role of biostatistician and biostatistical programming in epidemiological studies - pepgra
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Pepgra experts provide regulatory biostatistics and epidemiology statistical programming support to all phases of clinical trial process development and commercialization. Health data contains important information that can help save lives and cro biostatistics services provide information to support public health initiatives. Epidemiological statistical services and biostatistical programming services are highly sought after to make sense of the data available from studies on public health. Continue Reading: http://bit.ly/2OBq9EZ Youtube: https://youtu.be/2NORssElgFg Contact Us: Website : https://bit.ly/33Fwsye Email us: [email protected] India: +91 9884350006 United Kingdom: +44- 74248 10299TRANSCRIPT
Copyright © 2020 pepgra. All rights reserved 1
Role of Biostatistician and Biostatistical Programming in Epidemiological
Studies
Dr. Nancy Agens, Head,
Technical Operations, Pepgra
In brief
Health data contains important
information that can help save lives and
cro biostatistics services provide
information to support public health
initiatives. Biostatisticians and
biostatistical programming services are
highly sought after to make sense of the
data available from studies on public
health.
Keywords
Epidemiology biostatistical service,
Statistical Programming Services,
Clinical biostatistics services, Biostatistics
services
I. EPIDEMIOLOGY
Epidemiology is a branch of
medicine that deals with the study of
disease in population, the incidence,
distribution, and ways to control the
same.Centres of disease control and
prevention (CDC) explains epidemiology
as a scientific and systematic data-driven
study of the distribution and determinants
of health-related states and events in
specific populations and application of the
same information for control of health
problems.iSo, we see that epidemiology
consists of three aspects: -
1. Identification of disease patterns in a
population,
2. Identify causes or associated
conditions and
3. Provide data for prevention, control,
and treatment of the health condition.
II. BIOSTATISTICS
Biostatistical analysis is the science
and art of dealing with variation in data to
get reliable results and conclusions.
Application of statistics to any field of
medicine or health is biostatistics.ii
III. BIOSTATISTICS IN
EPIDEMIOLOGICAL STUDIES
Epidemiological studies are heavily
dependent on biostatistics.
Epidemiological statistical services
convert data and information got from
epidemiological studies, analyseit, and
convert it into forms that help solve issues
related to public health. Biostatistical
services use quantitative methods to
combine the two disciplines of
epidemiology and biostatistics.iii
How do we know the risk factors
associated with heart disease? How did we
conclude that there is no one cause for this
but a combination of genetic and lifestyle
factors that increase the risk to have a
coronary event? This understanding is
thanks to the famous Framingham Heart
Study which is still underway. Here, over
5000 volunteers agreed to be followed up
for several decades to help public health
workers understand the risk factors
associated with heart disease.
As the world is struggling today to
understand and curtail the pandemic of
Covid-19, the role of epidemiology in
public health has never been clearer.
Biostatisticians are using statistics to
predict how the pandemic will behave,
spread, and the mortality rate.
Copyright © 2020 pepgra. All rights reserved 2
Thus, epidemiology and biostatistics are
the basic sciences of public health.
IV. STEPS IN EPIDEMIOLOGICAL
BIOSTATISTICS
Steps involved includeiv
: -
1. Address a public health question –
generate a hypothesis
A hypothesis in
epidemiology is an
assumption based on
o Scientific rationale
o Observation or anecdotal
evidence
o Results of prior studies
2. Conduct a study –
o Survey – studies extend of
health condition in defined
population
o Surveillance – Monitors or
detects health condition. It
can be done actively or
passively.
o Observational – study the
association between an
exposure and a health
condition. Here, there is a
natural distribution of the
control and study group.
o Experimental – study
involving exposure,
treatment, and disease
outcome.
3. Collect data – numerical facts and
figures, observations that are
obtained from the investigation.
Data must be reliable and accurate
for reliable and significant
outcomes.
4. Describe the observations / data –
by descriptive statistical methods,
the data is assessed descriptively
and organised in graphs, tables, and
other summary methods.
5. Assess strength of evidence for or
against the hypothesis – Inferential
statistics does a confirmatory data
analysis. The strength of evidence
is assessed, comparisons are made
with previous studies and
predictions are made. It also
provides future questions and areas
of future research.
6. Make recommendations based on
inferences – The study proves or
disproves or is inconclusive on the
hypothesis. The study may be
published in peer-review
publication or may be spread by
any other suitable medium of
communication. The outcome may
be a regulatory or policy change in
handling a health condition or a
change in behaviour of the people.
Epidemiology and biostatistics
services together provide valuable inputs
on study design, disease modelling,
sampling, surveillance, analysis, risk
stratification, identification of vulnerable
populations and prevention, control, and
treatment of the health condition in the
population. Biostatistics helps in designing
study methodology, data models that are
epidemiologically relevant to make
information and data more informative by
adequate analysis.v
V. BIOSTATISTICAL TOOLS
Most studies use observational and
descriptive statistics in the form of tables
and graphs are most used. There are
several biostatistical computerised tools
that are available today that make the
process automated. Of these, SAS and
STATA are the most used packages. Other
packages used are SUDAAN, SPSS, R,
ARCGIS, HLM, IVEWARE, BUGS etc.
Logistic regression is the most common
classical statistical technique used. vi
VI. BIOSTATISTICIANS
Biostatisticians are the ones
running the show for Statistical
Programming Services. They usually have
a master’s degree or a doctorate in
statistics, some also have a degree in
Copyright © 2020 pepgra. All rights reserved 2
public health. They often have a
background in mathematics or computer
science. They are the ones who help make
sense of the complex data that comes out
of the study. They help link the cause and
effect and solve the mystery of causation
vis-à-vis association between the exposure
and disease condition.
VII. FUTURE SCOPES
Biostatistics is the backbone to
study epidemiology public health, and it
needs to be included adequately in medical
curriculum. Medical professionals need to
understand biostatistical tools better to be
able to interpret and use public health
statistics in their practice. Several courses
in statistical methods are available online
for working medical professionals seeking
additional training.
VIII. CONCLUSION
Epidemiology and biostatistics are
two sides of the same coin and together
they form the backbone of the public
health information system. Strong
biostatistical support turns scientific data
into information that help epidemiologists
and governments plan strong public health
policies.
REFERENCES
iPark K. Textbook of preventive and social medicine.
21st ed. BanarasidasBhanot; 2011. iiMahajan BK. Methods in biostatistics. 7th ed. New
Delhi: Jaypee Brothers Medical Publishers; 2010. iiiBhuyan, Dhrubajyoti&Dua, Neha & Kothari, Tejal.
(2015). Epidemiology and biostatistics: Fundamentals of
research methodology. Open Journal of Psychiatry &
Allied Sciences. 7. 10.5958/2394-2061.2015.00022.1. ivSundaram KR, Dwivedi SN, Sreenivas V. Medical
statistics principles and methods. New Delhi: BI
Publications; 2010. vVilleneuve, P.J., Paradis, G. &Muhajarine, N. Always
better together: the Canadian Journal of Public
Health and the Canadian Society for Epidemiology and
Biostatistics. Can J Public Health 111, 305–307 (2020).
https://doi.org/10.17269/s41997-020-00362-x viHayat, M. J., Powell, A., Johnson, T., &Cadwell, B. L.
(2017). Statistical methods used in the public health
literature and implications for training of public health
professionals. PloS one, 12(6), e0179032.
https://doi.org/10.1371/journal.pone.0179032