Community Perception on COVID-19 Prevention and Control

COVID-19 Clinical Trial

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

Status Completed

Clinical Trial 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 important as there is very limited information of this disease in all these aspects. Keeping this in view, WHO has published a roadmap for global research referred to as the 2019 novel Coronavirus Global research and innovation forum: towards a research roadmap13. This document has identified around 34 knowledge gaps which need to be addressed in order to learn more about this illness. One of these gaps indicates that disease transmission is driven by both social and biological factors. Social sciences research, thus, can play a very important role in combating this illness. It can bring rich insights into social, behavioral and contextual aspects of communities, societies and populations affected by COVID-19 to enhance acceptability of and adherence to evidence-based public health measures for successful infection prevention and control (IPC).

Clinical Trial 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. ;

Related Conditions & MeSH terms

• COVID-19

• NCT number: NCT06452108
• Study type: Observational
• Source: University of Edinburgh
• Status: Completed
• Start date: April 4, 2020
• Completion date: December 31, 2021