Machine Learning Predictions on Outpatient No-Show Appointments in a Malaysia Major Tertiary Hospital.

Introduction: A no-show appointment occurs when a patient does not attend a previously booked appointment. This situation can cause other problems, such as discontinuity of patient treatments as well as a waste of both human and financial resources. One of the latest approaches to address this issue is predicting no-shows using machine learning techniques. This study aims to propose a predictive analytical approach for developing a patient no-show appointment model in Hospital Kuala Lumpur (HKL) using machine learning algorithms. Methods: This study uses outpatient data from the HKL's Patient Management System (SPP) throughout 2019. The final data set has 246,943 appointment records with 13 attributes used for both descriptive and predictive analyses. The predictive analysis was carried out using seven machine learning algorithms, namely, logistic regression (LR), decision tree (DT), k-near neighbours (k-NN), Naïve Bayes (NB), random forest (RF), gradient boosting (GB) and multilayer perceptron (MLP). Results: The descriptive analysis showed that the no-show rate was 28%, and attributes such as the month of the appointment and the gender of the patient seem to influence the possibility of a patient not showing up. Evaluation of the predictive model found that the GB model had the highest accuracy of 78%, F1 score of 0.76 and area under the curve (AUC) value of 0.65. Conclusion: The predictive model could be used to formulate intervention steps to reduce no-shows, improving patient care quality.

Group IV Getah Virus in Culex Mosquitoes, Malaysia.

A new Getah virus (GETV) strain, B254, was isolated from Culex fuscocephalus mosquitoes captured at Mount Ophir, Malaysia, in 2012. Phylogenetic analyses revealed that GETV B254 is distinct from the old Malaysia GETV MM2021 strain but closely related to group IV GETV from Russia (LEIV16275Mag), China (YN12031), and Thailand (GETV/SW/Thailand/2017).

Courtship activity, copulation & insemination success in a mosquito vector fed a herbal aphrodisiac: Implications for sterile insect technology.

BACKGROUND & OBJECTIVES: In sterile insect technology (SIT), mating competitiveness is a pre-condition for the reduction of target pest populations and a crucial parameter for judging efficacy. Still, current SIT trials are being hindered by decreased effectiveness due to reduced sexual performance of released males. Here, we explored the possible role of a herbal aphrodisiac in boosting the mating activity of Aedes aegypti. METHODS: Males were fed one of two diets in this study: experimental extract of Eurycoma longifolia (MSAs) and sugar only (MSOs). Differences in life span, courtship latency, copulation activity and mating success were examined between the two groups. RESULTS: No deaths occurred among MSA and MSO males. Life span of MSOs was similar to that of MSAs. The courtship latency of MSAs was shorter than that of MSOs (P<0.01). MSAs had greater copulation success than MSOs (P<0.001). In all female treatments, MSAs mated more than MSOs, but the differences in rate were significant only in the highest female density (P<0.05). In MSAs, mating success varied significantly with female density (P<0.01), with the 20-female group (P<0.01) having the lowest rate. Single MSA had better mating success at the two lowest female densities. In MSOs, there were no significant differences in mating success rate between the different female densities. INTERPRETATION & CONCLUSIONS: Our results suggested that the herbal aphrodisiac, E. longifolia, stimulated the sexual activity of Ae. aegypti and may be useful for improving the mating competitiveness of sterile males, thus improving SIT programmes.

Adulticidal Susceptibility Evaluation of Aedes albopictus Using New Diagnostic Doses in Penang Island, Malaysia.

Insecticide-based vector control approaches are facing challenges due to the development of resistance in vector mosquitoes. Therefore, a proper resistance surveillance program using baseline lethal concentrations is crucial for resistance management strategies. Currently, the World Health Organization's (WHO) diagnostic doses established for Aedes aegypti and Anopheles species are being used to study the resistance status of Aedes albopictus. In this study, we established the diagnostic doses for permethrin, deltamethrin, and malathion using a known susceptible reference strain. Five field-collected populations were screened against these doses, following the WHO protocol. This study established the diagnostic dose of malathion at 2.4%, permethrin at 0.95%, and deltamethrin at 0.28%, which differ from the WHO doses for Aedes aegypti and Anopheles spp. Among the insecticides tested on the 5 wild populations, only deltamethrin showed high effectiveness. Different susceptibility and resistance patterns were observed with permethrin, malathion, and dichloro-diphenyl-trichloroethane (DDT) at 4%. This study may assist the health authorities to improve future chemical-based vector control operations in dengue-endemic areas.

Comparative Effectiveness of Insecticides for Use Against the House Fly (Diptera: Muscidae): Determination of Resistance Levels on a Malaysian Poultry Farm.

In this study, the toxicology of two commercial larvicides--cyromazine (Neporex 50SP) and ChCy (combination of chlorpyrifos and cypermethrin, Naga 505)--and five commercial adulticides--thiamethoxam (Agita 10WG), cyfluthrin (Responsar WP), lambda-cyhalothrin (Icon 2.8EC), fipronil (Regent 50SC), and imidacloprid (Toxilat 10WP)--was examined against the WHO/VCRU (World Health Organization/ Vector Control Research Unit) susceptible strain and the AYTW (Ayer Tawar) field strain of house fly, Musca domestica L. These pesticides were administered topically, in the diet, or as a dry residue treatment on plywood. Probit analysis using at least five concentrations and the concentration that was lethal to 50% (LC(50)) of the organisms was applied to compare the toxicology and resistance levels of the AYTW population to different insecticides. In the larvicide laboratory study, ChCy was more effective than cyromazine, with a significantly lower LC(50) value when administered topically or in the diet, although the AYTW population was susceptible to both larvicides with a resistance ratio (RR) <10. For the adulticide laboratory study, cyfluthrin and fipronil exhibited the lowest LC50 values of the adulticides, indicating that they are both effective at controlling adult flies, although lambda-cyhalothrin showed moderate resistance (RR = 11.60 by topical application; 12.41 by plywood treatment). Further investigation of ChCy, cyromazine, cyfluthrin, and fipronil under field conditions confirmed that ChCy and cyromazine strikingly reduced larval density, and surprisingly, ChCy also exhibited adulticidal activity, which significantly reduced adult fly numbers compared with the control group. Cyfluthrin and fipronil were also confirmed to be effective, with a significant reduction in adult fly numbers compared with the control group.

Degradation of Insecticides in Poultry Manure: Determining the Insecticidal Treatment Interval for Managing House Fly (Diptera: Muscidae) Populations in Poultry Farms.

It is crucial to understand the degradation pattern of insecticides when designing a sustainable control program for the house fly, Musca domestica (L.), on poultry farms. The aim of this study was to determine the half-life and degradation rates of cyromazine, chlorpyrifos, and cypermethrin by spiking these insecticides into poultry manure, and then quantitatively analyzing the insecticide residue using ultra-performance liquid chromatography. The insecticides were later tested in the field in order to study the appropriate insecticidal treatment intervals. Bio-assays on manure samples were later tested at 3, 7, 10, and 15 d for bio-efficacy on susceptible house fly larvae. Degradation analysis demonstrated that cyromazine has the shortest half-life (3.01 d) compared with chlorpyrifos (4.36 d) and cypermethrin (3.75 d). Cyromazine also had a significantly greater degradation rate compared with chlorpyrifos and cypermethrin. For the field insecticidal treatment interval study, 10 d was the interval that had been determined for cyromazine due to its significantly lower residue; for ChCy (a mixture of chlorpyrifos and cypermethrin), the suggested interval was 7 d. Future work should focus on the effects of insecticide metabolites on targeted pests and the poultry manure environment.

Revised Discriminating Lethal Doses For Resistance Monitoring Program on Aedes albopictus Against Temephos and Malathion in Penang Island, Malaysia.

Dengue vector control still heavily relies on the use of chemical insecticides, and the widespread use of insecticides has led to resistance in mosquitoes. The diagnostic dose is a key part of resistance monitoring. The present study corroborates the discriminating lethal doses of temephos and malathion based on dose-response of known susceptible strain of Aedes albopictus following the World Health Organization (WHO) diagnostic test procedure. Late 3rd and early 4th instars were tested with a range of larvicides to determine the lethal concentrations (LC50 and LC99) values. A slightly higher diagnostic dose of 0.020 mg/liter as compared with the WHO-established value of 0.012 mg/liter was observed for temephos. Meanwhile, a malathion diagnostic dose of 0.200 mg/liter is also reported here since there are no such reported values by WHO. Doubling the LC99 values of susceptible strains, 3 of the 5 wild-collected populations showed resistance to temephos and 2 showed incipient resistance; all 5 populations showed incipient resistance to malathion. The revised and established lethal diagnostic dose findings from the current work are crucial to elaborate on the variation in susceptibility of Ae. albopictus in future resistance monitoring programs in Malaysia.

Insecticide susceptibility status in two medically important mosquito vectors, Anopheles gambiae, and Culex quinquefasciatus to three insecticides commonly used in Niger State, Nigeria.

High resistance ability on insecticides among major mosquito vectors of diseases in Nigeria is of growing concern for severe control strategies. The objective of this study was to assess the susceptibility status of females Anopheles gambiae and Culex quinquefasciatus complexes mosquitoes to permethrin (21.5 µg/bottle-pyrethroids), propoxur(12.5 µg/bottle-carbamate) and malathion (50 µg/bottle organophosphate), in Niger State, North-Central, Nigeria. Anopheline and Culecine larvae were collected from the larval habitats of the studied sites (Bosso, Katcha, Lapai, and Shiroro) larvae and pupae were identified guided by standard keys and reared to adults in troughs. Insecticide susceptibility bioassays were performed according to the CDC bottle bioassay standard operating procedures on 3 days old, sugar-fed female Anopheles and Culex mosquitoes. Post-exposure mortality after 24hr and knockdown values for KDT50 were calculated. Knock-down at 1-hour insecticide exposure ranged (84-96 %) permethrin, (94-100 %) propoxur and (100 %) malathion for An. gambiae and (86-97 %) permethrin, (92-100 %) propoxur and (96-100 %) malathion for Cx. quinquefasciatus. Mortality, after 24hr post-exposure was 100 % in malathion, indicating the high effect of the insecticide. Tested samples were found potentially resistant to permethrin recorded against mosquitoes collected from all study sites, in two locations of the study sites to propoxur and one location site to malathion. All the tested mosquitoes were found to be potentially resistant to permethrin, however, mosquitoes tested in Katcha and Shiroro resist potentially to propoxur. Except, Culex quinqufasciatus from Lapai that partially resist malathion, all the tested mosquitoes were found to be susceptible to malathion, across the study sites.

Update on temporal and spatial abundance of dengue vectors in Penang, Malaysia.

It is important to obtain frequent measurements of the abundance, distribution, and seasonality of mosquito vectors to determine the risk of disease transmission. The number of cases of dengue infection has increased in recent years on Penang Island, Malaysia, with recurring epidemics. However, ongoing control attempts are being critically hampered by the lack of up-to-date information regarding the vectors. To overcome this problem, we examined the current situation and distribution of dengue vectors on the island. Residences throughout the urban, suburban, and rural areas were inspected through wet and dry seasons between February 2009 and February 2010. Two vectors were encountered in the survey, with Aedes aegypti present in especially high numbers mostly in urban areas. Similar observations were noted for Ae. albopictus in rural areas. The former species was more abundant in outdoor containers, while the latter showed almost equivalent abundance both outdoors and indoors. The dengue virus was active in both urban and rural areas, and the number of cases of infection was higher in areas where Ae. aegypti was predominant. The abundance of immature Ae. albopictus was positively correlated with rainfall (r2 = 0.461; P < 0.05), but this was not the case for Ae. aegypti. For both species, the size of immature populations tended to increase with increasing intensity of rain, but heavy rains resulted in population loss. In addition to updating data regarding the larval habitats and locations (outdoors and indoors), this study highlighted the importance of spatial vector control stratification, which has the potential to reduce costs in control programs.

An annotated image dataset for training mosquito species recognition system on human skin.

This paper introduces a new mosquito images dataset that is suitable for training and evaluating a recognition system on mosquitoes in normal or smashed conditions. The images dataset served mainly for the development a machine learning model that can recognize the mosquito in the public community, which commonly found in the smashed/damaged form by human. Especially the images of mosquito in hashed condition, which to the best of our knowledge, a dataset that fulfilled such condition is not available. There are three mosquito species in the dataset, which are Aedes aegypti, Aedes albopictus and Culex quinquefasciatus, and the images were annotated until species level due to the specimen was purely bred in a WHO accredited breeding laboratory. The dataset consists of seven root files, six root files that composed of six classes (each species with either normal landing, or random damaged conditions) with a total of 1500 images, and one pre-processed file which consists of a train, test and prediction set, respectively for model construction.

An annotated image dataset of medically and forensically important flies for deep learning model training.

Conventional methods to study insect taxonomy especially forensic and medical dipterous flies are often tedious, time-consuming, labor-intensive, and expensive. An automated recognition system with image processing and computer vision provides an excellent solution to assist the process of insect identification. However, to the best of our knowledge, an image dataset that describes these dipterous flies is not available. Therefore, this paper introduces a new image dataset that is suitable for training and evaluation of a recognition system involved in identifying the forensic and medical importance of dipterous flies. The dataset consists of a total of 2876 images, in the input dimension (224 × 224 pixels) or as an embedded image model (96 × 96 pixels) for microcontrollers. There are three families (Calliphoridae, Sarcophagidae, Rhiniidae) and five genera (Chrysomya, Lucilia, Sarcophaga, Rhiniinae, Stomorhina), and each class of genus contained five different variants (same species) of fly to cover the variation of a species.

Community-based mosquito surveillance: an automatic mosquito-on-human-skin recognition system with a deep learning algorithm.

BACKGROUND: Public community engagement is crucial for mosquito surveillance programs. To support community participation, one of the approaches is assisting the public in recognizing the mosquitoes that carry pathogens. Therefore, this study aims to build an automatic recognition system to identify mosquitos at the public community level. We construct a customized image dataset consisting of three mosquito species in either damaged or un-damaged body conditions. To distinguish the mosquito in harsh conditions, we explore two state-of-the-art deep learning (DL) architectures: (i) a freezing convolutional base, with partial trainable weights, and (ii) training the entire model with most of the trainable weights. We project a weighted feature map on different layers of the model to visualize the morphological region used by the model in classification and compared it with the morphological key used by the expert. RESULT: It was found that the model with architecture two and the Adam optimizer achieves at least 98% accuracy in mosquito and conditions identification and when implemented on an independent dataset, the Xception model generalizes the best result with an accuracy of 0.7775 and 0.795 precision. Moreover, most of the morphological regions used by the model are able to match those of the human expert. CONCLUSION: We report a customized DL model for performing pest mosquito taxonomy identification, and through visualization, some regions using computers to discriminate mosquito species could be adopted later in systematic identification. © 2022 Society of Chemical Industry.

Cadaver wrapping and arrival performance of adult flies in an oil palm plantation in northern Peninsular Malaysia.

There is accumulating evidence that criminals wrap dead bodies in an attempt to conceal evidence. To anticipate the forensic implications of this phenomenon, we examined whether flies that are naturally associated with cadavers exhibit a delay in attendance or differ in species composition and abundance patterns because of the presence of wrapping material. Wrapped and exposed carcasses of dead monkeys placed in an oil plantation in Kedah, Malaysia, were visited over 50 d. On daily visits to each of the six carcasses, visiting adult flies were sampled using hand nets. Flies of 12 families were encountered. Calliphoridae (Chrysomya rufifacies Macquart and C. megacephala (F.) was the most prevalent family, followed by Sphaeroceridae. Some families tended to be more abundant in WRCs (i.e., Calliphoridae, Muscidae, and Phoridae), whereas others (i.e., Piophilidae, Sepsidae, and Psychodidae) were more prevalent in exposed carcasses. Wrapping delayed the arrival of all fly species encountered, with delays varying from 1 to 13 d depending on species. Wrapping did not affect species composition of flies, but prolong the occurrence of some species. The results of the current study emphasize the need to take into consideration the presence of a wrap when estimating postmortem interval.

Development of a deep learning model from breeding substrate images: a novel method for estimating the abundance of house fly (Musca domestica L.) larvae.

BACKGROUND: The application of computer vision and deep learning to pest monitoring has recently received much attention. Although several studies have demonstrated the application of object detection to the number of pests on a substrate, for house flies (Musca domestica L.), in which the larvae were aggregated and overlapped together, the object detection technique was difficult to implement. We demonstrate a novel method for estimating larval abundance by using computer vision on larval breeding substrate, in which the reflective color and topography are affected by the size of the population. RESULTS: We demonstrate a method using a web-based tool to construct a deep learning model and later export the model for deployment. We train the model by using breeding substrate images with different spectra of illumination on known densities of larvae and evaluate the training model in both the test set and field-collected samples. In general, the model was able to predict the larval abundance by the laboratory-prepared breeding substrate with 87.56% to 94.10% accuracy, precision, recall, and F-score on the unseen test set, and white and green illumination performed significantly higher compared to other illuminations. For field samples, the model was able to obtain at least 70% correct predictions by using white and infrared illumination. CONCLUSION: Larval abundance can be monitored with computer vision and deep learning, and the monitoring can be improved by using more biochemistry parameters as the predictors and examples of field samples included building a more robust model. © 2021 Society of Chemical Industry.

Implications of the COVID-19 Lockdown on Dengue Transmission in Malaysia.

We aim to investigate the effect of large-scale human movement restrictions during the COVID-19 lockdown on both the dengue transmission and vector occurrences. This study compared the weekly dengue incidences during the period of lockdown to the previous years (2015 to 2019) and a Seasonal Autoregressive Integrated Moving Average (SARIMA) model that expected no movement restrictions. We found that the trend of dengue incidence during the first two weeks (stage 1) of lockdown decreased significantly with the incidences lower than the lower confidence level (LCL) of SARIMA. By comparing the magnitude of the gradient of decrease, the trend is 319% steeper than the trend observed in previous years and 650% steeper than the simulated model, indicating that the control of population movement did reduce dengue transmission. However, starting from stage 2 of lockdown, the dengue incidences demonstrated an elevation and earlier rebound by four weeks and grew with an exponential pattern. We revealed that Aedes albopictus is the predominant species and demonstrated a strong correlation with the locally reported dengue incidences, and therefore we proposed the possible diffusive effect of the vector that led to a higher acceleration of incidence rate.

Implementation of a deep learning model for automated classification of Aedes aegypti (Linnaeus) and Aedes albopictus (Skuse) in real time.

Classification of Aedes aegypti (Linnaeus) and Aedes albopictus (Skuse) by humans remains challenging. We proposed a highly accessible method to develop a deep learning (DL) model and implement the model for mosquito image classification by using hardware that could regulate the development process. In particular, we constructed a dataset with 4120 images of Aedes mosquitoes that were older than 12 days old and had common morphological features that disappeared, and we illustrated how to set up supervised deep convolutional neural networks (DCNNs) with hyperparameter adjustment. The model application was first conducted by deploying the model externally in real time on three different generations of mosquitoes, and the accuracy was compared with human expert performance. Our results showed that both the learning rate and epochs significantly affected the accuracy, and the best-performing hyperparameters achieved an accuracy of more than 98% at classifying mosquitoes, which showed no significant difference from human-level performance. We demonstrated the feasibility of the method to construct a model with the DCNN when deployed externally on mosquitoes in real time.

In Vitro Efficacy of Aqueous and Methanol Extract of Cassia siamea Against the Motility of Caenorhabditis elegans.

Gastrointestinal nematode infections can cause great losses in revenue due to decrease livestock production and animal death. The use of anthelmintic to control gastrointestinal nematode put a selection pressure on nematode populations which led to emergence of anthelmintic resistance. Because of that, this study was carried out to investigate the efficacy of aqueous and methanol extract of Cassia siamea against the motility of C. elegans Bristol N2 and C. elegans DA1316. Caenorhabditis elegans Bristol N2 is a susceptible strain and C. elegans DA1316 is an ivermectin resistant strain. In vitro bioassay of various concentrations of (0.2, 0.6, 0.8, 1.0 and 2.0 mg mL-1) aqueous and methanol extracts of C. siamea was conducted against the motility of L4 larvae of C. elegans Bristol N2 and C. elegans DA1316. The L4 larvae were treated with 0.02 µg mL-1 of ivermectin served as positive control while those in M9 solution served as negative control. The activity of the extracts was observed after 24 h and 48 h. A significant difference was recorded in the extract performance compared to control at (P < 0.001) after 48 h against the motility of the larvae of both strains. The methanol extracts inhibited the motility of C. elegans Bristol N2 by 86.7% as well as DA1316 up to 84.9% at 2.0 mg mL-1 after 48 h. The methanol extract was more efficient than aqueous extract (P < 0.05) against the motility of both strains of C. elegans. Cassia siamea may be used as a natural source of lead compounds for the development of alternative anthelmintic against parasitic nematodes as well ivermectin resistant strains of nematodes.

The Diet for Edible-Nest Swiftlets: Nutritional Composition and Cost of Life Stages of Megaselia scalaris Loew (Diptera: Phoridae) Bred on 3 Commercial Breeding Materials.

Megaselia scalaris (Loew) is one of the best-known diets for the swiftlet. Previous studies have addressed the problem of some mass rearing conditions for this insect; unfortunately, the details of the nutritional composition of the life stages and cost of the breeding materials were insufficiently reported, even though this information is crucial for farming the edible-nest swiftlet. We aimed to investigate the nutritional composition of the life stages of M scalaris on a cost basis using 3 common commercial breeding materials: chicken pellets (CPs), fish pellets (FPs), and mouse pellets (MPs). Modified Association of Official Analytical Chemists (AOAC) proximate and mineral analyses were carried out on the insect's third instar larvae, pupal, and adult stages to determine the nutritional composition. Regardless of the breeding materials, the adult stage of M scalaris had significantly higher crude protein than the other stages; the pupae were rich in calcium, which is required for egg production; and the third instar larvae had the highest amount of crude fat compared with the other stages. Regarding the energy content, there were no significant differences among the stages according to the breeding materials. In terms of nutritional cost, CP was the most economic breeding material and generated the highest amount of nutrients per US dollar (US $). Different life stages of M scalaris were used by the swiftlets by supplying the required nutrients, and future studies should focus on effective diet feeding methods.

Substrate Moisture Affects the Development of Megaselia scalaris (Diptera: Phoridae): An Implication of the Growth Circumstances of the Fly in Forensic Entomology.

Megaselia scalaris (Loew) (Diptera: Phoridae) provides great evidential value in estimating the postmortem interval (PMI) compared with other dipterans due to its common occurrence on human corpses both indoors and in concealed environments. Studies have focused on the effect of temperature, larval diet, and photoperiod on the development of the species; however, knowledge of M. scalaris development at different moisture levels is insufficient. This study aimed to investigate the effects of substrate moisture on the larval development time, pupal recovery, pupal weight, adult emergence, and adult head width of M. scalaris. The larvae were reared in five replicates on substrates with six moisture levels ranging from 50 to 90%. Larvae and puparia were sampled daily, and the collection time, number, and weight were recorded, measured, and then compared using multivariate analysis of variance with a post hoc least significant difference test. Larvae developed most quickly (3.75 ± 0.04 d) at 50% substrate moisture; the larvae were able to survive in extremely wet substrates (90% moisture), but the development time was significantly longer (6.48 ± 0.19 d). Moisture greatly influenced the pupation rate and adult emergence but showed a weak effect on the pupae weight and adult head width. Due to the significance of moisture on the development of M. scalaris, PMI estimation using M. scalaris with cadavers of different moisture content must be carefully conducted to avoid inaccuracy.

Seroprevalence of dengue among healthy adults in a rural community in Southern Malaysia: a pilot study.

BACKGROUND: The frequency and magnitude of dengue epidemics continue to increase exponentially in Malaysia, with a shift in the age range predominance toward adults and an expansion to rural areas. Despite this, information pertaining to the extent of transmission of dengue virus (DENV) in the rural community is lacking. This community-based pilot study was conducted to establish DENV seroprevalence amongst healthy adults in a rural district in Southern Malaysia, and to identify influencing factors. METHODS: In this study undertaken between April and May 2015, a total of 277 adult participants were recruited from households across three localities in the Sungai Segamat subdistrict in Segamat district. Sera were tested for immunoglobulin G (IgG) (Panbio® Dengue Indirect IgG ELISA/high-titer capture) and immunoglobulin M (IgM) (Panbio®) antibodies. The plaque reduction neutralization test (PRNT) was conducted on random samples of IgG-positive sera for further confirmation. Medical history and a recall of previous history of dengue were collected through interviews, whereas sociodemographic information was obtained from an existing database. RESULTS: The overall seroprevalence for DENV infection was 86.6% (240/277) (95% CI: 83-91%). Serological evidence of recent infection (IgM/high-titer capture IgG) was noted in 11.2% (31/277) of participants, whereas there was evidence of past infection in 75.5% (209/277) of participants (indirect IgG minus recent infections). The PRNT assay showed that the detected antibodies were indeed specific to DENV. The multivariate analysis showed that the older age group was significantly associated with past DENV infections. Seropositivity increased with age; 48.5% in the age group of <25 years to more than 85% in age group of >45 years (P < 0.001). No associations with occupation, study site, housing type, comorbidity, educational level, and marital status were observed, although the latter two were statistically significant in the univariate analysis. None of the studied factors were significantly associated with recent DENV infections in the multivariate analysis, although there was a pattern suggestive of recent outbreak in two study sites populated predominately by Chinese people. The majority of infections did not give rise to recognizable disease (either asymptomatic or nonspecific symptoms) as only 12.9% of participants (31/240) recalled having dengue in the past. CONCLUSIONS: The predominantly rural community under study had a very high previous exposure to dengue. The finding of a high proportion of unreported cases possibly due to subclinical infections underscores the need for enhanced surveillance and control methods. This finding also has implications for measuring disease burden, understanding transmission dynamics, and hypothesizing effects on DENV vaccine efficacy and uptake.