Flattening the Earth, Two Thousand Years of Map Projections

Purpose of reviewThe present review will focus on some of the possible infectious disease consequences of disastrous natural phenomena and severe weather, with a particular emphasis on infections associated with floods and the destruction of infrastructure.Recent findingsThe risk of infectious disea

Infectious diseases of severe weather-related and flood-related natural disasters.

This study was designed to find out a relationship of dengue infection with climatic factors such as rainfall, temperature and relative humidity during the dengue fever epidemic in the year 2003. Blood samples were collected from 1550 patients experiencing a febrile illness clinically consistent with dengue infection. Serological confirmation of Dengue Infection was done using Dengue Duo IgM and IgG Rapid Strip test (Pan Bio, Australia), which detected dengue-specific antibodies. Monthly data of total rainfall, temperature and relative humidity for the year 2003 was obtained from Meteorological Department of Delhi, New Delhi and retrospectively analyzed. Out of 1550 suspected cases, 893 cases (57.36%) were confirmed as serologically positive. The difference between numbers of serologically positive cases during different months was significant (p < 0.05). Larger proportions of serologically positive cases were observed among adults. Outbreak coincided mainly with the post monsoon period of subnormal rainfall. The difference between serologically positive cases as compared to serologically negative ones in post monsoon period was significantly higher (p < 0.001). The difference in the rainfall and temperature between three seasonal periods was significant (p < 0.05). This prospective study highlighted rain, temperature and relative humidity as the major and important climatic factors, which could alone or collectively be responsible for an outbreak. More studies in this regard could further reveal the correlation between the climatic changes and dengue outbreaks, which would help in making the strategies and plans to forecast any outbreak in future well in advance.

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Eco-epidemiological analysis of dengue infection during an outbreak of dengue fever, India.

Background & objectives: Transmission of dengue virus depends on the presence of Aedes mosquito. Mosquito generation and development is known to be influenced by the climate. This study was carried out to examine whether the climatic factors data can be used to predict yearly dengue cases of Dhaka city, Bangladesh. Methods: Monthly reported dengue cases and climate data for the years 2000-2008 were obtained from the Directorate General of Health Services (DGHS) and Meteorological Department of Dhaka, Bangladesh, respectively. Data for the period 2000 to 2007 were used for development of a model through multiple linear regressions. Retrospective validation of the model was done with 2001, 2003, 2005 and 2008 data. Log transformation of the dependent variable was done to normalize data for linear regression. Average monthly humidity, rainfall, minimum and maximum temperature were used as independent variables and number of dengue cases reported monthly was used as dependent variable. Accuracy of the model for predicting outbreak was assessed through receiver operative characteristics (ROC) curve. Results: Climatic factors, i.e. rainfall, maximum temperature and relative humidity were significantly correlated with monthly reported dengue cases. The model incorporating climatic data of two-lag month explained 61 per cent of variation in number of reported dengue cases and this model was found to predict dengue outbreak (≥ 200 cases) with considerable accuracy [area under ROC curve = 0.89, 95%CI = (0.89-0.98)]. Interpretation & conclusions: Our results showed that the climate had a major effect on the occurrence of dengue infection in Dhaka city. Though the prediction model had some limitations in predicting the monthly number of dengue cases, it could forecast possible outbreak two months in advance with considerable accuracy.

Climatic factors influencing dengue cases in Dhaka city: a model for dengue prediction.

Oxidative stress in patients with non-complicated malaria.

Introduction Definitions and Different Perspectives of GIS Computational Aspects of GIS Computing Algorithms in GIS Motivation of the Book Organization of the Book Summary Computational Geodesy Definition of Geodesy Mathematical Models of Earth Geometry of Ellipse and Ellipsoid Computing Radius of Curvature Concept of Latitude Applications of Geodesy The Indian Geodetic Reference System (IGRS) Summary Reference Systems and Coordinate Transformations Definition of Reference System Classification of Reference Systems Datum and Coordinate System Attachment of Datum to the Real World Different Coordinate Systems Used in GIS Shape of Earth Coordinate Transformations Datum Transformation Usage of Coordinate Systems Summary Basics of Map Projection What is Map Projection? and Why it is Necessary? Mathematical Definition of Map Projection Process Flow of Map Projection Azimuthal Map Projection Cylinderical Map Projection Conical Map Projection Classification of Map Projections Application of Map Projections Summary Algorithms for Rectification of Geometric Distortions Sources of Geometric Distortion Algorithms for Satellite Image Registration Scale Invariant Feature Transform (SIFT) Fourier Mellin Transform Multiresolution Image Analysis Applications of Image Registration Summary Differential Geometric Principles and Operators Properties of Gaussian, Hessian and Difference of Gaussian Summary Computational Geometry and its Application to GIS Introduction Definitions Geometric Computational Techniques Triangulation of Simple Polygon Convex Hulls in Two Dimensions Divide and Conquer Algorithm Voronoi Diagrams Delaunay Triangulation Delaunay Triangulation: Randomized Incremental Algorithm Delaunay Triangulations and Convex Hulls Applications of Voronoi Diagram and Delaunay Triangulation Summary Spatial Interpolation Techniques Non-Geostatistical Interpolators Geostatistics Summary Spatial Statistical Methods Definition of Statistics Spatial statistics Classification of statistical methods Role of statistics in GIS Descriptive Statistical Methods Inferential Statistics Point Pattern Analysis in GIS Applications of Spatial Statistical Methods Summary An Introduction to Bathymetry Spatial Analysis of Bathymetric Data and Sea GIS Measurements and Analysis Using GIS Appendix Appendix-B Glossary of GIS Terms Bibliography

Computing in Geographic Information Systems

Lipid peroxidation was assessed by measuring malondialdehyde (MDA) in 30 patients with falciparum malaria and 20 controls (10 healthy adults and 10 patients of vivax malaria). Mean serum MDA was 0.96 +/- 0.38 nmol/ml, 1.1 +/- 0.17 nmol/ml and 2.9 +/- 1.1 nmol/ml in healthy controls, disease controls and falciparum malaria patients, respectively. Levels were significantly high (P less than 0.001) in patients with falciparum malaria. Higher values were associated with more number of complications and deaths.

Lipid peroxidation in acute falciparum malaria.

An outbreak of dengue haemorrhagic fever (DHF) swept the National Capital Territory of Delhi in 1996. A total of 10,252 cases and 423 deaths due to DHF were recorded in various parts of Delhi. Delhi has been endemic for dengue since the past several years. The first DHF outbreak was reported in 1988 which resulted in 33% mortality among children admitted in hospitals. Krishnamurthy et al.) (1964) and Katyal et al. (1996) carried out comprehensive surveys of the Aedes aegypti population in Delhi. The urbanization of Delhi has since then occurred at a very fast rate, creating in the process greater opportunities for the breeding of Aedes aegypti and also for the circulation of dengue virus due to increased migration. Two major outbreaks, in 1988 and 1996, affected children below 15 years of age. This highlighted the need for a special assessment of schools and hospitals where there is a large presence of vectors and a high potential for the transmission of dengue exists.

Aedes aegypti Prevalence in Hospitals and Schools, the Priority Sites for DHF Transmission in Delhi, India

The National Capital Territory (NCT) of Delhi, the Capital of the Republic of India, is situated on the banks of the river Yamuna. It covers an area of 1485 sq km, of which 900 sq km is urban and the rest is classified under the rural category. The city has experienced a phenomenal growth in its population, and as a centre offering vast economic opportunities has been attracting migrants not only from its immediate neighbourhood but also from far off places. The population of Delhi is now estimated to be much above 10 million.

Status Report on DF/DHF During 1998 in the National Capital Territory of Delhi, India

Outbreaks of Dengue/Dengue Haemorrhagic Fever have been occuring in the National Capital Territory (NCT) Delhi from time to time. A massive outbreak of Dengue/DHF causing considerable mortality occurred in 1996 in the NCT, Delhi, Since this outbreak regular entomological surveillance has been instituted, for timely preventive action against Dengue/ DHF. The Central Cross Checking Organisation (CCO) of the National Malaria Eradication Programme cross-checks Aedes surveillance activities in Delhi. In this paper we present our experiences in entomological surveillance in relation Dengue, to share them with other workers in this field.

Narayan Panigrahi

Papers

Computing in Geographic Information Systems

Lipid peroxidation in acute falciparum malaria.

Aedes aegypti Prevalence in Hospitals and Schools, the Priority Sites for DHF Transmission in Delhi, India

Status Report on DF/DHF During 1998 in the National Capital Territory of Delhi, India

Preventing dengue/dengue haemorrhagic fever outbreaks in the National Capital Territory of Delhi--the role of entomological surveillance.