Abstract:
Understanding the application of statistical methods is an essential component
in the analysis of pandemics. Although the management of emergencies
that stem from such pandemics can be a challenging task, the
effects caused by such emergencies can be mitigated by improved preparedness,
the implementation of preventive measures, timely response
and the implementation of recovery strategies. Statistical methods provide
tools that can access the relative magnitude of pandemics, such as
Covid-19. A key feature of public health management is an understanding
of data and analysis to quantify the extent of such pandemics, and to be
successful in their mandate. The statistics used in the current coronavirus
pandemic involve clinical characteristics of the infected population, and
are reported in the form of means, modes, medians, interquartile ranges
and confidence intervals. These measures form part of descriptive and
inferential statistics, and more specifically measures of central location
and variation, as well as measures of precision. The aim of this article
is to review these measures, which are typically used when reporting a
new epidemic outbreak. First, the difference between descriptive statistics
and inferential statistics is described, after which a thorough theoretical
explanation is given regarding measures of central location and variation,
as well as measures of precision. Straightforward explanations of these
statistical methods may promote understanding among public administrators
and managers about how epidemiological data is being analysed. This increased understanding could assist managers in responding to the
pandemic, its characteristics and descriptive statistics appropriately and
thus enhance their ability to formulate effective strategies.
