On forecasting the Indian summer monsoon: The intriguing season of 2002

This year, the rainfall over India during the first half of the summer monsoon season was 30 below normal. This has naturally led to a lot of concern and speculation about the causes. We have shown that the deficit in rainfall is a part of the natural variability. Analysis of the past data suggests that there is a 78 chance that seasonal mean rainfall this year will be 10 or more below the long-term average value. We discuss briefly how forecasts for seasonal rainfall are generated, whether this event could have been foreseen, and share our perspective on the problems and prospects of forecasting the summer monsoon rainfall over the Indian region

A comparison of weather variables linked to infectious disease patterns using laboratory addresses and patient residence addresses

Background: To understand the impact of weather on infectious diseases, information on weather parameters at patient locations is needed, but this is not always accessible due to confidentiality or data availability. Weather parameters at nearby locations are often used as a proxy, but the accuracy of this practice is not known. Methods: Daily Campylobacter and Cryptosporidium cases across England and Wales were linked to local temperature and rainfall at the residence postcodes of the patients and at the corresponding postcodes of the laboratory where the patient’s specimen was tested. The paired values of daily rainfall and temperature for the laboratory versus residence postcodes were interpolated from weather station data, and the results were analysed for agreement using linear regression. We also assessed potential dependency of the findings on the relative geographic distance between the patient’s residence and the laboratory. Results: There was significant and strong agreement between the daily values of rainfall and temperature at diagnostic laboratories with the values at the patient residence postcodes for samples containing the pathogens Campylobacter or Cryptosporidium. For rainfall, the R-squared was 0.96 for the former and 0.97 for the latter, and for maximum daily temperature, the R-squared was 0.99 for both. The overall mean distance between the patient residence and the laboratory was 11.9 km; however, the distribution of these distances exhibited a heavy tail, with some rare situations where the distance between the patient residence and the laboratory was larger than 500 km. These large distances impact the distributions of the weather variable discrepancies (i.e. the differences between weather parameters estimated at patient residence postcodes and those at laboratory postcodes), with discrepancies up to ±10 °C for the minimum and maximum temperature and 20 mm for rainfall. Nevertheless, the distributions of discrepancies (estimated separately for minimum and maximum temperature and rainfall), based on the cases where the distance between the patient residence and the laboratory was within 20 km, still exhibited tails somewhat longer than the corresponding exponential fits suggesting modest small scale variations in temperature and rainfall. Conclusion: The findings confirm that, for the purposes of studying the relationships between meteorological variables and infectious diseases using data based on laboratory postcodes, the weather results are sufficiently similar to justify the use of laboratory postcode as a surrogate for domestic postcode. Exclusion of the small percentage of cases where there is a large distance between the residence and the laboratory could increase the precision of estimates, but there are generally strong associations between daily weather parameters at residence and laboratory

A Prospective Three-Year Cohort Study of the Epidemiology and Virology of Acute Respiratory Infections of Children in Rural India

Acute respiratory infection (ARI) is a major killer of children in developing countries. Although the frequency of ARI is similar in both developed and developing countries, mortality due to ARI is 10-50 times higher in developing countries. Viruses are common causes of ARI among such children, yet the disease burden of these infections in rural communities is unknown.A prospective longitudinal study was carried out in children enrolled from two rural Indian villages at birth and followed weekly for the development of ARI, classified as upper respiratory infection, acute lower respiratory infection (ALRI), or severe ALRI. Respiratory syncytial virus (RSV), influenza, parainfluenza viruses and adenoviruses in nasopharyngeal aspirates were detected by direct fluorescent antibody testing (DFA) and, in addition, centrifugation enhanced culture for RSV was done. 281 infants enrolled in 39 months and followed until 42 months. During 440 child years of follow-up there were 1307 ARIs, including 236 ALRIs and 19 severe ALRIs. Virus specific incidence rates per 1000 child years for RSV were total ARI 234, ALRI 39, and severe ALRI 9; for influenza A total ARI 141, ALRI 39; for INF B total ARI 37; for PIV1 total ARI 23, for PIV2 total ARI 28, ALRI 5; for parainfluenza virus 3 total ARI 229, ALRI 48, and severe ALRI 5 and for adenovirus total ARI 18, ALRI 5. Repeat infections with RSV were seen in 18 children.RSV, influenza A and parainfluenza virus 3 were important causes of ARI among children in rural communities in India. These data will be useful for vaccine design, development and implementation purposes

Lessons from the Pacific programme to eliminate lymphatic filariasis: a case study of 5 countries

Lymphatic Filariasis (LF) is an important Neglected Tropical Disease, being a major cause of disability worldwide. The Global Programme to Eliminate Lymphatic Filariasis aims to eliminate LF as a public health problem by the year 2020, primarily through repeated Mass Drug Administration (MDA). The Pacific region programme commenced in 1999. By June 2007, five of the eleven countries classified as endemic had completed five MDA campaigns and post-MDA prevalence surveys to assess their progress. We review available programme data and discuss their implications for other LF elimination programs in developing countries. Reported MDA coverage and results from initial surveys and post-MDA surveys of LF using the immunochromatographic test (ICT) from these five Pacific Island countries (Tonga, Niue, Vanuatu, Samoa and Cook Islands) were analysed to provide an understanding of their quality and programme progress towards LF elimination. Denominator data reported by each country programme for 2001 was compared to official sources to assess the accuracy of MDA coverage data. Initial survey results from these five countries revealed an ICT prevalence of between 2.7 and 8.6 percent in individuals tested prior to commencement of the programme. Country MDA coverage results varied depending on the source of denominator data. Of the five countries in this case study, three countries (Tonga, Niue and Vanuatu) reached the target prevalence of <1% antigenaemia following five rounds of MDA. However, endpoint data could not be reliably compared to baseline data as survey methodology varied. It was concluded that accurate and representative baseline and post-campaign prevalence data is crucial for determining program effectiveness and the factors contributing to effectiveness. This is emphasised by the findings of this case study. While three of the five Pacific countries reported achieving the target prevalence of <1% antigenaemia, limitations in the data preclude identification of key determinants of this achievement

The benefit of symbols: monkeys show linear, human-like, accuracy when using symbols to represent scalar value

When humans and animals estimate numbers of items, their error rate is proportional to the number. To date, however, only humans show the capacity to represent large numbers symbolically, which endows them with increased precision, especially for large numbers, and with tools for manipulating numbers. This ability depends critically on our capacity to acquire and represent explicit symbols. Here we show that when rhesus monkeys are trained to use an explicit symbol system, they too show more precise, and linear, scaling than they do using a one-to-one corresponding numerosity representation. We also found that when taught two different types of representations for reward amount, the monkeys systematically undervalued the less precise representation. The results indicate that monkeys, like humans, can learn alternative mechanisms for representing a single value scale and that performance variability and relative value depend on the distinguishability of each representation

Meta-Analysis of the Association between Transforming Growth Factor-Beta Polymorphisms and Complications of Coronary Heart Disease

Objective: To investigate the association between common transforming growth factor beta (TGF-β) single nucleotide polymorphisms (SNP) and significant complications of coronary heart disease (CHD).\ud \ud Method: We performed a meta-analysis of published case-control studies assessing the association of TGF-β SNPs with a range of CHD complications. A random effects model was used to calculate odds ratios and confidence intervals. Analyses were conducted for additive, dominant and recessive modes of inheritance.\ud \ud Results: Six studies involving 5535 cases and 2970 controls examining the association of common SNPs in TGF-β1 with CHD were identified. Applying a dominant model of inheritance, three TGF-β1 SNPs were significantly associated with CHD complications: The T alleles of rs1800469 (OR = 1.125, 95% CI 1.016–1.247, p = 0.031) and rs1800470 (OR = 1.146, 95% CI 1.026–1.279, p = 0.021); and the C allele of rs1800471 (OR = 1.207, 95% CI 1.037–1.406, p = 0.021).\ud \ud Conclusion: This meta-analysis suggests that common genetic polymorphisms in TGF-β1 are associated with complications of CHD

Estimating Design Effect and Calculating Sample Size for Respondent-Driven Sampling Studies of Injection Drug Users in the United States

Respondent-driven sampling (RDS) has become increasingly popular for sampling hidden populations, including injecting drug users (IDU). However, RDS data are unique and require specialized analysis techniques, many of which remain underdeveloped. RDS sample size estimation requires knowing design effect (DE), which can only be calculated post hoc. Few studies have analyzed RDS DE using real world empirical data. We analyze estimated DE from 43 samples of IDU collected using a standardized protocol. We find the previous recommendation that sample size be at least doubled, consistent with DE = 2, underestimates true DE and recommend researchers use DE = 4 as an alternate estimate when calculating sample size. A formula for calculating sample size for RDS studies among IDU is presented. Researchers faced with limited resources may wish to accept slightly higher standard errors to keep sample size requirements low. Our results highlight dangers of ignoring sampling design in analysis

Three dimensional first-pass myocardial perfusion imaging at 3T: feasibility study

<p>Abstract</p> <p>Background</p> <p>In patients with ischemic heart disease, accurate assessment of the extent of myocardial perfusion deficit may be important in predicting prognosis of clinical cardiac outcomes. The aim of this study was to compare the ability of three dimensional (3D) and of two dimensional (2D) multi-slice myocardial perfusion imaging (MPI) using cardiovascular magnetic resonance (CMR) in determining the size of defects, and to demonstrate the feasibility of 3D MPI in healthy volunteers at 3 Tesla.</p> <p>Methods</p> <p>A heart phantom was used to compare the accuracy of 3D and 2D multi-slice MPI in estimating the volume fraction of seven rubber insets which simulated transmural myocardial perfusion defects. Three sets of cross-sectional planes were acquired for 2D multi-slice imaging, where each set was shifted along the partition encoding direction by ± 10 mm. 3D first-pass contrast-enhanced (0.1 mmol/kg Gd-DTPA) MPI was performed in three volunteers with sensitivity encoding for six-fold acceleration. The upslope of the myocardial time-intensity-curve and peak SNR/CNR values were calculated.</p> <p>Results</p> <p>Mean/standard deviation of errors in estimating the volume fraction across the seven defects were -0.44/1.49%, 2.23/2.97%, and 2.59/3.18% in 3D, 2D 4-slice, and 2D 3-slice imaging, respectively. 3D MPI performed in healthy volunteers produced excellent quality images with whole left ventricular (LV) coverage. Peak SNR/CNR was 57.6 ± 22.0/37.5 ± 19.7 over all segments in the first eight slices.</p> <p>Conclusion</p> <p>3D performed better than 2D multi-slice MPI in estimating the size of perfusion defects in phantoms. Highly accelerated 3D MPI at 3T was feasible in volunteers, allowing whole LV coverage with excellent image quality and high SNR/CNR.</p