Search

In late 2021, highly pathogenic avian influenza A(H5N8) clade 2.3.4.4b viruses were detected in domestic ducks in poultry markets in Cambodia. Surveillance, biosafety, and biosecurity efforts should be bolstered along the poultry value chain to limit spread and infection risk at the animal-human interface. [ABSTRACT FROM AUTHOR]

In February 2021, routine sentinel surveillance for influenza-like illness in Cambodia detected a human avian influenza A(H9N2) virus infection. Investigations identified no recent H9N2 virus infections in 43 close contacts. One chicken sample from the infected child's house was positive for H9N2 virus and genetically similar to the human virus. [ABSTRACT FROM AUTHOR]

Active surveillance in high-risk sites in Cambodia has identified multiple low-pathogenicity influenza A(H7) viruses, mainly in ducks. None fall within the A/Anhui/1/2013(H7N9) lineage; however, some A(H7) viruses from 2018 show temporal and phylogenetic similarity to the H7N4 virus that caused a nonfatal infection in Jiangsu Province, China, in December 2017. [ABSTRACT FROM AUTHOR]

Backyard farming with limited biosecurity creates a massive potential for zoonotic spillover. Cambodia, a developing nation in Southeast Asia, is a hub for emerging and endemic infectious diseases. Due to pandemic-induced job losses in the tourism sector, rumors suggest that many former Cambodian tour guides have turned to backyard farming as a source of income and food security. A cross-sectional study including 331 tour guides and 69 poultry farmers in Cambodia before and during the novel coronavirus disease 2019 (COVID-19) pandemic was conducted. Participants were administered a survey to assess food security, income, and general farming practices. Survey data were collected to evaluate the risk perceptions for avian influenza virus (AIV), antimicrobial resistance (AMR), and general biosecurity management implemented on these poultry farms. Overall, food security decreased for 80.1% of the tour guides during the COVID-19 pandemic. Approximately 21% of the tour guides interviewed used backyard poultry farming to supplement losses of income and food insecurity during the COVID-19 pandemic, with a significantly higher risk than for traditional poultry farmers. Agricultural intensification in Cambodia due to the COVID-19 pandemic has caused an influx of makeshift farms with limited biosecurity. Inadequate biosecurity measures in animal farms can facilitate spillover and contribute to future pandemics. Improved biosecurity and robust viral surveillance systems are critical for reducing the risk of spillover from backyard farms. IMPORTANCE While this study highlights COVID-19-associated changes in poultry production at a small scale in Cambodia, poultry production is expected to expand due to an increase in the global demand for poultry protein during the pandemic, changes in urbanization, and the reduction of the global pork supply caused by African swine fever (ASF). The global demand and surge in poultry products, combined with inadequate biosecurity methods, can lead to an increased risk of domestic animal and human spillovers of zoonotic pathogens such as avian influenza. Countries in regions of endemicity are often plagued by complex emergency situations (i.e., food insecurity and economic fallouts) that hinder efforts to effectively address the emergence (or reemergence) of zoonotic diseases. Thus, novel surveillance strategies for endemic and emerging infectious diseases require robust surveillance systems and biosecurity training programs to prevent future global pandemics.

In February 2021, routine sentinel surveillance for influenza-like illness in Cambodia detected a human avian influenza A(H9N2) virus infection. Investigations identified no recent H9N2 virus infections in 43 close contacts. One chicken sample from the infected child's house was positive for H9N2 virus and genetically similar to the human virus.

Background: In Cambodia, malaria transmission is low and most cases occur in forested areas. Sero-epidemiological techniques can be used to identify both areas of ongoing transmission and high-risk groups to be targeted by control interventions. This study utilizes repeated cross-sectional data to assess the risk of being malaria sero-positive at two consecutive time points during the rainy season and investigates who is most likely to sero-convert over the transmission season., Methods: In 2005, two cross-sectional surveys, one in the middle and the other at the end of the malaria transmission season, were carried out in two ecologically distinct regions in Cambodia. Parasitological and serological data were collected in four districts. Antibodies to Plasmodium falciparum Glutamate Rich Protein (GLURP) and Plasmodium vivax Merozoite Surface Protein-1(19) (MSP-1(19)) were detected using Enzyme Linked Immunosorbent Assay (ELISA). The force of infection was estimated using a simple catalytic model fitted using maximum likelihood methods. Risks for sero-converting during the rainy season were analysed using the Classification and Regression Tree (CART) method., Results: A total of 804 individuals participating in both surveys were analysed. The overall parasite prevalence was low (4.6% and 2.0% for P. falciparum and 7.9% and 6.0% for P. vivax in August and November respectively). P. falciparum force of infection was higher in the eastern region and increased between August and November, whilst P. vivax force of infection was higher in the western region and remained similar in both surveys. In the western region, malaria transmission changed very little across the season (for both species). CART analysis for P. falciparum in the east highlighted age, ethnicity, village of residence and forest work as important predictors for malaria exposure during the rainy season. Adults were more likely to increase their antibody responses to P. falciparum during the transmission season than children, whilst members of the Charay ethnic group demonstrated the largest increases., Discussion: In areas of low transmission intensity, such as in Cambodia, the analysis of longitudinal serological data enables a sensitive evaluation of transmission dynamics. Consecutive serological surveys allow an insight into spatio-temporal patterns of malaria transmission. The use of CART enabled multiple interactions to be accounted for simultaneously and permitted risk factors for exposure to be clearly identified.

Aims: To present a new approach for estimating the "true prevalence" of malaria and apply it to datasets from Peru, Vietnam, and Cambodia., Methods: Bayesian models were developed for estimating both the malaria prevalence using different diagnostic tests (microscopy, PCR & ELISA), without the need of a gold standard, and the tests' characteristics. Several sources of information, i.e. data, expert opinions and other sources of knowledge can be integrated into the model. This approach resulting in an optimal and harmonized estimate of malaria infection prevalence, with no conflict between the different sources of information, was tested on data from Peru, Vietnam and Cambodia., Results: Malaria sero-prevalence was relatively low in all sites, with ELISA showing the highest estimates. The sensitivity of microscopy and ELISA were statistically lower in Vietnam than in the other sites. Similarly, the specificities of microscopy, ELISA and PCR were significantly lower in Vietnam than in the other sites. In Vietnam and Peru, microscopy was closer to the "true" estimate than the other 2 tests while as expected ELISA, with its lower specificity, usually overestimated the prevalence., Conclusions: Bayesian methods are useful for analyzing prevalence results when no gold standard diagnostic test is available. Though some results are expected, e.g. PCR more sensitive than microscopy, a standardized and context-independent quantification of the diagnostic tests' characteristics (sensitivity and specificity) and the underlying malaria prevalence may be useful for comparing different sites. Indeed, the use of a single diagnostic technique could strongly bias the prevalence estimation. This limitation can be circumvented by using a Bayesian framework taking into account the imperfect characteristics of the currently available diagnostic tests. As discussed in the paper, this approach may further support global malaria burden estimation initiatives.