Original Article: Decline of notified dengue infections in Indonesia in 2017: Discussion of the possible determinants.

This study was conducted to quantify the trend in dengue notifications in the country in 2017 and to explore the possible determinants. Annual nation-wide dengue notification data were obtained from the National Disease Surveillance of Ministry of Health of Indonesia. Annual incidence rate (IR) and case fatality rate (CFR) in 2017 and the previous years were quantified and compared. Correlations between annual larva free index (LFI), implementation coverage of integrated vector management (IVM), El Niño Southern Oscillation (Niño3.4), Dipole Mode Index (DMI), Zika virus seropositivity and the percent change in IR and CFR of dengue were examined. The change of dengue IR and CFRs were mapped. In 2017, dengue IR was declined by 71% (22.55 per 100,000 population) compared to 2016 (77.96 per 100,000 population) while the CFR was slightly reduced from 0.79% to 0.75%. Reduction in IR and CFR occurred in 94.1% and 70.1% out of 34 provinces, respectively. The trend of dengue IR seems to be influenced by Niño3.4 but there is no clear evidence that Niño3.4 is the main reason for dengue reduction in 2017. It is difficult to elucidate that the reduction of dengue in 2017 was associated with previous Zika outbreaks. In conclusion, there was a significant reduction on dengue notifications in Indonesia in 2017. Further investigation is needed to look at the role of climate on the decline of dengue IR at finer temporal scale. In addition, study on the role of cross-protective immunity generated by Zika infection on dengue incidence is also warranted.

Effects of El Niño Southern Oscillation and Dipole Mode Index on Chikungunya Infection in Indonesia.

The aim of this study was to assess the possible association of El Niño Southern Oscillation (ENSO) and Dipole Mode Index (DMI) on chikungunya incidence overtime, including the significant reduction in cases that was observed in 2017 in Indonesia. Monthly nation-wide chikungunya case reports were obtained from the Indonesian National Disease Surveillance database, and incidence rates (IR) and case fatality rate (CFR) were calculated. Monthly data of Niño3.4 (indicator used to represent the ENSO) and DMI between 2011 and 2017 were also collected. Correlations between monthly IR and CFR and Niño3.4 and DMI were assessed using Spearman's rank correlation. We found that chikungunya case reports declined from 1972 cases in 2016 to 126 cases in 2017, a 92.6% reduction; the IR reduced from 0.67 to 0.05 cases per 100,000 population. No deaths associated with chikungunya have been recorded since its re-emergence in Indonesia in 2001. There was no significant correlation between monthly Niño3.4 and chikungunya incidence with r = -0.142 (95%CI: -0.320-0.046), p = 0.198. However, there was a significant negative correlation between monthly DMI and chikungunya incidence, r = -0.404 (95%CI: -0.229--0.554) with p < 0.001. In conclusion, our initial data suggests that the climate variable, DMI but not Niño3.4, is likely associated with changes in chikungunya incidence. Therefore, further analysis with a higher resolution of data, using the cross-wavelet coherence approach, may provide more robust evidence.

Using dengue epidemics and local weather in Bali, Indonesia to predict imported dengue in Australia.

BACKGROUND: Although the association between dengue in Bali, Indonesia, and imported dengue in Australia has been widely asserted, no study has quantified this association so far. METHODS: Monthly data on dengue and climatic factors over the past decade for Bali and Jakarta as well as monthly data on imported dengue in Australia underwent a three-stage analysis. Stage I: a quasi-Poisson regression with distributed lag non-linear model was used to assess the associations of climatic factors with dengue in Bali. Stage II: a generalized additive model was used to quantify the association of dengue in Bali with imported dengue in Australia with and without including the number of travelers in log scale as an offset. Stage III: the associations of mean temperature and rainfall (two climatic factors identified in stage I) in Bali with imported dengue in Australia were examined using stage I approach. RESULTS: The number of dengue cases in Bali increased with increasing mean temperature, and, up to a certain level, it also increased with increasing rainfall but dropped off for high levels of rainfall. Above a monthly incidence of 1.05 cases per 100,000, dengue in Bali was almost linearly associated with imported dengue in Australia at a lag of one month. Mean temperature (relative risk (RR) per 0.5 °C increase: 2.95, 95% confidence interval (CI): 1.87, 4.66) and rainfall (RR per 7.5 mm increase: 3.42, 95% CI: 1.07, 10.92) in Bali were significantly associated with imported dengue in Australia at a lag of four months. CONCLUSIONS: This study suggests that climatic factors (i.e., mean temperature and rainfall) known to be conducive of dengue transmission in Bali can provide an early warning with 4-month lead time for Australia in order to mitigate future outbreaks of local dengue in Australia. This study also provides a template and framework for future surveillance of travel-related infectious diseases globally.

Chikungunya virus infection in Indonesia: a systematic review and evolutionary analysis.

BACKGROUND: Despite the high number of chikungunya cases in Indonesia in recent years, comprehensive epidemiological data are lacking. The systematic review was undertaken to provide data on incidence, the seroprevalence of anti-Chikungunya virus (CHIKV) IgM and IgG antibodies, mortality, the genotypes of circulating CHIKV and travel-related cases of chikungunya in the country. In addition, a phylogenetic and evolutionary analysis of Indonesian CHIKV was conducted. METHODS: A systematic review was conducted to identify eligible studies from EMBASE, MEDLINE, PubMed and Web of Science as of October 16th 2017. Studies describing the incidence, seroprevalence of IgM and IgG, mortality, genotypes and travel-associated chikungunya were systematically reviewed. The maximum likelihood phylogenetic and evolutionary rate was estimated using Randomized Axelerated Maximum Likelihood (RAxML), and the Bayesian Markov chain Monte Carlo (MCMC) method identified the Time to Most Recent Common Ancestors (TMRCA) of Indonesian CHIKV. The systematic review was registered in the PROSPERO database (CRD42017078205). RESULTS: Chikungunya incidence ranged between 0.16-36.2 cases per 100,000 person-year. Overall, the median seroprevalence of anti-CHIKV IgM antibodies in both outbreak and non-outbreak scenarios was 13.3% (17.7 and 7.3% for outbreak and non-outbreak events, respectively). The median seroprevalence of IgG antibodies in both outbreak and non-outbreak settings was 18.5% (range 0.0-73.1%). There were 130 Indonesian CHIKV sequences available, of which 120 (92.3%) were of the Asian genotype and 10 (7.7%) belonged to the East/Central/South African (ECSA) genotype. The ECSA genotype was first isolated in Indonesia in 2008 and was continually sampled until 2011. All ECSA viruses sampled in Indonesia appear to be closely related to viruses that caused massive outbreaks in Southeast Asia countries during the same period. Massive nationwide chikungunya outbreaks in Indonesia were reported during 2009-2010 with a total of 137,655 cases. Our spatio-temporal, phylogenetic and evolutionary data suggest that these outbreaks were likely associated with the introduction of the ECSA genotype of CHIKV to Indonesia. CONCLUSIONS: Although no deaths have been recorded, the seroprevalence of anti-CHIKV IgM and IgG in the Indonesian population have been relatively high in recent years following re-emergence in early 2001. There is sufficient evidence to suggest that the introduction of ECSA into Indonesia was likely associated with massive chikungunya outbreaks during 2009-2010.

Molecular surveillance of Dengue in Sukabumi, West Java province, Indonesia.

INTRODUCTION: Dengue is endemic and affects people in all Indonesian provinces. Increasing dengue cases have been observed every year in Sukabumi in West Java province. Despite the endemicity, limited data is available on the genetic of dengue viruses (DENV) circulating in the country. To understand the dynamics of dengue disease, we performed molecular and serological surveillance of dengue in Sukabumi. METHODOLOGY: A total of 113 patients were recruited for this study. Serological data were obtained using anti-dengue IgM and IgG tests plus dengue NS1 antigen detection. Dengue detection and serotyping were performed using real-time RT-PCR. Viruses were isolated and the envelope genes were sequenced. Phylogenetic and evolutionary analyses were performed to determine the genotype of the viruses and their evolutionary rates. RESULTS: Real-time RT-PCR detected DENV in 25 (22%) of 113 samples. Serotyping revealed the predominance of DENV-2 (16 isolates, 64%), followed by DENV-1 (5 isolates, 20%), and DENV-4 (4 isolates, 16%). No DENV-3 was detected in the samples. Co-circulation of genotype I and IV of DENV-1 was observed. The DENV-2 isolates all belonged to the Cosmopolitan genotype, while DENV-4 isolates were grouped into genotype II. Overall, their evolutionary rates were similar to DENV from other countries. CONCLUSIONS: We revealed the distribution of DENV serotypes and genotypes in Sukabumi. Compared to data obtained from other cities in Indonesia, we observed the differing predominance of DENV serotypes but similar genotype distribution, where the infecting viruses were closely related with Indonesian endemic viruses isolated previously.