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Prediction of lead seven day minimum and maximum surface air temperature using neural network and genetic programming

K. Ramesh, P. Ramalakshmi, R. Anitha

Sains Malaysiana, 2015;44:1389-1396.

The determination of variance of surface air temperature is very essential since it has a direct impact on vegetation, environment and human livelihood. Forecast of surface air temperature is difficult because of the complex physical phenomenon and the random-like behavior of atmospheric system which influences the temperature event on the earth surface. In this study, forecast models based on artificial neural network (ANN) and genetic programming (GP) approaches were proposed to predict lead seven days minimum and maximum surface air temperature using the weather parameters observed at the station Chennai, India. The outcome of this study stated that models formulated using ANN approach are more accurate than genetic programming for all seven days with the highest coefficient of determination (R2), least mean absolute error (MAE), root mean square error (RMSE) and mean absolute percentage error (MAPE) on deployment with independent test dataset. ANN models give statistically acceptable mean absolute error of 0.59oC for lead day one in minimum temperature forecast and 0.86oC variance for lead day one in maximum temperature forecast. The study also clarified that the level of accuracy of the proposed prediction models were found to be better for smaller lead days when compared with higher lead days with both approaches.

Matched MeSH terms: Weather
Fulltext Predicting physical time series using dynamic ridge polynomial neural networks

Al-Jumeily D, Ghazali R, Hussain A

PLoS One, 2014;9(8):e105766.
PMID: 25157950 DOI: 10.1371/journal.pone.0105766

Forecasting naturally occurring phenomena is a common problem in many domains of science, and this has been addressed and investigated by many scientists. The importance of time series prediction stems from the fact that it has wide range of applications, including control systems, engineering processes, environmental systems and economics. From the knowledge of some aspects of the previous behaviour of the system, the aim of the prediction process is to determine or predict its future behaviour. In this paper, we consider a novel application of a higher order polynomial neural network architecture called Dynamic Ridge Polynomial Neural Network that combines the properties of higher order and recurrent neural networks for the prediction of physical time series. In this study, four types of signals have been used, which are; The Lorenz attractor, mean value of the AE index, sunspot number, and heat wave temperature. The simulation results showed good improvements in terms of the signal to noise ratio in comparison to a number of higher order and feedforward neural networks in comparison to the benchmarked techniques.

Matched MeSH terms: Weather
Fulltext Population's health information-seeking behaviors and geographic variations of stroke in Malaysia: an ecological correlation and time series study

Ganasegeran K, Ch'ng ASH, Aziz ZA, Looi I

Sci Rep, 2020 Jul 09;10(1):11353.
PMID: 32647336 DOI: 10.1038/s41598-020-68335-1

Stroke has emerged as a major public health concern in Malaysia. We aimed to determine the trends and temporal associations of real-time health information-seeking behaviors (HISB) and stroke incidences in Malaysia. We conducted a countrywide ecological correlation and time series study using novel internet multi-timeline data stream of 6,282 hit searches and conventional surveillance data of 14,396 stroke cases. We searched popular search terms related to stroke in Google Trends between January 2004 and March 2019. We explored trends by comparing average relative search volumes (RSVs) by month and weather through linear regression bootstrapping methods. Geographical variations between regions and states were determined through spatial analytics. Ecological correlation analysis between RSVs and stroke incidences was determined via Pearson's correlations. Forecasted model was yielded through exponential smoothing. HISB showed both cyclical and seasonal patterns. Average RSV was significantly higher during Northeast Monsoon when compared to Southwest Monsoon (P

Matched MeSH terms: Weather
Fulltext Photovoltaic Grid-Connected Modeling and Characterization Based on Experimental Results

Humada AM, Hojabri M, Sulaiman MH, Hamada HM, Ahmed MN

PLoS One, 2016;11(4):e0152766.
PMID: 27035575 DOI: 10.1371/journal.pone.0152766

A grid-connected photovoltaic (PV) system operates under fluctuated weather condition has been modeled and characterized based on specific test bed. A mathematical model of a small-scale PV system has been developed mainly for residential usage, and the potential results have been simulated. The proposed PV model based on three PV parameters, which are the photocurrent, IL, the reverse diode saturation current, Io, the ideality factor of diode, n. Accuracy of the proposed model and its parameters evaluated based on different benchmarks. The results showed that the proposed model fitting the experimental results with high accuracy compare to the other models, as well as the I-V characteristic curve. The results of this study can be considered valuable in terms of the installation of a grid-connected PV system in fluctuated climatic conditions.

Matched MeSH terms: Weather
Parental perspective of trigger factors in asthmatic children

Fadzil, A., Nurzila, M.Z.

Malaysian Journal of Paediatrics and Child Health, 2005;14(1):51-57.
MyJurnal

Introduction: Parents play an important role in the management of their asthmatic children. Thus the ability of parents to recognise asthma trigger factors are very important.
Objectives: The objectives of this study were to identify the trigger factors that were recognised by parents to cause acute exacerbation in their children and analyse the association of these factors with severity of asthma and parental asthma knowledge.
Methods: Sixty-seven parents were interviewed to identify factors that can exacerbate acute asthmatic attack in their asthmatic children. The factors were then categorised as: infection, exercise, allergen, irritant, emotion and weather. The profiles of children were asthma severity status, duration of asthma, age, frequency of admission and steroid dosage. Parents' profiles were their age, number of asthmatic children and the level of asthma knowledge.
Result: Fifty-six (83.5%) parents identified more than one trigger factor for their children's exacerbation. The commonest frequency was two trigger factors (31.3%). Upper respiratory tract infection (77.6%) was the commonest trigger factor. There was no association between the number of trigger factors with the severity of asthma and level of parental asthma knowledge. The number of trigger factors significantly correlated with asthma duration (r = 0.33, p = 0.006). The asthma severity was associated significantly with weather (p = 0.042) but not with other trigger factors.
Conclusion: The majority of parents recognised more than one trigger factors to cause asthma exacerbation.

Matched MeSH terms: Weather
Fulltext Optimised deep neural network model to predict asthma exacerbation based on personalised weather triggers

Haque R, Ho SB, Chai I, Abdullah A

F1000Res, 2021;10:911.
PMID: 34745565 DOI: 10.12688/f1000research.73026.1

Background - Recently, there have been attempts to develop mHealth applications for asthma self-management. However, there is a lack of applications that can offer accurate predictions of asthma exacerbation using the weather triggers and demographic characteristics to give tailored response to users. This paper proposes an optimised Deep Neural Network Regression (DNNR) model to predict asthma exacerbation based on personalised weather triggers. Methods - With the aim of integrating weather, demography, and asthma tracking, an mHealth application was developed where users conduct the Asthma Control Test (ACT) to identify the chances of their asthma exacerbation. The asthma dataset consists of panel data from 10 users that includes 1010 ACT scores as the target output. Moreover, the dataset contains 10 input features which include five weather features (temperature, humidity, air-pressure, UV-index, wind-speed) and five demography features (age, gender, outdoor-job, outdoor-activities, location). Results - Using the DNNR model on the asthma dataset, a score of 0.83 was achieved with Mean Absolute Error (MAE)=1.44 and Mean Squared Error (MSE)=3.62. It was recognised that, for effective asthma self-management, the prediction errors must be in the acceptable loss range (error<0.5). Therefore, an optimisation process was proposed to reduce the error rates and increase the accuracy by applying standardisation and fragmented-grid-search. Consequently, the optimised-DNNR model (with 2 hidden-layers and 50 hidden-nodes) using the Adam optimiser achieved a 94% accuracy with MAE=0.20 and MSE=0.09. Conclusions - This study is the first of its kind that recognises the potentials of DNNR to identify the correlation patterns among asthma, weather, and demographic variables. The optimised-DNNR model provides predictions with a significantly higher accuracy rate than the existing predictive models and using less computing time. Thus, the optimisation process is useful to build an enhanced model that can be integrated into the asthma self-management for mHealth application.

Matched MeSH terms: Weather
Numbers of Leptotrombidium (Leptotrombidium) deliense (Acarina: trombiculidae) and prevalence of Rickettsia tsutsugamushi in adjacent habitats of peninsular Malaysia

Roberts LW, Muul I, Robinson DM

Southeast Asian J. Trop. Med. Public Health, 1977 Jun;8(2):207-13.
PMID: 411177

Numbers of L. (L.) deliense larvae were determined in adjacent habitats over a 16 month period. Both R. argentiventer and R. tiomanicus were highly efficient hosts for L. (L.) deliense. R. argentiventer was host to significantly greater numbers of chiggers per rat than was R. tiomanicus. The 2 habitats were similar in numbers of chiggers collected. No consistent correlation was apparent between numbers of chiggers and any single weather factor, but the chigger population seemed to be adversely affected by a 2 month period during which total evaporation greatly exceeded total rainfall. Direct fluorescent antibody examination of tissues from unfed L. (L.) deliense showed that 2 of 420 larvae (0.5%) contained organisms morphologically resembling R. tsutsugamushi. Considering the vector load and numbers of chiggers being returned to the ground by a given host, a rate of 0.5% appeared adequate to account for the prevalence rate of R. tsutsugamushi observed in the 2 host species.

Matched MeSH terms: Weather
Fulltext New COVID-19 variant (B.1.1.7): Forecasting the occasion of virus and the related meteorological factors

Rendana M, Idris WMR

J Infect Public Health, 2021 Oct;14(10):1320-1327.
PMID: 34175236 DOI: 10.1016/j.jiph.2021.05.019

BACKGROUND: World Health Organization has reported fifty countries have now detected the new coronavirus (B.1.1.7 variant) since a couple of months ago. In Indonesia, the B.1.1.7 cases have been found in several provinces since January 2021, although they are still in a lower number than the old variant of COVID-19. Therefore, this study aims to create a forecast analysis regarding the occasions of COVID-19 and B.1.1.7 cases based on data from the 1st January to 18th March 2021, and also analyze the association between meteorological factors with B.1.1.7 incidences in three different provinces of Indonesia such as the West Java, South Sumatra and East Kalimantan.
METHODS: We used the Autoregressive Moving Average Models (ARIMA) to forecast the number of cases in the upcoming 14 days and the Spearman correlation analysis to analyze the relationship between B.1.1.7 cases and meteorological variables such as temperature, humidity, rainfall, sunshine, and wind speed.
RESULTS: The results of the study showed the fitted ARIMA models forecasted there was an increase in the daily cases in three provinces. The total cases in three provinces would increase by 36% (West Java), 13.5% (South Sumatra), and 30% (East Kalimantan) as compared with actual cases until the end of 14 days later. The temperature, rainfall and sunshine factors were the main contributors for B.1.1.7 cases with each correlation coefficients; r = -0.230; p < 0.05, r = 0.211; p < 0.05 and r = -0.418; p < 0.01, respectively.
CONCLUSIONS: We recapitulated that this investigation was the first preliminary study to analyze a short-term forecast regarding COVID-19 and B.1.1.7 cases as well as to determine the associated meteorological factors that become primary contributors to the virus spread.

Matched MeSH terms: Weather*
Fulltext Motivators and barriers of physical activity among private office workers in Selangor

Nui Jia Jun, Khairil Shazmin Kamarudin, Asma Ali, Noor Salihah Zakaria

Malaysian Journal of Medicine and Health Sciences, 2020;16(1):58-65.
MyJurnal

Introduction: In Malaysia, private office workers tend to be more physically inactive due to work burden. This study aimed to determine physical activity level, motivation factors and barrier towards physical activity among private office workers. Methods: A cross sectional study using convenience sampling was conducted at nine private com- panies in Selangor involving 106 office workers aged 21 to 55 years old. Self-administered questionnaires includ- ing Global Physical Activity Questionnaire (GPAQ), Physical Activity and Leisure Motivation Scale (PALMS) and Physical Activity Barrier (PAB) were administered. Results: Over half of the respondents (58.5%) were having low physical activity level. The main motivation factors include physical condition, psychological condition and mastery. Meanwhile, tired after work, laziness, lack of discipline, family commitment and adverse weather were the main perceived barriers. A weak positive correlation was found between total motivation score and total physical activity (r=0.296; p=0.002). In contrast, there was a weak negative correlation between barriers and total physical activity (r=-0.237; p=0.015). Conclusion: The current physical activity level, its main motivation factors and barriers among private office workers were identified, providing an opportunity to create effective setting-based health promotion and intervention. It is also recommended that policy suggestions are made to influence and prepare essential partners (e.g. companies and employees) to promote ways of incorporating physical activity into one’s daily routine.

Matched MeSH terms: Weather
Fulltext Monthly distribution map of carbon monoxide (CO) from AIRS over Peninsular Malaysia, Sabah and Sarawak for the year 2003

Jasim M. Rajab, Mat Jafri, M.Z, Lim, H.S., Abdullah, K.

Pertanika Journal of Science & Technology, 2011;19(3):89-96.
MyJurnal

Carbon monoxide (CO) is a ubiquitous, an indoor and outdoor air pollutant. It is not a significant greenhouse gas as it absorbs little infrared radiation from the Earth. It is produced by the incomplete combustion of fossil fuels, and biomass burning. The CO data are obtained from Atmospheric Infrared Sounder (AIRS) onboard NASA’s Aqua satellite. The AIRS provides information for several greenhouse gases, CO2, CH4, CO, and O3 as a one goal of the AIRS instrument (included on the EOS Aqua satellite launched, May 4, 2002) as well as to improve weather prediction of the water and energy cycle. The results of the analysis of the retrieved CO total column amount (CO_total_column_A) as well as effective of the CO volume mixing ratio (CO_VMR_eff_A), Level-3 monthly (AIR*3STM) 1º*1º spatial resolution, ascending are used to study the CO distribution over the East and West Malaysia for the year 2003. The CO maps over the study area were generated by using Kriging Interpolation technique and analyzed by using Photoshop CS. Variations in the biomass burning and the CO emissions where noted, while the highest CO occurred at late dry season in the region which has experienced extensive biomass burning and greater draw down of CO occurred in the pristine continental environment (East Malaysia). In all cases, the CO concentration at West Malaysia is higher than East Malaysia. The southeastern Sarawak (lat. 3.5˚ - long. 115.5˚) is less polluted regions and less the CO in most of times in the year. Examining satellite measurements revealed that the enhanced CO emission correlates with occasions of less rainfall during the dry season.

Matched MeSH terms: Weather
Modern analytical and bioanalytical technologies and concepts for smart and precision farming

Tsong JL, Khor SM

Anal Methods, 2023 Jul 06;15(26):3125-3148.
PMID: 37376849 DOI: 10.1039/d3ay00647f

Unpredictable natural disasters, disease outbreaks, climate change, pollution, and war constantly threaten food crop production. Smart and precision farming encourages using information or data obtained by using advanced technology (sensors, AI, and IoT) to improve decision-making in agriculture and achieve high productivity. For instance, weather prediction, nutrient information, pollutant assessment, and pathogen determination can be made with the help of new analytical and bioanalytical methods, demonstrating the potential for societal impact such as environmental, agricultural, and food science. As a rising technology, biosensors can be a potential tool to promote smart and precision farming in developing and underdeveloped countries. This review emphasizes the role of on-field, in vivo, and wearable biosensors in smart and precision farming, especially those biosensing systems that have proven with suitably complex and analytically challenging samples. The development of various agricultural biosensors in the past five years that fulfill market requirements such as portability, low cost, long-term stability, user-friendliness, rapidity, and on-site monitoring will be reviewed. The challenges and prospects for developing IoT and AI-integrated biosensors to increase crop yield and advance sustainable agriculture will be discussed. Using biosensors in smart and precision farming would ensure food security and revenue for farming communities.

Matched MeSH terms: Weather
Microplastics in the freshwater and terrestrial environments: Prevalence, fates, impacts and sustainable solutions

Wong JKH, Lee KK, Tang KHD, Yap PS

Sci Total Environ, 2020 Jun 01;719:137512.
PMID: 32229011 DOI: 10.1016/j.scitotenv.2020.137512

The ubiquitous occurrences of microplastics in the environment have raised much concern and resulted in voluminous studies related to microplastics. Studies on microplastics pollution of the marine environment have received significantly higher attention compared to those of the freshwater and terrestrial environments. With the impetus to better understand microplastics in the freshwater and terrestrial environments, this review elucidates the findings of >100 articles related to the prevalence, fates and impacts of microplastics therein and the sustainable solutions, mostly in the past 10 years. This review shows the interconnection between terrestrial and freshwater microplastics with wastewater and sewage treatment plants as the most significant contributors of environmental microplastics via sludge and effluent discharges. Microplastics in both ecosystems comprise the primary and secondary forms with the latter resulted from weathering of the former. Besides retaining in soil and infiltrating with rainwater underground, terrestrial microplastics also enter the freshwater environment. The environmental microplastics interact with the biotic and abiotic components resulting in entrainment, settlement, biofouling, degradation, fragmentation and entry into the food chain, with subsequent transfer across the food chain. The abundance of environmental microplastics is attributed to population density and urbanization though tidal cycle, storms, floods and human activities can affect their distribution. The leaching of additives from microplastics poses major health concern and sustainable solutions target at reduction of plastics use and disposal, substitution with bioplastics and wastewater treatment innovations. Further studies on classification, detection, characterization and toxicity of microplastics are necessary to permit more effective formulation of solutions.

Matched MeSH terms: Weather
Fulltext Microclimatic performance of courtyard residential buildings in Kafanchan-Nigeria

Markus Bulus, Lim, Yaik-Wah, Malsiah Hamid

Journal of Advanced Research Design, 2017;37(1):16-25.
MyJurnal

The Climatic performance of courtyard residential buildings needs to be
investigated if the assertion that courtyard is a microclimate modifier is to be
accepted. Therefore, this study seeks to examine the microclimatic performance
of two existing courtyard residential buildings with similar characteristics in
Kafanchan-Kaduna Nigeria, -the fully enclosed courtyard residential building and
the semi-enclosed courtyard residential building. The purpose of this research is
to investigate their microclimatic performances in other to establish the best
courtyard house. This study uses measurement to achieve its aim. The tool
employed for data collection is the Hobo Weather Data Loggers (HWDL). Three
HWDL were used to collect data in the two case-study, and the third one was
placed in the outside area as a benchmark. Only air temperature and relative
humidity were measured. This study revealed a tangible difference in the
microclimatic performance of the two case-study. The fully enclosed courtyard
residential building is seen to have air temperature difference of 1 oC to 3 oC, and
the relative humidity difference of 4 % to 8 %. In conclusion, the fully enclosed
courtyard house demonstrated a more favorable microclimatic performance than
the semi-enclosed, and further simulation studies towards its optimization are
required.

Matched MeSH terms: Weather
Meterological factors as affecting the incidence of malaria

Wilson T

Malayan Medical Journal, 1935;10:39-48.

Matched MeSH terms: Weather
Mapping flood by the object-based method using backscattering coefficient and interference coherence of Sentinel-1 time series

Zhang X, Chan NW, Pan B, Ge X, Yang H

Sci Total Environ, 2021 Nov 10;794:148388.
PMID: 34217078 DOI: 10.1016/j.scitotenv.2021.148388

The SAR has the ability of all-weather and all-time data acquisition, it can penetrate the cloud and is not affected by extreme weather conditions, and the acquired images have better contrast and rich texture information. This paper aims to investigate the use of an object-oriented classification approach for flood information monitoring in floodplains using backscattering coefficients and interferometric coherence of Sentinel-1 data under time series. Firstly, the backscattering characteristics and interference coherence variation characteristics of SAR time series are used to analyze whether the flood disaster information can be accurately reflected and provide the basis for selecting input classification characteristics of subsequent SAR images. Subsequently, the contribution rate index of the RF model is used to calculate the importance of each index in time series to convert the selected large number of classification features into low dimensional feature space to improve the classification accuracy and reduce the data redundancy. Finally, the SAR image features in each period after multi-scale segmentation and feature selection are jointly used as the input features of RF classification to extract and segment the water in the study area to monitor floods' spatial distribution and dynamic characteristics. The results showed that the various attributes of backscatter coefficients and interferometric coherence under time series could accurately correspond with the actual flood risk, and the combined use of backscattering coefficient and interferometric coherence for flood extraction can significantly improve the accuracy of flood information extraction. Overall, the object-based random forest method using the backscattering coefficient and interference coherence of Sentinel-1 time series for flood extraction advances our understanding of flooding's temporal and spatial dynamics, essential for the timely adoption of adaptation and mitigation strategies for loss reduction.

Matched MeSH terms: Weather
Fulltext Macroeconomic dataset for generating macroeconomic volatility among selected countries in the Asia Pacific region

Chow YP, Muhammad J, Amin Noordin BA, Cheng FF

Data Brief, 2018 Feb;16:23-28.
PMID: 29167816 DOI: 10.1016/j.dib.2017.11.015

This data article provides macroeconomic data that can be used to generate macroeconomic volatility. The data cover a sample of seven selected countries in the Asia Pacific region for the period 2004-2014, including both developing and developed countries. This dataset was generated to enhance our understanding of the sources of macroeconomic volatility affecting the countries in this region. Although the Asia Pacific region continues to remain as the most dynamic part of the world's economy, it is not spared from various sources of macroeconomic volatility through the decades. The reported data cover 15 types of macroeconomic data series, representing three broad categories of indicators that can be used to proxy macroeconomic volatility. They are indicators that account for macroeconomic volatility (i.e. volatility as a macroeconomic outcome), domestic sources of macroeconomic volatility and external sources of macroeconomic volatility. In particular, the selected countries are Malaysia, Thailand, Indonesia and Philippines, which are regarded as developing countries, while Singapore, Japan and Australia are developed countries. Despite the differences in level of economic development, these countries were affected by similar sources of macroeconomic volatility such as the Asian Financial Crisis and the Global Financial Crisis. These countries were also affected by other similar external turbulence arising from factors such as the global economic slowdown, geopolitical risks in the Middle East and volatile commodity prices. Nonetheless, there were also sources of macroeconomic volatility which were peculiar to certain countries only. These were generally domestic sources of volatility such as political instability (for Thailand, Indonesia and Philippines), natural disasters and anomalous weather conditions (for Thailand, Indonesia, Philippines, Japan and Australia) and over-dependence on the electronic sector (for Singapore).

Matched MeSH terms: Weather
Levels of 137Cs in soils and vegetation of West Malaysia

Lowe BG

Health Phys, 1978 May;34(5):439-44.
PMID: 568609
Matched MeSH terms: Weather
Level and transport pattern of faecal coliform bacteria from tropical urban catchments

Chow MF, Yusop Z, Toriman ME

Water Sci Technol, 2013;67(8):1822-31.
PMID: 23579839 DOI: 10.2166/wst.2013.048

Urbanization and frequent storms play important roles in increasing faecal bacteria pollution, especially for tropical urban catchments. However, only little information on the faecal bacteria levels from different land use types and the factors that influence bacteria concentrations is available. Thus, the objectives of this study were to quantify the levels and transport mechanism of faecal coliforms (FCs) from residential and commercial catchments. Stormwaters were sampled and the runoff flow rates were measured from both catchments during four storm events in Skudai, Malaysia. The samples were then analysed for FC, biochemical oxygen demand (BOD5), chemical oxygen demand (COD), total suspended solids (TSS) and ammoniacal-nitrogen (NH3-N) concentrations. Intra-storm and inter-storm characteristics of FC bacteria were investigated in order to identify the level and transport pattern of FC. The commercial catchment showed significantly higher event mean concentration (EMC) of FC than the residential catchment. For the residential catchment, the highest bacterial concentrations occurred during the early part of stormwater runoff with peak concentrations usually preceding the peak flow. First flush effect was more prevalent at the residential catchment.

Matched MeSH terms: Weather
Large-scale distribution and composition of floating plastic debris in the transition region of the North Pacific

Miyazono K, Yamashita R, Miyamoto H, Ishak NHA, Tadokoro K, Shimizu Y, et al.

Mar Pollut Bull, 2021 Sep;170:112631.
PMID: 34175698 DOI: 10.1016/j.marpolbul.2021.112631

Floating plastic debris was investigated in the transition region in the North Pacific between 141°E and 165°W to understand its transportation process from Asian coast to central subtropical Pacific. Distribution was influenced primarily by the current system and the generation process of the high concentration area differed between the western and eastern areas. West of 180°, debris largely accumulated around nearshore convergent area and was transported by eddies and quasi-stationary jet from south to the subarctic region. The average was 15% higher than that previously reported in 1989, suggesting an increase in plastic debris in 30 years. East of 180°, debris concentrated in the calm water downstream of the Kuroshio Extension Bifurcation with considerably high concentration (505,032 ± 991,989 pieces km-2), due to the accumulation of small transparent film caused by calm weather conditions, suggesting a further investigation on small plastic (<1 mm) in the subsurface depth in the subtropical North Pacific.

Matched MeSH terms: Weather
Keratosis Obturans: A Disease of the Tropics?

Chong AW, Raman R

Indian J Otolaryngol Head Neck Surg, 2017 Sep;69(3):291-295.
PMID: 28929057 DOI: 10.1007/s12070-017-1071-z

Keratosis obturans appears to be an obscure and relatively uncommon entity, even in literature search of journals and reference texts, so much so that there is not even any prevalence or incidence statistics available. However, the condition did not appear to be as uncommon based on our clinical observations. We have managed to obtain 64 patients representing 67 ears with keratosis obturans in our study period of about 18 months with a pattern of occurrence during this period. Humid weather seemed to play a role in the frequency of its appearance during certain period in our observation. There also appears to be a correlation between the severity of symptoms (predominantly pain and hearing loss) and the presenting appearance of the condition, i.e., presence or absence of granulation tissue, as well as that the degree of difficulty in exenteration of the keratosis obturans (matrix and content) depending on the expansion of the bony canal. Our figures showed the majority of the patients are females and young individuals, the majority of them occur unilaterally. The condition also appear to stop short of involving the tympanic membrane with only the bony canal being expanded with the surrounding oedema creating an apparent "canal stenosis".

Matched MeSH terms: Weather

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