Research Approach and Methodology
1\. Healthcare workers' risk and 2. Infection prevention and control needs: Study design and setting
To fulfill specific objectives, a prospective investigation of all HCWs working in all governmental university hospitals and the affiliated COVID-19 quarantine hospitals.
To date, the Ministry of Higher Education has dedicated quarantine hospitals at the following governmental universities: Ain Shams, Cairo, Helwan, Alexandria, Mansoura, Assiut, Minia. This list may be expanded in the future. The project will be pilot tested in Ain Shams University, then extended to other universities subsequently.
Study population For the purpose of this study, HCWs are defined as all staff in the governmental university hospitals involved in emergency and intensive care and in the provision of care for COVID-19 patients in the affiliated COVID-19 quarantine hospitals. These include those who have been present in the same area as the patient, as well as those who may not have provided direct care to the patient, but who have had contact with the patient's body fluids, potentially contaminated items or environmental surfaces. This includes health care professionals, allied health workers, auxiliary health workers (e.g. cleaning and laundry personnel, x-ray physicians and technicians, clerks, phlebotomists, respiratory therapist, nutritionists, social workers, physical therapists, lab personnel, cleaners, admission/reception clerks, patient transporters, catering staff etc.). Once a case of COVID-19 has been identified in these hospitals, a list of all health care workers with any exposure to COVID-19 patient will need to be drawn up.
Study tool and data collection For risk categorization of HCWs exposed to COVID-19 virus and assessment of infection control needs, an online survey questionnaire will be administered to all HCWs in the governmental university hospitals involved in emergency and intensive care and in the provision of care for COVID-19 patients in the affiliated COVID-19 quarantine hospitals.
The questionnaire will be adapted from the World Health Organization relevant protocols and interim guidance. The sections of the questionnaire will cover:
1. Socio-demographic, background information including history of tobacco use, and pre-existing medical conditions;
2. COVID-19 virus exposure risk assessment for community exposure;
3. COVID-19 virus exposure risk assessment for nosocomial exposure (i.e. contact and possible exposure with the COVID-19 patients since the patient has been admitted to the health care facility);
4. HCW interactions with COVID-19 patient information;
5. HCW activities performed on COVID-19 patient in health care facility;
6. HCW symptoms;
7. Adherence to infection prevention and control measures during health care interactions;
8. Adherence to infection prevention and control measures when performing aerosol-generating procedures (e.g. tracheal intubation, nebulizer treatment, open airway suctioning, collection of sputum, tracheotomy, bronchoscopy, cardiopulmonary resuscitation, etc.); and
9. Accidents with biological material.
This online survey will be completed at baseline and at any future contact or possible exposure with the COVID-19 patients since the patient has been admitted to the hospital.
Other forms will complement the data collected in the online survey questionnaire. The complementary forms include:
* Laboratory form for specimen collection for screening and testing and the relevant results
* Follow-up laboratory form for specimen collection for screening and testing and the relevant results
* HCW symptom diary: Each HCW contact will be asked to record the presence or absence of various signs or symptoms each day for up to 21 days after the administration of the baseline questionnaire (minimum 14 days).
* Outcome form for follow up of HCWs who experience contact or possible exposure with the COVID-19 patients since the patient has been admitted to the hospital.
* Health care facility infection prevention and control form: filled once at baseline for each of the study hospitals.
These will be filled by HCWs, and dedicated teams and coordinators representing the hospital infection control focal points and the hospital management at each of the study hospitals. The forms will be electronically linked to the online survey for instant updates of HCW information using an automatically generated unique serial study number for each HCW to be used across all study forms.
3\. Testing for COVID-19 among healthcare workers:
For confirmation of seroconversion, determination of the secondary-infection attack rate, and the proportion of asymptomatic infection paired serological samples will be collected:
1. A baseline serum sample will be collected from all healthcare workers with any exposure (regardless of symptoms), as soon as possible after confirmation of a COVED-19 infected patient in the hospital.
2. A second serum sample will be collected from the same healthcare workers at least 21 days after the collection of the first serum sample
For measuring the validity of the available rapid serological tests:
A respiratory sample will be taken for viral detection by RT-PCR
4\. Geospatial mapping of health care workers' risk and infection control needs:
To achieve this aim the following subtasks must be done:
\- Build a full stack web-based platform that is integrated with a geographical information system. Where, the platform frontend is a real-time interactive map.
Moreover, the platform backend is a database system to store and manipulate the HCWs' risk and infection control data.
* Build a real-time Signal-R flagging service to track the survey results and put flags on the platform interactive map where these flags represent the location of high HCWs' risk and infection control rate.
* Build a real-time reporting service based on Signal-R and Artificial Intelligence techniques to follow up the survey results and inform the policy and the decision makers with the location and information of the high HCWs' risk and infection control rate.
Furthermore, this reporting service provides more insights on the survey results using the Artificial Intelligence techniques such as the association between the geographical information and the high HCWs' risk rate.
