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BackgroundFuture distribution of dengue risk is usually predicted based on predicted climate changes using general circulation models (GCMs). However, it is difficult to validate the GCM results and assess the uncertainty of the predictions. The observed changes in climate may be very different from the GCM results. We aim to utilize trends in observed climate dynamics to predict future risks of Aedes albopictus in China.MethodsWe collected Ae. albopictus surveillance data and observed climate records from 80 meteorological stations from 1970 to 2021. We analyzed the trends in climate change in China and made predictions on future climate for the years 2050 and 2080 based on trend analyses. We analyzed the relationship between climatic variables and the prevalence of Ae. albopictus in different months/seasons. We built a classification tree model (based on the average of 999 runs of classification and regression tree analyses) to predict the monthly/seasonal Ae. albopictus distribution based on the average climate from 1970 to 2000 and assessed the contributions of different climatic variables to the Ae. albopictus distribution. Using these models, we projected the future distributions of Ae. albopictus for 2050 and 2080.ResultsThe study included Ae. albopictus surveillance from 259 sites in China found that winter to early spring (November-February) temperatures were strongly correlated with Ae. albopictus prevalence (prediction accuracy ranges 93.0-98.8%)-the higher the temperature the higher the prevalence, while precipitation in summer (June-September) was important predictor for Ae. albopictus prevalence. The machine learning tree models predicted the current prevalence of Ae. albopictus with high levels of agreement (accuracy > 90% and Kappa agreement > 80% for all 12 months). Overall, winter temperature contributed the most to Ae. albopictus distribution, followed by summer precipitation. An increase in temperature was observed from 1970 to 2021 in most places in China, and annual change rates varied substantially from -0.22 ºC/year to 0.58 ºC/year among sites, with the largest increase in temperature occurring from February to April (an annual increase of 1.4-4.7 ºC in monthly mean, 0.6-4.0 ºC in monthly minimum, and 1.3-4.3 ºC in monthly maximum temperature) and the smallest in November and December. Temperature increases were lower in the tropics/subtropics (1.5-2.3 ºC from February-April) compared to the high-latitude areas (2.6-4.6 ºC from February-April). The projected temperatures in 2050 and 2080 by this study were approximately 1-1.5 °C higher than those projected by GCMs. The estimated current Ae. albopictus risk distribution had a northern boundary of north-central China and the southern edge of northeastern China, with a risk period of June-September. The projected future Ae. albopictus risks in 2050 and 2080 cover nearly all of China, with an expanded risk period of April-October. The current at-risk population was estimated to be 960 million and the future at-risk population was projected to be 1.2 billion.ConclusionsThe magnitude of climate change in China is likely to surpass GCM predictions. Future dengue risks will expand to cover nearly all of China if current climate trends continue.

Abstract: Background. Future distribution of dengue risk is usually predicted based on predicted climate changes using general circulation models (GCMs). However, it is hard to validate the GCM results and assess the uncertainty of the predictions. Observed changes in climate may be very different from GCM results.Methods.We collected Aedes albopictus surveillance data and observed climate records from about 90 meteorological stations for the period 1970–2021. We analyzed the trends of climate change in China and made predictions on future climate for the years 2050 and 2080 based on trend analyses. We analyzed the relationship between climatic variables and the prevalence of Ae. albopictusin different months/seasons. We built a series of machine learning classification tree models to predict the monthly/seasonal Ae. albopictus distribution based on the average climate from 1970 to 2000 and assessed the contributions of different climatic variables to the Ae. albopictus distribution. Using these models, we projected the future distributions of Ae. albopictus for the years of 2050 and 2080.Results. The study included Ae. albopictus surveillance from 259 sites in China and found that winter to early spring (November–February) temperatures were strongly correlated with Ae. albopictus prevalence – the higher the temperature the higher the prevalence, while precipitation in summer (June–September) was important predictors for Ae. albopictus prevalence. The machine learning tree models predicted the current prevalence of Ae. albopictus with high agreement (accuracy > 90% and Kappa agreement > 80% for all months). Overall, winter temperature contributed the most to Ae. albopictus distribution, followed by summer precipitation. Increase in temperature was observed in most places in China and rates of annual change varied substantially among sites, with the highest increase in temperature occurring from February to April (annual increase of 1.4 – 4.7ºC for monthly mean, 0.6 – 4.0ºC for monthly minimum, and 1.3 – 4.3ºC for monthly maximum temperature) and the lowest in November and December. Temperature increases were lower in the tropics/subtropics compared to the high-latitude areas. The projected temperatures in 2050 and 2080 by this study were about 1~1.5°C higher than projected by GCMs. The estimated current Ae. albopictus risk distribution had a northern boundary of north-central China and the southern edge of northeastern China, with a risk period of June–September. The projected future Ae. albopictus risks in 2050 and 2080 cover nearly all of China, with an expanded risk period of April–October. The current at-risk population was estimated to be 960 million and the future at-risk population was projected to be 1.2 billion.Conclusions.The magnitude of climate change in China is likely to surpass the GCM predictions. Future dengue risks will expand to cover nearly all of China if the current climate trends continue.

Vector-borne diseases leave a large footprint on global health. Notable culprits include West Nile virus (WNV), St. Louis encephalitis virus (SLEV), and Japanese encephalitis virus (JEV), all transmitted by Culex mosquitoes. Chemical insecticides have been widely used to reduce the spread of mosquito-borne diseases. Still, mosquitoes are becoming more and more resistant to most chemical insecticides which cause particular harm to the ecology. Wolbachia belongs to the family Ehrlichiaceae in the order Rickettsiales and is a matrilineally inherited endosymbiont present in 60% of insects in nature. Wolbachia is capable of inducing a wide range of reproductive abnormalities in its hosts, such as cytoplasmic incompatibility, and can alter mosquito resistance to pathogen infection. Wolbachia has been proposed as a biological alternative to chemical vector control, and specific research progress and effectiveness have been achieved. Despite the importance of Wolbachia, this strategy has not been tested in Culex pipiens pallens, the most prevalent mosquito species in Shandong Province, China. Little is known about how the mass release of Wolbachia-infected mosquitoes may impact the genetic structure of Culex pipiens pallens, and how the symbiotic bacterium Wolbachia interacts with mitochondria during host mosquito transmission. Based on the population genetic structure of Culex pipiens pallens in Shandong Province, this study investigated the infection rate and infection type of Wolbachia in Shandong Province and jointly analysed the evolutionary relationship between the host mosquito and the symbiotic bacterium Wolbachia. Our study showed that Wolbachia naturally infected by Culex pipiens pallens in Shandong Province was less homologous to Wolbachia infected by Aedes albopictus released from mosquito factory in Guangzhou. Our results also show that Culex pipiens pallens is undergoing demographic expansion in Shandong Province. The overall Wolbachia infection rate of Culex pipiens pallens was 92.8%, and a total of 15 WSP haplotypes were detected. We found that the genetic diversity of Wolbachia was low in Culex pipiens pallens from Shandong Province, and the mosquitoes were infected only with type B Wolbachia. Visualizing the relationship between Culex pipiens pallens and Wolbachia using a tanglegram revealed patterns of widespread associations. A specific coevolutionary relationship exists between the host mosquito and Wolbachia. Knowledge of this mosquito–Wolbachia relationship will provide essential scientific information required for Wolbachia-based vector control approaches in Shandong Province and will lead to a better understanding of the diversity and evolution of Wolbachia for its utility as a biocontrol agent. Author summary: This study was the first to investigate the population genetic structure and Wolbachia infection of Culex pipiens pallens in Shandong Province, providing a basis for mosquito-borne control and disease prevention. The joint analysis of Wolbachia and mitochondrial markers highlighted the coevolutionary relationship between Wolbachia and its host. It also provided the scientific basis for green precision prevention and control of mosquito-borne bacteria and viruses. [ABSTRACT FROM AUTHOR]

Mosquitoes are vectors of many important human diseases. The prolonged and widespread use of insecticides has led to the development of mosquito resistance to these insecticides. The gut microbiota is considered the master of host development and physiology; it influences mosquito biology, disease pathogen transmission, and resistance to insecticides. Understanding the role and mechanisms of mosquito gut microbiota in mosquito insecticide resistance is useful for developing new strategies for tackling mosquito insecticide resistance. We searched online databases, including PubMed, MEDLINE, SciELO, Web of Science, and the Chinese Science Citation Database. We searched all terms, including microbiota and mosquitoes, or any specific genera or species of mosquitoes. We reviewed the relationships between microbiota and mosquito growth, development, survival, reproduction, and disease pathogen transmission, as well as the interactions between microbiota and mosquito insecticide resistance. Overall, 429 studies were included in this review after filtering 8139 search results. Mosquito gut microbiota show a complex community structure with rich species diversity, dynamic changes in the species composition over time (season) and across space (environmental setting), and variation among mosquito species and mosquito developmental stages (larval vs. adult). The community composition of the microbiota plays profound roles in mosquito development, survival, and reproduction. There was a reciprocal interaction between the mosquito midgut microbiota and virus infection in mosquitoes. Wolbachia, Asaia, and Serratia are the three most studied bacteria that influence disease pathogen transmission. The insecticide resistance or exposure led to the enrichment or reduction in certain microorganisms in the resistant mosquitoes while enhancing the abundance of other microorganisms in insect-susceptible mosquitoes, and they involved many different species/genera/families of microorganisms. Conversely, microbiota can promote insecticide resistance in their hosts by isolating and degrading insecticidal compounds or altering the expression of host genes and metabolic detoxification enzymes. Currently, knowledge is scarce about the community structure of mosquito gut microbiota and its functionality in relation to mosquito pathogen transmission and insecticide resistance. The new multi-omics techniques should be adopted to find the links among environment, mosquito, and host and bring mosquito microbiota studies to the next level. [ABSTRACT FROM AUTHOR]

Objective Aedes albopictus is the main indigenous vector of dengue fever in China. Understanding the spatial genetic structure of Aedes albopictus populations, migration, and gene flow is crucial for the effective prevention and control of vector-borne diseases. Methods From June to September 2023, mosquitoes were collected and morphologically identified from eight different geographic locations across tropical, subtropical, and temperate zones of China. Genomic DNA was extracted from individual female mosquitoes, and the mitochondrial cytochrome C oxidase I gene was amplified and sequenced. Population genetic diversity and associated population characteristics were assessed using software such as BioEdit, DnaSP version 6, Arlequin 3.5, and Mega 11. Results A total of 233 samples from eight Aedes albopictus populations across the three climatic zones were successfully sequenced, yielding a gene fragment sequence of 632 bp with 19 variable sites and no insertion or deletion mutations. A total of 21 haplotypes were detected, with H4 being the dominant shared haplotype among the three climate types. Haplotype diversity (Hd) ranged from 0.191 (Beijing population) to 0.887 (Xishuangbanna population), and nucleotide diversity (Pi) ranged from 0.000 51 (Beijing population) to 0.002 98 (Xishuangbanna population), suggesting high haplotype diversity and low nucleotide diversity in Aedes albopictus. The genetic differentiation indices ranged from 0.026 to 0.641, with higher genetic differentiation between temperate and tropical/subtropical regions. The analysis of molecular variation supported that genetic differentiation mainly came from within populations (60.45%). Conclusions The ecological and climatic environment in the tropics results in higher genetic diversity of Aedes albopictus. Human activities have exacerbated the risk of dengue transmission across different climatic zones. [ABSTRACT FROM AUTHOR]

Objective To explore the genetic diversity of Aedes albopictus populations in plain, hilly, and mountainous areas of Hainan Province, and to analyze the genetic structure of Aedes albopictus populations in different terrain regions of Hainan Province. Methods Aedes albopictus were collected from the plain areas of Sanya and Haikou City, the hills of Danzhou and Tunchang City, and the mountainous areas of Baisha City in Hainan Province. DNA was extracted from a single mosquito and stored in a -80 °C refrigerator for use. Mitochondrial cytochrome C oxidase subunit I (mtDNA-CO I) was amplified by PCR and sequenced. The results were compared on the National Center for Biotechnology Information (NCBI) website, sequence peaks were observed using BioEdit 7.0, genetic diversity parameters were calculated using DnaSP v6, haplotype networks were constructed using PopART 1.7, and analysis of molecular variance (AMOVA) values were calculated using Arlequin to analyze differences between populations. Results A total of 414 mtDNA-CO I sequences were obtained from Aedes albopictus populations in 5 regions, with lengths of 663 bp. All sequences had five mutation sites, with a G+C content of 32.86% and an A+T content of 67.14%, consistent with mitochondrial DNA characteristics. Compared with other populations, the nucleotide diversity of the Danzhou and Tunchang populations in the plain and hilly areas was higher. The average nucleotide differences were higher in the Sanya, Tunchang, and Danzhou populations. Haploid analysis revealed 6 haplotypes, with H02 being the dominant haplotype. The Sanya and Tunchang populations had the highest number of haplotypes, while the Haikou and Sanya populations had exclusive haplotypes. Only the plains populations had unique haplotypes, while the hill and mountainous populations had relatively fewer haplotypes. The neutral results and mismatch distribution map indicated that the population of Aedes albopictus has recently expanded in all regions. The AMOVA value showed that the intra-population differences were greater than the inter-population differences. Conclusions The mtDNA-CO I gene can serve as a molecular marker for studying the genetic diversity of Aedes albopictus populations. The Sanya population in the plain region shows higher genetic diversity, and the two populations in the hilly region also have higher genetic diversity. However, the number of haplotypes is only higher in the Sanya population in the plains and the Danzhou population in the hills. [ABSTRACT FROM AUTHOR]