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      Harnessing artificial intelligence to enhance key surveillance and response measures for arbovirus disease outbreaks: the exemplar of Australia

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          1. Contributions to the field statement Arboviruses present a significant public health risk to the Australian population. Both the many indigenous arboviruses and imported cases of major global pathogens contribute to this burden. Effective surveillance measures, which involve monitoring for mosquitoes responsible for transmission, the signs and symptoms of disease in humans, and a range of environmental and climactic factors, are essential to detect and respond early to local outbreaks. This is particularly crucial in regional Australia, a vast area that is underserved but is now becoming a focal point for economic and social development. As this transformation progresses, there will be increased human interaction with native reservoir animal hosts and vector mosquitoes, creating a potential scenario for a higher prevalence of neglected indigenous arbovirus infections. Additionally, the impact of climate change in the tropical north of the country is predicted to lead to a population boom of arbovirus-transmitting mosquitoes, further exacerbating the situation. Hence, it is imperative to maintain diligent attention to vector monitoring and control efforts. Integrating artificial intelligence to rapidly process large volumes of data should enhance surveillance by improving data analysis, prediction, and decision-making. More accurate and quicker detection of arboviral disease outbreaks will enable proactive and effective public health responses. 2. Introduction: the public health problem Viruses that are transmitted between vertebrate hosts by biting, blood-feeding arthropods (primarily mosquitoes and ticks) are called arthropod-borne viruses or, for short, arboviruses. The transmission of arboviruses to humans poses a significant and accelerating global public health risk (Madewell, 2020). It is estimated that 3.9 billion people, approaching half of the world's population is at risk (World Health Organization, 2022), leading to hundreds of millions of symptomatic infections, a disease burden of tens of thousands of deaths and up to 5 million disability-adjusted life years lost annually (Labeaud et al., 2011). Notable examples of pathogens include dengue (DENV), chikungunya, yellow fever, Japanese encephalitis (JEV), West Nile, Zika and Mayaro viruses. For several of these, humans serve as the primary reservoir host, with many causing pandemics over the last few decades (Mayer et al., 2017). Mild infection is typically associated with influenza-like symptoms such as fever, headache, muscle or joint pain, and/or a skin rash. Less commonly, severe infection is characterised by rapid onset of haemorrhagic fever (with internal bleeding) or life-threatening shock syndrome (with circulatory collapse). Signs and symptoms of encephalitis include confusion, tremors, seizures, paralysis, and loss of consciousness (Labeaud et al., 2011; Mayer et al., 2017). The distribution of an arbovirus is restricted by the territory of its mosquito vector(s) of transmission, which tends to be limited to tropical and subtropical zones. Yet, due to the effects of climate change (involving rainfall patterns) the geographical range of common vectors may be predicted to expand in future (Madewell, 2020). Thus, locations that at present are currently not affected should not be complacent that they will always remain free of arboviruses. The dramatic emergence and re-emergence of arboviral diseases has been greatly exacerbated by a combination of global meteorological, demographic, and societal changes, principally increasing rates and levels of climate change, urbanisation, globalisation, and international mobility (Bellone et al., 2023). These environmental and anthropogenic factors have facilitated viral etiological agents to break out of their natural ecological zones to become established in novel geographical sites where susceptible arthropod vectors and human hosts provide conditions supportive to their causing epidemics (Madewell, 2020). 3. The usual suspects DENV is an arbovirus of global concern but for which local outbreaks in Australia are restricted to Queensland, where the vector mosquito Aedes aegypti is established (Beebe et al., 2009). Community acquired infections have been reported only from urban areas in the northeast of the state, where the vector is most abundant. However, historical data show that much of Australia has previously sustained both the virus and the vector mosquito (Russell et al., 2009). Factors such as increased DENV activity in neighbouring countries like Indonesia and Papua New Guinea, plus the growing human population of northern Australia contribute to the risk of DENV transmission (Gyawali et al., 2016a). Climate change projections also suggest potential rises in dengue incidence and distribution associated with increasing temperatures (Williams et al., 2014). This also applies to JEV, the recent and rapid emergence of which in several states is a cause for concern (Williams et al., 2022). Imported cases of DENV and other arboviruses, including JEV, also pose a risk to public health in Australia. With increased global travel and trade, there is a potential for the introduction of arboviruses through infected travellers or imported vectors (Mackenzie and Williams, 2009). The spread of arboviruses to regions without established vectors, such as Ae. aegypti and Ae. albopictus, can occur through international air and sea ports (Gyawali et al., 2016a). Therefore, surveillance and control measures at ports of entry are crucial to prevent the importation and establishment of arboviruses in Australia. The most recent national report, for 2016, shows 2,227 notifications of DENV, of which 31 were locally acquired and the remainder travel-related, mostly tourists visiting Bali (Australian Government Department of Health, 2021). 4. The less usual suspects The threat presented by emerging indigenous arboviruses in Australia is arguably undervalued (Gyawali et al., 2016b). More than 75 arboviruses have been identified that are unique to the continent. While several are recognised to cause disease in humans, information on the potential human pathogenicity of most of these indigenous viruses is negligible (Gyawali et al., 2017a). Ross River (RRV) and Barmah Forest (BFV) viruses trigger an often debilitating and sometimes chronic type of arthritis that affects several joints at once. Murray Valley encephalitis (MVEV) and West Nile Kunjin strain (KUNV) viruses cause inflammation of the brain. One of the key arboviruses of concern is RRV, which is endemic and enzootic in the country and Papua New Guinea (Kuleshov et al., 2022). The major vector in inland areas is the freshwater-breeding Culex annulirostris, whereas Ochlerotatus vigilax and O. camptorhynchus transmit in brackish coastal waters. RRV infection in humans can cause peripheral polyarthralgia or arthritis, with disease notifications averaging 5,000 per year in Australia since the start of this century. Yet, there is considerable annual fluctuation of confirmed case reports; for instance, 9,555 notifications in 2015 but 3,677 in the following year (Australian Government Department of Health, 2021). As with RRV, human infections with BFV have been reported from all states and territories in Australia. Moreover, serological surveys indicate that this is a widespread phenomenon. Clinical manifestations often include fever, rash, chronic fatigue and polyarthritis. BFV is transmitted primarily by Cx. annulirostris and Aedes funereus in inland and in coastal regions, respectively. The reported incidence is usually close to 1,000 cases per annum since routine testing by immunoassay antibody detection became widely available (Gyawali and Taylor-Robinson, 2017). MVEV is endemic in northern Australia, with sporadic outbreaks occurring (Broom et al., 2003). The virus is transmitted primarily by Cx. annulirostris mosquitoes, and its activity is influenced by rainfall and flooding. Other emerging arboviruses, such as KUNV, have been detected in this and other ornithophilic mosquitoes and pose a potential public health threat (Broom et al., 2003). The presence of competent vectors and the potential for virus introduction through travel and trade increase the risk of emerging indigenous arboviruses in Australia (Mackenzie and Williams, 2009). Other Australian arboviruses, such as Alfuy, Edge Hill, Gan Gan, Kokobera, Sindbis and Stratford, are also associated with human disease (Gyawali et al., 2019). However, they appear to cause predominantly mild symptoms and a major outbreak has not yet been reported. While the epidemiology of these neglected viruses is poorly understood, they are likely maintained in zoonotic cycles rather than by human-to-human transmission. Hence, they are harboured by apathogenic, persistent infections in native Australian reservoir mammals (such as kangaroos and wallabies) and birds (including herons and egrets) (e.g., Gyawali et al., 2020), with occasional spillover into humans. 5. Need for improved early detection For many years it was speculated that infection with arboviruses may be a cause of febrile illness in Australia, as elsewhere in the world. This was confirmed with the discovery of the now frequently diagnosed RRV in 1959 and BFV in 1974. Yet, even after identification of these viruses it took almost 15 years for routine laboratory tests (involving detection of virus-specific immunoglobulin (Ig) M and IgG) to diagnose infection to become available (Gyawali et al., 2017a). While paired serology of RRV and BBV is considered clinical best practise, it requires careful interpretation considering the high rates of false positive and negative results, plus the long-term persistence of IgM in some individuals. Incorrect interpretation risks misdiagnosis and therefore inappropriate patient treatment (Gyawali et al., 2017b). Compounding this problem of inaccurate viral infection case reporting is the fact that more than half of so-called undifferentiated fevers (those with non-specific symptoms) in Australia still go undiagnosed (Gyawali et al., 2017a). In many instances this is because the treating physician may consider the cost of testing is not justified or the causative agent is novel, not known to cause human disease or no routine diagnostic test is available. In such cases, an association could be assumed but not proved between arboviruses and feverish illness. Hence, establishing a robust surveillance system would enable the early warning of an infection outbreak. Developing accurate diagnostic tools would aid early diagnosis and correct treatment of febrile primary care patients. Unforeseen climatic and environmental variations, such as the increased incidence of cyclones, heavy rainfall, and resultant intensified flooding associated with outbreaks of RRV (Tall et al., 2014) and MVEV (Selvey et al., 2014), have been occurring of late with disconcerting regularity, potentially effectuating an ecological change for Australian arboviruses (Young, 2018). The projected future climatic suitability of Northern Australia for competent vector mosquito species needs to be evaluated. In this context, improved epidemiological surveillance of prevailing environmental conditions, mosquito vector species and reservoir host animals, should be considered a public health priority. 6. A proposed solution In order to prepare effectively for the emergence of an arbovirus outbreak of public health concern, both globally (Weaver and Reisen, 2010), and in particular in regional Australia (Gyawali and Taylor-Robinson, 2017), key surveillance measures are essential. These include the following five actions: Vector surveillance: monitoring and mapping the distribution and abundance of mosquito vectors is crucial. This involves regular trapping and identification of vector species, as well as testing them for the presence of arboviruses. Vector surveillance helps identify areas at risk and informs targeted control measures. Environmental surveillance: monitoring environmental factors, such as temperature, rainfall, and humidity, can provide insights into vector breeding and arbovirus transmission dynamics. This information helps predict and anticipate outbreaks, enabling timely interventions. Animal surveillance: monitoring arboviral infections in animal populations, particularly in sentinel species, can serve as an early warning system for human outbreaks. Animals, such as marsupials and water birds, can act as reservoir hosts or environmental indicators of arbovirus activity. Disease surveillance: active surveillance for human cases of arboviral infections is vital. This involves monitoring and reporting suspected cases, conducting microbiology laboratory testing for confirmation, and analysing epidemiological data to identify trends and patterns. Early detection and reporting of cases allow for prompt public health responses. Syndromic surveillance: implementing surveillance systems that monitor specific clinical symptoms or syndromes associated with arboviral infections can provide early indications of outbreaks. Health indicators that are discernible before confirmed diagnosis include monitoring febrile illnesses, neurological symptoms, and other relevant clinical presentations. 7. A novel approach Artificial intelligence (AI) can play a prominent role in enhancing arbovirus surveillance at scales ranging from local to global. AI algorithms can analyze large volumes of data, including environmental, epidemiological, and entomological data. Integrating human, pathogen, vector, and climatic variables from various existing surveillance sources into a unified system can enhance pattern recognition and generate probabilistic risk models for outbreak spread and severity (Pley et al., 2021). This allows epidemiologists to detect patterns, predict outbreaks, and inform targeted interventions more accurately using such high-throughput techniques as metatranscriptomic sequencing (Batovska et al., 2022). Moreover, AI can automate data processing, improve data integration, assist in modelling, and provide real-time monitoring and analysis of multiple variables. This enables public health authorities to identify areas at high risk, to allocate resources more efficiently and thereby to make more proactive and effective responses (Batovska et al., 2019; Pley et al., 2021). In the context of arbovirus surveillance, AI can assist in the identification and tracking of mosquito vectors, processes that are crucial for understanding the transmission dynamics of arboviruses. By analysing data on mosquito populations, AI algorithms can identify trends and patterns that may indicate increased virus activity or the novel emergence of a virus in a location (Ramírez et al., 2018). This information can then be used to guide control and preventive measures. For example, AI can analyze satellite imagery and climate data, mosquito surveillance data, and human case data to reveal vector habitats, identify high-risk areas for disease outbreaks, and predict disease transmission dynamics (Kurucz et al., 2022). AI algorithms can also analyze social media and internet search data for disease outbreaks and public concerns to help to develop early warning systems and decision support tools (Batovska et al., 2022). Additionally, AI can assist in data integration and modelling to improve disease forecasting and inform targeted interventions by public health authorities. Research conducted in Kenya has demonstrated the effectiveness of mosquito-based arbovirus surveillance in diverse ecological zones (Ochieng et al., 2013). Similarly, in Burkina Faso, AI has been employed to enhance surveillance during dengue outbreaks, leading to improved understanding of the burden of arboviral diseases (Sanou et al., 2018). These experiences highlight the potential of AI in strengthening surveillance and response measures for arbovirus disease outbreaks globally. Therefore, the use of AI in arbovirus surveillance is not limited to Australia. Yet, this affluent developed nation is particularly suited to integrating AI into outbreak preparedness procedures (van den Hurk et al., 2012). It has the infrastructure and resources to leverage AI better than most countries, while also having plenty to gain by mitigating a neglected public health threat, especially in rural and regional locations that are relatively underserved. 8. Conclusion Arboviruses pose a significant public health threat to the population of Australia. There is a risk of emerging indigenous arboviruses, while imported cases also contribute to the burden. Surveillance measures, including monitoring vectors, diseases, and environmental factors, are crucial for early detection and response to outbreaks. This is particularly impactful in regional Australia, a historically underinvested region that is set to become a focus of economic and social development. This will increasingly bring humans into close contact with native reservoir hosts and vector mosquitoes. Such a convergence of factors could trigger an increased prevalence of infection with neglected indigenous arboviruses. Moreover, the escalating rate and effects of climate change that are observed in the tropical north of the country will likely drive a population boom of arbovirus-transmitting mosquitoes. As a commensurate response, continuing assiduous attention to vector monitoring and control is required. It is anticipated that the integration of artificial intelligence to process large volumes of data rapidly will enhance surveillance efforts by improving data analysis, prediction, and decision-making, ultimately leading to improved accuracy in detecting arboviral disease outbreaks and enabling more proactive and effective public health responses. The lessons learned from this Australian experience can help to better prepare government agencies in other nations to adopt AI technology in their enhanced surveillance efforts. In particular, this applies to low- and lower-middle income countries in tropical and subtropical zones where the rising incidence of arboviral diseases is a major public health concern. Author contributions AWT-R: Conceptualisation, Formal analysis, Investigation, Writing—original draft, Writing—review and editing.

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          Present and future arboviral threats.

          Arthropod-borne viruses (arboviruses) are important causes of human disease nearly worldwide. All arboviruses circulate among wild animals, and many cause disease after spillover transmission to humans and agriculturally important domestic animals that are incidental or dead-end hosts. Viruses such as dengue (DENV) and chikungunya (CHIKV) that have lost the requirement for enzootic amplification now produce extensive epidemics in tropical urban centers. Many arboviruses recently have increased in importance as human and veterinary pathogens using a variety of mechanisms. Beginning in 1999, West Nile virus (WNV) underwent a dramatic geographic expansion into the Americas. High amplification associated with avian virulence coupled with adaptation for replication at higher temperatures in mosquito vectors, has caused the largest epidemic of arboviral encephalitis ever reported in the Americas. Japanese encephalitis virus (JEV), the most frequent arboviral cause of encephalitis worldwide, has spread throughout most of Asia and as far south as Australia from its putative origin in Indonesia and Malaysia. JEV has caused major epidemics as it invaded new areas, often enabled by rice culture and amplification in domesticated swine. Rift Valley fever virus (RVFV), another arbovirus that infects humans after amplification in domesticated animals, undergoes epizootic transmission during wet years following droughts. Warming of the Indian Ocean, linked to the El Niño-Southern Oscillation in the Pacific, leads to heavy rainfall in east Africa inundating surface pools and vertically infected mosquito eggs laid during previous seasons. Like WNV, JEV and RVFV could become epizootic and epidemic in the Americas if introduced unintentionally via commerce or intentionally for nefarious purposes. Climate warming also could facilitate the expansion of the distributions of many arboviruses, as documented for bluetongue viruses (BTV), major pathogens of ruminants. BTV, especially BTV-8, invaded Europe after climate warming and enabled the major midge vector to expand is distribution northward into southern Europe, extending the transmission season and vectorial capacity of local midge species. Perhaps the greatest health risk of arboviral emergence comes from extensive tropical urbanization and the colonization of this expanding habitat by the highly anthropophilic (attracted to humans) mosquito, Aedes aegypti. These factors led to the emergence of permanent endemic cycles of urban DENV and CHIKV, as well as seasonal interhuman transmission of yellow fever virus. The recent invasion into the Americas, Europe and Africa by Aedes albopictus, an important CHIKV and secondary DENV vector, could enhance urban transmission of these viruses in tropical as well as temperate regions. The minimal requirements for sustained endemic arbovirus transmission, adequate human viremia and vector competence of Ae. aegypti and/or Ae. albopictus, may be met by two other viruses with the potential to become major human pathogens: Venezuelan equine encephalitis virus, already an important cause of neurological disease in humans and equids throughout the Americas, and Mayaro virus, a close relative of CHIKV that produces a comparably debilitating arthralgic disease in South America. Further research is needed to understand the potential of these and other arboviruses to emerge in the future, invade new geographic areas, and become important public and veterinary health problems. Copyright 2009 Elsevier B.V. All rights reserved.
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            The emergence of arthropod-borne viral diseases: A global prospective on dengue, chikungunya and zika fevers

            Highlights • Arboviruses are still expanding their geographic distribution and causing significant public health impact around the world. • DENV, CHIKV and ZIKV are mosquito-transmitted pathogens posing a threat to human health in many regions of the world. • Global travel and trade have facilitated the emergence of vector-borne diseases. • Surveillance of areas close to the forest is important to monitor the emergence of pathogens from their sylvatic cycle.
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              Australia's Dengue Risk Driven by Human Adaptation to Climate Change

              Introduction Aedes (Stegomyia) aegypti (Linneaus) is an important vector of dengue and other arboviruses. Despite its limited flight dispersal capability [1],[2], its close association with humans and its desiccation-resistant eggs have facilitated many long distance dispersal events within and between continents, allowing it to expand its range globally from its origin in Africa. Its global emergence and resurgence can be attributed to factors including urbanisation, transportation, changes in human movement, and behaviour, resulting in dengue running second to malaria in terms of human morbidity and mortality [3],[4]. Global historical collections and laboratory experiments on this well studied vector have suggested its distribution is limited by the 10°C winter isotherm [5], while a more recent and complex stochastic population dynamics model analysis suggests the temperature's limiting value to be more towards the 15°C yearly isotherm [6]. While historical surveys in Australia have indicated that Ae. aegypti occurred over much of the continent (see Fig. 1), its range has receded from Western Australia, the Northern Territory and New South Wales (NSW) over the last 50 years. It is now only found in Queensland [7],[8], although recent incursions into the Northern Territory have required costly eradication strategies [8]. The significant reduction in vector distribution has been attributed to a combination of events including the introduction of reticulated water, which reduced the domestic water storage requirements of households that had provided stable larval sites [7],[9], as well as the removal of the railway-based water storage containers hypothesised as being responsible for the long distance dispersal events of Ae. aegypti into rural regions in NSW via steam trains [7],[10]. 10.1371/journal.pntd.0000429.g001 Figure 1 Map of Australia showing the 234 Ae. aegypti collection sites described in Table S1. Almost all localities (except site 219 and 220) can be regarded as historical collections while red sites indicate historical sites where Ae. aegypti is no longer found and green sites are regarded as contemporary sites, collected since 1980. Top right map displays the current Australia resident population distribution and each dot represents approximately 1000 people (Source: Australian Demographic Statistics (3101.1)). Today, epidemic dengue is limited to regions of Queensland where Ae. aegypti is extant, and the frequency of outbreaks has increased constantly over the past decade [11]. Historically, epidemics of dengue were recorded in northern Queensland in the late 1800s and in southeast Queensland in 1904–05 [10]. Dengue epidemics in 1926, 1942 and 1943 all extended from Queensland south into NSW, stopping only on the arrival of winter [12]. Derrick and Bicks [12] found that these dengue epidemics ceased when the outside temperature reached a wet bulb isotherm of between 14–15°C and suggested that a parameter of 14.2°C mean annual wet bulb isotherm (TW) best represented the limiting parameter for the 1926 epidemic. The current drying of southeast Australia has placed this region's urban and rural communities on escalating water restrictions, with anthropogenic climate change forecasts suggesting that this drying trend will continue [13]. To mitigate against this regional drying effect and the stress it places on domestic water supply, state government rebate programs have been initiated to encourage the installation of large (>3000 L) domestic water tanks in towns and cities throughout this region. Data from the Australian Bureau of Statistics [14] records that in 2006, 20.6% of all Australian household dwellings had rainwater tanks. Given the expansion of domestic rainwater tanks in southern Australia, and assuming these domestic water tanks can provide oviposition sites, we ask this question: can climate be assessed to determine the distributional limits of Ae. aegypti and dengue in Australia? We first use a genetic algorithm to develop ecological niche models for the distribution of Ae. aegypti in Australia (using data points drawn from both historical and contemporary collection sites) and evaluate the potential distributional limits of Ae. aegypti in Australia under today's climate and in future projected climate change scenarios. We map these limits in relation to published experimental and theoretical projections of Ae. aegypti's temperature limits and then compare all projections to dengue transmission climate limits obtained from epidemiological studies of historical dengue epidemics in Australian. We find that human adaptation to climate change – through the installation of large stable water storage tanks – may pose a more substantial risk to the Australian population than do the direct effects of climate change. Additionally, we find that using point occurrence data and environmental parameters of climate and elevation to map the distribution of Ae. aegypti in Australia prove deceptive and require interpretation as some Ae. aegypti collection sites exist outside our ecological niche models and both theoretical cold temperature limits. This suggests that Ae. aegypti's domestic behaviour – with a lifecycle based around human habitation that includes blood-feeding and resting indoors as well as egg laying in artificial containers around houses – plays an influencing role on distribution. Materials and Methods Distribution of Aedes aegypti in Australia Coordinates for a total of 234 Ae. aegypti collections sites are described in Table S1. Historical collection sites were compiled [7],[9],[15],[16]. Contemporary collection sites were regarded as those collected since 1980 because most country towns had moved to reticulated water, steam powered trains had been replaced by diesel, and the common railway station water-filled fire buckets were removed [9],[17],[18]. Contemporary sites also include collections made between 1990 and 2005 from southeast Queensland (P. Mottram, unpub. data), and the Northern Territory (P. Whelan, unpub. data). Base climate layers Raster ASCII grids were generated for Australia at a spatial resolution of 0.025° (approximately 2.5 km) for eight climate variables plus elevation. These included annual mean rainfall and annual mean temperature produced by BIOCLIM using the ANUCLIM software package [19] as well as mean values of maximum temperatures and minimum temperatures for the months of January and July produced by the ESOCLIM component of ANUCLIM. This procedure involved the use of monthly mean climate surface coefficients, generated by the thin plate smoothing spline technique ANUSPLIN [20] from Australian Bureau of Meteorology climate data between 1921 and 1995 [21]. The geographic coordinates of the meteorological stations were used as independent spline variables together with a 0.025° digital elevation model (DEM) for Australia generated with ANUDEM [22] which acted as a third independent variable. As atmospheric moisture is known to be an important factor in terms of the survival and longevity of adult mosquitoes, mean values of dewpoint for January and July were generated with ESOCLIM to provide this. Climate change layers A further series of ASCII grids were generated from climate change scenarios using OzClim version 2 software [23],[24] at a spatial resolution of 0.25° (approximately 25 km). The scenarios used for this study were for 2030 and 2050 using CSIRO: Mk2 Climate Change Pattern with SRES Marker Scenario A1B and mid climate sensitivity. The output variables corresponded to the predicted change from the base climate for the rainfall and temperature parameters generated with ANUCLIM. This version of OzClim outputs vapour pressure rather than dewpoint as a measure of atmospheric moisture. For the present study vapour pressure grids for the predicted change from base climate for January and July were generated and the grid cell values were converted to dewpoint by applying the inverse of Tetens' equation [dp = (241.88×ln(vp/610.78))/(17.558−ln(vp/610.78)]. This mathematical procedure was implemented with the use of ImageJ software (publicly available at http://rsbweb.info.nih.gov/ij) together with the raster operations of TNTmips (MicroImages Inc., Lincoln, Nebraska). The environmental layers used for climate change modelling were prepared by resampling the OzClim outputs to the geographical extents and grid cell size of the ANUCLIM grids using TNTmips. The resampled outputs were then added to the corresponding ANUCLIM base climate layers to produce the environmental layers predicted for the chosen climate change scenarios. Ecological niche modelling DesktopGarp version 1_1_6 [25] was used for ecological niche modelling in a manner similar to our earlier studies [26]. Models derived from the historical climate data were generated using the record sites for Ae. aegypti as inputs together with the eight base climate layers and elevation (the ANUDEM generated DEM is described above) to model the range of Ae. aegypti. Species record sites and the climate change layers for 8 environmental parameters were derived from the climate change scenarios for 2030 and 2050 as well as the elevation layer. We utilized the medium sensitivity which corresponds to a global warming of 2.6°C for a doubling of CO2 from 280 ppm to 560 ppm [27]. The GARP procedure was implemented using half of the species record sites as a training data set for model building and the other half for model testing. Optimization parameters included 100 models for each run with 1000 iterations per model and 0.01 convergence limits. The best subsets procedure [28] was used to select 5 models which were added together using TNTmips to produce predicted range maps for each species. Theoretical temperature limits for Ae. aegypti extrapolated across Australia Previous studies of the distributional limits of Ae. aegypti were used to develop distribution maps for Australia. Christophers [5] hypothesised a climate limit of 10°C winter isotherm based on historical global collection data and laboratory-based experiments. We also evaluated the hypothetical limit from Otero and colleagues [6], who used a complex stochastic population model that incorporates the lifecycle parameters of Ae. aegypti to suggest a 15°C annual mean isotherm. Both these values were incorporated into distributional maps of Australia using TNTmips. Climate limit of dengue transmission in Australia Dengue transmission maps were developed using data from historical dengue outbreaks in Australia [12]. This work found that these dengue epidemics ceased when the outside temperature reached 14–15°C wet bulb isotherm and that a single parameter of 14.2°C annual mean wet bulb isotherm (TW) best approximated the limit of the 1926 epidemic – probably as a result of reducing the mosquitoes' feeding activity and the ability of the virus to replicate. This 14.2°C annual mean wet bulb isotherm value was mapped onto Australia for the current climate using TNTmips and three seasonal increments: the annual mean, the warmest quarter (December–February), and the coolest quarter (June–August). Results Distributional projections of Ae. aegypti: GARP modelling Distribution sites for Ae. aegypti in Australia (234 sites) were collated and displayed in a single map using GPS coordinates (Table S1 and Fig. 1). Ecological niche models were built with desktop GARP to produce a best subset model that showed agreement with the full complement of Ae. aegypti collections in Australia (Fig. 2A). In this projection, much of northern, eastern and southeast Australia was projected to present a suitable niche. This model closely tracks an annual rainfall pattern of less than 300 mm. However, the excluded region around central Australia included two Ae. aegypti positive collection sites (Meekatharra in central Western Australia and Boulia in Queensland): both collection localities are small regional centres on main inland transport routes. 10.1371/journal.pntd.0000429.g002 Figure 2 Distributional projections of Ae. aegypti in Australia based on 234 collection sites and built using desktop GARP and eight climatic variables. Panel A is the base layer projection (gray region) for the climate of 1995 and is regarded as current climate. Panel B is the projection of the forecasted climate changes for 2030 mid scenario. Panel C is the projection of the forecasted climate changes for 2050 mid scenario. The projected climate change scenario for 2030 produced distributional models with small expansions of the base model envelope, mostly evident in southern Australia (Fig. 2B). Likewise the 2050 model (Fig. 2C) extended the 2030 trend, resulting in a reduced niche in north-west Australia's Pilbara region while parts of central Australia opened up as a potential niche. Theoretical temperature limits of Ae. aegypti The temperature limit parameters of 10°C winter isotherm [5] and 15°C annual isotherm [6] were used to build theoretical isotherm limits for Ae. aegypti in Australia (Fig. 3). Figure 3A shows a 10°C winter isotherm limit base map for the current climate and OzClim projections were then generated for 2030 and 2050 by adding the projected changes to this base map (3B and 3C respectively). The 15°C annual isotherm limits were similarly generated using a base map and adding the OzClim changes. Both the 10°C (average winter) and 15°C (average annual) limits incorporate the major state capitals cities – Brisbane, Sydney, Adelaide and Perth. When these isotherm limits were subjected to the climate change scenarios for 2030 and 2050, the projection expanded to include the other mainland state capital, Melbourne (Fig. 3B and 3C). 10.1371/journal.pntd.0000429.g003 Figure 3 Theoretical distribution limits for Ae. aegypti and dengue transmission in Australia. Panels A–C represent the 10°C July isotherm with panel A the base layer projection for the current climate (1995). Panels B and C show the 10°C July isotherm limit of the climate change (mid) scenarios for 2030 and 2050 respectively. Panels D–F show distribution limits of Ae. aegypti in Australia based on the climate limit of 15°C annual mean isotherm. Panel D is the current climate (1995), panels E and F show the 15°C annual mean isotherm for climate change mid scenarios 2030 and 2050 respectively. Several Ae. aegypti collection sites occurred well within the two theoretical cold climate limits. Table 1 details six Ae. aegypti collection sites as examples where the annual mean temperature and the mean temperature for July (calculated as (mintemp+maxtemp)/2) fall below the theoretical values and range from 12.4–15.4°C and 5.2–7.6°C respectively. 10.1371/journal.pntd.0000429.t001 Table 1 Collection sites in NSW that fall below theoretical cool temperature limits. Site Locality Annual mean temp (°C) Max/min temp July (°C) Mean temp July (°C) Elevation (M) 98 Breadalbane 12.4 10.3/0.2 5.25 701 116 Culcairn 14.7 11.9/2.2 7.05 221 187 Wagga Wagga 15.4 12.8/2.4 7.6 177 133 Junee 15.1 12.4/2.2 7.3 295 131 Harden 14.3 12.1/1.2 6.65 396 189 Wallendbeen 13.9 11.6/1.0 6.3 468 Theoretical dengue transmission limits Derrick and Bicks [12] suggested that dengue transmission stopped between the 15°C and 14°C TW isotherm and suggested that a 14.2°C TW annual mean isotherm best approximated the temperature limit for transmission in the 1926 dengue epidemic. We applied this isotherm to Australia for the annual mean isotherm (Fig. 4A) as well as the warmest quarter isotherm (summer; December–February, Fig. 4B) and the coldest quarter isotherm (winter; June–August, Fig. 4C). These climate limit maps indicate that if the vector could re-establish itself throughout its former range then much of northern tropical Australia would be receptive to dengue transmission year round and transmission would be possible throughout most of Australia during the summer months. 10.1371/journal.pntd.0000429.g004 Figure 4 Employing a hypothetical dengue climate limit estimated from epidemics in Australia that stopped on the arrival of winter where the outside temperature fell to a wet bulb isotherm (TW) of 14–15°C [12], we mapped a 14.2°C TW isotherm onto Australia using three temporal increments. Panel A represents the 14.2°C annual mean TW for Australia [12]. Panel B represents the 14.2°C TW for Australia's warmest quarter (December–February), representing summer transmission. Panel C represents the same isotherm for Australia's coolest quarter (June–August), representing potential year-round transmission. Discussion Can the historical distribution of Ae. aegypti in Australia provide an insight into the potential distribution potential of this mosquito? Using 234 different spatial data points generated from historical and contemporary collections of Ae. aegypti in Australia, we developed ecological niche models to hypothesise the potential range expansion of this mosquito under today's climate and under future climate change scenarios for 2030 and 2050 using OzClim mid sensitivity values that correspond to a global warming of 2.6°C for a doubling of CO2 from 280 ppm to 560 ppm [27]. In Australia general warming estimates are approximately 1.0°C by 2030 and 1.2 to 2.2°C by 2050, the latter values being dependent on CO2 emissions. While rainfall (outside of far north Australia) is estimated to decrease by 2% to 5%, southern Australia is projected to encounter a 5% reduction in rainfall [13]. Our GARP model for current climate suggested that Ae. aegypti could potentially coexist with over 95% of the Australian population and this distribution did not change significantly, with regard to the Australian population distribution, under either the 2030 and 2050 climate change scenarios. Only the highly arid central Australian region was excluded from the projection (annual rainfall less than 300 mm). The GARP model did not show southern cold climate thermal limits in Australia, probably due to the presence of several Ae. aegypti collection sites from inland New South Wales that show cool climate parameters. We then mapped two theoretical cool climate limits across Australia – the 10°C winter (July) isotherm [5] and the 15°C annual mean isotherm [6]. Of these two isotherm limits the 15°C annual mean isotherm appeared more representative of the known distribution of Ae. aegypti in Australia, although collection sites did exist outside these temperature isotherm limits. It remains unknown if the cold climate tolerant populations were breeding in the warmer months and surviving the colder winter months as eggs [29], or were surviving as larvae. With regard to these questions, observations have been recorded of viable Ae. aegypti larvae in ice encrusted water [5],[7], while experiments have suggested that a water temperature of 1.0°C can be lethal over 24 hours, but larvae can be viable at a constant 7.0°C for over a week [5]. At the other temperature extreme, laboratory experiments show that Ae. aegypti larvae perish when the water temperature exceeds 34°C while adults start to die off as the air temperature exceeds 40°C [5]. Domestic water tanks in Australia contain thousands of litres of water that would – in combination with the mosquitoes' domestic (indoor) nature – provide a buffer to temperature extremes and assist mosquito survival in what may appear unsuitable environments. For example, Ae. aegypti exists and transmit dengue in India's Thar desert townships in north-western Rajasthan, where the mosquito utilises household pitchers and underground cement water tanks. [30]. The incongruence between the temperature limits and our ecological niche models highlights the difficulties of using what are essentially sophisticated climate pattern matching procedures to study an organism with a biology and ecology strongly influenced by human activity. Fortunately, we can directly compare our GARP model with a new mechanistic model of the same organism over the same environment [31]. This mechanistic model utilises biophysical life processes parameters such as the effects of climate on reproduction and larval development. Larval development in both rainwater tanks and smaller containers were assessed and the potential distribution of Ae. aegypti was projected across Australia. Projections using rainwater tanks larval development resembled our GARP model for Northern and central Australia, but unlike our projections, a southern cold climate thermal limit was identified which was actually lower than the published parameters displayed in Fig. 3 [5],[6]. Apart from showing the clear advantage of a bottom-up approach for modelling this mosquito, this study supports the hypothesis that domestic rainwater tanks contributed for the historical southern distribution of Ae.aegypti in Australia. Humans not only facilitate long distance dispersal events for this mosquito, co-habitation with humans can provide thermal buffers to the outdoor climate as adults rest indoors, and domestic rainwater tanks can provide stable oviposition sites. When the theoretical distributions (GARP models and temperature limits) and actual Ae. aegypti distributions are viewed alongside the expansion of domestic water tanks underway in Australia, a trend emerges where Ae. aegypti could potentially exist year-round in today's climate throughout the southern Australian mainland. This potential distribution includes the metropolitan areas of Brisbane (pop 1.8 million), Sydney (pop 4.2 million), Adelaide (pop 1.1 million) and Perth (pop 1.5 million). Additionally the climate change temperature limit projections for the mid scenario 2050 see this range expand to include Melbourne (pop 3.6 million). The addition of a theoretical dengue virus transmission limit parameter (we used a 14.2°C wet bulb isotherm) suggests an overlapping dengue risk in many of Australia's metropolitan regions during the summer months (December–February). The potential for dengue virus introduction to these regions through travellers from endemic regions (including north Queensland) during summer presents a transmission risk that can be inferred by the current incidence of imported and endemic cases of dengue in Australia – many of which enter Australia through national and international transport nodes. For example, for the year to June 2008 there were 250 dengue notifications for Australia, of which 113 came from Queensland (most via local transmission), 72 from NSW, 15 from NT, 12 from SA, 8 from VIC, and 28 from WA. Notifications from New South Wales, South Australia, Victoria and Western Australia exceeded the five-year mean in each jurisdiction suggesting that the frequency of dengue is increasing [32]. Understanding the relationship between climate and dengue transmission is difficult because non-linear relationships exist between the daily survival of Ae. aegypti, the extrinsic incubation period (EIP) of the virus, temperature and humidity [33]–[35]. Forecasted regional warming in Australia may lengthen and intensify the dengue transmission season by shortening the mosquitoes' EIP, although it is important to note that dengue epidemics appear to be more strongly influenced by intrinsic population dynamic (epidemiological) processes than by climate [36]. Even so, any temporal extension effect in the transmission season will follow the expansion of potential larval sites that is now underway in Australia. Thus, while the issue of regional warming is important, the expansion of large rainwater tanks throughout urban regions of Australia is at present a prevailing human adaptation with more immediate possibilities for changing vector distributions in Australia than the direct warming effects projected by anthropogenic climate change scenarios. Whether southern Australia's current drought is due to the region's natural climate variability or part of a changing climate pattern, will continue to be debated by some. Nonetheless, it is important to avoid the cycle where human changes in water storage result in an Ae. aegypti range expansion followed by dengue epidemics seeded by viremic travellers [4],[37]. Additionally, domestic water storage can sustain Ae. aegypti populations (and dengue transmission) in regions not normally suitable for its survival [38], while active government and community contributions can remove established Ae. aegypti populations (and dengue) from areas where it has been endemic [39] – and both of these are human modifications. In Australia, ineffectively screened domestic rainwater tanks have been identified as key containers with respect to Ae. aegypti productivity [40],[41]. The introduction of reticulated water systems in towns and cities throughout Australia is believed responsible for a major range contraction of Ae. aegypti over the last 50 years. This trend may now be reversed as humans adapt to climate-change-induced drought conditions – the increased use of domestic water storage in tanks could deliver stable primary larval sites into urban neighbourhoods. In Queensland's capital city, Brisbane – which is currently Ae. aegypti free – severe water shortages resulted in escalating water restrictions with an eventual prohibition on the use of all outside reticulated water outlets (November 2007–July 2008) and 75,000 domestic water tanks being installed by late 2007. This number of tanks represents approximately 21% of households with reticulated water in the Brisbane area (F. Chandler, Brisbane City Council, pers. comm.). Additionally, ad hoc uncontrolled water tanks are now also commonly being used to store rainwater, adding to the potential surfeit of stable breeding sites around Australia that are likely to facilitate the expansion risk of Ae. aegypti into urban areas. It is unlikely that any of these water storage tanks – government approved or not – will be maintained sufficiently to prevent mosquito access in the long term. The flight range for Ae. aegypti is understood to be generally small: mark-release recapture experiments show them to have a flight range of only hundreds of metres [42]–[44]. However, these estimates are limited in time and space, being derived from a snapshot of one or a few gonotrophic cycles which take place in the context of an abundance of ovipositing sites. Longer distance flight range dispersal may be more common, especially when ovipositing sites are rare, but this is difficult to quantify [45],[46]. Human mediated long distance dispersal events are mostly responsible for Ae. aegypti movement: their highly domestic nature and desiccation-resistant eggs facilitate successful movement via human transport routes. Surveys in Queensland in the 1990s [17] and 1990–2005 (P. Mottram, unpublished) reveal Ae. aegypti collections from over 70 townships and this number is likely an underestimate. As the numbers of individuals and populations of Ae. aegypti increase in Queensland towns, the incursion risk beyond these regions via human-induced long distance dispersal events also increases, and with the presence of new stable oviposition sites growing, the expansion of this dengue vector must now be expected. Operations to remove Ae. aegypti incursions are resource-heavy, often requiring both government legislation and widespread community cooperation to reduce adult mosquito populations. A recent example from a 2004 incursion of Ae. aegypti into the small Northern Territory town of Tennant Creek (pop 3,200) from Queensland resulted in a two-year eradication campaign that required 11 personnel and cost approximately $1.5 million and was achieved in 2006 [8]. Conclusion Determining the potential distribution of Ae. aegypti in Australia using climatic parameters can be problematic and in this case produced results that neither fully match the known distribution, nor reveal cold climate limits in Australia. Reasons for this may exist in the difficulty of relating the point occurrence data of a species' distribution that is closely tied to humans – unlike native mosquito species in Australia where GARP models appear more representative of known distributions [26],[47]. We must also consider the limited climatic parameters available through the OzClim climate scenario generator that reduced the GARP modelling to a subset of environmental parameters that may have little influence on the organism. Because the GARP models showed no cold temperature limits for Ae. aegypti in Australia, we also assessed two published theoretical cold temperature limits across Australia. These temperature limit projections also could not contain all collection sites, which may suggest that in Australia, climate - and in particular temperature - plays a less important role in determining the range of this species due to a combination of its intimate relationship with humans and our propensity to store water. This is where the use of statistical approaches and point occurrence data to evaluate species' distribution may be weak and integrating life processes parameters such as the effects of climate on reproduction and larval development may be more practical and informative. If it is an assumption that burgeoning domestic water tanks will provide stable larval sites for Ae. aegypti, then the synthesis of our GARP modelling, the theoretical climate limits and the historical distribution of this mosquito strongly suggest that a distributional expansion is possible and could expose the majority of Australia's population to this dengue vector. Additionally, viewing this synthesis of Ae. aegypti in Australia with dengue transmission climate limits obtained from historical Australian dengue epidemics suggests a real risk of dengue transmission occurring in regions ranging well beyond north Queensland during the summer months. We conclude that if the installation and maintenance of domestic water storage tanks is not tightly controlled today, Ae. aegypti could be spread by humans to cohabit with the majority of Australia's population, presenting a high potential dengue transmission risk during our warm summers. Supporting Information Table S1 Aedes aegypti collection sites in Australia. (0.69 MB RTF) Click here for additional data file.
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                URI : http://loop.frontiersin.org/people/219003/overviewRole: Role: Role: Role: Role:
                Journal
                Front Microbiol
                Front Microbiol
                Front. Microbiol.
                Frontiers in Microbiology
                Frontiers Media S.A.
                1664-302X
                25 October 2023
                2023
                : 14
                : 1284838
                Affiliations
                [1] 1College of Health Sciences, VinUniversity , Hanoi, Vietnam
                [2] 2VinUniversity-University of Illinois Smart Health Center, VinUniversity , Hanoi, Vietnam
                [3] 3Center for Global Health, Perelman School of Medicine, University of Pennsylvania , Philadelphia, PA, United States
                [4] 4College of Health and Human Sciences, Charles Darwin University , Casuarina, NT, Australia
                Author notes

                Edited by: Ke Liu, Chinese Academy of Agricultural Sciences (CAAS), China

                Reviewed by: Rui-De Xue, University of the Sciences, Philadelphia, United States

                *Correspondence: Andrew W. Taylor-Robinson andrew.tr@ 123456vinuni.edu.vn

                †ORCID: Andrew W. Taylor-Robinson orcid.org/0000-0001-7342-8348

                Article
                10.3389/fmicb.2023.1284838
                10634219
                329b8339-9c7c-4390-9496-5df21eb8f70b
                Copyright © 2023 Taylor-Robinson.

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                History
                : 29 August 2023
                : 10 October 2023
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                The author(s) declare that no financial support was received for the research, authorship, and/or publication of this article.
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                Microbiology & Virology
                research topic: transmission and infection of arboviruses,surveillance,response,outbreak,public health,artificial intelligence,australia

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