Predicting the Start of the Aedes albopictus (Diptera: Culicidae) Female Adult Biting Season Using the Spring Temperature in Japan

Enhancing health resilience in Japan in a changing climate

Climate change poses significant threats to human health, propelling Japan to take decisive action through the Climate Change Adaptation Act of 2018. This Act has led to the implementation of climate change adaptation policies across various sectors, including healthcare. In this review, we synthesized existing scientific evidence on the impacts of climate change on health in Japan and outlined the adaptation strategies and measures implemented by the central and local governments. The country has prioritized tackling heat-related illness and mortality and undertaken various adaptation measures to mitigate these risks. However, it faces unique challenges due to its super-aged society. Ensuring effective and coordinated strategies to address the growing uncertainties in vulnerability to climate change and the complex intersectoral impacts of disasters remains a critical issue. To combat the additional health risks by climate change, a comprehensive approach embracing adaptation and mitigation policies in the health sector is crucial. Encouraging intersectoral communication and collaboration will be vital for developing coherent and effective strategies to safeguard public health in the face of climate change.

Critical Photoperiod and Its Potential to Predict Mosquito Distributions and Control Medically Important Pests

Diapause, a period of arrested development that allows mosquitoes to survive inhospitable conditions, is triggered by short daylengths in temperate mosquitoes. Different populations of mosquitoes initiate diapause in response to a specific photoperiod, or daylength, resulting in population-specific differences in annual cycles of abundance. The photoperiod that causes approximately 50% of a population to initiate diapause is known as the critical photoperiod (CPP). The autumn daylength corresponding to the CPP in the field likely marks the day beyond which the photoperiods would trigger and maintain 50% or more diapause incidence in a population, although temperature, diet, and other factors can impact diapause initiation. In the Northern Hemisphere, northern populations of mosquitoes experience lower temperatures earlier in the year and must be triggered into diapause by longer daylengths than southern populations. CPP is genetically based, but also adapts over time responding to the population's environment. Therefore, CPP has been shown to lengthen with increasing latitude and altitude. While the positive correlation between CPP and latitude/altitude has been established in a few mosquito species, including Aedes albopictus (Skuse, Diptera: Culicidae), Aedes triseriatus, Aedes sierrensis, and Wyeomyia smithii (Coquillett, Diptera: Culicidae), we do not know when most other species initiate their seasonal responses. As several of these species transmit important diseases, characterizing the CPP of arthropod vectors could improve existing control by ensuring that surveillance efforts align with the vector's seasonally active period. Additionally, better understanding when mosquitoes and other vectors initiate diapause can reduce the frequency of chemical applications, thereby ameliorating the negative impacts to nontarget insects.

Seasonality and timing of peak abundance of <em>Aedes albopictus</em> in Europe: Implications to public and animal health

Aedes albopictus is a known vector of dengue and chikungunya. Understanding the population dynamics characteristics of vector species is of pivotal importance to optimise surveillance and control activities, to estimate risk for pathogen-transmission, and thus to enhance support of public health decisions. In this paper we used a seasonal activity model to simulate the start (spring hatching) and end (autumn diapause) of the vector season. In parallel, the peak abundance of the species was assessed using both VectorNet field survey data complemented with field studies obtained from literature across the Mediterranean Basin. Our results suggest that spring hatching of eggs in the current distribution area can start at the beginning of March in southern Europe and in April in western Europe. In northern Europe, where the species is not (yet) present, spring hatching would occur from late April to late May. Aedes albopictus can remain active up to 41 weeks in southern Europe whilst the climatic conditions in northern Europe are limiting its potential activity to a maximum of 23 weeks. The peak of egg density is found during summer months from end of July until end of September. During these two months the climatic conditions for species development are optimal, which implies a higher risk for arbovirus transmission by Ae. albopictus and occurrence of epidemics.

Ecological mechanism of climate-mediated selection in a rapidly evolving invasive species

Recurring seasonal changes can lead to the evolution of phenological cues. For example, many arthropods undergo photoperiodic diapause, a programmed developmental arrest induced by short autumnal day length. The selective mechanisms that determine the timing of autumnal diapause initiation have not been empirically identified. We quantified latitudinal clines in genetically determined diapause timing of an invasive mosquito, Aedes albopictus, on two continents. We show that variation in diapause timing within and between continents is explained by a novel application of a growing degree day (GDD) model that delineates a location-specific deadline after which it is not possible to complete an additional full life cycle. GDD models are widely used to predict spring phenology by modelling growth and development as physiological responses to ambient temperatures. Our results show that the energy accumulation dynamics represented by GDD models have also led to the evolution of an anticipatory life-history cue in autumn.

Seasonality modeling of the distribution of Aedes albopictus in China based on climatic and environmental suitability

Background

Aedes albopictus is a highly invasive mosquito species and a major vector of numerous viral pathogens. Many recent dengue fever outbreaks in China have been caused solely by the vector. Mapping of the potential distribution ranges of Ae. albopictus is crucial for epidemic preparedness and the monitoring of vector populations for disease control. Climate is a key factor influencing the distribution of the species. Despite field studies indicating seasonal population variations, very little modeling work has been done to analyze how environmental conditions influence the seasonality of Ae. albopictus. The aim of the present study was to develop a model based on available observations, climatic and environmental data, and machine learning methods for the prediction of the potential seasonal ranges of Ae. albopictus in China.

Methods

We collected comprehensive up-to-date surveillance data in China, particularly records from the northern distribution margin of Ae. albopictus. All records were assigned long-term (1970–2000) climatic data averages based on the WorldClim 2.0 data set. Machine learning regression tree models were developed using a 10-fold cross-validation method to predict the potential seasonal (or monthly) distribution ranges of Ae. albopictus in China at high resolution based on environmental conditions. The models were assessed based on sensitivity, specificity, and accuracy, using area under curve (AUC). WorldClim 2.0 and climatic and environmental data were used to produce environmental conduciveness (probability) prediction surfaces. Predicted probabilities were generated based on the averages of the 10 models.

Results

During 1998–2017, Ae. albopictus was observed at 200 out of the 242 localities surveyed. In addition, at least 15 new Ae. albopictus occurrence sites lay outside the potential ranges that have been predicted using models previously. The average accuracy was 98.4% (97.1–99.5%), and the average AUC was 99.1% (95.6–99.9%). The predicted Ae. albopictus distribution in winter (December–February) was limited to a small subtropical-tropical area of China, and Ae. albopictus was predicted to occur in northern China only during the short summer season (usually June–September). The predicted distribution areas in summer could reach northeastern China bordering Russia and the eastern part of the Qinghai-Tibet Plateau in southwestern China. Ae. albopictus could remain active in expansive areas from central to southern China in October and November.

Conclusions

Climate and environmental conditions are key factors influencing the seasonal distribution of Ae. albopictus in China. The areas predicted to potentially host Ae. albopictus seasonally in the present study could reach northeastern China and the eastern slope of the Qinghai-Tibet Plateau. Our results present new evidence and suggest the expansion of systematic vector population monitoring activities and regular re-assessment of epidemic risk potential.