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The complex transmission profiles of vector-borne zoonoses (VZB) and vector-borne infections with animal reservoirs (VBIAR) complicate efforts to break the transmission circuit of these infections. To control and eliminate VZB and VBIAR, insecticide application may not be conducted easily in all circumstances, particularly for infections with sylvatic transmission cycle. As a result, alternative approaches have been considered in the vector management against these infections. In this review, we highlighted differences among the environmental, chemical, and biological control approaches in vector management, from the perspectives of VZB and VBIAR. Concerns and knowledge gaps pertaining to the available control approaches were discussed to better understand the prospects of integrating these vector control approaches to synergistically break the transmission of VZB and VBIAR in humans, in line with the integrated vector management (IVM) developed by the World Health Organization (WHO) since 2004.

Several vector-borne pathogens of primates have potential for human spillover. An example is the simian malaria Plasmodium knowlesi which is now a major public health problem in Malaysia. Characterization of exposure to mosquito vectors is essential for assessment of the force of infection within wild simian populations, however few methods exist to do so. Here we demonstrate the use of thermal imaging and mosquito magnet independence traps (MMIT) to assess the abundance, diversity and infection rates in mosquitoes host seeking near long-tailed macaque (Macaca fasicularis) sleeping sites in the Lower Kinabatangan Wildlife Sanctuary, Malaysian Borneo. The primary Plasmodium knowlesi vector, Anopheles balabacensis, was trapped at higher abundance near sleeping sites than control trees. Although none of the An. balabacensis collected (n = 15) were positive for P. knowlesi by PCR screening, two were infected with another simian malaria Plasmodium inui. Analysis of macaque stools from sleeping sites confirmed a high prevalence of Plasmodium infection, suspected to be P. inui. Recently, natural transmission of P. inui has been detected in humans and An. cracens in Peninsular Malaysia. The presence of P. inui in An. balabacensis here and previously in human-biting collections highlight its potential for spillover from macaques to humans in Sabah. We advocate the use of MMITs for non-invasive sampling of mosquito vectors that host seek on wild simian populations.

Additional file 1. Systematic review protocol.

Additional file 1: Table S1. The overall number of mosquito species collected using different trapping methods in four different locations in Peninsular Malaysia.

Additional file 1: Table S1. Summary of mosquito species used in the study from six states in Malaysia. Collection was carried out using human landing catch (HLC), mosquito magnetic trap and ovitrap. Table S2. Mosquito collection sites. Mosquitoes were collected from different settings: urban, village, island, forest and wetland across several states in Malaysia. Table S3. Anopheles samples with Plasmodium infections.

Multilingual abstracts in the five official working languages of the United Nations. (PDF 346 kb)

Additional file 2: Figure S1. Gel electrophoresis of AS-PCR products corresponding to the Ae. aegypti sodium channel gene mutation. a F1534C mutation: each of the three genotypes is shown. Lane 1: ultra-low range DNA ladder; Lane 2: wild-type homozygous (FF); Lane 3: heterozygous (FC); Lane 4: mutant homozygous (CC); Lane 5: negative control. b V1016G mutation: Lane 1: ultra-low range DNA ladder marker; Lane 2: mutant homozygous (GG); Lane 3: heterozygous (VG); Lane 4: wild-type homozygous (VV); Lane 5: negative control. c S989P mutation: Lane 1: 100 bp DNA ladder marker; Lanes 2, 3: wild-type homozygous (SS); Lanes 4, 5: heterozygous (SP); Lanes 6, 7: mutant homozygous (PP); Lanes 8, 9: negative control. Figure S2. Genotype sequence of V1016G mutation. Figure S3. Genotype sequence of S989P mutation. Figure S4. Genotype sequence of F1534C mutation.

Additional file 1: Table S1. Knockdown rate and mortality rate of adult female Ae. aegypti against various insecticides and synergists. Table S2. Knockdown times KT50 and KT99 of adult female Ae. aegypti to various insecticides. Table S3. Frequency of the F1534C mutation in the Ae. aegypti voltage-gated sodium channel gene within resistance and susceptible mosquitoes from nine different districts of Selangor determined using AS-PCR. Table S4. Frequency of the V1016G mutation in the Ae. aegypti voltage-gated sodium channel gene within resistance and susceptible mosquitoes from nine different districts of Selangor determined using AS-PCR. Table S5. Frequency of the S989P mutation in the Ae. aegypti voltage-gated sodium channel gene within resistance and susceptible mosquitoes from nine different districts of Selangor determined using AS-PCR.

Table S1. Study samples and origin. (DOCX 20 kb)

Additional file 4. Amino acid alignment of PkMSP1 (A) Domain I, (B) Domain III, (C) Domain V and (D) Domain VII between Thailand (n = 23) and Malaysian (n = 11) isolates. Period and hyphen represents identical amino acids and deletions, respectively. Thailand; AEQ01041-AEQ01055 and AFR68690–AFR68697. Malaysia; deduced amino acids ERR274221, ERR274222, ERR366425, ERR366426, ERR985374, ERR985377, ERR985416, ERR985418, and P_Malaysia_2 along with H-strain (CAQ39354). Others [M] and Others [T] refers to observed sequential variations within Malaysian or Thailand isolates, respectively.

Additional file 2. Accession number of PkMSP1 sequences used in the study and their geographical origin.

Total pools and number of mosquitoes positive by weeks using NS1 Rapid Test Kit. Table S2. Mosquito pools tested by NS1 and RT-PCR. (DOCX 15Â kb)

Total pools and number of mosquitoes positive by weeks using NS1 Rapid Test Kit. Table S2. Mosquito pools tested by NS1 and RT-PCR. (DOCX 15Â kb)

Background\ud In recent years, the primate malaria Plasmodium knowlesi has emerged in human populations throughout South East Asia, with the largest hotspot being in Sabah, Malaysian Borneo. Control efforts are hindered by limited knowledge of where and when people get exposed to mosquito vectors. It is assumed that exposure occurs primarily when people are working in forest areas, but the role of other potential exposure routes (including domestic or peri-domestic transmission) has not been thoroughly investigated.\ud Methodology/Principal Findings\ud We integrated entomological surveillance within a comprehensive case-control study occurring within a large hotspot of transmission in Sabah, Malaysia. Mosquitoes were collected at 28 pairs households composed of one where an occupant had a confirmed P. knowlesi infection within the preceding 3 weeks (“case”) and an associated “control” where no infection was reported. Human landing catches were conducted to measure the number and diversity of mosquitoes host seeking inside houses and in the surrounding peri-domestic (outdoors but around the household) areas. The predominant malaria vector species was Anopheles balabacensis, most of which were caught outdoors in the early evening (6pm - 9pm). It was significantly more abundant in the peri-domestic area than inside houses (5.5-fold), and also higher at case than control households (0.28±0.194 vs 0.17±0.127, p

BACKGROUND: Malaria cases caused by Plasmodium knowlesi, a simian parasite naturally found in long-tailed and pig-tailed macaques, are increasing rapidly in Sabah, Malaysia. One hypothesis is that this increase is associated with changes in land use. A study was carried out to identify the anopheline vectors present in different forest types and to observe the human landing behaviour of mosquitoes. METHODS: Mosquito collections were carried out using human landing catches at ground and canopy levels in the Tawau Division of Sabah. Collections were conducted along an anthropogenic disturbance gradient (primary forest, lightly logged virgin jungle reserve and salvage logged forest) between 18:00 and 22:00 h. RESULTS: Anopheles balabacensis, a vector of P. knowlesi, was the predominant species in all collection areas, accounting for 70 % of the total catch, with a peak landing time of 18:30-20:00 h. Anopheles balabacensis had a preference for landing on humans at ground level compared to the canopy (p

Additional file 1. Species accumulation curves for human landing catch sampling in primary forest at (a) Ground and (b) Canopy level, virgin jungle reserve at (c) Ground and (d) Canopy level, and logged forest at (e) Ground and (f) Canopy level. Shaded area indicates 95Â % confidence intervals.

Environmental variables used in the species distribution models and construction of the forest cover layers. Details of the covariate data used are provided together with their source details. The construction and validation of the intact and disturbed forest layers is described in detail. (DOCX 27Â kb)

The 0.025 and 0.975 quantile model predictions, and the top predictors, for each mosquito model. For each mosquito species, complex or group, the 0.025 and 0.975 quantile model outputs, masked out on islands outside each species or complex range, are provided with the mean AUC (Âą standard error) and the relative influence of the top predictors for that model. (DOCX 1331Â kb)

The 0.025 and 0.975 quantile model predictions, and the top predictors, for each mosquito model. For each mosquito species, complex or group, the 0.025 and 0.975 quantile model outputs, masked out on islands outside each species or complex range, are provided with the mean AUC (Âą standard error) and the relative influence of the top predictors for that model. (DOCX 1331Â kb)

The 0.025 and 0.975 quantile model predictions, and the top predictors, for each macaque species. For each macaque species the 0.025 and 0.975 quantile model outputs, masked out on islands outside each species range, are provided with the mean AUC (Âą standard error) and the relative influence of the top predictors for that species. (DOCX 1183Â kb)

Proportional land cover in areas with high predicted probability of species occurrence. Plots showing the relative density of pixels at each percentage land class coverage for all pixels where the probability of species occurrence was greater than 0.75, for each species. (DOCX 795Â kb)

Distributions of the model input data in space and time. The spatial distributions of the species occurrence data and background data are shown on a series of maps and their temporal distributions are shown by a series of histograms. (DOCX 1584Â kb)

Investigating the impact of using annual land cover data. The model was run using identical datasets and either 1) year-matched land cover data or 2) 2012 land cover data. The resulting distributions are shown with the AUCâ Âąâ standard error, and the top predictors with their relative influences. A map showing the difference between the two resulting distributions is also provided. (DOCX 2977Â kb)

Environmental variables used in the species distribution models and construction of the forest cover layers. Details of the covariate data used are provided together with their source details. The construction and validation of the intact and disturbed forest layers is described in detail. (DOCX 27Â kb)

Investigating the impact of using annual land cover data. The model was run using identical datasets and either 1) year-matched land cover data or 2) 2012 land cover data. The resulting distributions are shown with the AUCâ Âąâ standard error, and the top predictors with their relative influences. A map showing the difference between the two resulting distributions is also provided. (DOCX 2977Â kb)

One strain of Japanese encephalitis (JE) virus isolated from a pool of Ae. albopictus and Ae. butleri in Peninsula Malaysia in 1992 was sequenced for its PreM gene region, by direct sequencing the product from reverse transcriptase polymerase chain reaction (RTPCR). The sequence in the length of 240 nucleotides (nt) and deduced amino acid (AA) sequence were compared with the published sequences for the various JE virus strains from different geographical regions. This virus strain, MaSAr39692, showed a close homology to the strains from epidemic areas such as Japan, China, Taiwan, Sri Lanka and India. The homology between MaSAr39692 and JaOArS982 strain, for which entire genome sequence was first determined, was 95.8%, with 10 nt and 3 AA sequence divergence., 熱帯医学 Tropical medicine 36(2). p51-56, 1994

Additional file 1: Table S1. PCR primers used for detecting Plasmodium spp. in Anopheles specimens.

Additional file 5: Table S3. Total Anopheles specimens collected at study sites in Paus, Ranau and Keritan Ulu, Keningau.

Additional file 3: Table S2. Mean interaction statistic between habitat type and time period as predicted by GLMM. Habitat types: FE: forest edge; PG: playground; LH: longhouse; OP: oil palm plantation; BU: shrub bushes. Time periods are: early night (18:00–21:00 h); late night (21:00–00:00 h); predawn (00:00–03:00 h); dawn (03:00–06:00 h).

Additional file 3: Table S2. Mean interaction statistic between habitat type and time period as predicted by GLMM. Habitat types: FE: forest edge; PG: playground; LH: longhouse; OP: oil palm plantation; BU: shrub bushes. Time periods are: early night (18:00–21:00 h); late night (21:00–00:00 h); predawn (00:00–03:00 h); dawn (03:00–06:00 h).

Additional file 1: Table S1. PCR primers used for detecting Plasmodium spp. in Anopheles specimens.

Additional file 5: Table S3. Total Anopheles specimens collected at study sites in Paus, Ranau and Keritan Ulu, Keningau.

Background: Plasmodium knowlesi is a zoonotic pathogen, transmitted among macaques and to humans by anopheline mosquitoes. Information on P. knowlesi malaria is lacking in most regions so the first step to understand the geographical distribution of disease risk is to define the distributions of the reservoir and vector species. Methods: We used macaque and mosquito species presence data, background data that captured sampling bias in the presence data, a boosted regression tree model and environmental datasets, including annual data for land classes, to predict the distributions of each vector and host species. We then compared the predicted distribution of each species with cover of each land class. Results: Fine-scale distribution maps were generated for three macaque host species (Macaca fascicularis, M. nemestrina and M. leonina) and two mosquito vector complexes (the Dirus Complex and the Leucosphyrus Complex). The Leucosphyrus Complex was predicted to occur in areas with disturbed, but not intact, forest cover (> 60 % tree cover) whereas the Dirus Complex was predicted to occur in areas with 10–100 % tree cover as well as vegetation mosaics and cropland. Of the macaque species, M. nemestrina was mainly predicted to occur in forested areas whereas M. fascicularis was predicted to occur in vegetation mosaics, cropland, wetland and urban areas in addition to forested areas. Conclusions: The predicted M. fascicularis distribution encompassed a wide range of habitats where humans are found. This is of most significance in the northern part of its range where members of the Dirus Complex are the main P. knowlesi vectors because these mosquitoes were also predicted to occur in a wider range of habitats. Our results support the hypothesis that conversion of intact forest into disturbed forest (for example plantations or timber concessions), or the creation of vegetation mosaics, will increase the probability that members of the Leucosphyrus Complex occur at these locations, as well as bringing humans into these areas. An explicit analysis of disease risk itself using infection data is required to explore this further. The species distributions generated here can now be included in future analyses of P. knowlesi infection risk.