Household Protection Against Dengue Hemorrhagic Fever Epidemics in Coastal City of Makassar

The skill of two simple models for predicting Dengue Hemorrhagic Fever (DHF) epidemics in a coastal city of Makassar was evaluated. One model uses persistence while the other uses past dengue cases and climate factors to make predictions. It was shown that the skill of the models was not significantly different. The value of the prediction was also investigated when it was used for deciding whether or not to protect a household from epidemics. When the model predicts that a DHF epidemic was forthcoming, a highly effective but low-cost DEET product was applied to the whole family as protection against mosquito bites. It was found that the cost of implementing such model prediction was much cheaper than other options such as: (i) using protection without any forecast and, (ii) neglecting any protection. It was also found that the value of a forecast depends on forecast skill and the cost-to-loss ratio

Effects of the El Niño-Southern Oscillation on dengue epidemics in Thailand, 1996-2005

<p>Abstract</p> <p>Background</p> <p>Despite intensive vector control efforts, dengue epidemics continue to occur throughout Southeast Asia in multi-annual cycles. Weather is considered an important factor in these cycles, but the extent to which the El Niño-Southern Oscillation (ENSO) is a driving force behind dengue epidemics remains unclear.</p> <p>Methods</p> <p>We examined the temporal relationship between El Niño and the occurrence of dengue epidemics, and constructed Poisson autoregressive models for incidences of dengue cases. Global ENSO records, dengue surveillance data, and local meteorological data in two geographically diverse regions in Thailand (the tropical southern coastal region and the northern inland mountainous region) were analyzed.</p> <p>Results</p> <p>The strength of El Niño was consistently a predictor for the occurrence of dengue epidemics throughout time lags from 1 to 11 months in the two selected regions of Thailand. Up to 22% (in 8 northern inland mountainous provinces) and 15% (in 5 southern tropical coastal provinces) of the variation in the monthly incidence of dengue cases were attributable to global ENSO cycles. Province-level predictive models were fitted using 1996-2004 data and validated with out-of-fit data from 2005. The multivariate ENSO index was an independent predictor in 10 of the 13 studied provinces.</p> <p>Conclusion</p> <p>El Niño is one of the important driving forces for dengue epidemics across the geographically diverse regions of Thailand; however, spatial heterogeneity in the effect exists. The effects of El Niño should be taken into account in future epidemic forecasting for public health preparedness.</p

Chapter 9: Spatio-Temporal Analysis of Dengue Fever in Makassar Indonesia: A Comparison of Models Based on CARBayes

Background: Dengue fever is one of the world’s most important vector-borne diseases and it is still a major public health problem in the Asia-Pacific region including Indonesia. Makassar is one of the major cities in Indonesia where the incidence of dengue fever is still quite high. Since dengue cases vary between areas and over time, these spatial and temporal components should be taken into consideration. However, unlike many other spatio-temporal contexts, Makassar is comprised of only a small number of areas and data are available over a relatively short timeframe. The aim of this paper is to better understand the spatial and temporal patterns of dengue incidence in Makassar, Indonesia by comparing the performance of six existing spatio-temporal models, taking into account these specific data characteristics (small number of areas and limited small number of time periods) and to select the best model for Makassar dengue dataset. Methods: Six different Bayesian spatio-temporal conditional autoregressive (ST CAR) models were compared in the context of a substantive case study, namely annual dengue fever incidence in 14 geographic areas of Makassar, Indonesia, during 2002–2015. The candidate models included linear, ANOVA, separate spatial, autoregressive (AR), adaptive and localised approaches. The models were implemented using CARBayesST and the goodness of fit was compared using the Deviance Information Criterion (DIC) and Watanabe-Akaike Information Criterion (WAIC). Results: The six models performed differently in the context of this case study. Among the six models, the spatio-temporal conditional autoregressive localised model had a much better fit than other options in terms of DIC, while the conditional autoregressive model with separate spatial and temporal components performed worst. However, the spatio-temporal CAR AR had a much better fit than other models in terms of WAIC. The different performance of the models may have been influenced by the small number of areas. Conclusion: Different spatio-temporal models appeared to have a large impact on results. Careful selection of a range of spatio-temporal models is important for assessing the spatial and temporal patterns of dengue fever, especially in a context characterised by relatively few spatial areas and limited time periods

A rare tumor of trachea: Inflammatory myofibroblastic tumor diagnosis and endoscopic treatment

Inflammatory myofibroblastic tumors (IMTs) are rare childhood neoplasms, with benign clinical course. Although etiology of IMTs are not clear, recent studies have reported that IMT is a true neoplasm rather than a reactive or inflammatory lesion. IMTs are rarely seen in adults and tracheal involvement is also rare both in adults and also in children. We describe a 16-year old female patient who was misdiagnosed and treated as asthma in another center for a few months and presented with acute respiratory distress due to upper airway obstruction. Computerized tomography (CT) of the chest and rigid bronchoscopy revealed a mass lesion that was nearly totally obliterating tracheal lumen. Bronchoscopic resection was performed under general anesthesia and the final pathological diagnosis was tracheal IMT

Climatic influences on southern makassar strait salinity over the past century

The Indonesian Throughflow (ITF) is a globally important ocean current that fuels heat and buoyancy fluxes throughout the Indo‐Pacific and is known to covary in strength with the El Niño Southern Oscillation at interannual time scales. A climate system with a less well‐quantified impact on the ITF is the East Asian Winter Monsoon (EAWM), which drives less saline surface waters from the South China Sea (SCS) into the Makassar Strait, obstructing surface ITF flow. We present a subannually resolved record of sea surface salinity (SSS) from 1927 to 2011 based on coral δ18O from the Makassar Strait that reveals variability in the relative contributions of different source waters to the surface waters of the Makassar Strait during the boreal winter monsoon. We find that the EAWM (January–March) strongly influences interannual SSS variability during boreal winter over the twentieth century (r = 0.54, p << 0.0001), impacting surface water circulation in the SCS and Indonesian Seas.NRF (Natl Research Foundation, S’pore)Published versio

Lymph node characteristics of sarcoidosis with endobronchial ultrasound

Background: Sonographic features of lymph nodes on endobronchial ultrasound (EBUS) have been shown to be useful in prediction of malignancy in mediastinum and hilum. The aim of this study was to assess the utility of morphologic features of mediastinal and/or hilar lymph nodes obtained by EBUS in patients with sarcoidosis. Materials and Methods: We retrospectively reviewed the records of 224 patients with mediastinal/hilar lymph node enlargements who underwent EBUS for diagnostic purpose. The lymph nodes were characterized based on the EBUS images as follows: (1) Size; based on short-axis dimension, = 1 cm, (2) shape; oval or round, (3) margin; distinct or indistinct, (4) echogenicity; homogeneous or heterogeneous, (5) presence or absence of central hilar structure, and (6) presence or absence of granular (sandpaper) appearance. Results: One hundred (24.4%) nodes exhibited indistinct margins while 309 (75.6%) had distinct margins. One hundred and ninety nine (48.7%) nodes were characterized as homogeneous, and 210 (51.3%) nodes as heterogeneous. Granular appearance was observed in 130 (31.8%) lymph nodes. The presence of granules in lymph nodes on EBUS had the highest specificity (99.3%) for the diagnosis of sarcoidosis. Logistic regression analysis revealed the finding of distinct margin alone as an independent predictive factor for the diagnosis of sarcoidosis. Conclusions: The presence of granular appearance in lymph nodes by EBUS had the highest specificity (99.3%) for the diagnosis of sarcoidosis. Lymph nodes having distinct margins tend to suggest sarcoidosis