A sequential approach for noninferiority or equivalence of a linear contrast under cost constraints.

Planning an appropriate sample size for a study involves considering several issues. Two important considerations are cost constraints and variability inherent in the population from which data will be sampled. Methodologists have developed sample size planning methods for two or more populations when testing for equivalence or noninferiority/superiority for a linear contrast of population means. Additionally, cost constraints and variance heterogeneity among populations have also been considered. We extend these methods by developing a theory for sequential procedures for testing the equivalence or noninferiority/superiority for a linear contrast of population means under cost constraints, which we prove to effectively utilize the allocated resources. Our method, due to the sequential framework, does not require prespecified values of unknown population variance(s), something that is historically an impediment to designing studies. Importantly, our method does not require an assumption of a specific type of distribution of the data in the relevant population from which the observations are sampled, as we make our developments in a data distribution-free context. We provide an illustrative example to show how the implementation of the proposed approach can be useful in applied research. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Application of pooled testing in estimating the prevalence of COVID-19.

Testing at a mass scale has been widely accepted as an effective way to contain the spread of the SARS-CoV-2 Virus. In the initial stages, the shortage of test kits severely restricted mass-scale testing. Pooled testing was offered as a partial solution to this problem. However, it is a relatively lesser-known fact that pooled testing can also result in significant gains, both in terms of cost savings as well as measurement accuracy, in prevalence estimation surveys. We review here the statistical theory of pooled testing for screening as well as for prevalence estimation. We study the impact of the diagnostic errors, and misspecification of the sensitivity and the specificity on the performances of the pooled as well as individual testing procedures. Our investigation clarifies some of the issues hotly debated in the context of COVID-19 and shows the potential gains for the Indian Council for Medical Research (ICMR) in using a pooled sampling for their upcoming COVID-19 prevalence surveys.

Beyond job security and money: driving factors of motivation for government doctors in India.

BACKGROUND: Despite many efforts from government to address the shortage of medical officers (MOs) in rural areas, rural health centres continue to suffer from severe shortage of MOs. Lack of motivation to join and continue service in rural areas is a major reason for such shortage. In the present study, we aimed to assess and rank the driving factors of motivation important for in-service MOs in their current job. METHODS: The study participants included ninety two in-service government MOs from three states in India. The study participants were required to rank 14 factors of motivation important for them in their current job. The factors for the study were selected using Herzberg's two-factor theory of motivation and the data were collected using an instrument that has an established reliability and validity. Test of Kendall's coefficient of concordance (W) was carried out to assess the agreement in ranks assigned by participants to various motivation factors. Next, we studied the distributions of ranks of different motivating factors using standard descriptive statistics and box plots, which gave us interesting insights into the strength of agreement of the MOs in assigning ranks to various factors. And finally to assess whether MOs are more intrinsically motivated or extrinsically motivated, we used Kolmogorov-Smirnov test. RESULTS: The (W) test indicated statistically significant (P < 0.01) agreement of the participants in assigning ranks. The Kolmogorov-Smirnov test indicated that from policy perspectives, MOs place significantly more motivational importance to intrinsic factors than to extrinsic factors. The study results indicate that job security was the most important factor related to motivation, closely followed by interesting work and respect and recognition. Among the top five preferred factors, three were intrinsic factors indicating a great importance given by MOs to factors beyond money and job security. CONCLUSION: To address the issue of motivation, the health departments need to pay close attention to devising management strategies that address not only extrinsic but also intrinsic factors of motivation. The study results may be useful to understand the complicated issue of work motivation and can give some useful insights to design comprehensive management strategies that are based on motivational needs of MOs.

Increased mortality rate associated with chikungunya epidemic, Ahmedabad, India.

In 2005-2006, Réunion Island in the Indian Ocean reported approximately 266,000 cases of chikungunya; 254 were fatal (case-fatality rate 1/1,000). India reported 1.39 million cases of chikungunya fever in 2006 with no attributable deaths; Ahmedabad, India, reported 60,777 suspected chikungunya cases. To assess the effect of this epidemic, mortality rates in 2006 were compared with those in 2002-2005 for Ahmedabad (population 3.8 million). A total of 2,944 excess deaths occurred during the chikungunya epidemic (August-November 2006) when compared with the average number of deaths in the same months during the previous 4 years. These excess deaths may be attributable to this epidemic. However, a hidden or unexplained cause of death is also possible. Public health authorities should thoroughly investigate this increase in deaths associated with this epidemic and implement measures to prevent further epidemics of chikungunya.