A significant seasonal variation in tuberculosis (TB) is observed in north India during 2006-2011, particularly in states like Himachal Pradesh, Haryana and Rajasthan. To quantify the seasonal variation, we measure average amplitude (peak to trough distance) across seasons in smear positive cases of TB and observe that it is maximum for Himachal Pradesh (40.01%) and minimum for Maharashtra (3.87%). In north India, smear positive cases peak in second quarter (April-June) and reach a trough in fourth quarter (October-December), however low seasonal variation is observed in southern region of the country. The significant correlations as 0.64 (p-value<0.001), 0.54 (p-value<0.01) and 0.42 (p-value<0.05) are observed between minimum temperature and seasonality of TB at lag-1 in north, central and northeast India respectively. However, in south India, this correlation is not significant.
ABSTRACT:The present endeavour aims to identify the spatiotemporal footprints of temperature change in India by analysing monthly temperature data pertaining to the period of . Functional data analysis (FDA) has been implemented for detecting the temporal manifestation of mean change years. The estimated change years have been observed to largely pertain to the latter half of 20th century and to fall in close proximity to the previously reported global change years 1963 and 1976. Large portions of the Indian mainland have been observed to exhibit significant temperature changes after approximately every 12 years since 1940. The all-India temperature rise is estimated to be 0.53 ∘ C during 1901-2005. It has also been observed that, temperature rise has primarily occurred during post-monsoon and winter seasons. An index, consolidating the results of FDA such as change years and temperature rise, has been developed to quantify temperature-change severity. Based on the spatial distribution of index values, the hot-spots have been found to cluster over the north-central and eastern parts of the country.
Tuberculosis (TB) is one of the most common infectious diseases and a leading cause of death in the world. Despite the full implementation of Revised National Tuberculosis Control Programme, the disease continues to be a leading cause of morality and economic burden in India. The basic reproduction is a fundamental key parameter that quantifies the spread of a disease. In this article, we present a Bayesian melding approach to estimate the basic reproduction number using a deterministic model of TB. We present a point estimate of the basic reproduction number of 35 states and union territories of India during 2006 to 2011. The basic reproduction number of TB for India is computed to be 0.92, which indicates the slow elimination of TB in India during 2006 to 2011.
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