RRE and C/EBPα binding motifs within oriLyt in cells harboring the KSHV bacterial artificial chromosome (BAC). A transient-transfection ChIP assay demonstrated that the interaction of ORF59 with oriLyt is dependent on binding with K-Rta and that ORF59 fails to bind to oriLyt in the absence of K-Rta. Also, using the cotransfection replication assay, overexpression of the interaction domain of K-Rta with ORF59 has a dominant negative effect on oriLyt amplification, suggesting that the interaction of K-Rta with ORF59 is essential for DNA synthesis and supporting the hypothesis that K-Rta facilitates the formation of a replication complex at oriLyt