Gaurangadeb Chattopadhyay

Abstract: In India, chloroquine has been replaced by a combination of artesunate and sulfadoxine-pyrimethamine (AS-SP) for uncomplicated P. falciparum malaria. Other available combinations, artemether-lumefantrine (AM-LF) and artesunate-mefloquine (AS-MQ), not included in the national program, are widely used by private practitioners. Little is known about the therapeutic efficacy of these artemisinin combinations and the prevalence of molecular markers associated with antimalarial drug resistance. A total of 157 patients with P. falciparum monoinfection were recruited and randomized into three study groups (AS-SP, AM-LF, and AS-MQ). All patients were followed up for 42 days to study the clinical and parasitological responses according to the WHO protocol (2009). We assessed the polymorphism of the pfATPase6 , pfcrt , pfdhfr , and pfdhps genes by the DNA-sequencing method. The PCR-corrected therapeutic efficacies of AS-SP, AM-LF, and AS-MQ were 90.6% (95% confidence interval [CI], 0.793 to 0.969), 95.9% (95% CI, 0.860 to 0.995), and 100% (95% CI, 0.927 to 1.00), respectively. No specific mutational pattern was observed in the pfATPase6 gene. All isolates had a K76T mutation in the pfcrt gene. In the pfdhfr-pfdhps genotype, quadruple mutation was frequent, and quintuple mutation was documented in 6.3% of P. falciparum isolates. The significant failure rate of AS-SP (9.5%), although within the limit (10%) for drug policy change, was due to SP failure because of prevailing mutations in pfdhfr , I 51 R 59 N 108 , with pfdhps , G 437 and/or E 540 . The efficacy of this ACT needs periodic monitoring. Artemether-lumefantrine and artesunate-mefloquine are effective alternatives to the artesunate-sulfadoxine-pyrimethamine combination.

Abstract: Scientific formalizations of the notion of growth and measurement of the rate of growth in living organisms are age-old problems. The most frequently used metric, “Average Relative Growth Rate” is invariant under the choice of the underlying growth model. Theoretically, the estimated rate parameter and relative growth rate remain constant for all mutually exclusive and exhaustive time intervals if the underlying law is exponential but not for other common growth laws (e.g., logistic, Gompertz, power, general logistic). We propose a new growth metric specific to a particular growth law and show that it is capable of identifying the underlying growth model. The metric remains constant over different time intervals if the underlying law is true, while the extent of its variation reflects the departure of the assumed model from the true one. We propose a new estimator of the relative growth rate, which is more sensitive to the true underlying model than the existing one. The advantage of using this is that it can detect crucial intervals where the growth process is erratic and unusual. It may help experimental scientists to study more closely the effect of the parameters responsible for the growth of the organism/population under study.

Abstract: . A model-based predictive estimator is proposed for the population proportions of a polychotomous response variable, based on a sample from the population and on auxiliary variables, whose values are known for the entire population. The responses for the non-sample units are predicted using a multinomial logit model, which is a parametric function of the auxiliary variables. A bootstrap estimator is proposed for the variance of the predictive estimator, its consistency is proved and its small sample performance is compared with that of an analytical estimator. The proposed predictive estimator is compared with other available estimators, including model-assisted ones, both in a simulation study involving different sampling designs and model mis-specification, and using real data from an opinion survey. The results indicate that the prediction approach appears to use auxiliary information more efficiently than the model-assisted approach.

Abstract: In this paper we propose a new approach to detailed inference for any two-decision problem under the frequentist framework, based on a somewhat different interpretation of the confidence coefficients in terms of betting odds. We first elaborate this interpretation with reference to summary inference and enlarge the interpretation to the needs of detailed inference. The actual application of the proposed technique requires the choice of some suitable utility functions. We illustrate our ideas through some examples.AMS Subject Classification: 62 A 99.

Abstract: The procedure for detailed statistical inference developed by the authors in an earlier paper (1992) for the two-decision case, is extended here to the case of several decisions. Alongwith the rule for choosing the decision, the problem of stating data dependent measures of confidence in terms of betting odds, is considered. The extension involves generalization oftlie coneept of legitimacy of betting odds introduced in the earlier paper and the choice of a suitable utility function for bets. The actual solution is worked out in the case of logarithmic utility. A rather intricate mathematical result requires to be established to prove the existence of an optimum rule in this case. Application of the procedure is illustrated through some numerical examples.

Abstract: In this paper, we show that the conditional frequentist method of testing a precise hypothesis can be made virtually equiva- lent to Bayesian testing. The conditioning strategy proposed by Berger, Brown and Wolpert in 1994, for the simple versus simple case, is gener- alized to testing a precise null hypothesis versus a composite alternative hypothesis. Using this strategy, both the conditional frequentist and the Bayesian will report the same error probabilities upon rejecting or ac- cepting. This is of considerable interest because it is often perceived that Bayesian and frequentist testing are incompatible in this situation. That they are compatible, when conditional frequentist testing is allowed, is a strong indication that the \wrong" frequentist tests are currently be- ing used for postexperimental assessment of accuracy. The new unied testing procedure is discussed and illustrated in several common testing situations.

Abstract: Preexperimental frequentist error probabilities are arguably inadequate, as summaries of evidence from data, in many hypothesis-testing settings. The conditional frequentist may respond to this by identifying certain subsets of the outcome space and reporting a conditional error probability, given the subset of the outcome space in which the observed data lie. Statistical methods consistent with the likelihood principle, including Bayesian methods, avoid the problem by a more extreme form of conditioning. In this paper we prove that the conditional frequentist's method can be made exactly equivalent to the Bayesian's in simple versus simple hypothesis testing: specifically, we find a conditioning strategy for which the conditional frequentist's reported conditional error probabilities are the same as the Bayesian's posterior probabilities of error. A conditional frequentist who uses such a strategy can exploit other features of the Bayesian approach--for example, the validity of sequential hypothesis tests (including versions of the sequential probability ratio test, or SPRT) even if the stopping rule is incompletely specified.

Abstract: Background Anti-malarial drug resistance in Plasmodium falciparum in India has historically travelled from northeast India along the Myanmar border. The treatment policy for P. falciparum in the region was, therefore, changed from chloroquine to artesunate (AS) plus sulphadoxine-pyrimethamine (SP) in selected areas in 2005 and in 2008 it became the first-line treatment. Recognizing that resistance to the partner drug can limit the useful life of this combination therapy, routine in vivo and molecular monitoring of anti-malarial drug efficacy through sentinel sites was initiated in 2009.