University of Cape Town
Browse
11 Covid-19 Toolkit v1.0.zip (388.97 kB)

H3Africa PHWG Data Collection Toolkit - Covid-19 v1.0

Download (388.97 kB)
standard
posted on 2022-11-14, 14:19 authored by Lyndon ZassLyndon Zass, Nicki Tiffin, Kate WebbKate Webb, Michael Pepper, Katherine JohnstonKatherine Johnston, Liberata Mwita, Upendo Masamu, Nihad Alsayed, Samah Ahmed

Description

The COVID-19 module can be used to collect essential phenotypes associated with COVID-19 and MISC-related research, including: COVID-19 Exposure History; Symptoms and Signs; Comorbidities; COVID-19 Diagnoses and Treatments. The module is subdivided into core phenotypes (phenotypes incorporated from the H3Africa Standard) and COVID-19 & MISC-specific phenotypes.

Administration

The phenotype protocols contained in the module range from Interviewer/Self-administered questionnaires to clinically-administered and bioassay/lab-based assessments. The module is applicable to human participants of all life stages, though some phenotype protocols are age-specific. For more information on administration of the module, see the module guideline.

References

The module consists of both existing and novel data collection standards, and was based on several existing resources. These resources are listed below:

  1. Global Effort on COVID-19 (GECO) Health Research Phenotype Questionnaire.
  2. Enhanced COVID-19 Notifiable Medical Conditions (NMC) Notification Form (SA)
  3. PHA4GE SARS-CoV-2 Contextual Data Specification - Collection template
  4. NSW Government COVID-19 case questionnaire
  5. WHO Global COVID-19 Clinical Platform: Rapid core case report form
  6. WHO Global COVID-19 Clinical Platform: Case Report Form for suspected cases of Multisystem inflammatory syndrome (MIS) in children and adolescents temporally related to COVID-19
  7. Enhanced MIS-C Notifiable Medical Conditions (NMC) Notification Form (SA)
  8. Mayo Clinic Documentation (https://www.mayoclinic.org/diseases-conditions/coronavirus/symptoms-causes/syc-20479963)

Funding

H3ABioNet: a sustainable African Bioinformatics Network for H3Africa

National Human Genome Research Institute

Find out more...

History

Department/Unit

Computational Biology, University of Cape Town