Aedes aegypti (L.) mosquitoes preferentially oviposit in natural and artificial receptacles where their eggs are able to withstand drying as water levels fluctuate. Desiccation-resistant eggs also increase the potential for establishment in non-native habitats while providing logistical impediments to control programs. Viability and mean survival times of eggs stored under three dryness conditions for up to 367 days were investigated among three field-derived colonies of Australian Ae. aegypti to understand variation in desiccation survival. Further investigations compared egg survival between an established colony and its wild counterpart. Our results confirmed that Ae. aegypti eggs can withstand desiccation for extended periods of time with approximately 2-15% egg viability recorded after one year and viability remaining above 88% under all conditions through 56 days. Intraspecific variations in egg survival times were recorded, suggesting local adaptation while each of the colonies demonstrated a consistent preference for higher humidity. Egg volume varied between the populations, suggesting a relationship between egg volume and survival time, with the marginally larger eggs (Charters Towers and Innisfail) having greater desiccation resistance over the range of conditions. The strong survivorship of Charters Towers eggs in dry, warm conditions demonstrates the adaptive significance of a desiccation-resistant egg. Journal of Vector Ecology 40 (2): 292-300. 2015.

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The Australian native mosquito Aedes (Finlaya) notoscriptus (Skuse) is closely associated with natural and artificial water holding receptacles. Eggs are laid in habitats where they are exposed to drying conditions as water levels fluctuate. Withstanding desiccation enables survival in challenging environments and increases the potential for establishment in non-native habitats. Until now, the desiccation resistance of Ae. notoscriptus eggs has been unknown despite the historical invasive success of this important dog heartworm and arbovirus vector. Viability and mean survival times of eggs from two Ae. notoscriptus populations (metropolitan areas of Sydney, NSW and Adelaide, SA) were evaluated, with eggs stored under three dryness conditions for up to 367 days. Our results revealed that Ae. notoscriptus eggs can withstand desiccation for extended periods, under a variety of conditions, with approximately 9-13% egg viability recorded after one year. This prolonged egg survival reflects the widespread distribution of this mosquito in Australia and its history of incursions and subsequent establishment in non-native habitats. Differences in mean egg volume were recorded in addition to significantly different egg length to width ratios for the two populations, which may reflect adaptation to biotope of origin and an associated likelihood of drought and drying conditions. The results of this study suggest that the desiccation resistant eggs of Ae. notoscriptus make this species highly adaptable, increasing the risk of movement to non-endemic regions of the world. Journal of Vector Ecology 41 (1): 55-62. 2016.

Objective To review the diagnostic test accuracy and predictive value of statistical models in differentiating the severity of dengue infection. Methods Electronic searches were conducted in the Cochrane Database of Systematic Reviews, Cochrane Central Register of Controlled Trials, MEDLINE (complete), PubMed and Scopus. Eligible studies to be included in this review were cohort studies with participants confirmed by laboratory test for dengue infection and comparison among the different severity of dengue infection by using statistical models. The methodological quality of the paper was assessed by independent reviewers using QUADAS‐2. Results Twenty‐six studies published from 1994 to 2017 were included. Most diagnostic models produced an accuracy of 75% to 80% except one with 86%. Two models predicting severe dengue according to the WHO 2009 classification have 86% accuracy. Both of these logistic regression models were applied during the first three days of illness, and their sensitivity and specificity were 91–100% and 79.3–86%, respectively. Another model which evaluated the 30‐day mortality of dengue infection had an accuracy of 98.5%. Conclusion Although there are several potential predictive or diagnostic models for dengue infection, their limitations could affect their validity. It is recommended that these models be revalidated in other clinical settings and their methods be improved and standardised in future.