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Algorithm for sample availability prediction in a hospital-based epidemiological study spreadsheet-based sample availability calculator.

ABSTRACT: Looking at the population's behavior by taking samples is quite uncertain due to its big and dynamic structure and unimaginable variability. All quantitative sampling approaches aim to draw a representative sample from the population so that the results of the studying samples can then be generalized back to the population. The probability of detecting a true effect of a study largely depends on the sample size and if taking small samples will give lowers statistical power, higher risk of missing a meaningful underlying difference. The probability of rejecting the null hypothesis i.e., finding significant difference using the sample largely depends upon the statistical power. There are a lot of online tools used for calculating the sample size, but none tell us about the availability of samples from single site in a fixed span. This study aims to provide an efficient calculation method for the availability of samples during a specific period of a research study which is an important question to be answered during the research study design. So, we have designed a spreadsheet-based sample availability calculator tool implemented in MS-Excel 2007.

SUBMITTER: Sudershan A

PROVIDER: S-EPMC8814063 | biostudies-literature | 2022 Feb

REPOSITORIES: biostudies-literature

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Algorithm for sample availability prediction in a hospital-based epidemiological study spreadsheet-based sample availability calculator.

Sudershan Amrit A Mahajan Kanak K Panjaliya Rakesh K RK Dhar Manoj K MK Kumar Parvinder P

Scientific reports 20220203 1

Looking at the population's behavior by taking samples is quite uncertain due to its big and dynamic structure and unimaginable variability. All quantitative sampling approaches aim to draw a representative sample from the population so that the results of the studying samples can then be generalized back to the population. The probability of detecting a true effect of a study largely depends on the sample size and if taking small samples will give lowers statistical power, higher risk of missin ...[more]

PMID: 35115548

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Project description:IntroductionSri Lanka has one of the highest incidences of leptospirosis worldwide. We hypothesised that different geographical locations and patient context will have a distinct molecular epidemiology of leptospirosis, based on microgeographical characteristics related to regiona-specific Leptospira predominance. Our objective is to characterise the clinical, epidemiological and molecular aspects of leptospirosis in Sri Lanka to understand disease progression, risk factors and obtain isolates of Leptospira.Methods and analysisWe designed a multicentre prospective study in Sri Lanka to recruit undifferentiated febrile patients and conduct follow-ups during hospital stays. Patients will be recruited from outpatient departments and medical wards. This study will be conducted at two main sites (Anuradhapura and Peradeniya) and several additional sites (Awissawella, Ratnapura and Polonnaruwa). Blood and urine will be collected from patients on the day of admission to the ward or presentation to the outpatient department. Bedside inoculation of 2-4 drops of venous blood will be performed with Ellinghausen-McCullough-Johnson-Harris (EMJH) semisolid media supplemented with antibiotics. Regionally optimised microscopic agglutination test, culture and qPCR-evidence will be performed to confirm the presence of Leptospira in blood which in turn will confirm the presence of disease. Whole genome sequencing will be carried out for all isolates recovered from patients. Multilocus sequence typing (MLST) will be used for the genotyping of new isolates. Sri Lankan isolates will be identified using three published MLST schemes for Leptospira.Ethics and disseminationEthical clearance for the study was obtained from Ethics Review Committees (ERC), Medicine and Allied Sciences (FMAS), Rajarata University of Sri Lanka (RUSL) and University of Peradeniya. All genomic data generated through this project will be available at GenBank. Anonymised data will be deposited at the ERC, FMAS, RUSL.

Dataset Information

Algorithm for sample availability prediction in a hospital-based epidemiological study spreadsheet-based sample availability calculator.

Publications

Algorithm for sample availability prediction in a hospital-based epidemiological study spreadsheet-based sample availability calculator.

Similar Datasets

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