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Atul Kakar

Bio: Atul Kakar is an academic researcher. The author has contributed to research in topics: Population & Section (typography). The author has an hindex of 3, co-authored 47 publications receiving 45 citations.

Papers
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Book ChapterDOI
01 Jan 2022
TL;DR: In this paper, the determination of an adequate sample size is a prerequisite for any research program and a study concluded on the basis of a smaller sample size than required is termed an underpowered study and its reliability is questionable.
Abstract: The determination of an adequate sample size is a prerequisite for any research programme. A study concluded on the basis of a smaller sample size than required is termed an ‘underpowered study’ and its reliability is questionable. Such a study may lead to faulty conclusions and consequent waste of resources. On the other hand, a study with a larger sample size than required may enhance its reliability but unnecessarily consumes expensive resources, takes a long time, and may even put the subjects to various health hazards. Thus, the researcher should look for an adequate sample size that can serve the purpose of this study.

6 citations

Journal ArticleDOI
TL;DR: Hemoglobin and absolute lymphocyte counts obtained on automated cell counter are robust, cost-effective and easily available methods to follow up PLHA patients and patients on ART and are especially useful in a developing country where the cost of these tests is one-fifth of flow cytometry.
Abstract: India is a developing country where resources are limited. HIV/ AIDS is an ominous public health problem faced by our population and the affordability of patients for 3-6 monthly monitoring of CD4 counts becomes difficult for most patients. The intent of the study was to identify parameters on complete blood counts that can predict a CD4 count of 1250/μL is predictive of a CD4 count <200/μL with a sensitivity and specificity of 87.3% and 70.0% respectively. In addition, a haemoglobin value <11.15g/dL is also a good predictor of the CD4 count <200/μL. The combination of both Hb <11.15g/dl and ALC counter <1250/μL was like a confirmatory test with a specificity of 92.2% and a NPV of 79.5%. Hemoglobin and absolute lymphocyte counts obtained on automated cell counter are robust, cost-effective and easily available methods to follow up PLHA patients and patients on ART. These can effectively predict the CD4 count <200/μL and are especially useful in a developing country where the cost of these tests is one-fifth of flow cytometry.

4 citations

Journal ArticleDOI
TL;DR: This case imparts an important message to look for presence of coexisting entities in a single specimen and highlights the benefits of testing both plasma cell and B-cell compartments when the clinical features are not entirely consistent Flow cytometry together with protein electrophoresis can help to clinch difficult and rare dual diagnosis.
Abstract: A 74 years old male patient, presented with history of generalized weakness, fatigue, loss of appetite and breathlessness on exertion for past one and a half months On examination, he was found to have significant pallor and generalized lymphadenopathy (cervical, axillary and inguinal) The skeletal survey showed punched out lytic lesions in skull and pelvic bones The peripheral smear examination showed lymphocytosis with absolute lymphocyte count of 25,000/μL The bone marrow aspirates revealed a hypercellular marrow with 74 % lymphocytes & 14 % plasma cells, suggestive of chronic lymphoplasmacytic disorder The bone marrow biopsy had two morphologically distinct populations of lymphocytes & plasma cells The immunohistochemical markers on bone marrow biopsy showed hat plasma cells were positive for CD138 with kappa light chain restriction Flow cytometry showed B cell population with CD19/CD5 co expression, CD5/CD23 coexpression, were positive for CD22, CD20 and negative for FMC-7 and lambda light chain In addition, plasma cells were also identified as CD45 negative cells and showed CD38/CD138 co-expression with variable CD19 and CD56 positivity Serum protein electrophoresis revealed M band, serum immunofixation electrophoresis corresponded to IgA -Kappa The final diagnosis of chronic lymphocytic leukemia with concomittant presence of plasma cell myeloma was concluded This case imparts an important message to look for presence of coexisting entities in a single specimen and highlights the benefits of testing both plasma cell and B-cell compartments when the clinical features are not entirely consistent Flow cytometry together with protein electrophoresis can help to clinch difficult and rare dual diagnosis These cases are rare and pose therapeutic challenge

3 citations


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Journal ArticleDOI
TL;DR: In this article, the authors evaluated the spatiotemporal variations in five criteria pollutants over two time periods, i.e., March-April 2019 and March -April 2020 and 10th-20th March 2020 (before lockdown) and 25th March to 6th April 2020 (during lockdown).
Abstract: The coronavirus disease (COVID-19) created enormous pressure across the globe due to an increasing number of COVID-19 infected cases. All the governments’ primary focus is to save humanity from this pandemic problem, and they have lockdown almost the entire nation to stop the spread of infection. This lockdown resulted in a considerable impact on the global as well as a local economy that will take a long time to perform with business as usual scenario. However, improvement in the air quality of the cities across the globe has emerged as a key benefit of this lockdown. Therefore, this study aims to assess the overall impact of social and travel lockdown in five megacities of India; Delhi, Mumbai, Chennai, Kolkata, and Bangalore. The study evaluated the spatiotemporal variations in five criteria pollutants over two time periods, i.e., March–April 2019 and March–April 2020 and 10th–20th March 2020 (before lockdown) and 25th March to 6th April 2020 (during lockdown). The results highlighted a statistically significant decline in all the pollutants in all the megacities except for ozone. It was observed that the concentration of PM2.5, PM10, NO2 and CO declined by ~41% (66–39 µg m–3), ~52% (153–73 µg m–3), ~51% (39–19 µg m–3) and ~28% (0.9–0.65 mg m–3) during the lockdown phase in comparison to the before lockdown in Delhi, respectively. Similar decline in pollutant concentration was observed in other megacities as well. Further, the study conducted an expert survey to identify the possible challenges India might face after lockdown is over. All the experts said that reviving the economy will be a big challenge for the government, and it may result in some tradeoff while managing the air quality in the near future due to scarcity of funds, etc.

202 citations

Posted ContentDOI
18 Apr 2020-medRxiv
TL;DR: The short- and long-term impact of an initial 21-day lockdown on the total number of COVID-19 cases in India compared to other less severe non-pharmaceutical interventions is studied using epidemiological forecasting models and Bayesian estimation algorithms.
Abstract: Importance: India has taken strong and early public health measures for arresting the spread of the COVID-19 epidemic. With only 536 COVID-19 cases and 11 fatalities, India - a democracy of 1.34 billion people - took the historic decision of a 21-day national lockdown on March 25. The lockdown was further extended to May 3, soon after the analysis of this paper was completed. Objective: To study the short- and long-term impact of an initial 21-day lockdown on the total number of COVID-19 cases in India compared to other less severe non-pharmaceutical interventions using epidemiological forecasting models and Bayesian estimation algorithms; to compare effects of hypothetical durations of lockdown from an epidemiological perspective; to study alternative explanations for slower growth rate of the virus outbreak in India, including exploring the association of the number of cases and average monthly temperature; and finally, to outline the pivotal role of reliable and transparent data, reproducible data science methods, tools and products as we reopen the country and prepare for a post lock-down phase of the pandemic. Design, Setting, and Participants: We use the daily data on the number of COVID-19 cases, of recovered and of deaths from March 1 until April 7, 2020 from the 2019 Novel Coronavirus Visual Dashboard operated by the Johns Hopkins University Center for Systems Science and Engineering (JHU CSSE). Additionally, we use COVID-19 incidence counts data from Kaggle and the monthly average temperature of major cities across the world from Wikipedia. Main Outcome and Measures: The current time-series data on daily proportions of cases and removed (recovered and death combined) from India are analyzed using an extended version of the standard SIR (susceptible, infected, and removed) model. The eSIR model incorporates time-varying transmission rates that help us predict the effect of lockdown compared to other hypothetical interventions on the number of cases at future time points. A Markov Chain Monte Carlo implementation of this model provided predicted proportions of the cases at future time points along with credible intervals (CI). Results: Our predicted cumulative number of COVID-19 cases in India on April 30 assuming a 1-week delay in people9s adherence to a 21-day lockdown (March 25 - April 14) and a gradual, moderate resumption of daily activities after April 14 is 9,181 with upper 95% CI of 72,245. In comparison, the predicted cumulative number of cases under "no intervention" and "social distancing and travel bans without lockdown" are 358 thousand and 46 thousand (upper 95% CI of nearly 2.3 million and 0.3 million) respectively. An effective lockdown can prevent roughly 343 thousand (upper 95% CI 1.8 million) and 2.4 million (upper 95% CI 38.4 million) COVID-19 cases nationwide compared to social distancing alone by May 15 and June 15, respectively. When comparing a 21-day lockdown with a hypothetical lockdown of longer duration, we find that 28-, 42-, and 56-day lockdowns can approximately prevent 238 thousand (upper 95% CI 2.3 million), 622 thousand (upper 95% CI 4.3 million), 781 thousand (upper 95% CI 4.6 million) cases by June 15, respectively. We find some suggestive evidence that the COVID-19 incidence rates worldwide are negatively associated with temperature in a crude unadjusted analysis with Pearson correlation estimates [95% confidence interval] between average monthly temperature and total monthly incidence around the world being -0.185 [-0.548, 0.236] for January, -0.110 [-0.362, 0.157] for February, and -0.173 [-0.314, -0.026] for March. Conclusions and Relevance: The lockdown, if implemented correctly in the end, has a high chance of reducing the total number of COVID-19 cases in the short term, and buy India invaluable time to prepare its healthcare and disease monitoring system. Our analysis shows we need to have some measures of suppression in place after the lockdown for the best outcome. We cannot heavily rely on the hypothetical prevention governed by meteorological factors such as temperature based on current evidence. From an epidemiological perspective, a longer lockdown between 42-56 days is preferable. However, the lockdown comes at a tremendous price to social and economic health through a contagion process not dissimilar to that of the coronavirus itself. Data can play a defining role as we design post-lockdown testing, reopening and resource allocation strategies. Software: Our contribution to data science includes an interactive and dynamic app (covind19.org) with short- and long-term projections updated daily that can help inform policy and practice related to COVID-19 in India. Anyone can visualize the observed data for India and create predictions under hypothetical scenarios with quantification of uncertainties. We make our prediction codes freely available (https://github.com/umich-cphds/cov-ind-19) for reproducible science and for other COVID-19 affected countries to use them for their prediction and data visualization work.

72 citations

Journal ArticleDOI
TL;DR: The findings emphasize the need to develop context-adequate education and communication programs to raise vigilance about asymptomatic transmission and to sustain preventative behaviors.
Abstract: The health and economic consequences of the COVID-19 pandemic is expected to disproportionately impact residents of lower-middle income countries Understanding the psychological impact of the pandemic is important to guide outreach interventions In this study, we examined people's awareness of COVID-19 symptoms, risk perception, and changes in behaviors and stress levels during the lockdown in peri-urban Tamil Nadu India Field workers conducted phone call surveys (included n = 2044) in 26 communities from 20-25 May 2020 The majority perceived no (60%) or low (23%) level of risk of personally contracting coronavirus Common fears were related to health and economic concerns, including loss of income (62%), inability to travel freely (46%), and becoming sick (46%) Residents were well aware of the common symptoms of COVID-19, such as fever (66%) and dry cough (57%), but not the asymptomatic transmission (24%) The majority experienced increased stress about finance (79%) and the lockdown (51%) Our findings emphasize the need to develop context-adequate education and communication programs to raise vigilance about asymptomatic transmission and to sustain preventative behaviors The evidence on fear and changes in stress levels could inform designing coping strategies and programs focused on mental well-being

67 citations

Journal ArticleDOI
TL;DR: The way forward could be a pragmatic and utilitarian approach involving continued access to alcohol, while observing all physical distancing norms necessary during the pandemic, for those who want to continue drinking; and implementing innovative measures such as tele-counselling for thosewho wish not to return back to drinking.

52 citations

Journal ArticleDOI
TL;DR: In this paper, the authors analyzed the impact of COVID-19 pandemic on air pollution in eight major cities of India (Delhi, Ahmedabad, Kolkata, Mumbai, Hyderabad, Chennai, Bengaluru and Pune).
Abstract: Air pollution poses a grave health risk and is a matter of concern for researchers around the globe. Toxic pollutants like nitrogen dioxide (NO2) is a result of industrial and transport sector emissions and need to be analysed at the current scenario. After the world realised the effect of COVID-19 pandemic, countries around the globe proposed complete lockdown to contain the spread. The present research focuses on analysing the gaseous pollution scenarios, before and during lockdown through satellite (Sentinel-5P data sets) and ground-based measurements (Central Pollution Control Board’s Air Quality Index, AQI) for 8 five-million plus cities in India (Delhi, Ahmedabad, Kolkata, Mumbai, Hyderabad, Chennai, Bengaluru and Pune). The long-term exposure to NO2 was also linked to pandemic-related mortality cases across the country. An average of 46% reduction in average NO2 values and 27% improvement in AQI was observed in the eight cities during the first lockdown phase with respect to pre-lockdown phase. Also, 53% of Corona positive cases and 61% of fatality cases were observed in the eight major cities of the country alone, coinciding with locations having high long-term NO2 exposure.

46 citations