scholarly journals Sample size calculation for estimating key epidemiological parameters using serological data and mathematical modelling

2018 ◽  
Author(s):  
Stéphanie Blaizot ◽  
Sereina A. Herzog ◽  
Steven Abrams ◽  
Heidi Theeten ◽  
Amber Litzroth ◽  
...  
Keyword(s):  
Mathematical Modelling ◽  
Sample Size ◽  
Optimal Allocation ◽  
Age Groups ◽  
Serological Survey ◽  
Cross Sectional ◽  
Simulation Based ◽  
Sample Size Calculations ◽  
Sampling Structure ◽  
Epidemiological Parameters

AbstractBackgroundOur work was motivated by the need to, given serum availability and/or financial resources, decide on which samples to test for different pathogens in a serum bank. Simulation-based sample size calculations were performed to determine the age-based sampling structures and optimal allocation of a given number of samples for testing across various age groups best suited to estimate key epidemiological parameters (e.g., seroprevalence or force of infection) with acceptable precision levels in a cross-sectional seroprevalence survey.MethodsStatistical and mathematical models and three age-based sampling structures (survey-based structure, population-based structure, uniform structure) were used. Our calculations are based on Belgian serological survey data collected in 2002 where testing was done, amongst others, for the presence of IgG antibodies against measles, mumps, and rubella, for which a national mass immunisation programme was introduced in 1985 in Belgium, and against varicella-zoster virus and parvovirus B19 for which the endemic equilibrium assumption is tenable in Belgium.ResultsThe optimal age-based sampling structure to use in the sampling of a serological survey as well as the optimal allocation distribution varied depending on the epidemiological parameter of interest for a given infection and between infections.ConclusionsWhen estimating key epidemiological parameters with acceptable levels of precision within the context of a single cross-sectional serological survey, attention should be given to the age-based sampling structure. Simulation-based sample size calculations in combination with mathematical modelling can be utilised for choosing the optimal allocation of a given number of samples over various age groups.

scholarly journals Sample Size Calculations for Variant Surveillance in the Presence of Biological and Systematic Biases

2022 ◽  
Author(s):  
Shirlee Wohl ◽  
Elizabeth C Lee ◽  
Bethany L DiPrete ◽  
Justin Lessler
Keyword(s):  
Sample Size ◽  
Disease Outbreaks ◽  
Sample Sizes ◽  
Cross Sectional ◽  
Continuous Sampling ◽  
Infectious Disease Outbreaks ◽  
Sample Size Calculations ◽  
Surveillance Programs ◽  
Systematic Biases ◽  
Pathogen Genome

As demonstrated during the SARS-CoV-2 pandemic, detecting and tracking the emergence and spread of pathogen variants is an important component of monitoring infectious disease outbreaks. Pathogen genome sequencing has emerged as the primary tool for variant characterization, so it is important to consider the number of sequences needed when designing surveillance programs or studies, both to ensure accurate conclusions and to optimize use of limited resources. However, current approaches to calculating sample size for variant monitoring often do not account for the biological and logistical processes that can bias which infections are detected and which samples are ultimately selected for sequencing. In this manuscript, we introduce a framework that models the full process from infection detection to variant characterization and demonstrate how to use this framework to calculate appropriate sample sizes for sequencing-based surveillance studies. We consider both cross-sectional and continuous sampling, and we have implemented our method in a publicly available tool that allows users to estimate necessary sample sizes given a specific aim (e.g., variant detection or measuring variant prevalence) and sampling method. Our framework is designed to be easy to use, while also flexible enough to be adapted to other pathogens and surveillance scenarios.

scholarly journals Haematological Parameters Associated with Malaria and Its Controls

2019 ◽  
pp. 1-13
Author(s):  
Ussher Abeku Francis ◽  
Amiteye Daniel
Keyword(s):  
Blood Cell ◽  
Sample Size ◽  
Age Groups ◽  
Haematological Parameters ◽  
Cross Sectional ◽  
Counter Machine ◽  
Haematological Profile ◽  
Initiation Of Therapy ◽  
Cell Counter ◽  
Rbc Count

Aims: This research aimed to evaluate the haematological parameters associated with malaria and its controls. Materials and Methods: A convenient cross-sectional technique was used for the study for which the sample size was determined by using the formula; n= Z² (P) (1-P) / (A) ². The haematological profile was performed using the Sysmex 2000i automated blood cell counter machine. Results and Discussion: The erythrocyte profiles (RBC, HB, HCT, RDW-SD and RDW-CV) are highly affected by malaria, whereas MCH, MCHC, and MCV did not show significant variations between the positive malaria cases and negative malaria cases. Means of haemoglobin concentrations, RBC count and HCT values for cases with positive malaria were significantly lower than negative malaria cases and controls for all the age groups and sexes. Conclusion: The study showed that there were haematological profiles between the positive and negative malaria cases and this can be used in conjunction with clinical and microscopic parameters to heighten the suspicion of malaria as well as prompt initiation of therapy for diagnosing malaria.

OVARIAN VOLUME BETWEEN FERTILE AND INFERTILE MARRIED WOMEN WITH TRANSVAGINAL SONOGRAPHY

2019 ◽  
Vol 16 (4) ◽  
pp. 101-104
Author(s):  
Sarah Yunus ◽  
Sadaf Rasheed ◽  
Amir Amanullah ◽  
Shehla Aman ◽  
Usman Ullah ◽  
...  
Keyword(s):  
Sample Size ◽  
Demographic Variable ◽  
Color Doppler ◽  
Age Groups ◽  
Sampling Technique ◽  
Transvaginal Sonography ◽  
P Value ◽  
Cross Sectional ◽  
Ovarian Volume ◽  
Infertile Women

Background: Infertility is a social problem and a big stigma. The objectives of the study were to determine the age wise distribution of ovarian volume and the difference in ovarian volume between married fertile and infertile women with transvaginal sonography. Materials & Methods: This comparative, cross-sectional study was conducted in the Department of Anatomy, Gomal Medical College, D.I.Khan, Pakistan from March 2013 to December 2013. Sample Size was 100 women selected by consecutive non probability sampling technique. Sample size was calculated using online calculator Raosoft. Inclusion criteria were women aged 18-50 years, married, fertile and infertile. Color Doppler sonoscape with multi frequency transvaginal probes were used in measurements on any day in the start of menstrual cycle by the same observer. The volume was calculated by applying formula for ellipsoid called Prolate ellipsoid formula. The total volume was represented by sum of volume of two ovaries. Data collection site was out patient department of Radiology DHQ Teaching Hospital, D.I.Khan. Demographic variable were age groups and presence of fertility. Research variable was ovarian volume. Mean and standard deviation were calculated for ovarian volume whereas frequency and percentages were calculated for age groups and presence of fertility. Descriptive statistics along with estimation of parameter was done at 95% confidence interval for proportion and mean. Student- t test was used for significance of difference in ovarian volume between fertile and infertile women with p value

scholarly journals Validity of sample sizes in publications of randomised controlled trials on the treatment of age-related macular degeneration: cross-sectional evaluation

BMJ Open ◽  
2019 ◽  
Vol 9 (10) ◽  
pp. e030312
Author(s):  
Sabrina Tulka ◽  
Berit Geis ◽  
Christine Baulig ◽  
Stephanie Knippschild ◽  
Frank Krummenauer
Keyword(s):  
Macular Degeneration ◽  
Sample Size ◽  
Primary Endpoint ◽  
Sample Size Calculation ◽  
Age Related Macular Degeneration ◽  
Cross Sectional ◽  
Age Related ◽  
Number Of Patients ◽  
Sample Size Calculations ◽  
Randomised Controlled

ObjectiveThe aim of this cross-sectional study was to examine the completeness and accuracy of the reporting of sample size calculations in randomised controlled trial (RCT) publications on the treatment of age-related macular degeneration (AMD).MethodsA sample of 97 RCTs published between 2004 and 2014 was reviewed for the calculation of their sample size. It was examined whether a (complete) description of the sample size calculation was presented. Furthermore, the sample size was recalculated, whenever possible based on the published details, in order to verify the reported number of patients.Primary outcome measureThe primary endpoint of this cross-sectional investigation was a described sample size calculation that was reproducible, complete and correct (maximum tolerated deviation between reported and replicated sample size ±2 participants per trial arm).ResultsA total of 50 publications (52%) did not provide any information on the justification of the number of patients included. Only 17 publications (18%) provided all the necessary parameters for recalculation; 8 of 97 (8%, 95%-CI: 4% to 16%) publications achieved the primary endpoint. The median relative deviation between reported and recalculated sample sizes was 1%, with a range from −43% to +66%.ConclusionAlthough a transparent sample size legitimation is a crucial determinant of an RCT’s methodological validity, more than half of the RCT publications considered failed to report them. Furthermore, reported sample size legitimations were often incomplete or incorrect. In summary, clinical authors should pay more attention to the transparent reporting of sample size calculation, and clinical journal reviewers may opt to reproduce reported sample size calculations.SynopsisMore than half of the analysed RCT publications on the treatment of AMD did not report a transparent sample size calculation. Only 8% reported a complete and correct sample size calculation.

scholarly journals Sample size calculation for estimating key epidemiological parameters using serological data and mathematical modelling

2019 ◽  
Vol 19 (1) ◽  
Author(s):  
Stéphanie Blaizot ◽  
Sereina A. Herzog ◽  
Steven Abrams ◽  
Heidi Theeten ◽  
Amber Litzroth ◽  
...  
Keyword(s):  
Mathematical Modelling ◽  
Sample Size ◽  
Sample Size Calculation ◽  
Serological Data ◽  
Epidemiological Parameters

scholarly journals 2304

2017 ◽  
Vol 1 (S1) ◽  
pp. 34-34
Author(s):  
Christina Azevedo ◽  
Steven Cen ◽  
Ling Zheng ◽  
Pelletier Amirhossein Jaberzadeh
Keyword(s):  
Sample Size ◽  
Phase Ii ◽  
Primary Endpoint ◽  
Effect Size ◽  
Grey Matter ◽  
Brain Regions ◽  
Simulation Based ◽  
Sample Size Calculations ◽  
The Difference ◽  
Over Time

OBJECTIVES/SPECIFIC AIMS: To identify brain regions with the highest and least variable rate of multiple sclerosis (MS)-specific atrophy using an agnostic approach, and to perform simulation-based sample size calculations for Phase II s using these regions as primary endpoint. METHODS/STUDY POPULATION: In total, 601 subjects (2638 MRI scans) were analyzed; 520 subjects with relapsing forms of MS across the spectrum of disease severity and duration were followed in a single-center prospective cohort study at an academic MS Center between 2005 and 2010 with annual 3 T MRIs and clinical visits for 5 years, including standardized 1 mm3 3D T1-weighted images (3DT1s; 2483 MRIs). Separately, a convenience sample of 81 healthy controls (HC) was recruited from the same center and scanned longitudinally using the same MRI scanner and protocol (155 MRIs). 3DT1s were processed using FreeSurfer’s longitudinal pipeline (software version 5.3). Rates of change in all cortical and subcortical regions (n=119 brain regions) were estimated in MS patients and HC with linear mixed effects models. An effect size was calculated for each region as the difference in change over time between MS patients and HC divided by the standard error of the difference [d=β(MS×time)/SE β(MS×time)]. Regions were ranked according to absolute effect size, and the top regions were chosen for simulation-based sample size calculations to estimate the number of subjects needed to achieve 80% power to detect a slowing of MS atrophy down to normal aging, assuming significance levels of 5% and 10%. Ten percent was included because some have advocated for a more relaxed alpha in Phase II s. RESULTS/ANTICIPATED RESULTS: Four regions (putamen, subcortical grey matter, caudate, and thalamus) yielded the smallest sample sizes. At 80% power, ~50 subjects per arm would be needed with putamen or subcortical grey matter volume, or ~80–85 subjects per arm with caudate or thalamic volume as primary endpoint. For the remaining regions, >140 subjects per arm would be needed. A 20%–30% increase in sample size was observed when α=5% was used. DISCUSSION/SIGNIFICANCE OF IMPACT: Using an agnostic approach considering all brain regions and simulation-based sample size calculations specifically designed for longitudinal studies, putaminal, subcortical grey, caudate, and thalamic volumes are sensitive to change over time and yield feasible sample sizes for Phase II studies in MS. Because the effect size estimates incorporate normal aging, these regions represent the most sensitive outcomes for testing therapeutic interventions that target irreversible, MS-specific brain atrophy. The clinical relevance of these regions is our next focus to help inform which of these regions should be favored as primary endpoint.

scholarly journals SEROLOGICAL SURVEY OF SALMONELLA INFECTION IN NON-VACCINATED COMMERCIAL LAYER BIRDS IN KHULNA DISTRICT OF BANGLADESH

2012 ◽  
Vol 9 (1) ◽  
pp. 27-31 ◽  
Author(s):  
MA Jalil ◽  
MT Islam
Keyword(s):  
Random Sampling ◽  
Age Groups ◽  
Sampling Technique ◽  
Cross Sectional Study ◽  
Flock Size ◽  
Serological Survey ◽  
Sectional Study ◽  
Salmonella Infection ◽  
Cross Sectional ◽  
Sera Samples

A cross sectional study was conducted on 164120 non-vaccinated layer birds of 96 farms in six upazilas (Sadar, Batiaghata, Dumuria, Dighulia, Rupsha and Fultala) of Khulna district to determine the seroprevalence of Salmonella infection (S. pullorum and S. gallinarum) during the period from August 2009 to July 2010. Sera samples were collected from 1268 layer birds of different ages and the birds were selected through a disproportionate stratified random sampling technique based on the flock size of each farm. Sera samples were tested by Serum plate agglutination (SPA) test applying commercial Salmonella antigen (Nobilis® SA, Intervet International B.V. Boxmeer- Holland) to detect the presence of antibodies against Salmonella. The overall seroprevalence of Salmonella infection was recorded as 65.9%. The significantly higher seroprevalence (76.6%) of Salmonella infection was recorded in layer birds of >56 weeks of age than those of other age groups. Seasons had significant influence on the seroprevalence of Salmonella infection. The seroprevalence was significantly higher in summer (82%) than that in rainy (66.8%) and winter (50%) seasons. The location of farms, i.e. upazilas also had significant association with the occurrence of Salmonella infection. The seroprevalence significantly differed between the different categories of flock size. The flock size of 5001 and above had the highest seroprevalence (81.4%) among other categories. It may be concluded that above 60% layer birds in 92 out of 96 farms are infected with Salmonella organism, which requires keeping of vigilant eye of the poultry farmers and the hatchery owners in the control of Salmonella infection in poultry farms.DOI = http://dx.doi.org/10.3329/bjvm.v9i1.11206Bangl. J. Vet. Med. (2011). 9(1): 27-31 

scholarly journals Study on urolithiasis diagnosed in a private medical centre in Rajshahi City

2018 ◽  
Vol 29 (1) ◽  
pp. 24-28
Author(s):  
J Bhaduri ◽  
ZMM Hossain ◽  
MA Ferdos
Keyword(s):  
Sample Size ◽  
Ultrasound Examination ◽  
Age Groups ◽  
Descriptive Study ◽  
Medical Centre ◽  
Age Group ◽  
Cross Sectional ◽  
Female Data ◽  
Rajshahi City ◽  
Structured Questionnaire

It was a cross-sectional descriptive study. Sample size was 12227 of which 4148 were male and 8079 were female. Data were collected from all the patients attending the private medical centre, selected purposively, to have ultrasound examination for different reasons, during the calendar year 2016. A semi-structured questionnaire was used as the instrument of the study. It was observed that 18.32/1000 males and 9.90/1000 females had been diagnosed as cases of urolithiasis. Overall occurrence was calculated as 1.27%. Majority of the females had urolithiasis in the age-group of ‘up to 20 years’ (70%). In case of males, the problem was more common in ‘41 to 60 years’ and ‘61 years and above’ age-groups (62.5% and 66.7% respectively). Majority of the respondents had single stone only (68.6%). Kidney was the commonest site for the localization of both single (85.9%) and multiple stones (97.2%).TAJ 2016; 29(1): 24-28

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