Official Title
Community Perception on Effective Approaches to Promote Acceptance and Adherence to Public Health Measures for COVID-19 Prevention and Control
Brief Summary

In times whereby COVID-19 is rapidly spreading, research on the epidemiological,diagnostic, clinical and social aspects of the illness has been highlighted as importantas there is very limited information of this disease in all these aspects. Keeping thisin view, WHO has published a roadmap for global research referred to as the 2019 novelCoronavirus Global research and innovation forum: towards a research roadmap13. Thisdocument has identified around 34 knowledge gaps which need to be addressed in order tolearn more about this illness. One of these gaps indicates that disease transmission isdriven by both social and biological factors. Social sciences research, thus, can play avery important role in combating this illness. It can bring rich insights into social,behavioral and contextual aspects of communities, societies and populations affected byCOVID-19 to enhance acceptability of and adherence to evidence-based public healthmeasures for successful infection prevention and control (IPC).

Detailed Description

While much of published research regarding COVID-19 has focused on virology, epidemiology
and clinical aspects of COVID-19, commentaries, editorials and letters from sociologists,
economists and political scientists have highlighted the social impacts of COVID-19,
particularly in China. It is, therefore, very important to explore the community
perception of the impact this illness is having on the lives of the general public and
the practices which they are adopting to contain the disease. These kinds of insights are
important for national public health officials looking to implement control measures that
may have clear biomedical rationale but require social and behavioral cooperation from
citizens to be effective. Rapid identification of these impacts and research is necessary
to generate evidence that can inform approaches to mitigate them. This is because public
health authorities are not operating in a vacuum, but in already functioning communities
and societies with established socio-cultural systems that include different forms of
authority, organization and coping and resilience mechanisms to face adversity. Local
knowledge and perception of COVID-19 will, therefore, drive local reactions and
responses.

Among all the affected countries, Pakistan has also been affected with more than 76,398
confirmed cases and 1621 deaths till June 2, 202014. In March 2020, the government of
Pakistan published a National Action Plan (NAP) on COVID-19 to deal with the illness.
Among the important factors that focused on COVID-19, one was the generation of evidence
to guide better decision making15. Pakistani communities are very diverse in their
cultural and social norms and therefore their response to COVID-19 might also be varied.
It is, therefore, important to identify the perception, practice and attitude of the
community towards containing this disease. This is because clinical management of
COVID-19 patients can only be effective if the healthcare system is not overburdened with
a constant flow of patients which is increasing day by day. This increase in the
percentage of patients is directly proportional to the measures that the community takes
to contain the disease.

STUDY DESIGN A descriptive study design with a cross-sectional approach will be adopted
whereby nationally representative sample of respondents (based on latest census 2018)
across Pakistan through Computer Assisted Telephonic Interviewing (CATI) will be
interviewed. CATI is a research and analysis program with no direct human-human
interaction whereby data is collected telephonically through tablets/computers with
incorporated questionnaires with logical checks. CATI has the capacity of respondent
randomization, full central server quota control, sample management, appointments and
automatic dialing.

Upon local ethical clearance, development of the questionnaire, its pre-testing and
development of its CATI based version, the enumerators will be trained remotely through ,
Skype or MS teams. Skype will be used as a priority. These enumerators are our
collaborator International Research Force (IRF)'s trained data collectors.

For this particular study the enumerators will be trained on obtaining consent from the
respondents followed by data collection on the questionnaire. They will:

- Identify themselves promptly

- Clearly state the purpose of research

- Ensure that participation is voluntary based on information about the purpose and
nature of the research that is adequate and not misleading

- Respect the right of data subjects to refuse requests to participate in research

Each enumerator has a company laptop with headphones and microphone to conduct the data
collection. The enumerator, therefore, has the capacity to collect data, while working
from home through these systems connected to the central server that will automatically
dial numbers once logged in (each enumerator having a separate login and password).

Numbers will be automatically dialled from an already available panel of respondents who
have already agreed to take part in public opinion based surveys with frequency of
interviewing @ once a month. The system will be using the principle of random digital
dialing (RDD) to ensure random sampling. The system will automatically dial these numbers
ensuring that none of the enumerators will have access to the phone numbers of the
respondents. . Respondents will be interviewed on knowledge of COVID-19, social norms to
prevention, risk of disease, and important factors to promote adherence to the preventive
measures. We shall also be collecting demographic information including age, gender,
province , SES and level of education. Monitoring of the data collection process will be
conducted through an online dashboard by the project manager. The manager will access the
dashboard and observe the performance of each enumerator by noting the number of calls
made per day, and the disposition status given by the enumerator against each call
including the number of successful interviews, number of incomplete interviews, number of
refusals, not responding numbers etc. Data entered in the computer system by each
enumerator shall be sent to the central server which can be accessed remotely and
extracted by the data manager for analysis and reporting.

IDENTIFYING PARTICIPANTS Participants will be approached through RDD through a database
within the International Research Force (IRF) CATI system.

CONSENTING PARTICIPANTS Verbal consent will be obtained from all the participants before
the interview. Interviewer will read out the participant information sheet to the
respondent and will record the responses in the form. The information sheet includes
statements on voluntary participation with option to discontinue at any point of the
study with no penalty to the participants. Any queries from the participants regarding
the study will be resolved prior to taking the consent. If the respondent agrees to be
interviewed upon giving consent he/she will be interviewed otherwise he/she will be given
2-3 days to agree to participate upon which the enumerator will call the respondent to
determine consent which will be taken verbally and recorded.

Withdrawal of Study Participants Participants will be free to withdraw from the study at
any point with or without providing any reason or he/she can be a withdrawn by the
Investigator. If a withdrawal occurs, the primary reason for withdrawal will be
documented in the participant's case report form or marked unspecified if no reason was
given by the participant.

DATA COLLECTION

The IRF CATI software will enable data collection through:

1. Creating lists of leads from the panel which can be used for dialling automatically.

2. Calling respondents through RDD whereby the interviewer does not need to dial in the
numbers.

3. Scheduling the system for follow up calls for respondents unavailable in previous
attempts.

4. Allowing live data entry into the software.

5. Incorporating automatic logical skips and data coding checks to provide error free
or incomplete data entry.

6. Providing disposition status.

7. Providing minute by minute status of total and per-hour results-by-interviewer,
results per day or per attempt, the number of telephone numbers still active,
cooperation rates, and more.

Data Management Personal Data

The following personal data will be collected as part of the research:

- Age

- Provincial

- Gender

- Level of education

- Socioeconomic class

Personal data will be stored for up to 5 years after completion of the study after which
it will be destroyed. Once the data is obtained from the IRF CATI system for analysis, it
will be deleted from there.

Storage:

All data (raw and anonymized) in the form of excel sheets and SPSS data files along with
preliminary reports will be stored in password protected folders and computers with
access to authorized members of the research team only.

Backup:

3 copies of the original data will be created and stored on different locations. Original
copy will be stored on the password protected computer of the data manager. This will be
backed up fortnightly on the main server located at the central field office and on cloud
storage.

Anonymized, non-identifiable data will also be stored on the University of Edinburgh file
store. This is high quality, enterprise-class storage with guaranteed backup and
resilience. The data is automatically replicated to an off-site disaster facility and
backed up with a 60-day retention period, with 10 days of file history visible online.

File naming:

Files will be named as per the standard naming convention of the organization i.e.
organization name project ID_type of data file e.g. MCNHRN_RES007_excelsheet.txt

Organization:

Password protected folders will be created for each data file. Files will be placed in
their respective folders.

Transfer of Data All data collected or generated by the study (including personal data)
will not be transferred outside the research site except to the University of Edinburgh
data repository (DataShare) whereby only anonymized, non-identifiable data will be
stored.

Non-identifiable data from this project may be stored in a research data repository at
the University of Edinburgh to allow knowledge sharing and learnings about this study.
The University of Edinburgh provides its researchers (and their collaborators) two
services for sharing and archiving of data which will be used for their information.
There is an open access repository for anonymized data, which means that all
non-identifiable data is freely available. For sensitive information a secure repository
is used which can only be accessed by approved researchers who have undergone a rigorous
application and review process.

Data Controller The data controller is University of Edinburgh.

Completed
COVID-19
Eligibility Criteria

Inclusion Criteria:

- Inclusion criteria will be men and women over the age of 18 years.

Exclusion Criteria:

-

Eligibility Gender
All
Eligibility Age
Minimum: 18 Years ~ Maximum: 60 Years
Countries
Pakistan
Locations

MNCHRN
Islamabad, Federal, Pakistan

Dr Tabish Hazir, MBBS, FRCPCH, Principal Investigator
Maternal Neonatal Child Health Research Network

University of Edinburgh
NCT Number
Keywords
community perception
Pakistan
COVID-19 Prevention
COVID-19 control
MeSH Terms
COVID-19