Seasonal forecasts of Indian summer monsoon rainfall using local polynomial based non-parametric regression model

In this paper, details of new statistical models for forecasting southwest monsoon (June-September) rainfall over India (ISMR) and for northwest India summer monsoon rainfall (NWISMR) are discussed. These models are based on the local polynomial based non-parametric regression method. Two predictor sets (SET-I & SET-II consisting of 4 and 5 predictors respectively) were selected for developing two separate models for making predictions in April and late June respectively. Another predictor set (SET-III) was selected for developing model for monsoon rainfall over NW India (NWISMR). Principle Component Analysis (PCA) of predictor data set was done and the first two principal components were selected for model development. Data for the period 1977-2005 have been used for developing the model and the Jackknife method was used to assess the skill of the model. Both the models showed useful skill in predicting ISMR and showed better performance than the model based on pure climatology. The Hit scores for the three category forecasts during the verification period by April and June models are 0.65 and 0.66 respectively. Root Mean Square Error (RMSE) of these models during the verification period is 5.99 and 6.0 respectively from the Long Period Average (LPA) as against 10.0 from the LPA of the model based on climatology alone. RMSE of the Northwest India model during the independent period is 11.5 from LPA as against 18.5 from the LPA of the model based on the climatology alone. Hit score for the three category forecast for NW India during the verification period is 0.55

Toxocariasis: a silent threat with a progressive public health impact

Background: Toxocariasis is a neglected parasitic zoonosis that afflicts millions of the pediatric and adolescent populations worldwide, especially in impoverished communities. This disease is caused by infection with the larvae of Toxocara canis and T. cati, the most ubiquitous intestinal nematode parasite in dogs and cats, respectively. In this article, recent advances in the epidemiology, clinical presentation, diagnosis and pharmacotherapies that have been used in the treatment of toxocariasis are reviewed. Main text: Over the past two decades, we have come far in our understanding of the biology and epidemiology of toxocariasis. However, lack of laboratory infrastructure in some countries, lack of uniform case definitions and limited surveillance infrastructure are some of the challenges that hindered the estimation of global disease burden. Toxocariasis encompasses four clinical forms: visceral, ocular, covert and neural. Incorrect or misdiagnosis of any of these disabling conditions can result in severe health consequences and considerable medical care spending. Fortunately, multiple diagnostic modalities are available, which if effectively used together with the administration of appropriate pharmacologic therapies, can minimize any unnecessary patient morbidity. Conclusions: Although progress has been made in the management of toxocariasis patients, there remains much work to be done. Implementation of new technologies and better understanding of the pathogenesis of toxocariasis can identify new diagnostic biomarkers, which may help in increasing diagnostic accuracy. Also, further clinical research breakthroughs are needed to develop better ways to effectively control and prevent this serious disease

Relationship between lower stratospheric circulation and Indian summer monsoon rainfall : Implication for long range forecasts

In this study teleconnections between monthly northern hemisphere lower stratospheric geopotential heights (100, 50, 30 hPa) and seasonal Indian Summer Monsoon Rainfall (ISMR) have been established through the correlation analysis. Stable and consistent precursory signals for the ensuing monsoon were identified from the significant teleconnections. The usefulness of the precursory signals for the prediction of ISMR was also tested using a simple multiple linear regression model. These precursory signals show a good potential in the long range prediction scheme of Indian Summer Monsoon Rainfall

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