Clinical Trial Details
— Status: Recruiting
Administrative data
NCT number |
NCT05471635 |
Other study ID # |
GP0012022 |
Secondary ID |
|
Status |
Recruiting |
Phase |
|
First received |
|
Last updated |
|
Start date |
June 20, 2022 |
Est. completion date |
July 20, 2022 |
Study information
Verified date |
July 2022 |
Source |
University of Turin, Italy |
Contact |
Alberto Peano, Dr. |
Phone |
+39 3923983663 |
Email |
alberto.peano[@]unito.it |
Is FDA regulated |
No |
Health authority |
|
Study type |
Observational
|
Clinical Trial Summary
Vaccination coverage against COVID-19 differs widely between countries: in order to address
this public health issue, this observational study seeks to understand whether there are any
determinants/predictors. In order to highlight the presence of determinants and their
strength in influencing vaccination coverage, all possible socio-demographic, economic,
cultural, infrastructural and political variables considered capable of modifying such
coverage were selected and analysed.
Description:
The COVID-19 pandemic has had major health, economic and social implications, bringing with
it a large number of deaths worldwide. While the lethality rate could not be considered high,
the fact that the contagiousness was high resulted in a considerable number of deaths. As a
result, the COVID-19 pandemic has become a sudden, huge and urgent public health problem.
Initially faced with a new and unknown etiopathological entity, different countries adopted
different policies that proved more or less effective in containing the COVID-19 contagion.
While social and hygienic restrictive measures (i.e. so-called social distancing, curfews,
use of masks and hand hygiene) initially had a positive impact on reducing infections, for
the most part they proved to be ephemeral measures. These actions were short-lived because
they were not sustainable over time due to the damage they implied with regard to mental
health, besides the low adherence of the population. A relaxation of these restrictive
measures has always led to an increase in the spread of the COVID-19 pandemic, with a
resurgence of hospital admissions, an ever-increasing occupancy of intensive care beds and a
subsequent increase in the number of deaths.
Since the beginning of the COVID-19 pandemic, scientific research has been working to enable
the identification of the SARS-CoV-2 viral genome and possible target proteins for treatment.
Due to years of vaccine research and the launch of Access to COVID-19 Tools (ACT)-Accelerator
partnership, a rapid development of several candidate vaccines based on different vaccine
technologies and thus to their rapid clinical testing were possible.
Thanks also to the regulatory agencies' solicitude, in certain Countries (e.g. Israel, the
UK, the US and the EU) the COVID-19 vaccination campaign started at the end of 2020 and
extended worldwide during 2021 (with the exception of Eritrea and the Democratic Republic of
Korea).
Through purchasing agreements with individual vaccine manufacturers, governments (or
supranational institutions, e.g. the EU) secured the supply of the necessary doses. However,
this entailed a division of the world's population depending on the negotiating power of the
country of residence and, therefore, its economic strength. COVAX is one of the three pillars
of the ACT-Accelerator programme: dedicated to vaccines, the purpose of COVAX is to
accelerate the development and manufacture of COVID-19 vaccines, ensuring fair and equitable
access for every country in the world.
In a globalised world, guaranteeing everyone the right to health is mandatory from a moral as
well as an economic and global health point of view: everyone gains if the poorest improve
their condition (think infectious diseases). In a globalised world, it is necessary to
'globalise' health and not only the economy: this study aims to understand where governments,
supranational institutions and non-governmental organisations can act more incisively to
combat the COVID-19 pandemic with the weapon the vaccine represents.
On this basis, the investigators decided to examine whether certain variables could be
determinants of vaccination coverage for COVID-19. Two outcomes were identified as indicators
of vaccination coverage: the proportion of the population vaccinated with at least one dose
and the ratio of administered doses to the population. These data were obtained from the
COVID-19 dataset by Our World In Data as of 15th June for each country. If data was not
available on that date, the most recent available data was used looking retrospectively. In
order to analyze whether and which were determinants of vaccination coverage, several
variables are accounted: socio-demographic variables: total population, population density,
median age, GINI Index; economic variables: GDP per capita; health variables:
COVID-19-specific mortality, type of health system (public or private), health personnel
(Physicians /1000 population, Nurses and midwives personnel/1000 population); cultural
variables (literacy rate, Greenberg Index, presence of a predominant religion),
infrastructural variables (density of road network, access to electricity) and political
variables (civil liberties, political stability and absence of violence/terrorism). Data for
the aforementioned variables were extracted from institutional databases/ datasets: World
Bank, Our World In Data, World Religion Database and The World Factbook. For Greenberg Index,
as proxy of Cultural Diversity Index, the data were from Gören (2018), taking the 2020 figure
for each country, or the most recent available figure if the 2020 figure is not available.
Statistical analyses will be conducted including all countries in the world taken
individually, for which vaccination data are available as of 15 June 2022. In addition,
analyses will also be conducted for outcomes adjusted for vaccine doses delivered (in each
country). The data for this correction factor were obtained from the UNICEF database on 21th
June 2022.
Statistical analyses by subgroups will also be implemented, stratifying by World Bank country
classification by income level: High, Upper-middle, Lower-middle, Low.