Displaying publications 1 - 20 of 192 in total

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  1. GORDON SMITH CE
    Med J Malaya, 1956 Jun;10(4):289-303.
    PMID: 13399530
    Matched MeSH terms: Dengue/epidemiology*
  2. Wkly. Epidemiol. Rec., 1998 Jun 12;73(24):182-3.
    PMID: 9652206
    Matched MeSH terms: Dengue/epidemiology*; Severe Dengue/epidemiology
  3. Aziz AT, Al-Shami SA, Mahyoub JA, Hatabbi M, Ahmad AH, Md Rawi CS
    Parasit Vectors, 2014;7:487.
    PMID: 25403705 DOI: 10.1186/s13071-014-0487-5
    Currently, dengue fever is considered as the main health problem in several parts (Mekkah, Jeddah, Jazan and Najran) of Kingdom of Saudi Arabia (KSA) with dramatically increase in the number of cases reported every year. This is associated with obvious ineffectiveness in the recent control and management programs for the mosquito vector (Aedes aegypti). Here, we suggested promoting the health education and public awareness among Saudi people to improve the control of dengue mosquito vector. Several suggestions and recommendations were highlighted here to ensure effectiveness in the future control and management programs of dengue mosquito vector in KSA.
    Matched MeSH terms: Dengue/epidemiology*
  4. Gaoxiong Yi Xue Ke Xue Za Zhi, 1994 Dec;10 Suppl:S113-5.
    PMID: 7844838
    Matched MeSH terms: Dengue/epidemiology
  5. Chang MS, Rubis P, Jute N, Lim TW
    Med J Malaysia, 1981 Jun;36(2):79-82.
    PMID: 7343823
    Matched MeSH terms: Dengue/epidemiology*
  6. George R
    PMID: 3324361
    The historical background, epidemiology and changing pattern of clinical disease as seen in Malaysia is reviewed. The preliminary results of the longitudinal study of epidemiology of dengue in Malaysia is also presented. Studies led by Rudnick et al. over some 18 years have established that the disease is endemically transmitted by both Aedes aegypti and Aedes albopictus causing illnesses ranging from mild febrile episodes through classical dengue fever, dengue haemorrhagic fever and the dengue shock syndrome. The first epidemic occurred in 1962 in Penang, and the second major epidemic in 1974 in Selangor. From then on epidemics seem to occur every 4 years, i.e. 1978, and then in 1982. With increasing number of cases being seen from the end of 1985 and in 1986, and with the increasing numbers of positive virus isolates, another epidemic may occur this year. Though in the early years, mainly children were affected, recently more cases are being seen in 16-30 years age group. There is also a changing pattern in the clinical presentation of the cases. The clinician has to be aware of the various modes of presentation of this sinister disease. A high index of suspicion is needed for early diagnosis, as management is mainly symptomatic and there is no specific drug as yet to combat the shock and bleeding manifestations.
    Matched MeSH terms: Dengue/epidemiology*
  7. Cardosa MJ
    PMID: 3217825
    Matched MeSH terms: Dengue/epidemiology*
  8. Sulaiman S, Pawanchee ZA, Arifin Z, Wahab A
    J Am Mosq Control Assoc, 1996 Sep;12(3 Pt 1):494-6.
    PMID: 8887232
    The relationship between the Breteau index, the House index, and the occurrence of dengue/dengue hemorrhagic fever in the 6 zones of Kuala Lumpur was studied throughout 1994. Cases of dengue/dengue hemorrhagic fever varied between zones and between months, ranging from 0 to 21 cases. In most of the zones in Kuala Lumpur, the occurrence of dengue/dengue hemorrhagic fever has no relationship with the Breteau and House indices. Cases of dengue/dengue hemorrhagic fever occurred in all zones despite the low Breteau and House indices.
    Matched MeSH terms: Dengue/epidemiology
  9. Aziz S, Ngui R, Lim YA, Sholehah I, Nur Farhana J, Azizan AS, et al.
    Trop Biomed, 2012 Mar;29(1):113-20.
    PMID: 22543611 MyJurnal
    In the last few years in Malaysia, dengue fever has increased dramatically and has caused huge public health concerns. The present study aimed to establish a spatial distribution of dengue cases in the city of Kuala Lumpur using a combination of Geographic Information System (GIS) and spatial statistical tools. Collation of data from 1,618 dengue cases in 2009 was obtained from Kuala Lumpur City Hall (DBKL). These data were processed and then converted into GIS format. Information on the average monthly rainfall was also used to correlate with the distribution pattern of dengue cases. To asses the spatial distribution of dengue cases, Average Nearest Neighbor (ANN) Analysis was applied together with spatial analysis with the ESRI ArcGIS V9.3 programme. Results indicated that the distribution of dengue cases in Kuala Lumpur for the year 2009 was spatially clustered with R value less than 1 (R = 0.42; z-scores = - 4.47; p < 0.001). Nevertheless, when this pattern was further analyzed according to month by each zone within Kuala Lumpur, two distinct patterns were observed which include a clustered pattern (R value < 1) between April to June and a dispersed pattern (R value > 1) between August and November. In addition, the mean monthly rainfall has not influenced the distribution pattern of the dengue cases. Implementation of control measures is more difficult for dispersed pattern compared to clustered pattern. From this study, it was found that distribution pattern of dengue cases in Kuala Lumpur in 2009 was spatially distributed (dispersed or clustered) rather than cases occurring randomly. It was proven that by using GIS and spatial statistic tools, we can determine the spatial distribution between dengue and population. Utilization of GIS tools is vital in assisting health agencies, epidemiologist, public health officer, town planner and relevant authorities in developing efficient control measures and contingency programmes to effectively combat dengue fever.
    Matched MeSH terms: Dengue/epidemiology*
  10. Wartel TA, Prayitno A, Hadinegoro SR, Capeding MR, Thisyakorn U, Tran NH, et al.
    Asia Pac J Public Health, 2017 Jan;29(1):7-16.
    PMID: 28198645 DOI: 10.1177/1010539516675701
    We described and quantified epidemiologic trends in dengue disease burden in 5 Asian countries (Indonesia, Thailand, Malaysia, Philippines, and Vietnam) and identified and estimated outbreaks impact over the last 3 decades. Dengue surveillance data from 1980 to 2010 were retrieved from DengueNet and from World Health Organization sources. Trends in incidence, mortality, and case fatality rate (CFR) were systematically analyzed using annual average percent change (AAPC), and the contribution of epidemic years identified over the observation period was quantified. Over the 30-year period, incidence increased in all countries (AAPC 1980-2010: 6.7% in Thailand, 10.4% in Vietnam, 12.0% in Indonesia, 18.1% in Malaysia, 24.4% in Philippines). Mortality also increased in Indonesia, Malaysia, and Philippines (AAPC: 6.8%, 7.0%, and 29.2%, respectively), but slightly decreased in Thailand and Vietnam (AAPC: -1.3% and -2.5%), and CFR decreased in all countries (AAPC: -4.2% to -8.3%). Epidemic years, despite representing less than a third of the observation period, contributed from 1 to 3 times more cases versus nonepidemic years. Implementation of more sensitive surveillance methods over the study period may have contributed to a reporting or ascertainment bias in some countries. Nonetheless, these data support the urgent need for novel, integrated, or otherwise effective dengue prevention and control tools and approaches.
    Matched MeSH terms: Dengue/epidemiology*
  11. Sandosham AA
    Med J Malaysia, 1973 Sep;28(1):1-2.
    PMID: 4273777
    Matched MeSH terms: Dengue/epidemiology*
  12. Thiruchelvam L, Dass SC, Zaki R, Yahya A, Asirvadam VS
    Geospat Health, 2018 05 07;13(1):613.
    PMID: 29772882 DOI: 10.4081/gh.2018.613
    This study investigated the potential relationship between dengue cases and air quality - as measured by the Air Pollution Index (API) for five zones in the state of Selangor, Malaysia. Dengue case patterns can be learned using prediction models based on feedback (lagged terms). However, the question whether air quality affects dengue cases is still not thoroughly investigated based on such feedback models. This work developed dengue prediction models using the autoregressive integrated moving average (ARIMA) and ARIMA with an exogeneous variable (ARIMAX) time series methodologies with API as the exogeneous variable. The Box Jenkins approach based on maximum likelihood was used for analysis as it gives effective model estimates and prediction. Three stages of model comparison were carried out for each zone: first with ARIMA models without API, then ARIMAX models with API data from the API station for that zone and finally, ARIMAX models with API data from the zone and spatially neighbouring zones. Bayesian Information Criterion (BIC) gives goodness-of-fit versus parsimony comparisons between all elicited models. Our study found that ARIMA models, with the lowest BIC value, outperformed the rest in all five zones. The BIC values for the zone of Kuala Selangor were -800.66, -796.22, and -790.5229, respectively, for ARIMA only, ARIMAX with single API component and ARIMAX with API components from its zone and spatially neighbouring zones. Therefore, we concluded that API levels, either temporally for each zone or spatio- temporally based on neighbouring zones, do not have a significant effect on dengue cases.
    Matched MeSH terms: Dengue/epidemiology*
  13. Jayaraj VJ, Avoi R, Gopalakrishnan N, Raja DB, Umasa Y
    Acta Trop, 2019 Sep;197:105055.
    PMID: 31185224 DOI: 10.1016/j.actatropica.2019.105055
    Dengue is fast becoming the most urgent health issue in Malaysia, recording close to a 10-fold increase in cases over the last decade. With much uncertainty hovering over the recently introduced tetravalent vaccine and no effective antiviral drugs, vector control remains the most important strategy in combating dengue. This study analyses the relationship between weather predictors including its lagged terms, and dengue incidence in the District of Tawau over a period of 12 years, from 2006 to 2017. A forecasting model purposed to predict future outbreaks in Tawau was then developed using this data. Monthly dengue incidence data, mean temperature, maximum temperature, minimum temperature, mean relative humidity and mean rainfall over a period of 12 years from 2006 to 2017 in Tawau were retrieved from Tawau District Health Office and the Malaysian Meteorological Department. Cross-correlation analysis between weather predictors, lagged terms of weather predictors and dengue incidences established statistically significant cross-correlation between lagged periods of weather predictors-namely maximum temperature, mean relative humidity and mean rainfall with dengue incidence at time lags of 4-6 months. These variables were then employed into 3 different methods: a multivariate Poisson regression model, a Seasonal Autoregressive Integrated Moving Average (SARIMA) model and a SARIMA with external regressors for selection. Three models were selected but the SARIMA with external regressors model utilising maximum temperature at a lag of 6 months (p-value:0.001), minimum temperature at a lag of 4 months (p-value:0.01), mean relative humidity at a lag of 2 months (p-value:0.001), and mean rainfall at a lag of 6 months (p-value:0.001) produced an AIC of 841.94, and a log-likelihood score of -413.97 establishing it as the best fitting model of the methodologies utilised. In validating the models, they were utilised to develop forecasts with the model selected with the highest accuracy of predictions being the SARIMA model predicting 1 month in advance (MAE: 7.032, MSE: 83.977). This study establishes the effect of weather on the intensity and magnitude of dengue incidence as has been previously studied. A prediction model remains a novel method of evidence-based forecasting in Tawau, Sabah. The model developed in this study, demonstrated an ability to forecast potential dengue outbreaks 1 to 4 months in advance. These findings are not dissimilar to what has been previously studied in many different countries- with temperature and humidity consistently being established as powerful predictors of dengue incidence magnitude. When used in prognostication, it can enhance- decision making and allow judicious use of resources in public health setting. Nevertheless, the model remains a work in progress- requiring larger and more diverse data.
    Matched MeSH terms: Dengue/epidemiology*
  14. Shepard DS, Undurraga EA, Lees RS, Halasa Y, Lum LCS, Ng CW
    Am J Trop Med Hyg, 2012 Nov;87(5):796-805.
    PMID: 23033404 DOI: 10.4269/ajtmh.2012.12-0019
    Dengue represents a substantial burden in many tropical and sub-tropical regions of the world. We estimated the economic burden of dengue illness in Malaysia. Information about economic burden is needed for setting health policy priorities, but accurate estimation is difficult because of incomplete data. We overcame this limitation by merging multiple data sources to refine our estimates, including an extensive literature review, discussion with experts, review of data from health and surveillance systems, and implementation of a Delphi process. Because Malaysia has a passive surveillance system, the number of dengue cases is under-reported. Using an adjusted estimate of total dengue cases, we estimated an economic burden of dengue illness of US$56 million (Malaysian Ringgit MYR196 million) per year, which is approximately US$2.03 (Malaysian Ringgit 7.14) per capita. The overall economic burden of dengue would be even higher if we included costs associated with dengue prevention and control, dengue surveillance, and long-term sequelae of dengue.
    Matched MeSH terms: Dengue/epidemiology*
  15. van Panhuis WG, Choisy M, Xiong X, Chok NS, Akarasewi P, Iamsirithaworn S, et al.
    Proc Natl Acad Sci U S A, 2015 Oct 20;112(42):13069-74.
    PMID: 26438851 DOI: 10.1073/pnas.1501375112
    Dengue is a mosquito-transmitted virus infection that causes epidemics of febrile illness and hemorrhagic fever across the tropics and subtropics worldwide. Annual epidemics are commonly observed, but there is substantial spatiotemporal heterogeneity in intensity. A better understanding of this heterogeneity in dengue transmission could lead to improved epidemic prediction and disease control. Time series decomposition methods enable the isolation and study of temporal epidemic dynamics with a specific periodicity (e.g., annual cycles related to climatic drivers and multiannual cycles caused by dynamics in population immunity). We collected and analyzed up to 18 y of monthly dengue surveillance reports on a total of 3.5 million reported dengue cases from 273 provinces in eight countries in Southeast Asia, covering ∼ 10(7) km(2). We detected strong patterns of synchronous dengue transmission across the entire region, most markedly during a period of high incidence in 1997-1998, which was followed by a period of extremely low incidence in 2001-2002. This synchrony in dengue incidence coincided with elevated temperatures throughout the region in 1997-1998 and the strongest El Niño episode of the century. Multiannual dengue cycles (2-5 y) were highly coherent with the Oceanic Niño Index, and synchrony of these cycles increased with temperature. We also detected localized traveling waves of multiannual dengue epidemic cycles in Thailand, Laos, and the Philippines that were dependent on temperature. This study reveals forcing mechanisms that drive synchronization of dengue epidemics on a continental scale across Southeast Asia.
    Matched MeSH terms: Dengue/epidemiology*
  16. Jamaiah I, Rohela M, Nissapatorn V, Maizatulhikma MM, Norazlinda R, Syaheerah H, et al.
    PMID: 16438209
    Dengue fever and dengue hemorrhagic fever have been known to be endemic and reportable diseases in Malaysia since 1971. Major outbreaks occurred in 1973, 1982 and in 1998. For the past few decades until now. many studies have been performed to investigate the importance of these two diseases in Malaysia. A retrospective study was carried out in Hospital Tengku Ampuan Rahimah Klang to find the prevalence of these diseases. The data was collected from the record department of this hospital starting from the year 1999 until 2003 (5 years). A total of 6,577 cases of dengue fever and 857 cases of dengue hemorrhagic fever were reported. From the year 2000 onwards, cases of dengue fever had increased tremendously. However for the year 2001, there was a slight decrease in the reported cases. Most cases occurred in 2003, increasing from 674 in 1999 to 2,813 in 2003. Highest incidence was seen in Malay males more than 12 years of age. However, the cases of dengue hemorrhagic fever declined tremendously throughout the years. Most cases occurred in 1999 with 674 cases, then declining to only one in the year 2001 before it increased to 60 and 72 in the years 2002 and 2003, respectively. Most cases occurred in patients above 12 years old, the majority of which were Malay males.
    Matched MeSH terms: Dengue/epidemiology*; Severe Dengue/epidemiology*
  17. Cheong YL, Leitão PJ, Lakes T
    Spat Spatiotemporal Epidemiol, 2014 Jul;10:75-84.
    PMID: 25113593 DOI: 10.1016/j.sste.2014.05.002
    The transmission of dengue disease is influenced by complex interactions among vector, host and virus. Land use such as water bodies or certain agricultural practices have been identified as likely risk factors for dengue because of the provision of suitable habitats for the vector. Many studies have focused on the land use factors of dengue vector abundance in small areas but have not yet studied the relationship between land use factors and dengue cases for large regions. This study aims to clarify if land use factors other than human settlements, e.g. different types of agricultural land use, water bodies and forest are associated with reported dengue cases from 2008 to 2010 in the state of Selangor, Malaysia. From the correlative relationship, we aim to generate a prediction risk map. We used Boosted Regression Trees (BRT) to account for nonlinearities and interactions between the factors with high predictive accuracies. Our model with a cross-validated performance score (Area Under the Receiver Operator Characteristic Curve, ROC AUC) of 0.81 showed that the most important land use factors are human settlements (model importance of 39.2%), followed by water bodies (16.1%), mixed horticulture (8.7%), open land (7.5%) and neglected grassland (6.7%). A risk map after 100 model runs with a cross-validated ROC AUC mean of 0.81 (±0.001 s.d.) is presented. Our findings may be an important asset for improving surveillance and control interventions for dengue.
    Matched MeSH terms: Dengue/epidemiology*
  18. Mia MS, Begum RA, Er AC, Abidin RD, Pereira JJ
    Asian Pac J Trop Med, 2013 Jun;6(6):462-6.
    PMID: 23711707 DOI: 10.1016/S1995-7645(13)60075-9
    OBJECTIVE: To analyze trends of dengue incidences and deaths in Malaysia from 2000 to 2010 as well as the predominant dengue virus serotypes during the last decade.

    METHODS: We used the national data on annual reported cases, deaths, incidence rate, mortality rate, and case fatality rate of dengue fever (DF) and dengue hemorrhagic fever (DHF) as well as dengue virus serotypes prevalent in Malaysia during the last decade. Trend/ regression lines were fitted to investigate the trend of dengue incidences and deaths due to the disease for a 11-year period (2000-2010). For the distribution of national incidence rate, mortality rate, and case fatality rate of DF and DHF, descriptive statistics using mean and 95% confidence intervals (CI 39) for means, and range were applied.

    RESULTS: The number of dengue cases and number of deaths have increased, on average, by 14% and 8% per year respectively. The average annual incidence rate of DF per 100 000 populations was higher as compared to that of DHF. Conversely, the yearly mean mortality rate of DHF per 100 000 populations was greater than that of DF. The simultaneous circulation of all four dengue serotypes has been found in Malaysia. But a particular dengue virus serotype predominates for at least two years before it becomes replaced by another serotype.

    CONCLUSIONS: The dengue situation in Malaysia has worsened with an increasing number of reported cases and deaths during the last decade. The increasing trend of dengue highlights the need for a more systematic surveillance and reporting of the disease.

    Matched MeSH terms: Dengue/epidemiology*
  19. Mulligan K, Elliott SJ, Schuster-Wallace C
    Health Place, 2012 May;18(3):613-20.
    PMID: 22310527 DOI: 10.1016/j.healthplace.2012.01.001
    This case study investigates the connections among urban planning, governance and dengue fever in an emerging market context in the Global South. Key informant interviews were conducted with leading figures in public health, urban planning and governance in the planned city of Putrajaya, Malaysia. Drawing on theories of urban political ecology and ecosocial epidemiology, the qualitative study found the health of place - expressed as dengue-bearing mosquitoes and dengue fever in human bodies in the urban environment - was influenced by the place of health in a hierarchy of urban priorities.
    Matched MeSH terms: Dengue/epidemiology*
  20. Ang KT, Ruhaini I, Chua KB
    Med J Malaysia, 2006 Aug;61(3):292-5.
    PMID: 17240578 MyJurnal
    Dengue fever is major public health problem especially among the highly urbanized states of Malaysia, such as, Selangor and Kuala Lumpur Federal Territory. We report an epidemiological cluster pattern of dengue outbreak in the district of Gombak, Selangor that may mimic other acute febrile illnesses in which the transmission mode is via close contact. This dengue outbreak consisted of two waves; an initial cluster of three cases (including the first deceased, JI) which occurred between 20th and 21st of July, followed by a later larger cluster of 11 cases that occurred between 1st and 8th of August 2005. This epidemiological clustering pattern of acute dengue virus infection among close contacts suggests an intense rate of dengue virus transmission within the vicinity of the first deceased's house.
    Matched MeSH terms: Dengue/epidemiology*
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