Spatial and Temporal Patterns of Ross River Virus in Queensland, 2001-2020

Arbovirus Transmission in Australia from 2002 to 2017

Arboviruses pose a significant global public health threat, with Ross River virus (RRV), Barmah Forest virus (BFV), and dengue virus (DENV) being among the most common and clinically significant in Australia. Some arboviruses, including those prevalent in Australia, have been reported to cause transfusion-transmitted infections. This study examined the spatiotemporal variation of these arboviruses and their potential impact on blood donation numbers across Australia. Using data from the Australian Department of Health on eight arboviruses from 2002 to 2017, we retrospectively assessed the distribution and clustering of incidence rates in space and time using Geographic Information System mapping and space-time scan statistics. Regression models were used to investigate how weather variables, their lag months, space, and time affect case and blood donation counts. The predictors' importance varied with the spatial scale of analysis. Key predictors were average rainfall, minimum temperature, daily temperature variation, and relative humidity. Blood donation number was significantly associated with the incidence rate of all viruses and its interaction with local transmission of DENV, overall. This study, the first to cover eight clinically relevant arboviruses at a fine geographical level in Australia, identifies regions at risk for transmission and provides valuable insights for public health intervention.

Prediction of Ross River Virus Incidence Using Mosquito Data in Three Cities of Queensland, Australia

Ross River virus (RRV) is the most common mosquito-borne disease in Australia, with Queensland recording high incidence rates (with an annual average incidence rate of 0.05% over the last 20 years). Accurate prediction of RRV incidence is critical for disease management and control. Many factors, including mosquito abundance, climate, weather, geographical factors, and socio-economic indices, can influence the RRV transmission cycle and thus have potential utility as predictors of RRV incidence. We collected mosquito data from the city councils of Brisbane, Redlands, and Mackay in Queensland, together with other meteorological and geographical data. Predictors were selected to build negative binomial generalised linear models for prediction. The models demonstrated excellent performance in Brisbane and Redlands but were less satisfactory in Mackay. Mosquito abundance was selected in the Brisbane model and can improve the predictive performance. Sufficient sample sizes of continuous mosquito data and RRV cases were essential for accurate and effective prediction, highlighting the importance of routine vector surveillance for disease management and control. Our results are consistent with variation in transmission cycles across different cities, and our study demonstrates the usefulness of mosquito surveillance data for predicting RRV incidence within small geographical areas.

Latest Advances in Arbovirus Diagnostics

Arboviruses are a diverse family of vector-borne pathogens that include members of the Flaviviridae, Togaviridae, Phenuviridae, Peribunyaviridae, Reoviridae, Asfarviridae, Rhabdoviridae, Orthomyxoviridae and Poxviridae families. It is thought that new world arboviruses such as yellow fever virus emerged in the 16th century due to the slave trade from Africa to America. Severe disease-causing viruses in humans include Japanese encephalitis virus (JEV), yellow fever virus (YFV), dengue virus (DENV), West Nile virus (WNV), Zika virus (ZIKV), Crimean-Congo hemorrhagic fever virus (CCHFV), severe fever with thrombocytopenia syndrome virus (SFTSV) and Rift Valley fever virus (RVFV). Numerous methods have been developed to detect the presence of these pathogens in clinical samples, including enzyme-linked immunosorbent assays (ELISAs), lateral flow assays (LFAs) and reverse transcriptase-polymerase chain reaction (RT-PCR). Most of these assays are performed in centralized laboratories due to the need for specialized equipment, such as PCR thermal cyclers and dedicated infrastructure. More recently, molecular methods have been developed which can be performed at a constant temperature, termed isothermal amplification, negating the need for expensive thermal cycling equipment. In most cases, isothermal amplification can now be carried out in as little as 5-20 min. These methods can potentially be used as inexpensive point of care (POC) tests and in-field deployable applications, thus decentralizing the molecular diagnosis of arboviral disease. This review focuses on the latest developments in isothermal amplification technology and detection techniques that have been applied to arboviral diagnostics and highlights future applications of these new technologies.

Prediction of Ross River virus incidence in Queensland, Australia: building and comparing models

Transmission of Ross River virus (RRV) is influenced by climatic, environmental, and socio-economic factors. Accurate and robust predictions based on these factors are necessary for disease prevention and control. However, the complicated transmission cycle and the characteristics of RRV notification data present challenges. Studies to compare model performance are lacking. In this study, we used RRV notification data and exposure data from 2001 to 2020 in Queensland, Australia, and compared ten models (including generalised linear models, zero-inflated models, and generalised additive models) to predict RRV incidence in different regions of Queensland. We aimed to compare model performance and to evaluate the effect of statistical over-dispersion and zero-inflation of RRV surveillance data, and non-linearity of predictors on model fit. A variable selection strategy for screening important predictors was developed and was found to be efficient and able to generate consistent and reasonable numbers of predictors across regions and in all training sets. Negative binomial models generally exhibited better model fit than Poisson models, suggesting that over-dispersion in the data is the primary factor driving model fit compared to non-linearity of predictors and excess zeros. All models predicted the peak periods well but were unable to fit and predict the magnitude of peaks, especially when there were high numbers of cases. Adding new variables including historical RRV cases and mosquito abundance may improve model performance. The standard negative binomial generalised linear model is stable, simple, and effective in prediction, and is thus considered the best choice among all models.

N-Linked Glycans Shape Skin Immune Responses during Arthritis and Myositis after Intradermal Infection with Ross River Virus

Arthritogenic alphaviruses are mosquito-borne arboviruses that include several re-emerging human pathogens, including the chikungunya (CHIKV), Ross River (RRV), Mayaro (MAYV), and o'nyong-nyong (ONNV) virus. Arboviruses are transmitted via a mosquito bite to the skin. Herein, we describe intradermal RRV infection in a mouse model that replicates the arthritis and myositis seen in humans with Ross River virus disease (RRVD). We show that skin infection with RRV results in the recruitment of inflammatory monocytes and neutrophils, which together with dendritic cells migrate to draining lymph nodes (LN) of the skin. Neutrophils and monocytes are productively infected and traffic virus from the skin to LN. We show that viral envelope N-linked glycosylation is a key determinant of skin immune responses and disease severity. RRV grown in mammalian cells elicited robust early antiviral responses in the skin, while RRV grown in mosquito cells stimulated poorer early antiviral responses. We used glycan mass spectrometry to characterize the glycan profile of mosquito and mammalian cell-derived RRV, showing deglycosylation of the RRV E2 glycoprotein is associated with curtailed skin immune responses and reduced disease following intradermal infection. Altogether, our findings demonstrate skin infection with an arthritogenic alphavirus leads to musculoskeletal disease and envelope glycoprotein glycosylation shapes disease outcome. IMPORTANCE Arthritogenic alphaviruses are transmitted via mosquito bites through the skin, potentially causing debilitating diseases. Our understanding of how viral infection starts in the skin and how virus systemically disseminates to cause disease remains limited. Intradermal arbovirus infection described herein results in musculoskeletal pathology, which is dependent on viral envelope N-linked glycosylation. As such, intradermal infection route provides new insights into how arboviruses cause disease and could be extended to future investigations of skin immune responses following infection with other re-emerging arboviruses.