Members of the Maculatus group are important malaria vectors in the border regions of Thailand. However, the role of each species in malaria transmission remains unclear because of their highly similar morphologies, making them difficult to be differentiated. Whereas An. pseudowillmori may be identified by the color pattern of some scales on abdomen and wings, the distinction between An. maculatus and An. sawadwongporni relies on the wings only. Scales are labile structures, as they may be accidentally removed during capture and transportation to the laboratory. To discriminate among the species of this complex, we tested the suitability of geometric techniques. Shape variables were used as input for discriminant analyses and validated reclassification. Both landmark-and outline-based geometric techniques disclosed significant differences between the three species. For the delicate An. maculatus-An. sawadwongporni distinction, the outline-based approach appeared as the most promising, with validated reclassification scores reaching 93%, as compared to 77% obtained by landmark data. For An. pseudowillmori, reclassification scores were 100% and 94%, respectively. Geometric morphometrics may provide an alternative and useful complement for discriminating members of the Maculatus group.

It is often challenging to identify mosquito vectors in the field based on morphological features due to their similar morphologies and difficulties in obtaining undamaged samples but is required for their successful control. Geometric morphometrics (GM) overcomes this issue by analyzing a suite of traits simultaneously and has the added advantages of being easy to use, low cost, and quick. Therefore, this research compared the efficiency and precision of landmark- and outline-based GM techniques for separating species of mosquitoes in Huay Nam Nak village, Ratchaburi Province, Thailand. This research collected 273 individuals belonging to seven species: Anopheles barbirostris, An. subpictus, Culex quinquefasciatus, Cx. vishnui, Cx. whitmorei, Aedes aegypti, and Ae. albopictus. Both landmark-based and outline-based GM techniques could identify malaria vectors in this area to the genus level successfully and were also very effective for identifying the malaria vectors Anopheles spp. and the dengue vectors Aedes spp. to the species level. However, they were less effective for distinguishing between species of Culex. Therefore, GM represents a valuable tool for the identification of mosquito vectors in the field, which will facilitate their successful control.

Malaria is transmitted by female mosquitoes in the genus Anopheles and is a major public health issue. Different species of Anopheles mosquitoes have different epidemiological characteristics, behaviors, and ecological requirements, and so an understanding of their biology and ecology in a particular area is critical for successful disease control. The aim of this study was to determine which environmental factors are associated with Anopheles larvae in a malaria-endemic area in Ratchaburi Province, Thailand, which shares a border with Myanmar. In October 2016, we collected mosquito larvae and measured six environmental factors at 10 study sites located along Lam Pachi River, which flows through Huay Nam Nak village in Ratchaburi Province. We found two species of Anopheles larvae (An. subpictus sensu lato (s.l.) Grassi and An. barbirostris s.l. van der Wulp) at 7 of the 10 study sites, the numbers of which significantly differed between sites (p < 0.05). Pearson correlation analysis showed that the numbers of larvae of both species were significantly positively correlated with the dissolved oxygen level (p < 0.01) and significantly negatively correlated with the width of the river (p < 0.05) and pH (p < 0.01). By contrast, turbidity, water depth, and water temperature were not associated with larval abundance. Mosquito species which belong to genus Anopheles are considered to be of public health and medical importance. Therefore, Anopheles mosquito surveillance and control in the study sites are essential. This information will facilitate vector-borne disease control and improve our understanding of the biology of Anopheles vectors in rivers located along international borders, further reducing the number of patients in this malaria-endemic area.

Anopheles (Cellia) dirus Peyton & Harrison and Anopheles baimaii Sallum & Peyton are sibling species within the Dirus complex belonging to the Leucosphyrus group, and have been incriminated as primary vectors of malaria in Thailand. In the present study, DNA barcoding and geometric morphometrics were used to distinguish between An. dirus and An. baimaii in the international border areas, Trat Province, eastern Thailand. Our results revealed that DNA barcoding based on the cytochrome c oxidase subunit I gene could not be used to distinguish An. dirus from An. baimaii. The overlapping values between intra- and interspecific genetic divergence indicated no barcoding gap present for An. dirus and An. baimaii (ranging from 0 to 0.99%). However, the results of the geometric morphometric analysis based on the wing shape clearly distinguished An. dirus and An. baimaii, with 92.42% of specimens assigned to the correct species. We concluded that geometric morphometrics is an effective tool for the correct species identification of these two malaria vectors. Our findings could be used to make entomological surveillance information more accurate, leading to further effective mosquito control planning in Thailand and other countries in Southeast Asia.

Background Anopheles sawadwongporni Rattanarithikul & Green, Anopheles maculatus Theobald and Anopheles pseudowillmori (Theobald) of the Anopheles maculatus group (Diptera: Culicidae) are recognized as potential malaria vectors in many countries from the Indian subcontinent through Southeast Asia to Taiwan. A number of malaria vectors in malaria hotspot areas along the Thai-Myanmar border belong to this complex. However, the species distribution and dynamic trends remain understudied in this malaria endemic region. Methods Mosquitoes of the Maculatus group were collected using CDC light traps every other week from four villages in Tha Song Yang District, Tak Province, Thailand from January to December 2015. Adult female mosquitoes were morphologically identified on site using taxonomic keys. Molecular species identification was performed by multiplex PCR based on the internal transcribed spacer 2 (ITS2) region of ribosomal DNA (rDNA) and sequencing of the cox1 gene at a DNA barcoding region in a subset of 29 specimens. Results A total of 1328 An. maculatus (sensu lato) female mosquitoes were captured with An. maculatus, An. sawadwongporni and An. pseudowilmori accounting for 75.2, 22.1 and 2.7% respectively. The field captured mosquitoes of the Maculatus group were most abundant in the wet season and had a preferred distribution in villages at higher elevations. The phylogenetic relationships of 29 cox1 sequences showed a clear-cut separation of the three member species of the Maculatus group, with the An. pseudowillmori cluster being separated from An. sawadwongporni and An. maculatus. Conclusions This study provides updated information for the species composition, seasonal dynamics and microgeographical distribution of the Maculatus group in malaria-endemic areas of western Thailand. This information can be used to guide the planning and implementation of mosquito control measures in the pursuance of malaria transmission.

Mosquito-borne diseases are a major public health issue in nearly all tropical and subtropical countries, making vector control imperative. The mosquito trapping box is one type of mosquito traps that is popular in some areas because it is affordable, environmentally friendly, and easy to produce. This research investigated whether the effectiveness of the mosquito trapping box could be increased through the addition of various physical factors, including a wooden frame, black cotton cloth, a fan, carbon dioxide (CO2), and heat, by testing a range of box designs in the Samut Songkhram Province, Thailand, between December 2016 and January 2017. We found that trapping boxes constructed with Pinus kesiya wood caught more mosquitoes than those constructed with two other types of wood or aluminum. We also found that mosquito trapping boxes were more effective when more factors were added, although these differences were only significant for black cotton cloth and CO2. These findings will guide the future development of mosquito trapping boxes for effective mosquito control in other areas, helping to reduce the incidence of mosquito-borne diseases.

Samut Songkhram is one of popular tourist destinations in Thailand; however, it is the very high risk province of the dengue hemorrhagic fever (DHF) outbreak. Therefore, it is essential and urgent to monitor the tourists within the areas from the DHF. This research aimed to study the application of Geographic Information System (GIS) in DHF risk assessment and to study factors influencing of this province. The researcher collected 11 factors data including population density, household number, elevation, temperature, humidity, rainfall, residential areas, drainage areas, agricultural areas and man-made and natural water resources from related organizations to analyze relationship with DHF patients in the province. With the Pearson's Correlations statistic, there were four main factors relating the DHF incidence including population density, household number, residential areas and man-made water resources. According to the created GIS model of DHF risk assessment, it was discovered that 9% of the total areas were the very high risk areas, 23.89% were the high risk areas, 13.14% were the moderate risk areas, and 53.97% were the low risk areas. At a district level including Muang Samut Songkham, Bang Khonthi and Amphawa, it was found that Muang Samut Songkham was the only very high risk area covering 79.78km 2 . At a subdistrict level, Mae Khlong and Lat Yai were the very high risk areas. The factors influencing showed residential areas. After applying the GIS in DHF risk assessment, it was demonstrated that the GIS was one of an effective tools for DHF surveillance.

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