H5N1 highly pathogenic avian influenza in Indonesia: retrospective considerations.

Indonesia is one of the five countries where highly pathogenic avian influenza viruses of the H5N1 subtype (H5N1 HPAI) remain endemic in poultry. Importantly, it is one of the countries where the virus causes human infections. WHO data indicate that as of 2 May 2012, 189 human cases of Influenza A (H5N1) had been reported in Indonesia, with 157 human deaths. These human cases included a small number in which limited human-to-human transmission could have occurred. Hence, there remains a critical need in Indonesia for a more effective One Health approach to the control and prevention of this disease in people and in poultry. This chapter explores a number of aspects of the evolution of this disease in Indonesia, the virus that causes it and the control and preventive measures introduced, focusing on the successes and shortcomings of veterinary and One Health approaches. Indonesia provides many examples of situations where this latter approach has been successful, and others where further work is needed to maximize the benefits from coordinated responses to this disease leading to effective management of the risk to human health.

Contact rate and risk factors of classical swine fever disease in commercial and smallholder pig farms, Karanganyar, Central Java, Indonesia.

BACKGROUND AND AIM: Classical swine fever (CSF) is one of the primary diseases in animals in Indonesia, particularly areas that supply pig meat to the country, such as Karanganyar district, Central Java. The government has tried to prevent and control the disease by vaccination, but it has not yet given effective results. Therefore, another attempt to prevent the recurrence of CSF cases is to apply biosecurity in pig farms by looking for risk factors associated with on-farm and off-farm contact. This study aims to determine the contact rate and investigate the risk factors associated with on-farm and off-farm contact in commercial and smallholder pig farms in Karanganyar, Central Java, Indonesia, in the context of controlling CSF disease. MATERIALS AND METHODS: This study used a cross-sectional study design in which the pig farm was designed as the observed epidemiological unit. The contact structure data were conducted by sampling using a two-stage random method. We selected Karanganyar district because it is the center of a pig farm in the Central Java Province and has many CSF cases in several years before. The study was conducted for more or less 1 month from August to September 2019. The contact data were collected from 37 smallholder farms and 27 commercial farms within interviews. Risk factors for contact with pigs were analyzed using logistic regression using theStatistix Program version 8.0.(www.statistix.com). RESULTS: In comparison to smallholder farms, commercial farms had 2.38 and 3.32 times higher contact rate in outside farms and inside farms, respectively. Two factors increased the risk for on-farm contacts including commercials type farm (p=0.0012; odds ratio [OR]=8.32) with contact rate of 1.24 times/day and the time interval of CSF vaccination for 1-3 months (p=0.0013; OR=8.43) with contact rate of 0.98 times/day, and three factors increased the risk for off-farm contacts including the commercial farm type (p=0.012; OR=4.88) with 1.50 contact/day, the time interval of CSF vaccination for 1-3 months (p=0.036; OR=3.83) with 1.30 contact/day, and farmers with experience in pig husbandry <5 years (p=0.075; OR=3.56) with 1.13 contact/day. CONCLUSION: This study shows that commercial farms and short CSF vaccination intervals increased the risk of either off-farm or on-farm contacts. The contact structure of pig farms in Karanganyar district is similar to that in other areas in Indonesia. Reducing the risk of contacts either outside or inside the pig farms is essential to prevent disease transmission. Enhancing communication and education to pig farmers and surveillance is also necessary to prevent such diseases in pigs.

Co-circulation and characterization of HPAI-H5N1 and LPAI-H9N2 recovered from a duck farm, Yogyakarta, Indonesia.

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.

Development of veterinary laboratory networks for avian influenza and other emerging infectious disease control: the southeast asian experience.

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.

Metapopulation dynamics and determinants of H5N1 highly pathogenic avian influenza outbreaks in Indonesian poultry.

In 2008, the Indonesian Government implemented a revised village-level Participatory Disease Surveillance and Response (PDSR) program to gain a better understanding of both the magnitude and spatial distribution of H5N1 highly pathogenic avian influenza (HPAI) outbreaks in backyard poultry. To date, there has been considerable collection of data, but limited publically available analysis. This study utilizes data collected by the PDSR program between April 2008 and September 2010 for Java, Bali and the Lampung Province of Sumatra. The analysis employs hierarchical Bayesian occurrence models to quantify spatial and temporal dynamics in backyard HPAI infection reports at the District level in 90 day time periods, and relates the probability of HPAI occurrence to PDSR-reported village HPAI infection status and human and poultry density. The probability of infection in a District was assumed to be dependent on the status of the District in the previous 90 day time period, and described by either a colonization probability (the probability of HPAI infection in a District given there had not been infection in the previous 90 day time period) or a persistence probability (the probability of HPAI infection being maintained in the District from the previous to current 90 day period). Results suggest that the number of surveillance activities in a district had little relationship to outbreak occurrence probabilities, but human and poultry densities were found to have non-linear relationships to outbreak occurrence probabilities. We found significant spatial dependency among neighboring districts, indicating that there are latent spatial processes that are not captured by the covariates available for this study, but which nonetheless impact outbreak dynamics. The results of this work may help improve understanding of the seasonal nature of H5N1 in poultry and the potential role of poultry density in enabling endemicity to occur, as well as to assist the Government of Indonesia target scarce resources to regions and time periods when outbreaks of HPAI in poultry are most likely to occur.